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| html_url
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| feature_patch
stringlengths 805
8.42M
| test_patch
stringlengths 548
207k
| doc_changes
listlengths 0
92
| version
stringclasses 57
values | base_commit
stringlengths 40
40
| PASS2PASS
listlengths 0
3.51k
| FAIL2PASS
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|---|---|---|---|---|---|---|---|---|---|---|---|---|
pydata/xarray
|
pydata__xarray-3425
|
https://github.com/pydata/xarray/pull/3425
|
diff --git a/MANIFEST.in b/MANIFEST.in
index a006660e5fb..4d5c34f622c 100644
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -6,3 +6,4 @@ prune doc/generated
global-exclude .DS_Store
include versioneer.py
include xarray/_version.py
+recursive-include xarray/static *
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index 9d3e64badb8..12bed8f332e 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -36,6 +36,12 @@ New Features
``pip install git+https://github.com/andrewgsavage/pint.git@refs/pull/6/head)``.
Even with it, interaction with non-numpy array libraries, e.g. dask or sparse, is broken.
+- Added new :py:meth:`Dataset._repr_html_` and :py:meth:`DataArray._repr_html_` to improve
+ representation of objects in jupyter. By default this feature is turned off
+ for now. Enable it with :py:meth:`xarray.set_options(display_style="html")`.
+ (:pull:`3425`) by `Benoit Bovy <https://github.com/benbovy>`_ and
+ `Julia Signell <https://github.com/jsignell>`_.
+
Bug fixes
~~~~~~~~~
- Fix regression introduced in v0.14.0 that would cause a crash if dask is installed
diff --git a/setup.py b/setup.py
old mode 100644
new mode 100755
index 08d4f54764f..cba0c74aa3a
--- a/setup.py
+++ b/setup.py
@@ -104,5 +104,7 @@
tests_require=TESTS_REQUIRE,
url=URL,
packages=find_packages(),
- package_data={"xarray": ["py.typed", "tests/data/*"]},
+ package_data={
+ "xarray": ["py.typed", "tests/data/*", "static/css/*", "static/html/*"]
+ },
)
diff --git a/xarray/core/common.py b/xarray/core/common.py
index 45d860a1797..1a8cf34ed39 100644
--- a/xarray/core/common.py
+++ b/xarray/core/common.py
@@ -1,5 +1,6 @@
import warnings
from contextlib import suppress
+from html import escape
from textwrap import dedent
from typing import (
Any,
@@ -18,10 +19,10 @@
import numpy as np
import pandas as pd
-from . import dtypes, duck_array_ops, formatting, ops
+from . import dtypes, duck_array_ops, formatting, formatting_html, ops
from .arithmetic import SupportsArithmetic
from .npcompat import DTypeLike
-from .options import _get_keep_attrs
+from .options import OPTIONS, _get_keep_attrs
from .pycompat import dask_array_type
from .rolling_exp import RollingExp
from .utils import Frozen, ReprObject, either_dict_or_kwargs
@@ -134,6 +135,11 @@ def __array__(self: Any, dtype: DTypeLike = None) -> np.ndarray:
def __repr__(self) -> str:
return formatting.array_repr(self)
+ def _repr_html_(self):
+ if OPTIONS["display_style"] == "text":
+ return f"<pre>{escape(repr(self))}</pre>"
+ return formatting_html.array_repr(self)
+
def _iter(self: Any) -> Iterator[Any]:
for n in range(len(self)):
yield self[n]
diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index 12d5cbdc9f3..eba580f84bd 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -3,6 +3,7 @@
import sys
import warnings
from collections import defaultdict
+from html import escape
from numbers import Number
from pathlib import Path
from typing import (
@@ -39,6 +40,7 @@
dtypes,
duck_array_ops,
formatting,
+ formatting_html,
groupby,
ops,
resample,
@@ -1619,6 +1621,11 @@ def to_zarr(
def __repr__(self) -> str:
return formatting.dataset_repr(self)
+ def _repr_html_(self):
+ if OPTIONS["display_style"] == "text":
+ return f"<pre>{escape(repr(self))}</pre>"
+ return formatting_html.dataset_repr(self)
+
def info(self, buf=None) -> None:
"""
Concise summary of a Dataset variables and attributes.
diff --git a/xarray/core/formatting_html.py b/xarray/core/formatting_html.py
new file mode 100644
index 00000000000..b03ecc12962
--- /dev/null
+++ b/xarray/core/formatting_html.py
@@ -0,0 +1,274 @@
+import uuid
+import pkg_resources
+from collections import OrderedDict
+from functools import partial
+from html import escape
+
+from .formatting import inline_variable_array_repr, short_data_repr
+
+
+CSS_FILE_PATH = "/".join(("static", "css", "style.css"))
+CSS_STYLE = pkg_resources.resource_string("xarray", CSS_FILE_PATH).decode("utf8")
+
+
+ICONS_SVG_PATH = "/".join(("static", "html", "icons-svg-inline.html"))
+ICONS_SVG = pkg_resources.resource_string("xarray", ICONS_SVG_PATH).decode("utf8")
+
+
+def short_data_repr_html(array):
+ """Format "data" for DataArray and Variable."""
+ internal_data = getattr(array, "variable", array)._data
+ if hasattr(internal_data, "_repr_html_"):
+ return internal_data._repr_html_()
+ return escape(short_data_repr(array))
+
+
+def format_dims(dims, coord_names):
+ if not dims:
+ return ""
+
+ dim_css_map = {
+ k: " class='xr-has-index'" if k in coord_names else "" for k, v in dims.items()
+ }
+
+ dims_li = "".join(
+ f"<li><span{dim_css_map[dim]}>" f"{escape(dim)}</span>: {size}</li>"
+ for dim, size in dims.items()
+ )
+
+ return f"<ul class='xr-dim-list'>{dims_li}</ul>"
+
+
+def summarize_attrs(attrs):
+ attrs_dl = "".join(
+ f"<dt><span>{escape(k)} :</span></dt>" f"<dd>{escape(str(v))}</dd>"
+ for k, v in attrs.items()
+ )
+
+ return f"<dl class='xr-attrs'>{attrs_dl}</dl>"
+
+
+def _icon(icon_name):
+ # icon_name should be defined in xarray/static/html/icon-svg-inline.html
+ return (
+ "<svg class='icon xr-{0}'>"
+ "<use xlink:href='#{0}'>"
+ "</use>"
+ "</svg>".format(icon_name)
+ )
+
+
+def _summarize_coord_multiindex(name, coord):
+ preview = f"({', '.join(escape(l) for l in coord.level_names)})"
+ return summarize_variable(
+ name, coord, is_index=True, dtype="MultiIndex", preview=preview
+ )
+
+
+def summarize_coord(name, var):
+ is_index = name in var.dims
+ if is_index:
+ coord = var.variable.to_index_variable()
+ if coord.level_names is not None:
+ coords = {}
+ coords[name] = _summarize_coord_multiindex(name, coord)
+ for lname in coord.level_names:
+ var = coord.get_level_variable(lname)
+ coords[lname] = summarize_variable(lname, var)
+ return coords
+
+ return {name: summarize_variable(name, var, is_index)}
+
+
+def summarize_coords(variables):
+ coords = {}
+ for k, v in variables.items():
+ coords.update(**summarize_coord(k, v))
+
+ vars_li = "".join(f"<li class='xr-var-item'>{v}</li>" for v in coords.values())
+
+ return f"<ul class='xr-var-list'>{vars_li}</ul>"
+
+
+def summarize_variable(name, var, is_index=False, dtype=None, preview=None):
+ variable = var.variable if hasattr(var, "variable") else var
+
+ cssclass_idx = " class='xr-has-index'" if is_index else ""
+ dims_str = f"({', '.join(escape(dim) for dim in var.dims)})"
+ name = escape(name)
+ dtype = dtype or var.dtype
+
+ # "unique" ids required to expand/collapse subsections
+ attrs_id = "attrs-" + str(uuid.uuid4())
+ data_id = "data-" + str(uuid.uuid4())
+ disabled = "" if len(var.attrs) else "disabled"
+
+ preview = preview or escape(inline_variable_array_repr(variable, 35))
+ attrs_ul = summarize_attrs(var.attrs)
+ data_repr = short_data_repr_html(variable)
+
+ attrs_icon = _icon("icon-file-text2")
+ data_icon = _icon("icon-database")
+
+ return (
+ f"<div class='xr-var-name'><span{cssclass_idx}>{name}</span></div>"
+ f"<div class='xr-var-dims'>{dims_str}</div>"
+ f"<div class='xr-var-dtype'>{dtype}</div>"
+ f"<div class='xr-var-preview xr-preview'>{preview}</div>"
+ f"<input id='{attrs_id}' class='xr-var-attrs-in' "
+ f"type='checkbox' {disabled}>"
+ f"<label for='{attrs_id}' title='Show/Hide attributes'>"
+ f"{attrs_icon}</label>"
+ f"<input id='{data_id}' class='xr-var-data-in' type='checkbox'>"
+ f"<label for='{data_id}' title='Show/Hide data repr'>"
+ f"{data_icon}</label>"
+ f"<div class='xr-var-attrs'>{attrs_ul}</div>"
+ f"<pre class='xr-var-data'>{data_repr}</pre>"
+ )
+
+
+def summarize_vars(variables):
+ vars_li = "".join(
+ f"<li class='xr-var-item'>{summarize_variable(k, v)}</li>"
+ for k, v in variables.items()
+ )
+
+ return f"<ul class='xr-var-list'>{vars_li}</ul>"
+
+
+def collapsible_section(
+ name, inline_details="", details="", n_items=None, enabled=True, collapsed=False
+):
+ # "unique" id to expand/collapse the section
+ data_id = "section-" + str(uuid.uuid4())
+
+ has_items = n_items is not None and n_items
+ n_items_span = "" if n_items is None else f" <span>({n_items})</span>"
+ enabled = "" if enabled and has_items else "disabled"
+ collapsed = "" if collapsed or not has_items else "checked"
+ tip = " title='Expand/collapse section'" if enabled else ""
+
+ return (
+ f"<input id='{data_id}' class='xr-section-summary-in' "
+ f"type='checkbox' {enabled} {collapsed}>"
+ f"<label for='{data_id}' class='xr-section-summary' {tip}>"
+ f"{name}:{n_items_span}</label>"
+ f"<div class='xr-section-inline-details'>{inline_details}</div>"
+ f"<div class='xr-section-details'>{details}</div>"
+ )
+
+
+def _mapping_section(mapping, name, details_func, max_items_collapse, enabled=True):
+ n_items = len(mapping)
+ collapsed = n_items >= max_items_collapse
+
+ return collapsible_section(
+ name,
+ details=details_func(mapping),
+ n_items=n_items,
+ enabled=enabled,
+ collapsed=collapsed,
+ )
+
+
+def dim_section(obj):
+ dim_list = format_dims(obj.dims, list(obj.coords))
+
+ return collapsible_section(
+ "Dimensions", inline_details=dim_list, enabled=False, collapsed=True
+ )
+
+
+def array_section(obj):
+ # "unique" id to expand/collapse the section
+ data_id = "section-" + str(uuid.uuid4())
+ collapsed = ""
+ preview = escape(inline_variable_array_repr(obj.variable, max_width=70))
+ data_repr = short_data_repr_html(obj)
+ data_icon = _icon("icon-database")
+
+ return (
+ "<div class='xr-array-wrap'>"
+ f"<input id='{data_id}' class='xr-array-in' type='checkbox' {collapsed}>"
+ f"<label for='{data_id}' title='Show/hide data repr'>{data_icon}</label>"
+ f"<div class='xr-array-preview xr-preview'><span>{preview}</span></div>"
+ f"<pre class='xr-array-data'>{data_repr}</pre>"
+ "</div>"
+ )
+
+
+coord_section = partial(
+ _mapping_section,
+ name="Coordinates",
+ details_func=summarize_coords,
+ max_items_collapse=25,
+)
+
+
+datavar_section = partial(
+ _mapping_section,
+ name="Data variables",
+ details_func=summarize_vars,
+ max_items_collapse=15,
+)
+
+
+attr_section = partial(
+ _mapping_section,
+ name="Attributes",
+ details_func=summarize_attrs,
+ max_items_collapse=10,
+)
+
+
+def _obj_repr(header_components, sections):
+ header = f"<div class='xr-header'>{''.join(h for h in header_components)}</div>"
+ sections = "".join(f"<li class='xr-section-item'>{s}</li>" for s in sections)
+
+ return (
+ "<div>"
+ f"{ICONS_SVG}<style>{CSS_STYLE}</style>"
+ "<div class='xr-wrap'>"
+ f"{header}"
+ f"<ul class='xr-sections'>{sections}</ul>"
+ "</div>"
+ "</div>"
+ )
+
+
+def array_repr(arr):
+ dims = OrderedDict((k, v) for k, v in zip(arr.dims, arr.shape))
+
+ obj_type = "xarray.{}".format(type(arr).__name__)
+ arr_name = "'{}'".format(arr.name) if getattr(arr, "name", None) else ""
+ coord_names = list(arr.coords) if hasattr(arr, "coords") else []
+
+ header_components = [
+ "<div class='xr-obj-type'>{}</div>".format(obj_type),
+ "<div class='xr-array-name'>{}</div>".format(arr_name),
+ format_dims(dims, coord_names),
+ ]
+
+ sections = [array_section(arr)]
+
+ if hasattr(arr, "coords"):
+ sections.append(coord_section(arr.coords))
+
+ sections.append(attr_section(arr.attrs))
+
+ return _obj_repr(header_components, sections)
+
+
+def dataset_repr(ds):
+ obj_type = "xarray.{}".format(type(ds).__name__)
+
+ header_components = [f"<div class='xr-obj-type'>{escape(obj_type)}</div>"]
+
+ sections = [
+ dim_section(ds),
+ coord_section(ds.coords),
+ datavar_section(ds.data_vars),
+ attr_section(ds.attrs),
+ ]
+
+ return _obj_repr(header_components, sections)
diff --git a/xarray/core/options.py b/xarray/core/options.py
index 2f464a33fb1..72f9ad8e1fa 100644
--- a/xarray/core/options.py
+++ b/xarray/core/options.py
@@ -8,6 +8,7 @@
CMAP_SEQUENTIAL = "cmap_sequential"
CMAP_DIVERGENT = "cmap_divergent"
KEEP_ATTRS = "keep_attrs"
+DISPLAY_STYLE = "display_style"
OPTIONS = {
@@ -19,9 +20,11 @@
CMAP_SEQUENTIAL: "viridis",
CMAP_DIVERGENT: "RdBu_r",
KEEP_ATTRS: "default",
+ DISPLAY_STYLE: "text",
}
_JOIN_OPTIONS = frozenset(["inner", "outer", "left", "right", "exact"])
+_DISPLAY_OPTIONS = frozenset(["text", "html"])
def _positive_integer(value):
@@ -35,6 +38,7 @@ def _positive_integer(value):
FILE_CACHE_MAXSIZE: _positive_integer,
WARN_FOR_UNCLOSED_FILES: lambda value: isinstance(value, bool),
KEEP_ATTRS: lambda choice: choice in [True, False, "default"],
+ DISPLAY_STYLE: _DISPLAY_OPTIONS.__contains__,
}
@@ -98,6 +102,9 @@ class set_options:
attrs, ``False`` to always discard them, or ``'default'`` to use original
logic that attrs should only be kept in unambiguous circumstances.
Default: ``'default'``.
+ - ``display_style``: display style to use in jupyter for xarray objects.
+ Default: ``'text'``. Other options are ``'html'``.
+
You can use ``set_options`` either as a context manager:
diff --git a/xarray/static/css/style.css b/xarray/static/css/style.css
new file mode 100644
index 00000000000..536b8ab6103
--- /dev/null
+++ b/xarray/static/css/style.css
@@ -0,0 +1,310 @@
+/* CSS stylesheet for displaying xarray objects in jupyterlab.
+ *
+ */
+
+.xr-wrap {
+ min-width: 300px;
+ max-width: 700px;
+}
+
+.xr-header {
+ padding-top: 6px;
+ padding-bottom: 6px;
+ margin-bottom: 4px;
+ border-bottom: solid 1px #ddd;
+}
+
+.xr-header > div,
+.xr-header > ul {
+ display: inline;
+ margin-top: 0;
+ margin-bottom: 0;
+}
+
+.xr-obj-type,
+.xr-array-name {
+ margin-left: 2px;
+ margin-right: 10px;
+}
+
+.xr-obj-type {
+ color: #555;
+}
+
+.xr-array-name {
+ color: #000;
+}
+
+.xr-sections {
+ padding-left: 0 !important;
+ display: grid;
+ grid-template-columns: 150px auto auto 1fr 20px 20px;
+}
+
+.xr-section-item {
+ display: contents;
+}
+
+.xr-section-item input {
+ display: none;
+}
+
+.xr-section-item input + label {
+ color: #ccc;
+}
+
+.xr-section-item input:enabled + label {
+ cursor: pointer;
+ color: #555;
+}
+
+.xr-section-item input:enabled + label:hover {
+ color: #000;
+}
+
+.xr-section-summary {
+ grid-column: 1;
+ color: #555;
+ font-weight: 500;
+}
+
+.xr-section-summary > span {
+ display: inline-block;
+ padding-left: 0.5em;
+}
+
+.xr-section-summary-in:disabled + label {
+ color: #555;
+}
+
+.xr-section-summary-in + label:before {
+ display: inline-block;
+ content: '►';
+ font-size: 11px;
+ width: 15px;
+ text-align: center;
+}
+
+.xr-section-summary-in:disabled + label:before {
+ color: #ccc;
+}
+
+.xr-section-summary-in:checked + label:before {
+ content: '▼';
+}
+
+.xr-section-summary-in:checked + label > span {
+ display: none;
+}
+
+.xr-section-summary,
+.xr-section-inline-details {
+ padding-top: 4px;
+ padding-bottom: 4px;
+}
+
+.xr-section-inline-details {
+ grid-column: 2 / -1;
+}
+
+.xr-section-details {
+ display: none;
+ grid-column: 1 / -1;
+ margin-bottom: 5px;
+}
+
+.xr-section-summary-in:checked ~ .xr-section-details {
+ display: contents;
+}
+
+.xr-array-wrap {
+ grid-column: 1 / -1;
+ display: grid;
+ grid-template-columns: 20px auto;
+}
+
+.xr-array-wrap > label {
+ grid-column: 1;
+ vertical-align: top;
+}
+
+.xr-preview {
+ color: #888;
+}
+
+.xr-array-preview,
+.xr-array-data {
+ padding: 0 5px !important;
+ grid-column: 2;
+}
+
+.xr-array-data,
+.xr-array-in:checked ~ .xr-array-preview {
+ display: none;
+}
+
+.xr-array-in:checked ~ .xr-array-data,
+.xr-array-preview {
+ display: inline-block;
+}
+
+.xr-dim-list {
+ display: inline-block !important;
+ list-style: none;
+ padding: 0 !important;
+ margin: 0;
+}
+
+.xr-dim-list li {
+ display: inline-block;
+ padding: 0;
+ margin: 0;
+}
+
+.xr-dim-list:before {
+ content: '(';
+}
+
+.xr-dim-list:after {
+ content: ')';
+}
+
+.xr-dim-list li:not(:last-child):after {
+ content: ',';
+ padding-right: 5px;
+}
+
+.xr-has-index {
+ font-weight: bold;
+}
+
+.xr-var-list,
+.xr-var-item {
+ display: contents;
+}
+
+.xr-var-item > div,
+.xr-var-item label,
+.xr-var-item > .xr-var-name span {
+ background-color: #fcfcfc;
+ margin-bottom: 0;
+}
+
+.xr-var-item > .xr-var-name:hover span {
+ padding-right: 5px;
+}
+
+.xr-var-list > li:nth-child(odd) > div,
+.xr-var-list > li:nth-child(odd) > label,
+.xr-var-list > li:nth-child(odd) > .xr-var-name span {
+ background-color: #efefef;
+}
+
+.xr-var-name {
+ grid-column: 1;
+}
+
+.xr-var-dims {
+ grid-column: 2;
+}
+
+.xr-var-dtype {
+ grid-column: 3;
+ text-align: right;
+ color: #555;
+}
+
+.xr-var-preview {
+ grid-column: 4;
+}
+
+.xr-var-name,
+.xr-var-dims,
+.xr-var-dtype,
+.xr-preview,
+.xr-attrs dt {
+ white-space: nowrap;
+ overflow: hidden;
+ text-overflow: ellipsis;
+ padding-right: 10px;
+}
+
+.xr-var-name:hover,
+.xr-var-dims:hover,
+.xr-var-dtype:hover,
+.xr-attrs dt:hover {
+ overflow: visible;
+ width: auto;
+ z-index: 1;
+}
+
+.xr-var-attrs,
+.xr-var-data {
+ display: none;
+ background-color: #fff !important;
+ padding-bottom: 5px !important;
+}
+
+.xr-var-attrs-in:checked ~ .xr-var-attrs,
+.xr-var-data-in:checked ~ .xr-var-data {
+ display: block;
+}
+
+.xr-var-data > table {
+ float: right;
+}
+
+.xr-var-name span,
+.xr-var-data,
+.xr-attrs {
+ padding-left: 25px !important;
+}
+
+.xr-attrs,
+.xr-var-attrs,
+.xr-var-data {
+ grid-column: 1 / -1;
+}
+
+dl.xr-attrs {
+ padding: 0;
+ margin: 0;
+ display: grid;
+ grid-template-columns: 125px auto;
+}
+
+.xr-attrs dt, dd {
+ padding: 0;
+ margin: 0;
+ float: left;
+ padding-right: 10px;
+ width: auto;
+}
+
+.xr-attrs dt {
+ font-weight: normal;
+ grid-column: 1;
+}
+
+.xr-attrs dt:hover span {
+ display: inline-block;
+ background: #fff;
+ padding-right: 10px;
+}
+
+.xr-attrs dd {
+ grid-column: 2;
+ white-space: pre-wrap;
+ word-break: break-all;
+}
+
+.xr-icon-database,
+.xr-icon-file-text2 {
+ display: inline-block;
+ vertical-align: middle;
+ width: 1em;
+ height: 1.5em !important;
+ stroke-width: 0;
+ stroke: currentColor;
+ fill: currentColor;
+}
diff --git a/xarray/static/html/icons-svg-inline.html b/xarray/static/html/icons-svg-inline.html
new file mode 100644
index 00000000000..c44f89c4304
--- /dev/null
+++ b/xarray/static/html/icons-svg-inline.html
@@ -0,0 +1,17 @@
+<svg style="position: absolute; width: 0; height: 0; overflow: hidden">
+<defs>
+<symbol id="icon-database" viewBox="0 0 32 32">
+<title>Show/Hide data repr</title>
+<path d="M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z"></path>
+<path d="M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z"></path>
+<path d="M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z"></path>
+</symbol>
+<symbol id="icon-file-text2" viewBox="0 0 32 32">
+<title>Show/Hide attributes</title>
+<path d="M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z"></path>
+<path d="M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z"></path>
+<path d="M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z"></path>
+<path d="M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z"></path>
+</symbol>
+</defs>
+</svg>
|
diff --git a/xarray/tests/test_formatting_html.py b/xarray/tests/test_formatting_html.py
new file mode 100644
index 00000000000..e7f54b22d06
--- /dev/null
+++ b/xarray/tests/test_formatting_html.py
@@ -0,0 +1,132 @@
+from distutils.version import LooseVersion
+
+import numpy as np
+import pandas as pd
+import pytest
+
+import xarray as xr
+from xarray.core import formatting_html as fh
+
+
+@pytest.fixture
+def dataarray():
+ return xr.DataArray(np.random.RandomState(0).randn(4, 6))
+
+
+@pytest.fixture
+def dask_dataarray(dataarray):
+ pytest.importorskip("dask")
+ return dataarray.chunk()
+
+
+@pytest.fixture
+def multiindex():
+ mindex = pd.MultiIndex.from_product(
+ [["a", "b"], [1, 2]], names=("level_1", "level_2")
+ )
+ return xr.Dataset({}, {"x": mindex})
+
+
+@pytest.fixture
+def dataset():
+ times = pd.date_range("2000-01-01", "2001-12-31", name="time")
+ annual_cycle = np.sin(2 * np.pi * (times.dayofyear.values / 365.25 - 0.28))
+
+ base = 10 + 15 * annual_cycle.reshape(-1, 1)
+ tmin_values = base + 3 * np.random.randn(annual_cycle.size, 3)
+ tmax_values = base + 10 + 3 * np.random.randn(annual_cycle.size, 3)
+
+ return xr.Dataset(
+ {
+ "tmin": (("time", "location"), tmin_values),
+ "tmax": (("time", "location"), tmax_values),
+ },
+ {"time": times, "location": ["<IA>", "IN", "IL"]},
+ attrs={"description": "Test data."},
+ )
+
+
+def test_short_data_repr_html(dataarray):
+ data_repr = fh.short_data_repr_html(dataarray)
+ assert data_repr.startswith("array")
+
+
+def test_short_data_repr_html_dask(dask_dataarray):
+ import dask
+
+ if LooseVersion(dask.__version__) < "2.0.0":
+ assert not hasattr(dask_dataarray.data, "_repr_html_")
+ data_repr = fh.short_data_repr_html(dask_dataarray)
+ assert (
+ data_repr
+ == "dask.array<xarray-<this-array>, shape=(4, 6), dtype=float64, chunksize=(4, 6)>"
+ )
+ else:
+ assert hasattr(dask_dataarray.data, "_repr_html_")
+ data_repr = fh.short_data_repr_html(dask_dataarray)
+ assert data_repr == dask_dataarray.data._repr_html_()
+
+
+def test_format_dims_no_dims():
+ dims, coord_names = {}, []
+ formatted = fh.format_dims(dims, coord_names)
+ assert formatted == ""
+
+
+def test_format_dims_unsafe_dim_name():
+ dims, coord_names = {"<x>": 3, "y": 2}, []
+ formatted = fh.format_dims(dims, coord_names)
+ assert "<x>" in formatted
+
+
+def test_format_dims_non_index():
+ dims, coord_names = {"x": 3, "y": 2}, ["time"]
+ formatted = fh.format_dims(dims, coord_names)
+ assert "class='xr-has-index'" not in formatted
+
+
+def test_format_dims_index():
+ dims, coord_names = {"x": 3, "y": 2}, ["x"]
+ formatted = fh.format_dims(dims, coord_names)
+ assert "class='xr-has-index'" in formatted
+
+
+def test_summarize_attrs_with_unsafe_attr_name_and_value():
+ attrs = {"<x>": 3, "y": "<pd.DataFrame>"}
+ formatted = fh.summarize_attrs(attrs)
+ assert "<dt><span><x> :</span></dt>" in formatted
+ assert "<dt><span>y :</span></dt>" in formatted
+ assert "<dd>3</dd>" in formatted
+ assert "<dd><pd.DataFrame></dd>" in formatted
+
+
+def test_repr_of_dataarray(dataarray):
+ formatted = fh.array_repr(dataarray)
+ assert "dim_0" in formatted
+ # has an expandable data section
+ assert formatted.count("class='xr-array-in' type='checkbox' >") == 1
+ # coords and attrs don't have an items so they'll be be disabled and collapsed
+ assert (
+ formatted.count("class='xr-section-summary-in' type='checkbox' disabled >") == 2
+ )
+
+
+def test_summary_of_multiindex_coord(multiindex):
+ idx = multiindex.x.variable.to_index_variable()
+ formatted = fh._summarize_coord_multiindex("foo", idx)
+ assert "(level_1, level_2)" in formatted
+ assert "MultiIndex" in formatted
+ assert "<span class='xr-has-index'>foo</span>" in formatted
+
+
+def test_repr_of_multiindex(multiindex):
+ formatted = fh.dataset_repr(multiindex)
+ assert "(x)" in formatted
+
+
+def test_repr_of_dataset(dataset):
+ formatted = fh.dataset_repr(dataset)
+ # coords, attrs, and data_vars are expanded
+ assert (
+ formatted.count("class='xr-section-summary-in' type='checkbox' checked>") == 3
+ )
diff --git a/xarray/tests/test_options.py b/xarray/tests/test_options.py
index 2aa77ecd6b3..f155acbf494 100644
--- a/xarray/tests/test_options.py
+++ b/xarray/tests/test_options.py
@@ -67,6 +67,16 @@ def test_nested_options():
assert OPTIONS["display_width"] == original
+def test_display_style():
+ original = "text"
+ assert OPTIONS["display_style"] == original
+ with pytest.raises(ValueError):
+ xarray.set_options(display_style="invalid_str")
+ with xarray.set_options(display_style="html"):
+ assert OPTIONS["display_style"] == "html"
+ assert OPTIONS["display_style"] == original
+
+
def create_test_dataset_attrs(seed=0):
ds = create_test_data(seed)
ds.attrs = {"attr1": 5, "attr2": "history", "attr3": {"nested": "more_info"}}
@@ -164,3 +174,30 @@ def test_merge_attr_retention(self):
# option doesn't affect this
result = merge([da1, da2])
assert result.attrs == original_attrs
+
+ def test_display_style_text(self):
+ ds = create_test_dataset_attrs()
+ text = ds._repr_html_()
+ assert text.startswith("<pre>")
+ assert "'nested'" in text
+ assert "<xarray.Dataset>" in text
+
+ def test_display_style_html(self):
+ ds = create_test_dataset_attrs()
+ with xarray.set_options(display_style="html"):
+ html = ds._repr_html_()
+ assert html.startswith("<div>")
+ assert "'nested'" in html
+
+ def test_display_dataarray_style_text(self):
+ da = create_test_dataarray_attrs()
+ text = da._repr_html_()
+ assert text.startswith("<pre>")
+ assert "<xarray.DataArray 'var1'" in text
+
+ def test_display_dataarray_style_html(self):
+ da = create_test_dataarray_attrs()
+ with xarray.set_options(display_style="html"):
+ html = da._repr_html_()
+ assert html.startswith("<div>")
+ assert "#x27;nested'" in html
|
[
{
"path": "doc/whats-new.rst",
"old_path": "a/doc/whats-new.rst",
"new_path": "b/doc/whats-new.rst",
"metadata": "diff --git a/doc/whats-new.rst b/doc/whats-new.rst\nindex 9d3e64badb8..12bed8f332e 100644\n--- a/doc/whats-new.rst\n+++ b/doc/whats-new.rst\n@@ -36,6 +36,12 @@ New Features\n ``pip install git+https://github.com/andrewgsavage/pint.git@refs/pull/6/head)``.\n Even with it, interaction with non-numpy array libraries, e.g. dask or sparse, is broken.\n \n+- Added new :py:meth:`Dataset._repr_html_` and :py:meth:`DataArray._repr_html_` to improve\n+ representation of objects in jupyter. By default this feature is turned off\n+ for now. Enable it with :py:meth:`xarray.set_options(display_style=\"html\")`.\n+ (:pull:`3425`) by `Benoit Bovy <https://github.com/benbovy>`_ and\n+ `Julia Signell <https://github.com/jsignell>`_.\n+\n Bug fixes\n ~~~~~~~~~\n - Fix regression introduced in v0.14.0 that would cause a crash if dask is installed\n"
}
] |
0014
|
652dd3ca77dd19bbd1ab21fe556340c1904ec382
|
[
"xarray/tests/test_options.py::test_file_cache_maxsize",
"xarray/tests/test_options.py::TestAttrRetention::test_concat_attr_retention",
"xarray/tests/test_options.py::TestAttrRetention::test_dataset_attr_retention",
"xarray/tests/test_options.py::test_display_width",
"xarray/tests/test_options.py::test_invalid_option_raises",
"xarray/tests/test_options.py::test_nested_options",
"xarray/tests/test_options.py::test_keep_attrs",
"xarray/tests/test_options.py::test_arithmetic_join",
"xarray/tests/test_options.py::TestAttrRetention::test_groupby_attr_retention",
"xarray/tests/test_options.py::test_enable_cftimeindex",
"xarray/tests/test_options.py::TestAttrRetention::test_dataarray_attr_retention"
] |
[
"xarray/tests/test_formatting_html.py::test_repr_of_multiindex",
"xarray/tests/test_formatting_html.py::test_format_dims_unsafe_dim_name",
"xarray/tests/test_formatting_html.py::test_format_dims_index",
"xarray/tests/test_formatting_html.py::test_format_dims_no_dims",
"xarray/tests/test_options.py::TestAttrRetention::test_display_dataarray_style_html",
"xarray/tests/test_formatting_html.py::test_summary_of_multiindex_coord",
"xarray/tests/test_formatting_html.py::test_repr_of_dataarray",
"xarray/tests/test_formatting_html.py::test_short_data_repr_html",
"xarray/tests/test_options.py::test_display_style",
"xarray/tests/test_options.py::TestAttrRetention::test_display_style_text",
"xarray/tests/test_options.py::TestAttrRetention::test_display_style_html",
"xarray/tests/test_formatting_html.py::test_format_dims_non_index",
"xarray/tests/test_formatting_html.py::test_repr_of_dataset",
"xarray/tests/test_options.py::TestAttrRetention::test_display_dataarray_style_text",
"xarray/tests/test_formatting_html.py::test_summarize_attrs_with_unsafe_attr_name_and_value"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": [
{
"type": "function",
"name": "format_dims"
},
{
"type": "field",
"name": "data_repr"
},
{
"type": "field",
"name": "formatting_html"
},
{
"type": "field",
"name": "name"
},
{
"type": "field",
"name": "short_data_repr_html"
},
{
"type": "field",
"name": "values"
},
{
"type": "field",
"name": "variable"
},
{
"type": "field",
"name": "coord_names"
},
{
"type": "field",
"name": "summarize_attrs"
},
{
"type": "function",
"name": "dataset_repr"
},
{
"type": "file",
"name": "xarray/core/formatting_html.py"
},
{
"type": "field",
"name": "dims"
},
{
"type": "field",
"name": "format_dims"
},
{
"type": "function",
"name": "array_repr"
},
{
"type": "field",
"name": "_summarize_coord_multiindex"
},
{
"type": "field",
"name": "size"
},
{
"type": "field",
"name": "to_index_variable"
},
{
"type": "function",
"name": "_summarize_coord_multiindex"
},
{
"type": "field",
"name": "attrs"
},
{
"type": "field",
"name": "hasattr"
},
{
"type": "function",
"name": "short_data_repr_html"
},
{
"type": "function",
"name": "summarize_attrs"
},
{
"type": "field",
"name": "formatting_html"
}
]
}
|
[
{
"path": "doc/whats-new.rst",
"old_path": "a/doc/whats-new.rst",
"new_path": "b/doc/whats-new.rst",
"metadata": "diff --git a/doc/whats-new.rst b/doc/whats-new.rst\nindex 9d3e64badb8..12bed8f332e 100644\n--- a/doc/whats-new.rst\n+++ b/doc/whats-new.rst\n@@ -36,6 +36,12 @@ New Features\n ``pip install git+https://github.com/andrewgsavage/pint.git@refs/pull/6/head)``.\n Even with it, interaction with non-numpy array libraries, e.g. dask or sparse, is broken.\n \n+- Added new :py:meth:`Dataset._repr_html_` and :py:meth:`DataArray._repr_html_` to improve\n+ representation of objects in jupyter. By default this feature is turned off\n+ for now. Enable it with :py:meth:`xarray.set_options(display_style=\"html\")`.\n+ (:pull:`<PRID>`) by `<NAME>`_ and\n+ <NAME>_.\n+\n Bug fixes\n ~~~~~~~~~\n - Fix regression introduced in v0.14.0 that would cause a crash if dask is installed\n"
}
] |
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index 9d3e64badb8..12bed8f332e 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -36,6 +36,12 @@ New Features
``pip install git+https://github.com/andrewgsavage/pint.git@refs/pull/6/head)``.
Even with it, interaction with non-numpy array libraries, e.g. dask or sparse, is broken.
+- Added new :py:meth:`Dataset._repr_html_` and :py:meth:`DataArray._repr_html_` to improve
+ representation of objects in jupyter. By default this feature is turned off
+ for now. Enable it with :py:meth:`xarray.set_options(display_style="html")`.
+ (:pull:`<PRID>`) by `<NAME>`_ and
+ <NAME>_.
+
Bug fixes
~~~~~~~~~
- Fix regression introduced in v0.14.0 that would cause a crash if dask is installed
If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:
[{'type': 'function', 'name': 'format_dims'}, {'type': 'field', 'name': 'data_repr'}, {'type': 'field', 'name': 'formatting_html'}, {'type': 'field', 'name': 'name'}, {'type': 'field', 'name': 'short_data_repr_html'}, {'type': 'field', 'name': 'values'}, {'type': 'field', 'name': 'variable'}, {'type': 'field', 'name': 'coord_names'}, {'type': 'field', 'name': 'summarize_attrs'}, {'type': 'function', 'name': 'dataset_repr'}, {'type': 'file', 'name': 'xarray/core/formatting_html.py'}, {'type': 'field', 'name': 'dims'}, {'type': 'field', 'name': 'format_dims'}, {'type': 'function', 'name': 'array_repr'}, {'type': 'field', 'name': '_summarize_coord_multiindex'}, {'type': 'field', 'name': 'size'}, {'type': 'field', 'name': 'to_index_variable'}, {'type': 'function', 'name': '_summarize_coord_multiindex'}, {'type': 'field', 'name': 'attrs'}, {'type': 'field', 'name': 'hasattr'}, {'type': 'function', 'name': 'short_data_repr_html'}, {'type': 'function', 'name': 'summarize_attrs'}, {'type': 'field', 'name': 'formatting_html'}]
|
pydata/xarray
|
pydata__xarray-3636
|
https://github.com/pydata/xarray/pull/3636
|
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index 00d1c50780e..402a06840e2 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -37,6 +37,9 @@ New Features
- Added the ``count`` reduction method to both :py:class:`~core.rolling.DatasetCoarsen`
and :py:class:`~core.rolling.DataArrayCoarsen` objects. (:pull:`3500`)
By `Deepak Cherian <https://github.com/dcherian>`_
+- :py:meth:`Dataset.swap_dims` and :py:meth:`DataArray.swap_dims`
+ now allow swapping to dimension names that don't exist yet. (:pull:`3636`)
+ By `Justus Magin <https://github.com/keewis>`_.
- Extend :py:class:`core.accessor_dt.DatetimeAccessor` properties
and support `.dt` accessor for timedelta
via :py:class:`core.accessor_dt.TimedeltaAccessor` (:pull:`3612`)
diff --git a/xarray/core/dataarray.py b/xarray/core/dataarray.py
index 31aa4da57b2..cbd8d243385 100644
--- a/xarray/core/dataarray.py
+++ b/xarray/core/dataarray.py
@@ -1480,8 +1480,7 @@ def swap_dims(self, dims_dict: Mapping[Hashable, Hashable]) -> "DataArray":
----------
dims_dict : dict-like
Dictionary whose keys are current dimension names and whose values
- are new names. Each value must already be a coordinate on this
- array.
+ are new names.
Returns
-------
@@ -1504,6 +1503,13 @@ def swap_dims(self, dims_dict: Mapping[Hashable, Hashable]) -> "DataArray":
Coordinates:
x (y) <U1 'a' 'b'
* y (y) int64 0 1
+ >>> arr.swap_dims({"x": "z"})
+ <xarray.DataArray (z: 2)>
+ array([0, 1])
+ Coordinates:
+ x (z) <U1 'a' 'b'
+ y (z) int64 0 1
+ Dimensions without coordinates: z
See Also
--------
diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index 6be06fed117..a1da99e2b9a 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -2868,8 +2868,7 @@ def swap_dims(
----------
dims_dict : dict-like
Dictionary whose keys are current dimension names and whose values
- are new names. Each value must already be a variable in the
- dataset.
+ are new names.
Returns
-------
@@ -2898,6 +2897,16 @@ def swap_dims(
Data variables:
a (y) int64 5 7
b (y) float64 0.1 2.4
+ >>> ds.swap_dims({"x": "z"})
+ <xarray.Dataset>
+ Dimensions: (z: 2)
+ Coordinates:
+ x (z) <U1 'a' 'b'
+ y (z) int64 0 1
+ Dimensions without coordinates: z
+ Data variables:
+ a (z) int64 5 7
+ b (z) float64 0.1 2.4
See Also
--------
@@ -2914,7 +2923,7 @@ def swap_dims(
"cannot swap from dimension %r because it is "
"not an existing dimension" % k
)
- if self.variables[v].dims != (k,):
+ if v in self.variables and self.variables[v].dims != (k,):
raise ValueError(
"replacement dimension %r is not a 1D "
"variable along the old dimension %r" % (v, k)
@@ -2923,7 +2932,7 @@ def swap_dims(
result_dims = {dims_dict.get(dim, dim) for dim in self.dims}
coord_names = self._coord_names.copy()
- coord_names.update(dims_dict.values())
+ coord_names.update({dim for dim in dims_dict.values() if dim in self.variables})
variables: Dict[Hashable, Variable] = {}
indexes: Dict[Hashable, pd.Index] = {}
|
diff --git a/xarray/tests/test_dataarray.py b/xarray/tests/test_dataarray.py
index f957316d8ac..4189c3b504a 100644
--- a/xarray/tests/test_dataarray.py
+++ b/xarray/tests/test_dataarray.py
@@ -1530,6 +1530,11 @@ def test_swap_dims(self):
actual = array.swap_dims({"x": "y"})
assert_identical(expected, actual)
+ array = DataArray(np.random.randn(3), {"x": list("abc")}, "x")
+ expected = DataArray(array.values, {"x": ("y", list("abc"))}, dims="y")
+ actual = array.swap_dims({"x": "y"})
+ assert_identical(expected, actual)
+
def test_expand_dims_error(self):
array = DataArray(
np.random.randn(3, 4),
diff --git a/xarray/tests/test_dataset.py b/xarray/tests/test_dataset.py
index 7db1911621b..9a029121a10 100644
--- a/xarray/tests/test_dataset.py
+++ b/xarray/tests/test_dataset.py
@@ -2525,6 +2525,12 @@ def test_swap_dims(self):
with raises_regex(ValueError, "replacement dimension"):
original.swap_dims({"x": "z"})
+ expected = Dataset(
+ {"y": ("u", list("abc")), "z": 42}, coords={"x": ("u", [1, 2, 3])}
+ )
+ actual = original.swap_dims({"x": "u"})
+ assert_identical(expected, actual)
+
def test_expand_dims_error(self):
original = Dataset(
{
|
[
{
"path": "doc/whats-new.rst",
"old_path": "a/doc/whats-new.rst",
"new_path": "b/doc/whats-new.rst",
"metadata": "diff --git a/doc/whats-new.rst b/doc/whats-new.rst\nindex 00d1c50780e..402a06840e2 100644\n--- a/doc/whats-new.rst\n+++ b/doc/whats-new.rst\n@@ -37,6 +37,9 @@ New Features\n - Added the ``count`` reduction method to both :py:class:`~core.rolling.DatasetCoarsen`\n and :py:class:`~core.rolling.DataArrayCoarsen` objects. (:pull:`3500`)\n By `Deepak Cherian <https://github.com/dcherian>`_\n+- :py:meth:`Dataset.swap_dims` and :py:meth:`DataArray.swap_dims`\n+ now allow swapping to dimension names that don't exist yet. (:pull:`3636`)\n+ By `Justus Magin <https://github.com/keewis>`_.\n - Extend :py:class:`core.accessor_dt.DatetimeAccessor` properties \n and support `.dt` accessor for timedelta \n via :py:class:`core.accessor_dt.TimedeltaAccessor` (:pull:`3612`)\n"
}
] |
0015
|
b3d3b4480b7fb63402eb6c02103bb8d6c7dbf93a
|
[
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"xarray/tests/test_dataset.py::TestDataset::test_isel_expand_dims_roundtrip",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-2-None-False]",
"xarray/tests/test_dataset.py::TestDataset::test_reduce_non_numeric",
"xarray/tests/test_dataset.py::TestDataset::test_repr_period_index",
"xarray/tests/test_dataarray.py::TestDataArray::test_to_masked_array",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-3-1-True-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-1-3-False-1]",
"xarray/tests/test_dataset.py::TestDataset::test_dataset_diff_n1_simple",
"xarray/tests/test_dataset.py::test_rolling_reduce[mean-3-3-True-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-3-None-True-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_reindex_fill_value[2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[mean-1-None-True-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-4-2-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-2-None-False-1]",
"xarray/tests/test_dataset.py::TestDataset::test_expand_dims_existing_scalar_coord",
"xarray/tests/test_dataset.py::test_rolling_reduce[median-2-None-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-3-1-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-1-3-True-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_coord_coords",
"xarray/tests/test_dataset.py::TestDataset::test_merge_multiindex_level",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-4-None-True-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[median-2-3-True-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-3-None-False-1]",
"xarray/tests/test_dataset.py::TestDataset::test_shift[2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-1-1-True-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-4-1-False-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[median-3-1-True-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_upsample_nd",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-2-3-True-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_getitem",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-1-None-False-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[sum-1-3-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-2-None-True-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[sum-4-3-False]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-3-3-False]",
"xarray/tests/test_dataset.py::test_dataset_constructor_aligns_to_explicit_coords[coords1-unaligned_coords0]",
"xarray/tests/test_dataset.py::test_rolling_reduce[sum-3-None-False-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_transpose",
"xarray/tests/test_dataset.py::TestDataset::test_head",
"xarray/tests/test_dataset.py::test_rolling_reduce[median-4-2-True-1]",
"xarray/tests/test_dataset.py::test_rolling_properties[1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-3-3-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[sum-1-2-True-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_groupby_multidim_map",
"xarray/tests/test_dataarray.py::TestDataArray::test_to_dict_with_numpy_attrs",
"xarray/tests/test_dataset.py::test_rolling_reduce[mean-3-1-False-1]",
"xarray/tests/test_dataset.py::TestDataset::test_assign_attrs",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-2-2-True]",
"xarray/tests/test_dataset.py::TestDataset::test_coords_modify",
"xarray/tests/test_dataset.py::TestDataset::test_resample_by_last_discarding_attrs",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-None-None-mean]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-1-1-True-1]",
"xarray/tests/test_dataset.py::TestDataset::test_asarray",
"xarray/tests/test_dataarray.py::TestDataArray::test_stack_unstack",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-3-3-False-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-3-2-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-1-None-False-1]",
"xarray/tests/test_dataset.py::TestDataset::test_dataset_transpose",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-4-1-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-2-3-True-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_reset_coords",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-4-2-True-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-3-1-False-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-2-2-True-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-3-None-False-1]",
"xarray/tests/test_dataset.py::TestDataset::test_groupby_math",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-2-2-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_pandas_compat[4-1-False]",
"xarray/tests/test_dataarray.py::TestDataArray::test_broadcast_arrays_nocopy",
"xarray/tests/test_dataarray.py::TestDataArray::test_inplace_math_automatic_alignment",
"xarray/tests/test_dataset.py::test_dataset_constructor_aligns_to_explicit_coords[coords1-unaligned_coords8]",
"xarray/tests/test_dataarray.py::TestDataArray::test_loc_assign",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[sum-1-3-False]",
"xarray/tests/test_dataarray.py::TestDataArray::test_expand_dims_error",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-2-None-True-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-3-3-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-1-None-True-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-1-1-True-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_align_without_indexes_errors",
"xarray/tests/test_dataarray.py::test_rolling_wrapped_bottleneck[1-1-None-min]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-2-1-False]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-2-1-False-2]",
"xarray/tests/test_dataset.py::test_coarsen[1-pad-right-False]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-1-True-mean]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-1-None-sum]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-2-3-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-2-None-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[median-4-3-True-1]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-None-True-std]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-3-None-True-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[min-1-None-True-1]"
] |
[
"xarray/tests/test_dataset.py::TestDataset::test_swap_dims",
"xarray/tests/test_dataarray.py::TestDataArray::test_swap_dims"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/whats-new.rst",
"old_path": "a/doc/whats-new.rst",
"new_path": "b/doc/whats-new.rst",
"metadata": "diff --git a/doc/whats-new.rst b/doc/whats-new.rst\nindex 00d1c50780e..402a06840e2 100644\n--- a/doc/whats-new.rst\n+++ b/doc/whats-new.rst\n@@ -37,6 +37,9 @@ New Features\n - Added the ``count`` reduction method to both :py:class:`~core.rolling.DatasetCoarsen`\n and :py:class:`~core.rolling.DataArrayCoarsen` objects. (:pull:`<PRID>`)\n By `<NAME>`_\n+- :py:meth:`Dataset.swap_dims` and :py:meth:`DataArray.swap_dims`\n+ now allow swapping to dimension names that don't exist yet. (:pull:`<PRID>`)\n+ By `<NAME>`_.\n - Extend :py:class:`core.accessor_dt.DatetimeAccessor` properties \n and support `.dt` accessor for timedelta \n via :py:class:`core.accessor_dt.TimedeltaAccessor` (:pull:`<PRID>`)\n"
}
] |
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index 00d1c50780e..402a06840e2 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -37,6 +37,9 @@ New Features
- Added the ``count`` reduction method to both :py:class:`~core.rolling.DatasetCoarsen`
and :py:class:`~core.rolling.DataArrayCoarsen` objects. (:pull:`<PRID>`)
By `<NAME>`_
+- :py:meth:`Dataset.swap_dims` and :py:meth:`DataArray.swap_dims`
+ now allow swapping to dimension names that don't exist yet. (:pull:`<PRID>`)
+ By `<NAME>`_.
- Extend :py:class:`core.accessor_dt.DatetimeAccessor` properties
and support `.dt` accessor for timedelta
via :py:class:`core.accessor_dt.TimedeltaAccessor` (:pull:`<PRID>`)
|
pydata/xarray
|
pydata__xarray-3527
|
https://github.com/pydata/xarray/pull/3527
|
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index ea3b012cc98..ad430b1bcfc 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -76,6 +76,8 @@ New Features
invoked. (:issue:`3378`, :pull:`3446`, :pull:`3515`)
By `Deepak Cherian <https://github.com/dcherian>`_ and
`Guido Imperiale <https://github.com/crusaderky>`_.
+- Add the documented-but-missing :py:meth:`xarray.core.groupby.DatasetGroupBy.quantile`.
+ (:issue:`3525`, :pull:`3527`). By `Justus Magin <https://github.com/keewis>`_.
Bug fixes
~~~~~~~~~
diff --git a/xarray/core/groupby.py b/xarray/core/groupby.py
index c73ee3cf7c5..38ecc04534a 100644
--- a/xarray/core/groupby.py
+++ b/xarray/core/groupby.py
@@ -557,6 +557,59 @@ def fillna(self, value):
out = ops.fillna(self, value)
return out
+ def quantile(self, q, dim=None, interpolation="linear", keep_attrs=None):
+ """Compute the qth quantile over each array in the groups and
+ concatenate them together into a new array.
+
+ Parameters
+ ----------
+ q : float in range of [0,1] (or sequence of floats)
+ Quantile to compute, which must be between 0 and 1
+ inclusive.
+ dim : `...`, str or sequence of str, optional
+ Dimension(s) over which to apply quantile.
+ Defaults to the grouped dimension.
+ interpolation : {'linear', 'lower', 'higher', 'midpoint', 'nearest'}
+ This optional parameter specifies the interpolation method to
+ use when the desired quantile lies between two data points
+ ``i < j``:
+ * linear: ``i + (j - i) * fraction``, where ``fraction`` is
+ the fractional part of the index surrounded by ``i`` and
+ ``j``.
+ * lower: ``i``.
+ * higher: ``j``.
+ * nearest: ``i`` or ``j``, whichever is nearest.
+ * midpoint: ``(i + j) / 2``.
+
+ Returns
+ -------
+ quantiles : Variable
+ If `q` is a single quantile, then the result is a
+ scalar. If multiple percentiles are given, first axis of
+ the result corresponds to the quantile. In either case a
+ quantile dimension is added to the return array. The other
+ dimensions are the dimensions that remain after the
+ reduction of the array.
+
+ See Also
+ --------
+ numpy.nanpercentile, pandas.Series.quantile, Dataset.quantile,
+ DataArray.quantile
+ """
+ if dim is None:
+ dim = self._group_dim
+
+ out = self.map(
+ self._obj.__class__.quantile,
+ shortcut=False,
+ q=q,
+ dim=dim,
+ interpolation=interpolation,
+ keep_attrs=keep_attrs,
+ )
+
+ return out
+
def where(self, cond, other=dtypes.NA):
"""Return elements from `self` or `other` depending on `cond`.
@@ -737,60 +790,6 @@ def _combine(self, applied, restore_coord_dims=False, shortcut=False):
combined = self._maybe_unstack(combined)
return combined
- def quantile(self, q, dim=None, interpolation="linear", keep_attrs=None):
- """Compute the qth quantile over each array in the groups and
- concatenate them together into a new array.
-
- Parameters
- ----------
- q : float in range of [0,1] (or sequence of floats)
- Quantile to compute, which must be between 0 and 1
- inclusive.
- dim : `...`, str or sequence of str, optional
- Dimension(s) over which to apply quantile.
- Defaults to the grouped dimension.
- interpolation : {'linear', 'lower', 'higher', 'midpoint', 'nearest'}
- This optional parameter specifies the interpolation method to
- use when the desired quantile lies between two data points
- ``i < j``:
- * linear: ``i + (j - i) * fraction``, where ``fraction`` is
- the fractional part of the index surrounded by ``i`` and
- ``j``.
- * lower: ``i``.
- * higher: ``j``.
- * nearest: ``i`` or ``j``, whichever is nearest.
- * midpoint: ``(i + j) / 2``.
-
- Returns
- -------
- quantiles : Variable
- If `q` is a single quantile, then the result
- is a scalar. If multiple percentiles are given, first axis of
- the result corresponds to the quantile and a quantile dimension
- is added to the return array. The other dimensions are the
- dimensions that remain after the reduction of the array.
-
- See Also
- --------
- numpy.nanpercentile, pandas.Series.quantile, Dataset.quantile,
- DataArray.quantile
- """
- if dim is None:
- dim = self._group_dim
-
- out = self.map(
- self._obj.__class__.quantile,
- shortcut=False,
- q=q,
- dim=dim,
- interpolation=interpolation,
- keep_attrs=keep_attrs,
- )
-
- if np.asarray(q, dtype=np.float64).ndim == 0:
- out = out.drop_vars("quantile")
- return out
-
def reduce(
self, func, dim=None, axis=None, keep_attrs=None, shortcut=True, **kwargs
):
|
diff --git a/xarray/tests/test_groupby.py b/xarray/tests/test_groupby.py
index 581affa3471..97bd31ae050 100644
--- a/xarray/tests/test_groupby.py
+++ b/xarray/tests/test_groupby.py
@@ -137,42 +137,58 @@ def test_da_groupby_empty():
def test_da_groupby_quantile():
- array = xr.DataArray([1, 2, 3, 4, 5, 6], [("x", [1, 1, 1, 2, 2, 2])])
+ array = xr.DataArray(
+ data=[1, 2, 3, 4, 5, 6], coords={"x": [1, 1, 1, 2, 2, 2]}, dims="x"
+ )
# Scalar quantile
- expected = xr.DataArray([2, 5], [("x", [1, 2])])
+ expected = xr.DataArray(
+ data=[2, 5], coords={"x": [1, 2], "quantile": 0.5}, dims="x"
+ )
actual = array.groupby("x").quantile(0.5)
assert_identical(expected, actual)
# Vector quantile
- expected = xr.DataArray([[1, 3], [4, 6]], [("x", [1, 2]), ("quantile", [0, 1])])
+ expected = xr.DataArray(
+ data=[[1, 3], [4, 6]],
+ coords={"x": [1, 2], "quantile": [0, 1]},
+ dims=("x", "quantile"),
+ )
actual = array.groupby("x").quantile([0, 1])
assert_identical(expected, actual)
# Multiple dimensions
array = xr.DataArray(
- [[1, 11, 26], [2, 12, 22], [3, 13, 23], [4, 16, 24], [5, 15, 25]],
- [("x", [1, 1, 1, 2, 2]), ("y", [0, 0, 1])],
+ data=[[1, 11, 26], [2, 12, 22], [3, 13, 23], [4, 16, 24], [5, 15, 25]],
+ coords={"x": [1, 1, 1, 2, 2], "y": [0, 0, 1]},
+ dims=("x", "y"),
)
actual_x = array.groupby("x").quantile(0, dim=...)
- expected_x = xr.DataArray([1, 4], [("x", [1, 2])])
+ expected_x = xr.DataArray(
+ data=[1, 4], coords={"x": [1, 2], "quantile": 0}, dims="x"
+ )
assert_identical(expected_x, actual_x)
actual_y = array.groupby("y").quantile(0, dim=...)
- expected_y = xr.DataArray([1, 22], [("y", [0, 1])])
+ expected_y = xr.DataArray(
+ data=[1, 22], coords={"y": [0, 1], "quantile": 0}, dims="y"
+ )
assert_identical(expected_y, actual_y)
actual_xx = array.groupby("x").quantile(0)
expected_xx = xr.DataArray(
- [[1, 11, 22], [4, 15, 24]], [("x", [1, 2]), ("y", [0, 0, 1])]
+ data=[[1, 11, 22], [4, 15, 24]],
+ coords={"x": [1, 2], "y": [0, 0, 1], "quantile": 0},
+ dims=("x", "y"),
)
assert_identical(expected_xx, actual_xx)
actual_yy = array.groupby("y").quantile(0)
expected_yy = xr.DataArray(
- [[1, 26], [2, 22], [3, 23], [4, 24], [5, 25]],
- [("x", [1, 1, 1, 2, 2]), ("y", [0, 1])],
+ data=[[1, 26], [2, 22], [3, 23], [4, 24], [5, 25]],
+ coords={"x": [1, 1, 1, 2, 2], "y": [0, 1], "quantile": 0},
+ dims=("x", "y"),
)
assert_identical(expected_yy, actual_yy)
@@ -180,14 +196,14 @@ def test_da_groupby_quantile():
x = [0, 1]
foo = xr.DataArray(
np.reshape(np.arange(365 * 2), (365, 2)),
- coords=dict(time=times, x=x),
+ coords={"time": times, "x": x},
dims=("time", "x"),
)
g = foo.groupby(foo.time.dt.month)
actual = g.quantile(0, dim=...)
expected = xr.DataArray(
- [
+ data=[
0.0,
62.0,
120.0,
@@ -201,12 +217,111 @@ def test_da_groupby_quantile():
610.0,
670.0,
],
- [("month", np.arange(1, 13))],
+ coords={"month": np.arange(1, 13), "quantile": 0},
+ dims="month",
)
assert_identical(expected, actual)
actual = g.quantile(0, dim="time")[:2]
- expected = xr.DataArray([[0.0, 1], [62.0, 63]], [("month", [1, 2]), ("x", [0, 1])])
+ expected = xr.DataArray(
+ data=[[0.0, 1], [62.0, 63]],
+ coords={"month": [1, 2], "x": [0, 1], "quantile": 0},
+ dims=("month", "x"),
+ )
+ assert_identical(expected, actual)
+
+
+def test_ds_groupby_quantile():
+ ds = xr.Dataset(
+ data_vars={"a": ("x", [1, 2, 3, 4, 5, 6])}, coords={"x": [1, 1, 1, 2, 2, 2]}
+ )
+
+ # Scalar quantile
+ expected = xr.Dataset(
+ data_vars={"a": ("x", [2, 5])}, coords={"quantile": 0.5, "x": [1, 2]}
+ )
+ actual = ds.groupby("x").quantile(0.5)
+ assert_identical(expected, actual)
+
+ # Vector quantile
+ expected = xr.Dataset(
+ data_vars={"a": (("x", "quantile"), [[1, 3], [4, 6]])},
+ coords={"x": [1, 2], "quantile": [0, 1]},
+ )
+ actual = ds.groupby("x").quantile([0, 1])
+ assert_identical(expected, actual)
+
+ # Multiple dimensions
+ ds = xr.Dataset(
+ data_vars={
+ "a": (
+ ("x", "y"),
+ [[1, 11, 26], [2, 12, 22], [3, 13, 23], [4, 16, 24], [5, 15, 25]],
+ )
+ },
+ coords={"x": [1, 1, 1, 2, 2], "y": [0, 0, 1]},
+ )
+
+ actual_x = ds.groupby("x").quantile(0, dim=...)
+ expected_x = xr.Dataset({"a": ("x", [1, 4])}, coords={"x": [1, 2], "quantile": 0})
+ assert_identical(expected_x, actual_x)
+
+ actual_y = ds.groupby("y").quantile(0, dim=...)
+ expected_y = xr.Dataset({"a": ("y", [1, 22])}, coords={"y": [0, 1], "quantile": 0})
+ assert_identical(expected_y, actual_y)
+
+ actual_xx = ds.groupby("x").quantile(0)
+ expected_xx = xr.Dataset(
+ {"a": (("x", "y"), [[1, 11, 22], [4, 15, 24]])},
+ coords={"x": [1, 2], "y": [0, 0, 1], "quantile": 0},
+ )
+ assert_identical(expected_xx, actual_xx)
+
+ actual_yy = ds.groupby("y").quantile(0)
+ expected_yy = xr.Dataset(
+ {"a": (("x", "y"), [[1, 26], [2, 22], [3, 23], [4, 24], [5, 25]])},
+ coords={"x": [1, 1, 1, 2, 2], "y": [0, 1], "quantile": 0},
+ ).transpose()
+ assert_identical(expected_yy, actual_yy)
+
+ times = pd.date_range("2000-01-01", periods=365)
+ x = [0, 1]
+ foo = xr.Dataset(
+ {"a": (("time", "x"), np.reshape(np.arange(365 * 2), (365, 2)))},
+ coords=dict(time=times, x=x),
+ )
+ g = foo.groupby(foo.time.dt.month)
+
+ actual = g.quantile(0, dim=...)
+ expected = xr.Dataset(
+ {
+ "a": (
+ "month",
+ [
+ 0.0,
+ 62.0,
+ 120.0,
+ 182.0,
+ 242.0,
+ 304.0,
+ 364.0,
+ 426.0,
+ 488.0,
+ 548.0,
+ 610.0,
+ 670.0,
+ ],
+ )
+ },
+ coords={"month": np.arange(1, 13), "quantile": 0},
+ )
+ assert_identical(expected, actual)
+
+ actual = g.quantile(0, dim="time").isel(month=slice(None, 2))
+ expected = xr.Dataset(
+ data_vars={"a": (("month", "x"), [[0.0, 1], [62.0, 63]])},
+ coords={"month": [1, 2], "x": [0, 1], "quantile": 0},
+ )
assert_identical(expected, actual)
|
[
{
"path": "doc/whats-new.rst",
"old_path": "a/doc/whats-new.rst",
"new_path": "b/doc/whats-new.rst",
"metadata": "diff --git a/doc/whats-new.rst b/doc/whats-new.rst\nindex ea3b012cc98..ad430b1bcfc 100644\n--- a/doc/whats-new.rst\n+++ b/doc/whats-new.rst\n@@ -76,6 +76,8 @@ New Features\n invoked. (:issue:`3378`, :pull:`3446`, :pull:`3515`)\n By `Deepak Cherian <https://github.com/dcherian>`_ and\n `Guido Imperiale <https://github.com/crusaderky>`_.\n+- Add the documented-but-missing :py:meth:`xarray.core.groupby.DatasetGroupBy.quantile`.\n+ (:issue:`3525`, :pull:`3527`). By `Justus Magin <https://github.com/keewis>`_.\n \n Bug fixes\n ~~~~~~~~~\n"
}
] |
0014
|
c0ef2f616e87e9f924425bcd373ac265f14203cb
|
[
"xarray/tests/test_groupby.py::test_ds_groupby_map_func_args",
"xarray/tests/test_groupby.py::test_groupby_repr[obj0-y]",
"xarray/tests/test_groupby.py::test_multi_index_groupby_sum",
"xarray/tests/test_groupby.py::test_groupby_repr[obj0-month]",
"xarray/tests/test_groupby.py::test_consolidate_slices",
"xarray/tests/test_groupby.py::test_groupby_grouping_errors",
"xarray/tests/test_groupby.py::test_groupby_da_datetime",
"xarray/tests/test_groupby.py::test_groupby_dims_property",
"xarray/tests/test_groupby.py::test_groupby_reduce_dimension_error",
"xarray/tests/test_groupby.py::test_da_groupby_empty",
"xarray/tests/test_groupby.py::test_groupby_bins_timeseries",
"xarray/tests/test_groupby.py::test_groupby_repr[obj0-x]",
"xarray/tests/test_groupby.py::test_groupby_repr[obj1-x]",
"xarray/tests/test_groupby.py::test_groupby_input_mutation",
"xarray/tests/test_groupby.py::test_groupby_repr[obj0-z]",
"xarray/tests/test_groupby.py::test_da_groupby_map_func_args",
"xarray/tests/test_groupby.py::test_da_groupby_assign_coords",
"xarray/tests/test_groupby.py::test_groupby_drops_nans",
"xarray/tests/test_groupby.py::test_groupby_duplicate_coordinate_labels",
"xarray/tests/test_groupby.py::test_groupby_repr[obj1-z]",
"xarray/tests/test_groupby.py::test_groupby_repr[obj1-month]",
"xarray/tests/test_groupby.py::test_groupby_repr_datetime[obj1]",
"xarray/tests/test_groupby.py::test_groupby_repr[obj1-y]",
"xarray/tests/test_groupby.py::test_multi_index_groupby_map",
"xarray/tests/test_groupby.py::test_groupby_repr_datetime[obj0]"
] |
[
"xarray/tests/test_groupby.py::test_da_groupby_quantile",
"xarray/tests/test_groupby.py::test_ds_groupby_quantile"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/whats-new.rst",
"old_path": "a/doc/whats-new.rst",
"new_path": "b/doc/whats-new.rst",
"metadata": "diff --git a/doc/whats-new.rst b/doc/whats-new.rst\nindex ea3b012cc98..ad430b1bcfc 100644\n--- a/doc/whats-new.rst\n+++ b/doc/whats-new.rst\n@@ -76,6 +76,8 @@ New Features\n invoked. (:issue:`<PRID>`, :pull:`<PRID>`, :pull:`<PRID>`)\n By `<NAME>`_ and\n <NAME>_.\n+- Add the documented-but-missing :py:meth:`xarray.core.groupby.DatasetGroupBy.quantile`.\n+ (:issue:`<PRID>`, :pull:`<PRID>`). By `<NAME>`_.\n \n Bug fixes\n ~~~~~~~~~\n"
}
] |
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index ea3b012cc98..ad430b1bcfc 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -76,6 +76,8 @@ New Features
invoked. (:issue:`<PRID>`, :pull:`<PRID>`, :pull:`<PRID>`)
By `<NAME>`_ and
<NAME>_.
+- Add the documented-but-missing :py:meth:`xarray.core.groupby.DatasetGroupBy.quantile`.
+ (:issue:`<PRID>`, :pull:`<PRID>`). By `<NAME>`_.
Bug fixes
~~~~~~~~~
|
pydata/xarray
|
pydata__xarray-3596
|
https://github.com/pydata/xarray/pull/3596
|
diff --git a/doc/api-hidden.rst b/doc/api-hidden.rst
index 437f53b1a91..cc9517a98ba 100644
--- a/doc/api-hidden.rst
+++ b/doc/api-hidden.rst
@@ -379,7 +379,6 @@
Variable.min
Variable.no_conflicts
Variable.notnull
- Variable.pad_with_fill_value
Variable.prod
Variable.quantile
Variable.rank
@@ -453,7 +452,6 @@
IndexVariable.min
IndexVariable.no_conflicts
IndexVariable.notnull
- IndexVariable.pad_with_fill_value
IndexVariable.prod
IndexVariable.quantile
IndexVariable.rank
diff --git a/doc/api.rst b/doc/api.rst
index 4492d882355..b3b6aa9139d 100644
--- a/doc/api.rst
+++ b/doc/api.rst
@@ -220,6 +220,7 @@ Reshaping and reorganizing
Dataset.to_stacked_array
Dataset.shift
Dataset.roll
+ Dataset.pad
Dataset.sortby
Dataset.broadcast_like
@@ -399,6 +400,7 @@ Reshaping and reorganizing
DataArray.to_unstacked_dataset
DataArray.shift
DataArray.roll
+ DataArray.pad
DataArray.sortby
DataArray.broadcast_like
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index 24120270444..fa71be23db9 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -125,6 +125,8 @@ Breaking changes
New Features
~~~~~~~~~~~~
+- Implement :py:meth:`DataArray.pad` and :py:meth:`Dataset.pad`. (:issue:`2605`, :pull:`3596`).
+ By `Mark Boer <https://github.com/mark-boer>`_.
- :py:meth:`DataArray.sel` and :py:meth:`Dataset.sel` now support :py:class:`pandas.CategoricalIndex`. (:issue:`3669`)
By `Keisuke Fujii <https://github.com/fujiisoup>`_.
- Support using an existing, opened h5netcdf ``File`` with
diff --git a/xarray/core/dask_array_compat.py b/xarray/core/dask_array_compat.py
index 05f750a1355..94c50d90e84 100644
--- a/xarray/core/dask_array_compat.py
+++ b/xarray/core/dask_array_compat.py
@@ -1,3 +1,4 @@
+import warnings
from distutils.version import LooseVersion
from typing import Iterable
@@ -99,6 +100,52 @@ def meta_from_array(x, ndim=None, dtype=None):
return meta
+def _validate_pad_output_shape(input_shape, pad_width, output_shape):
+ """ Validates the output shape of dask.array.pad, raising a RuntimeError if they do not match.
+ In the current versions of dask (2.2/2.4), dask.array.pad with mode='reflect' sometimes returns
+ an invalid shape.
+ """
+ isint = lambda i: isinstance(i, int)
+
+ if isint(pad_width):
+ pass
+ elif len(pad_width) == 2 and all(map(isint, pad_width)):
+ pad_width = sum(pad_width)
+ elif (
+ len(pad_width) == len(input_shape)
+ and all(map(lambda x: len(x) == 2, pad_width))
+ and all((isint(i) for p in pad_width for i in p))
+ ):
+ pad_width = np.sum(pad_width, axis=1)
+ else:
+ # unreachable: dask.array.pad should already have thrown an error
+ raise ValueError("Invalid value for `pad_width`")
+
+ if not np.array_equal(np.array(input_shape) + pad_width, output_shape):
+ raise RuntimeError(
+ "There seems to be something wrong with the shape of the output of dask.array.pad, "
+ "try upgrading Dask, use a different pad mode e.g. mode='constant' or first convert "
+ "your DataArray/Dataset to one backed by a numpy array by calling the `compute()` method."
+ "See: https://github.com/dask/dask/issues/5303"
+ )
+
+
+def pad(array, pad_width, mode="constant", **kwargs):
+ padded = da.pad(array, pad_width, mode=mode, **kwargs)
+ # workaround for inconsistency between numpy and dask: https://github.com/dask/dask/issues/5303
+ if mode == "mean" and issubclass(array.dtype.type, np.integer):
+ warnings.warn(
+ 'dask.array.pad(mode="mean") converts integers to floats. xarray converts '
+ "these floats back to integers to keep the interface consistent. There is a chance that "
+ "this introduces rounding errors. If you wish to keep the values as floats, first change "
+ "the dtype to a float before calling pad.",
+ UserWarning,
+ )
+ return da.round(padded).astype(array.dtype)
+ _validate_pad_output_shape(array.shape, pad_width, padded.shape)
+ return padded
+
+
if LooseVersion(dask_version) >= LooseVersion("2.8.1"):
median = da.median
else:
diff --git a/xarray/core/dataarray.py b/xarray/core/dataarray.py
index 4e80ef222c2..4d9993d7383 100644
--- a/xarray/core/dataarray.py
+++ b/xarray/core/dataarray.py
@@ -3239,6 +3239,174 @@ def map_blocks(
return map_blocks(func, self, args, kwargs)
+ def pad(
+ self,
+ pad_width: Mapping[Hashable, Union[int, Tuple[int, int]]] = None,
+ mode: str = "constant",
+ stat_length: Union[
+ int, Tuple[int, int], Mapping[Hashable, Tuple[int, int]]
+ ] = None,
+ constant_values: Union[
+ int, Tuple[int, int], Mapping[Hashable, Tuple[int, int]]
+ ] = None,
+ end_values: Union[
+ int, Tuple[int, int], Mapping[Hashable, Tuple[int, int]]
+ ] = None,
+ reflect_type: str = None,
+ **pad_width_kwargs: Any,
+ ) -> "DataArray":
+ """Pad this array along one or more dimensions.
+
+ .. warning::
+ This function is experimental and its behaviour is likely to change
+ especially regarding padding of dimension coordinates (or IndexVariables).
+
+ When using one of the modes ("edge", "reflect", "symmetric", "wrap"),
+ coordinates will be padded with the same mode, otherwise coordinates
+ are padded using the "constant" mode with fill_value dtypes.NA.
+
+ Parameters
+ ----------
+ pad_width : Mapping with the form of {dim: (pad_before, pad_after)}
+ Number of values padded along each dimension.
+ {dim: pad} is a shortcut for pad_before = pad_after = pad
+ mode : str
+ One of the following string values (taken from numpy docs)
+
+ 'constant' (default)
+ Pads with a constant value.
+ 'edge'
+ Pads with the edge values of array.
+ 'linear_ramp'
+ Pads with the linear ramp between end_value and the
+ array edge value.
+ 'maximum'
+ Pads with the maximum value of all or part of the
+ vector along each axis.
+ 'mean'
+ Pads with the mean value of all or part of the
+ vector along each axis.
+ 'median'
+ Pads with the median value of all or part of the
+ vector along each axis.
+ 'minimum'
+ Pads with the minimum value of all or part of the
+ vector along each axis.
+ 'reflect'
+ Pads with the reflection of the vector mirrored on
+ the first and last values of the vector along each
+ axis.
+ 'symmetric'
+ Pads with the reflection of the vector mirrored
+ along the edge of the array.
+ 'wrap'
+ Pads with the wrap of the vector along the axis.
+ The first values are used to pad the end and the
+ end values are used to pad the beginning.
+ stat_length : int, tuple or mapping of the form {dim: tuple}
+ Used in 'maximum', 'mean', 'median', and 'minimum'. Number of
+ values at edge of each axis used to calculate the statistic value.
+ {dim_1: (before_1, after_1), ... dim_N: (before_N, after_N)} unique
+ statistic lengths along each dimension.
+ ((before, after),) yields same before and after statistic lengths
+ for each dimension.
+ (stat_length,) or int is a shortcut for before = after = statistic
+ length for all axes.
+ Default is ``None``, to use the entire axis.
+ constant_values : scalar, tuple or mapping of the form {dim: tuple}
+ Used in 'constant'. The values to set the padded values for each
+ axis.
+ ``{dim_1: (before_1, after_1), ... dim_N: (before_N, after_N)}`` unique
+ pad constants along each dimension.
+ ``((before, after),)`` yields same before and after constants for each
+ dimension.
+ ``(constant,)`` or ``constant`` is a shortcut for ``before = after = constant`` for
+ all dimensions.
+ Default is 0.
+ end_values : scalar, tuple or mapping of the form {dim: tuple}
+ Used in 'linear_ramp'. The values used for the ending value of the
+ linear_ramp and that will form the edge of the padded array.
+ ``{dim_1: (before_1, after_1), ... dim_N: (before_N, after_N)}`` unique
+ end values along each dimension.
+ ``((before, after),)`` yields same before and after end values for each
+ axis.
+ ``(constant,)`` or ``constant`` is a shortcut for ``before = after = constant`` for
+ all axes.
+ Default is 0.
+ reflect_type : {'even', 'odd'}, optional
+ Used in 'reflect', and 'symmetric'. The 'even' style is the
+ default with an unaltered reflection around the edge value. For
+ the 'odd' style, the extended part of the array is created by
+ subtracting the reflected values from two times the edge value.
+ **pad_width_kwargs:
+ The keyword arguments form of ``pad_width``.
+ One of ``pad_width`` or ``pad_width_kwargs`` must be provided.
+
+ Returns
+ -------
+ padded : DataArray
+ DataArray with the padded coordinates and data.
+
+ See also
+ --------
+ DataArray.shift, DataArray.roll, DataArray.bfill, DataArray.ffill, numpy.pad, dask.array.pad
+
+ Notes
+ -----
+ By default when ``mode="constant"`` and ``constant_values=None``, integer types will be
+ promoted to ``float`` and padded with ``np.nan``. To avoid type promotion
+ specify ``constant_values=np.nan``
+
+ Examples
+ --------
+
+ >>> arr = xr.DataArray([5, 6, 7], coords=[("x", [0,1,2])])
+ >>> arr.pad(x=(1,2), constant_values=0)
+ <xarray.DataArray (x: 6)>
+ array([0, 5, 6, 7, 0, 0])
+ Coordinates:
+ * x (x) float64 nan 0.0 1.0 2.0 nan nan
+
+ >>> da = xr.DataArray([[0,1,2,3], [10,11,12,13]],
+ dims=["x", "y"],
+ coords={"x": [0,1], "y": [10, 20 ,30, 40], "z": ("x", [100, 200])}
+ )
+ >>> da.pad(x=1)
+ <xarray.DataArray (x: 4, y: 4)>
+ array([[nan, nan, nan, nan],
+ [ 0., 1., 2., 3.],
+ [10., 11., 12., 13.],
+ [nan, nan, nan, nan]])
+ Coordinates:
+ * x (x) float64 nan 0.0 1.0 nan
+ * y (y) int64 10 20 30 40
+ z (x) float64 nan 100.0 200.0 nan
+ >>> da.pad(x=1, constant_values=np.nan)
+ <xarray.DataArray (x: 4, y: 4)>
+ array([[-9223372036854775808, -9223372036854775808, -9223372036854775808,
+ -9223372036854775808],
+ [ 0, 1, 2,
+ 3],
+ [ 10, 11, 12,
+ 13],
+ [-9223372036854775808, -9223372036854775808, -9223372036854775808,
+ -9223372036854775808]])
+ Coordinates:
+ * x (x) float64 nan 0.0 1.0 nan
+ * y (y) int64 10 20 30 40
+ z (x) float64 nan 100.0 200.0 nan
+ """
+ ds = self._to_temp_dataset().pad(
+ pad_width=pad_width,
+ mode=mode,
+ stat_length=stat_length,
+ constant_values=constant_values,
+ end_values=end_values,
+ reflect_type=reflect_type,
+ **pad_width_kwargs,
+ )
+ return self._from_temp_dataset(ds)
+
# this needs to be at the end, or mypy will confuse with `str`
# https://mypy.readthedocs.io/en/latest/common_issues.html#dealing-with-conflicting-names
str = property(StringAccessor)
diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index 52940e98b27..937bebc2bc8 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -5699,5 +5699,171 @@ def map_blocks(
return map_blocks(func, self, args, kwargs)
+ def pad(
+ self,
+ pad_width: Mapping[Hashable, Union[int, Tuple[int, int]]] = None,
+ mode: str = "constant",
+ stat_length: Union[
+ int, Tuple[int, int], Mapping[Hashable, Tuple[int, int]]
+ ] = None,
+ constant_values: Union[
+ int, Tuple[int, int], Mapping[Hashable, Tuple[int, int]]
+ ] = None,
+ end_values: Union[
+ int, Tuple[int, int], Mapping[Hashable, Tuple[int, int]]
+ ] = None,
+ reflect_type: str = None,
+ **pad_width_kwargs: Any,
+ ) -> "Dataset":
+ """Pad this dataset along one or more dimensions.
+
+ .. warning::
+ This function is experimental and its behaviour is likely to change
+ especially regarding padding of dimension coordinates (or IndexVariables).
+
+ When using one of the modes ("edge", "reflect", "symmetric", "wrap"),
+ coordinates will be padded with the same mode, otherwise coordinates
+ are padded using the "constant" mode with fill_value dtypes.NA.
+
+ Parameters
+ ----------
+ pad_width : Mapping with the form of {dim: (pad_before, pad_after)}
+ Number of values padded along each dimension.
+ {dim: pad} is a shortcut for pad_before = pad_after = pad
+ mode : str
+ One of the following string values (taken from numpy docs).
+
+ 'constant' (default)
+ Pads with a constant value.
+ 'edge'
+ Pads with the edge values of array.
+ 'linear_ramp'
+ Pads with the linear ramp between end_value and the
+ array edge value.
+ 'maximum'
+ Pads with the maximum value of all or part of the
+ vector along each axis.
+ 'mean'
+ Pads with the mean value of all or part of the
+ vector along each axis.
+ 'median'
+ Pads with the median value of all or part of the
+ vector along each axis.
+ 'minimum'
+ Pads with the minimum value of all or part of the
+ vector along each axis.
+ 'reflect'
+ Pads with the reflection of the vector mirrored on
+ the first and last values of the vector along each
+ axis.
+ 'symmetric'
+ Pads with the reflection of the vector mirrored
+ along the edge of the array.
+ 'wrap'
+ Pads with the wrap of the vector along the axis.
+ The first values are used to pad the end and the
+ end values are used to pad the beginning.
+ stat_length : int, tuple or mapping of the form {dim: tuple}
+ Used in 'maximum', 'mean', 'median', and 'minimum'. Number of
+ values at edge of each axis used to calculate the statistic value.
+ {dim_1: (before_1, after_1), ... dim_N: (before_N, after_N)} unique
+ statistic lengths along each dimension.
+ ((before, after),) yields same before and after statistic lengths
+ for each dimension.
+ (stat_length,) or int is a shortcut for before = after = statistic
+ length for all axes.
+ Default is ``None``, to use the entire axis.
+ constant_values : scalar, tuple or mapping of the form {dim: tuple}
+ Used in 'constant'. The values to set the padded values for each
+ axis.
+ ``{dim_1: (before_1, after_1), ... dim_N: (before_N, after_N)}`` unique
+ pad constants along each dimension.
+ ``((before, after),)`` yields same before and after constants for each
+ dimension.
+ ``(constant,)`` or ``constant`` is a shortcut for ``before = after = constant`` for
+ all dimensions.
+ Default is 0.
+ end_values : scalar, tuple or mapping of the form {dim: tuple}
+ Used in 'linear_ramp'. The values used for the ending value of the
+ linear_ramp and that will form the edge of the padded array.
+ ``{dim_1: (before_1, after_1), ... dim_N: (before_N, after_N)}`` unique
+ end values along each dimension.
+ ``((before, after),)`` yields same before and after end values for each
+ axis.
+ ``(constant,)`` or ``constant`` is a shortcut for ``before = after = constant`` for
+ all axes.
+ Default is 0.
+ reflect_type : {'even', 'odd'}, optional
+ Used in 'reflect', and 'symmetric'. The 'even' style is the
+ default with an unaltered reflection around the edge value. For
+ the 'odd' style, the extended part of the array is created by
+ subtracting the reflected values from two times the edge value.
+ **pad_width_kwargs:
+ The keyword arguments form of ``pad_width``.
+ One of ``pad_width`` or ``pad_width_kwargs`` must be provided.
+
+ Returns
+ -------
+ padded : Dataset
+ Dataset with the padded coordinates and data.
+
+ See also
+ --------
+ Dataset.shift, Dataset.roll, Dataset.bfill, Dataset.ffill, numpy.pad, dask.array.pad
+
+ Notes
+ -----
+ By default when ``mode="constant"`` and ``constant_values=None``, integer types will be
+ promoted to ``float`` and padded with ``np.nan``. To avoid type promotion
+ specify ``constant_values=np.nan``
+
+ Examples
+ --------
+
+ >>> ds = xr.Dataset({'foo': ('x', range(5))})
+ >>> ds.pad(x=(1,2))
+ <xarray.Dataset>
+ Dimensions: (x: 8)
+ Dimensions without coordinates: x
+ Data variables:
+ foo (x) float64 nan 0.0 1.0 2.0 3.0 4.0 nan nan
+ """
+ pad_width = either_dict_or_kwargs(pad_width, pad_width_kwargs, "pad")
+
+ if mode in ("edge", "reflect", "symmetric", "wrap"):
+ coord_pad_mode = mode
+ coord_pad_options = {
+ "stat_length": stat_length,
+ "constant_values": constant_values,
+ "end_values": end_values,
+ "reflect_type": reflect_type,
+ }
+ else:
+ coord_pad_mode = "constant"
+ coord_pad_options = {}
+
+ variables = {}
+ for name, var in self.variables.items():
+ var_pad_width = {k: v for k, v in pad_width.items() if k in var.dims}
+ if not var_pad_width:
+ variables[name] = var
+ elif name in self.data_vars:
+ variables[name] = var.pad(
+ pad_width=var_pad_width,
+ mode=mode,
+ stat_length=stat_length,
+ constant_values=constant_values,
+ end_values=end_values,
+ reflect_type=reflect_type,
+ )
+ else:
+ variables[name] = var.pad(
+ pad_width=var_pad_width,
+ mode=coord_pad_mode,
+ **coord_pad_options, # type: ignore
+ )
+
+ return self._replace_vars_and_dims(variables)
+
ops.inject_all_ops_and_reduce_methods(Dataset, array_only=False)
diff --git a/xarray/core/duck_array_ops.py b/xarray/core/duck_array_ops.py
index 6d0abe9a6fc..ff2d0af63ed 100644
--- a/xarray/core/duck_array_ops.py
+++ b/xarray/core/duck_array_ops.py
@@ -114,7 +114,7 @@ def notnull(data):
isin = _dask_or_eager_func("isin", array_args=slice(2))
take = _dask_or_eager_func("take")
broadcast_to = _dask_or_eager_func("broadcast_to")
-pad = _dask_or_eager_func("pad")
+pad = _dask_or_eager_func("pad", dask_module=dask_array_compat)
_concatenate = _dask_or_eager_func("concatenate", list_of_args=True)
_stack = _dask_or_eager_func("stack", list_of_args=True)
diff --git a/xarray/core/rolling.py b/xarray/core/rolling.py
index 61178cfb15f..6e5cf187d5a 100644
--- a/xarray/core/rolling.py
+++ b/xarray/core/rolling.py
@@ -348,7 +348,7 @@ def _bottleneck_reduce(self, func, **kwargs):
else:
shift = (-self.window // 2) + 1
valid = (slice(None),) * axis + (slice(-shift, None),)
- padded = padded.pad_with_fill_value({self.dim: (0, -shift)})
+ padded = padded.pad({self.dim: (0, -shift)}, mode="constant")
if isinstance(padded.data, dask_array_type):
raise AssertionError("should not be reachable")
diff --git a/xarray/core/variable.py b/xarray/core/variable.py
index 62f9fde6a2e..ce27b118180 100644
--- a/xarray/core/variable.py
+++ b/xarray/core/variable.py
@@ -1,11 +1,12 @@
import copy
import functools
import itertools
+import numbers
import warnings
from collections import defaultdict
from datetime import timedelta
from distutils.version import LooseVersion
-from typing import Any, Dict, Hashable, Mapping, TypeVar, Union
+from typing import Any, Dict, Hashable, Mapping, Tuple, TypeVar, Union
import numpy as np
import pandas as pd
@@ -32,12 +33,6 @@
infix_dims,
)
-try:
- import dask.array as da
-except ImportError:
- pass
-
-
NON_NUMPY_SUPPORTED_ARRAY_TYPES = (
indexing.ExplicitlyIndexed,
pd.Index,
@@ -1150,66 +1145,114 @@ def shift(self, shifts=None, fill_value=dtypes.NA, **shifts_kwargs):
result = result._shift_one_dim(dim, count, fill_value=fill_value)
return result
- def pad_with_fill_value(
- self, pad_widths=None, fill_value=dtypes.NA, **pad_widths_kwargs
+ def _pad_options_dim_to_index(
+ self,
+ pad_option: Mapping[Hashable, Union[int, Tuple[int, int]]],
+ fill_with_shape=False,
+ ):
+ if fill_with_shape:
+ return [
+ (n, n) if d not in pad_option else pad_option[d]
+ for d, n in zip(self.dims, self.data.shape)
+ ]
+ return [(0, 0) if d not in pad_option else pad_option[d] for d in self.dims]
+
+ def pad(
+ self,
+ pad_width: Mapping[Hashable, Union[int, Tuple[int, int]]] = None,
+ mode: str = "constant",
+ stat_length: Union[
+ int, Tuple[int, int], Mapping[Hashable, Tuple[int, int]]
+ ] = None,
+ constant_values: Union[
+ int, Tuple[int, int], Mapping[Hashable, Tuple[int, int]]
+ ] = None,
+ end_values: Union[
+ int, Tuple[int, int], Mapping[Hashable, Tuple[int, int]]
+ ] = None,
+ reflect_type: str = None,
+ **pad_width_kwargs: Any,
):
"""
- Return a new Variable with paddings.
+ Return a new Variable with padded data.
Parameters
----------
- pad_width: Mapping of the form {dim: (before, after)}
- Number of values padded to the edges of each dimension.
- **pad_widths_kwargs:
- Keyword argument for pad_widths
+ pad_width: Mapping with the form of {dim: (pad_before, pad_after)}
+ Number of values padded along each dimension.
+ {dim: pad} is a shortcut for pad_before = pad_after = pad
+ mode: (str)
+ See numpy / Dask docs
+ stat_length : int, tuple or mapping of the form {dim: tuple}
+ Used in 'maximum', 'mean', 'median', and 'minimum'. Number of
+ values at edge of each axis used to calculate the statistic value.
+ constant_values : scalar, tuple or mapping of the form {dim: tuple}
+ Used in 'constant'. The values to set the padded values for each
+ axis.
+ end_values : scalar, tuple or mapping of the form {dim: tuple}
+ Used in 'linear_ramp'. The values used for the ending value of the
+ linear_ramp and that will form the edge of the padded array.
+ reflect_type : {'even', 'odd'}, optional
+ Used in 'reflect', and 'symmetric'. The 'even' style is the
+ default with an unaltered reflection around the edge value. For
+ the 'odd' style, the extended part of the array is created by
+ subtracting the reflected values from two times the edge value.
+ **pad_width_kwargs:
+ One of pad_width or pad_width_kwargs must be provided.
+
+ Returns
+ -------
+ padded : Variable
+ Variable with the same dimensions and attributes but padded data.
"""
- pad_widths = either_dict_or_kwargs(pad_widths, pad_widths_kwargs, "pad")
+ pad_width = either_dict_or_kwargs(pad_width, pad_width_kwargs, "pad")
- if fill_value is dtypes.NA:
- dtype, fill_value = dtypes.maybe_promote(self.dtype)
+ # change default behaviour of pad with mode constant
+ if mode == "constant" and (
+ constant_values is None or constant_values is dtypes.NA
+ ):
+ dtype, constant_values = dtypes.maybe_promote(self.dtype)
else:
dtype = self.dtype
- if isinstance(self.data, dask_array_type):
- array = self.data
-
- # Dask does not yet support pad. We manually implement it.
- # https://github.com/dask/dask/issues/1926
- for d, pad in pad_widths.items():
- axis = self.get_axis_num(d)
- before_shape = list(array.shape)
- before_shape[axis] = pad[0]
- before_chunks = list(array.chunks)
- before_chunks[axis] = (pad[0],)
- after_shape = list(array.shape)
- after_shape[axis] = pad[1]
- after_chunks = list(array.chunks)
- after_chunks[axis] = (pad[1],)
-
- arrays = []
- if pad[0] > 0:
- arrays.append(
- da.full(
- before_shape, fill_value, dtype=dtype, chunks=before_chunks
- )
- )
- arrays.append(array)
- if pad[1] > 0:
- arrays.append(
- da.full(
- after_shape, fill_value, dtype=dtype, chunks=after_chunks
- )
- )
- if len(arrays) > 1:
- array = da.concatenate(arrays, axis=axis)
- else:
- pads = [(0, 0) if d not in pad_widths else pad_widths[d] for d in self.dims]
- array = np.pad(
- self.data.astype(dtype, copy=False),
- pads,
- mode="constant",
- constant_values=fill_value,
+ # create pad_options_kwargs, numpy requires only relevant kwargs to be nonempty
+ if isinstance(stat_length, dict):
+ stat_length = self._pad_options_dim_to_index(
+ stat_length, fill_with_shape=True
)
+ if isinstance(constant_values, dict):
+ constant_values = self._pad_options_dim_to_index(constant_values)
+ if isinstance(end_values, dict):
+ end_values = self._pad_options_dim_to_index(end_values)
+
+ # workaround for bug in Dask's default value of stat_length https://github.com/dask/dask/issues/5303
+ if stat_length is None and mode in ["maximum", "mean", "median", "minimum"]:
+ stat_length = [(n, n) for n in self.data.shape] # type: ignore
+
+ # change integer values to a tuple of two of those values and change pad_width to index
+ for k, v in pad_width.items():
+ if isinstance(v, numbers.Number):
+ pad_width[k] = (v, v)
+ pad_width_by_index = self._pad_options_dim_to_index(pad_width)
+
+ # create pad_options_kwargs, numpy/dask requires only relevant kwargs to be nonempty
+ pad_option_kwargs = {}
+ if stat_length is not None:
+ pad_option_kwargs["stat_length"] = stat_length
+ if constant_values is not None:
+ pad_option_kwargs["constant_values"] = constant_values
+ if end_values is not None:
+ pad_option_kwargs["end_values"] = end_values
+ if reflect_type is not None:
+ pad_option_kwargs["reflect_type"] = reflect_type # type: ignore
+
+ array = duck_array_ops.pad(
+ self.data.astype(dtype, copy=False),
+ pad_width_by_index,
+ mode=mode,
+ **pad_option_kwargs,
+ )
+
return type(self)(self.dims, array)
def _roll_one_dim(self, dim, count):
@@ -1926,10 +1969,10 @@ def _coarsen_reshape(self, windows, boundary, side):
if pad < 0:
pad += window
if side[d] == "left":
- pad_widths = {d: (0, pad)}
+ pad_width = {d: (0, pad)}
else:
- pad_widths = {d: (pad, 0)}
- variable = variable.pad_with_fill_value(pad_widths)
+ pad_width = {d: (pad, 0)}
+ variable = variable.pad(pad_width, mode="constant")
else:
raise TypeError(
"{} is invalid for boundary. Valid option is 'exact', "
|
diff --git a/xarray/tests/test_dataarray.py b/xarray/tests/test_dataarray.py
index b8a9c5edaf9..b63ff91f28e 100644
--- a/xarray/tests/test_dataarray.py
+++ b/xarray/tests/test_dataarray.py
@@ -4177,6 +4177,113 @@ def test_rank(self):
y = DataArray([0.75, 0.25, np.nan, 0.5, 1.0], dims=("z",))
assert_equal(y.rank("z", pct=True), y)
+ def test_pad_constant(self):
+ ar = DataArray(np.arange(3 * 4 * 5).reshape(3, 4, 5))
+ actual = ar.pad(dim_0=(1, 3))
+ expected = DataArray(
+ np.pad(
+ np.arange(3 * 4 * 5).reshape(3, 4, 5).astype(np.float32),
+ mode="constant",
+ pad_width=((1, 3), (0, 0), (0, 0)),
+ constant_values=np.nan,
+ )
+ )
+ assert actual.shape == (7, 4, 5)
+ assert_identical(actual, expected)
+
+ def test_pad_coords(self):
+ ar = DataArray(
+ np.arange(3 * 4 * 5).reshape(3, 4, 5),
+ [("x", np.arange(3)), ("y", np.arange(4)), ("z", np.arange(5))],
+ )
+ actual = ar.pad(x=(1, 3), constant_values=1)
+ expected = DataArray(
+ np.pad(
+ np.arange(3 * 4 * 5).reshape(3, 4, 5),
+ mode="constant",
+ pad_width=((1, 3), (0, 0), (0, 0)),
+ constant_values=1,
+ ),
+ [
+ (
+ "x",
+ np.pad(
+ np.arange(3).astype(np.float32),
+ mode="constant",
+ pad_width=(1, 3),
+ constant_values=np.nan,
+ ),
+ ),
+ ("y", np.arange(4)),
+ ("z", np.arange(5)),
+ ],
+ )
+ assert_identical(actual, expected)
+
+ @pytest.mark.parametrize("mode", ("minimum", "maximum", "mean", "median"))
+ @pytest.mark.parametrize(
+ "stat_length", (None, 3, (1, 3), {"dim_0": (2, 1), "dim_2": (4, 2)})
+ )
+ def test_pad_stat_length(self, mode, stat_length):
+ ar = DataArray(np.arange(3 * 4 * 5).reshape(3, 4, 5))
+ actual = ar.pad(dim_0=(1, 3), dim_2=(2, 2), mode=mode, stat_length=stat_length)
+ if isinstance(stat_length, dict):
+ stat_length = (stat_length["dim_0"], (4, 4), stat_length["dim_2"])
+ expected = DataArray(
+ np.pad(
+ np.arange(3 * 4 * 5).reshape(3, 4, 5),
+ pad_width=((1, 3), (0, 0), (2, 2)),
+ mode=mode,
+ stat_length=stat_length,
+ )
+ )
+ assert actual.shape == (7, 4, 9)
+ assert_identical(actual, expected)
+
+ @pytest.mark.parametrize(
+ "end_values", (None, 3, (3, 5), {"dim_0": (2, 1), "dim_2": (4, 2)})
+ )
+ def test_pad_linear_ramp(self, end_values):
+ ar = DataArray(np.arange(3 * 4 * 5).reshape(3, 4, 5))
+ actual = ar.pad(
+ dim_0=(1, 3), dim_2=(2, 2), mode="linear_ramp", end_values=end_values
+ )
+ if end_values is None:
+ end_values = 0
+ elif isinstance(end_values, dict):
+ end_values = (end_values["dim_0"], (4, 4), end_values["dim_2"])
+ expected = DataArray(
+ np.pad(
+ np.arange(3 * 4 * 5).reshape(3, 4, 5),
+ pad_width=((1, 3), (0, 0), (2, 2)),
+ mode="linear_ramp",
+ end_values=end_values,
+ )
+ )
+ assert actual.shape == (7, 4, 9)
+ assert_identical(actual, expected)
+
+ @pytest.mark.parametrize("mode", ("reflect", "symmetric"))
+ @pytest.mark.parametrize("reflect_type", (None, "even", "odd"))
+ def test_pad_reflect(self, mode, reflect_type):
+
+ ar = DataArray(np.arange(3 * 4 * 5).reshape(3, 4, 5))
+ actual = ar.pad(
+ dim_0=(1, 3), dim_2=(2, 2), mode=mode, reflect_type=reflect_type
+ )
+ np_kwargs = {
+ "array": np.arange(3 * 4 * 5).reshape(3, 4, 5),
+ "pad_width": ((1, 3), (0, 0), (2, 2)),
+ "mode": mode,
+ }
+ # numpy does not support reflect_type=None
+ if reflect_type is not None:
+ np_kwargs["reflect_type"] = reflect_type
+ expected = DataArray(np.pad(**np_kwargs))
+
+ assert actual.shape == (7, 4, 9)
+ assert_identical(actual, expected)
+
@pytest.fixture(params=[1])
def da(request):
diff --git a/xarray/tests/test_dataset.py b/xarray/tests/test_dataset.py
index 44ffafb23b1..ab684434aa6 100644
--- a/xarray/tests/test_dataset.py
+++ b/xarray/tests/test_dataset.py
@@ -5457,6 +5457,19 @@ def test_ipython_key_completion(self):
ds.data_vars[item] # should not raise
assert sorted(actual) == sorted(expected)
+ def test_pad(self):
+ ds = create_test_data(seed=1)
+ padded = ds.pad(dim2=(1, 1), constant_values=42)
+
+ assert padded["dim2"].shape == (11,)
+ assert padded["var1"].shape == (8, 11)
+ assert padded["var2"].shape == (8, 11)
+ assert padded["var3"].shape == (10, 8)
+ assert dict(padded.dims) == {"dim1": 8, "dim2": 11, "dim3": 10, "time": 20}
+
+ np.testing.assert_equal(padded["var1"].isel(dim2=[0, -1]).data, 42)
+ np.testing.assert_equal(padded["dim2"][[0, -1]].data, np.nan)
+
# Py.test tests
diff --git a/xarray/tests/test_sparse.py b/xarray/tests/test_sparse.py
index 21a212c29b3..09ab1be9af9 100644
--- a/xarray/tests/test_sparse.py
+++ b/xarray/tests/test_sparse.py
@@ -175,7 +175,7 @@ def test_variable_property(prop):
marks=xfail(reason="mixed sparse-dense operation"),
),
param(
- do("pad_with_fill_value", pad_widths={"x": (1, 1)}, fill_value=5),
+ do("pad", mode="constant", pad_widths={"x": (1, 1)}, fill_value=5),
True,
marks=xfail(reason="Missing implementation for np.pad"),
),
diff --git a/xarray/tests/test_units.py b/xarray/tests/test_units.py
index 9f63ebb1d42..bc784c6adc2 100644
--- a/xarray/tests/test_units.py
+++ b/xarray/tests/test_units.py
@@ -9,7 +9,7 @@
from xarray.core import formatting
from xarray.core.npcompat import IS_NEP18_ACTIVE
-from .test_variable import VariableSubclassobjects
+from .test_variable import _PAD_XR_NP_ARGS, VariableSubclassobjects
pint = pytest.importorskip("pint")
DimensionalityError = pint.errors.DimensionalityError
@@ -2032,42 +2032,32 @@ def test_no_conflicts(self, unit, dtype):
assert expected == actual
- def test_pad(self, dtype):
+ @pytest.mark.parametrize("xr_arg, np_arg", _PAD_XR_NP_ARGS)
+ def test_pad_constant_values(self, dtype, xr_arg, np_arg):
data = np.arange(4 * 3 * 2).reshape(4, 3, 2).astype(dtype) * unit_registry.m
v = xr.Variable(["x", "y", "z"], data)
- xr_args = [{"x": (2, 1)}, {"y": (0, 3)}, {"x": (3, 1), "z": (2, 0)}]
- np_args = [
- ((2, 1), (0, 0), (0, 0)),
- ((0, 0), (0, 3), (0, 0)),
- ((3, 1), (0, 0), (2, 0)),
- ]
- for xr_arg, np_arg in zip(xr_args, np_args):
- actual = v.pad_with_fill_value(**xr_arg)
- expected = xr.Variable(
- v.dims,
- np.pad(
- v.data.astype(float),
- np_arg,
- mode="constant",
- constant_values=np.nan,
- ),
- )
- xr.testing.assert_identical(expected, actual)
- assert_units_equal(expected, actual)
- assert isinstance(actual._data, type(v._data))
+ actual = v.pad(**xr_arg, mode="constant")
+ expected = xr.Variable(
+ v.dims,
+ np.pad(
+ v.data.astype(float), np_arg, mode="constant", constant_values=np.nan,
+ ),
+ )
+ xr.testing.assert_identical(expected, actual)
+ assert_units_equal(expected, actual)
+ assert isinstance(actual._data, type(v._data))
# for the boolean array, we pad False
data = np.full_like(data, False, dtype=bool).reshape(4, 3, 2)
v = xr.Variable(["x", "y", "z"], data)
- for xr_arg, np_arg in zip(xr_args, np_args):
- actual = v.pad_with_fill_value(fill_value=data.flat[0], **xr_arg)
- expected = xr.Variable(
- v.dims,
- np.pad(v.data, np_arg, mode="constant", constant_values=v.data.flat[0]),
- )
- xr.testing.assert_identical(actual, expected)
- assert_units_equal(expected, actual)
+ actual = v.pad(**xr_arg, mode="constant", constant_values=data.flat[0])
+ expected = xr.Variable(
+ v.dims,
+ np.pad(v.data, np_arg, mode="constant", constant_values=v.data.flat[0]),
+ )
+ xr.testing.assert_identical(actual, expected)
+ assert_units_equal(expected, actual)
@pytest.mark.parametrize(
"unit,error",
@@ -2089,16 +2079,16 @@ def test_pad(self, dtype):
pytest.param(unit_registry.m, None, id="identical_unit"),
),
)
- def test_pad_with_fill_value(self, unit, error, dtype):
+ def test_pad_unit_constant_value(self, unit, error, dtype):
array = np.linspace(0, 5, 3 * 10).reshape(3, 10).astype(dtype) * unit_registry.m
variable = xr.Variable(("x", "y"), array)
fill_value = -100 * unit
- func = method("pad_with_fill_value", x=(2, 3), y=(1, 4))
+ func = method("pad", mode="constant", x=(2, 3), y=(1, 4))
if error is not None:
with pytest.raises(error):
- func(variable, fill_value=fill_value)
+ func(variable, constant_values=fill_value)
return
@@ -2106,11 +2096,11 @@ def test_pad_with_fill_value(self, unit, error, dtype):
expected = attach_units(
func(
strip_units(variable),
- fill_value=strip_units(convert_units(fill_value, units)),
+ constant_values=strip_units(convert_units(fill_value, units)),
),
units,
)
- actual = func(variable, fill_value=fill_value)
+ actual = func(variable, constant_values=fill_value)
assert_units_equal(expected, actual)
xr.testing.assert_identical(expected, actual)
diff --git a/xarray/tests/test_variable.py b/xarray/tests/test_variable.py
index c86ecd0121f..428ad9280e2 100644
--- a/xarray/tests/test_variable.py
+++ b/xarray/tests/test_variable.py
@@ -38,6 +38,14 @@
source_ndarray,
)
+_PAD_XR_NP_ARGS = [
+ [{"x": (2, 1)}, ((2, 1), (0, 0), (0, 0))],
+ [{"x": 1}, ((1, 1), (0, 0), (0, 0))],
+ [{"y": (0, 3)}, ((0, 0), (0, 3), (0, 0))],
+ [{"x": (3, 1), "z": (2, 0)}, ((3, 1), (0, 0), (2, 0))],
+ [{"x": (3, 1), "z": 2}, ((3, 1), (0, 0), (2, 2))],
+]
+
class VariableSubclassobjects:
def test_properties(self):
@@ -785,36 +793,65 @@ def test_getitem_error(self):
with raises_regex(IndexError, "Dimensions of indexers mis"):
v[:, ind]
- def test_pad(self):
+ @pytest.mark.parametrize(
+ "mode",
+ [
+ "mean",
+ pytest.param(
+ "median",
+ marks=pytest.mark.xfail(reason="median is not implemented by Dask"),
+ ),
+ pytest.param(
+ "reflect", marks=pytest.mark.xfail(reason="dask.array.pad bug")
+ ),
+ "edge",
+ pytest.param(
+ "linear_ramp",
+ marks=pytest.mark.xfail(
+ reason="pint bug: https://github.com/hgrecco/pint/issues/1026"
+ ),
+ ),
+ "maximum",
+ "minimum",
+ "symmetric",
+ "wrap",
+ ],
+ )
+ @pytest.mark.parametrize("xr_arg, np_arg", _PAD_XR_NP_ARGS)
+ def test_pad(self, mode, xr_arg, np_arg):
data = np.arange(4 * 3 * 2).reshape(4, 3, 2)
v = self.cls(["x", "y", "z"], data)
- xr_args = [{"x": (2, 1)}, {"y": (0, 3)}, {"x": (3, 1), "z": (2, 0)}]
- np_args = [
- ((2, 1), (0, 0), (0, 0)),
- ((0, 0), (0, 3), (0, 0)),
- ((3, 1), (0, 0), (2, 0)),
- ]
- for xr_arg, np_arg in zip(xr_args, np_args):
- actual = v.pad_with_fill_value(**xr_arg)
- expected = np.pad(
- np.array(v.data.astype(float)),
- np_arg,
- mode="constant",
- constant_values=np.nan,
- )
- assert_array_equal(actual, expected)
- assert isinstance(actual._data, type(v._data))
+ actual = v.pad(mode=mode, **xr_arg)
+ expected = np.pad(data, np_arg, mode=mode)
+
+ assert_array_equal(actual, expected)
+ assert isinstance(actual._data, type(v._data))
+
+ @pytest.mark.parametrize("xr_arg, np_arg", _PAD_XR_NP_ARGS)
+ def test_pad_constant_values(self, xr_arg, np_arg):
+ data = np.arange(4 * 3 * 2).reshape(4, 3, 2)
+ v = self.cls(["x", "y", "z"], data)
+
+ actual = v.pad(**xr_arg)
+ expected = np.pad(
+ np.array(v.data.astype(float)),
+ np_arg,
+ mode="constant",
+ constant_values=np.nan,
+ )
+ assert_array_equal(actual, expected)
+ assert isinstance(actual._data, type(v._data))
# for the boolean array, we pad False
data = np.full_like(data, False, dtype=bool).reshape(4, 3, 2)
v = self.cls(["x", "y", "z"], data)
- for xr_arg, np_arg in zip(xr_args, np_args):
- actual = v.pad_with_fill_value(fill_value=False, **xr_arg)
- expected = np.pad(
- np.array(v.data), np_arg, mode="constant", constant_values=False
- )
- assert_array_equal(actual, expected)
+
+ actual = v.pad(mode="constant", constant_values=False, **xr_arg)
+ expected = np.pad(
+ np.array(v.data), np_arg, mode="constant", constant_values=False
+ )
+ assert_array_equal(actual, expected)
def test_rolling_window(self):
# Just a working test. See test_nputils for the algorithm validation
@@ -2054,8 +2091,28 @@ def test_getitem_uint(self):
super().test_getitem_fancy()
@pytest.mark.xfail
- def test_pad(self):
- super().test_rolling_window()
+ @pytest.mark.parametrize(
+ "mode",
+ [
+ "mean",
+ "median",
+ "reflect",
+ "edge",
+ "linear_ramp",
+ "maximum",
+ "minimum",
+ "symmetric",
+ "wrap",
+ ],
+ )
+ @pytest.mark.parametrize("xr_arg, np_arg", _PAD_XR_NP_ARGS)
+ def test_pad(self, mode, xr_arg, np_arg):
+ super().test_pad(mode, xr_arg, np_arg)
+
+ @pytest.mark.xfail
+ @pytest.mark.parametrize("xr_arg, np_arg", _PAD_XR_NP_ARGS)
+ def test_pad_constant_values(self, xr_arg, np_arg):
+ super().test_pad_constant_values(xr_arg, np_arg)
@pytest.mark.xfail
def test_rolling_window(self):
|
[
{
"path": "doc/api-hidden.rst",
"old_path": "a/doc/api-hidden.rst",
"new_path": "b/doc/api-hidden.rst",
"metadata": "diff --git a/doc/api-hidden.rst b/doc/api-hidden.rst\nindex 437f53b1a91..cc9517a98ba 100644\n--- a/doc/api-hidden.rst\n+++ b/doc/api-hidden.rst\n@@ -379,7 +379,6 @@\n Variable.min\n Variable.no_conflicts\n Variable.notnull\n- Variable.pad_with_fill_value\n Variable.prod\n Variable.quantile\n Variable.rank\n@@ -453,7 +452,6 @@\n IndexVariable.min\n IndexVariable.no_conflicts\n IndexVariable.notnull\n- IndexVariable.pad_with_fill_value\n IndexVariable.prod\n IndexVariable.quantile\n IndexVariable.rank\n"
},
{
"path": "doc/api.rst",
"old_path": "a/doc/api.rst",
"new_path": "b/doc/api.rst",
"metadata": "diff --git a/doc/api.rst b/doc/api.rst\nindex 4492d882355..b3b6aa9139d 100644\n--- a/doc/api.rst\n+++ b/doc/api.rst\n@@ -220,6 +220,7 @@ Reshaping and reorganizing\n Dataset.to_stacked_array\n Dataset.shift\n Dataset.roll\n+ Dataset.pad\n Dataset.sortby\n Dataset.broadcast_like\n \n@@ -399,6 +400,7 @@ Reshaping and reorganizing\n DataArray.to_unstacked_dataset\n DataArray.shift\n DataArray.roll\n+ DataArray.pad\n DataArray.sortby\n DataArray.broadcast_like\n \n"
},
{
"path": "doc/whats-new.rst",
"old_path": "a/doc/whats-new.rst",
"new_path": "b/doc/whats-new.rst",
"metadata": "diff --git a/doc/whats-new.rst b/doc/whats-new.rst\nindex 24120270444..fa71be23db9 100644\n--- a/doc/whats-new.rst\n+++ b/doc/whats-new.rst\n@@ -125,6 +125,8 @@ Breaking changes\n \n New Features\n ~~~~~~~~~~~~\n+- Implement :py:meth:`DataArray.pad` and :py:meth:`Dataset.pad`. (:issue:`2605`, :pull:`3596`).\n+ By `Mark Boer <https://github.com/mark-boer>`_.\n - :py:meth:`DataArray.sel` and :py:meth:`Dataset.sel` now support :py:class:`pandas.CategoricalIndex`. (:issue:`3669`)\n By `Keisuke Fujii <https://github.com/fujiisoup>`_.\n - Support using an existing, opened h5netcdf ``File`` with\n"
}
] |
0015
|
9fbb4170c1732fe2f3cd57b2b96d770a5bac50ed
|
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"xarray/tests/test_variable.py::TestVariable::test_reduce_keepdims",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-3-2-False-2]",
"xarray/tests/test_variable.py::TestIndexVariable::test_concat_multiindex",
"xarray/tests/test_variable.py::TestIndexVariable::test_encoding_preserved",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-1-None-False-1]",
"xarray/tests/test_variable.py::TestIndexVariable::test_getitem_1d",
"xarray/tests/test_dataset.py::TestDataset::test_dataset_transpose",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-4-1-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-2-3-True-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_reset_coords",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-4-2-True-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-3-1-False-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-2-2-True-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-3-None-False-1]",
"xarray/tests/test_dataset.py::TestDataset::test_groupby_math",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-2-2-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_pandas_compat[4-1-False]",
"xarray/tests/test_dataarray.py::TestDataArray::test_broadcast_arrays_nocopy",
"xarray/tests/test_dataarray.py::TestDataArray::test_inplace_math_automatic_alignment",
"xarray/tests/test_dataset.py::test_dataset_constructor_aligns_to_explicit_coords[coords1-unaligned_coords8]",
"xarray/tests/test_dataarray.py::TestDataArray::test_swap_dims",
"xarray/tests/test_dataarray.py::TestDataArray::test_loc_assign",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[sum-1-3-False]",
"xarray/tests/test_dataarray.py::TestDataArray::test_expand_dims_error",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-2-None-True-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-3-3-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-1-None-True-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-1-1-True-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_align_without_indexes_errors",
"xarray/tests/test_dataarray.py::test_rolling_wrapped_bottleneck[1-1-None-min]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-2-1-False]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-2-1-False-2]",
"xarray/tests/test_dataset.py::test_coarsen[1-pad-right-False]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-1-True-mean]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-1-None-sum]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-2-3-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-2-None-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[median-4-3-True-1]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-None-True-std]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-3-None-True-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[min-1-None-True-1]"
] |
[
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg0-np_arg0-mean]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg0-np_arg0-wrap]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg2-np_arg2-minimum]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_stat_length[3-mean]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg4-np_arg4-mean]",
"xarray/tests/test_variable.py::TestVariable::test_pad_constant_values[xr_arg0-np_arg0]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg1-np_arg1-edge]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_reflect[even-symmetric]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_reflect[odd-symmetric]",
"xarray/tests/test_variable.py::TestVariable::test_pad_constant_values[xr_arg1-np_arg1]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg4-np_arg4-maximum]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg4-np_arg4-symmetric]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_stat_length[3-minimum]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg2-np_arg2-mean]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg1-np_arg1-wrap]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_stat_length[None-minimum]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg0-np_arg0-minimum]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_stat_length[stat_length3-maximum]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_stat_length[3-maximum]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg2-np_arg2-maximum]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg1-np_arg1-symmetric]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_coords",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg0-np_arg0-maximum]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_linear_ramp[end_values3]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg1-np_arg1-minimum]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_stat_length[None-maximum]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg4-np_arg4-wrap]",
"xarray/tests/test_variable.py::TestVariable::test_pad_constant_values[xr_arg4-np_arg4]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg2-np_arg2-wrap]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_reflect[None-reflect]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_linear_ramp[3]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_stat_length[None-median]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_stat_length[stat_length3-minimum]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg0-np_arg0-edge]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_constant",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_linear_ramp[end_values2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_stat_length[stat_length2-maximum]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg2-np_arg2-symmetric]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_stat_length[None-mean]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_linear_ramp[None]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg3-np_arg3-symmetric]",
"xarray/tests/test_dataset.py::TestDataset::test_pad",
"xarray/tests/test_variable.py::TestVariable::test_pad_constant_values[xr_arg2-np_arg2]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg3-np_arg3-wrap]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg3-np_arg3-edge]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg3-np_arg3-minimum]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_reflect[None-symmetric]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg1-np_arg1-mean]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_reflect[even-reflect]",
"xarray/tests/test_variable.py::TestVariable::test_pad_constant_values[xr_arg3-np_arg3]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg0-np_arg0-symmetric]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg3-np_arg3-mean]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_stat_length[stat_length3-median]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_stat_length[stat_length3-mean]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg2-np_arg2-edge]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg4-np_arg4-edge]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_stat_length[3-median]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_stat_length[stat_length2-median]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_stat_length[stat_length2-minimum]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg1-np_arg1-maximum]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_stat_length[stat_length2-mean]",
"xarray/tests/test_dataarray.py::TestDataArray::test_pad_reflect[odd-reflect]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg4-np_arg4-minimum]",
"xarray/tests/test_variable.py::TestVariable::test_pad[xr_arg3-np_arg3-maximum]"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": [
{
"type": "field",
"name": "constant_values"
},
{
"type": "field",
"name": "pad_width"
},
{
"type": "field",
"name": "pad_width"
},
{
"type": "field",
"name": "stat_length"
},
{
"type": "field",
"name": "mode"
},
{
"type": "field",
"name": "pad_width"
},
{
"type": "field",
"name": "end_values"
},
{
"type": "field",
"name": "pad_width"
},
{
"type": "field",
"name": "constant_values"
},
{
"type": "field",
"name": "reflect_type"
},
{
"type": "field",
"name": "mode"
},
{
"type": "field",
"name": "mode"
},
{
"type": "field",
"name": "padded"
},
{
"type": "field",
"name": "reflect_type"
},
{
"type": "field",
"name": "end_values"
},
{
"type": "field",
"name": "stat_length"
},
{
"type": "field",
"name": "end_values"
},
{
"type": "field",
"name": "stat_length"
},
{
"type": "field",
"name": "reflect_type"
}
]
}
|
[
{
"path": "doc/api-hidden.rst",
"old_path": "a/doc/api-hidden.rst",
"new_path": "b/doc/api-hidden.rst",
"metadata": "diff --git a/doc/api-hidden.rst b/doc/api-hidden.rst\nindex 437f53b1a91..cc9517a98ba 100644\n--- a/doc/api-hidden.rst\n+++ b/doc/api-hidden.rst\n@@ -379,7 +379,6 @@\n Variable.min\n Variable.no_conflicts\n Variable.notnull\n- Variable.pad_with_fill_value\n Variable.prod\n Variable.quantile\n Variable.rank\n@@ -453,7 +452,6 @@\n IndexVariable.min\n IndexVariable.no_conflicts\n IndexVariable.notnull\n- IndexVariable.pad_with_fill_value\n IndexVariable.prod\n IndexVariable.quantile\n IndexVariable.rank\n"
},
{
"path": "doc/api.rst",
"old_path": "a/doc/api.rst",
"new_path": "b/doc/api.rst",
"metadata": "diff --git a/doc/api.rst b/doc/api.rst\nindex 4492d882355..b3b6aa9139d 100644\n--- a/doc/api.rst\n+++ b/doc/api.rst\n@@ -220,6 +220,7 @@ Reshaping and reorganizing\n Dataset.to_stacked_array\n Dataset.shift\n Dataset.roll\n+ Dataset.pad\n Dataset.sortby\n Dataset.broadcast_like\n \n@@ -399,6 +400,7 @@ Reshaping and reorganizing\n DataArray.to_unstacked_dataset\n DataArray.shift\n DataArray.roll\n+ DataArray.pad\n DataArray.sortby\n DataArray.broadcast_like\n \n"
},
{
"path": "doc/whats-new.rst",
"old_path": "a/doc/whats-new.rst",
"new_path": "b/doc/whats-new.rst",
"metadata": "diff --git a/doc/whats-new.rst b/doc/whats-new.rst\nindex 24120270444..fa71be23db9 100644\n--- a/doc/whats-new.rst\n+++ b/doc/whats-new.rst\n@@ -125,6 +125,8 @@ Breaking changes\n \n New Features\n ~~~~~~~~~~~~\n+- Implement :py:meth:`DataArray.pad` and :py:meth:`Dataset.pad`. (:issue:`<PRID>`, :pull:`<PRID>`).\n+ By `<NAME>`_.\n - :py:meth:`DataArray.sel` and :py:meth:`Dataset.sel` now support :py:class:`pandas.CategoricalIndex`. (:issue:`<PRID>`)\n By `<NAME>`_.\n - Support using an existing, opened h5netcdf ``File`` with\n"
}
] |
diff --git a/doc/api-hidden.rst b/doc/api-hidden.rst
index 437f53b1a91..cc9517a98ba 100644
--- a/doc/api-hidden.rst
+++ b/doc/api-hidden.rst
@@ -379,7 +379,6 @@
Variable.min
Variable.no_conflicts
Variable.notnull
- Variable.pad_with_fill_value
Variable.prod
Variable.quantile
Variable.rank
@@ -453,7 +452,6 @@
IndexVariable.min
IndexVariable.no_conflicts
IndexVariable.notnull
- IndexVariable.pad_with_fill_value
IndexVariable.prod
IndexVariable.quantile
IndexVariable.rank
diff --git a/doc/api.rst b/doc/api.rst
index 4492d882355..b3b6aa9139d 100644
--- a/doc/api.rst
+++ b/doc/api.rst
@@ -220,6 +220,7 @@ Reshaping and reorganizing
Dataset.to_stacked_array
Dataset.shift
Dataset.roll
+ Dataset.pad
Dataset.sortby
Dataset.broadcast_like
@@ -399,6 +400,7 @@ Reshaping and reorganizing
DataArray.to_unstacked_dataset
DataArray.shift
DataArray.roll
+ DataArray.pad
DataArray.sortby
DataArray.broadcast_like
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index 24120270444..fa71be23db9 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -125,6 +125,8 @@ Breaking changes
New Features
~~~~~~~~~~~~
+- Implement :py:meth:`DataArray.pad` and :py:meth:`Dataset.pad`. (:issue:`<PRID>`, :pull:`<PRID>`).
+ By `<NAME>`_.
- :py:meth:`DataArray.sel` and :py:meth:`Dataset.sel` now support :py:class:`pandas.CategoricalIndex`. (:issue:`<PRID>`)
By `<NAME>`_.
- Support using an existing, opened h5netcdf ``File`` with
If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:
[{'type': 'field', 'name': 'constant_values'}, {'type': 'field', 'name': 'pad_width'}, {'type': 'field', 'name': 'pad_width'}, {'type': 'field', 'name': 'stat_length'}, {'type': 'field', 'name': 'mode'}, {'type': 'field', 'name': 'pad_width'}, {'type': 'field', 'name': 'end_values'}, {'type': 'field', 'name': 'pad_width'}, {'type': 'field', 'name': 'constant_values'}, {'type': 'field', 'name': 'reflect_type'}, {'type': 'field', 'name': 'mode'}, {'type': 'field', 'name': 'mode'}, {'type': 'field', 'name': 'padded'}, {'type': 'field', 'name': 'reflect_type'}, {'type': 'field', 'name': 'end_values'}, {'type': 'field', 'name': 'stat_length'}, {'type': 'field', 'name': 'end_values'}, {'type': 'field', 'name': 'stat_length'}, {'type': 'field', 'name': 'reflect_type'}]
|
pydata/xarray
|
pydata__xarray-3424
|
https://github.com/pydata/xarray/pull/3424
|
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index 73618782460..7a97e262ac9 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -34,6 +34,9 @@ New Features
to reduce over all dimensions. While we have no plans to remove `xr.ALL_DIMS`, we suggest
using `...`.
By `Maximilian Roos <https://github.com/max-sixty>`_
+- :py:func:`~xarray.dot`, and :py:func:`~xarray.DataArray.dot` now support the
+ `dims=...` option to sum over the union of dimensions of all input arrays
+ (:issue:`3423`) by `Mathias Hauser <https://github.com/mathause>`_.
- Added integration tests against `pint <https://pint.readthedocs.io/>`_.
(:pull:`3238`) by `Justus Magin <https://github.com/keewis>`_.
diff --git a/xarray/core/computation.py b/xarray/core/computation.py
index 1393d76f283..96992bd2a3a 100644
--- a/xarray/core/computation.py
+++ b/xarray/core/computation.py
@@ -1055,9 +1055,9 @@ def dot(*arrays, dims=None, **kwargs):
----------
arrays: DataArray (or Variable) objects
Arrays to compute.
- dims: str or tuple of strings, optional
- Which dimensions to sum over.
- If not speciified, then all the common dimensions are summed over.
+ dims: '...', str or tuple of strings, optional
+ Which dimensions to sum over. Ellipsis ('...') sums over all dimensions.
+ If not specified, then all the common dimensions are summed over.
**kwargs: dict
Additional keyword arguments passed to numpy.einsum or
dask.array.einsum
@@ -1070,7 +1070,7 @@ def dot(*arrays, dims=None, **kwargs):
--------
>>> import numpy as np
- >>> import xarray as xp
+ >>> import xarray as xr
>>> da_a = xr.DataArray(np.arange(3 * 2).reshape(3, 2), dims=['a', 'b'])
>>> da_b = xr.DataArray(np.arange(3 * 2 * 2).reshape(3, 2, 2),
... dims=['a', 'b', 'c'])
@@ -1117,6 +1117,14 @@ def dot(*arrays, dims=None, **kwargs):
[273, 446, 619]])
Dimensions without coordinates: a, d
+ >>> xr.dot(da_a, da_b)
+ <xarray.DataArray (c: 2)>
+ array([110, 125])
+ Dimensions without coordinates: c
+
+ >>> xr.dot(da_a, da_b, dims=...)
+ <xarray.DataArray ()>
+ array(235)
"""
from .dataarray import DataArray
from .variable import Variable
@@ -1141,7 +1149,9 @@ def dot(*arrays, dims=None, **kwargs):
einsum_axes = "abcdefghijklmnopqrstuvwxyz"
dim_map = {d: einsum_axes[i] for i, d in enumerate(all_dims)}
- if dims is None:
+ if dims is ...:
+ dims = all_dims
+ elif dims is None:
# find dimensions that occur more than one times
dim_counts = Counter()
for arr in arrays:
diff --git a/xarray/core/dataarray.py b/xarray/core/dataarray.py
index 33dcad13204..2e59af57260 100644
--- a/xarray/core/dataarray.py
+++ b/xarray/core/dataarray.py
@@ -2742,9 +2742,9 @@ def dot(
----------
other : DataArray
The other array with which the dot product is performed.
- dims: hashable or sequence of hashables, optional
- Along which dimensions to be summed over. Default all the common
- dimensions are summed over.
+ dims: '...', hashable or sequence of hashables, optional
+ Which dimensions to sum over. Ellipsis ('...') sums over all dimensions.
+ If not specified, then all the common dimensions are summed over.
Returns
-------
|
diff --git a/xarray/tests/test_computation.py b/xarray/tests/test_computation.py
index 383427b479b..1f2634cc9b0 100644
--- a/xarray/tests/test_computation.py
+++ b/xarray/tests/test_computation.py
@@ -998,6 +998,23 @@ def test_dot(use_dask):
assert actual.dims == ("b",)
assert (actual.data == np.zeros(actual.shape)).all()
+ # Ellipsis (...) sums over all dimensions
+ actual = xr.dot(da_a, da_b, dims=...)
+ assert actual.dims == ()
+ assert (actual.data == np.einsum("ij,ijk->", a, b)).all()
+
+ actual = xr.dot(da_a, da_b, da_c, dims=...)
+ assert actual.dims == ()
+ assert (actual.data == np.einsum("ij,ijk,kl-> ", a, b, c)).all()
+
+ actual = xr.dot(da_a, dims=...)
+ assert actual.dims == ()
+ assert (actual.data == np.einsum("ij-> ", a)).all()
+
+ actual = xr.dot(da_a.sel(a=[]), da_a.sel(a=[]), dims=...)
+ assert actual.dims == ()
+ assert (actual.data == np.zeros(actual.shape)).all()
+
# Invalid cases
if not use_dask:
with pytest.raises(TypeError):
diff --git a/xarray/tests/test_dataarray.py b/xarray/tests/test_dataarray.py
index ad474d533be..38fe7384df2 100644
--- a/xarray/tests/test_dataarray.py
+++ b/xarray/tests/test_dataarray.py
@@ -3925,6 +3925,16 @@ def test_dot(self):
expected = DataArray(expected_vals, coords=[x, j], dims=["x", "j"])
assert_equal(expected, actual)
+ # Ellipsis: all dims are shared
+ actual = da.dot(da, dims=...)
+ expected = da.dot(da)
+ assert_equal(expected, actual)
+
+ # Ellipsis: not all dims are shared
+ actual = da.dot(dm, dims=...)
+ expected = da.dot(dm, dims=("j", "x", "y", "z"))
+ assert_equal(expected, actual)
+
with pytest.raises(NotImplementedError):
da.dot(dm.to_dataset(name="dm"))
with pytest.raises(TypeError):
|
[
{
"path": "doc/whats-new.rst",
"old_path": "a/doc/whats-new.rst",
"new_path": "b/doc/whats-new.rst",
"metadata": "diff --git a/doc/whats-new.rst b/doc/whats-new.rst\nindex 73618782460..7a97e262ac9 100644\n--- a/doc/whats-new.rst\n+++ b/doc/whats-new.rst\n@@ -34,6 +34,9 @@ New Features\n to reduce over all dimensions. While we have no plans to remove `xr.ALL_DIMS`, we suggest\n using `...`.\n By `Maximilian Roos <https://github.com/max-sixty>`_\n+- :py:func:`~xarray.dot`, and :py:func:`~xarray.DataArray.dot` now support the\n+ `dims=...` option to sum over the union of dimensions of all input arrays\n+ (:issue:`3423`) by `Mathias Hauser <https://github.com/mathause>`_.\n - Added integration tests against `pint <https://pint.readthedocs.io/>`_.\n (:pull:`3238`) by `Justus Magin <https://github.com/keewis>`_.\n \n"
}
] |
0014
|
74ca69a3b7b53d2b8cc8c88ddaf0fe8c6c7bbf6c
|
[
"xarray/tests/test_dataarray.py::test_rolling_wrapped_bottleneck[1-None-True-min]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-4-2-False]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-2-1-False-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-1-3-True-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_groupby_bins_multidim",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-1-None-False-2]",
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"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-3-3-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-4-1-False-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_expand_dims",
"xarray/tests/test_dataarray.py::TestDataArray::test_to_dict_with_numpy_attrs",
"xarray/tests/test_dataarray.py::TestDataArray::test_matmul",
"xarray/tests/test_dataarray.py::TestDataArray::test_drop_coordinates",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[sum-1-1-False]",
"xarray/tests/test_computation.py::test_apply_two_outputs",
"xarray/tests/test_dataarray.py::TestDataArray::test_combine_first",
"xarray/tests/test_dataarray.py::test_name_in_masking",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-2-2-True]",
"xarray/tests/test_dataarray.py::test_rolling_pandas_compat[2-2-False]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-1-1-True-1]",
"xarray/tests/test_dataarray.py::test_rolling_wrapped_bottleneck[1-1-True-std]",
"xarray/tests/test_dataarray.py::TestDataArray::test_reindex_like_no_index",
"xarray/tests/test_computation.py::test_signature_properties",
"xarray/tests/test_dataarray.py::TestDataArray::test_init_value",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-2-1-True-2]",
"xarray/tests/test_dataarray.py::test_rolling_wrapped_bottleneck[1-1-None-std]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-4-None-True-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_stack_unstack",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-4-3-True-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-3-3-False-1]",
"xarray/tests/test_dataarray.py::test_raise_no_warning_for_nan_in_binary_ops",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-3-2-False-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_reindex_like",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-1-None-False-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-1-3-False-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_isel_fancy",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-2-2-True-1]",
"xarray/tests/test_computation.py::test_apply_two_inputs",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-4-1-False-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_reset_coords",
"xarray/tests/test_dataarray.py::TestDataArray::test_groupby_apply_center",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-4-2-True-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-1-3-True-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-2-2-True-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_shift[fill_value1-float-1]",
"xarray/tests/test_computation.py::test_where",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-1-2-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-1-None-True-2]",
"xarray/tests/test_dataarray.py::test_rolling_pandas_compat[4-1-False]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-2-None-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[sum-4-2-True]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-4-1-False-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_broadcast_arrays_nocopy",
"xarray/tests/test_dataarray.py::TestDataArray::test_inplace_math_automatic_alignment",
"xarray/tests/test_dataarray.py::TestDataArray::test_sel_float",
"xarray/tests/test_dataarray.py::test_rolling_wrapped_bottleneck[1-1-False-median]",
"xarray/tests/test_computation.py::test_output_wrong_dims",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-3-2-False-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_swap_dims",
"xarray/tests/test_dataarray.py::TestDataArray::test_loc_assign",
"xarray/tests/test_dataarray.py::test_rolling_wrapped_bottleneck[1-None-True-median]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[sum-1-3-False]",
"xarray/tests/test_dataarray.py::TestDataArray::test_expand_dims_error",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-3-3-False-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_align_without_indexes_errors",
"xarray/tests/test_dataarray.py::test_rolling_wrapped_bottleneck[1-1-None-min]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-2-1-False]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-3-3-True-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-2-1-False-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_align_dtype",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-4-3-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-2-3-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-2-None-True-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_constructor_from_self_described",
"xarray/tests/test_dataarray.py::TestDataArray::test_to_and_from_dict_with_time_dim",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-4-2-False-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-4-3-True-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_broadcast_coordinates",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-3-None-True-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-2-None-False-2]"
] |
[
"xarray/tests/test_computation.py::test_dot[False]",
"xarray/tests/test_dataarray.py::TestDataArray::test_dot"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/whats-new.rst",
"old_path": "a/doc/whats-new.rst",
"new_path": "b/doc/whats-new.rst",
"metadata": "diff --git a/doc/whats-new.rst b/doc/whats-new.rst\nindex 73618782460..7a97e262ac9 100644\n--- a/doc/whats-new.rst\n+++ b/doc/whats-new.rst\n@@ -34,6 +34,9 @@ New Features\n to reduce over all dimensions. While we have no plans to remove `xr.ALL_DIMS`, we suggest\n using `...`.\n By `<NAME>`_\n+- :py:func:`~xarray.dot`, and :py:func:`~xarray.DataArray.dot` now support the\n+ `dims=...` option to sum over the union of dimensions of all input arrays\n+ (:issue:`<PRID>`) by `<NAME>`_.\n - Added integration tests against `pint <https://pint.readthedocs.io/>`_.\n (:pull:`<PRID>`) by `<NAME>`_.\n \n"
}
] |
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index 73618782460..7a97e262ac9 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -34,6 +34,9 @@ New Features
to reduce over all dimensions. While we have no plans to remove `xr.ALL_DIMS`, we suggest
using `...`.
By `<NAME>`_
+- :py:func:`~xarray.dot`, and :py:func:`~xarray.DataArray.dot` now support the
+ `dims=...` option to sum over the union of dimensions of all input arrays
+ (:issue:`<PRID>`) by `<NAME>`_.
- Added integration tests against `pint <https://pint.readthedocs.io/>`_.
(:pull:`<PRID>`) by `<NAME>`_.
|
pydata/xarray
|
pydata__xarray-3459
|
https://github.com/pydata/xarray/pull/3459
|
diff --git a/doc/computation.rst b/doc/computation.rst
index ae5f4bc5c66..d477cb63d72 100644
--- a/doc/computation.rst
+++ b/doc/computation.rst
@@ -462,13 +462,13 @@ Datasets support most of the same methods found on data arrays:
abs(ds)
Datasets also support NumPy ufuncs (requires NumPy v1.13 or newer), or
-alternatively you can use :py:meth:`~xarray.Dataset.apply` to apply a function
+alternatively you can use :py:meth:`~xarray.Dataset.map` to map a function
to each variable in a dataset:
.. ipython:: python
np.sin(ds)
- ds.apply(np.sin)
+ ds.map(np.sin)
Datasets also use looping over variables for *broadcasting* in binary
arithmetic. You can do arithmetic between any ``DataArray`` and a dataset:
diff --git a/doc/groupby.rst b/doc/groupby.rst
index 52a27f4f160..f5943703765 100644
--- a/doc/groupby.rst
+++ b/doc/groupby.rst
@@ -35,10 +35,11 @@ Let's create a simple example dataset:
.. ipython:: python
- ds = xr.Dataset({'foo': (('x', 'y'), np.random.rand(4, 3))},
- coords={'x': [10, 20, 30, 40],
- 'letters': ('x', list('abba'))})
- arr = ds['foo']
+ ds = xr.Dataset(
+ {"foo": (("x", "y"), np.random.rand(4, 3))},
+ coords={"x": [10, 20, 30, 40], "letters": ("x", list("abba"))},
+ )
+ arr = ds["foo"]
ds
If we groupby the name of a variable or coordinate in a dataset (we can also
@@ -93,7 +94,7 @@ Apply
~~~~~
To apply a function to each group, you can use the flexible
-:py:meth:`~xarray.DatasetGroupBy.apply` method. The resulting objects are automatically
+:py:meth:`~xarray.DatasetGroupBy.map` method. The resulting objects are automatically
concatenated back together along the group axis:
.. ipython:: python
@@ -101,7 +102,7 @@ concatenated back together along the group axis:
def standardize(x):
return (x - x.mean()) / x.std()
- arr.groupby('letters').apply(standardize)
+ arr.groupby('letters').map(standardize)
GroupBy objects also have a :py:meth:`~xarray.DatasetGroupBy.reduce` method and
methods like :py:meth:`~xarray.DatasetGroupBy.mean` as shortcuts for applying an
@@ -202,7 +203,7 @@ __ http://cfconventions.org/cf-conventions/v1.6.0/cf-conventions.html#_two_dimen
dims=['ny','nx'])
da
da.groupby('lon').sum(...)
- da.groupby('lon').apply(lambda x: x - x.mean(), shortcut=False)
+ da.groupby('lon').map(lambda x: x - x.mean(), shortcut=False)
Because multidimensional groups have the ability to generate a very large
number of bins, coarse-binning via :py:meth:`~xarray.Dataset.groupby_bins`
diff --git a/doc/howdoi.rst b/doc/howdoi.rst
index 721d1323e73..91644ba2718 100644
--- a/doc/howdoi.rst
+++ b/doc/howdoi.rst
@@ -44,7 +44,7 @@ How do I ...
* - convert a possibly irregularly sampled timeseries to a regularly sampled timeseries
- :py:meth:`DataArray.resample`, :py:meth:`Dataset.resample` (see :ref:`resampling` for more)
* - apply a function on all data variables in a Dataset
- - :py:meth:`Dataset.apply`
+ - :py:meth:`Dataset.map`
* - write xarray objects with complex values to a netCDF file
- :py:func:`Dataset.to_netcdf`, :py:func:`DataArray.to_netcdf` specifying ``engine="h5netcdf", invalid_netcdf=True``
* - make xarray objects look like other xarray objects
diff --git a/doc/quick-overview.rst b/doc/quick-overview.rst
index 7d84199323d..741b3d1a5fe 100644
--- a/doc/quick-overview.rst
+++ b/doc/quick-overview.rst
@@ -142,7 +142,7 @@ xarray supports grouped operations using a very similar API to pandas (see :ref:
labels = xr.DataArray(['E', 'F', 'E'], [data.coords['y']], name='labels')
labels
data.groupby(labels).mean('y')
- data.groupby(labels).apply(lambda x: x - x.min())
+ data.groupby(labels).map(lambda x: x - x.min())
Plotting
--------
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index 04fe88e9993..b572b1dda67 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -44,6 +44,13 @@ New Features
option for dropping either labels or variables, but using the more specific methods is encouraged.
(:pull:`3475`)
By `Maximilian Roos <https://github.com/max-sixty>`_
+- :py:meth:`Dataset.map` & :py:meth:`GroupBy.map` & :py:meth:`Resample.map` have been added for
+ mapping / applying a function over each item in the collection, reflecting the widely used
+ and least surprising name for this operation.
+ The existing ``apply`` methods remain for backward compatibility, though using the ``map``
+ methods is encouraged.
+ (:pull:`3459`)
+ By `Maximilian Roos <https://github.com/max-sixty>`_
- :py:meth:`Dataset.transpose` and :py:meth:`DataArray.transpose` now support an ellipsis (`...`)
to represent all 'other' dimensions. For example, to move one dimension to the front,
use `.transpose('x', ...)`. (:pull:`3421`)
diff --git a/xarray/core/dataarray.py b/xarray/core/dataarray.py
index d2d37871ee9..c9ccd88b61e 100644
--- a/xarray/core/dataarray.py
+++ b/xarray/core/dataarray.py
@@ -919,7 +919,7 @@ def copy(self, deep: bool = True, data: Any = None) -> "DataArray":
Coordinates:
* x (x) <U1 'a' 'b' 'c'
- See also
+ See Also
--------
pandas.DataFrame.copy
"""
@@ -1716,7 +1716,7 @@ def stack(
codes=[[0, 0, 0, 1, 1, 1], [0, 1, 2, 0, 1, 2]],
names=['x', 'y'])
- See also
+ See Also
--------
DataArray.unstack
"""
@@ -1764,7 +1764,7 @@ def unstack(
>>> arr.identical(roundtripped)
True
- See also
+ See Also
--------
DataArray.stack
"""
@@ -1922,6 +1922,11 @@ def drop(
"""Backward compatible method based on `drop_vars` and `drop_sel`
Using either `drop_vars` or `drop_sel` is encouraged
+
+ See Also
+ --------
+ DataArray.drop_vars
+ DataArray.drop_sel
"""
ds = self._to_temp_dataset().drop(labels, dim, errors=errors)
return self._from_temp_dataset(ds)
diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index 2cadc90334c..dc5a315e72a 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -3557,6 +3557,11 @@ def drop(self, labels=None, dim=None, *, errors="raise", **labels_kwargs):
"""Backward compatible method based on `drop_vars` and `drop_sel`
Using either `drop_vars` or `drop_sel` is encouraged
+
+ See Also
+ --------
+ Dataset.drop_vars
+ Dataset.drop_sel
"""
if errors not in ["raise", "ignore"]:
raise ValueError('errors must be either "raise" or "ignore"')
@@ -4108,14 +4113,14 @@ def reduce(
variables, coord_names=coord_names, attrs=attrs, indexes=indexes
)
- def apply(
+ def map(
self,
func: Callable,
keep_attrs: bool = None,
args: Iterable[Any] = (),
**kwargs: Any,
) -> "Dataset":
- """Apply a function over the data variables in this dataset.
+ """Apply a function to each variable in this dataset
Parameters
----------
@@ -4135,7 +4140,7 @@ def apply(
Returns
-------
applied : Dataset
- Resulting dataset from applying ``func`` over each data variable.
+ Resulting dataset from applying ``func`` to each data variable.
Examples
--------
@@ -4148,7 +4153,7 @@ def apply(
Data variables:
foo (dim_0, dim_1) float64 -0.3751 -1.951 -1.945 0.2948 0.711 -0.3948
bar (x) int64 -1 2
- >>> ds.apply(np.fabs)
+ >>> ds.map(np.fabs)
<xarray.Dataset>
Dimensions: (dim_0: 2, dim_1: 3, x: 2)
Dimensions without coordinates: dim_0, dim_1, x
@@ -4165,6 +4170,27 @@ def apply(
attrs = self.attrs if keep_attrs else None
return type(self)(variables, attrs=attrs)
+ def apply(
+ self,
+ func: Callable,
+ keep_attrs: bool = None,
+ args: Iterable[Any] = (),
+ **kwargs: Any,
+ ) -> "Dataset":
+ """
+ Backward compatible implementation of ``map``
+
+ See Also
+ --------
+ Dataset.map
+ """
+ warnings.warn(
+ "Dataset.apply may be deprecated in the future. Using Dataset.map is encouraged",
+ PendingDeprecationWarning,
+ stacklevel=2,
+ )
+ return self.map(func, keep_attrs, args, **kwargs)
+
def assign(
self, variables: Mapping[Hashable, Any] = None, **variables_kwargs: Hashable
) -> "Dataset":
diff --git a/xarray/core/groupby.py b/xarray/core/groupby.py
index c8906e34737..8ae65d9b9df 100644
--- a/xarray/core/groupby.py
+++ b/xarray/core/groupby.py
@@ -608,7 +608,7 @@ def assign_coords(self, coords=None, **coords_kwargs):
Dataset.swap_dims
"""
coords_kwargs = either_dict_or_kwargs(coords, coords_kwargs, "assign_coords")
- return self.apply(lambda ds: ds.assign_coords(**coords_kwargs))
+ return self.map(lambda ds: ds.assign_coords(**coords_kwargs))
def _maybe_reorder(xarray_obj, dim, positions):
@@ -655,8 +655,8 @@ def lookup_order(dimension):
new_order = sorted(stacked.dims, key=lookup_order)
return stacked.transpose(*new_order, transpose_coords=self._restore_coord_dims)
- def apply(self, func, shortcut=False, args=(), **kwargs):
- """Apply a function over each array in the group and concatenate them
+ def map(self, func, shortcut=False, args=(), **kwargs):
+ """Apply a function to each array in the group and concatenate them
together into a new array.
`func` is called like `func(ar, *args, **kwargs)` for each array `ar`
@@ -702,6 +702,21 @@ def apply(self, func, shortcut=False, args=(), **kwargs):
applied = (maybe_wrap_array(arr, func(arr, *args, **kwargs)) for arr in grouped)
return self._combine(applied, shortcut=shortcut)
+ def apply(self, func, shortcut=False, args=(), **kwargs):
+ """
+ Backward compatible implementation of ``map``
+
+ See Also
+ --------
+ DataArrayGroupBy.map
+ """
+ warnings.warn(
+ "GroupBy.apply may be deprecated in the future. Using GroupBy.map is encouraged",
+ PendingDeprecationWarning,
+ stacklevel=2,
+ )
+ return self.map(func, shortcut=shortcut, args=args, **kwargs)
+
def _combine(self, applied, restore_coord_dims=False, shortcut=False):
"""Recombine the applied objects like the original."""
applied_example, applied = peek_at(applied)
@@ -765,7 +780,7 @@ def quantile(self, q, dim=None, interpolation="linear", keep_attrs=None):
if dim is None:
dim = self._group_dim
- out = self.apply(
+ out = self.map(
self._obj.__class__.quantile,
shortcut=False,
q=q,
@@ -820,7 +835,7 @@ def reduce_array(ar):
check_reduce_dims(dim, self.dims)
- return self.apply(reduce_array, shortcut=shortcut)
+ return self.map(reduce_array, shortcut=shortcut)
ops.inject_reduce_methods(DataArrayGroupBy)
@@ -828,8 +843,8 @@ def reduce_array(ar):
class DatasetGroupBy(GroupBy, ImplementsDatasetReduce):
- def apply(self, func, args=(), shortcut=None, **kwargs):
- """Apply a function over each Dataset in the group and concatenate them
+ def map(self, func, args=(), shortcut=None, **kwargs):
+ """Apply a function to each Dataset in the group and concatenate them
together into a new Dataset.
`func` is called like `func(ds, *args, **kwargs)` for each dataset `ds`
@@ -862,6 +877,22 @@ def apply(self, func, args=(), shortcut=None, **kwargs):
applied = (func(ds, *args, **kwargs) for ds in self._iter_grouped())
return self._combine(applied)
+ def apply(self, func, args=(), shortcut=None, **kwargs):
+ """
+ Backward compatible implementation of ``map``
+
+ See Also
+ --------
+ DatasetGroupBy.map
+ """
+
+ warnings.warn(
+ "GroupBy.apply may be deprecated in the future. Using GroupBy.map is encouraged",
+ PendingDeprecationWarning,
+ stacklevel=2,
+ )
+ return self.map(func, shortcut=shortcut, args=args, **kwargs)
+
def _combine(self, applied):
"""Recombine the applied objects like the original."""
applied_example, applied = peek_at(applied)
@@ -914,7 +945,7 @@ def reduce_dataset(ds):
check_reduce_dims(dim, self.dims)
- return self.apply(reduce_dataset)
+ return self.map(reduce_dataset)
def assign(self, **kwargs):
"""Assign data variables by group.
@@ -923,7 +954,7 @@ def assign(self, **kwargs):
--------
Dataset.assign
"""
- return self.apply(lambda ds: ds.assign(**kwargs))
+ return self.map(lambda ds: ds.assign(**kwargs))
ops.inject_reduce_methods(DatasetGroupBy)
diff --git a/xarray/core/resample.py b/xarray/core/resample.py
index 2cb1bd55e19..fb388490d06 100644
--- a/xarray/core/resample.py
+++ b/xarray/core/resample.py
@@ -1,3 +1,5 @@
+import warnings
+
from . import ops
from .groupby import DataArrayGroupBy, DatasetGroupBy
@@ -173,8 +175,8 @@ def __init__(self, *args, dim=None, resample_dim=None, **kwargs):
super().__init__(*args, **kwargs)
- def apply(self, func, shortcut=False, args=(), **kwargs):
- """Apply a function over each array in the group and concatenate them
+ def map(self, func, shortcut=False, args=(), **kwargs):
+ """Apply a function to each array in the group and concatenate them
together into a new array.
`func` is called like `func(ar, *args, **kwargs)` for each array `ar`
@@ -212,7 +214,9 @@ def apply(self, func, shortcut=False, args=(), **kwargs):
applied : DataArray or DataArray
The result of splitting, applying and combining this array.
"""
- combined = super().apply(func, shortcut=shortcut, args=args, **kwargs)
+ # TODO: the argument order for Resample doesn't match that for its parent,
+ # GroupBy
+ combined = super().map(func, shortcut=shortcut, args=args, **kwargs)
# If the aggregation function didn't drop the original resampling
# dimension, then we need to do so before we can rename the proxy
@@ -225,6 +229,21 @@ def apply(self, func, shortcut=False, args=(), **kwargs):
return combined
+ def apply(self, func, args=(), shortcut=None, **kwargs):
+ """
+ Backward compatible implementation of ``map``
+
+ See Also
+ --------
+ DataArrayResample.map
+ """
+ warnings.warn(
+ "Resample.apply may be deprecated in the future. Using Resample.map is encouraged",
+ PendingDeprecationWarning,
+ stacklevel=2,
+ )
+ return self.map(func=func, shortcut=shortcut, args=args, **kwargs)
+
ops.inject_reduce_methods(DataArrayResample)
ops.inject_binary_ops(DataArrayResample)
@@ -247,7 +266,7 @@ def __init__(self, *args, dim=None, resample_dim=None, **kwargs):
super().__init__(*args, **kwargs)
- def apply(self, func, args=(), shortcut=None, **kwargs):
+ def map(self, func, args=(), shortcut=None, **kwargs):
"""Apply a function over each Dataset in the groups generated for
resampling and concatenate them together into a new Dataset.
@@ -282,6 +301,22 @@ def apply(self, func, args=(), shortcut=None, **kwargs):
return combined.rename({self._resample_dim: self._dim})
+ def apply(self, func, args=(), shortcut=None, **kwargs):
+ """
+ Backward compatible implementation of ``map``
+
+ See Also
+ --------
+ DataSetResample.map
+ """
+
+ warnings.warn(
+ "Resample.apply may be deprecated in the future. Using Resample.map is encouraged",
+ PendingDeprecationWarning,
+ stacklevel=2,
+ )
+ return self.map(func=func, shortcut=shortcut, args=args, **kwargs)
+
def reduce(self, func, dim=None, keep_attrs=None, **kwargs):
"""Reduce the items in this group by applying `func` along the
pre-defined resampling dimension.
|
diff --git a/xarray/tests/test_dataarray.py b/xarray/tests/test_dataarray.py
index acfe684d220..42fae2c9dd4 100644
--- a/xarray/tests/test_dataarray.py
+++ b/xarray/tests/test_dataarray.py
@@ -2417,7 +2417,7 @@ def test_groupby_properties(self):
assert_array_equal(expected_groups[key], grouped.groups[key])
assert 3 == len(grouped)
- def test_groupby_apply_identity(self):
+ def test_groupby_map_identity(self):
expected = self.make_groupby_example_array()
idx = expected.coords["y"]
@@ -2428,7 +2428,7 @@ def identity(x):
for shortcut in [False, True]:
for squeeze in [False, True]:
grouped = expected.groupby(g, squeeze=squeeze)
- actual = grouped.apply(identity, shortcut=shortcut)
+ actual = grouped.map(identity, shortcut=shortcut)
assert_identical(expected, actual)
def test_groupby_sum(self):
@@ -2461,7 +2461,7 @@ def test_groupby_sum(self):
[["a", "b", "c"]],
["abc"],
)
- actual = array["y"].groupby("abc").apply(np.sum)
+ actual = array["y"].groupby("abc").map(np.sum)
assert_allclose(expected, actual)
actual = array["y"].groupby("abc").sum(...)
assert_allclose(expected, actual)
@@ -2532,7 +2532,7 @@ def test_groupby_reduce_attrs(self):
expected.attrs["foo"] = "bar"
assert_identical(expected, actual)
- def test_groupby_apply_center(self):
+ def test_groupby_map_center(self):
def center(x):
return x - np.mean(x)
@@ -2545,16 +2545,16 @@ def center(x):
)
expected_ds["foo"] = (["x", "y"], exp_data)
expected_centered = expected_ds["foo"]
- assert_allclose(expected_centered, grouped.apply(center))
+ assert_allclose(expected_centered, grouped.map(center))
- def test_groupby_apply_ndarray(self):
+ def test_groupby_map_ndarray(self):
# regression test for #326
array = self.make_groupby_example_array()
grouped = array.groupby("abc")
- actual = grouped.apply(np.asarray)
+ actual = grouped.map(np.asarray)
assert_equal(array, actual)
- def test_groupby_apply_changes_metadata(self):
+ def test_groupby_map_changes_metadata(self):
def change_metadata(x):
x.coords["x"] = x.coords["x"] * 2
x.attrs["fruit"] = "lemon"
@@ -2562,7 +2562,7 @@ def change_metadata(x):
array = self.make_groupby_example_array()
grouped = array.groupby("abc")
- actual = grouped.apply(change_metadata)
+ actual = grouped.map(change_metadata)
expected = array.copy()
expected = change_metadata(expected)
assert_equal(expected, actual)
@@ -2631,7 +2631,7 @@ def test_groupby_restore_dim_order(self):
("a", ("a", "y")),
("b", ("x", "b")),
]:
- result = array.groupby(by).apply(lambda x: x.squeeze())
+ result = array.groupby(by).map(lambda x: x.squeeze())
assert result.dims == expected_dims
def test_groupby_restore_coord_dims(self):
@@ -2651,13 +2651,13 @@ def test_groupby_restore_coord_dims(self):
("a", ("a", "y")),
("b", ("x", "b")),
]:
- result = array.groupby(by, restore_coord_dims=True).apply(
+ result = array.groupby(by, restore_coord_dims=True).map(
lambda x: x.squeeze()
)["c"]
assert result.dims == expected_dims
with pytest.warns(FutureWarning):
- array.groupby("x").apply(lambda x: x.squeeze())
+ array.groupby("x").map(lambda x: x.squeeze())
def test_groupby_first_and_last(self):
array = DataArray([1, 2, 3, 4, 5], dims="x")
@@ -2699,9 +2699,9 @@ def test_groupby_multidim(self):
actual_sum = array.groupby(dim).sum(...)
assert_identical(expected_sum, actual_sum)
- def test_groupby_multidim_apply(self):
+ def test_groupby_multidim_map(self):
array = self.make_groupby_multidim_example_array()
- actual = array.groupby("lon").apply(lambda x: x - x.mean())
+ actual = array.groupby("lon").map(lambda x: x - x.mean())
expected = DataArray(
[[[-2.5, -6.0], [-5.0, -8.5]], [[2.5, 3.0], [8.0, 8.5]]],
coords=array.coords,
@@ -2722,7 +2722,7 @@ def test_groupby_bins(self):
)
# the problem with this is that it overwrites the dimensions of array!
# actual = array.groupby('dim_0', bins=bins).sum()
- actual = array.groupby_bins("dim_0", bins).apply(lambda x: x.sum())
+ actual = array.groupby_bins("dim_0", bins).map(lambda x: x.sum())
assert_identical(expected, actual)
# make sure original array dims are unchanged
assert len(array.dim_0) == 4
@@ -2744,12 +2744,12 @@ def test_groupby_bins_multidim(self):
bins = [0, 15, 20]
bin_coords = pd.cut(array["lat"].values.flat, bins).categories
expected = DataArray([16, 40], dims="lat_bins", coords={"lat_bins": bin_coords})
- actual = array.groupby_bins("lat", bins).apply(lambda x: x.sum())
+ actual = array.groupby_bins("lat", bins).map(lambda x: x.sum())
assert_identical(expected, actual)
# modify the array coordinates to be non-monotonic after unstacking
array["lat"].data = np.array([[10.0, 20.0], [20.0, 10.0]])
expected = DataArray([28, 28], dims="lat_bins", coords={"lat_bins": bin_coords})
- actual = array.groupby_bins("lat", bins).apply(lambda x: x.sum())
+ actual = array.groupby_bins("lat", bins).map(lambda x: x.sum())
assert_identical(expected, actual)
def test_groupby_bins_sort(self):
@@ -2784,7 +2784,7 @@ def func(arg1, arg2, arg3=0.0):
times = pd.date_range("2000", periods=3, freq="D")
da = xr.DataArray([1.0, 1.0, 1.0], coords=[times], dims=["time"])
expected = xr.DataArray([3.0, 3.0, 3.0], coords=[times], dims=["time"])
- actual = da.resample(time="D").apply(func, args=(1.0,), arg3=1.0)
+ actual = da.resample(time="D").map(func, args=(1.0,), arg3=1.0)
assert_identical(actual, expected)
def test_resample_first(self):
diff --git a/xarray/tests/test_dataset.py b/xarray/tests/test_dataset.py
index 50e78c9f685..d001c43da94 100644
--- a/xarray/tests/test_dataset.py
+++ b/xarray/tests/test_dataset.py
@@ -3310,17 +3310,17 @@ def identity(x):
return x
for k in ["x", "c", "y"]:
- actual = data.groupby(k, squeeze=False).apply(identity)
+ actual = data.groupby(k, squeeze=False).map(identity)
assert_equal(data, actual)
def test_groupby_returns_new_type(self):
data = Dataset({"z": (["x", "y"], np.random.randn(3, 5))})
- actual = data.groupby("x").apply(lambda ds: ds["z"])
+ actual = data.groupby("x").map(lambda ds: ds["z"])
expected = data["z"]
assert_identical(expected, actual)
- actual = data["z"].groupby("x").apply(lambda x: x.to_dataset())
+ actual = data["z"].groupby("x").map(lambda x: x.to_dataset())
expected = data
assert_identical(expected, actual)
@@ -3639,7 +3639,7 @@ def func(arg1, arg2, arg3=0.0):
times = pd.date_range("2000", freq="D", periods=3)
ds = xr.Dataset({"foo": ("time", [1.0, 1.0, 1.0]), "time": times})
expected = xr.Dataset({"foo": ("time", [3.0, 3.0, 3.0]), "time": times})
- actual = ds.resample(time="D").apply(func, args=(1.0,), arg3=1.0)
+ actual = ds.resample(time="D").map(func, args=(1.0,), arg3=1.0)
assert_identical(expected, actual)
def test_to_array(self):
@@ -4515,31 +4515,36 @@ def test_count(self):
actual = ds.count()
assert_identical(expected, actual)
- def test_apply(self):
+ def test_map(self):
data = create_test_data()
data.attrs["foo"] = "bar"
- assert_identical(data.apply(np.mean), data.mean())
+ assert_identical(data.map(np.mean), data.mean())
expected = data.mean(keep_attrs=True)
- actual = data.apply(lambda x: x.mean(keep_attrs=True), keep_attrs=True)
+ actual = data.map(lambda x: x.mean(keep_attrs=True), keep_attrs=True)
assert_identical(expected, actual)
- assert_identical(
- data.apply(lambda x: x, keep_attrs=True), data.drop_vars("time")
- )
+ assert_identical(data.map(lambda x: x, keep_attrs=True), data.drop_vars("time"))
def scale(x, multiple=1):
return multiple * x
- actual = data.apply(scale, multiple=2)
+ actual = data.map(scale, multiple=2)
assert_equal(actual["var1"], 2 * data["var1"])
assert_identical(actual["numbers"], data["numbers"])
- actual = data.apply(np.asarray)
+ actual = data.map(np.asarray)
expected = data.drop_vars("time") # time is not used on a data var
assert_equal(expected, actual)
+ def test_apply_pending_deprecated_map(self):
+ data = create_test_data()
+ data.attrs["foo"] = "bar"
+
+ with pytest.warns(PendingDeprecationWarning):
+ assert_identical(data.apply(np.mean), data.mean())
+
def make_example_math_dataset(self):
variables = {
"bar": ("x", np.arange(100, 400, 100)),
@@ -4566,15 +4571,15 @@ def test_dataset_number_math(self):
def test_unary_ops(self):
ds = self.make_example_math_dataset()
- assert_identical(ds.apply(abs), abs(ds))
- assert_identical(ds.apply(lambda x: x + 4), ds + 4)
+ assert_identical(ds.map(abs), abs(ds))
+ assert_identical(ds.map(lambda x: x + 4), ds + 4)
for func in [
lambda x: x.isnull(),
lambda x: x.round(),
lambda x: x.astype(int),
]:
- assert_identical(ds.apply(func), func(ds))
+ assert_identical(ds.map(func), func(ds))
assert_identical(ds.isnull(), ~ds.notnull())
@@ -4587,7 +4592,7 @@ def test_unary_ops(self):
def test_dataset_array_math(self):
ds = self.make_example_math_dataset()
- expected = ds.apply(lambda x: x - ds["foo"])
+ expected = ds.map(lambda x: x - ds["foo"])
assert_identical(expected, ds - ds["foo"])
assert_identical(expected, -ds["foo"] + ds)
assert_identical(expected, ds - ds["foo"].variable)
@@ -4596,7 +4601,7 @@ def test_dataset_array_math(self):
actual -= ds["foo"]
assert_identical(expected, actual)
- expected = ds.apply(lambda x: x + ds["bar"])
+ expected = ds.map(lambda x: x + ds["bar"])
assert_identical(expected, ds + ds["bar"])
actual = ds.copy(deep=True)
actual += ds["bar"]
@@ -4612,7 +4617,7 @@ def test_dataset_dataset_math(self):
assert_identical(ds, ds + 0 * ds)
assert_identical(ds, ds + {"foo": 0, "bar": 0})
- expected = ds.apply(lambda x: 2 * x)
+ expected = ds.map(lambda x: 2 * x)
assert_identical(expected, 2 * ds)
assert_identical(expected, ds + ds)
assert_identical(expected, ds + ds.data_vars)
@@ -4709,7 +4714,7 @@ def test_dataset_transpose(self):
assert_identical(expected, actual)
actual = ds.transpose("x", "y")
- expected = ds.apply(lambda x: x.transpose("x", "y", transpose_coords=True))
+ expected = ds.map(lambda x: x.transpose("x", "y", transpose_coords=True))
assert_identical(expected, actual)
ds = create_test_data()
diff --git a/xarray/tests/test_groupby.py b/xarray/tests/test_groupby.py
index e2216547ac8..581affa3471 100644
--- a/xarray/tests/test_groupby.py
+++ b/xarray/tests/test_groupby.py
@@ -45,14 +45,14 @@ def test_groupby_dims_property(dataset):
assert stacked.groupby("xy").dims == stacked.isel(xy=0).dims
-def test_multi_index_groupby_apply(dataset):
+def test_multi_index_groupby_map(dataset):
# regression test for GH873
ds = dataset.isel(z=1, drop=True)[["foo"]]
expected = 2 * ds
actual = (
ds.stack(space=["x", "y"])
.groupby("space")
- .apply(lambda x: 2 * x)
+ .map(lambda x: 2 * x)
.unstack("space")
)
assert_equal(expected, actual)
@@ -107,23 +107,23 @@ def test_groupby_input_mutation():
assert_identical(array, array_copy) # should not modify inputs
-def test_da_groupby_apply_func_args():
+def test_da_groupby_map_func_args():
def func(arg1, arg2, arg3=0):
return arg1 + arg2 + arg3
array = xr.DataArray([1, 1, 1], [("x", [1, 2, 3])])
expected = xr.DataArray([3, 3, 3], [("x", [1, 2, 3])])
- actual = array.groupby("x").apply(func, args=(1,), arg3=1)
+ actual = array.groupby("x").map(func, args=(1,), arg3=1)
assert_identical(expected, actual)
-def test_ds_groupby_apply_func_args():
+def test_ds_groupby_map_func_args():
def func(arg1, arg2, arg3=0):
return arg1 + arg2 + arg3
dataset = xr.Dataset({"foo": ("x", [1, 1, 1])}, {"x": [1, 2, 3]})
expected = xr.Dataset({"foo": ("x", [3, 3, 3])}, {"x": [1, 2, 3]})
- actual = dataset.groupby("x").apply(func, args=(1,), arg3=1)
+ actual = dataset.groupby("x").map(func, args=(1,), arg3=1)
assert_identical(expected, actual)
@@ -285,7 +285,7 @@ def test_groupby_drops_nans():
expected.variable.values[0, 0, :] = np.nan
expected.variable.values[-1, -1, :] = np.nan
expected.variable.values[3, 0, :] = np.nan
- actual = grouped.apply(lambda x: x).transpose(*ds.variable.dims)
+ actual = grouped.map(lambda x: x).transpose(*ds.variable.dims)
assert_identical(actual, expected)
# reduction along grouped dimension
diff --git a/xarray/tests/test_sparse.py b/xarray/tests/test_sparse.py
index 8e2d4b8e064..a31da162487 100644
--- a/xarray/tests/test_sparse.py
+++ b/xarray/tests/test_sparse.py
@@ -339,7 +339,7 @@ def test_dataarray_property(prop):
(do("copy"), True),
(do("count"), False),
(do("diff", "x"), True),
- (do("drop", "x"), True),
+ (do("drop_vars", "x"), True),
(do("expand_dims", {"z": 2}, axis=2), True),
(do("get_axis_num", "x"), False),
(do("get_index", "x"), False),
|
[
{
"path": "doc/computation.rst",
"old_path": "a/doc/computation.rst",
"new_path": "b/doc/computation.rst",
"metadata": "diff --git a/doc/computation.rst b/doc/computation.rst\nindex ae5f4bc5c66..d477cb63d72 100644\n--- a/doc/computation.rst\n+++ b/doc/computation.rst\n@@ -462,13 +462,13 @@ Datasets support most of the same methods found on data arrays:\n abs(ds)\n \n Datasets also support NumPy ufuncs (requires NumPy v1.13 or newer), or\n-alternatively you can use :py:meth:`~xarray.Dataset.apply` to apply a function\n+alternatively you can use :py:meth:`~xarray.Dataset.map` to map a function\n to each variable in a dataset:\n \n .. ipython:: python\n \n np.sin(ds)\n- ds.apply(np.sin)\n+ ds.map(np.sin)\n \n Datasets also use looping over variables for *broadcasting* in binary\n arithmetic. You can do arithmetic between any ``DataArray`` and a dataset:\n"
},
{
"path": "doc/groupby.rst",
"old_path": "a/doc/groupby.rst",
"new_path": "b/doc/groupby.rst",
"metadata": "diff --git a/doc/groupby.rst b/doc/groupby.rst\nindex 52a27f4f160..f5943703765 100644\n--- a/doc/groupby.rst\n+++ b/doc/groupby.rst\n@@ -35,10 +35,11 @@ Let's create a simple example dataset:\n \n .. ipython:: python\n \n- ds = xr.Dataset({'foo': (('x', 'y'), np.random.rand(4, 3))},\n- coords={'x': [10, 20, 30, 40],\n- 'letters': ('x', list('abba'))})\n- arr = ds['foo']\n+ ds = xr.Dataset(\n+ {\"foo\": ((\"x\", \"y\"), np.random.rand(4, 3))},\n+ coords={\"x\": [10, 20, 30, 40], \"letters\": (\"x\", list(\"abba\"))},\n+ )\n+ arr = ds[\"foo\"]\n ds\n \n If we groupby the name of a variable or coordinate in a dataset (we can also\n@@ -93,7 +94,7 @@ Apply\n ~~~~~\n \n To apply a function to each group, you can use the flexible\n-:py:meth:`~xarray.DatasetGroupBy.apply` method. The resulting objects are automatically\n+:py:meth:`~xarray.DatasetGroupBy.map` method. The resulting objects are automatically\n concatenated back together along the group axis:\n \n .. ipython:: python\n@@ -101,7 +102,7 @@ concatenated back together along the group axis:\n def standardize(x):\n return (x - x.mean()) / x.std()\n \n- arr.groupby('letters').apply(standardize)\n+ arr.groupby('letters').map(standardize)\n \n GroupBy objects also have a :py:meth:`~xarray.DatasetGroupBy.reduce` method and\n methods like :py:meth:`~xarray.DatasetGroupBy.mean` as shortcuts for applying an\n@@ -202,7 +203,7 @@ __ http://cfconventions.org/cf-conventions/v1.6.0/cf-conventions.html#_two_dimen\n dims=['ny','nx'])\n da\n da.groupby('lon').sum(...)\n- da.groupby('lon').apply(lambda x: x - x.mean(), shortcut=False)\n+ da.groupby('lon').map(lambda x: x - x.mean(), shortcut=False)\n \n Because multidimensional groups have the ability to generate a very large\n number of bins, coarse-binning via :py:meth:`~xarray.Dataset.groupby_bins`\n"
},
{
"path": "doc/howdoi.rst",
"old_path": "a/doc/howdoi.rst",
"new_path": "b/doc/howdoi.rst",
"metadata": "diff --git a/doc/howdoi.rst b/doc/howdoi.rst\nindex 721d1323e73..91644ba2718 100644\n--- a/doc/howdoi.rst\n+++ b/doc/howdoi.rst\n@@ -44,7 +44,7 @@ How do I ...\n * - convert a possibly irregularly sampled timeseries to a regularly sampled timeseries\n - :py:meth:`DataArray.resample`, :py:meth:`Dataset.resample` (see :ref:`resampling` for more)\n * - apply a function on all data variables in a Dataset\n- - :py:meth:`Dataset.apply`\n+ - :py:meth:`Dataset.map`\n * - write xarray objects with complex values to a netCDF file\n - :py:func:`Dataset.to_netcdf`, :py:func:`DataArray.to_netcdf` specifying ``engine=\"h5netcdf\", invalid_netcdf=True``\n * - make xarray objects look like other xarray objects\n"
},
{
"path": "doc/quick-overview.rst",
"old_path": "a/doc/quick-overview.rst",
"new_path": "b/doc/quick-overview.rst",
"metadata": "diff --git a/doc/quick-overview.rst b/doc/quick-overview.rst\nindex 7d84199323d..741b3d1a5fe 100644\n--- a/doc/quick-overview.rst\n+++ b/doc/quick-overview.rst\n@@ -142,7 +142,7 @@ xarray supports grouped operations using a very similar API to pandas (see :ref:\n labels = xr.DataArray(['E', 'F', 'E'], [data.coords['y']], name='labels')\n labels\n data.groupby(labels).mean('y')\n- data.groupby(labels).apply(lambda x: x - x.min())\n+ data.groupby(labels).map(lambda x: x - x.min())\n \n Plotting\n --------\n"
},
{
"path": "doc/whats-new.rst",
"old_path": "a/doc/whats-new.rst",
"new_path": "b/doc/whats-new.rst",
"metadata": "diff --git a/doc/whats-new.rst b/doc/whats-new.rst\nindex 04fe88e9993..b572b1dda67 100644\n--- a/doc/whats-new.rst\n+++ b/doc/whats-new.rst\n@@ -44,6 +44,13 @@ New Features\n option for dropping either labels or variables, but using the more specific methods is encouraged.\n (:pull:`3475`)\n By `Maximilian Roos <https://github.com/max-sixty>`_\n+- :py:meth:`Dataset.map` & :py:meth:`GroupBy.map` & :py:meth:`Resample.map` have been added for \n+ mapping / applying a function over each item in the collection, reflecting the widely used\n+ and least surprising name for this operation.\n+ The existing ``apply`` methods remain for backward compatibility, though using the ``map``\n+ methods is encouraged.\n+ (:pull:`3459`)\n+ By `Maximilian Roos <https://github.com/max-sixty>`_\n - :py:meth:`Dataset.transpose` and :py:meth:`DataArray.transpose` now support an ellipsis (`...`)\n to represent all 'other' dimensions. For example, to move one dimension to the front,\n use `.transpose('x', ...)`. (:pull:`3421`)\n"
}
] |
0014
|
bb89534687ee5dac54d87c22154d3cfeb030ce21
|
[
"xarray/tests/test_dataset.py::test_rolling_reduce[max-1-None-False-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-3-1-False-2]",
"xarray/tests/test_groupby.py::test_groupby_da_datetime",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-4-3-True-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[median-3-2-True-2]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z1-None-True-std]",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-3-3-False-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_dataarray_diff_n1",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z1-1-None-median]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-1-1-False]",
"xarray/tests/test_dataset.py::TestDataset::test_stack",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-1-3-True-2]",
"xarray/tests/test_dataset.py::test_dataset_constructor_aligns_to_explicit_coords[coords1-unaligned_coords5]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-3-1-True-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_sel_dataarray",
"xarray/tests/test_dataset.py::test_dir_non_string[None]",
"xarray/tests/test_dataset.py::test_rolling_reduce[median-2-1-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-1-3-True]",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-3-1-True-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[sum-3-2-True]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z1-None-True-median]",
"xarray/tests/test_dataset.py::test_rolling_reduce[sum-4-None-False-1]",
"xarray/tests/test_dataset.py::TestDataset::test_reindex_like_fill_value[2]",
"xarray/tests/test_dataset.py::TestDataset::test_sel",
"xarray/tests/test_dataarray.py::TestDataArray::test_align_mixed_indexes",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-2-None-True-1]",
"xarray/tests/test_dataset.py::test_differentiate_datetime[True]",
"xarray/tests/test_dataset.py::test_rolling_reduce[sum-3-3-True-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[sum-4-1-True]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-None-False-max]",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-4-3-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_pandas_compat[4-1-True]",
"xarray/tests/test_dataset.py::test_rolling_reduce[mean-3-2-False-2]",
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"xarray/tests/test_dataset.py::TestDataset::test_resample_by_last_discarding_attrs",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-None-None-mean]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-1-1-True-1]",
"xarray/tests/test_dataset.py::TestDataset::test_asarray",
"xarray/tests/test_dataarray.py::TestDataArray::test_stack_unstack",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-3-3-False-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-3-2-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-1-None-False-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-4-1-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-2-3-True-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_reset_coords",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-4-2-True-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-3-1-False-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-2-2-True-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-3-None-False-1]",
"xarray/tests/test_dataset.py::TestDataset::test_groupby_math",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-2-2-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_pandas_compat[4-1-False]",
"xarray/tests/test_dataarray.py::TestDataArray::test_broadcast_arrays_nocopy",
"xarray/tests/test_dataarray.py::TestDataArray::test_inplace_math_automatic_alignment",
"xarray/tests/test_dataset.py::test_dataset_constructor_aligns_to_explicit_coords[coords1-unaligned_coords8]",
"xarray/tests/test_dataarray.py::TestDataArray::test_swap_dims",
"xarray/tests/test_dataarray.py::TestDataArray::test_loc_assign",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[sum-1-3-False]",
"xarray/tests/test_groupby.py::test_groupby_input_mutation",
"xarray/tests/test_dataarray.py::TestDataArray::test_expand_dims_error",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-2-None-True-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-3-3-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-1-None-True-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-1-1-True-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_align_without_indexes_errors",
"xarray/tests/test_dataarray.py::test_rolling_wrapped_bottleneck[1-1-None-min]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-2-1-False]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-2-1-False-2]",
"xarray/tests/test_dataset.py::test_coarsen[1-pad-right-False]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-1-True-mean]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-1-None-sum]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-2-3-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-2-None-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[median-4-3-True-1]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-None-True-std]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-3-None-True-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[min-1-None-True-1]"
] |
[
"xarray/tests/test_dataarray.py::TestDataArray::test_groupby_map_center",
"xarray/tests/test_dataarray.py::TestDataArray::test_groupby_map_changes_metadata",
"xarray/tests/test_dataarray.py::TestDataArray::test_da_resample_func_args",
"xarray/tests/test_dataarray.py::TestDataArray::test_groupby_map_identity",
"xarray/tests/test_dataset.py::TestDataset::test_ds_resample_apply_func_args",
"xarray/tests/test_dataarray.py::TestDataArray::test_groupby_bins_multidim",
"xarray/tests/test_dataarray.py::TestDataArray::test_groupby_restore_dim_order",
"xarray/tests/test_groupby.py::test_da_groupby_map_func_args",
"xarray/tests/test_dataset.py::TestDataset::test_map",
"xarray/tests/test_dataset.py::TestDataset::test_dataset_array_math",
"xarray/tests/test_dataarray.py::TestDataArray::test_groupby_restore_coord_dims",
"xarray/tests/test_dataset.py::TestDataset::test_apply_pending_deprecated_map",
"xarray/tests/test_groupby.py::test_groupby_drops_nans",
"xarray/tests/test_dataset.py::TestDataset::test_dataset_dataset_math",
"xarray/tests/test_dataset.py::TestDataset::test_groupby",
"xarray/tests/test_dataset.py::TestDataset::test_groupby_returns_new_type",
"xarray/tests/test_dataarray.py::TestDataArray::test_groupby_bins",
"xarray/tests/test_dataset.py::TestDataset::test_unary_ops",
"xarray/tests/test_dataarray.py::TestDataArray::test_groupby_sum",
"xarray/tests/test_dataarray.py::TestDataArray::test_groupby_map_ndarray",
"xarray/tests/test_groupby.py::test_ds_groupby_map_func_args",
"xarray/tests/test_groupby.py::test_multi_index_groupby_map",
"xarray/tests/test_dataarray.py::TestDataArray::test_groupby_multidim_map",
"xarray/tests/test_dataset.py::TestDataset::test_dataset_transpose"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/computation.rst",
"old_path": "a/doc/computation.rst",
"new_path": "b/doc/computation.rst",
"metadata": "diff --git a/doc/computation.rst b/doc/computation.rst\nindex ae5f4bc5c66..d477cb63d72 100644\n--- a/doc/computation.rst\n+++ b/doc/computation.rst\n@@ -462,13 +462,13 @@ Datasets support most of the same methods found on data arrays:\n abs(ds)\n \n Datasets also support NumPy ufuncs (requires NumPy v1.13 or newer), or\n-alternatively you can use :py:meth:`~xarray.Dataset.apply` to apply a function\n+alternatively you can use :py:meth:`~xarray.Dataset.map` to map a function\n to each variable in a dataset:\n \n .. ipython:: python\n \n np.sin(ds)\n- ds.apply(np.sin)\n+ ds.map(np.sin)\n \n Datasets also use looping over variables for *broadcasting* in binary\n arithmetic. You can do arithmetic between any ``DataArray`` and a dataset:\n"
},
{
"path": "doc/groupby.rst",
"old_path": "a/doc/groupby.rst",
"new_path": "b/doc/groupby.rst",
"metadata": "diff --git a/doc/groupby.rst b/doc/groupby.rst\nindex 52a27f4f160..f5943703765 100644\n--- a/doc/groupby.rst\n+++ b/doc/groupby.rst\n@@ -35,10 +35,11 @@ Let's create a simple example dataset:\n \n .. ipython:: python\n \n- ds = xr.Dataset({'foo': (('x', 'y'), np.random.rand(4, 3))},\n- coords={'x': [10, 20, 30, 40],\n- 'letters': ('x', list('abba'))})\n- arr = ds['foo']\n+ ds = xr.Dataset(\n+ {\"foo\": ((\"x\", \"y\"), np.random.rand(4, 3))},\n+ coords={\"x\": [10, 20, 30, 40], \"letters\": (\"x\", list(\"abba\"))},\n+ )\n+ arr = ds[\"foo\"]\n ds\n \n If we groupby the name of a variable or coordinate in a dataset (we can also\n@@ -93,7 +94,7 @@ Apply\n ~~~~~\n \n To apply a function to each group, you can use the flexible\n-:py:meth:`~xarray.DatasetGroupBy.apply` method. The resulting objects are automatically\n+:py:meth:`~xarray.DatasetGroupBy.map` method. The resulting objects are automatically\n concatenated back together along the group axis:\n \n .. ipython:: python\n@@ -101,7 +102,7 @@ concatenated back together along the group axis:\n def standardize(x):\n return (x - x.mean()) / x.std()\n \n- arr.groupby('letters').apply(standardize)\n+ arr.groupby('letters').map(standardize)\n \n GroupBy objects also have a :py:meth:`~xarray.DatasetGroupBy.reduce` method and\n methods like :py:meth:`~xarray.DatasetGroupBy.mean` as shortcuts for applying an\n@@ -202,7 +203,7 @@ __ http://cfconventions.org/cf-conventions/v1.6.0/cf-conventions.html#_two_dimen\n dims=['ny','nx'])\n da\n da.groupby('lon').sum(...)\n- da.groupby('lon').apply(lambda x: x - x.mean(), shortcut=False)\n+ da.groupby('lon').map(lambda x: x - x.mean(), shortcut=False)\n \n Because multidimensional groups have the ability to generate a very large\n number of bins, coarse-binning via :py:meth:`~xarray.Dataset.groupby_bins`\n"
},
{
"path": "doc/howdoi.rst",
"old_path": "a/doc/howdoi.rst",
"new_path": "b/doc/howdoi.rst",
"metadata": "diff --git a/doc/howdoi.rst b/doc/howdoi.rst\nindex 721d1323e73..91644ba2718 100644\n--- a/doc/howdoi.rst\n+++ b/doc/howdoi.rst\n@@ -44,7 +44,7 @@ How do I ...\n * - convert a possibly irregularly sampled timeseries to a regularly sampled timeseries\n - :py:meth:`DataArray.resample`, :py:meth:`Dataset.resample` (see :ref:`resampling` for more)\n * - apply a function on all data variables in a Dataset\n- - :py:meth:`Dataset.apply`\n+ - :py:meth:`Dataset.map`\n * - write xarray objects with complex values to a netCDF file\n - :py:func:`Dataset.to_netcdf`, :py:func:`DataArray.to_netcdf` specifying ``engine=\"h5netcdf\", invalid_netcdf=True``\n * - make xarray objects look like other xarray objects\n"
},
{
"path": "doc/quick-overview.rst",
"old_path": "a/doc/quick-overview.rst",
"new_path": "b/doc/quick-overview.rst",
"metadata": "diff --git a/doc/quick-overview.rst b/doc/quick-overview.rst\nindex 7d84199323d..741b3d1a5fe 100644\n--- a/doc/quick-overview.rst\n+++ b/doc/quick-overview.rst\n@@ -142,7 +142,7 @@ xarray supports grouped operations using a very similar API to pandas (see :ref:\n labels = xr.DataArray(['E', 'F', 'E'], [data.coords['y']], name='labels')\n labels\n data.groupby(labels).mean('y')\n- data.groupby(labels).apply(lambda x: x - x.min())\n+ data.groupby(labels).map(lambda x: x - x.min())\n \n Plotting\n --------\n"
},
{
"path": "doc/whats-new.rst",
"old_path": "a/doc/whats-new.rst",
"new_path": "b/doc/whats-new.rst",
"metadata": "diff --git a/doc/whats-new.rst b/doc/whats-new.rst\nindex 04fe88e9993..b572b1dda67 100644\n--- a/doc/whats-new.rst\n+++ b/doc/whats-new.rst\n@@ -44,6 +44,13 @@ New Features\n option for dropping either labels or variables, but using the more specific methods is encouraged.\n (:pull:`<PRID>`)\n By `<NAME>`_\n+- :py:meth:`Dataset.map` & :py:meth:`GroupBy.map` & :py:meth:`Resample.map` have been added for \n+ mapping / applying a function over each item in the collection, reflecting the widely used\n+ and least surprising name for this operation.\n+ The existing ``apply`` methods remain for backward compatibility, though using the ``map``\n+ methods is encouraged.\n+ (:pull:`<PRID>`)\n+ By `<NAME>`_\n - :py:meth:`Dataset.transpose` and :py:meth:`DataArray.transpose` now support an ellipsis (`...`)\n to represent all 'other' dimensions. For example, to move one dimension to the front,\n use `.transpose('x', ...)`. (:pull:`<PRID>`)\n"
}
] |
diff --git a/doc/computation.rst b/doc/computation.rst
index ae5f4bc5c66..d477cb63d72 100644
--- a/doc/computation.rst
+++ b/doc/computation.rst
@@ -462,13 +462,13 @@ Datasets support most of the same methods found on data arrays:
abs(ds)
Datasets also support NumPy ufuncs (requires NumPy v1.13 or newer), or
-alternatively you can use :py:meth:`~xarray.Dataset.apply` to apply a function
+alternatively you can use :py:meth:`~xarray.Dataset.map` to map a function
to each variable in a dataset:
.. ipython:: python
np.sin(ds)
- ds.apply(np.sin)
+ ds.map(np.sin)
Datasets also use looping over variables for *broadcasting* in binary
arithmetic. You can do arithmetic between any ``DataArray`` and a dataset:
diff --git a/doc/groupby.rst b/doc/groupby.rst
index 52a27f4f160..f5943703765 100644
--- a/doc/groupby.rst
+++ b/doc/groupby.rst
@@ -35,10 +35,11 @@ Let's create a simple example dataset:
.. ipython:: python
- ds = xr.Dataset({'foo': (('x', 'y'), np.random.rand(4, 3))},
- coords={'x': [10, 20, 30, 40],
- 'letters': ('x', list('abba'))})
- arr = ds['foo']
+ ds = xr.Dataset(
+ {"foo": (("x", "y"), np.random.rand(4, 3))},
+ coords={"x": [10, 20, 30, 40], "letters": ("x", list("abba"))},
+ )
+ arr = ds["foo"]
ds
If we groupby the name of a variable or coordinate in a dataset (we can also
@@ -93,7 +94,7 @@ Apply
~~~~~
To apply a function to each group, you can use the flexible
-:py:meth:`~xarray.DatasetGroupBy.apply` method. The resulting objects are automatically
+:py:meth:`~xarray.DatasetGroupBy.map` method. The resulting objects are automatically
concatenated back together along the group axis:
.. ipython:: python
@@ -101,7 +102,7 @@ concatenated back together along the group axis:
def standardize(x):
return (x - x.mean()) / x.std()
- arr.groupby('letters').apply(standardize)
+ arr.groupby('letters').map(standardize)
GroupBy objects also have a :py:meth:`~xarray.DatasetGroupBy.reduce` method and
methods like :py:meth:`~xarray.DatasetGroupBy.mean` as shortcuts for applying an
@@ -202,7 +203,7 @@ __ http://cfconventions.org/cf-conventions/v1.6.0/cf-conventions.html#_two_dimen
dims=['ny','nx'])
da
da.groupby('lon').sum(...)
- da.groupby('lon').apply(lambda x: x - x.mean(), shortcut=False)
+ da.groupby('lon').map(lambda x: x - x.mean(), shortcut=False)
Because multidimensional groups have the ability to generate a very large
number of bins, coarse-binning via :py:meth:`~xarray.Dataset.groupby_bins`
diff --git a/doc/howdoi.rst b/doc/howdoi.rst
index 721d1323e73..91644ba2718 100644
--- a/doc/howdoi.rst
+++ b/doc/howdoi.rst
@@ -44,7 +44,7 @@ How do I ...
* - convert a possibly irregularly sampled timeseries to a regularly sampled timeseries
- :py:meth:`DataArray.resample`, :py:meth:`Dataset.resample` (see :ref:`resampling` for more)
* - apply a function on all data variables in a Dataset
- - :py:meth:`Dataset.apply`
+ - :py:meth:`Dataset.map`
* - write xarray objects with complex values to a netCDF file
- :py:func:`Dataset.to_netcdf`, :py:func:`DataArray.to_netcdf` specifying ``engine="h5netcdf", invalid_netcdf=True``
* - make xarray objects look like other xarray objects
diff --git a/doc/quick-overview.rst b/doc/quick-overview.rst
index 7d84199323d..741b3d1a5fe 100644
--- a/doc/quick-overview.rst
+++ b/doc/quick-overview.rst
@@ -142,7 +142,7 @@ xarray supports grouped operations using a very similar API to pandas (see :ref:
labels = xr.DataArray(['E', 'F', 'E'], [data.coords['y']], name='labels')
labels
data.groupby(labels).mean('y')
- data.groupby(labels).apply(lambda x: x - x.min())
+ data.groupby(labels).map(lambda x: x - x.min())
Plotting
--------
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index 04fe88e9993..b572b1dda67 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -44,6 +44,13 @@ New Features
option for dropping either labels or variables, but using the more specific methods is encouraged.
(:pull:`<PRID>`)
By `<NAME>`_
+- :py:meth:`Dataset.map` & :py:meth:`GroupBy.map` & :py:meth:`Resample.map` have been added for
+ mapping / applying a function over each item in the collection, reflecting the widely used
+ and least surprising name for this operation.
+ The existing ``apply`` methods remain for backward compatibility, though using the ``map``
+ methods is encouraged.
+ (:pull:`<PRID>`)
+ By `<NAME>`_
- :py:meth:`Dataset.transpose` and :py:meth:`DataArray.transpose` now support an ellipsis (`...`)
to represent all 'other' dimensions. For example, to move one dimension to the front,
use `.transpose('x', ...)`. (:pull:`<PRID>`)
|
pydata/xarray
|
pydata__xarray-3421
|
https://github.com/pydata/xarray/pull/3421
|
diff --git a/doc/reshaping.rst b/doc/reshaping.rst
index 51202f9be41..455a24f9216 100644
--- a/doc/reshaping.rst
+++ b/doc/reshaping.rst
@@ -18,12 +18,14 @@ Reordering dimensions
---------------------
To reorder dimensions on a :py:class:`~xarray.DataArray` or across all variables
-on a :py:class:`~xarray.Dataset`, use :py:meth:`~xarray.DataArray.transpose`:
+on a :py:class:`~xarray.Dataset`, use :py:meth:`~xarray.DataArray.transpose`. An
+ellipsis (`...`) can be use to represent all other dimensions:
.. ipython:: python
ds = xr.Dataset({'foo': (('x', 'y', 'z'), [[[42]]]), 'bar': (('y', 'z'), [[24]])})
ds.transpose('y', 'z', 'x')
+ ds.transpose(..., 'x') # equivalent
ds.transpose() # reverses all dimensions
Expand and squeeze dimensions
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index dea110b5e46..cced7276ff3 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -25,6 +25,10 @@ Breaking changes
New Features
~~~~~~~~~~~~
+- :py:meth:`Dataset.transpose` and :py:meth:`DataArray.transpose` now support an ellipsis (`...`)
+ to represent all 'other' dimensions. For example, to move one dimension to the front,
+ use `.transpose('x', ...)`. (:pull:`3421`)
+ By `Maximilian Roos <https://github.com/max-sixty>`_
- Changed `xr.ALL_DIMS` to equal python's `Ellipsis` (`...`), and changed internal usages to use
`...` directly. As before, you can use this to instruct a `groupby` operation
to reduce over all dimensions. While we have no plans to remove `xr.ALL_DIMS`, we suggest
diff --git a/setup.cfg b/setup.cfg
index eee8b2477b2..fec2ca6bbe4 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -117,4 +117,7 @@ tag_prefix = v
parentdir_prefix = xarray-
[aliases]
-test = pytest
\ No newline at end of file
+test = pytest
+
+[pytest-watch]
+nobeep = True
\ No newline at end of file
diff --git a/xarray/core/dataarray.py b/xarray/core/dataarray.py
index 5fccb9236e8..33dcad13204 100644
--- a/xarray/core/dataarray.py
+++ b/xarray/core/dataarray.py
@@ -1863,12 +1863,7 @@ def transpose(self, *dims: Hashable, transpose_coords: bool = None) -> "DataArra
Dataset.transpose
"""
if dims:
- if set(dims) ^ set(self.dims):
- raise ValueError(
- "arguments to transpose (%s) must be "
- "permuted array dimensions (%s)" % (dims, tuple(self.dims))
- )
-
+ dims = tuple(utils.infix_dims(dims, self.dims))
variable = self.variable.transpose(*dims)
if transpose_coords:
coords: Dict[Hashable, Variable] = {}
diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index 55ac0bc6135..2a0464515c6 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -3712,14 +3712,14 @@ def transpose(self, *dims: Hashable) -> "Dataset":
DataArray.transpose
"""
if dims:
- if set(dims) ^ set(self.dims):
+ if set(dims) ^ set(self.dims) and ... not in dims:
raise ValueError(
"arguments to transpose (%s) must be "
"permuted dataset dimensions (%s)" % (dims, tuple(self.dims))
)
ds = self.copy()
for name, var in self._variables.items():
- var_dims = tuple(dim for dim in dims if dim in var.dims)
+ var_dims = tuple(dim for dim in dims if dim in (var.dims + (...,)))
ds._variables[name] = var.transpose(*var_dims)
return ds
diff --git a/xarray/core/utils.py b/xarray/core/utils.py
index 6befe0b5efc..492c595a887 100644
--- a/xarray/core/utils.py
+++ b/xarray/core/utils.py
@@ -10,6 +10,7 @@
AbstractSet,
Any,
Callable,
+ Collection,
Container,
Dict,
Hashable,
@@ -660,6 +661,30 @@ def __len__(self) -> int:
return len(self._data) - num_hidden
+def infix_dims(dims_supplied: Collection, dims_all: Collection) -> Iterator:
+ """
+ Resolves a supplied list containing an ellispsis representing other items, to
+ a generator with the 'realized' list of all items
+ """
+ if ... in dims_supplied:
+ if len(set(dims_all)) != len(dims_all):
+ raise ValueError("Cannot use ellipsis with repeated dims")
+ if len([d for d in dims_supplied if d == ...]) > 1:
+ raise ValueError("More than one ellipsis supplied")
+ other_dims = [d for d in dims_all if d not in dims_supplied]
+ for d in dims_supplied:
+ if d == ...:
+ yield from other_dims
+ else:
+ yield d
+ else:
+ if set(dims_supplied) ^ set(dims_all):
+ raise ValueError(
+ f"{dims_supplied} must be a permuted list of {dims_all}, unless `...` is included"
+ )
+ yield from dims_supplied
+
+
def get_temp_dimname(dims: Container[Hashable], new_dim: Hashable) -> Hashable:
""" Get an new dimension name based on new_dim, that is not used in dims.
If the same name exists, we add an underscore(s) in the head.
diff --git a/xarray/core/variable.py b/xarray/core/variable.py
index 93ad1eafb97..7d03fd58d39 100644
--- a/xarray/core/variable.py
+++ b/xarray/core/variable.py
@@ -25,6 +25,7 @@
OrderedSet,
decode_numpy_dict_values,
either_dict_or_kwargs,
+ infix_dims,
ensure_us_time_resolution,
)
@@ -1228,6 +1229,7 @@ def transpose(self, *dims) -> "Variable":
"""
if len(dims) == 0:
dims = self.dims[::-1]
+ dims = tuple(infix_dims(dims, self.dims))
axes = self.get_axis_num(dims)
if len(dims) < 2: # no need to transpose if only one dimension
return self.copy(deep=False)
|
diff --git a/xarray/tests/__init__.py b/xarray/tests/__init__.py
index 88476e5e730..f85a33f7a3c 100644
--- a/xarray/tests/__init__.py
+++ b/xarray/tests/__init__.py
@@ -158,18 +158,21 @@ def source_ndarray(array):
def assert_equal(a, b):
+ __tracebackhide__ = True
xarray.testing.assert_equal(a, b)
xarray.testing._assert_internal_invariants(a)
xarray.testing._assert_internal_invariants(b)
def assert_identical(a, b):
+ __tracebackhide__ = True
xarray.testing.assert_identical(a, b)
xarray.testing._assert_internal_invariants(a)
xarray.testing._assert_internal_invariants(b)
def assert_allclose(a, b, **kwargs):
+ __tracebackhide__ = True
xarray.testing.assert_allclose(a, b, **kwargs)
xarray.testing._assert_internal_invariants(a)
xarray.testing._assert_internal_invariants(b)
diff --git a/xarray/tests/test_dataarray.py b/xarray/tests/test_dataarray.py
index 101bb44660c..ad474d533be 100644
--- a/xarray/tests/test_dataarray.py
+++ b/xarray/tests/test_dataarray.py
@@ -2068,6 +2068,10 @@ def test_transpose(self):
)
assert_equal(expected, actual)
+ # same as previous but with ellipsis
+ actual = da.transpose("z", ..., "x", transpose_coords=True)
+ assert_equal(expected, actual)
+
with pytest.raises(ValueError):
da.transpose("x", "y")
diff --git a/xarray/tests/test_dataset.py b/xarray/tests/test_dataset.py
index b3ffdf68e3f..647eb733adb 100644
--- a/xarray/tests/test_dataset.py
+++ b/xarray/tests/test_dataset.py
@@ -4675,6 +4675,10 @@ def test_dataset_transpose(self):
)
assert_identical(expected, actual)
+ actual = ds.transpose(...)
+ expected = ds
+ assert_identical(expected, actual)
+
actual = ds.transpose("x", "y")
expected = ds.apply(lambda x: x.transpose("x", "y", transpose_coords=True))
assert_identical(expected, actual)
@@ -4690,13 +4694,32 @@ def test_dataset_transpose(self):
expected_dims = tuple(d for d in new_order if d in ds[k].dims)
assert actual[k].dims == expected_dims
- with raises_regex(ValueError, "arguments to transpose"):
+ # same as above but with ellipsis
+ new_order = ("dim2", "dim3", "dim1", "time")
+ actual = ds.transpose("dim2", "dim3", ...)
+ for k in ds.variables:
+ expected_dims = tuple(d for d in new_order if d in ds[k].dims)
+ assert actual[k].dims == expected_dims
+
+ with raises_regex(ValueError, "permuted"):
ds.transpose("dim1", "dim2", "dim3")
- with raises_regex(ValueError, "arguments to transpose"):
+ with raises_regex(ValueError, "permuted"):
ds.transpose("dim1", "dim2", "dim3", "time", "extra_dim")
assert "T" not in dir(ds)
+ def test_dataset_ellipsis_transpose_different_ordered_vars(self):
+ # https://github.com/pydata/xarray/issues/1081#issuecomment-544350457
+ ds = Dataset(
+ dict(
+ a=(("w", "x", "y", "z"), np.ones((2, 3, 4, 5))),
+ b=(("x", "w", "y", "z"), np.zeros((3, 2, 4, 5))),
+ )
+ )
+ result = ds.transpose(..., "z", "y")
+ assert list(result["a"].dims) == list("wxzy")
+ assert list(result["b"].dims) == list("xwzy")
+
def test_dataset_retains_period_index_on_transpose(self):
ds = create_test_data()
diff --git a/xarray/tests/test_utils.py b/xarray/tests/test_utils.py
index c36e8a1775d..5bb9deaf240 100644
--- a/xarray/tests/test_utils.py
+++ b/xarray/tests/test_utils.py
@@ -275,3 +275,27 @@ def test_either_dict_or_kwargs():
with pytest.raises(ValueError, match=r"foo"):
result = either_dict_or_kwargs(dict(a=1), dict(a=1), "foo")
+
+
+@pytest.mark.parametrize(
+ ["supplied", "all_", "expected"],
+ [
+ (list("abc"), list("abc"), list("abc")),
+ (["a", ..., "c"], list("abc"), list("abc")),
+ (["a", ...], list("abc"), list("abc")),
+ (["c", ...], list("abc"), list("cab")),
+ ([..., "b"], list("abc"), list("acb")),
+ ([...], list("abc"), list("abc")),
+ ],
+)
+def test_infix_dims(supplied, all_, expected):
+ result = list(utils.infix_dims(supplied, all_))
+ assert result == expected
+
+
+@pytest.mark.parametrize(
+ ["supplied", "all_"], [([..., ...], list("abc")), ([...], list("aac"))]
+)
+def test_infix_dims_errors(supplied, all_):
+ with pytest.raises(ValueError):
+ list(utils.infix_dims(supplied, all_))
diff --git a/xarray/tests/test_variable.py b/xarray/tests/test_variable.py
index 78723eda013..528027ed149 100644
--- a/xarray/tests/test_variable.py
+++ b/xarray/tests/test_variable.py
@@ -1280,6 +1280,9 @@ def test_transpose(self):
w2 = Variable(["d", "b", "c", "a"], np.einsum("abcd->dbca", x))
assert w2.shape == (5, 3, 4, 2)
assert_identical(w2, w.transpose("d", "b", "c", "a"))
+ assert_identical(w2, w.transpose("d", ..., "a"))
+ assert_identical(w2, w.transpose("d", "b", "c", ...))
+ assert_identical(w2, w.transpose(..., "b", "c", "a"))
assert_identical(w, w2.transpose("a", "b", "c", "d"))
w3 = Variable(["b", "c", "d", "a"], np.einsum("abcd->bcda", x))
assert_identical(w, w3.transpose("a", "b", "c", "d"))
|
[
{
"path": "doc/reshaping.rst",
"old_path": "a/doc/reshaping.rst",
"new_path": "b/doc/reshaping.rst",
"metadata": "diff --git a/doc/reshaping.rst b/doc/reshaping.rst\nindex 51202f9be41..455a24f9216 100644\n--- a/doc/reshaping.rst\n+++ b/doc/reshaping.rst\n@@ -18,12 +18,14 @@ Reordering dimensions\n ---------------------\n \n To reorder dimensions on a :py:class:`~xarray.DataArray` or across all variables\n-on a :py:class:`~xarray.Dataset`, use :py:meth:`~xarray.DataArray.transpose`:\n+on a :py:class:`~xarray.Dataset`, use :py:meth:`~xarray.DataArray.transpose`. An \n+ellipsis (`...`) can be use to represent all other dimensions:\n \n .. ipython:: python\n \n ds = xr.Dataset({'foo': (('x', 'y', 'z'), [[[42]]]), 'bar': (('y', 'z'), [[24]])})\n ds.transpose('y', 'z', 'x')\n+ ds.transpose(..., 'x') # equivalent\n ds.transpose() # reverses all dimensions\n \n Expand and squeeze dimensions\n"
},
{
"path": "doc/whats-new.rst",
"old_path": "a/doc/whats-new.rst",
"new_path": "b/doc/whats-new.rst",
"metadata": "diff --git a/doc/whats-new.rst b/doc/whats-new.rst\nindex dea110b5e46..cced7276ff3 100644\n--- a/doc/whats-new.rst\n+++ b/doc/whats-new.rst\n@@ -25,6 +25,10 @@ Breaking changes\n \n New Features\n ~~~~~~~~~~~~\n+- :py:meth:`Dataset.transpose` and :py:meth:`DataArray.transpose` now support an ellipsis (`...`)\n+ to represent all 'other' dimensions. For example, to move one dimension to the front,\n+ use `.transpose('x', ...)`. (:pull:`3421`)\n+ By `Maximilian Roos <https://github.com/max-sixty>`_\n - Changed `xr.ALL_DIMS` to equal python's `Ellipsis` (`...`), and changed internal usages to use\n `...` directly. As before, you can use this to instruct a `groupby` operation\n to reduce over all dimensions. While we have no plans to remove `xr.ALL_DIMS`, we suggest\n"
}
] |
0014
|
fb0cf7b5fe56519a933ffcecbce9e9327fe236a6
|
[
"xarray/tests/test_dataset.py::test_rolling_reduce[max-1-None-False-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-3-1-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-4-3-True-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[median-3-2-True-2]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z1-None-True-std]",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-3-3-False-1]",
"xarray/tests/test_variable.py::TestIndexVariable::test_concat_number_strings",
"xarray/tests/test_dataarray.py::TestDataArray::test_dataarray_diff_n1",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z1-1-None-median]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-1-1-False]",
"xarray/tests/test_dataset.py::TestDataset::test_stack",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-1-3-True-2]",
"xarray/tests/test_dataset.py::test_dataset_constructor_aligns_to_explicit_coords[coords1-unaligned_coords5]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-3-1-True-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_sel_dataarray",
"xarray/tests/test_dataset.py::test_dir_non_string[None]",
"xarray/tests/test_dataset.py::test_rolling_reduce[median-2-1-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-1-3-True]",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-3-1-True-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[sum-3-2-True]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z1-None-True-median]",
"xarray/tests/test_variable.py::TestVariable::test_copy[int-True]",
"xarray/tests/test_dataset.py::test_rolling_reduce[sum-4-None-False-1]",
"xarray/tests/test_variable.py::TestVariable::test_set_dims_object_dtype",
"xarray/tests/test_dataset.py::TestDataset::test_reindex_like_fill_value[2]",
"xarray/tests/test_dataset.py::TestDataset::test_sel",
"xarray/tests/test_dataarray.py::TestDataArray::test_align_mixed_indexes",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-2-None-True-1]",
"xarray/tests/test_dataset.py::test_differentiate_datetime[True]",
"xarray/tests/test_dataset.py::test_rolling_reduce[sum-3-3-True-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[sum-4-1-True]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-None-False-max]",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-4-3-False-2]",
"xarray/tests/test_utils.py::test_is_grib_path",
"xarray/tests/test_dataarray.py::test_rolling_pandas_compat[4-1-True]",
"xarray/tests/test_dataset.py::test_rolling_reduce[mean-3-2-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-4-3-False]",
"xarray/tests/test_accessor_dt.py::TestDatetimeAccessor::test_rounders",
"xarray/tests/test_dataset.py::TestDataset::test_align_fill_value[2.0]",
"xarray/tests/test_dataset.py::TestDataset::test_coords_properties",
"xarray/tests/test_dataset.py::test_rolling_reduce[min-1-3-True-1]",
"xarray/tests/test_variable.py::TestVariable::test_shift2d",
"xarray/tests/test_dataset.py::test_rolling_reduce[sum-3-2-False-2]",
"xarray/tests/test_variable.py::TestIndexVariable::test_index_0d_not_a_time",
"xarray/tests/test_dataset.py::TestDataset::test_to_stacked_array_dtype_dims",
"xarray/tests/test_dataarray.py::test_rolling_wrapped_bottleneck[1-None-None-mean]",
"xarray/tests/test_dataset.py::TestDataset::test_to_and_from_dict_with_time_dim",
"xarray/tests/test_variable.py::TestVariable::test_rank",
"xarray/tests/test_dataarray.py::TestDataArray::test_attr_sources_multiindex",
"xarray/tests/test_dataarray.py::test_rolling_wrapped_bottleneck[1-1-None-max]",
"xarray/tests/test_variable.py::TestVariable::test_getitem_with_mask_size_zero",
"xarray/tests/test_dataarray.py::test_rolling_pandas_compat[3-3-True]",
"xarray/tests/test_dataset.py::test_rolling_reduce[min-4-None-False-1]",
"xarray/tests/test_dataset.py::TestDataset::test_to_stacked_array_name",
"xarray/tests/test_dataset.py::TestDataset::test_constructor_pandas_sequence",
"xarray/tests/test_dataset.py::test_rolling_reduce[median-1-1-True-1]",
"xarray/tests/test_variable.py::TestIndexVariable::test_multiindex",
"xarray/tests/test_dataset.py::TestDataset::test_roll_coords_none",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-3-None-True-2]",
"xarray/tests/test_variable.py::TestIndexVariable::test_equals_all_dtypes",
"xarray/tests/test_variable.py::TestVariable::test_setitem_fancy",
"xarray/tests/test_dataset.py::test_rolling_pandas_compat[4-1-True]",
"xarray/tests/test_dataset.py::test_rolling_reduce[sum-3-None-True-2]",
"xarray/tests/test_variable.py::TestVariable::test_timedelta64_conversion",
"xarray/tests/test_dataarray.py::TestDataArray::test_resample_first",
"xarray/tests/test_utils.py::Test_is_uniform_and_sorted::test_sorted_uniform",
"xarray/tests/test_dataset.py::TestDataset::test_reindex_method",
"xarray/tests/test_dataarray.py::test_rolling_wrapped_bottleneck[1-None-None-max]",
"xarray/tests/test_dataset.py::test_rolling_reduce[median-3-2-False-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-4-3-False-1]",
"xarray/tests/test_dataset.py::test_rolling_pandas_compat[1-1-True]",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-3-None-False-2]",
"xarray/tests/test_variable.py::TestVariable::test_pad",
"xarray/tests/test_variable.py::TestVariable::test_0d_timedelta",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-3-2-False-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-4-None-False-2]",
"xarray/tests/test_variable.py::TestIndexVariable::test_index_0d_datetime",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-1-3-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-1-2-True-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-4-1-True]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-3-None-False-1]",
"xarray/tests/test_dataset.py::test_coarsen[1-trim-left-False]",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-4-1-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-4-2-False-1]",
"xarray/tests/test_dataset.py::TestDataset::test_assign_multiindex_level",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-1-3-True-1]",
"xarray/tests/test_utils.py::TestDictionaries::test_ordered_dict_intersection",
"xarray/tests/test_dataset.py::test_rolling_reduce[min-4-3-True-2]",
"xarray/tests/test_dataset.py::test_rolling_pandas_compat[2-None-True]",
"xarray/tests/test_dataset.py::TestDataset::test_variable",
"xarray/tests/test_dataset.py::test_rolling_reduce[sum-3-1-False-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_where",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-1-2-False]",
"xarray/tests/test_dataset.py::test_rolling_reduce[min-1-2-True-2]",
"xarray/tests/test_variable.py::TestVariable::test_shift[fill_value0]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-3-2-True-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[min-2-1-False-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_dropna",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-1-1-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-3-2-True-2]",
"xarray/tests/test_variable.py::TestVariable::test_squeeze",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-2-2-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-2-None-True-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-1-2-False-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[sum-3-1-True]",
"xarray/tests/test_dataset.py::test_rolling_construct[3-True]",
"xarray/tests/test_dataarray.py::TestDataArray::test_struct_array_dims",
"xarray/tests/test_dataset.py::test_dataset_constructor_aligns_to_explicit_coords[coords0-unaligned_coords8]",
"xarray/tests/test_dataarray.py::test_rolling_wrapped_bottleneck[1-None-None-std]",
"xarray/tests/test_dataarray.py::TestDataArray::test_resample_bad_resample_dim",
"xarray/tests/test_dataset.py::TestDataset::test_coords_merge",
"xarray/tests/test_dataset.py::test_rolling_reduce[min-1-3-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-4-3-False-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[sum-4-1-True-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-1-3-True-1]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z1-1-None-mean]",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-4-None-True-2]",
"xarray/tests/test_variable.py::TestIndexVariable::test_load",
"xarray/tests/test_dataarray.py::TestDataArray::test_math_with_coords",
"xarray/tests/test_dataset.py::TestDataset::test_groupby_nan",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-3-2-False-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_loc",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-3-1-False-2]",
"xarray/tests/test_dataset.py::TestDataset::test_groupby_math_virtual",
"xarray/tests/test_variable.py::TestVariable::test_0d_str",
"xarray/tests/test_dataarray.py::TestDataArray::test_groupby_apply_changes_metadata",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-3-None-False-2]",
"xarray/tests/test_dataset.py::TestDataset::test_where_other",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-4-1-True-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-1-1-False-2]",
"xarray/tests/test_dataset.py::TestDataset::test_rename_old_name",
"xarray/tests/test_dataset.py::test_rolling_reduce[mean-4-3-True-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_constructor_from_0d",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-4-2-True-2]",
"xarray/tests/test_dataset.py::TestDataset::test_quantile",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-2-3-False-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-3-3-True-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[mean-4-None-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-3-3-False-1]",
"xarray/tests/test_dataarray.py::test_rolling_wrapped_bottleneck[1-None-False-mean]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-1-2-True-1]",
"xarray/tests/test_dataset.py::TestDataset::test_reindex_warning",
"xarray/tests/test_dataset.py::test_rolling_pandas_compat[3-1-False]",
"xarray/tests/test_dataarray.py::test_rolling_construct[4-True]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-2-1-True]",
"xarray/tests/test_dataarray.py::TestDataArray::test_align_without_indexes_exclude",
"xarray/tests/test_dataset.py::TestDataset::test_constructor",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-1-None-False-1]",
"xarray/tests/test_dataarray.py::test_rolling_pandas_compat[3-3-False]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-4-2-True-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-2-3-True-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_getitem_dict",
"xarray/tests/test_dataset.py::test_rolling_reduce[median-1-2-True-2]",
"xarray/tests/test_dataset.py::TestDataset::test_reduce_bad_dim",
"xarray/tests/test_dataarray.py::test_rolling_wrapped_bottleneck[1-None-True-std]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-2-2-False-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[sum-4-None-True]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-3-2-True-1]",
"xarray/tests/test_dataarray.py::test_rolling_pandas_compat[1-1-False]",
"xarray/tests/test_dataset.py::test_rolling_pandas_compat[3-1-True]",
"xarray/tests/test_variable.py::TestIndexVariable::test_name",
"xarray/tests/test_dataset.py::TestDataset::test_coords_setitem_multiindex",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-1-None-True-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-1-3-True-1]",
"xarray/tests/test_dataarray.py::test_rolling_wrapped_bottleneck[1-1-False-sum]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-3-None-True-2]",
"xarray/tests/test_variable.py::TestIndexVariable::test_multiindex_default_level_names",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-1-3-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[min-1-None-False-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[mean-1-3-True-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_da_resample_func_args",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-4-2-False-2]",
"xarray/tests/test_variable.py::TestIndexVariable::test_attrs",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z1-1-True-max]",
"xarray/tests/test_dataarray.py::TestDataArray::test_getitem_empty_index",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-3-None-True-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[mean-4-2-True-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_sel",
"xarray/tests/test_dataset.py::TestDataset::test_resample_loffset",
"xarray/tests/test_dataset.py::test_rolling_reduce[mean-3-None-True-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-1-None-True-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-1-2-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-2-3-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_pandas_compat[3-1-False]",
"xarray/tests/test_dataset.py::test_rolling_reduce[min-3-1-True-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-4-1-True-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[min-3-None-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-2-1-False-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[sum-2-3-True-2]",
"xarray/tests/test_dataset.py::TestDataset::test_expand_dims_mixed_int_and_coords",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-2-3-True-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-2-3-False-1]",
"xarray/tests/test_variable.py::TestVariable::test_rolling_window",
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"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-1-1-True-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-4-1-False-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[median-3-1-True-2]",
"xarray/tests/test_variable.py::TestIndexVariable::test_datetime64_conversion",
"xarray/tests/test_dataarray.py::TestDataArray::test_upsample_nd",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-2-3-True-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_getitem",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-1-None-False-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[sum-1-3-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-2-None-True-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[sum-4-3-False]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-3-3-False]",
"xarray/tests/test_dataset.py::test_dataset_constructor_aligns_to_explicit_coords[coords1-unaligned_coords0]",
"xarray/tests/test_dataset.py::test_rolling_reduce[sum-3-None-False-1]",
"xarray/tests/test_dataset.py::TestDataset::test_head",
"xarray/tests/test_dataset.py::test_rolling_reduce[median-4-2-True-1]",
"xarray/tests/test_dataset.py::test_rolling_properties[1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-3-3-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[sum-1-2-True-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_to_dict_with_numpy_attrs",
"xarray/tests/test_dataset.py::test_rolling_reduce[mean-3-1-False-1]",
"xarray/tests/test_dataset.py::TestDataset::test_assign_attrs",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-2-2-True]",
"xarray/tests/test_dataset.py::TestDataset::test_coords_modify",
"xarray/tests/test_dataset.py::TestDataset::test_resample_by_last_discarding_attrs",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-None-None-mean]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-1-1-True-1]",
"xarray/tests/test_dataset.py::TestDataset::test_asarray",
"xarray/tests/test_dataarray.py::TestDataArray::test_stack_unstack",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-3-3-False-1]",
"xarray/tests/test_variable.py::TestVariable::test_shift[2.0]",
"xarray/tests/test_variable.py::TestVariable::test_reduce_keepdims",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-3-2-False-2]",
"xarray/tests/test_variable.py::TestIndexVariable::test_concat_multiindex",
"xarray/tests/test_utils.py::test_hidden_key_dict",
"xarray/tests/test_variable.py::TestIndexVariable::test_encoding_preserved",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-1-None-False-1]",
"xarray/tests/test_variable.py::TestIndexVariable::test_getitem_1d",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-4-1-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-2-3-True-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_reset_coords",
"xarray/tests/test_dataarray.py::TestDataArray::test_groupby_apply_center",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-4-2-True-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-3-1-False-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-2-2-True-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-3-None-False-1]",
"xarray/tests/test_dataset.py::TestDataset::test_groupby_math",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-2-2-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_pandas_compat[4-1-False]",
"xarray/tests/test_dataarray.py::TestDataArray::test_broadcast_arrays_nocopy",
"xarray/tests/test_dataarray.py::TestDataArray::test_inplace_math_automatic_alignment",
"xarray/tests/test_dataset.py::test_dataset_constructor_aligns_to_explicit_coords[coords1-unaligned_coords8]",
"xarray/tests/test_dataarray.py::TestDataArray::test_swap_dims",
"xarray/tests/test_dataarray.py::TestDataArray::test_loc_assign",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[sum-1-3-False]",
"xarray/tests/test_dataarray.py::TestDataArray::test_expand_dims_error",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-2-None-True-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-3-3-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-1-None-True-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-1-1-True-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_align_without_indexes_errors",
"xarray/tests/test_dataarray.py::test_rolling_wrapped_bottleneck[1-1-None-min]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-2-1-False]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-2-1-False-2]",
"xarray/tests/test_dataset.py::test_coarsen[1-pad-right-False]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-1-True-mean]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-1-None-sum]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-2-3-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-2-None-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[median-4-3-True-1]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-None-True-std]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-3-None-True-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[min-1-None-True-1]"
] |
[
"xarray/tests/test_utils.py::test_infix_dims[supplied1-all_1-expected1]",
"xarray/tests/test_utils.py::test_infix_dims_errors[supplied0-all_0]",
"xarray/tests/test_utils.py::test_infix_dims[supplied2-all_2-expected2]",
"xarray/tests/test_utils.py::test_infix_dims[supplied4-all_4-expected4]",
"xarray/tests/test_utils.py::test_infix_dims[supplied3-all_3-expected3]",
"xarray/tests/test_utils.py::test_infix_dims[supplied0-all_0-expected0]",
"xarray/tests/test_utils.py::test_infix_dims_errors[supplied1-all_1]",
"xarray/tests/test_dataset.py::TestDataset::test_dataset_ellipsis_transpose_different_ordered_vars",
"xarray/tests/test_utils.py::test_infix_dims[supplied5-all_5-expected5]",
"xarray/tests/test_variable.py::TestVariable::test_transpose",
"xarray/tests/test_dataarray.py::TestDataArray::test_transpose",
"xarray/tests/test_dataset.py::TestDataset::test_dataset_transpose"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": [
{
"type": "function",
"name": "infix_dims"
},
{
"type": "field",
"name": "infix_dims"
},
{
"type": "field",
"name": "infix_dims"
}
]
}
|
[
{
"path": "doc/reshaping.rst",
"old_path": "a/doc/reshaping.rst",
"new_path": "b/doc/reshaping.rst",
"metadata": "diff --git a/doc/reshaping.rst b/doc/reshaping.rst\nindex 51202f9be41..455a24f9216 100644\n--- a/doc/reshaping.rst\n+++ b/doc/reshaping.rst\n@@ -18,12 +18,14 @@ Reordering dimensions\n ---------------------\n \n To reorder dimensions on a :py:class:`~xarray.DataArray` or across all variables\n-on a :py:class:`~xarray.Dataset`, use :py:meth:`~xarray.DataArray.transpose`:\n+on a :py:class:`~xarray.Dataset`, use :py:meth:`~xarray.DataArray.transpose`. An \n+ellipsis (`...`) can be use to represent all other dimensions:\n \n .. ipython:: python\n \n ds = xr.Dataset({'foo': (('x', 'y', 'z'), [[[42]]]), 'bar': (('y', 'z'), [[24]])})\n ds.transpose('y', 'z', 'x')\n+ ds.transpose(..., 'x') # equivalent\n ds.transpose() # reverses all dimensions\n \n Expand and squeeze dimensions\n"
},
{
"path": "doc/whats-new.rst",
"old_path": "a/doc/whats-new.rst",
"new_path": "b/doc/whats-new.rst",
"metadata": "diff --git a/doc/whats-new.rst b/doc/whats-new.rst\nindex dea110b5e46..cced7276ff3 100644\n--- a/doc/whats-new.rst\n+++ b/doc/whats-new.rst\n@@ -25,6 +25,10 @@ Breaking changes\n \n New Features\n ~~~~~~~~~~~~\n+- :py:meth:`Dataset.transpose` and :py:meth:`DataArray.transpose` now support an ellipsis (`...`)\n+ to represent all 'other' dimensions. For example, to move one dimension to the front,\n+ use `.transpose('x', ...)`. (:pull:`<PRID>`)\n+ By `<NAME>`_\n - Changed `xr.ALL_DIMS` to equal python's `Ellipsis` (`...`), and changed internal usages to use\n `...` directly. As before, you can use this to instruct a `groupby` operation\n to reduce over all dimensions. While we have no plans to remove `xr.ALL_DIMS`, we suggest\n"
}
] |
diff --git a/doc/reshaping.rst b/doc/reshaping.rst
index 51202f9be41..455a24f9216 100644
--- a/doc/reshaping.rst
+++ b/doc/reshaping.rst
@@ -18,12 +18,14 @@ Reordering dimensions
---------------------
To reorder dimensions on a :py:class:`~xarray.DataArray` or across all variables
-on a :py:class:`~xarray.Dataset`, use :py:meth:`~xarray.DataArray.transpose`:
+on a :py:class:`~xarray.Dataset`, use :py:meth:`~xarray.DataArray.transpose`. An
+ellipsis (`...`) can be use to represent all other dimensions:
.. ipython:: python
ds = xr.Dataset({'foo': (('x', 'y', 'z'), [[[42]]]), 'bar': (('y', 'z'), [[24]])})
ds.transpose('y', 'z', 'x')
+ ds.transpose(..., 'x') # equivalent
ds.transpose() # reverses all dimensions
Expand and squeeze dimensions
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index dea110b5e46..cced7276ff3 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -25,6 +25,10 @@ Breaking changes
New Features
~~~~~~~~~~~~
+- :py:meth:`Dataset.transpose` and :py:meth:`DataArray.transpose` now support an ellipsis (`...`)
+ to represent all 'other' dimensions. For example, to move one dimension to the front,
+ use `.transpose('x', ...)`. (:pull:`<PRID>`)
+ By `<NAME>`_
- Changed `xr.ALL_DIMS` to equal python's `Ellipsis` (`...`), and changed internal usages to use
`...` directly. As before, you can use this to instruct a `groupby` operation
to reduce over all dimensions. While we have no plans to remove `xr.ALL_DIMS`, we suggest
If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:
[{'type': 'function', 'name': 'infix_dims'}, {'type': 'field', 'name': 'infix_dims'}, {'type': 'field', 'name': 'infix_dims'}]
|
pydata/xarray
|
pydata__xarray-3418
|
https://github.com/pydata/xarray/pull/3418
|
diff --git a/doc/examples/multidimensional-coords.rst b/doc/examples/multidimensional-coords.rst
index a5084043977..55569b7662a 100644
--- a/doc/examples/multidimensional-coords.rst
+++ b/doc/examples/multidimensional-coords.rst
@@ -107,7 +107,7 @@ function to specify the output coordinates of the group.
lat_center = np.arange(1, 90, 2)
# group according to those bins and take the mean
Tair_lat_mean = (ds.Tair.groupby_bins('xc', lat_bins, labels=lat_center)
- .mean(xr.ALL_DIMS))
+ .mean(...))
# plot the result
@savefig xarray_multidimensional_coords_14_1.png width=5in
Tair_lat_mean.plot();
diff --git a/doc/groupby.rst b/doc/groupby.rst
index e1d88e289d2..52a27f4f160 100644
--- a/doc/groupby.rst
+++ b/doc/groupby.rst
@@ -116,7 +116,13 @@ dimensions *other than* the provided one:
.. ipython:: python
- ds.groupby('x').std(xr.ALL_DIMS)
+ ds.groupby('x').std(...)
+
+.. note::
+
+ We use an ellipsis (`...`) here to indicate we want to reduce over all
+ other dimensions
+
First and last
~~~~~~~~~~~~~~
@@ -127,7 +133,7 @@ values for group along the grouped dimension:
.. ipython:: python
- ds.groupby('letters').first(xr.ALL_DIMS)
+ ds.groupby('letters').first(...)
By default, they skip missing values (control this with ``skipna``).
@@ -142,7 +148,7 @@ coordinates. For example:
.. ipython:: python
- alt = arr.groupby('letters').mean(xr.ALL_DIMS)
+ alt = arr.groupby('letters').mean(...)
alt
ds.groupby('letters') - alt
@@ -195,7 +201,7 @@ __ http://cfconventions.org/cf-conventions/v1.6.0/cf-conventions.html#_two_dimen
'lat': (['ny','nx'], [[10,10],[20,20]] ),},
dims=['ny','nx'])
da
- da.groupby('lon').sum(xr.ALL_DIMS)
+ da.groupby('lon').sum(...)
da.groupby('lon').apply(lambda x: x - x.mean(), shortcut=False)
Because multidimensional groups have the ability to generate a very large
@@ -213,4 +219,4 @@ applying your function, and then unstacking the result:
.. ipython:: python
stacked = da.stack(gridcell=['ny', 'nx'])
- stacked.groupby('gridcell').sum(xr.ALL_DIMS).unstack('gridcell')
+ stacked.groupby('gridcell').sum(...).unstack('gridcell')
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index 9d3e64badb8..c912fd9e1de 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -25,6 +25,11 @@ Breaking changes
New Features
~~~~~~~~~~~~
+- Changed `xr.ALL_DIMS` to equal python's `Ellipsis` (`...`), and changed internal usages to use
+ `...` directly. As before, you can use this to instruct a `groupby` operation
+ to reduce over all dimensions. While we have no plans to remove `xr.ALL_DIMS`, we suggest
+ using `...`.
+ By `Maximilian Roos <https://github.com/max-sixty>`_
- Added integration tests against `pint <https://pint.readthedocs.io/>`_.
(:pull:`3238`) by `Justus Magin <https://github.com/keewis>`_.
diff --git a/xarray/core/common.py b/xarray/core/common.py
index 45d860a1797..53aecb47601 100644
--- a/xarray/core/common.py
+++ b/xarray/core/common.py
@@ -24,10 +24,10 @@
from .options import _get_keep_attrs
from .pycompat import dask_array_type
from .rolling_exp import RollingExp
-from .utils import Frozen, ReprObject, either_dict_or_kwargs
+from .utils import Frozen, either_dict_or_kwargs
# Used as a sentinel value to indicate a all dimensions
-ALL_DIMS = ReprObject("<all-dims>")
+ALL_DIMS = ...
C = TypeVar("C")
diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index 12d5cbdc9f3..35a8771a28a 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -47,7 +47,6 @@
)
from .alignment import _broadcast_helper, _get_broadcast_dims_map_common_coords, align
from .common import (
- ALL_DIMS,
DataWithCoords,
ImplementsDatasetReduce,
_contains_datetime_like_objects,
@@ -4030,7 +4029,7 @@ def reduce(
Dataset with this object's DataArrays replaced with new DataArrays
of summarized data and the indicated dimension(s) removed.
"""
- if dim is None or dim is ALL_DIMS:
+ if dim is None or dim is ...:
dims = set(self.dims)
elif isinstance(dim, str) or not isinstance(dim, Iterable):
dims = {dim}
@@ -4995,7 +4994,7 @@ def quantile(
if isinstance(dim, str):
dims = {dim}
- elif dim is None or dim is ALL_DIMS:
+ elif dim in [None, ...]:
dims = set(self.dims)
else:
dims = set(dim)
diff --git a/xarray/core/groupby.py b/xarray/core/groupby.py
index 52eb17df18d..68bd28ddb12 100644
--- a/xarray/core/groupby.py
+++ b/xarray/core/groupby.py
@@ -7,7 +7,7 @@
from . import dtypes, duck_array_ops, nputils, ops
from .arithmetic import SupportsArithmetic
-from .common import ALL_DIMS, ImplementsArrayReduce, ImplementsDatasetReduce
+from .common import ImplementsArrayReduce, ImplementsDatasetReduce
from .concat import concat
from .formatting import format_array_flat
from .options import _get_keep_attrs
@@ -712,7 +712,7 @@ def quantile(self, q, dim=None, interpolation="linear", keep_attrs=None):
q : float in range of [0,1] (or sequence of floats)
Quantile to compute, which must be between 0 and 1
inclusive.
- dim : xarray.ALL_DIMS, str or sequence of str, optional
+ dim : `...`, str or sequence of str, optional
Dimension(s) over which to apply quantile.
Defaults to the grouped dimension.
interpolation : {'linear', 'lower', 'higher', 'midpoint', 'nearest'}
@@ -769,7 +769,7 @@ def reduce(
Function which can be called in the form
`func(x, axis=axis, **kwargs)` to return the result of collapsing
an np.ndarray over an integer valued axis.
- dim : xarray.ALL_DIMS, str or sequence of str, optional
+ dim : `...`, str or sequence of str, optional
Dimension(s) over which to apply `func`.
axis : int or sequence of int, optional
Axis(es) over which to apply `func`. Only one of the 'dimension'
@@ -794,9 +794,9 @@ def reduce(
if keep_attrs is None:
keep_attrs = _get_keep_attrs(default=False)
- if dim is not ALL_DIMS and dim not in self.dims:
+ if dim is not ... and dim not in self.dims:
raise ValueError(
- "cannot reduce over dimension %r. expected either xarray.ALL_DIMS to reduce over all dimensions or one or more of %r."
+ "cannot reduce over dimension %r. expected either '...' to reduce over all dimensions or one or more of %r."
% (dim, self.dims)
)
@@ -867,7 +867,7 @@ def reduce(self, func, dim=None, keep_attrs=None, **kwargs):
Function which can be called in the form
`func(x, axis=axis, **kwargs)` to return the result of collapsing
an np.ndarray over an integer valued axis.
- dim : xarray.ALL_DIMS, str or sequence of str, optional
+ dim : `...`, str or sequence of str, optional
Dimension(s) over which to apply `func`.
axis : int or sequence of int, optional
Axis(es) over which to apply `func`. Only one of the 'dimension'
@@ -895,9 +895,9 @@ def reduce(self, func, dim=None, keep_attrs=None, **kwargs):
def reduce_dataset(ds):
return ds.reduce(func, dim, keep_attrs, **kwargs)
- if dim is not ALL_DIMS and dim not in self.dims:
+ if dim is not ... and dim not in self.dims:
raise ValueError(
- "cannot reduce over dimension %r. expected either xarray.ALL_DIMS to reduce over all dimensions or one or more of %r."
+ "cannot reduce over dimension %r. expected either '...' to reduce over all dimensions or one or more of %r."
% (dim, self.dims)
)
diff --git a/xarray/core/variable.py b/xarray/core/variable.py
index 37672cd82d9..93ad1eafb97 100644
--- a/xarray/core/variable.py
+++ b/xarray/core/variable.py
@@ -1450,7 +1450,7 @@ def reduce(
Array with summarized data and the indicated dimension(s)
removed.
"""
- if dim is common.ALL_DIMS:
+ if dim == ...:
dim = None
if dim is not None and axis is not None:
raise ValueError("cannot supply both 'axis' and 'dim' arguments")
|
diff --git a/xarray/tests/test_dask.py b/xarray/tests/test_dask.py
index ae8f43cb66d..50517ae3c9c 100644
--- a/xarray/tests/test_dask.py
+++ b/xarray/tests/test_dask.py
@@ -435,8 +435,8 @@ def test_groupby(self):
u = self.eager_array
v = self.lazy_array
- expected = u.groupby("x").mean(xr.ALL_DIMS)
- actual = v.groupby("x").mean(xr.ALL_DIMS)
+ expected = u.groupby("x").mean(...)
+ actual = v.groupby("x").mean(...)
self.assertLazyAndAllClose(expected, actual)
def test_groupby_first(self):
diff --git a/xarray/tests/test_dataarray.py b/xarray/tests/test_dataarray.py
index a3a2f55f6cc..b13527bc098 100644
--- a/xarray/tests/test_dataarray.py
+++ b/xarray/tests/test_dataarray.py
@@ -13,7 +13,7 @@
from xarray.coding.times import CFDatetimeCoder
from xarray.convert import from_cdms2
from xarray.core import dtypes
-from xarray.core.common import ALL_DIMS, full_like
+from xarray.core.common import full_like
from xarray.tests import (
LooseVersion,
ReturnItem,
@@ -2443,8 +2443,8 @@ def test_groupby_sum(self):
"abc": Variable(["abc"], np.array(["a", "b", "c"])),
}
)["foo"]
- assert_allclose(expected_sum_all, grouped.reduce(np.sum, dim=ALL_DIMS))
- assert_allclose(expected_sum_all, grouped.sum(ALL_DIMS))
+ assert_allclose(expected_sum_all, grouped.reduce(np.sum, dim=...))
+ assert_allclose(expected_sum_all, grouped.sum(...))
expected = DataArray(
[
@@ -2456,7 +2456,7 @@ def test_groupby_sum(self):
)
actual = array["y"].groupby("abc").apply(np.sum)
assert_allclose(expected, actual)
- actual = array["y"].groupby("abc").sum(ALL_DIMS)
+ actual = array["y"].groupby("abc").sum(...)
assert_allclose(expected, actual)
expected_sum_axis1 = Dataset(
@@ -2590,9 +2590,9 @@ def test_groupby_math(self):
assert_identical(expected, actual)
grouped = array.groupby("abc")
- expected_agg = (grouped.mean(ALL_DIMS) - np.arange(3)).rename(None)
+ expected_agg = (grouped.mean(...) - np.arange(3)).rename(None)
actual = grouped - DataArray(range(3), [("abc", ["a", "b", "c"])])
- actual_agg = actual.groupby("abc").mean(ALL_DIMS)
+ actual_agg = actual.groupby("abc").mean(...)
assert_allclose(expected_agg, actual_agg)
with raises_regex(TypeError, "only support binary ops"):
@@ -2698,7 +2698,7 @@ def test_groupby_multidim(self):
("lon", DataArray([5, 28, 23], coords=[("lon", [30.0, 40.0, 50.0])])),
("lat", DataArray([16, 40], coords=[("lat", [10.0, 20.0])])),
]:
- actual_sum = array.groupby(dim).sum(ALL_DIMS)
+ actual_sum = array.groupby(dim).sum(...)
assert_identical(expected_sum, actual_sum)
def test_groupby_multidim_apply(self):
diff --git a/xarray/tests/test_dataset.py b/xarray/tests/test_dataset.py
index 006d6881b5a..b3ffdf68e3f 100644
--- a/xarray/tests/test_dataset.py
+++ b/xarray/tests/test_dataset.py
@@ -11,7 +11,6 @@
import xarray as xr
from xarray import (
- ALL_DIMS,
DataArray,
Dataset,
IndexVariable,
@@ -3327,7 +3326,7 @@ def test_groupby_reduce(self):
expected = data.mean("y")
expected["yonly"] = expected["yonly"].variable.set_dims({"x": 3})
- actual = data.groupby("x").mean(ALL_DIMS)
+ actual = data.groupby("x").mean(...)
assert_allclose(expected, actual)
actual = data.groupby("x").mean("y")
@@ -3336,12 +3335,12 @@ def test_groupby_reduce(self):
letters = data["letters"]
expected = Dataset(
{
- "xy": data["xy"].groupby(letters).mean(ALL_DIMS),
+ "xy": data["xy"].groupby(letters).mean(...),
"xonly": (data["xonly"].mean().variable.set_dims({"letters": 2})),
"yonly": data["yonly"].groupby(letters).mean(),
}
)
- actual = data.groupby("letters").mean(ALL_DIMS)
+ actual = data.groupby("letters").mean(...)
assert_allclose(expected, actual)
def test_groupby_math(self):
@@ -3404,14 +3403,14 @@ def test_groupby_math_virtual(self):
{"x": ("t", [1, 2, 3])}, {"t": pd.date_range("20100101", periods=3)}
)
grouped = ds.groupby("t.day")
- actual = grouped - grouped.mean(ALL_DIMS)
+ actual = grouped - grouped.mean(...)
expected = Dataset({"x": ("t", [0, 0, 0])}, ds[["t", "t.day"]])
assert_identical(actual, expected)
def test_groupby_nan(self):
# nan should be excluded from groupby
ds = Dataset({"foo": ("x", [1, 2, 3, 4])}, {"bar": ("x", [1, 1, 2, np.nan])})
- actual = ds.groupby("bar").mean(ALL_DIMS)
+ actual = ds.groupby("bar").mean(...)
expected = Dataset({"foo": ("bar", [1.5, 3]), "bar": [1, 2]})
assert_identical(actual, expected)
@@ -3421,7 +3420,7 @@ def test_groupby_order(self):
for vn in ["a", "b", "c"]:
ds[vn] = DataArray(np.arange(10), dims=["t"])
data_vars_ref = list(ds.data_vars.keys())
- ds = ds.groupby("t").mean(ALL_DIMS)
+ ds = ds.groupby("t").mean(...)
data_vars = list(ds.data_vars.keys())
assert data_vars == data_vars_ref
# coords are now at the end of the list, so the test below fails
diff --git a/xarray/tests/test_groupby.py b/xarray/tests/test_groupby.py
index be494c4ae2b..a6de41beb66 100644
--- a/xarray/tests/test_groupby.py
+++ b/xarray/tests/test_groupby.py
@@ -147,11 +147,11 @@ def test_da_groupby_quantile():
[("x", [1, 1, 1, 2, 2]), ("y", [0, 0, 1])],
)
- actual_x = array.groupby("x").quantile(0, dim=xr.ALL_DIMS)
+ actual_x = array.groupby("x").quantile(0, dim=...)
expected_x = xr.DataArray([1, 4], [("x", [1, 2])])
assert_identical(expected_x, actual_x)
- actual_y = array.groupby("y").quantile(0, dim=xr.ALL_DIMS)
+ actual_y = array.groupby("y").quantile(0, dim=...)
expected_y = xr.DataArray([1, 22], [("y", [0, 1])])
assert_identical(expected_y, actual_y)
@@ -177,7 +177,7 @@ def test_da_groupby_quantile():
)
g = foo.groupby(foo.time.dt.month)
- actual = g.quantile(0, dim=xr.ALL_DIMS)
+ actual = g.quantile(0, dim=...)
expected = xr.DataArray(
[
0.0,
diff --git a/xarray/tests/test_plot.py b/xarray/tests/test_plot.py
index 3ac45a9720f..7deabd46eae 100644
--- a/xarray/tests/test_plot.py
+++ b/xarray/tests/test_plot.py
@@ -417,7 +417,7 @@ def test_convenient_facetgrid_4d(self):
def test_coord_with_interval(self):
bins = [-1, 0, 1, 2]
- self.darray.groupby_bins("dim_0", bins).mean(xr.ALL_DIMS).plot()
+ self.darray.groupby_bins("dim_0", bins).mean(...).plot()
class TestPlot1D(PlotTestCase):
@@ -502,7 +502,7 @@ def test_step(self):
def test_coord_with_interval_step(self):
bins = [-1, 0, 1, 2]
- self.darray.groupby_bins("dim_0", bins).mean(xr.ALL_DIMS).plot.step()
+ self.darray.groupby_bins("dim_0", bins).mean(...).plot.step()
assert len(plt.gca().lines[0].get_xdata()) == ((len(bins) - 1) * 2)
@@ -544,7 +544,7 @@ def test_plot_nans(self):
def test_hist_coord_with_interval(self):
(
self.darray.groupby_bins("dim_0", [-1, 0, 1, 2])
- .mean(xr.ALL_DIMS)
+ .mean(...)
.plot.hist(range=(-1, 2))
)
diff --git a/xarray/tests/test_sparse.py b/xarray/tests/test_sparse.py
index bd26b96f6d4..73c4b9b8c74 100644
--- a/xarray/tests/test_sparse.py
+++ b/xarray/tests/test_sparse.py
@@ -756,8 +756,8 @@ def test_dot(self):
def test_groupby(self):
x1 = self.ds_xr
x2 = self.sp_xr
- m1 = x1.groupby("x").mean(xr.ALL_DIMS)
- m2 = x2.groupby("x").mean(xr.ALL_DIMS)
+ m1 = x1.groupby("x").mean(...)
+ m2 = x2.groupby("x").mean(...)
assert isinstance(m2.data, sparse.SparseArray)
assert np.allclose(m1.data, m2.data.todense())
@@ -772,8 +772,8 @@ def test_groupby_first(self):
def test_groupby_bins(self):
x1 = self.ds_xr
x2 = self.sp_xr
- m1 = x1.groupby_bins("x", bins=[0, 3, 7, 10]).sum(xr.ALL_DIMS)
- m2 = x2.groupby_bins("x", bins=[0, 3, 7, 10]).sum(xr.ALL_DIMS)
+ m1 = x1.groupby_bins("x", bins=[0, 3, 7, 10]).sum(...)
+ m2 = x2.groupby_bins("x", bins=[0, 3, 7, 10]).sum(...)
assert isinstance(m2.data, sparse.SparseArray)
assert np.allclose(m1.data, m2.data.todense())
|
[
{
"path": "doc/examples/multidimensional-coords.rst",
"old_path": "a/doc/examples/multidimensional-coords.rst",
"new_path": "b/doc/examples/multidimensional-coords.rst",
"metadata": "diff --git a/doc/examples/multidimensional-coords.rst b/doc/examples/multidimensional-coords.rst\nindex a5084043977..55569b7662a 100644\n--- a/doc/examples/multidimensional-coords.rst\n+++ b/doc/examples/multidimensional-coords.rst\n@@ -107,7 +107,7 @@ function to specify the output coordinates of the group.\n lat_center = np.arange(1, 90, 2)\n # group according to those bins and take the mean\n Tair_lat_mean = (ds.Tair.groupby_bins('xc', lat_bins, labels=lat_center)\n-\t .mean(xr.ALL_DIMS))\n+\t .mean(...))\n # plot the result\n @savefig xarray_multidimensional_coords_14_1.png width=5in\n Tair_lat_mean.plot();\n"
},
{
"path": "doc/groupby.rst",
"old_path": "a/doc/groupby.rst",
"new_path": "b/doc/groupby.rst",
"metadata": "diff --git a/doc/groupby.rst b/doc/groupby.rst\nindex e1d88e289d2..52a27f4f160 100644\n--- a/doc/groupby.rst\n+++ b/doc/groupby.rst\n@@ -116,7 +116,13 @@ dimensions *other than* the provided one:\n \n .. ipython:: python\n \n- ds.groupby('x').std(xr.ALL_DIMS)\n+ ds.groupby('x').std(...)\n+\n+.. note::\n+\n+ We use an ellipsis (`...`) here to indicate we want to reduce over all\n+ other dimensions \n+\n \n First and last\n ~~~~~~~~~~~~~~\n@@ -127,7 +133,7 @@ values for group along the grouped dimension:\n \n .. ipython:: python\n \n- ds.groupby('letters').first(xr.ALL_DIMS)\n+ ds.groupby('letters').first(...)\n \n By default, they skip missing values (control this with ``skipna``).\n \n@@ -142,7 +148,7 @@ coordinates. For example:\n \n .. ipython:: python\n \n- alt = arr.groupby('letters').mean(xr.ALL_DIMS)\n+ alt = arr.groupby('letters').mean(...)\n alt\n ds.groupby('letters') - alt\n \n@@ -195,7 +201,7 @@ __ http://cfconventions.org/cf-conventions/v1.6.0/cf-conventions.html#_two_dimen\n 'lat': (['ny','nx'], [[10,10],[20,20]] ),},\n dims=['ny','nx'])\n da\n- da.groupby('lon').sum(xr.ALL_DIMS)\n+ da.groupby('lon').sum(...)\n da.groupby('lon').apply(lambda x: x - x.mean(), shortcut=False)\n \n Because multidimensional groups have the ability to generate a very large\n@@ -213,4 +219,4 @@ applying your function, and then unstacking the result:\n .. ipython:: python\n \n stacked = da.stack(gridcell=['ny', 'nx'])\n- stacked.groupby('gridcell').sum(xr.ALL_DIMS).unstack('gridcell')\n+ stacked.groupby('gridcell').sum(...).unstack('gridcell')\n"
},
{
"path": "doc/whats-new.rst",
"old_path": "a/doc/whats-new.rst",
"new_path": "b/doc/whats-new.rst",
"metadata": "diff --git a/doc/whats-new.rst b/doc/whats-new.rst\nindex 9d3e64badb8..c912fd9e1de 100644\n--- a/doc/whats-new.rst\n+++ b/doc/whats-new.rst\n@@ -25,6 +25,11 @@ Breaking changes\n \n New Features\n ~~~~~~~~~~~~\n+- Changed `xr.ALL_DIMS` to equal python's `Ellipsis` (`...`), and changed internal usages to use\n+ `...` directly. As before, you can use this to instruct a `groupby` operation\n+ to reduce over all dimensions. While we have no plans to remove `xr.ALL_DIMS`, we suggest\n+ using `...`.\n+ By `Maximilian Roos <https://github.com/max-sixty>`_\n - Added integration tests against `pint <https://pint.readthedocs.io/>`_.\n (:pull:`3238`) by `Justus Magin <https://github.com/keewis>`_.\n \n"
}
] |
0014
|
652dd3ca77dd19bbd1ab21fe556340c1904ec382
|
[
"xarray/tests/test_dataset.py::test_rolling_reduce[median-3-3-True-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-3-2-False-1]",
"xarray/tests/test_dataarray.py::test_rolling_wrapped_bottleneck[1-1-False-mean]",
"xarray/tests/test_dataset.py::test_rolling_reduce[mean-3-2-True-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-2-3-True-2]",
"xarray/tests/test_dataset.py::TestDataset::test_setitem_dimension_override",
"xarray/tests/test_dataset.py::TestDataset::test_asarray",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-1-2-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-3-None-False-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-4-3-False-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[sum-2-3-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-2-None-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-1-None-False-2]",
"xarray/tests/test_dataset.py::TestDataset::test_stack_unstack_slow",
"xarray/tests/test_dataarray.py::TestDataArray::test_groupby_iter",
"xarray/tests/test_dataarray.py::test_rolling_construct[4-True]",
"xarray/tests/test_dataarray.py::TestDataArray::test_dataarray_diff_n1",
"xarray/tests/test_dataset.py::test_rolling_reduce[min-4-None-False-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_series_categorical_index",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-1-None-True-1]",
"xarray/tests/test_dataarray.py::test_rolling_pandas_compat[2-None-True]",
"xarray/tests/test_dataset.py::test_rolling_pandas_compat[3-1-True]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-4-None-True-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_constructor_from_self_described",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-4-1-True-1]",
"xarray/tests/test_dataset.py::TestDataset::test_selection_multiindex",
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"xarray/tests/test_dataarray.py::test_rolling_reduce[std-4-None-True-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-4-None-True-1]",
"xarray/tests/test_dataset.py::test_constructor_raises_with_invalid_coords[unaligned_coords0]",
"xarray/tests/test_dataarray.py::test_rolling_pandas_compat[4-3-False]",
"xarray/tests/test_dataarray.py::TestDataArray::test_tail",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-2-3-False-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_get_index",
"xarray/tests/test_dataarray.py::TestDataArray::test_resample_first",
"xarray/tests/test_dataset.py::test_rolling_reduce[median-2-1-False-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[mean-4-None-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-4-None-True-2]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-1-None-sum]",
"xarray/tests/test_dataset.py::TestDataset::test_squeeze_drop",
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"xarray/tests/test_dataset.py::test_rolling_reduce[sum-4-None-False-2]",
"xarray/tests/test_dataset.py::TestDataset::test_setitem_original_non_unique_index",
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"xarray/tests/test_dataset.py::test_rolling_reduce[min-4-3-True-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_broadcast_coordinates",
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"xarray/tests/test_dataset.py::test_rolling_reduce[std-3-None-True-1]",
"xarray/tests/test_dataarray.py::test_rolling_pandas_compat[1-None-True]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-3-3-True-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-1-None-False]",
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"xarray/tests/test_dataarray.py::test_rolling_reduce[max-4-2-False-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-3-1-False-2]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-None-False-min]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z1-None-True-var]",
"xarray/tests/test_dataset.py::test_coarsen[1-pad-right-True]",
"xarray/tests/test_dataset.py::test_rolling_reduce[var-3-2-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_pandas_compat[2-1-True]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[mean-3-2-True-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_shift[fill_value1-float-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[std-1-2-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-4-2-True]",
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"xarray/tests/test_dataset.py::test_rolling_reduce[std-4-1-False-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-2-None-False-1]",
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"xarray/tests/test_dataarray.py::test_rolling_reduce[std-4-2-True-1]",
"xarray/tests/test_dataset.py::test_dataset_constructor_aligns_to_explicit_coords[coords1-unaligned_coords9]",
"xarray/tests/test_dataset.py::TestDataset::test_assign_multiindex_level",
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] |
[
"xarray/tests/test_groupby.py::test_da_groupby_quantile",
"xarray/tests/test_dataset.py::TestDataset::test_groupby_order",
"xarray/tests/test_dataset.py::TestDataset::test_groupby_math_virtual",
"xarray/tests/test_dataarray.py::TestDataArray::test_groupby_multidim",
"xarray/tests/test_dataarray.py::TestDataArray::test_groupby_math",
"xarray/tests/test_dataset.py::TestDataset::test_groupby_reduce",
"xarray/tests/test_dataarray.py::TestDataArray::test_groupby_sum",
"xarray/tests/test_dataset.py::TestDataset::test_groupby_nan"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/examples/multidimensional-coords.rst",
"old_path": "a/doc/examples/multidimensional-coords.rst",
"new_path": "b/doc/examples/multidimensional-coords.rst",
"metadata": "diff --git a/doc/examples/multidimensional-coords.rst b/doc/examples/multidimensional-coords.rst\nindex a5084043977..55569b7662a 100644\n--- a/doc/examples/multidimensional-coords.rst\n+++ b/doc/examples/multidimensional-coords.rst\n@@ -107,7 +107,7 @@ function to specify the output coordinates of the group.\n lat_center = np.arange(1, 90, 2)\n # group according to those bins and take the mean\n Tair_lat_mean = (ds.Tair.groupby_bins('xc', lat_bins, labels=lat_center)\n-\t .mean(xr.ALL_DIMS))\n+\t .mean(...))\n # plot the result\n @savefig xarray_multidimensional_coords_14_1.png width=5in\n Tair_lat_mean.plot();\n"
},
{
"path": "doc/groupby.rst",
"old_path": "a/doc/groupby.rst",
"new_path": "b/doc/groupby.rst",
"metadata": "diff --git a/doc/groupby.rst b/doc/groupby.rst\nindex e1d88e289d2..52a27f4f160 100644\n--- a/doc/groupby.rst\n+++ b/doc/groupby.rst\n@@ -116,7 +116,13 @@ dimensions *other than* the provided one:\n \n .. ipython:: python\n \n- ds.groupby('x').std(xr.ALL_DIMS)\n+ ds.groupby('x').std(...)\n+\n+.. note::\n+\n+ We use an ellipsis (`...`) here to indicate we want to reduce over all\n+ other dimensions \n+\n \n First and last\n ~~~~~~~~~~~~~~\n@@ -127,7 +133,7 @@ values for group along the grouped dimension:\n \n .. ipython:: python\n \n- ds.groupby('letters').first(xr.ALL_DIMS)\n+ ds.groupby('letters').first(...)\n \n By default, they skip missing values (control this with ``skipna``).\n \n@@ -142,7 +148,7 @@ coordinates. For example:\n \n .. ipython:: python\n \n- alt = arr.groupby('letters').mean(xr.ALL_DIMS)\n+ alt = arr.groupby('letters').mean(...)\n alt\n ds.groupby('letters') - alt\n \n@@ -195,7 +201,7 @@ __ http://cfconventions.org/cf-conventions/v1.6.0/cf-conventions.html#_two_dimen\n 'lat': (['ny','nx'], [[10,10],[20,20]] ),},\n dims=['ny','nx'])\n da\n- da.groupby('lon').sum(xr.ALL_DIMS)\n+ da.groupby('lon').sum(...)\n da.groupby('lon').apply(lambda x: x - x.mean(), shortcut=False)\n \n Because multidimensional groups have the ability to generate a very large\n@@ -213,4 +219,4 @@ applying your function, and then unstacking the result:\n .. ipython:: python\n \n stacked = da.stack(gridcell=['ny', 'nx'])\n- stacked.groupby('gridcell').sum(xr.ALL_DIMS).unstack('gridcell')\n+ stacked.groupby('gridcell').sum(...).unstack('gridcell')\n"
},
{
"path": "doc/whats-new.rst",
"old_path": "a/doc/whats-new.rst",
"new_path": "b/doc/whats-new.rst",
"metadata": "diff --git a/doc/whats-new.rst b/doc/whats-new.rst\nindex 9d3e64badb8..c912fd9e1de 100644\n--- a/doc/whats-new.rst\n+++ b/doc/whats-new.rst\n@@ -25,6 +25,11 @@ Breaking changes\n \n New Features\n ~~~~~~~~~~~~\n+- Changed `xr.ALL_DIMS` to equal python's `Ellipsis` (`...`), and changed internal usages to use\n+ `...` directly. As before, you can use this to instruct a `groupby` operation\n+ to reduce over all dimensions. While we have no plans to remove `xr.ALL_DIMS`, we suggest\n+ using `...`.\n+ By `<NAME>`_\n - Added integration tests against `pint <https://pint.readthedocs.io/>`_.\n (:pull:`<PRID>`) by `<NAME>`_.\n \n"
}
] |
diff --git a/doc/examples/multidimensional-coords.rst b/doc/examples/multidimensional-coords.rst
index a5084043977..55569b7662a 100644
--- a/doc/examples/multidimensional-coords.rst
+++ b/doc/examples/multidimensional-coords.rst
@@ -107,7 +107,7 @@ function to specify the output coordinates of the group.
lat_center = np.arange(1, 90, 2)
# group according to those bins and take the mean
Tair_lat_mean = (ds.Tair.groupby_bins('xc', lat_bins, labels=lat_center)
- .mean(xr.ALL_DIMS))
+ .mean(...))
# plot the result
@savefig xarray_multidimensional_coords_14_1.png width=5in
Tair_lat_mean.plot();
diff --git a/doc/groupby.rst b/doc/groupby.rst
index e1d88e289d2..52a27f4f160 100644
--- a/doc/groupby.rst
+++ b/doc/groupby.rst
@@ -116,7 +116,13 @@ dimensions *other than* the provided one:
.. ipython:: python
- ds.groupby('x').std(xr.ALL_DIMS)
+ ds.groupby('x').std(...)
+
+.. note::
+
+ We use an ellipsis (`...`) here to indicate we want to reduce over all
+ other dimensions
+
First and last
~~~~~~~~~~~~~~
@@ -127,7 +133,7 @@ values for group along the grouped dimension:
.. ipython:: python
- ds.groupby('letters').first(xr.ALL_DIMS)
+ ds.groupby('letters').first(...)
By default, they skip missing values (control this with ``skipna``).
@@ -142,7 +148,7 @@ coordinates. For example:
.. ipython:: python
- alt = arr.groupby('letters').mean(xr.ALL_DIMS)
+ alt = arr.groupby('letters').mean(...)
alt
ds.groupby('letters') - alt
@@ -195,7 +201,7 @@ __ http://cfconventions.org/cf-conventions/v1.6.0/cf-conventions.html#_two_dimen
'lat': (['ny','nx'], [[10,10],[20,20]] ),},
dims=['ny','nx'])
da
- da.groupby('lon').sum(xr.ALL_DIMS)
+ da.groupby('lon').sum(...)
da.groupby('lon').apply(lambda x: x - x.mean(), shortcut=False)
Because multidimensional groups have the ability to generate a very large
@@ -213,4 +219,4 @@ applying your function, and then unstacking the result:
.. ipython:: python
stacked = da.stack(gridcell=['ny', 'nx'])
- stacked.groupby('gridcell').sum(xr.ALL_DIMS).unstack('gridcell')
+ stacked.groupby('gridcell').sum(...).unstack('gridcell')
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index 9d3e64badb8..c912fd9e1de 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -25,6 +25,11 @@ Breaking changes
New Features
~~~~~~~~~~~~
+- Changed `xr.ALL_DIMS` to equal python's `Ellipsis` (`...`), and changed internal usages to use
+ `...` directly. As before, you can use this to instruct a `groupby` operation
+ to reduce over all dimensions. While we have no plans to remove `xr.ALL_DIMS`, we suggest
+ using `...`.
+ By `<NAME>`_
- Added integration tests against `pint <https://pint.readthedocs.io/>`_.
(:pull:`<PRID>`) by `<NAME>`_.
|
pydata/xarray
|
pydata__xarray-3475
|
https://github.com/pydata/xarray/pull/3475
|
diff --git a/doc/data-structures.rst b/doc/data-structures.rst
index d5567f4863e..93cdc7e9765 100644
--- a/doc/data-structures.rst
+++ b/doc/data-structures.rst
@@ -393,14 +393,14 @@ methods (like pandas) for transforming datasets into new objects.
For removing variables, you can select and drop an explicit list of
variables by indexing with a list of names or using the
-:py:meth:`~xarray.Dataset.drop` methods to return a new ``Dataset``. These
+:py:meth:`~xarray.Dataset.drop_vars` methods to return a new ``Dataset``. These
operations keep around coordinates:
.. ipython:: python
ds[['temperature']]
ds[['temperature', 'temperature_double']]
- ds.drop('temperature')
+ ds.drop_vars('temperature')
To remove a dimension, you can use :py:meth:`~xarray.Dataset.drop_dims` method.
Any variables using that dimension are dropped:
diff --git a/doc/indexing.rst b/doc/indexing.rst
index 9ee8f1dddf8..ace960689a8 100644
--- a/doc/indexing.rst
+++ b/doc/indexing.rst
@@ -232,14 +232,14 @@ Using indexing to *assign* values to a subset of dataset (e.g.,
Dropping labels and dimensions
------------------------------
-The :py:meth:`~xarray.Dataset.drop` method returns a new object with the listed
+The :py:meth:`~xarray.Dataset.drop_sel` method returns a new object with the listed
index labels along a dimension dropped:
.. ipython:: python
- ds.drop(space=['IN', 'IL'])
+ ds.drop_sel(space=['IN', 'IL'])
-``drop`` is both a ``Dataset`` and ``DataArray`` method.
+``drop_sel`` is both a ``Dataset`` and ``DataArray`` method.
Use :py:meth:`~xarray.Dataset.drop_dims` to drop a full dimension from a Dataset.
Any variables with these dimensions are also dropped:
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index dcaab011e67..0906058469d 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -38,6 +38,12 @@ Breaking changes
New Features
~~~~~~~~~~~~
+- :py:meth:`Dataset.drop_sel` & :py:meth:`DataArray.drop_sel` have been added for dropping labels.
+ :py:meth:`Dataset.drop_vars` & :py:meth:`DataArray.drop_vars` have been added for
+ dropping variables (including coordinates). The existing ``drop`` methods remain as a backward compatible
+ option for dropping either lables or variables, but using the more specific methods is encouraged.
+ (:pull:`3475`)
+ By `Maximilian Roos <https://github.com/max-sixty>`_
- :py:meth:`Dataset.transpose` and :py:meth:`DataArray.transpose` now support an ellipsis (`...`)
to represent all 'other' dimensions. For example, to move one dimension to the front,
use `.transpose('x', ...)`. (:pull:`3421`)
@@ -3752,6 +3758,7 @@ Enhancements
explicitly listed variables or index labels:
.. ipython:: python
+ :okwarning:
# drop variables
ds = xray.Dataset({'x': 0, 'y': 1})
diff --git a/xarray/core/concat.py b/xarray/core/concat.py
index c26153eb0d8..5b4fc078236 100644
--- a/xarray/core/concat.py
+++ b/xarray/core/concat.py
@@ -388,7 +388,7 @@ def ensure_common_dims(vars):
result = result.set_coords(coord_names)
result.encoding = result_encoding
- result = result.drop(unlabeled_dims, errors="ignore")
+ result = result.drop_vars(unlabeled_dims, errors="ignore")
if coord is not None:
# add concat dimension last to ensure that its in the final Dataset
diff --git a/xarray/core/dataarray.py b/xarray/core/dataarray.py
index 35ee90fb5c8..d2d37871ee9 100644
--- a/xarray/core/dataarray.py
+++ b/xarray/core/dataarray.py
@@ -16,7 +16,6 @@
TypeVar,
Union,
cast,
- overload,
)
import numpy as np
@@ -53,7 +52,7 @@
from .formatting import format_item
from .indexes import Indexes, default_indexes
from .options import OPTIONS
-from .utils import Default, ReprObject, _default, _check_inplace, either_dict_or_kwargs
+from .utils import Default, ReprObject, _check_inplace, _default, either_dict_or_kwargs
from .variable import (
IndexVariable,
Variable,
@@ -249,7 +248,7 @@ class DataArray(AbstractArray, DataWithCoords):
Dictionary for holding arbitrary metadata.
"""
- _accessors: Optional[Dict[str, Any]]
+ _accessors: Optional[Dict[str, Any]] # noqa
_coords: Dict[Any, Variable]
_indexes: Optional[Dict[Hashable, pd.Index]]
_name: Optional[Hashable]
@@ -1890,41 +1889,72 @@ def transpose(self, *dims: Hashable, transpose_coords: bool = None) -> "DataArra
def T(self) -> "DataArray":
return self.transpose()
- # Drop coords
- @overload
- def drop(
- self, labels: Union[Hashable, Iterable[Hashable]], *, errors: str = "raise"
+ def drop_vars(
+ self, names: Union[Hashable, Iterable[Hashable]], *, errors: str = "raise"
) -> "DataArray":
- ...
+ """Drop variables from this DataArray.
+
+ Parameters
+ ----------
+ names : hashable or iterable of hashables
+ Name(s) of variables to drop.
+ errors: {'raise', 'ignore'}, optional
+ If 'raise' (default), raises a ValueError error if any of the variable
+ passed are not in the dataset. If 'ignore', any given names that are in the
+ DataArray are dropped and no error is raised.
+
+ Returns
+ -------
+ dropped : Dataset
+
+ """
+ ds = self._to_temp_dataset().drop_vars(names, errors=errors)
+ return self._from_temp_dataset(ds)
- # Drop index labels along dimension
- @overload # noqa: F811
def drop(
- self, labels: Any, dim: Hashable, *, errors: str = "raise" # array-like
+ self,
+ labels: Mapping = None,
+ dim: Hashable = None,
+ *,
+ errors: str = "raise",
+ **labels_kwargs,
) -> "DataArray":
- ...
+ """Backward compatible method based on `drop_vars` and `drop_sel`
- def drop(self, labels, dim=None, *, errors="raise"): # noqa: F811
- """Drop coordinates or index labels from this DataArray.
+ Using either `drop_vars` or `drop_sel` is encouraged
+ """
+ ds = self._to_temp_dataset().drop(labels, dim, errors=errors)
+ return self._from_temp_dataset(ds)
+
+ def drop_sel(
+ self,
+ labels: Mapping[Hashable, Any] = None,
+ *,
+ errors: str = "raise",
+ **labels_kwargs,
+ ) -> "DataArray":
+ """Drop index labels from this DataArray.
Parameters
----------
- labels : hashable or sequence of hashables
- Name(s) of coordinates or index labels to drop.
- If dim is not None, labels can be any array-like.
- dim : hashable, optional
- Dimension along which to drop index labels. By default (if
- ``dim is None``), drops coordinates rather than index labels.
+ labels : Mapping[Hashable, Any]
+ Index labels to drop
errors: {'raise', 'ignore'}, optional
If 'raise' (default), raises a ValueError error if
- any of the coordinates or index labels passed are not
- in the array. If 'ignore', any given labels that are in the
- array are dropped and no error is raised.
+ any of the index labels passed are not
+ in the dataset. If 'ignore', any given labels that are in the
+ dataset are dropped and no error is raised.
+ **labels_kwargs : {dim: label, ...}, optional
+ The keyword arguments form of ``dim`` and ``labels``
+
Returns
-------
dropped : DataArray
"""
- ds = self._to_temp_dataset().drop(labels, dim, errors=errors)
+ if labels_kwargs or isinstance(labels, dict):
+ labels = either_dict_or_kwargs(labels, labels_kwargs, "drop")
+
+ ds = self._to_temp_dataset().drop_sel(labels, errors=errors)
return self._from_temp_dataset(ds)
def dropna(
diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index 978242e5f6b..2cadc90334c 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -25,7 +25,6 @@
TypeVar,
Union,
cast,
- overload,
)
import numpy as np
@@ -80,6 +79,7 @@
hashable,
is_dict_like,
is_list_like,
+ is_scalar,
maybe_wrap_array,
)
from .variable import IndexVariable, Variable, as_variable, broadcast_variables
@@ -3519,39 +3519,98 @@ def _assert_all_in_dataset(
"cannot be found in this dataset"
)
- # Drop variables
- @overload # noqa: F811
- def drop(
- self, labels: Union[Hashable, Iterable[Hashable]], *, errors: str = "raise"
+ def drop_vars(
+ self, names: Union[Hashable, Iterable[Hashable]], *, errors: str = "raise"
) -> "Dataset":
- ...
+ """Drop variables from this dataset.
- # Drop index labels along dimension
- @overload # noqa: F811
- def drop(
- self, labels: Any, dim: Hashable, *, errors: str = "raise" # array-like
- ) -> "Dataset":
- ...
+ Parameters
+ ----------
+ names : hashable or iterable of hashables
+ Name(s) of variables to drop.
+ errors: {'raise', 'ignore'}, optional
+ If 'raise' (default), raises a ValueError error if any of the variable
+ passed are not in the dataset. If 'ignore', any given names that are in the
+ dataset are dropped and no error is raised.
- def drop( # noqa: F811
- self, labels=None, dim=None, *, errors="raise", **labels_kwargs
- ):
- """Drop variables or index labels from this dataset.
+ Returns
+ -------
+ dropped : Dataset
+
+ """
+ # the Iterable check is required for mypy
+ if is_scalar(names) or not isinstance(names, Iterable):
+ names = {names}
+ else:
+ names = set(names)
+ if errors == "raise":
+ self._assert_all_in_dataset(names)
+
+ variables = {k: v for k, v in self._variables.items() if k not in names}
+ coord_names = {k for k in self._coord_names if k in variables}
+ indexes = {k: v for k, v in self.indexes.items() if k not in names}
+ return self._replace_with_new_dims(
+ variables, coord_names=coord_names, indexes=indexes
+ )
+
+ def drop(self, labels=None, dim=None, *, errors="raise", **labels_kwargs):
+ """Backward compatible method based on `drop_vars` and `drop_sel`
+
+ Using either `drop_vars` or `drop_sel` is encouraged
+ """
+ if errors not in ["raise", "ignore"]:
+ raise ValueError('errors must be either "raise" or "ignore"')
+
+ if is_dict_like(labels) and not isinstance(labels, dict):
+ warnings.warn(
+ "dropping coordinates using `drop` is be deprecated; use drop_vars.",
+ FutureWarning,
+ stacklevel=2,
+ )
+ return self.drop_vars(labels, errors=errors)
+
+ if labels_kwargs or isinstance(labels, dict):
+ if dim is not None:
+ raise ValueError("cannot specify dim and dict-like arguments.")
+ labels = either_dict_or_kwargs(labels, labels_kwargs, "drop")
+
+ if dim is None and (is_list_like(labels) or is_scalar(labels)):
+ warnings.warn(
+ "dropping variables using `drop` will be deprecated; using drop_vars is encouraged.",
+ PendingDeprecationWarning,
+ stacklevel=2,
+ )
+ return self.drop_vars(labels, errors=errors)
+ if dim is not None:
+ warnings.warn(
+ "dropping labels using list-like labels is deprecated; using "
+ "dict-like arguments with `drop_sel`, e.g. `ds.drop_sel(dim=[labels]).",
+ DeprecationWarning,
+ stacklevel=2,
+ )
+ return self.drop_sel({dim: labels}, errors=errors, **labels_kwargs)
+
+ warnings.warn(
+ "dropping labels using `drop` will be deprecated; using drop_sel is encouraged.",
+ PendingDeprecationWarning,
+ stacklevel=2,
+ )
+ return self.drop_sel(labels, errors=errors)
+
+ def drop_sel(self, labels=None, *, errors="raise", **labels_kwargs):
+ """Drop index labels from this dataset.
Parameters
----------
- labels : hashable or iterable of hashables
- Name(s) of variables or index labels to drop.
- dim : None or hashable, optional
- Dimension along which to drop index labels. By default (if
- ``dim is None``), drops variables rather than index labels.
+ labels : Mapping[Hashable, Any]
+ Index labels to drop
errors: {'raise', 'ignore'}, optional
If 'raise' (default), raises a ValueError error if
- any of the variable or index labels passed are not
+ any of the index labels passed are not
in the dataset. If 'ignore', any given labels that are in the
dataset are dropped and no error is raised.
**labels_kwargs : {dim: label, ...}, optional
- The keyword arguments form of ``dim`` and ``labels``.
+ The keyword arguments form of ``dim`` and ``labels`
Returns
-------
@@ -3562,7 +3621,7 @@ def drop( # noqa: F811
>>> data = np.random.randn(2, 3)
>>> labels = ['a', 'b', 'c']
>>> ds = xr.Dataset({'A': (['x', 'y'], data), 'y': labels})
- >>> ds.drop(y=['a', 'c'])
+ >>> ds.drop_sel(y=['a', 'c'])
<xarray.Dataset>
Dimensions: (x: 2, y: 1)
Coordinates:
@@ -3570,7 +3629,7 @@ def drop( # noqa: F811
Dimensions without coordinates: x
Data variables:
A (x, y) float64 -0.3454 0.1734
- >>> ds.drop(y='b')
+ >>> ds.drop_sel(y='b')
<xarray.Dataset>
Dimensions: (x: 2, y: 2)
Coordinates:
@@ -3582,61 +3641,22 @@ def drop( # noqa: F811
if errors not in ["raise", "ignore"]:
raise ValueError('errors must be either "raise" or "ignore"')
- if is_dict_like(labels) and not isinstance(labels, dict):
- warnings.warn(
- "dropping coordinates using key values of dict-like labels is "
- "deprecated; use drop_vars or a list of coordinates.",
- FutureWarning,
- stacklevel=2,
- )
- if dim is not None and is_list_like(labels):
- warnings.warn(
- "dropping dimensions using list-like labels is deprecated; use "
- "dict-like arguments.",
- DeprecationWarning,
- stacklevel=2,
- )
+ labels = either_dict_or_kwargs(labels, labels_kwargs, "drop")
- if labels_kwargs or isinstance(labels, dict):
- labels_kwargs = either_dict_or_kwargs(labels, labels_kwargs, "drop")
- if dim is not None:
- raise ValueError("cannot specify dim and dict-like arguments.")
- ds = self
- for dim, labels in labels_kwargs.items():
- ds = ds._drop_labels(labels, dim, errors=errors)
- return ds
- elif dim is None:
- if isinstance(labels, str) or not isinstance(labels, Iterable):
- labels = {labels}
- else:
- labels = set(labels)
- return self._drop_vars(labels, errors=errors)
- else:
- return self._drop_labels(labels, dim, errors=errors)
-
- def _drop_labels(self, labels=None, dim=None, errors="raise"):
- # Don't cast to set, as it would harm performance when labels
- # is a large numpy array
- if utils.is_scalar(labels):
- labels = [labels]
- labels = np.asarray(labels)
- try:
- index = self.indexes[dim]
- except KeyError:
- raise ValueError("dimension %r does not have coordinate labels" % dim)
- new_index = index.drop(labels, errors=errors)
- return self.loc[{dim: new_index}]
-
- def _drop_vars(self, names: set, errors: str = "raise") -> "Dataset":
- if errors == "raise":
- self._assert_all_in_dataset(names)
-
- variables = {k: v for k, v in self._variables.items() if k not in names}
- coord_names = {k for k in self._coord_names if k in variables}
- indexes = {k: v for k, v in self.indexes.items() if k not in names}
- return self._replace_with_new_dims(
- variables, coord_names=coord_names, indexes=indexes
- )
+ ds = self
+ for dim, labels_for_dim in labels.items():
+ # Don't cast to set, as it would harm performance when labels
+ # is a large numpy array
+ if utils.is_scalar(labels_for_dim):
+ labels_for_dim = [labels_for_dim]
+ labels_for_dim = np.asarray(labels_for_dim)
+ try:
+ index = self.indexes[dim]
+ except KeyError:
+ raise ValueError("dimension %r does not have coordinate labels" % dim)
+ new_index = index.drop(labels_for_dim, errors=errors)
+ ds = ds.loc[{dim: new_index}]
+ return ds
def drop_dims(
self, drop_dims: Union[Hashable, Iterable[Hashable]], *, errors: str = "raise"
@@ -3679,7 +3699,7 @@ def drop_dims(
)
drop_vars = {k for k, v in self._variables.items() if set(v.dims) & drop_dims}
- return self._drop_vars(drop_vars)
+ return self.drop_vars(drop_vars)
def transpose(self, *dims: Hashable) -> "Dataset":
"""Return a new Dataset object with all array dimensions transposed.
diff --git a/xarray/core/groupby.py b/xarray/core/groupby.py
index 209ac14184b..c8906e34737 100644
--- a/xarray/core/groupby.py
+++ b/xarray/core/groupby.py
@@ -775,7 +775,7 @@ def quantile(self, q, dim=None, interpolation="linear", keep_attrs=None):
)
if np.asarray(q, dtype=np.float64).ndim == 0:
- out = out.drop("quantile")
+ out = out.drop_vars("quantile")
return out
def reduce(
diff --git a/xarray/core/merge.py b/xarray/core/merge.py
index daf0c3b059f..10c7804d718 100644
--- a/xarray/core/merge.py
+++ b/xarray/core/merge.py
@@ -859,6 +859,6 @@ def dataset_update_method(
if c not in value.dims and c in dataset.coords
]
if coord_names:
- other[key] = value.drop(coord_names)
+ other[key] = value.drop_vars(coord_names)
return merge_core([dataset, other], priority_arg=1, indexes=dataset.indexes)
diff --git a/xarray/core/resample.py b/xarray/core/resample.py
index 998964273be..2cb1bd55e19 100644
--- a/xarray/core/resample.py
+++ b/xarray/core/resample.py
@@ -47,7 +47,7 @@ def _upsample(self, method, *args, **kwargs):
if k == self._dim:
continue
if self._dim in v.dims:
- self._obj = self._obj.drop(k)
+ self._obj = self._obj.drop_vars(k)
if method == "asfreq":
return self.mean(self._dim)
@@ -146,7 +146,7 @@ def _interpolate(self, kind="linear"):
dummy = self._obj.copy()
for k, v in self._obj.coords.items():
if k != self._dim and self._dim in v.dims:
- dummy = dummy.drop(k)
+ dummy = dummy.drop_vars(k)
return dummy.interp(
assume_sorted=True,
method=kind,
@@ -218,7 +218,7 @@ def apply(self, func, shortcut=False, args=(), **kwargs):
# dimension, then we need to do so before we can rename the proxy
# dimension we used.
if self._dim in combined.coords:
- combined = combined.drop(self._dim)
+ combined = combined.drop_vars(self._dim)
if self._resample_dim in combined.dims:
combined = combined.rename({self._resample_dim: self._dim})
|
diff --git a/xarray/tests/test_backends.py b/xarray/tests/test_backends.py
index 9b000b82b03..de3a7eadab0 100644
--- a/xarray/tests/test_backends.py
+++ b/xarray/tests/test_backends.py
@@ -800,7 +800,7 @@ def equals_latlon(obj):
assert "coordinates" not in ds["lat"].attrs
assert "coordinates" not in ds["lon"].attrs
- modified = original.drop(["temp", "precip"])
+ modified = original.drop_vars(["temp", "precip"])
with self.roundtrip(modified) as actual:
assert_identical(actual, modified)
with create_tmp_file() as tmp_file:
@@ -2177,7 +2177,7 @@ def test_cross_engine_read_write_netcdf4(self):
# Drop dim3, because its labels include strings. These appear to be
# not properly read with python-netCDF4, which converts them into
# unicode instead of leaving them as bytes.
- data = create_test_data().drop("dim3")
+ data = create_test_data().drop_vars("dim3")
data.attrs["foo"] = "bar"
valid_engines = ["netcdf4", "h5netcdf"]
for write_engine in valid_engines:
@@ -2344,7 +2344,7 @@ def test_open_twice(self):
def test_open_fileobj(self):
# open in-memory datasets instead of local file paths
- expected = create_test_data().drop("dim3")
+ expected = create_test_data().drop_vars("dim3")
expected.attrs["foo"] = "bar"
with create_tmp_file() as tmp_file:
expected.to_netcdf(tmp_file, engine="h5netcdf")
@@ -4190,7 +4190,7 @@ def test_open_dataarray_options(self):
with create_tmp_file() as tmp:
data.to_netcdf(tmp)
- expected = data.drop("y")
+ expected = data.drop_vars("y")
with open_dataarray(tmp, drop_variables=["y"]) as loaded:
assert_identical(expected, loaded)
diff --git a/xarray/tests/test_dask.py b/xarray/tests/test_dask.py
index 34115b29b23..fa8ae9991d7 100644
--- a/xarray/tests/test_dask.py
+++ b/xarray/tests/test_dask.py
@@ -1129,11 +1129,11 @@ def test_map_blocks_to_array(map_ds):
[
lambda x: x,
lambda x: x.to_dataset(),
- lambda x: x.drop("x"),
+ lambda x: x.drop_vars("x"),
lambda x: x.expand_dims(k=[1, 2, 3]),
lambda x: x.assign_coords(new_coord=("y", x.y * 2)),
lambda x: x.astype(np.int32),
- # TODO: [lambda x: x.isel(x=1).drop("x"), map_da],
+ # TODO: [lambda x: x.isel(x=1).drop_vars("x"), map_da],
],
)
def test_map_blocks_da_transformations(func, map_da):
@@ -1147,9 +1147,9 @@ def test_map_blocks_da_transformations(func, map_da):
"func",
[
lambda x: x,
- lambda x: x.drop("cxy"),
- lambda x: x.drop("a"),
- lambda x: x.drop("x"),
+ lambda x: x.drop_vars("cxy"),
+ lambda x: x.drop_vars("a"),
+ lambda x: x.drop_vars("x"),
lambda x: x.expand_dims(k=[1, 2, 3]),
lambda x: x.rename({"a": "new1", "b": "new2"}),
# TODO: [lambda x: x.isel(x=1)],
diff --git a/xarray/tests/test_dataarray.py b/xarray/tests/test_dataarray.py
index 2c823b0c20a..acfe684d220 100644
--- a/xarray/tests/test_dataarray.py
+++ b/xarray/tests/test_dataarray.py
@@ -906,7 +906,7 @@ def test_sel_dataarray(self):
assert_array_equal(actual, da.isel(x=[0, 1, 2]))
assert "new_dim" in actual.dims
assert "new_dim" in actual.coords
- assert_equal(actual["new_dim"].drop("x"), ind["new_dim"])
+ assert_equal(actual["new_dim"].drop_vars("x"), ind["new_dim"])
def test_sel_invalid_slice(self):
array = DataArray(np.arange(10), [("x", np.arange(10))])
@@ -1660,7 +1660,7 @@ def test_expand_dims_with_greater_dim_size(self):
coords=expected_coords,
dims=list(expected_coords.keys()),
attrs={"key": "entry"},
- ).drop(["y", "dim_0"])
+ ).drop_vars(["y", "dim_0"])
assert_identical(expected, actual)
# Test with kwargs instead of passing dict to dim arg.
@@ -1677,7 +1677,7 @@ def test_expand_dims_with_greater_dim_size(self):
},
dims=["dim_1", "x", "dim_0"],
attrs={"key": "entry"},
- ).drop("dim_0")
+ ).drop_vars("dim_0")
assert_identical(other_way_expected, other_way)
def test_set_index(self):
@@ -1993,7 +1993,7 @@ def test_stack_unstack(self):
)
pd.util.testing.assert_index_equal(a, b)
- actual = orig.stack(z=["x", "y"]).unstack("z").drop(["x", "y"])
+ actual = orig.stack(z=["x", "y"]).unstack("z").drop_vars(["x", "y"])
assert_identical(orig, actual)
dims = ["a", "b", "c", "d", "e"]
@@ -2001,11 +2001,11 @@ def test_stack_unstack(self):
stacked = orig.stack(ab=["a", "b"], cd=["c", "d"])
unstacked = stacked.unstack(["ab", "cd"])
- roundtripped = unstacked.drop(["a", "b", "c", "d"]).transpose(*dims)
+ roundtripped = unstacked.drop_vars(["a", "b", "c", "d"]).transpose(*dims)
assert_identical(orig, roundtripped)
unstacked = stacked.unstack()
- roundtripped = unstacked.drop(["a", "b", "c", "d"]).transpose(*dims)
+ roundtripped = unstacked.drop_vars(["a", "b", "c", "d"]).transpose(*dims)
assert_identical(orig, roundtripped)
def test_stack_unstack_decreasing_coordinate(self):
@@ -2109,40 +2109,43 @@ def test_drop_coordinates(self):
expected = DataArray(np.random.randn(2, 3), dims=["x", "y"])
arr = expected.copy()
arr.coords["z"] = 2
- actual = arr.drop("z")
+ actual = arr.drop_vars("z")
assert_identical(expected, actual)
with pytest.raises(ValueError):
- arr.drop("not found")
+ arr.drop_vars("not found")
- actual = expected.drop("not found", errors="ignore")
+ actual = expected.drop_vars("not found", errors="ignore")
assert_identical(actual, expected)
with raises_regex(ValueError, "cannot be found"):
- arr.drop("w")
+ arr.drop_vars("w")
- actual = expected.drop("w", errors="ignore")
+ actual = expected.drop_vars("w", errors="ignore")
assert_identical(actual, expected)
renamed = arr.rename("foo")
with raises_regex(ValueError, "cannot be found"):
- renamed.drop("foo")
+ renamed.drop_vars("foo")
- actual = renamed.drop("foo", errors="ignore")
+ actual = renamed.drop_vars("foo", errors="ignore")
assert_identical(actual, renamed)
def test_drop_index_labels(self):
arr = DataArray(np.random.randn(2, 3), coords={"y": [0, 1, 2]}, dims=["x", "y"])
- actual = arr.drop([0, 1], dim="y")
+ actual = arr.drop_sel(y=[0, 1])
expected = arr[:, 2:]
assert_identical(actual, expected)
with raises_regex((KeyError, ValueError), "not .* in axis"):
- actual = arr.drop([0, 1, 3], dim="y")
+ actual = arr.drop_sel(y=[0, 1, 3])
- actual = arr.drop([0, 1, 3], dim="y", errors="ignore")
+ actual = arr.drop_sel(y=[0, 1, 3], errors="ignore")
assert_identical(actual, expected)
+ with pytest.warns(DeprecationWarning):
+ arr.drop([0, 1, 3], dim="y", errors="ignore")
+
def test_dropna(self):
x = np.random.randn(4, 4)
x[::2, 0] = np.nan
@@ -3360,7 +3363,7 @@ def test_to_pandas(self):
da = DataArray(np.random.randn(*shape), dims=dims)
with warnings.catch_warnings():
warnings.filterwarnings("ignore", r"\W*Panel is deprecated")
- roundtripped = DataArray(da.to_pandas()).drop(dims)
+ roundtripped = DataArray(da.to_pandas()).drop_vars(dims)
assert_identical(da, roundtripped)
with raises_regex(ValueError, "cannot convert"):
@@ -3411,11 +3414,13 @@ def test_to_and_from_series(self):
assert_array_equal(expected.index.values, actual.index.values)
assert "foo" == actual.name
# test roundtrip
- assert_identical(self.dv, DataArray.from_series(actual).drop(["x", "y"]))
+ assert_identical(self.dv, DataArray.from_series(actual).drop_vars(["x", "y"]))
# test name is None
actual.name = None
expected_da = self.dv.rename(None)
- assert_identical(expected_da, DataArray.from_series(actual).drop(["x", "y"]))
+ assert_identical(
+ expected_da, DataArray.from_series(actual).drop_vars(["x", "y"])
+ )
@requires_sparse
def test_from_series_sparse(self):
@@ -3478,7 +3483,7 @@ def test_to_and_from_dict(self):
# and the most bare bones representation still roundtrips
d = {"name": "foo", "dims": ("x", "y"), "data": array.values}
- assert_identical(array.drop("x"), DataArray.from_dict(d))
+ assert_identical(array.drop_vars("x"), DataArray.from_dict(d))
# missing a dims in the coords
d = {
diff --git a/xarray/tests/test_dataset.py b/xarray/tests/test_dataset.py
index b9fa20fab26..50e78c9f685 100644
--- a/xarray/tests/test_dataset.py
+++ b/xarray/tests/test_dataset.py
@@ -322,7 +322,7 @@ def __repr__(self):
def test_info(self):
ds = create_test_data(seed=123)
- ds = ds.drop("dim3") # string type prints differently in PY2 vs PY3
+ ds = ds.drop_vars("dim3") # string type prints differently in PY2 vs PY3
ds.attrs["unicode_attr"] = "ba®"
ds.attrs["string_attr"] = "bar"
@@ -509,7 +509,9 @@ def test_constructor_compat(self):
{"c": (("x", "y"), np.zeros((2, 3))), "x": [0, 1]},
)
- actual = Dataset({"a": original["a"][:, 0], "b": original["a"][0].drop("x")})
+ actual = Dataset(
+ {"a": original["a"][:, 0], "b": original["a"][0].drop_vars("x")}
+ )
assert_identical(expected, actual)
data = {"x": DataArray(0, coords={"y": 3}), "y": ("z", [1, 1, 1])}
@@ -775,9 +777,9 @@ def test_coords_set(self):
one_coord.reset_coords("x")
actual = all_coords.reset_coords("zzz", drop=True)
- expected = all_coords.drop("zzz")
+ expected = all_coords.drop_vars("zzz")
assert_identical(expected, actual)
- expected = two_coords.drop("zzz")
+ expected = two_coords.drop_vars("zzz")
assert_identical(expected, actual)
def test_coords_to_dataset(self):
@@ -954,7 +956,7 @@ def test_dask_is_lazy(self):
ds.fillna(0)
ds.rename({"dim1": "foobar"})
ds.set_coords("var1")
- ds.drop("var1")
+ ds.drop_vars("var1")
def test_isel(self):
data = create_test_data()
@@ -1097,7 +1099,7 @@ def test_isel_fancy(self):
actual = data.isel(dim1=stations["dim1s"], dim2=stations["dim2s"])
assert "station" in actual.coords
assert "station" in actual.dims
- assert_identical(actual["station"].drop(["dim2"]), stations["station"])
+ assert_identical(actual["station"].drop_vars(["dim2"]), stations["station"])
with raises_regex(ValueError, "conflicting values for "):
data.isel(
@@ -1123,7 +1125,7 @@ def test_isel_fancy(self):
assert "dim2" in actual.coords
assert "a" in actual["dim2"].dims
- assert_identical(actual["a"].drop(["dim2"]), stations["a"])
+ assert_identical(actual["a"].drop_vars(["dim2"]), stations["a"])
assert_identical(actual["b"], stations["b"])
expected_var1 = data["var1"].variable[
stations["dim1s"].variable, stations["dim2s"].variable
@@ -1132,7 +1134,7 @@ def test_isel_fancy(self):
stations["dim1s"].variable, stations["dim2s"].variable
]
expected_var3 = data["var3"].variable[slice(None), stations["dim1s"].variable]
- assert_equal(actual["a"].drop("dim2"), stations["a"])
+ assert_equal(actual["a"].drop_vars("dim2"), stations["a"])
assert_array_equal(actual["var1"], expected_var1)
assert_array_equal(actual["var2"], expected_var2)
assert_array_equal(actual["var3"], expected_var3)
@@ -1200,7 +1202,7 @@ def test_isel_dataarray(self):
indexing_da = indexing_da < 3
actual = data.isel(dim2=indexing_da)
assert_identical(
- actual["dim2"].drop("non_dim").drop("non_dim2"), data["dim2"][:2]
+ actual["dim2"].drop_vars("non_dim").drop_vars("non_dim2"), data["dim2"][:2]
)
assert_identical(actual["non_dim"], indexing_da["non_dim"][:2])
assert_identical(actual["non_dim2"], indexing_da["non_dim2"])
@@ -1286,8 +1288,10 @@ def test_sel_dataarray(self):
expected = data.isel(dim2=[0, 1, 2]).rename({"dim2": "new_dim"})
assert "new_dim" in actual.dims
assert "new_dim" in actual.coords
- assert_equal(actual.drop("new_dim").drop("dim2"), expected.drop("new_dim"))
- assert_equal(actual["new_dim"].drop("dim2"), ind["new_dim"])
+ assert_equal(
+ actual.drop_vars("new_dim").drop_vars("dim2"), expected.drop_vars("new_dim")
+ )
+ assert_equal(actual["new_dim"].drop_vars("dim2"), ind["new_dim"])
# with conflicted coordinate (silently ignored)
ind = DataArray(
@@ -1304,10 +1308,12 @@ def test_sel_dataarray(self):
coords={"new_dim": ["a", "b", "c"], "dim2": 3},
)
actual = data.sel(dim2=ind)
- assert_equal(actual["new_dim"].drop("dim2"), ind["new_dim"].drop("dim2"))
+ assert_equal(
+ actual["new_dim"].drop_vars("dim2"), ind["new_dim"].drop_vars("dim2")
+ )
expected = data.isel(dim2=[0, 1, 2])
expected["dim2"] = (("new_dim"), expected["dim2"].values)
- assert_equal(actual["dim2"].drop("new_dim"), expected["dim2"])
+ assert_equal(actual["dim2"].drop_vars("new_dim"), expected["dim2"])
assert actual["var1"].dims == ("dim1", "new_dim")
# with non-dimensional coordinate
@@ -1322,7 +1328,7 @@ def test_sel_dataarray(self):
)
actual = data.sel(dim2=ind)
expected = data.isel(dim2=[0, 1, 2])
- assert_equal(actual.drop("new_dim"), expected)
+ assert_equal(actual.drop_vars("new_dim"), expected)
assert np.allclose(actual["new_dim"].values, ind["new_dim"].values)
def test_sel_dataarray_mindex(self):
@@ -1554,8 +1560,8 @@ def test_sel_fancy(self):
expected_ary = data["foo"][[0, 1, 2], [0, 2, 1]]
actual = data.sel(x=idx_x, y=idx_y)
assert_array_equal(expected_ary, actual["foo"])
- assert_identical(actual["a"].drop("x"), idx_x["a"])
- assert_identical(actual["b"].drop("y"), idx_y["b"])
+ assert_identical(actual["a"].drop_vars("x"), idx_x["a"])
+ assert_identical(actual["b"].drop_vars("y"), idx_y["b"])
with pytest.raises(KeyError):
data.sel(x=[2.5], y=[2.0], method="pad", tolerance=1e-3)
@@ -2094,36 +2100,50 @@ def test_variable_indexing(self):
def test_drop_variables(self):
data = create_test_data()
- assert_identical(data, data.drop([]))
+ assert_identical(data, data.drop_vars([]))
expected = Dataset({k: data[k] for k in data.variables if k != "time"})
- actual = data.drop("time")
+ actual = data.drop_vars("time")
assert_identical(expected, actual)
- actual = data.drop(["time"])
+ actual = data.drop_vars(["time"])
assert_identical(expected, actual)
with raises_regex(ValueError, "cannot be found"):
- data.drop("not_found_here")
+ data.drop_vars("not_found_here")
+
+ actual = data.drop_vars("not_found_here", errors="ignore")
+ assert_identical(data, actual)
+
+ actual = data.drop_vars(["not_found_here"], errors="ignore")
+ assert_identical(data, actual)
+
+ actual = data.drop_vars(["time", "not_found_here"], errors="ignore")
+ assert_identical(expected, actual)
+
+ # deprecated approach with `drop` works (straight copy paste from above)
- actual = data.drop("not_found_here", errors="ignore")
+ with pytest.warns(PendingDeprecationWarning):
+ actual = data.drop("not_found_here", errors="ignore")
assert_identical(data, actual)
- actual = data.drop(["not_found_here"], errors="ignore")
+ with pytest.warns(PendingDeprecationWarning):
+ actual = data.drop(["not_found_here"], errors="ignore")
assert_identical(data, actual)
- actual = data.drop(["time", "not_found_here"], errors="ignore")
+ with pytest.warns(PendingDeprecationWarning):
+ actual = data.drop(["time", "not_found_here"], errors="ignore")
assert_identical(expected, actual)
def test_drop_index_labels(self):
data = Dataset({"A": (["x", "y"], np.random.randn(2, 3)), "x": ["a", "b"]})
with pytest.warns(DeprecationWarning):
- actual = data.drop(["a"], "x")
+ actual = data.drop(["a"], dim="x")
expected = data.isel(x=[1])
assert_identical(expected, actual)
with pytest.warns(DeprecationWarning):
- actual = data.drop(["a", "b"], "x")
+ actual = data.drop(["a", "b"], dim="x")
expected = data.isel(x=slice(0, 0))
assert_identical(expected, actual)
@@ -2147,30 +2167,30 @@ def test_drop_index_labels(self):
# DataArrays as labels are a nasty corner case as they are not
# Iterable[Hashable] - DataArray.__iter__ yields scalar DataArrays.
- actual = data.drop(DataArray(["a", "b", "c"]), "x", errors="ignore")
+ actual = data.drop_sel(x=DataArray(["a", "b", "c"]), errors="ignore")
expected = data.isel(x=slice(0, 0))
assert_identical(expected, actual)
+ with pytest.warns(DeprecationWarning):
+ data.drop(DataArray(["a", "b", "c"]), dim="x", errors="ignore")
+ assert_identical(expected, actual)
with raises_regex(ValueError, "does not have coordinate labels"):
- data.drop(1, "y")
+ data.drop_sel(y=1)
def test_drop_labels_by_keyword(self):
- # Tests for #2910: Support for a additional `drop()` API.
data = Dataset(
{"A": (["x", "y"], np.random.randn(2, 6)), "x": ["a", "b"], "y": range(6)}
)
# Basic functionality.
assert len(data.coords["x"]) == 2
- # In the future, this will break.
with pytest.warns(DeprecationWarning):
ds1 = data.drop(["a"], dim="x")
- ds2 = data.drop(x="a")
- ds3 = data.drop(x=["a"])
- ds4 = data.drop(x=["a", "b"])
- ds5 = data.drop(x=["a", "b"], y=range(0, 6, 2))
+ ds2 = data.drop_sel(x="a")
+ ds3 = data.drop_sel(x=["a"])
+ ds4 = data.drop_sel(x=["a", "b"])
+ ds5 = data.drop_sel(x=["a", "b"], y=range(0, 6, 2))
- # In the future, this will result in different behavior.
arr = DataArray(range(3), dims=["c"])
with pytest.warns(FutureWarning):
data.drop(arr.coords)
@@ -2187,10 +2207,11 @@ def test_drop_labels_by_keyword(self):
# Error handling if user tries both approaches.
with pytest.raises(ValueError):
data.drop(labels=["a"], x="a")
- with pytest.raises(ValueError):
- data.drop(dim="x", x="a")
with pytest.raises(ValueError):
data.drop(labels=["a"], dim="x", x="a")
+ warnings.filterwarnings("ignore", r"\W*drop")
+ with pytest.raises(ValueError):
+ data.drop(dim="x", x="a")
def test_drop_dims(self):
data = xr.Dataset(
@@ -2203,15 +2224,15 @@ def test_drop_dims(self):
)
actual = data.drop_dims("x")
- expected = data.drop(["A", "B", "x"])
+ expected = data.drop_vars(["A", "B", "x"])
assert_identical(expected, actual)
actual = data.drop_dims("y")
- expected = data.drop("A")
+ expected = data.drop_vars("A")
assert_identical(expected, actual)
actual = data.drop_dims(["x", "y"])
- expected = data.drop(["A", "B", "x"])
+ expected = data.drop_vars(["A", "B", "x"])
assert_identical(expected, actual)
with pytest.raises((ValueError, KeyError)):
@@ -2230,7 +2251,7 @@ def test_drop_dims(self):
actual = data.drop_dims("z", errors="wrong_value")
actual = data.drop_dims(["x", "y", "z"], errors="ignore")
- expected = data.drop(["A", "B", "x"])
+ expected = data.drop_vars(["A", "B", "x"])
assert_identical(expected, actual)
def test_copy(self):
@@ -2571,7 +2592,7 @@ def test_expand_dims_mixed_int_and_coords(self):
original["x"].values * np.ones([4, 3, 3]),
coords=dict(d=range(4), e=["l", "m", "n"], a=np.linspace(0, 1, 3)),
dims=["d", "e", "a"],
- ).drop("d"),
+ ).drop_vars("d"),
"y": xr.DataArray(
original["y"].values * np.ones([4, 3, 4, 3]),
coords=dict(
@@ -2581,7 +2602,7 @@ def test_expand_dims_mixed_int_and_coords(self):
a=np.linspace(0, 1, 3),
),
dims=["d", "e", "b", "a"],
- ).drop("d"),
+ ).drop_vars("d"),
},
coords={"c": np.linspace(0, 1, 5)},
)
@@ -3059,7 +3080,7 @@ def test_setitem_with_coords(self):
np.arange(10), dims="dim3", coords={"numbers": ("dim3", np.arange(10))}
)
expected = ds.copy()
- expected["var3"] = other.drop("numbers")
+ expected["var3"] = other.drop_vars("numbers")
actual = ds.copy()
actual["var3"] = other
assert_identical(expected, actual)
@@ -4504,7 +4525,9 @@ def test_apply(self):
actual = data.apply(lambda x: x.mean(keep_attrs=True), keep_attrs=True)
assert_identical(expected, actual)
- assert_identical(data.apply(lambda x: x, keep_attrs=True), data.drop("time"))
+ assert_identical(
+ data.apply(lambda x: x, keep_attrs=True), data.drop_vars("time")
+ )
def scale(x, multiple=1):
return multiple * x
@@ -4514,7 +4537,7 @@ def scale(x, multiple=1):
assert_identical(actual["numbers"], data["numbers"])
actual = data.apply(np.asarray)
- expected = data.drop("time") # time is not used on a data var
+ expected = data.drop_vars("time") # time is not used on a data var
assert_equal(expected, actual)
def make_example_math_dataset(self):
@@ -4616,7 +4639,7 @@ def test_dataset_math_auto_align(self):
assert_identical(expected, actual)
actual = ds.isel(y=slice(1)) + ds.isel(y=slice(1, None))
- expected = 2 * ds.drop(ds.y, dim="y")
+ expected = 2 * ds.drop_sel(y=ds.y)
assert_equal(actual, expected)
actual = ds + ds[["bar"]]
diff --git a/xarray/tests/test_duck_array_ops.py b/xarray/tests/test_duck_array_ops.py
index 9df2f167cf2..f678af2fec5 100644
--- a/xarray/tests/test_duck_array_ops.py
+++ b/xarray/tests/test_duck_array_ops.py
@@ -441,7 +441,8 @@ def test_argmin_max(dim_num, dtype, contains_nan, dask, func, skipna, aggdim):
)
expected = getattr(da, func)(dim=aggdim, skipna=skipna)
assert_allclose(
- actual.drop(list(actual.coords)), expected.drop(list(expected.coords))
+ actual.drop_vars(list(actual.coords)),
+ expected.drop_vars(list(expected.coords)),
)
diff --git a/xarray/tests/test_interp.py b/xarray/tests/test_interp.py
index b9dc9a71acc..b93325d7eab 100644
--- a/xarray/tests/test_interp.py
+++ b/xarray/tests/test_interp.py
@@ -553,7 +553,7 @@ def test_datetime_single_string():
actual = da.interp(time="2000-01-01T12:00")
expected = xr.DataArray(0.5)
- assert_allclose(actual.drop("time"), expected)
+ assert_allclose(actual.drop_vars("time"), expected)
@requires_cftime
diff --git a/xarray/tests/test_plot.py b/xarray/tests/test_plot.py
index 7deabd46eae..6e283ea01da 100644
--- a/xarray/tests/test_plot.py
+++ b/xarray/tests/test_plot.py
@@ -1837,7 +1837,11 @@ def test_default_labels(self):
assert substring_in_axes(self.darray.name, ax)
def test_test_empty_cell(self):
- g = self.darray.isel(row=1).drop("row").plot(col="col", hue="hue", col_wrap=2)
+ g = (
+ self.darray.isel(row=1)
+ .drop_vars("row")
+ .plot(col="col", hue="hue", col_wrap=2)
+ )
bottomright = g.axes[-1, -1]
assert not bottomright.has_data()
assert not bottomright.get_visible()
diff --git a/xarray/tests/test_units.py b/xarray/tests/test_units.py
index 9d14104bb50..80063f8b4bc 100644
--- a/xarray/tests/test_units.py
+++ b/xarray/tests/test_units.py
@@ -1093,7 +1093,7 @@ def test_content_manipulation(self, func, dtype):
"func",
(
pytest.param(
- method("drop", labels=np.array([1, 5]), dim="x"),
+ method("drop_sel", labels=dict(x=np.array([1, 5]))),
marks=pytest.mark.xfail(
reason="selecting using incompatible units does not raise"
),
@@ -1128,9 +1128,9 @@ def test_content_manipulation_with_units(self, func, unit, error, dtype):
expected = attach_units(
func(strip_units(data_array), **stripped_kwargs),
- {"data": quantity.units if func.name == "drop" else unit, "x": x.units},
+ {"data": quantity.units if func.name == "drop_sel" else unit, "x": x.units},
)
- if error is not None and func.name == "drop":
+ if error is not None and func.name == "drop_sel":
with pytest.raises(error):
func(data_array, **kwargs)
else:
|
[
{
"path": "doc/data-structures.rst",
"old_path": "a/doc/data-structures.rst",
"new_path": "b/doc/data-structures.rst",
"metadata": "diff --git a/doc/data-structures.rst b/doc/data-structures.rst\nindex d5567f4863e..93cdc7e9765 100644\n--- a/doc/data-structures.rst\n+++ b/doc/data-structures.rst\n@@ -393,14 +393,14 @@ methods (like pandas) for transforming datasets into new objects.\n \n For removing variables, you can select and drop an explicit list of\n variables by indexing with a list of names or using the\n-:py:meth:`~xarray.Dataset.drop` methods to return a new ``Dataset``. These\n+:py:meth:`~xarray.Dataset.drop_vars` methods to return a new ``Dataset``. These\n operations keep around coordinates:\n \n .. ipython:: python\n \n ds[['temperature']]\n ds[['temperature', 'temperature_double']]\n- ds.drop('temperature')\n+ ds.drop_vars('temperature')\n \n To remove a dimension, you can use :py:meth:`~xarray.Dataset.drop_dims` method.\n Any variables using that dimension are dropped:\n"
},
{
"path": "doc/indexing.rst",
"old_path": "a/doc/indexing.rst",
"new_path": "b/doc/indexing.rst",
"metadata": "diff --git a/doc/indexing.rst b/doc/indexing.rst\nindex 9ee8f1dddf8..ace960689a8 100644\n--- a/doc/indexing.rst\n+++ b/doc/indexing.rst\n@@ -232,14 +232,14 @@ Using indexing to *assign* values to a subset of dataset (e.g.,\n Dropping labels and dimensions\n ------------------------------\n \n-The :py:meth:`~xarray.Dataset.drop` method returns a new object with the listed\n+The :py:meth:`~xarray.Dataset.drop_sel` method returns a new object with the listed\n index labels along a dimension dropped:\n \n .. ipython:: python\n \n- ds.drop(space=['IN', 'IL'])\n+ ds.drop_sel(space=['IN', 'IL'])\n \n-``drop`` is both a ``Dataset`` and ``DataArray`` method.\n+``drop_sel`` is both a ``Dataset`` and ``DataArray`` method.\n \n Use :py:meth:`~xarray.Dataset.drop_dims` to drop a full dimension from a Dataset.\n Any variables with these dimensions are also dropped:\n"
},
{
"path": "doc/whats-new.rst",
"old_path": "a/doc/whats-new.rst",
"new_path": "b/doc/whats-new.rst",
"metadata": "diff --git a/doc/whats-new.rst b/doc/whats-new.rst\nindex dcaab011e67..0906058469d 100644\n--- a/doc/whats-new.rst\n+++ b/doc/whats-new.rst\n@@ -38,6 +38,12 @@ Breaking changes\n \n New Features\n ~~~~~~~~~~~~\n+- :py:meth:`Dataset.drop_sel` & :py:meth:`DataArray.drop_sel` have been added for dropping labels.\n+ :py:meth:`Dataset.drop_vars` & :py:meth:`DataArray.drop_vars` have been added for \n+ dropping variables (including coordinates). The existing ``drop`` methods remain as a backward compatible \n+ option for dropping either lables or variables, but using the more specific methods is encouraged.\n+ (:pull:`3475`)\n+ By `Maximilian Roos <https://github.com/max-sixty>`_\n - :py:meth:`Dataset.transpose` and :py:meth:`DataArray.transpose` now support an ellipsis (`...`)\n to represent all 'other' dimensions. For example, to move one dimension to the front,\n use `.transpose('x', ...)`. (:pull:`3421`)\n@@ -3752,6 +3758,7 @@ Enhancements\n explicitly listed variables or index labels:\n \n .. ipython:: python\n+ :okwarning:\n \n # drop variables\n ds = xray.Dataset({'x': 0, 'y': 1})\n"
}
] |
0014
|
4dce93f134e8296ea730104b46ce3372b90304ac
|
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"xarray/tests/test_dataset.py::test_rolling_reduce[sum-1-2-True-2]",
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"xarray/tests/test_duck_array_ops.py::test_reduce[x-False-min-False-float-2]",
"xarray/tests/test_dataset.py::TestDataset::test_assign_attrs",
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"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-2-2-True]",
"xarray/tests/test_dataset.py::TestDataset::test_coords_modify",
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"xarray/tests/test_dataset.py::TestDataset::test_dataset_transpose",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-4-1-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-2-3-True-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_reset_coords",
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"xarray/tests/test_duck_array_ops.py::test_reduce[None-False-min-False-float32-1]",
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"xarray/tests/test_dataarray.py::test_rolling_pandas_compat[4-1-False]",
"xarray/tests/test_duck_array_ops.py::test_reduce[None-False-sum-False-float-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_broadcast_arrays_nocopy",
"xarray/tests/test_dataarray.py::TestDataArray::test_inplace_math_automatic_alignment",
"xarray/tests/test_backends.py::TestCommon::test_robust_getitem",
"xarray/tests/test_dataset.py::test_dataset_constructor_aligns_to_explicit_coords[coords1-unaligned_coords8]",
"xarray/tests/test_dataarray.py::TestDataArray::test_swap_dims",
"xarray/tests/test_dataarray.py::TestDataArray::test_loc_assign",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[sum-1-3-False]",
"xarray/tests/test_dataarray.py::TestDataArray::test_expand_dims_error",
"xarray/tests/test_duck_array_ops.py::test_reduce[x-False-sum-False-int-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[std-2-None-True-2]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-3-3-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-1-None-True-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-1-1-True-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_align_without_indexes_errors",
"xarray/tests/test_dataarray.py::test_rolling_wrapped_bottleneck[1-1-None-min]",
"xarray/tests/test_dataarray.py::test_rolling_reduce_nonnumeric[max-2-1-False]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[max-2-1-False-2]",
"xarray/tests/test_dataset.py::test_coarsen[1-pad-right-False]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-1-True-mean]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-1-None-sum]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-2-3-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[max-2-None-False-2]",
"xarray/tests/test_dataset.py::test_rolling_reduce[median-4-3-True-1]",
"xarray/tests/test_dataset.py::test_rolling_wrapped_bottleneck[1-z2-None-True-std]",
"xarray/tests/test_duck_array_ops.py::test_reduce[x-False-var-False-bool_-1]",
"xarray/tests/test_dataarray.py::test_rolling_reduce[sum-3-None-True-1]",
"xarray/tests/test_dataset.py::test_rolling_reduce[min-1-None-True-1]"
] |
[
"xarray/tests/test_dataarray.py::TestDataArray::test_sel_dataarray",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-False-str-1]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-False-int-1]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-False-False-float32-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-False-float32-1]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-True-bool_-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-False-False-str-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-False-True-bool_-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-min-False-False-bool_-2]",
"xarray/tests/test_dataset.py::TestDataset::test_expand_dims_mixed_int_and_coords",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-False-False-float-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-False-False-float-1]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-False-bool_-1]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-False-bool_-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_to_pandas",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-max-False-False-float32-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_to_and_from_dict",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-False-False-int-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-False-int-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-False-float-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-True-str-1]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-max-False-False-bool_-2]",
"xarray/tests/test_dataset.py::TestDataset::test_isel_dataarray",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-False-bool_-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-False-False-float32-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-False-True-str-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-False-False-float32-2]",
"xarray/tests/test_dataset.py::TestDataset::test_constructor_compat",
"xarray/tests/test_dataset.py::TestDataset::test_dataset_math_auto_align",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-True-str-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-min-False-False-float-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-False-False-bool_-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-False-False-float-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-False-False-int-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-False-float32-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-False-True-str-2]",
"xarray/tests/test_dataset.py::TestDataset::test_isel_fancy",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-False-False-str-1]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-True-bool_-1]",
"xarray/tests/test_dataset.py::TestDataset::test_drop_index_labels",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-min-False-False-float32-2]",
"xarray/tests/test_dataarray.py::TestDataArray::test_drop_coordinates",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-False-False-str-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-False-False-str-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-min-False-False-str-2]",
"xarray/tests/test_dataset.py::TestDataset::test_coords_set",
"xarray/tests/test_dataset.py::TestDataset::test_sel_dataarray",
"xarray/tests/test_dataarray.py::TestDataArray::test_drop_index_labels",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-True-bool_-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-False-False-float-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-min-False-False-int-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-max-False-False-int-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-False-False-int-1]",
"xarray/tests/test_dataset.py::TestDataset::test_info",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-False-False-int-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-False-bool_-1]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-False-str-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-False-True-bool_-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-False-float32-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-False-False-bool_-1]",
"xarray/tests/test_dataset.py::TestDataset::test_drop_variables",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-True-str-1]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-False-float-1]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-False-False-float32-1]",
"xarray/tests/test_dataset.py::TestDataset::test_setitem_with_coords",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-False-float-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_expand_dims_with_greater_dim_size",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-True-str-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-False-int-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-False-False-bool_-2]",
"xarray/tests/test_dataset.py::TestDataset::test_drop_labels_by_keyword",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-False-False-str-1]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-False-False-float-1]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-False-False-str-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-False-int-1]",
"xarray/tests/test_dataset.py::TestDataset::test_sel_fancy",
"xarray/tests/test_dataarray.py::TestDataArray::test_to_and_from_series",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-False-False-bool_-2]",
"xarray/tests/test_dataset.py::TestDataset::test_apply",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-False-False-float32-1]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-False-False-bool_-1]",
"xarray/tests/test_dataset.py::TestDataset::test_drop_dims",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-False-float-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-False-False-float32-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-False-False-float-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-False-False-int-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-False-float32-1]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-max-False-False-str-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-False-False-bool_-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-False-str-1]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-True-bool_-1]",
"xarray/tests/test_dataarray.py::TestDataArray::test_stack_unstack",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-max-False-False-float-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-False-str-2]",
"xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-False-False-int-1]"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": [
{
"type": "field",
"name": "PendingDeprecationWarning"
}
]
}
|
[
{
"path": "doc/data-structures.rst",
"old_path": "a/doc/data-structures.rst",
"new_path": "b/doc/data-structures.rst",
"metadata": "diff --git a/doc/data-structures.rst b/doc/data-structures.rst\nindex d5567f4863e..93cdc7e9765 100644\n--- a/doc/data-structures.rst\n+++ b/doc/data-structures.rst\n@@ -393,14 +393,14 @@ methods (like pandas) for transforming datasets into new objects.\n \n For removing variables, you can select and drop an explicit list of\n variables by indexing with a list of names or using the\n-:py:meth:`~xarray.Dataset.drop` methods to return a new ``Dataset``. These\n+:py:meth:`~xarray.Dataset.drop_vars` methods to return a new ``Dataset``. These\n operations keep around coordinates:\n \n .. ipython:: python\n \n ds[['temperature']]\n ds[['temperature', 'temperature_double']]\n- ds.drop('temperature')\n+ ds.drop_vars('temperature')\n \n To remove a dimension, you can use :py:meth:`~xarray.Dataset.drop_dims` method.\n Any variables using that dimension are dropped:\n"
},
{
"path": "doc/indexing.rst",
"old_path": "a/doc/indexing.rst",
"new_path": "b/doc/indexing.rst",
"metadata": "diff --git a/doc/indexing.rst b/doc/indexing.rst\nindex 9ee8f1dddf8..ace960689a8 100644\n--- a/doc/indexing.rst\n+++ b/doc/indexing.rst\n@@ -232,14 +232,14 @@ Using indexing to *assign* values to a subset of dataset (e.g.,\n Dropping labels and dimensions\n ------------------------------\n \n-The :py:meth:`~xarray.Dataset.drop` method returns a new object with the listed\n+The :py:meth:`~xarray.Dataset.drop_sel` method returns a new object with the listed\n index labels along a dimension dropped:\n \n .. ipython:: python\n \n- ds.drop(space=['IN', 'IL'])\n+ ds.drop_sel(space=['IN', 'IL'])\n \n-``drop`` is both a ``Dataset`` and ``DataArray`` method.\n+``drop_sel`` is both a ``Dataset`` and ``DataArray`` method.\n \n Use :py:meth:`~xarray.Dataset.drop_dims` to drop a full dimension from a Dataset.\n Any variables with these dimensions are also dropped:\n"
},
{
"path": "doc/whats-new.rst",
"old_path": "a/doc/whats-new.rst",
"new_path": "b/doc/whats-new.rst",
"metadata": "diff --git a/doc/whats-new.rst b/doc/whats-new.rst\nindex dcaab011e67..0906058469d 100644\n--- a/doc/whats-new.rst\n+++ b/doc/whats-new.rst\n@@ -38,6 +38,12 @@ Breaking changes\n \n New Features\n ~~~~~~~~~~~~\n+- :py:meth:`Dataset.drop_sel` & :py:meth:`DataArray.drop_sel` have been added for dropping labels.\n+ :py:meth:`Dataset.drop_vars` & :py:meth:`DataArray.drop_vars` have been added for \n+ dropping variables (including coordinates). The existing ``drop`` methods remain as a backward compatible \n+ option for dropping either lables or variables, but using the more specific methods is encouraged.\n+ (:pull:`<PRID>`)\n+ By `<NAME>`_\n - :py:meth:`Dataset.transpose` and :py:meth:`DataArray.transpose` now support an ellipsis (`...`)\n to represent all 'other' dimensions. For example, to move one dimension to the front,\n use `.transpose('x', ...)`. (:pull:`<PRID>`)\n@@ -3752,6 +3758,7 @@ Enhancements\n explicitly listed variables or index labels:\n \n .. ipython:: python\n+ :okwarning:\n \n # drop variables\n ds = xray.Dataset({'x': 0, 'y': 1})\n"
}
] |
diff --git a/doc/data-structures.rst b/doc/data-structures.rst
index d5567f4863e..93cdc7e9765 100644
--- a/doc/data-structures.rst
+++ b/doc/data-structures.rst
@@ -393,14 +393,14 @@ methods (like pandas) for transforming datasets into new objects.
For removing variables, you can select and drop an explicit list of
variables by indexing with a list of names or using the
-:py:meth:`~xarray.Dataset.drop` methods to return a new ``Dataset``. These
+:py:meth:`~xarray.Dataset.drop_vars` methods to return a new ``Dataset``. These
operations keep around coordinates:
.. ipython:: python
ds[['temperature']]
ds[['temperature', 'temperature_double']]
- ds.drop('temperature')
+ ds.drop_vars('temperature')
To remove a dimension, you can use :py:meth:`~xarray.Dataset.drop_dims` method.
Any variables using that dimension are dropped:
diff --git a/doc/indexing.rst b/doc/indexing.rst
index 9ee8f1dddf8..ace960689a8 100644
--- a/doc/indexing.rst
+++ b/doc/indexing.rst
@@ -232,14 +232,14 @@ Using indexing to *assign* values to a subset of dataset (e.g.,
Dropping labels and dimensions
------------------------------
-The :py:meth:`~xarray.Dataset.drop` method returns a new object with the listed
+The :py:meth:`~xarray.Dataset.drop_sel` method returns a new object with the listed
index labels along a dimension dropped:
.. ipython:: python
- ds.drop(space=['IN', 'IL'])
+ ds.drop_sel(space=['IN', 'IL'])
-``drop`` is both a ``Dataset`` and ``DataArray`` method.
+``drop_sel`` is both a ``Dataset`` and ``DataArray`` method.
Use :py:meth:`~xarray.Dataset.drop_dims` to drop a full dimension from a Dataset.
Any variables with these dimensions are also dropped:
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index dcaab011e67..0906058469d 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -38,6 +38,12 @@ Breaking changes
New Features
~~~~~~~~~~~~
+- :py:meth:`Dataset.drop_sel` & :py:meth:`DataArray.drop_sel` have been added for dropping labels.
+ :py:meth:`Dataset.drop_vars` & :py:meth:`DataArray.drop_vars` have been added for
+ dropping variables (including coordinates). The existing ``drop`` methods remain as a backward compatible
+ option for dropping either lables or variables, but using the more specific methods is encouraged.
+ (:pull:`<PRID>`)
+ By `<NAME>`_
- :py:meth:`Dataset.transpose` and :py:meth:`DataArray.transpose` now support an ellipsis (`...`)
to represent all 'other' dimensions. For example, to move one dimension to the front,
use `.transpose('x', ...)`. (:pull:`<PRID>`)
@@ -3752,6 +3758,7 @@ Enhancements
explicitly listed variables or index labels:
.. ipython:: python
+ :okwarning:
# drop variables
ds = xray.Dataset({'x': 0, 'y': 1})
If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:
[{'type': 'field', 'name': 'PendingDeprecationWarning'}]
|
pydata/xarray
|
pydata__xarray-3276
|
https://github.com/pydata/xarray/pull/3276
|
diff --git a/doc/api.rst b/doc/api.rst
index 256a1dbf3af..40f9add3c57 100644
--- a/doc/api.rst
+++ b/doc/api.rst
@@ -30,6 +30,7 @@ Top-level functions
zeros_like
ones_like
dot
+ map_blocks
Dataset
=======
@@ -499,6 +500,8 @@ Dataset methods
Dataset.persist
Dataset.load
Dataset.chunk
+ Dataset.unify_chunks
+ Dataset.map_blocks
Dataset.filter_by_attrs
Dataset.info
@@ -529,6 +532,8 @@ DataArray methods
DataArray.persist
DataArray.load
DataArray.chunk
+ DataArray.unify_chunks
+ DataArray.map_blocks
GroupBy objects
===============
@@ -629,6 +634,7 @@ Testing
testing.assert_equal
testing.assert_identical
testing.assert_allclose
+ testing.assert_chunks_equal
Exceptions
==========
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index 520f1f79870..b6e12f01f4b 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -49,6 +49,11 @@ Breaking changes
New functions/methods
~~~~~~~~~~~~~~~~~~~~~
+- Added :py:func:`~xarray.map_blocks`, modeled after :py:func:`dask.array.map_blocks`.
+ Also added :py:meth:`Dataset.unify_chunks`, :py:meth:`DataArray.unify_chunks` and
+ :py:meth:`testing.assert_chunks_equal`. By `Deepak Cherian <https://github.com/dcherian>`_
+ and `Guido Imperiale <https://github.com/crusaderky>`_.
+
Enhancements
~~~~~~~~~~~~
diff --git a/xarray/__init__.py b/xarray/__init__.py
index cdca708e28c..394dd0f80bc 100644
--- a/xarray/__init__.py
+++ b/xarray/__init__.py
@@ -17,6 +17,7 @@
from .core.dataarray import DataArray
from .core.merge import merge, MergeError
from .core.options import set_options
+from .core.parallel import map_blocks
from .backends.api import (
open_dataset,
diff --git a/xarray/coding/times.py b/xarray/coding/times.py
index 1508fb50b38..ed6908117a2 100644
--- a/xarray/coding/times.py
+++ b/xarray/coding/times.py
@@ -22,7 +22,6 @@
unpack_for_encoding,
)
-
# standard calendars recognized by cftime
_STANDARD_CALENDARS = {"standard", "gregorian", "proleptic_gregorian"}
diff --git a/xarray/core/dask_array_compat.py b/xarray/core/dask_array_compat.py
new file mode 100644
index 00000000000..c3dbdd27098
--- /dev/null
+++ b/xarray/core/dask_array_compat.py
@@ -0,0 +1,91 @@
+from distutils.version import LooseVersion
+
+import dask.array as da
+import numpy as np
+from dask import __version__ as dask_version
+
+if LooseVersion(dask_version) >= LooseVersion("2.0.0"):
+ meta_from_array = da.utils.meta_from_array
+else:
+ # Copied from dask v2.4.0
+ # Used under the terms of Dask's license, see licenses/DASK_LICENSE.
+ import numbers
+
+ def meta_from_array(x, ndim=None, dtype=None):
+ """ Normalize an array to appropriate meta object
+
+ Parameters
+ ----------
+ x: array-like, callable
+ Either an object that looks sufficiently like a Numpy array,
+ or a callable that accepts shape and dtype keywords
+ ndim: int
+ Number of dimensions of the array
+ dtype: Numpy dtype
+ A valid input for ``np.dtype``
+
+ Returns
+ -------
+ array-like with zero elements of the correct dtype
+ """
+ # If using x._meta, x must be a Dask Array, some libraries (e.g. zarr)
+ # implement a _meta attribute that are incompatible with Dask Array._meta
+ if hasattr(x, "_meta") and isinstance(x, da.Array):
+ x = x._meta
+
+ if dtype is None and x is None:
+ raise ValueError("You must specify the meta or dtype of the array")
+
+ if np.isscalar(x):
+ x = np.array(x)
+
+ if x is None:
+ x = np.ndarray
+
+ if isinstance(x, type):
+ x = x(shape=(0,) * (ndim or 0), dtype=dtype)
+
+ if (
+ not hasattr(x, "shape")
+ or not hasattr(x, "dtype")
+ or not isinstance(x.shape, tuple)
+ ):
+ return x
+
+ if isinstance(x, list) or isinstance(x, tuple):
+ ndims = [
+ 0
+ if isinstance(a, numbers.Number)
+ else a.ndim
+ if hasattr(a, "ndim")
+ else len(a)
+ for a in x
+ ]
+ a = [a if nd == 0 else meta_from_array(a, nd) for a, nd in zip(x, ndims)]
+ return a if isinstance(x, list) else tuple(x)
+
+ if ndim is None:
+ ndim = x.ndim
+
+ try:
+ meta = x[tuple(slice(0, 0, None) for _ in range(x.ndim))]
+ if meta.ndim != ndim:
+ if ndim > x.ndim:
+ meta = meta[
+ (Ellipsis,) + tuple(None for _ in range(ndim - meta.ndim))
+ ]
+ meta = meta[tuple(slice(0, 0, None) for _ in range(meta.ndim))]
+ elif ndim == 0:
+ meta = meta.sum()
+ else:
+ meta = meta.reshape((0,) * ndim)
+ except Exception:
+ meta = np.empty((0,) * ndim, dtype=dtype or x.dtype)
+
+ if np.isscalar(meta):
+ meta = np.array(meta)
+
+ if dtype and meta.dtype != dtype:
+ meta = meta.astype(dtype)
+
+ return meta
diff --git a/xarray/core/dataarray.py b/xarray/core/dataarray.py
index d536d0de2c5..1b1d23bc2fc 100644
--- a/xarray/core/dataarray.py
+++ b/xarray/core/dataarray.py
@@ -14,6 +14,7 @@
Optional,
Sequence,
Tuple,
+ TypeVar,
Union,
cast,
overload,
@@ -63,6 +64,8 @@
)
if TYPE_CHECKING:
+ T_DSorDA = TypeVar("T_DSorDA", "DataArray", Dataset)
+
try:
from dask.delayed import Delayed
except ImportError:
@@ -3038,6 +3041,79 @@ def integrate(
ds = self._to_temp_dataset().integrate(dim, datetime_unit)
return self._from_temp_dataset(ds)
+ def unify_chunks(self) -> "DataArray":
+ """ Unify chunk size along all chunked dimensions of this DataArray.
+
+ Returns
+ -------
+
+ DataArray with consistent chunk sizes for all dask-array variables
+
+ See Also
+ --------
+
+ dask.array.core.unify_chunks
+ """
+ ds = self._to_temp_dataset().unify_chunks()
+ return self._from_temp_dataset(ds)
+
+ def map_blocks(
+ self,
+ func: "Callable[..., T_DSorDA]",
+ args: Sequence[Any] = (),
+ kwargs: Mapping[str, Any] = None,
+ ) -> "T_DSorDA":
+ """
+ Apply a function to each chunk of this DataArray. This method is experimental
+ and its signature may change.
+
+ Parameters
+ ----------
+ func: callable
+ User-provided function that accepts a DataArray as its first parameter. The
+ function will receive a subset of this DataArray, corresponding to one chunk
+ along each chunked dimension. ``func`` will be executed as
+ ``func(obj_subset, *args, **kwargs)``.
+
+ The function will be first run on mocked-up data, that looks like this array
+ but has sizes 0, to determine properties of the returned object such as
+ dtype, variable names, new dimensions and new indexes (if any).
+
+ This function must return either a single DataArray or a single Dataset.
+
+ This function cannot change size of existing dimensions, or add new chunked
+ dimensions.
+ args: Sequence
+ Passed verbatim to func after unpacking, after the sliced DataArray. xarray
+ objects, if any, will not be split by chunks. Passing dask collections is
+ not allowed.
+ kwargs: Mapping
+ Passed verbatim to func after unpacking. xarray objects, if any, will not be
+ split by chunks. Passing dask collections is not allowed.
+
+ Returns
+ -------
+ A single DataArray or Dataset with dask backend, reassembled from the outputs of
+ the function.
+
+ Notes
+ -----
+ This method is designed for when one needs to manipulate a whole xarray object
+ within each chunk. In the more common case where one can work on numpy arrays,
+ it is recommended to use apply_ufunc.
+
+ If none of the variables in this DataArray is backed by dask, calling this
+ method is equivalent to calling ``func(self, *args, **kwargs)``.
+
+ See Also
+ --------
+ dask.array.map_blocks, xarray.apply_ufunc, xarray.map_blocks,
+ xarray.Dataset.map_blocks
+ """
+ from .parallel import map_blocks
+
+ return map_blocks(func, self, args, kwargs)
+
# this needs to be at the end, or mypy will confuse with `str`
# https://mypy.readthedocs.io/en/latest/common_issues.html#dealing-with-conflicting-names
str = property(StringAccessor)
diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index 7b4c7b441bd..42990df6f65 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -21,6 +21,7 @@
Sequence,
Set,
Tuple,
+ TypeVar,
Union,
cast,
overload,
@@ -85,6 +86,8 @@
from .dataarray import DataArray
from .merge import CoercibleMapping
+ T_DSorDA = TypeVar("T_DSorDA", DataArray, "Dataset")
+
try:
from dask.delayed import Delayed
except ImportError:
@@ -1670,7 +1673,10 @@ def chunks(self) -> Mapping[Hashable, Tuple[int, ...]]:
if v.chunks is not None:
for dim, c in zip(v.dims, v.chunks):
if dim in chunks and c != chunks[dim]:
- raise ValueError("inconsistent chunks")
+ raise ValueError(
+ f"Object has inconsistent chunks along dimension {dim}. "
+ "This can be fixed by calling unify_chunks()."
+ )
chunks[dim] = c
return Frozen(SortedKeysDict(chunks))
@@ -1855,7 +1861,7 @@ def isel(
self,
indexers: Mapping[Hashable, Any] = None,
drop: bool = False,
- **indexers_kwargs: Any
+ **indexers_kwargs: Any,
) -> "Dataset":
"""Returns a new dataset with each array indexed along the specified
dimension(s).
@@ -1938,7 +1944,7 @@ def sel(
method: str = None,
tolerance: Number = None,
drop: bool = False,
- **indexers_kwargs: Any
+ **indexers_kwargs: Any,
) -> "Dataset":
"""Returns a new dataset with each array indexed by tick labels
along the specified dimension(s).
@@ -2011,7 +2017,7 @@ def sel(
def head(
self,
indexers: Union[Mapping[Hashable, int], int] = None,
- **indexers_kwargs: Any
+ **indexers_kwargs: Any,
) -> "Dataset":
"""Returns a new dataset with the first `n` values of each array
for the specified dimension(s).
@@ -2058,7 +2064,7 @@ def head(
def tail(
self,
indexers: Union[Mapping[Hashable, int], int] = None,
- **indexers_kwargs: Any
+ **indexers_kwargs: Any,
) -> "Dataset":
"""Returns a new dataset with the last `n` values of each array
for the specified dimension(s).
@@ -2108,7 +2114,7 @@ def tail(
def thin(
self,
indexers: Union[Mapping[Hashable, int], int] = None,
- **indexers_kwargs: Any
+ **indexers_kwargs: Any,
) -> "Dataset":
"""Returns a new dataset with each array indexed along every `n`th
value for the specified dimension(s)
@@ -2246,7 +2252,7 @@ def reindex(
tolerance: Number = None,
copy: bool = True,
fill_value: Any = dtypes.NA,
- **indexers_kwargs: Any
+ **indexers_kwargs: Any,
) -> "Dataset":
"""Conform this object onto a new set of indexes, filling in
missing values with ``fill_value``. The default fill value is NaN.
@@ -2447,7 +2453,7 @@ def interp(
method: str = "linear",
assume_sorted: bool = False,
kwargs: Mapping[str, Any] = None,
- **coords_kwargs: Any
+ **coords_kwargs: Any,
) -> "Dataset":
""" Multidimensional interpolation of Dataset.
@@ -2673,7 +2679,7 @@ def rename(
self,
name_dict: Mapping[Hashable, Hashable] = None,
inplace: bool = None,
- **names: Hashable
+ **names: Hashable,
) -> "Dataset":
"""Returns a new object with renamed variables and dimensions.
@@ -2876,7 +2882,7 @@ def expand_dims(
self,
dim: Union[None, Hashable, Sequence[Hashable], Mapping[Hashable, Any]] = None,
axis: Union[None, int, Sequence[int]] = None,
- **dim_kwargs: Any
+ **dim_kwargs: Any,
) -> "Dataset":
"""Return a new object with an additional axis (or axes) inserted at
the corresponding position in the array shape. The new object is a
@@ -3022,7 +3028,7 @@ def set_index(
indexes: Mapping[Hashable, Union[Hashable, Sequence[Hashable]]] = None,
append: bool = False,
inplace: bool = None,
- **indexes_kwargs: Union[Hashable, Sequence[Hashable]]
+ **indexes_kwargs: Union[Hashable, Sequence[Hashable]],
) -> "Dataset":
"""Set Dataset (multi-)indexes using one or more existing coordinates
or variables.
@@ -3124,7 +3130,7 @@ def reorder_levels(
self,
dim_order: Mapping[Hashable, Sequence[int]] = None,
inplace: bool = None,
- **dim_order_kwargs: Sequence[int]
+ **dim_order_kwargs: Sequence[int],
) -> "Dataset":
"""Rearrange index levels using input order.
@@ -3190,7 +3196,7 @@ def _stack_once(self, dims, new_dim):
def stack(
self,
dimensions: Mapping[Hashable, Sequence[Hashable]] = None,
- **dimensions_kwargs: Sequence[Hashable]
+ **dimensions_kwargs: Sequence[Hashable],
) -> "Dataset":
"""
Stack any number of existing dimensions into a single new dimension.
@@ -3891,7 +3897,7 @@ def interpolate_na(
method: str = "linear",
limit: int = None,
use_coordinate: Union[bool, Hashable] = True,
- **kwargs: Any
+ **kwargs: Any,
) -> "Dataset":
"""Interpolate values according to different methods.
@@ -3942,7 +3948,7 @@ def interpolate_na(
method=method,
limit=limit,
use_coordinate=use_coordinate,
- **kwargs
+ **kwargs,
)
return new
@@ -4023,7 +4029,7 @@ def reduce(
keepdims: bool = False,
numeric_only: bool = False,
allow_lazy: bool = False,
- **kwargs: Any
+ **kwargs: Any,
) -> "Dataset":
"""Reduce this dataset by applying `func` along some dimension(s).
@@ -4098,7 +4104,7 @@ def reduce(
keep_attrs=keep_attrs,
keepdims=keepdims,
allow_lazy=allow_lazy,
- **kwargs
+ **kwargs,
)
coord_names = {k for k in self.coords if k in variables}
@@ -4113,7 +4119,7 @@ def apply(
func: Callable,
keep_attrs: bool = None,
args: Iterable[Any] = (),
- **kwargs: Any
+ **kwargs: Any,
) -> "Dataset":
"""Apply a function over the data variables in this dataset.
@@ -5366,5 +5372,108 @@ def filter_by_attrs(self, **kwargs):
selection.append(var_name)
return self[selection]
+ def unify_chunks(self) -> "Dataset":
+ """ Unify chunk size along all chunked dimensions of this Dataset.
+
+ Returns
+ -------
+
+ Dataset with consistent chunk sizes for all dask-array variables
+
+ See Also
+ --------
+
+ dask.array.core.unify_chunks
+ """
+
+ try:
+ self.chunks
+ except ValueError: # "inconsistent chunks"
+ pass
+ else:
+ # No variables with dask backend, or all chunks are already aligned
+ return self.copy()
+
+ # import dask is placed after the quick exit test above to allow
+ # running this method if dask isn't installed and there are no chunks
+ import dask.array
+
+ ds = self.copy()
+
+ dims_pos_map = {dim: index for index, dim in enumerate(ds.dims)}
+
+ dask_array_names = []
+ dask_unify_args = []
+ for name, variable in ds.variables.items():
+ if isinstance(variable.data, dask.array.Array):
+ dims_tuple = [dims_pos_map[dim] for dim in variable.dims]
+ dask_array_names.append(name)
+ dask_unify_args.append(variable.data)
+ dask_unify_args.append(dims_tuple)
+
+ _, rechunked_arrays = dask.array.core.unify_chunks(*dask_unify_args)
+
+ for name, new_array in zip(dask_array_names, rechunked_arrays):
+ ds.variables[name]._data = new_array
+
+ return ds
+
+ def map_blocks(
+ self,
+ func: "Callable[..., T_DSorDA]",
+ args: Sequence[Any] = (),
+ kwargs: Mapping[str, Any] = None,
+ ) -> "T_DSorDA":
+ """
+ Apply a function to each chunk of this Dataset. This method is experimental and
+ its signature may change.
+
+ Parameters
+ ----------
+ func: callable
+ User-provided function that accepts a Dataset as its first parameter. The
+ function will receive a subset of this Dataset, corresponding to one chunk
+ along each chunked dimension. ``func`` will be executed as
+ ``func(obj_subset, *args, **kwargs)``.
+
+ The function will be first run on mocked-up data, that looks like this
+ Dataset but has sizes 0, to determine properties of the returned object such
+ as dtype, variable names, new dimensions and new indexes (if any).
+
+ This function must return either a single DataArray or a single Dataset.
+
+ This function cannot change size of existing dimensions, or add new chunked
+ dimensions.
+ args: Sequence
+ Passed verbatim to func after unpacking, after the sliced DataArray. xarray
+ objects, if any, will not be split by chunks. Passing dask collections is
+ not allowed.
+ kwargs: Mapping
+ Passed verbatim to func after unpacking. xarray objects, if any, will not be
+ split by chunks. Passing dask collections is not allowed.
+
+ Returns
+ -------
+ A single DataArray or Dataset with dask backend, reassembled from the outputs of
+ the function.
+
+ Notes
+ -----
+ This method is designed for when one needs to manipulate a whole xarray object
+ within each chunk. In the more common case where one can work on numpy arrays,
+ it is recommended to use apply_ufunc.
+
+ If none of the variables in this Dataset is backed by dask, calling this method
+ is equivalent to calling ``func(self, *args, **kwargs)``.
+
+ See Also
+ --------
+ dask.array.map_blocks, xarray.apply_ufunc, xarray.map_blocks,
+ xarray.DataArray.map_blocks
+ """
+ from .parallel import map_blocks
+
+ return map_blocks(func, self, args, kwargs)
+
ops.inject_all_ops_and_reduce_methods(Dataset, array_only=False)
diff --git a/xarray/core/parallel.py b/xarray/core/parallel.py
new file mode 100644
index 00000000000..48bb9ccfc3d
--- /dev/null
+++ b/xarray/core/parallel.py
@@ -0,0 +1,339 @@
+try:
+ import dask
+ import dask.array
+ from dask.highlevelgraph import HighLevelGraph
+ from .dask_array_compat import meta_from_array
+
+except ImportError:
+ pass
+
+import itertools
+import operator
+from typing import (
+ Any,
+ Callable,
+ Dict,
+ Hashable,
+ Mapping,
+ Sequence,
+ Tuple,
+ TypeVar,
+ Union,
+)
+
+import numpy as np
+
+from .dataarray import DataArray
+from .dataset import Dataset
+
+T_DSorDA = TypeVar("T_DSorDA", DataArray, Dataset)
+
+
+def dataset_to_dataarray(obj: Dataset) -> DataArray:
+ if not isinstance(obj, Dataset):
+ raise TypeError("Expected Dataset, got %s" % type(obj))
+
+ if len(obj.data_vars) > 1:
+ raise TypeError(
+ "Trying to convert Dataset with more than one data variable to DataArray"
+ )
+
+ return next(iter(obj.data_vars.values()))
+
+
+def make_meta(obj):
+ """If obj is a DataArray or Dataset, return a new object of the same type and with
+ the same variables and dtypes, but where all variables have size 0 and numpy
+ backend.
+ If obj is neither a DataArray nor Dataset, return it unaltered.
+ """
+ if isinstance(obj, DataArray):
+ obj_array = obj
+ obj = obj._to_temp_dataset()
+ elif isinstance(obj, Dataset):
+ obj_array = None
+ else:
+ return obj
+
+ meta = Dataset()
+ for name, variable in obj.variables.items():
+ meta_obj = meta_from_array(variable.data, ndim=variable.ndim)
+ meta[name] = (variable.dims, meta_obj, variable.attrs)
+ meta.attrs = obj.attrs
+ meta = meta.set_coords(obj.coords)
+
+ if obj_array is not None:
+ return obj_array._from_temp_dataset(meta)
+ return meta
+
+
+def infer_template(
+ func: Callable[..., T_DSorDA], obj: Union[DataArray, Dataset], *args, **kwargs
+) -> T_DSorDA:
+ """Infer return object by running the function on meta objects.
+ """
+ meta_args = [make_meta(arg) for arg in (obj,) + args]
+
+ try:
+ template = func(*meta_args, **kwargs)
+ except Exception as e:
+ raise Exception(
+ "Cannot infer object returned from running user provided function."
+ ) from e
+
+ if not isinstance(template, (Dataset, DataArray)):
+ raise TypeError(
+ "Function must return an xarray DataArray or Dataset. Instead it returned "
+ f"{type(template)}"
+ )
+
+ return template
+
+
+def make_dict(x: Union[DataArray, Dataset]) -> Dict[Hashable, Any]:
+ """Map variable name to numpy(-like) data
+ (Dataset.to_dict() is too complicated).
+ """
+ if isinstance(x, DataArray):
+ x = x._to_temp_dataset()
+
+ return {k: v.data for k, v in x.variables.items()}
+
+
+def map_blocks(
+ func: Callable[..., T_DSorDA],
+ obj: Union[DataArray, Dataset],
+ args: Sequence[Any] = (),
+ kwargs: Mapping[str, Any] = None,
+) -> T_DSorDA:
+ """Apply a function to each chunk of a DataArray or Dataset. This function is
+ experimental and its signature may change.
+
+ Parameters
+ ----------
+ func: callable
+ User-provided function that accepts a DataArray or Dataset as its first
+ parameter. The function will receive a subset of 'obj' (see below),
+ corresponding to one chunk along each chunked dimension. ``func`` will be
+ executed as ``func(obj_subset, *args, **kwargs)``.
+
+ The function will be first run on mocked-up data, that looks like 'obj' but
+ has sizes 0, to determine properties of the returned object such as dtype,
+ variable names, new dimensions and new indexes (if any).
+
+ This function must return either a single DataArray or a single Dataset.
+
+ This function cannot change size of existing dimensions, or add new chunked
+ dimensions.
+ obj: DataArray, Dataset
+ Passed to the function as its first argument, one dask chunk at a time.
+ args: Sequence
+ Passed verbatim to func after unpacking, after the sliced obj. xarray objects,
+ if any, will not be split by chunks. Passing dask collections is not allowed.
+ kwargs: Mapping
+ Passed verbatim to func after unpacking. xarray objects, if any, will not be
+ split by chunks. Passing dask collections is not allowed.
+
+ Returns
+ -------
+ A single DataArray or Dataset with dask backend, reassembled from the outputs of the
+ function.
+
+ Notes
+ -----
+ This function is designed for when one needs to manipulate a whole xarray object
+ within each chunk. In the more common case where one can work on numpy arrays, it is
+ recommended to use apply_ufunc.
+
+ If none of the variables in obj is backed by dask, calling this function is
+ equivalent to calling ``func(obj, *args, **kwargs)``.
+
+ See Also
+ --------
+ dask.array.map_blocks, xarray.apply_ufunc, xarray.Dataset.map_blocks,
+ xarray.DataArray.map_blocks
+ """
+
+ def _wrapper(func, obj, to_array, args, kwargs):
+ if to_array:
+ obj = dataset_to_dataarray(obj)
+
+ result = func(obj, *args, **kwargs)
+
+ for name, index in result.indexes.items():
+ if name in obj.indexes:
+ if len(index) != len(obj.indexes[name]):
+ raise ValueError(
+ "Length of the %r dimension has changed. This is not allowed."
+ % name
+ )
+
+ return make_dict(result)
+
+ if not isinstance(args, Sequence):
+ raise TypeError("args must be a sequence (for example, a list or tuple).")
+ if kwargs is None:
+ kwargs = {}
+ elif not isinstance(kwargs, Mapping):
+ raise TypeError("kwargs must be a mapping (for example, a dict)")
+
+ for value in list(args) + list(kwargs.values()):
+ if dask.is_dask_collection(value):
+ raise TypeError(
+ "Cannot pass dask collections in args or kwargs yet. Please compute or "
+ "load values before passing to map_blocks."
+ )
+
+ if not dask.is_dask_collection(obj):
+ return func(obj, *args, **kwargs)
+
+ if isinstance(obj, DataArray):
+ # only using _to_temp_dataset would break
+ # func = lambda x: x.to_dataset()
+ # since that relies on preserving name.
+ if obj.name is None:
+ dataset = obj._to_temp_dataset()
+ else:
+ dataset = obj.to_dataset()
+ input_is_array = True
+ else:
+ dataset = obj
+ input_is_array = False
+
+ input_chunks = dataset.chunks
+
+ template: Union[DataArray, Dataset] = infer_template(func, obj, *args, **kwargs)
+ if isinstance(template, DataArray):
+ result_is_array = True
+ template_name = template.name
+ template = template._to_temp_dataset()
+ elif isinstance(template, Dataset):
+ result_is_array = False
+ else:
+ raise TypeError(
+ f"func output must be DataArray or Dataset; got {type(template)}"
+ )
+
+ template_indexes = set(template.indexes)
+ dataset_indexes = set(dataset.indexes)
+ preserved_indexes = template_indexes & dataset_indexes
+ new_indexes = template_indexes - dataset_indexes
+ indexes = {dim: dataset.indexes[dim] for dim in preserved_indexes}
+ indexes.update({k: template.indexes[k] for k in new_indexes})
+
+ graph: Dict[Any, Any] = {}
+ gname = "%s-%s" % (
+ dask.utils.funcname(func),
+ dask.base.tokenize(dataset, args, kwargs),
+ )
+
+ # map dims to list of chunk indexes
+ ichunk = {dim: range(len(chunks_v)) for dim, chunks_v in input_chunks.items()}
+ # mapping from chunk index to slice bounds
+ chunk_index_bounds = {
+ dim: np.cumsum((0,) + chunks_v) for dim, chunks_v in input_chunks.items()
+ }
+
+ # iterate over all possible chunk combinations
+ for v in itertools.product(*ichunk.values()):
+ chunk_index_dict = dict(zip(dataset.dims, v))
+
+ # this will become [[name1, variable1],
+ # [name2, variable2],
+ # ...]
+ # which is passed to dict and then to Dataset
+ data_vars = []
+ coords = []
+
+ for name, variable in dataset.variables.items():
+ # make a task that creates tuple of (dims, chunk)
+ if dask.is_dask_collection(variable.data):
+ # recursively index into dask_keys nested list to get chunk
+ chunk = variable.__dask_keys__()
+ for dim in variable.dims:
+ chunk = chunk[chunk_index_dict[dim]]
+
+ chunk_variable_task = ("%s-%s" % (gname, chunk[0]),) + v
+ graph[chunk_variable_task] = (
+ tuple,
+ [variable.dims, chunk, variable.attrs],
+ )
+ else:
+ # non-dask array with possibly chunked dimensions
+ # index into variable appropriately
+ subsetter = {}
+ for dim in variable.dims:
+ if dim in chunk_index_dict:
+ which_chunk = chunk_index_dict[dim]
+ subsetter[dim] = slice(
+ chunk_index_bounds[dim][which_chunk],
+ chunk_index_bounds[dim][which_chunk + 1],
+ )
+
+ subset = variable.isel(subsetter)
+ chunk_variable_task = (
+ "%s-%s" % (gname, dask.base.tokenize(subset)),
+ ) + v
+ graph[chunk_variable_task] = (
+ tuple,
+ [subset.dims, subset, subset.attrs],
+ )
+
+ # this task creates dict mapping variable name to above tuple
+ if name in dataset._coord_names:
+ coords.append([name, chunk_variable_task])
+ else:
+ data_vars.append([name, chunk_variable_task])
+
+ from_wrapper = (gname,) + v
+ graph[from_wrapper] = (
+ _wrapper,
+ func,
+ (Dataset, (dict, data_vars), (dict, coords), dataset.attrs),
+ input_is_array,
+ args,
+ kwargs,
+ )
+
+ # mapping from variable name to dask graph key
+ var_key_map: Dict[Hashable, str] = {}
+ for name, variable in template.variables.items():
+ if name in indexes:
+ continue
+ gname_l = "%s-%s" % (gname, name)
+ var_key_map[name] = gname_l
+
+ key: Tuple[Any, ...] = (gname_l,)
+ for dim in variable.dims:
+ if dim in chunk_index_dict:
+ key += (chunk_index_dict[dim],)
+ else:
+ # unchunked dimensions in the input have one chunk in the result
+ key += (0,)
+
+ graph[key] = (operator.getitem, from_wrapper, name)
+
+ graph = HighLevelGraph.from_collections(gname, graph, dependencies=[dataset])
+
+ result = Dataset(coords=indexes, attrs=template.attrs)
+ for name, gname_l in var_key_map.items():
+ dims = template[name].dims
+ var_chunks = []
+ for dim in dims:
+ if dim in input_chunks:
+ var_chunks.append(input_chunks[dim])
+ elif dim in indexes:
+ var_chunks.append((len(indexes[dim]),))
+
+ data = dask.array.Array(
+ graph, name=gname_l, chunks=var_chunks, dtype=template[name].dtype
+ )
+ result[name] = (dims, data, template[name].attrs)
+
+ result = result.set_coords(template._coord_names)
+
+ if result_is_array:
+ da = dataset_to_dataarray(result)
+ da.name = template_name
+ return da # type: ignore
+ return result # type: ignore
diff --git a/xarray/core/pdcompat.py b/xarray/core/pdcompat.py
index 7591fff3abe..f2e4518e0dc 100644
--- a/xarray/core/pdcompat.py
+++ b/xarray/core/pdcompat.py
@@ -41,7 +41,6 @@
import pandas as pd
-
# allow ourselves to type checks for Panel even after it's removed
if LooseVersion(pd.__version__) < "0.25.0":
Panel = pd.Panel
diff --git a/xarray/core/variable.py b/xarray/core/variable.py
index 6d7a07c6791..24865d62666 100644
--- a/xarray/core/variable.py
+++ b/xarray/core/variable.py
@@ -3,7 +3,7 @@
from collections import OrderedDict, defaultdict
from datetime import timedelta
from distutils.version import LooseVersion
-from typing import Any, Hashable, Mapping, Union, TypeVar
+from typing import Any, Hashable, Mapping, TypeVar, Union
import numpy as np
import pandas as pd
|
diff --git a/xarray/testing.py b/xarray/testing.py
index f01cbe896b9..95e41cfb10c 100644
--- a/xarray/testing.py
+++ b/xarray/testing.py
@@ -142,6 +142,26 @@ def assert_allclose(a, b, rtol=1e-05, atol=1e-08, decode_bytes=True):
raise TypeError("{} not supported by assertion comparison".format(type(a)))
+def assert_chunks_equal(a, b):
+ """
+ Assert that chunksizes along chunked dimensions are equal.
+
+ Parameters
+ ----------
+ a : xarray.Dataset or xarray.DataArray
+ The first object to compare.
+ b : xarray.Dataset or xarray.DataArray
+ The second object to compare.
+ """
+
+ if isinstance(a, DataArray) != isinstance(b, DataArray):
+ raise TypeError("a and b have mismatched types")
+
+ left = a.unify_chunks()
+ right = b.unify_chunks()
+ assert left.chunks == right.chunks
+
+
def _assert_indexes_invariants_checks(indexes, possible_coord_variables, dims):
assert isinstance(indexes, OrderedDict), indexes
assert all(isinstance(v, pd.Index) for v in indexes.values()), {
diff --git a/xarray/tests/__init__.py b/xarray/tests/__init__.py
index 8b4d3073e1c..acf8b67effa 100644
--- a/xarray/tests/__init__.py
+++ b/xarray/tests/__init__.py
@@ -9,6 +9,7 @@
import numpy as np
import pytest
from numpy.testing import assert_array_equal # noqa: F401
+from pandas.testing import assert_frame_equal # noqa: F401
import xarray.testing
from xarray.core import utils
@@ -17,8 +18,6 @@
from xarray.core.options import set_options
from xarray.plot.utils import import_seaborn
-from pandas.testing import assert_frame_equal # noqa: F401
-
# import mpl and change the backend before other mpl imports
try:
import matplotlib as mpl
diff --git a/xarray/tests/test_backends.py b/xarray/tests/test_backends.py
index 0120e2ca0fe..b5421a6bc9f 100644
--- a/xarray/tests/test_backends.py
+++ b/xarray/tests/test_backends.py
@@ -14,8 +14,8 @@
import numpy as np
import pandas as pd
-from pandas.errors import OutOfBoundsDatetime
import pytest
+from pandas.errors import OutOfBoundsDatetime
import xarray as xr
from xarray import (
diff --git a/xarray/tests/test_coding_times.py b/xarray/tests/test_coding_times.py
index 406b9c1ba69..33a409e6f45 100644
--- a/xarray/tests/test_coding_times.py
+++ b/xarray/tests/test_coding_times.py
@@ -6,7 +6,6 @@
import pytest
from pandas.errors import OutOfBoundsDatetime
-
from xarray import DataArray, Dataset, Variable, coding, decode_cf
from xarray.coding.times import (
_import_cftime,
@@ -30,7 +29,6 @@
requires_cftime_or_netCDF4,
)
-
_NON_STANDARD_CALENDARS_SET = {
"noleap",
"365_day",
diff --git a/xarray/tests/test_dask.py b/xarray/tests/test_dask.py
index c142ca7643b..3e2e132825f 100644
--- a/xarray/tests/test_dask.py
+++ b/xarray/tests/test_dask.py
@@ -1,3 +1,4 @@
+import operator
import pickle
from collections import OrderedDict
from contextlib import suppress
@@ -11,6 +12,7 @@
import xarray as xr
import xarray.ufuncs as xu
from xarray import DataArray, Dataset, Variable
+from xarray.testing import assert_chunks_equal
from xarray.tests import mock
from . import (
@@ -894,3 +896,243 @@ def test_dask_layers_and_dependencies():
assert set(x.foo.__dask_graph__().dependencies).issuperset(
ds.__dask_graph__().dependencies
)
+
+
+def make_da():
+ da = xr.DataArray(
+ np.ones((10, 20)),
+ dims=["x", "y"],
+ coords={"x": np.arange(10), "y": np.arange(100, 120)},
+ name="a",
+ ).chunk({"x": 4, "y": 5})
+ da.attrs["test"] = "test"
+ da.coords["c2"] = 0.5
+ da.coords["ndcoord"] = da.x * 2
+ da.coords["cxy"] = (da.x * da.y).chunk({"x": 4, "y": 5})
+
+ return da
+
+
+def make_ds():
+ map_ds = xr.Dataset()
+ map_ds["a"] = make_da()
+ map_ds["b"] = map_ds.a + 50
+ map_ds["c"] = map_ds.x + 20
+ map_ds = map_ds.chunk({"x": 4, "y": 5})
+ map_ds["d"] = ("z", [1, 1, 1, 1])
+ map_ds["z"] = [0, 1, 2, 3]
+ map_ds["e"] = map_ds.x + map_ds.y
+ map_ds.coords["c1"] = 0.5
+ map_ds.coords["cx"] = ("x", np.arange(len(map_ds.x)))
+ map_ds.coords["cx"].attrs["test2"] = "test2"
+ map_ds.attrs["test"] = "test"
+ map_ds.coords["xx"] = map_ds["a"] * map_ds.y
+
+ return map_ds
+
+
+# fixtures cannot be used in parametrize statements
+# instead use this workaround
+# https://docs.pytest.org/en/latest/deprecations.html#calling-fixtures-directly
+@pytest.fixture
+def map_da():
+ return make_da()
+
+
+@pytest.fixture
+def map_ds():
+ return make_ds()
+
+
+def test_unify_chunks(map_ds):
+ ds_copy = map_ds.copy()
+ ds_copy["cxy"] = ds_copy.cxy.chunk({"y": 10})
+
+ with raises_regex(ValueError, "inconsistent chunks"):
+ ds_copy.chunks
+
+ expected_chunks = {"x": (4, 4, 2), "y": (5, 5, 5, 5), "z": (4,)}
+ with raise_if_dask_computes():
+ actual_chunks = ds_copy.unify_chunks().chunks
+ expected_chunks == actual_chunks
+ assert_identical(map_ds, ds_copy.unify_chunks())
+
+
+@pytest.mark.parametrize("obj", [make_ds(), make_da()])
+@pytest.mark.parametrize(
+ "transform", [lambda x: x.compute(), lambda x: x.unify_chunks()]
+)
+def test_unify_chunks_shallow_copy(obj, transform):
+ obj = transform(obj)
+ unified = obj.unify_chunks()
+ assert_identical(obj, unified) and obj is not obj.unify_chunks()
+
+
+def test_map_blocks_error(map_da, map_ds):
+ def bad_func(darray):
+ return (darray * darray.x + 5 * darray.y)[:1, :1]
+
+ with raises_regex(ValueError, "Length of the.* has changed."):
+ xr.map_blocks(bad_func, map_da).compute()
+
+ def returns_numpy(darray):
+ return (darray * darray.x + 5 * darray.y).values
+
+ with raises_regex(TypeError, "Function must return an xarray DataArray"):
+ xr.map_blocks(returns_numpy, map_da)
+
+ with raises_regex(TypeError, "args must be"):
+ xr.map_blocks(operator.add, map_da, args=10)
+
+ with raises_regex(TypeError, "kwargs must be"):
+ xr.map_blocks(operator.add, map_da, args=[10], kwargs=[20])
+
+ def really_bad_func(darray):
+ raise ValueError("couldn't do anything.")
+
+ with raises_regex(Exception, "Cannot infer"):
+ xr.map_blocks(really_bad_func, map_da)
+
+ ds_copy = map_ds.copy()
+ ds_copy["cxy"] = ds_copy.cxy.chunk({"y": 10})
+
+ with raises_regex(ValueError, "inconsistent chunks"):
+ xr.map_blocks(bad_func, ds_copy)
+
+ with raises_regex(TypeError, "Cannot pass dask collections"):
+ xr.map_blocks(bad_func, map_da, args=[map_da.chunk()])
+
+ with raises_regex(TypeError, "Cannot pass dask collections"):
+ xr.map_blocks(bad_func, map_da, kwargs=dict(a=map_da.chunk()))
+
+
+@pytest.mark.parametrize("obj", [make_da(), make_ds()])
+def test_map_blocks(obj):
+ def func(obj):
+ result = obj + obj.x + 5 * obj.y
+ return result
+
+ with raise_if_dask_computes():
+ actual = xr.map_blocks(func, obj)
+ expected = func(obj)
+ assert_chunks_equal(expected.chunk(), actual)
+ xr.testing.assert_identical(actual.compute(), expected.compute())
+
+
+@pytest.mark.parametrize("obj", [make_da(), make_ds()])
+def test_map_blocks_convert_args_to_list(obj):
+ expected = obj + 10
+ with raise_if_dask_computes():
+ actual = xr.map_blocks(operator.add, obj, [10])
+ assert_chunks_equal(expected.chunk(), actual)
+ xr.testing.assert_identical(actual.compute(), expected.compute())
+
+
+@pytest.mark.parametrize("obj", [make_da(), make_ds()])
+def test_map_blocks_add_attrs(obj):
+ def add_attrs(obj):
+ obj = obj.copy(deep=True)
+ obj.attrs["new"] = "new"
+ obj.cxy.attrs["new2"] = "new2"
+ return obj
+
+ expected = add_attrs(obj)
+ with raise_if_dask_computes():
+ actual = xr.map_blocks(add_attrs, obj)
+
+ xr.testing.assert_identical(actual.compute(), expected.compute())
+
+
+def test_map_blocks_change_name(map_da):
+ def change_name(obj):
+ obj = obj.copy(deep=True)
+ obj.name = "new"
+ return obj
+
+ expected = change_name(map_da)
+ with raise_if_dask_computes():
+ actual = xr.map_blocks(change_name, map_da)
+
+ xr.testing.assert_identical(actual.compute(), expected.compute())
+
+
+@pytest.mark.parametrize("obj", [make_da(), make_ds()])
+def test_map_blocks_kwargs(obj):
+ expected = xr.full_like(obj, fill_value=np.nan)
+ with raise_if_dask_computes():
+ actual = xr.map_blocks(xr.full_like, obj, kwargs=dict(fill_value=np.nan))
+ assert_chunks_equal(expected.chunk(), actual)
+ xr.testing.assert_identical(actual.compute(), expected.compute())
+
+
+def test_map_blocks_to_array(map_ds):
+ with raise_if_dask_computes():
+ actual = xr.map_blocks(lambda x: x.to_array(), map_ds)
+
+ # to_array does not preserve name, so cannot use assert_identical
+ assert_equal(actual.compute(), map_ds.to_array().compute())
+
+
+@pytest.mark.parametrize(
+ "func",
+ [
+ lambda x: x,
+ lambda x: x.to_dataset(),
+ lambda x: x.drop("x"),
+ lambda x: x.expand_dims(k=[1, 2, 3]),
+ lambda x: x.assign_coords(new_coord=("y", x.y * 2)),
+ lambda x: x.astype(np.int32),
+ # TODO: [lambda x: x.isel(x=1).drop("x"), map_da],
+ ],
+)
+def test_map_blocks_da_transformations(func, map_da):
+ with raise_if_dask_computes():
+ actual = xr.map_blocks(func, map_da)
+
+ assert_identical(actual.compute(), func(map_da).compute())
+
+
+@pytest.mark.parametrize(
+ "func",
+ [
+ lambda x: x,
+ lambda x: x.drop("cxy"),
+ lambda x: x.drop("a"),
+ lambda x: x.drop("x"),
+ lambda x: x.expand_dims(k=[1, 2, 3]),
+ lambda x: x.rename({"a": "new1", "b": "new2"}),
+ # TODO: [lambda x: x.isel(x=1)],
+ ],
+)
+def test_map_blocks_ds_transformations(func, map_ds):
+ with raise_if_dask_computes():
+ actual = xr.map_blocks(func, map_ds)
+
+ assert_identical(actual.compute(), func(map_ds).compute())
+
+
+@pytest.mark.parametrize("obj", [make_da(), make_ds()])
+def test_map_blocks_object_method(obj):
+ def func(obj):
+ result = obj + obj.x + 5 * obj.y
+ return result
+
+ with raise_if_dask_computes():
+ expected = xr.map_blocks(func, obj)
+ actual = obj.map_blocks(func)
+
+ assert_identical(expected.compute(), actual.compute())
+
+
+def test_make_meta(map_ds):
+ from ..core.parallel import make_meta
+
+ meta = make_meta(map_ds)
+
+ for variable in map_ds._coord_names:
+ assert variable in meta._coord_names
+ assert meta.coords[variable].shape == (0,) * meta.coords[variable].ndim
+
+ for variable in map_ds.data_vars:
+ assert variable in meta.data_vars
+ assert meta.data_vars[variable].shape == (0,) * meta.data_vars[variable].ndim
|
[
{
"path": "doc/api.rst",
"old_path": "a/doc/api.rst",
"new_path": "b/doc/api.rst",
"metadata": "diff --git a/doc/api.rst b/doc/api.rst\nindex 256a1dbf3af..40f9add3c57 100644\n--- a/doc/api.rst\n+++ b/doc/api.rst\n@@ -30,6 +30,7 @@ Top-level functions\n zeros_like\n ones_like\n dot\n+ map_blocks\n \n Dataset\n =======\n@@ -499,6 +500,8 @@ Dataset methods\n Dataset.persist\n Dataset.load\n Dataset.chunk\n+ Dataset.unify_chunks\n+ Dataset.map_blocks\n Dataset.filter_by_attrs\n Dataset.info\n \n@@ -529,6 +532,8 @@ DataArray methods\n DataArray.persist\n DataArray.load\n DataArray.chunk\n+ DataArray.unify_chunks\n+ DataArray.map_blocks\n \n GroupBy objects\n ===============\n@@ -629,6 +634,7 @@ Testing\n testing.assert_equal\n testing.assert_identical\n testing.assert_allclose\n+ testing.assert_chunks_equal\n \n Exceptions\n ==========\n"
},
{
"path": "doc/whats-new.rst",
"old_path": "a/doc/whats-new.rst",
"new_path": "b/doc/whats-new.rst",
"metadata": "diff --git a/doc/whats-new.rst b/doc/whats-new.rst\nindex 520f1f79870..b6e12f01f4b 100644\n--- a/doc/whats-new.rst\n+++ b/doc/whats-new.rst\n@@ -49,6 +49,11 @@ Breaking changes\n New functions/methods\n ~~~~~~~~~~~~~~~~~~~~~\n \n+- Added :py:func:`~xarray.map_blocks`, modeled after :py:func:`dask.array.map_blocks`.\n+ Also added :py:meth:`Dataset.unify_chunks`, :py:meth:`DataArray.unify_chunks` and\n+ :py:meth:`testing.assert_chunks_equal`. By `Deepak Cherian <https://github.com/dcherian>`_\n+ and `Guido Imperiale <https://github.com/crusaderky>`_.\n+\n Enhancements\n ~~~~~~~~~~~~\n \n"
}
] |
2206
|
291cb805bf0bf326da87152cc6548191bbeb6aab
|
[
"xarray/tests/test_backends.py::TestScipyInMemoryData::test_invalid_dataarray_names_raise",
"xarray/tests/test_backends.py::TestH5NetCDFFileObject::test_open_subgroup",
"xarray/tests/test_backends.py::TestH5NetCDFViaDaskData::test_dataset_caching",
"xarray/tests/test_coding_times.py::test_use_cftime_false_non_standard_calendar[2000-julian]",
"xarray/tests/test_backends.py::TestH5NetCDFData::test_0dimensional_variable",
"xarray/tests/test_coding_times.py::test_cf_datetime[num_dates19-Hour since 1680-01-01 00:00:00-proleptic_gregorian]",
"xarray/tests/test_coding_times.py::test_cf_timedelta[1D-days-numbers0]",
"xarray/tests/test_backends.py::TestRasterio::test_geotiff_tags",
"xarray/tests/test_coding_times.py::test_cf_datetime[num_dates58-hours since 1900-01-01T00:00:00-proleptic_gregorian]",
"xarray/tests/test_dask.py::test_persist_DataArray[<lambda>0]",
"xarray/tests/test_backends.py::TestDask::test_roundtrip_test_data",
"xarray/tests/test_backends.py::TestNetCDF4ViaDaskData::test_read_variable_len_strings",
"xarray/tests/test_coding_times.py::test_cf_datetime[num_dates16-hour since 1680-01-01 00:00:00-proleptic_gregorian]",
"xarray/tests/test_dask.py::TestDataArrayAndDataset::test_ufuncs",
"xarray/tests/test_coding_times.py::test_cf_datetime[10-days since 2000-01-01-standard]",
"xarray/tests/test_backends.py::TestCommon::test_robust_getitem",
"xarray/tests/test_dask.py::TestDataArrayAndDataset::test_dataset_pickle",
"xarray/tests/test_backends.py::TestNetCDF4Data::test_read_variable_len_strings",
"xarray/tests/test_backends.py::TestNetCDF4Data::test_invalid_dataarray_names_raise",
"xarray/tests/test_backends.py::TestH5NetCDFFileObject::test_read_variable_len_strings",
"xarray/tests/test_dask.py::TestDataArrayAndDataset::test_dataarray_getattr",
"xarray/tests/test_backends.py::TestScipyFilePath::test_roundtrip_example_1_netcdf_gz",
"xarray/tests/test_coding_times.py::test_cf_datetime[num_dates15-hour since 1680-01-01 00:00:00-gregorian]",
"xarray/tests/test_coding_times.py::test_cf_timedelta_2d",
"xarray/tests/test_backends.py::TestDask::test_zero_dimensional_variable",
"xarray/tests/test_backends.py::TestDask::test_dataset_caching",
"xarray/tests/test_coding_times.py::test_cf_datetime[num_dates13-hours since 1680-01-01 00:00:00-proleptic_gregorian]",
"xarray/tests/test_coding_times.py::test_cf_datetime[0-milliseconds since 2000-01-01T00:00:00-gregorian]",
"xarray/tests/test_backends.py::TestNetCDF4ViaDaskData::test_invalid_dataarray_names_raise",
"xarray/tests/test_dask.py::TestVariable::test_repr",
"xarray/tests/test_dask.py::TestDataArrayAndDataset::test_where_dispatching",
"xarray/tests/test_coding_times.py::test_infer_cftime_datetime_units[date_args0-days since 1900-01-01 00:00:00.000000-all_leap]",
"xarray/tests/test_backends.py::TestDask::test_save_mfdataset_invalid_dataarray",
"xarray/tests/test_backends.py::TestDask::test_dataset_compute",
"xarray/tests/test_backends.py::TestH5NetCDFData::test_read_variable_len_strings",
"xarray/tests/test_backends.py::TestEncodingInvalid::test_extract_nc4_variable_encoding",
"xarray/tests/test_coding_times.py::test_use_cftime_false_non_standard_calendar[2000-noleap]",
"xarray/tests/test_dask.py::TestToDaskDataFrame::test_to_dask_dataframe",
"xarray/tests/test_coding_times.py::test_cf_timedelta[timedeltas5-None-numbers5]",
"xarray/tests/test_coding_times.py::test_use_cftime_false_non_standard_calendar[2500-366_day]",
"xarray/tests/test_dask.py::test_dask_kwargs_variable[compute]",
"xarray/tests/test_coding_times.py::test_cf_timedelta[timedeltas6-hours-numbers6]",
"xarray/tests/test_dask.py::TestVariable::test_squeeze",
"xarray/tests/test_coding_times.py::test_cf_datetime[num_dates6-days since 2000-01-01-gregorian]",
"xarray/tests/test_backends.py::TestNetCDF4ViaDaskData::test_open_group",
"xarray/tests/test_backends.py::TestH5NetCDFFileObject::test_open_badbytes",
"xarray/tests/test_backends.py::TestDask::test_write_store",
"xarray/tests/test_dask.py::TestDataArrayAndDataset::test_stack",
"xarray/tests/test_coding_times.py::test_infer_datetime_units[dates3-seconds since 1900-01-01 00:00:00]",
"xarray/tests/test_backends.py::TestH5NetCDFViaDaskData::test_open_encodings",
"xarray/tests/test_coding_times.py::test_use_cftime_false_non_standard_calendar[1500-360_day]",
"xarray/tests/test_backends.py::TestH5NetCDFViaDaskData::test_invalid_dataarray_names_raise",
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"xarray/tests/test_coding_times.py::test_cf_datetime[num_dates57-hours since 1900-01-01T00:00:00-gregorian]",
"xarray/tests/test_backends.py::TestScipyFilePath::test_multiindex_not_implemented",
"xarray/tests/test_coding_times.py::test_cf_datetime[num_dates12-hours since 1680-01-01 00:00:00-gregorian]",
"xarray/tests/test_coding_times.py::test_infer_cftime_datetime_units[date_args1-seconds since 1900-01-01 00:00:00.000000-gregorian]",
"xarray/tests/test_dask.py::test_dask_kwargs_variable[load]",
"xarray/tests/test_coding_times.py::test_cf_datetime[num_dates11-days since 2000-01-01-standard]",
"xarray/tests/test_coding_times.py::test_time_units_with_timezone_roundtrip[standard]",
"xarray/tests/test_backends.py::TestRasterio::test_notransform",
"xarray/tests/test_coding_times.py::test_cf_datetime[num_dates21- Hour since 1680-01-01 00:00:00 -gregorian]",
"xarray/tests/test_coding_times.py::test_format_cftime_datetime[date_args2-0100-02-03 04:05:06.000000]",
"xarray/tests/test_dask.py::TestToDaskDataFrame::test_to_dask_dataframe_coordinates",
"xarray/tests/test_coding_times.py::test_cf_datetime[num_dates10-days since 2000-01-01-proleptic_gregorian]",
"xarray/tests/test_backends.py::TestCfGrib::test_read",
"xarray/tests/test_backends.py::TestH5NetCDFViaDaskData::test_read_byte_attrs_as_unicode",
"xarray/tests/test_coding_times.py::test_infer_cftime_datetime_units[date_args1-seconds since 1900-01-01 00:00:00.000000-julian]",
"xarray/tests/test_backends.py::TestScipyFilePath::test_netcdf3_endianness",
"xarray/tests/test_coding_times.py::test_contains_cftime_datetimes_non_cftimes_dask[non_cftime_data1]",
"xarray/tests/test_backends.py::TestH5NetCDFViaDaskData::test_open_group",
"xarray/tests/test_backends.py::TestRasterio::test_pickle_rasterio",
"xarray/tests/test_dask.py::TestDataArrayAndDataset::test_rechunk",
"xarray/tests/test_backends.py::TestEncodingInvalid::test_extract_h5nc_encoding",
"xarray/tests/test_coding_times.py::test_cf_timedelta[1h-hours-numbers2]",
"xarray/tests/test_coding_times.py::test_use_cftime_false_non_standard_calendar[2000-360_day]",
"xarray/tests/test_coding_times.py::test_use_cftime_false_non_standard_calendar[1500-julian]",
"xarray/tests/test_coding_times.py::test_decode_cf[proleptic_gregorian]",
"xarray/tests/test_dask.py::TestVariable::test_bivariate_ufunc",
"xarray/tests/test_coding_times.py::test_cf_datetime[0-microseconds since 2000-01-01T00:00:00-gregorian]",
"xarray/tests/test_coding_times.py::test_cf_datetime[num_dates68-seconds since 1981-01-01-standard]",
"xarray/tests/test_coding_times.py::test_infer_timedelta_units[deltas0-days]",
"xarray/tests/test_coding_times.py::test_decode_cf[standard]",
"xarray/tests/test_dask.py::test_dataarray_with_dask_coords",
"xarray/tests/test_backends.py::TestRasterio::test_no_mftime",
"xarray/tests/test_backends.py::TestNetCDF4Data::test_multiindex_not_implemented",
"xarray/tests/test_coding_times.py::test_infer_cftime_datetime_units[date_args0-days since 1900-01-01 00:00:00.000000-366_day]",
"xarray/tests/test_coding_times.py::test_cf_datetime[num_dates5-days since 2000-01-01-standard]",
"xarray/tests/test_coding_times.py::test_cf_datetime[0-milliseconds since 2000-01-01T00:00:00-proleptic_gregorian]",
"xarray/tests/test_backends.py::TestZarrDictStore::test_encoding_kwarg_fixed_width_string",
"xarray/tests/test_backends.py::TestNetCDF4Data::test_0dimensional_variable",
"xarray/tests/test_coding_times.py::test_cf_datetime[num_dates14-hours since 1680-01-01 00:00:00-standard]",
"xarray/tests/test_backends.py::TestH5NetCDFData::test_open_group",
"xarray/tests/test_dask.py::TestVariable::test_chunk",
"xarray/tests/test_dask.py::TestVariable::test_equals",
"xarray/tests/test_coding_times.py::test_infer_cftime_datetime_units[date_args1-seconds since 1900-01-01 00:00:00.000000-365_day]"
] |
[
"xarray/tests/test_dask.py::test_map_blocks_da_transformations[<lambda>5]",
"xarray/tests/test_dask.py::test_unify_chunks_shallow_copy[<lambda>0-obj1]",
"xarray/tests/test_dask.py::test_map_blocks_da_transformations[<lambda>1]",
"xarray/tests/test_dask.py::test_map_blocks_ds_transformations[<lambda>2]",
"xarray/tests/test_dask.py::test_unify_chunks",
"xarray/tests/test_dask.py::test_unify_chunks_shallow_copy[<lambda>1-obj0]",
"xarray/tests/test_dask.py::test_unify_chunks_shallow_copy[<lambda>0-obj0]",
"xarray/tests/test_dask.py::test_map_blocks_ds_transformations[<lambda>3]",
"xarray/tests/test_dask.py::test_map_blocks_kwargs[obj1]",
"xarray/tests/test_dask.py::test_map_blocks_object_method[obj1]",
"xarray/tests/test_dask.py::test_map_blocks_add_attrs[obj0]",
"xarray/tests/test_dask.py::test_map_blocks[obj0]",
"xarray/tests/test_dask.py::test_map_blocks[obj1]",
"xarray/tests/test_dask.py::test_map_blocks_convert_args_to_list[obj1]",
"xarray/tests/test_dask.py::test_map_blocks_object_method[obj0]",
"xarray/tests/test_dask.py::test_unify_chunks_shallow_copy[<lambda>1-obj1]",
"xarray/tests/test_dask.py::test_map_blocks_ds_transformations[<lambda>5]",
"xarray/tests/test_dask.py::test_map_blocks_da_transformations[<lambda>4]",
"xarray/tests/test_dask.py::test_map_blocks_add_attrs[obj1]",
"xarray/tests/test_dask.py::test_map_blocks_change_name",
"xarray/tests/test_dask.py::test_map_blocks_ds_transformations[<lambda>0]",
"xarray/tests/test_dask.py::test_map_blocks_kwargs[obj0]",
"xarray/tests/test_dask.py::test_map_blocks_ds_transformations[<lambda>1]",
"xarray/tests/test_dask.py::test_map_blocks_da_transformations[<lambda>0]",
"xarray/tests/test_dask.py::test_map_blocks_da_transformations[<lambda>3]",
"xarray/tests/test_dask.py::test_map_blocks_convert_args_to_list[obj0]",
"xarray/tests/test_dask.py::test_make_meta",
"xarray/tests/test_dask.py::test_map_blocks_da_transformations[<lambda>2]",
"xarray/tests/test_dask.py::test_map_blocks_error",
"xarray/tests/test_dask.py::test_map_blocks_to_array",
"xarray/tests/test_dask.py::test_map_blocks_ds_transformations[<lambda>4]"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": [
{
"type": "field",
"name": "result"
},
{
"type": "field",
"name": "meta"
},
{
"type": "field",
"name": "parallel"
},
{
"type": "field",
"name": "shape"
},
{
"type": "field",
"name": "_coord_names"
},
{
"type": "field",
"name": "ndim"
},
{
"type": "field",
"name": "ndim"
},
{
"type": "file",
"name": "xarray/core/dask_array_compat.py"
},
{
"type": "field",
"name": "parallel"
},
{
"type": "field",
"name": "core"
},
{
"type": "field",
"name": "parallel"
},
{
"type": "field",
"name": "operator"
},
{
"type": "field",
"name": "meta"
},
{
"type": "file",
"name": "xarray/core/parallel.py"
},
{
"type": "field",
"name": "astype"
},
{
"type": "function",
"name": "make_meta"
},
{
"type": "field",
"name": "make_meta"
}
]
}
|
[
{
"path": "doc/api.rst",
"old_path": "a/doc/api.rst",
"new_path": "b/doc/api.rst",
"metadata": "diff --git a/doc/api.rst b/doc/api.rst\nindex 256a1dbf3af..40f9add3c57 100644\n--- a/doc/api.rst\n+++ b/doc/api.rst\n@@ -30,6 +30,7 @@ Top-level functions\n zeros_like\n ones_like\n dot\n+ map_blocks\n \n Dataset\n =======\n@@ -499,6 +500,8 @@ Dataset methods\n Dataset.persist\n Dataset.load\n Dataset.chunk\n+ Dataset.unify_chunks\n+ Dataset.map_blocks\n Dataset.filter_by_attrs\n Dataset.info\n \n@@ -529,6 +532,8 @@ DataArray methods\n DataArray.persist\n DataArray.load\n DataArray.chunk\n+ DataArray.unify_chunks\n+ DataArray.map_blocks\n \n GroupBy objects\n ===============\n@@ -629,6 +634,7 @@ Testing\n testing.assert_equal\n testing.assert_identical\n testing.assert_allclose\n+ testing.assert_chunks_equal\n \n Exceptions\n ==========\n"
},
{
"path": "doc/whats-new.rst",
"old_path": "a/doc/whats-new.rst",
"new_path": "b/doc/whats-new.rst",
"metadata": "diff --git a/doc/whats-new.rst b/doc/whats-new.rst\nindex 520f1f79870..b6e12f01f4b 100644\n--- a/doc/whats-new.rst\n+++ b/doc/whats-new.rst\n@@ -49,6 +49,11 @@ Breaking changes\n New functions/methods\n ~~~~~~~~~~~~~~~~~~~~~\n \n+- Added :py:func:`~xarray.map_blocks`, modeled after :py:func:`dask.array.map_blocks`.\n+ Also added :py:meth:`Dataset.unify_chunks`, :py:meth:`DataArray.unify_chunks` and\n+ :py:meth:`testing.assert_chunks_equal`. By `<NAME>`_\n+ and <NAME>_.\n+\n Enhancements\n ~~~~~~~~~~~~\n \n"
}
] |
diff --git a/doc/api.rst b/doc/api.rst
index 256a1dbf3af..40f9add3c57 100644
--- a/doc/api.rst
+++ b/doc/api.rst
@@ -30,6 +30,7 @@ Top-level functions
zeros_like
ones_like
dot
+ map_blocks
Dataset
=======
@@ -499,6 +500,8 @@ Dataset methods
Dataset.persist
Dataset.load
Dataset.chunk
+ Dataset.unify_chunks
+ Dataset.map_blocks
Dataset.filter_by_attrs
Dataset.info
@@ -529,6 +532,8 @@ DataArray methods
DataArray.persist
DataArray.load
DataArray.chunk
+ DataArray.unify_chunks
+ DataArray.map_blocks
GroupBy objects
===============
@@ -629,6 +634,7 @@ Testing
testing.assert_equal
testing.assert_identical
testing.assert_allclose
+ testing.assert_chunks_equal
Exceptions
==========
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index 520f1f79870..b6e12f01f4b 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -49,6 +49,11 @@ Breaking changes
New functions/methods
~~~~~~~~~~~~~~~~~~~~~
+- Added :py:func:`~xarray.map_blocks`, modeled after :py:func:`dask.array.map_blocks`.
+ Also added :py:meth:`Dataset.unify_chunks`, :py:meth:`DataArray.unify_chunks` and
+ :py:meth:`testing.assert_chunks_equal`. By `<NAME>`_
+ and <NAME>_.
+
Enhancements
~~~~~~~~~~~~
If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:
[{'type': 'field', 'name': 'result'}, {'type': 'field', 'name': 'meta'}, {'type': 'field', 'name': 'parallel'}, {'type': 'field', 'name': 'shape'}, {'type': 'field', 'name': '_coord_names'}, {'type': 'field', 'name': 'ndim'}, {'type': 'field', 'name': 'ndim'}, {'type': 'file', 'name': 'xarray/core/dask_array_compat.py'}, {'type': 'field', 'name': 'parallel'}, {'type': 'field', 'name': 'core'}, {'type': 'field', 'name': 'parallel'}, {'type': 'field', 'name': 'operator'}, {'type': 'field', 'name': 'meta'}, {'type': 'file', 'name': 'xarray/core/parallel.py'}, {'type': 'field', 'name': 'astype'}, {'type': 'function', 'name': 'make_meta'}, {'type': 'field', 'name': 'make_meta'}]
|
matplotlib/matplotlib
|
matplotlib__matplotlib-25904
|
https://github.com/matplotlib/matplotlib/pull/25904
|
diff --git a/doc/users/next_whats_new/spinesproxyset.rst b/doc/users/next_whats_new/spinesproxyset.rst
new file mode 100644
index 000000000000..cfd8d2908ec7
--- /dev/null
+++ b/doc/users/next_whats_new/spinesproxyset.rst
@@ -0,0 +1,3 @@
+``SpinesProxy`` now supports calling the ``set()`` method
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+One can now call e.g. ``ax.spines[:].set(visible=False)``.
diff --git a/lib/matplotlib/spines.py b/lib/matplotlib/spines.py
index 8560f7b6e4e2..eacb3e7e9d5c 100644
--- a/lib/matplotlib/spines.py
+++ b/lib/matplotlib/spines.py
@@ -479,7 +479,7 @@ def set_color(self, c):
class SpinesProxy:
"""
- A proxy to broadcast ``set_*`` method calls to all contained `.Spines`.
+ A proxy to broadcast ``set_*()`` and ``set()`` method calls to contained `.Spines`.
The proxy cannot be used for any other operations on its members.
@@ -493,7 +493,7 @@ def __init__(self, spine_dict):
def __getattr__(self, name):
broadcast_targets = [spine for spine in self._spine_dict.values()
if hasattr(spine, name)]
- if not name.startswith('set_') or not broadcast_targets:
+ if (name != 'set' and not name.startswith('set_')) or not broadcast_targets:
raise AttributeError(
f"'SpinesProxy' object has no attribute '{name}'")
@@ -531,8 +531,8 @@ class Spines(MutableMapping):
spines[:].set_visible(False)
- The latter two indexing methods will return a `SpinesProxy` that broadcasts
- all ``set_*`` calls to its members, but cannot be used for any other
+ The latter two indexing methods will return a `SpinesProxy` that broadcasts all
+ ``set_*()`` and ``set()`` calls to its members, but cannot be used for any other
operation.
"""
def __init__(self, **kwargs):
|
diff --git a/lib/matplotlib/tests/test_spines.py b/lib/matplotlib/tests/test_spines.py
index 89bc0c872de5..9ce16fb39227 100644
--- a/lib/matplotlib/tests/test_spines.py
+++ b/lib/matplotlib/tests/test_spines.py
@@ -12,6 +12,9 @@ class SpineMock:
def __init__(self):
self.val = None
+ def set(self, **kwargs):
+ vars(self).update(kwargs)
+
def set_val(self, val):
self.val = val
@@ -35,6 +38,9 @@ def set_val(self, val):
spines[:].set_val('y')
assert all(spine.val == 'y' for spine in spines.values())
+ spines[:].set(foo='bar')
+ assert all(spine.foo == 'bar' for spine in spines.values())
+
with pytest.raises(AttributeError, match='foo'):
spines.foo
with pytest.raises(KeyError, match='foo'):
|
[
{
"path": "doc/users/next_whats_new/spinesproxyset.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/spinesproxyset.rst",
"metadata": "diff --git a/doc/users/next_whats_new/spinesproxyset.rst b/doc/users/next_whats_new/spinesproxyset.rst\nnew file mode 100644\nindex 000000000000..cfd8d2908ec7\n--- /dev/null\n+++ b/doc/users/next_whats_new/spinesproxyset.rst\n@@ -0,0 +1,3 @@\n+``SpinesProxy`` now supports calling the ``set()`` method\n+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n+One can now call e.g. ``ax.spines[:].set(visible=False)``.\n"
}
] |
3.7
|
2466ccb77a92fe57e045ac0c0b56d61ce563abf9
|
[
"lib/matplotlib/tests/test_spines.py::test_spines_black_axes[svg]",
"lib/matplotlib/tests/test_spines.py::test_spines_axes_positions[svg]",
"lib/matplotlib/tests/test_spines.py::test_spine_nonlinear_data_positions[png]",
"lib/matplotlib/tests/test_spines.py::test_spines_data_positions[png]",
"lib/matplotlib/tests/test_spines.py::test_spines_capstyle[png]",
"lib/matplotlib/tests/test_spines.py::test_spines_axes_positions[png]",
"lib/matplotlib/tests/test_spines.py::test_spines_capstyle[svg]",
"lib/matplotlib/tests/test_spines.py::test_spines_axes_positions[pdf]",
"lib/matplotlib/tests/test_spines.py::test_spines_data_positions[svg]",
"lib/matplotlib/tests/test_spines.py::test_spines_data_positions[pdf]",
"lib/matplotlib/tests/test_spines.py::test_spines_black_axes[pdf]",
"lib/matplotlib/tests/test_spines.py::test_spines_black_axes[png]",
"lib/matplotlib/tests/test_spines.py::test_spines_capstyle[pdf]",
"lib/matplotlib/tests/test_spines.py::test_label_without_ticks"
] |
[
"lib/matplotlib/tests/test_spines.py::test_spine_class"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/users/next_whats_new/spinesproxyset.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/spinesproxyset.rst",
"metadata": "diff --git a/doc/users/next_whats_new/spinesproxyset.rst b/doc/users/next_whats_new/spinesproxyset.rst\nnew file mode 100644\nindex 000000000000..cfd8d2908ec7\n--- /dev/null\n+++ b/doc/users/next_whats_new/spinesproxyset.rst\n@@ -0,0 +1,3 @@\n+``SpinesProxy`` now supports calling the ``set()`` method\n+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n+One can now call e.g. ``ax.spines[:].set(visible=False)``.\n"
}
] |
diff --git a/doc/users/next_whats_new/spinesproxyset.rst b/doc/users/next_whats_new/spinesproxyset.rst
new file mode 100644
index 000000000000..cfd8d2908ec7
--- /dev/null
+++ b/doc/users/next_whats_new/spinesproxyset.rst
@@ -0,0 +1,3 @@
+``SpinesProxy`` now supports calling the ``set()`` method
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+One can now call e.g. ``ax.spines[:].set(visible=False)``.
|
matplotlib/matplotlib
|
matplotlib__matplotlib-26278
|
https://github.com/matplotlib/matplotlib/pull/26278
|
diff --git a/doc/users/next_whats_new/contour_clip_path.rst b/doc/users/next_whats_new/contour_clip_path.rst
new file mode 100644
index 000000000000..db4039a4fd70
--- /dev/null
+++ b/doc/users/next_whats_new/contour_clip_path.rst
@@ -0,0 +1,24 @@
+Clipping for contour plots
+--------------------------
+
+`~.Axes.contour` and `~.Axes.contourf` now accept the *clip_path* parameter.
+
+.. plot::
+ :include-source: true
+
+ import numpy as np
+ import matplotlib.pyplot as plt
+ import matplotlib.patches as mpatches
+
+ x = y = np.arange(-3.0, 3.01, 0.025)
+ X, Y = np.meshgrid(x, y)
+ Z1 = np.exp(-X**2 - Y**2)
+ Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
+ Z = (Z1 - Z2) * 2
+
+ fig, ax = plt.subplots()
+ patch = mpatches.RegularPolygon((0, 0), 5, radius=2,
+ transform=ax.transData)
+ ax.contourf(X, Y, Z, clip_path=patch)
+
+ plt.show()
diff --git a/lib/matplotlib/contour.py b/lib/matplotlib/contour.py
index 625c3524bfcb..6f97c5646ab0 100644
--- a/lib/matplotlib/contour.py
+++ b/lib/matplotlib/contour.py
@@ -751,7 +751,7 @@ def __init__(self, ax, *args,
hatches=(None,), alpha=None, origin=None, extent=None,
cmap=None, colors=None, norm=None, vmin=None, vmax=None,
extend='neither', antialiased=None, nchunk=0, locator=None,
- transform=None, negative_linestyles=None,
+ transform=None, negative_linestyles=None, clip_path=None,
**kwargs):
"""
Draw contour lines or filled regions, depending on
@@ -805,6 +805,7 @@ def __init__(self, ax, *args,
super().__init__(
antialiaseds=antialiased,
alpha=alpha,
+ clip_path=clip_path,
transform=transform,
)
self.axes = ax
@@ -1870,6 +1871,11 @@ def _initialize_x_y(self, z):
The default is taken from :rc:`contour.algorithm`.
+clip_path : `~matplotlib.patches.Patch` or `.Path` or `.TransformedPath`
+ Set the clip path. See `~matplotlib.artist.Artist.set_clip_path`.
+
+ .. versionadded:: 3.8
+
data : indexable object, optional
DATA_PARAMETER_PLACEHOLDER
diff --git a/lib/matplotlib/contour.pyi b/lib/matplotlib/contour.pyi
index c2190577169d..c7179637a1e1 100644
--- a/lib/matplotlib/contour.pyi
+++ b/lib/matplotlib/contour.pyi
@@ -4,8 +4,10 @@ from matplotlib.axes import Axes
from matplotlib.collections import Collection, PathCollection
from matplotlib.colors import Colormap, Normalize
from matplotlib.font_manager import FontProperties
+from matplotlib.path import Path
+from matplotlib.patches import Patch
from matplotlib.text import Text
-from matplotlib.transforms import Transform
+from matplotlib.transforms import Transform, TransformedPatchPath, TransformedPath
from matplotlib.ticker import Locator, Formatter
from numpy.typing import ArrayLike
@@ -99,6 +101,7 @@ class ContourSet(ContourLabeler, Collection):
negative_linestyles: None | Literal[
"solid", "dashed", "dashdot", "dotted"
] | Iterable[Literal["solid", "dashed", "dashdot", "dotted"]]
+ clip_path: Patch | Path | TransformedPath | TransformedPatchPath | None
labelTexts: list[Text]
labelCValues: list[ColorType]
allkinds: list[np.ndarray]
@@ -145,6 +148,7 @@ class ContourSet(ContourLabeler, Collection):
negative_linestyles: Literal["solid", "dashed", "dashdot", "dotted"]
| Iterable[Literal["solid", "dashed", "dashdot", "dotted"]]
| None = ...,
+ clip_path: Patch | Path | TransformedPath | TransformedPatchPath | None = ...,
**kwargs
) -> None: ...
def legend_elements(
|
diff --git a/lib/matplotlib/tests/test_contour.py b/lib/matplotlib/tests/test_contour.py
index c730c8ea332d..7a4c4570580c 100644
--- a/lib/matplotlib/tests/test_contour.py
+++ b/lib/matplotlib/tests/test_contour.py
@@ -9,6 +9,7 @@
import matplotlib as mpl
from matplotlib import pyplot as plt, rc_context, ticker
from matplotlib.colors import LogNorm, same_color
+import matplotlib.patches as mpatches
from matplotlib.testing.decorators import image_comparison
import pytest
@@ -752,6 +753,14 @@ def test_contour_no_args():
ax.contour(Z=data)
+def test_contour_clip_path():
+ fig, ax = plt.subplots()
+ data = [[0, 1], [1, 0]]
+ circle = mpatches.Circle([0.5, 0.5], 0.5, transform=ax.transAxes)
+ cs = ax.contour(data, clip_path=circle)
+ assert cs.get_clip_path() is not None
+
+
def test_bool_autolevel():
x, y = np.random.rand(2, 9)
z = (np.arange(9) % 2).reshape((3, 3)).astype(bool)
|
[
{
"path": "doc/users/next_whats_new/contour_clip_path.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/contour_clip_path.rst",
"metadata": "diff --git a/doc/users/next_whats_new/contour_clip_path.rst b/doc/users/next_whats_new/contour_clip_path.rst\nnew file mode 100644\nindex 000000000000..db4039a4fd70\n--- /dev/null\n+++ b/doc/users/next_whats_new/contour_clip_path.rst\n@@ -0,0 +1,24 @@\n+Clipping for contour plots\n+--------------------------\n+\n+`~.Axes.contour` and `~.Axes.contourf` now accept the *clip_path* parameter.\n+\n+.. plot::\n+ :include-source: true\n+\n+ import numpy as np\n+ import matplotlib.pyplot as plt\n+ import matplotlib.patches as mpatches\n+\n+ x = y = np.arange(-3.0, 3.01, 0.025)\n+ X, Y = np.meshgrid(x, y)\n+ Z1 = np.exp(-X**2 - Y**2)\n+ Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)\n+ Z = (Z1 - Z2) * 2\n+\n+ fig, ax = plt.subplots()\n+ patch = mpatches.RegularPolygon((0, 0), 5, radius=2,\n+ transform=ax.transData)\n+ ax.contourf(X, Y, Z, clip_path=patch)\n+\n+ plt.show()\n"
}
] |
3.7
|
02d2e137251ebcbd698b6f1ff8c455a1e52082af
|
[
"lib/matplotlib/tests/test_contour.py::test_contour_shape_error[args9-Input z must be at least a (2, 2) shaped array, but has shape (1, 1)]",
"lib/matplotlib/tests/test_contour.py::test_contour_shape_2d_valid",
"lib/matplotlib/tests/test_contour.py::test_contour_manual_labels[svg-False]",
"lib/matplotlib/tests/test_contour.py::test_contour_shape_error[args5-Shapes of y (9, 9) and z (9, 10) do not match]",
"lib/matplotlib/tests/test_contour.py::test_contourf_log_extension[png-True]",
"lib/matplotlib/tests/test_contour.py::test_negative_linestyles[dashdot]",
"lib/matplotlib/tests/test_contour.py::test_contourf_decreasing_levels",
"lib/matplotlib/tests/test_contour.py::test_algorithm_supports_corner_mask[serial]",
"lib/matplotlib/tests/test_contour.py::test_contour_shape_error[args1-Length of y (10) must match number of rows in z (9)]",
"lib/matplotlib/tests/test_contour.py::test_all_nan",
"lib/matplotlib/tests/test_contour.py::test_corner_mask[png-False]",
"lib/matplotlib/tests/test_contour.py::test_contourf_legend_elements",
"lib/matplotlib/tests/test_contour.py::test_algorithm_name[serial-SerialContourGenerator]",
"lib/matplotlib/tests/test_contour.py::test_contour_shape_error[args6-Inputs x and y must be 1D or 2D, not 3D]",
"lib/matplotlib/tests/test_contour.py::test_contour_datetime_axis[png-True]",
"lib/matplotlib/tests/test_contour.py::test_contour_datetime_axis[png-False]",
"lib/matplotlib/tests/test_contour.py::test_algorithm_name[invalid-None]",
"lib/matplotlib/tests/test_contour.py::test_contour_manual_labels[svg-True]",
"lib/matplotlib/tests/test_contour.py::test_algorithm_supports_corner_mask[mpl2005]",
"lib/matplotlib/tests/test_contour.py::test_bool_autolevel",
"lib/matplotlib/tests/test_contour.py::test_quadcontourset_reuse",
"lib/matplotlib/tests/test_contour.py::test_contour_shape_error[args4-Shapes of x (9, 9) and z (9, 10) do not match]",
"lib/matplotlib/tests/test_contour.py::test_contour_Nlevels",
"lib/matplotlib/tests/test_contour.py::test_contour_addlines[png-True]",
"lib/matplotlib/tests/test_contour.py::test_algorithm_name[mpl2005-Mpl2005ContourGenerator]",
"lib/matplotlib/tests/test_contour.py::test_circular_contour_warning",
"lib/matplotlib/tests/test_contour.py::test_labels[png-True]",
"lib/matplotlib/tests/test_contour.py::test_contour_manual_labels[png-True]",
"lib/matplotlib/tests/test_contour.py::test_find_nearest_contour",
"lib/matplotlib/tests/test_contour.py::test_contour_shape_error[args2-Number of dimensions of x (2) and y (1) do not match]",
"lib/matplotlib/tests/test_contour.py::test_contour_manual[png-True]",
"lib/matplotlib/tests/test_contour.py::test_contour_autolabel_beyond_powerlimits",
"lib/matplotlib/tests/test_contour.py::test_algorithm_name[mpl2014-Mpl2014ContourGenerator]",
"lib/matplotlib/tests/test_contour.py::test_contour_uneven[png-True]",
"lib/matplotlib/tests/test_contour.py::test_contour_shape_error[args3-Number of dimensions of x (1) and y (2) do not match]",
"lib/matplotlib/tests/test_contour.py::test_contourf_log_extension[png-False]",
"lib/matplotlib/tests/test_contour.py::test_contour_line_start_on_corner_edge[png-True]",
"lib/matplotlib/tests/test_contour.py::test_contour_manual[png-False]",
"lib/matplotlib/tests/test_contour.py::test_contour_shape_1d_valid",
"lib/matplotlib/tests/test_contour.py::test_contour_shape_error[args8-Input z must be at least a (2, 2) shaped array, but has shape (1, 1)]",
"lib/matplotlib/tests/test_contour.py::test_contourf_symmetric_locator",
"lib/matplotlib/tests/test_contour.py::test_clabel_zorder[False-123-None]",
"lib/matplotlib/tests/test_contour.py::test_contour_linewidth[1.23-4.24-None-4.24]",
"lib/matplotlib/tests/test_contour.py::test_log_locator_levels[svg-False]",
"lib/matplotlib/tests/test_contour.py::test_corner_mask[png-True]",
"lib/matplotlib/tests/test_contour.py::test_find_nearest_contour_no_filled",
"lib/matplotlib/tests/test_contour.py::test_subfigure_clabel",
"lib/matplotlib/tests/test_contour.py::test_all_algorithms[png-False]",
"lib/matplotlib/tests/test_contour.py::test_contour_closed_line_loop[png-True]",
"lib/matplotlib/tests/test_contour.py::test_labels[png-False]",
"lib/matplotlib/tests/test_contour.py::test_linestyles[dotted]",
"lib/matplotlib/tests/test_contour.py::test_contour_line_start_on_corner_edge[png-False]",
"lib/matplotlib/tests/test_contour.py::test_algorithm_name[threaded-ThreadedContourGenerator]",
"lib/matplotlib/tests/test_contour.py::test_contour_manual_labels[pdf-False]",
"lib/matplotlib/tests/test_contour.py::test_negative_linestyles[dotted]",
"lib/matplotlib/tests/test_contour.py::test_contour_remove",
"lib/matplotlib/tests/test_contour.py::test_contour_manual_labels[png-False]",
"lib/matplotlib/tests/test_contour.py::test_negative_linestyles[solid]",
"lib/matplotlib/tests/test_contour.py::test_contour_legend_elements",
"lib/matplotlib/tests/test_contour.py::test_contour_linewidth[1.23-None-None-1.23]",
"lib/matplotlib/tests/test_contour.py::test_linestyles[solid]",
"lib/matplotlib/tests/test_contour.py::test_contour_no_args",
"lib/matplotlib/tests/test_contour.py::test_clabel_zorder[False-123-1234]",
"lib/matplotlib/tests/test_contour.py::test_algorithm_supports_corner_mask[mpl2014]",
"lib/matplotlib/tests/test_contour.py::test_contour_manual_labels[pdf-True]",
"lib/matplotlib/tests/test_contour.py::test_given_colors_levels_and_extends[png-False]",
"lib/matplotlib/tests/test_contour.py::test_contour_closed_line_loop[png-False]",
"lib/matplotlib/tests/test_contour.py::test_linestyles[dashed]",
"lib/matplotlib/tests/test_contour.py::test_contour_uneven[png-False]",
"lib/matplotlib/tests/test_contour.py::test_clabel_zorder[True-123-None]",
"lib/matplotlib/tests/test_contour.py::test_algorithm_supports_corner_mask[threaded]",
"lib/matplotlib/tests/test_contour.py::test_given_colors_levels_and_extends[png-True]",
"lib/matplotlib/tests/test_contour.py::test_contour_shape_error[args0-Length of x (9) must match number of columns in z (10)]",
"lib/matplotlib/tests/test_contour.py::test_linestyles[dashdot]",
"lib/matplotlib/tests/test_contour.py::test_all_algorithms[png-True]",
"lib/matplotlib/tests/test_contour.py::test_log_locator_levels[svg-True]",
"lib/matplotlib/tests/test_contour.py::test_negative_linestyles[dashed]",
"lib/matplotlib/tests/test_contour.py::test_contour_addlines[png-False]",
"lib/matplotlib/tests/test_contour.py::test_clabel_zorder[True-123-1234]",
"lib/matplotlib/tests/test_contour.py::test_contour_shape_error[args7-Input z must be 2D, not 3D]",
"lib/matplotlib/tests/test_contour.py::test_contour_no_valid_levels",
"lib/matplotlib/tests/test_contour.py::test_label_nonagg",
"lib/matplotlib/tests/test_contour.py::test_contour_linewidth[1.23-4.24-5.02-5.02]"
] |
[
"lib/matplotlib/tests/test_contour.py::test_contour_clip_path"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/users/next_whats_new/contour_clip_path.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/contour_clip_path.rst",
"metadata": "diff --git a/doc/users/next_whats_new/contour_clip_path.rst b/doc/users/next_whats_new/contour_clip_path.rst\nnew file mode 100644\nindex 000000000000..db4039a4fd70\n--- /dev/null\n+++ b/doc/users/next_whats_new/contour_clip_path.rst\n@@ -0,0 +1,24 @@\n+Clipping for contour plots\n+--------------------------\n+\n+`~.Axes.contour` and `~.Axes.contourf` now accept the *clip_path* parameter.\n+\n+.. plot::\n+ :include-source: true\n+\n+ import numpy as np\n+ import matplotlib.pyplot as plt\n+ import matplotlib.patches as mpatches\n+\n+ x = y = np.arange(-3.0, 3.01, 0.025)\n+ X, Y = np.meshgrid(x, y)\n+ Z1 = np.exp(-X**2 - Y**2)\n+ Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)\n+ Z = (Z1 - Z2) * 2\n+\n+ fig, ax = plt.subplots()\n+ patch = mpatches.RegularPolygon((0, 0), 5, radius=2,\n+ transform=ax.transData)\n+ ax.contourf(X, Y, Z, clip_path=patch)\n+\n+ plt.show()\n"
}
] |
diff --git a/doc/users/next_whats_new/contour_clip_path.rst b/doc/users/next_whats_new/contour_clip_path.rst
new file mode 100644
index 000000000000..db4039a4fd70
--- /dev/null
+++ b/doc/users/next_whats_new/contour_clip_path.rst
@@ -0,0 +1,24 @@
+Clipping for contour plots
+--------------------------
+
+`~.Axes.contour` and `~.Axes.contourf` now accept the *clip_path* parameter.
+
+.. plot::
+ :include-source: true
+
+ import numpy as np
+ import matplotlib.pyplot as plt
+ import matplotlib.patches as mpatches
+
+ x = y = np.arange(-3.0, 3.01, 0.025)
+ X, Y = np.meshgrid(x, y)
+ Z1 = np.exp(-X**2 - Y**2)
+ Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
+ Z = (Z1 - Z2) * 2
+
+ fig, ax = plt.subplots()
+ patch = mpatches.RegularPolygon((0, 0), 5, radius=2,
+ transform=ax.transData)
+ ax.contourf(X, Y, Z, clip_path=patch)
+
+ plt.show()
|
matplotlib/matplotlib
|
matplotlib__matplotlib-24257
|
https://github.com/matplotlib/matplotlib/pull/24257
|
diff --git a/doc/api/next_api_changes/development/24257-AL.rst b/doc/api/next_api_changes/development/24257-AL.rst
new file mode 100644
index 000000000000..584420df8fd7
--- /dev/null
+++ b/doc/api/next_api_changes/development/24257-AL.rst
@@ -0,0 +1,2 @@
+importlib_resources>=2.3.0 is now required on Python<3.10
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
diff --git a/doc/devel/dependencies.rst b/doc/devel/dependencies.rst
index fb76857898a4..365c062364e2 100644
--- a/doc/devel/dependencies.rst
+++ b/doc/devel/dependencies.rst
@@ -26,6 +26,9 @@ reference.
* `Pillow <https://pillow.readthedocs.io/en/latest/>`_ (>= 6.2)
* `pyparsing <https://pypi.org/project/pyparsing/>`_ (>= 2.3.1)
* `setuptools <https://setuptools.readthedocs.io/en/latest/>`_
+* `pyparsing <https://pypi.org/project/pyparsing/>`_ (>= 2.3.1)
+* `importlib-resources <https://pypi.org/project/importlib-resources/>`_
+ (>= 3.2.0; only required on Python < 3.10)
.. _optional_dependencies:
diff --git a/doc/users/next_whats_new/styles_from_packages.rst b/doc/users/next_whats_new/styles_from_packages.rst
new file mode 100644
index 000000000000..d129bb356fa7
--- /dev/null
+++ b/doc/users/next_whats_new/styles_from_packages.rst
@@ -0,0 +1,11 @@
+Style files can be imported from third-party packages
+-----------------------------------------------------
+
+Third-party packages can now distribute style files that are globally available
+as follows. Assume that a package is importable as ``import mypackage``, with
+a ``mypackage/__init__.py`` module. Then a ``mypackage/presentation.mplstyle``
+style sheet can be used as ``plt.style.use("mypackage.presentation")``.
+
+The implementation does not actually import ``mypackage``, making this process
+safe against possible import-time side effects. Subpackages (e.g.
+``dotted.package.name``) are also supported.
diff --git a/environment.yml b/environment.yml
index 28ff3a1b2c34..c9b7aa610720 100644
--- a/environment.yml
+++ b/environment.yml
@@ -12,6 +12,7 @@ dependencies:
- contourpy>=1.0.1
- cycler>=0.10.0
- fonttools>=4.22.0
+ - importlib-resources>=3.2.0
- kiwisolver>=1.0.1
- numpy>=1.19
- pillow>=6.2
diff --git a/lib/matplotlib/style/core.py b/lib/matplotlib/style/core.py
index 646b39dcc5df..ed5cd4f63bc5 100644
--- a/lib/matplotlib/style/core.py
+++ b/lib/matplotlib/style/core.py
@@ -15,10 +15,18 @@
import logging
import os
from pathlib import Path
+import sys
import warnings
+if sys.version_info >= (3, 10):
+ import importlib.resources as importlib_resources
+else:
+ # Even though Py3.9 has importlib.resources, it doesn't properly handle
+ # modules added in sys.path.
+ import importlib_resources
+
import matplotlib as mpl
-from matplotlib import _api, _docstring, rc_params_from_file, rcParamsDefault
+from matplotlib import _api, _docstring, _rc_params_in_file, rcParamsDefault
_log = logging.getLogger(__name__)
@@ -64,23 +72,6 @@
"directly use the seaborn API instead.")
-def _remove_blacklisted_style_params(d, warn=True):
- o = {}
- for key in d: # prevent triggering RcParams.__getitem__('backend')
- if key in STYLE_BLACKLIST:
- if warn:
- _api.warn_external(
- f"Style includes a parameter, {key!r}, that is not "
- "related to style. Ignoring this parameter.")
- else:
- o[key] = d[key]
- return o
-
-
-def _apply_style(d, warn=True):
- mpl.rcParams.update(_remove_blacklisted_style_params(d, warn=warn))
-
-
@_docstring.Substitution(
"\n".join(map("- {}".format, sorted(STYLE_BLACKLIST, key=str.lower)))
)
@@ -99,20 +90,28 @@ def use(style):
Parameters
----------
style : str, dict, Path or list
- A style specification. Valid options are:
- +------+-------------------------------------------------------------+
- | str | The name of a style or a path/URL to a style file. For a |
- | | list of available style names, see `.style.available`. |
- +------+-------------------------------------------------------------+
- | dict | Dictionary with valid key/value pairs for |
- | | `matplotlib.rcParams`. |
- +------+-------------------------------------------------------------+
- | Path | A path-like object which is a path to a style file. |
- +------+-------------------------------------------------------------+
- | list | A list of style specifiers (str, Path or dict) applied from |
- | | first to last in the list. |
- +------+-------------------------------------------------------------+
+ A style specification.
+
+ - If a str, this can be one of the style names in `.style.available`
+ (a builtin style or a style installed in the user library path).
+
+ This can also be a dotted name of the form "package.style_name"; in
+ that case, "package" should be an importable Python package name,
+ e.g. at ``/path/to/package/__init__.py``; the loaded style file is
+ ``/path/to/package/style_name.mplstyle``. (Style files in
+ subpackages are likewise supported.)
+
+ This can also be the path or URL to a style file, which gets loaded
+ by `.rc_params_from_file`.
+
+ - If a dict, this is a mapping of key/value pairs for `.rcParams`.
+
+ - If a Path, this is the path to a style file, which gets loaded by
+ `.rc_params_from_file`.
+
+ - If a list, this is a list of style specifiers (str, Path or dict),
+ which get applied from first to last in the list.
Notes
-----
@@ -129,33 +128,52 @@ def use(style):
style_alias = {'mpl20': 'default', 'mpl15': 'classic'}
- def fix_style(s):
- if isinstance(s, str):
- s = style_alias.get(s, s)
- if s in _DEPRECATED_SEABORN_STYLES:
+ for style in styles:
+ if isinstance(style, str):
+ style = style_alias.get(style, style)
+ if style in _DEPRECATED_SEABORN_STYLES:
_api.warn_deprecated("3.6", message=_DEPRECATED_SEABORN_MSG)
- s = _DEPRECATED_SEABORN_STYLES[s]
- return s
-
- for style in map(fix_style, styles):
- if not isinstance(style, (str, Path)):
- _apply_style(style)
- elif style == 'default':
- # Deprecation warnings were already handled when creating
- # rcParamsDefault, no need to reemit them here.
- with _api.suppress_matplotlib_deprecation_warning():
- _apply_style(rcParamsDefault, warn=False)
- elif style in library:
- _apply_style(library[style])
- else:
+ style = _DEPRECATED_SEABORN_STYLES[style]
+ if style == "default":
+ # Deprecation warnings were already handled when creating
+ # rcParamsDefault, no need to reemit them here.
+ with _api.suppress_matplotlib_deprecation_warning():
+ # don't trigger RcParams.__getitem__('backend')
+ style = {k: rcParamsDefault[k] for k in rcParamsDefault
+ if k not in STYLE_BLACKLIST}
+ elif style in library:
+ style = library[style]
+ elif "." in style:
+ pkg, _, name = style.rpartition(".")
+ try:
+ path = (importlib_resources.files(pkg)
+ / f"{name}.{STYLE_EXTENSION}")
+ style = _rc_params_in_file(path)
+ except (ModuleNotFoundError, IOError) as exc:
+ # There is an ambiguity whether a dotted name refers to a
+ # package.style_name or to a dotted file path. Currently,
+ # we silently try the first form and then the second one;
+ # in the future, we may consider forcing file paths to
+ # either use Path objects or be prepended with "./" and use
+ # the slash as marker for file paths.
+ pass
+ if isinstance(style, (str, Path)):
try:
- rc = rc_params_from_file(style, use_default_template=False)
- _apply_style(rc)
+ style = _rc_params_in_file(style)
except IOError as err:
raise IOError(
- "{!r} not found in the style library and input is not a "
- "valid URL or path; see `style.available` for list of "
- "available styles".format(style)) from err
+ f"{style!r} is not a valid package style, path of style "
+ f"file, URL of style file, or library style name (library "
+ f"styles are listed in `style.available`)") from err
+ filtered = {}
+ for k in style: # don't trigger RcParams.__getitem__('backend')
+ if k in STYLE_BLACKLIST:
+ _api.warn_external(
+ f"Style includes a parameter, {k!r}, that is not "
+ f"related to style. Ignoring this parameter.")
+ else:
+ filtered[k] = style[k]
+ mpl.rcParams.update(filtered)
@contextlib.contextmanager
@@ -205,8 +223,7 @@ def read_style_directory(style_dir):
styles = dict()
for path in Path(style_dir).glob(f"*.{STYLE_EXTENSION}"):
with warnings.catch_warnings(record=True) as warns:
- styles[path.stem] = rc_params_from_file(
- path, use_default_template=False)
+ styles[path.stem] = _rc_params_in_file(path)
for w in warns:
_log.warning('In %s: %s', path, w.message)
return styles
diff --git a/setup.py b/setup.py
index 365de0c0b5a2..2f1fb84f8cc6 100644
--- a/setup.py
+++ b/setup.py
@@ -334,6 +334,11 @@ def make_release_tree(self, base_dir, files):
os.environ.get("CIBUILDWHEEL", "0") != "1"
) else []
),
+ extras_require={
+ ':python_version<"3.10"': [
+ "importlib-resources>=3.2.0",
+ ],
+ },
use_scm_version={
"version_scheme": "release-branch-semver",
"local_scheme": "node-and-date",
diff --git a/tutorials/introductory/customizing.py b/tutorials/introductory/customizing.py
index ea6b501e99ea..10fc21d2187b 100644
--- a/tutorials/introductory/customizing.py
+++ b/tutorials/introductory/customizing.py
@@ -9,9 +9,9 @@
There are three ways to customize Matplotlib:
- 1. :ref:`Setting rcParams at runtime<customizing-with-dynamic-rc-settings>`.
- 2. :ref:`Using style sheets<customizing-with-style-sheets>`.
- 3. :ref:`Changing your matplotlibrc file<customizing-with-matplotlibrc-files>`.
+1. :ref:`Setting rcParams at runtime<customizing-with-dynamic-rc-settings>`.
+2. :ref:`Using style sheets<customizing-with-style-sheets>`.
+3. :ref:`Changing your matplotlibrc file<customizing-with-matplotlibrc-files>`.
Setting rcParams at runtime takes precedence over style sheets, style
sheets take precedence over :file:`matplotlibrc` files.
@@ -137,6 +137,17 @@ def plotting_function():
# >>> import matplotlib.pyplot as plt
# >>> plt.style.use('./images/presentation.mplstyle')
#
+#
+# Distributing styles
+# -------------------
+#
+# You can include style sheets into standard importable Python packages (which
+# can be e.g. distributed on PyPI). If your package is importable as
+# ``import mypackage``, with a ``mypackage/__init__.py`` module, and you add
+# a ``mypackage/presentation.mplstyle`` style sheet, then it can be used as
+# ``plt.style.use("mypackage.presentation")``. Subpackages (e.g.
+# ``dotted.package.name``) are also supported.
+#
# Alternatively, you can make your style known to Matplotlib by placing
# your ``<style-name>.mplstyle`` file into ``mpl_configdir/stylelib``. You
# can then load your custom style sheet with a call to
|
diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml
index 020f09df4010..eddb14be0bc6 100644
--- a/.github/workflows/tests.yml
+++ b/.github/workflows/tests.yml
@@ -162,8 +162,8 @@ jobs:
# Install dependencies from PyPI.
python -m pip install --upgrade $PRE \
- 'contourpy>=1.0.1' cycler fonttools kiwisolver numpy packaging \
- pillow pyparsing python-dateutil setuptools-scm \
+ 'contourpy>=1.0.1' cycler fonttools kiwisolver importlib_resources \
+ numpy packaging pillow pyparsing python-dateutil setuptools-scm \
-r requirements/testing/all.txt \
${{ matrix.extra-requirements }}
diff --git a/lib/matplotlib/tests/test_style.py b/lib/matplotlib/tests/test_style.py
index c788c45920ae..7d1ed94ea236 100644
--- a/lib/matplotlib/tests/test_style.py
+++ b/lib/matplotlib/tests/test_style.py
@@ -190,3 +190,18 @@ def test_deprecated_seaborn_styles():
def test_up_to_date_blacklist():
assert mpl.style.core.STYLE_BLACKLIST <= {*mpl.rcsetup._validators}
+
+
+def test_style_from_module(tmp_path, monkeypatch):
+ monkeypatch.syspath_prepend(tmp_path)
+ monkeypatch.chdir(tmp_path)
+ pkg_path = tmp_path / "mpl_test_style_pkg"
+ pkg_path.mkdir()
+ (pkg_path / "test_style.mplstyle").write_text(
+ "lines.linewidth: 42", encoding="utf-8")
+ pkg_path.with_suffix(".mplstyle").write_text(
+ "lines.linewidth: 84", encoding="utf-8")
+ mpl.style.use("mpl_test_style_pkg.test_style")
+ assert mpl.rcParams["lines.linewidth"] == 42
+ mpl.style.use("mpl_test_style_pkg.mplstyle")
+ assert mpl.rcParams["lines.linewidth"] == 84
diff --git a/requirements/testing/minver.txt b/requirements/testing/minver.txt
index d932b0aa34e7..82301e900f52 100644
--- a/requirements/testing/minver.txt
+++ b/requirements/testing/minver.txt
@@ -3,6 +3,7 @@
contourpy==1.0.1
cycler==0.10
kiwisolver==1.0.1
+importlib-resources==3.2.0
numpy==1.19.0
packaging==20.0
pillow==6.2.1
|
[
{
"path": "doc/api/next_api_changes/development/24257-AL.rst",
"old_path": "/dev/null",
"new_path": "b/doc/api/next_api_changes/development/24257-AL.rst",
"metadata": "diff --git a/doc/api/next_api_changes/development/24257-AL.rst b/doc/api/next_api_changes/development/24257-AL.rst\nnew file mode 100644\nindex 000000000000..584420df8fd7\n--- /dev/null\n+++ b/doc/api/next_api_changes/development/24257-AL.rst\n@@ -0,0 +1,2 @@\n+importlib_resources>=2.3.0 is now required on Python<3.10\n+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n"
},
{
"path": "doc/devel/dependencies.rst",
"old_path": "a/doc/devel/dependencies.rst",
"new_path": "b/doc/devel/dependencies.rst",
"metadata": "diff --git a/doc/devel/dependencies.rst b/doc/devel/dependencies.rst\nindex fb76857898a4..365c062364e2 100644\n--- a/doc/devel/dependencies.rst\n+++ b/doc/devel/dependencies.rst\n@@ -26,6 +26,9 @@ reference.\n * `Pillow <https://pillow.readthedocs.io/en/latest/>`_ (>= 6.2)\n * `pyparsing <https://pypi.org/project/pyparsing/>`_ (>= 2.3.1)\n * `setuptools <https://setuptools.readthedocs.io/en/latest/>`_\n+* `pyparsing <https://pypi.org/project/pyparsing/>`_ (>= 2.3.1)\n+* `importlib-resources <https://pypi.org/project/importlib-resources/>`_\n+ (>= 3.2.0; only required on Python < 3.10)\n \n \n .. _optional_dependencies:\n"
},
{
"path": "doc/users/next_whats_new/styles_from_packages.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/styles_from_packages.rst",
"metadata": "diff --git a/doc/users/next_whats_new/styles_from_packages.rst b/doc/users/next_whats_new/styles_from_packages.rst\nnew file mode 100644\nindex 000000000000..d129bb356fa7\n--- /dev/null\n+++ b/doc/users/next_whats_new/styles_from_packages.rst\n@@ -0,0 +1,11 @@\n+Style files can be imported from third-party packages\n+-----------------------------------------------------\n+\n+Third-party packages can now distribute style files that are globally available\n+as follows. Assume that a package is importable as ``import mypackage``, with\n+a ``mypackage/__init__.py`` module. Then a ``mypackage/presentation.mplstyle``\n+style sheet can be used as ``plt.style.use(\"mypackage.presentation\")``.\n+\n+The implementation does not actually import ``mypackage``, making this process\n+safe against possible import-time side effects. Subpackages (e.g.\n+``dotted.package.name``) are also supported.\n"
}
] |
3.5
|
aca6e9d5e98811ca37c442217914b15e78127c89
|
[
"lib/matplotlib/tests/test_style.py::test_use",
"lib/matplotlib/tests/test_style.py::test_available",
"lib/matplotlib/tests/test_style.py::test_invalid_rc_warning_includes_filename",
"lib/matplotlib/tests/test_style.py::test_context_with_union_of_dict_and_namedstyle",
"lib/matplotlib/tests/test_style.py::test_context_with_dict_after_namedstyle",
"lib/matplotlib/tests/test_style.py::test_xkcd_cm",
"lib/matplotlib/tests/test_style.py::test_alias[mpl20]",
"lib/matplotlib/tests/test_style.py::test_alias[mpl15]",
"lib/matplotlib/tests/test_style.py::test_single_path",
"lib/matplotlib/tests/test_style.py::test_context",
"lib/matplotlib/tests/test_style.py::test_context_with_dict",
"lib/matplotlib/tests/test_style.py::test_use_url",
"lib/matplotlib/tests/test_style.py::test_deprecated_seaborn_styles",
"lib/matplotlib/tests/test_style.py::test_context_with_dict_before_namedstyle",
"lib/matplotlib/tests/test_style.py::test_up_to_date_blacklist",
"lib/matplotlib/tests/test_style.py::test_context_with_badparam",
"lib/matplotlib/tests/test_style.py::test_xkcd_no_cm"
] |
[
"lib/matplotlib/tests/test_style.py::test_style_from_module"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/api/next_api_changes/development/<PRID>-AL.rst",
"old_path": "/dev/null",
"new_path": "b/doc/api/next_api_changes/development/<PRID>-AL.rst",
"metadata": "diff --git a/doc/api/next_api_changes/development/<PRID>-AL.rst b/doc/api/next_api_changes/development/<PRID>-AL.rst\nnew file mode 100644\nindex 000000000000..584420df8fd7\n--- /dev/null\n+++ b/doc/api/next_api_changes/development/<PRID>-AL.rst\n@@ -0,0 +1,2 @@\n+importlib_resources>=2.3.0 is now required on Python<3.10\n+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n"
},
{
"path": "doc/devel/dependencies.rst",
"old_path": "a/doc/devel/dependencies.rst",
"new_path": "b/doc/devel/dependencies.rst",
"metadata": "diff --git a/doc/devel/dependencies.rst b/doc/devel/dependencies.rst\nindex fb76857898a4..365c062364e2 100644\n--- a/doc/devel/dependencies.rst\n+++ b/doc/devel/dependencies.rst\n@@ -26,6 +26,9 @@ reference.\n * `Pillow <https://pillow.readthedocs.io/en/latest/>`_ (>= 6.2)\n * `pyparsing <https://pypi.org/project/pyparsing/>`_ (>= 2.3.1)\n * `setuptools <https://setuptools.readthedocs.io/en/latest/>`_\n+* `pyparsing <https://pypi.org/project/pyparsing/>`_ (>= 2.3.1)\n+* `importlib-resources <https://pypi.org/project/importlib-resources/>`_\n+ (>= 3.2.0; only required on Python < 3.10)\n \n \n .. _optional_dependencies:\n"
},
{
"path": "doc/users/next_whats_new/styles_from_packages.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/styles_from_packages.rst",
"metadata": "diff --git a/doc/users/next_whats_new/styles_from_packages.rst b/doc/users/next_whats_new/styles_from_packages.rst\nnew file mode 100644\nindex 000000000000..d129bb356fa7\n--- /dev/null\n+++ b/doc/users/next_whats_new/styles_from_packages.rst\n@@ -0,0 +1,11 @@\n+Style files can be imported from third-party packages\n+-----------------------------------------------------\n+\n+Third-party packages can now distribute style files that are globally available\n+as follows. Assume that a package is importable as ``import mypackage``, with\n+a ``mypackage/__init__.py`` module. Then a ``mypackage/presentation.mplstyle``\n+style sheet can be used as ``plt.style.use(\"mypackage.presentation\")``.\n+\n+The implementation does not actually import ``mypackage``, making this process\n+safe against possible import-time side effects. Subpackages (e.g.\n+``dotted.package.name``) are also supported.\n"
}
] |
diff --git a/doc/api/next_api_changes/development/<PRID>-AL.rst b/doc/api/next_api_changes/development/<PRID>-AL.rst
new file mode 100644
index 000000000000..584420df8fd7
--- /dev/null
+++ b/doc/api/next_api_changes/development/<PRID>-AL.rst
@@ -0,0 +1,2 @@
+importlib_resources>=2.3.0 is now required on Python<3.10
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
diff --git a/doc/devel/dependencies.rst b/doc/devel/dependencies.rst
index fb76857898a4..365c062364e2 100644
--- a/doc/devel/dependencies.rst
+++ b/doc/devel/dependencies.rst
@@ -26,6 +26,9 @@ reference.
* `Pillow <https://pillow.readthedocs.io/en/latest/>`_ (>= 6.2)
* `pyparsing <https://pypi.org/project/pyparsing/>`_ (>= 2.3.1)
* `setuptools <https://setuptools.readthedocs.io/en/latest/>`_
+* `pyparsing <https://pypi.org/project/pyparsing/>`_ (>= 2.3.1)
+* `importlib-resources <https://pypi.org/project/importlib-resources/>`_
+ (>= 3.2.0; only required on Python < 3.10)
.. _optional_dependencies:
diff --git a/doc/users/next_whats_new/styles_from_packages.rst b/doc/users/next_whats_new/styles_from_packages.rst
new file mode 100644
index 000000000000..d129bb356fa7
--- /dev/null
+++ b/doc/users/next_whats_new/styles_from_packages.rst
@@ -0,0 +1,11 @@
+Style files can be imported from third-party packages
+-----------------------------------------------------
+
+Third-party packages can now distribute style files that are globally available
+as follows. Assume that a package is importable as ``import mypackage``, with
+a ``mypackage/__init__.py`` module. Then a ``mypackage/presentation.mplstyle``
+style sheet can be used as ``plt.style.use("mypackage.presentation")``.
+
+The implementation does not actually import ``mypackage``, making this process
+safe against possible import-time side effects. Subpackages (e.g.
+``dotted.package.name``) are also supported.
|
matplotlib/matplotlib
|
matplotlib__matplotlib-25542
|
https://github.com/matplotlib/matplotlib/pull/25542
|
diff --git a/doc/users/next_whats_new/multiplelocator_offset.rst b/doc/users/next_whats_new/multiplelocator_offset.rst
new file mode 100644
index 000000000000..863fdb3c4d7e
--- /dev/null
+++ b/doc/users/next_whats_new/multiplelocator_offset.rst
@@ -0,0 +1,17 @@
+``offset`` parameter for MultipleLocator
+----------------------------------------
+
+An *offset* may now be specified to shift all the ticks by the given value.
+
+.. plot::
+ :include-source: true
+
+ import matplotlib.pyplot as plt
+ import matplotlib.ticker as mticker
+
+ _, ax = plt.subplots()
+ ax.plot(range(10))
+ locator = mticker.MultipleLocator(base=3, offset=0.3)
+ ax.xaxis.set_major_locator(locator)
+
+ plt.show()
diff --git a/galleries/examples/ticks/tick-locators.py b/galleries/examples/ticks/tick-locators.py
index e634e022173c..6cf4afaf22d7 100644
--- a/galleries/examples/ticks/tick-locators.py
+++ b/galleries/examples/ticks/tick-locators.py
@@ -37,8 +37,8 @@ def setup(ax, title):
axs[0].xaxis.set_minor_locator(ticker.NullLocator())
# Multiple Locator
-setup(axs[1], title="MultipleLocator(0.5)")
-axs[1].xaxis.set_major_locator(ticker.MultipleLocator(0.5))
+setup(axs[1], title="MultipleLocator(0.5, offset=0.2)")
+axs[1].xaxis.set_major_locator(ticker.MultipleLocator(0.5, offset=0.2))
axs[1].xaxis.set_minor_locator(ticker.MultipleLocator(0.1))
# Fixed Locator
@@ -53,7 +53,7 @@ def setup(ax, title):
# Index Locator
setup(axs[4], title="IndexLocator(base=0.5, offset=0.25)")
-axs[4].plot(range(0, 5), [0]*5, color='white')
+axs[4].plot([0]*5, color='white')
axs[4].xaxis.set_major_locator(ticker.IndexLocator(base=0.5, offset=0.25))
# Auto Locator
diff --git a/lib/matplotlib/ticker.py b/lib/matplotlib/ticker.py
index bf059567f5fe..0877e58c5fe7 100644
--- a/lib/matplotlib/ticker.py
+++ b/lib/matplotlib/ticker.py
@@ -1831,17 +1831,41 @@ def view_limits(self, vmin, vmax):
class MultipleLocator(Locator):
"""
- Set a tick on each integer multiple of the *base* within the view
- interval.
+ Set a tick on each integer multiple of the *base* plus an *offset* within
+ the view interval.
"""
- def __init__(self, base=1.0):
+ def __init__(self, base=1.0, offset=0.0):
+ """
+ Parameters
+ ----------
+ base : float > 0
+ Interval between ticks.
+ offset : float
+ Value added to each multiple of *base*.
+
+ .. versionadded:: 3.8
+ """
self._edge = _Edge_integer(base, 0)
+ self._offset = offset
- def set_params(self, base):
- """Set parameters within this locator."""
+ def set_params(self, base=None, offset=None):
+ """
+ Set parameters within this locator.
+
+ Parameters
+ ----------
+ base : float > 0
+ Interval between ticks.
+ offset : float
+ Value added to each multiple of *base*.
+
+ .. versionadded:: 3.8
+ """
if base is not None:
self._edge = _Edge_integer(base, 0)
+ if offset is not None:
+ self._offset = offset
def __call__(self):
"""Return the locations of the ticks."""
@@ -1852,19 +1876,20 @@ def tick_values(self, vmin, vmax):
if vmax < vmin:
vmin, vmax = vmax, vmin
step = self._edge.step
+ vmin -= self._offset
+ vmax -= self._offset
vmin = self._edge.ge(vmin) * step
n = (vmax - vmin + 0.001 * step) // step
- locs = vmin - step + np.arange(n + 3) * step
+ locs = vmin - step + np.arange(n + 3) * step + self._offset
return self.raise_if_exceeds(locs)
def view_limits(self, dmin, dmax):
"""
- Set the view limits to the nearest multiples of *base* that
- contain the data.
+ Set the view limits to the nearest tick values that contain the data.
"""
if mpl.rcParams['axes.autolimit_mode'] == 'round_numbers':
- vmin = self._edge.le(dmin) * self._edge.step
- vmax = self._edge.ge(dmax) * self._edge.step
+ vmin = self._edge.le(dmin - self._offset) * self._edge.step + self._offset
+ vmax = self._edge.ge(dmax - self._offset) * self._edge.step + self._offset
if vmin == vmax:
vmin -= 1
vmax += 1
diff --git a/lib/matplotlib/ticker.pyi b/lib/matplotlib/ticker.pyi
index e53a665432e2..1f4239ef2718 100644
--- a/lib/matplotlib/ticker.pyi
+++ b/lib/matplotlib/ticker.pyi
@@ -212,9 +212,8 @@ class LinearLocator(Locator):
) -> None: ...
class MultipleLocator(Locator):
- def __init__(self, base: float = ...) -> None: ...
- # Makes set_params `base` argument mandatory
- def set_params(self, base: float | None) -> None: ... # type: ignore[override]
+ def __init__(self, base: float = ..., offset: float = ...) -> None: ...
+ def set_params(self, base: float | None = ..., offset: float | None = ...) -> None: ...
def view_limits(self, dmin: float, dmax: float) -> tuple[float, float]: ...
class _Edge_integer:
|
diff --git a/lib/matplotlib/tests/test_ticker.py b/lib/matplotlib/tests/test_ticker.py
index 3d38df575f09..53224d373f80 100644
--- a/lib/matplotlib/tests/test_ticker.py
+++ b/lib/matplotlib/tests/test_ticker.py
@@ -63,6 +63,12 @@ def test_basic(self):
9.441, 12.588])
assert_almost_equal(loc.tick_values(-7, 10), test_value)
+ def test_basic_with_offset(self):
+ loc = mticker.MultipleLocator(base=3.147, offset=1.2)
+ test_value = np.array([-8.241, -5.094, -1.947, 1.2, 4.347, 7.494,
+ 10.641])
+ assert_almost_equal(loc.tick_values(-7, 10), test_value)
+
def test_view_limits(self):
"""
Test basic behavior of view limits.
@@ -80,6 +86,15 @@ def test_view_limits_round_numbers(self):
loc = mticker.MultipleLocator(base=3.147)
assert_almost_equal(loc.view_limits(-4, 4), (-6.294, 6.294))
+ def test_view_limits_round_numbers_with_offset(self):
+ """
+ Test that everything works properly with 'round_numbers' for auto
+ limit.
+ """
+ with mpl.rc_context({'axes.autolimit_mode': 'round_numbers'}):
+ loc = mticker.MultipleLocator(base=3.147, offset=1.3)
+ assert_almost_equal(loc.view_limits(-4, 4), (-4.994, 4.447))
+
def test_set_params(self):
"""
Create multiple locator with 0.7 base, and change it to something else.
@@ -88,6 +103,8 @@ def test_set_params(self):
mult = mticker.MultipleLocator(base=0.7)
mult.set_params(base=1.7)
assert mult._edge.step == 1.7
+ mult.set_params(offset=3)
+ assert mult._offset == 3
class TestAutoMinorLocator:
|
[
{
"path": "doc/users/next_whats_new/multiplelocator_offset.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/multiplelocator_offset.rst",
"metadata": "diff --git a/doc/users/next_whats_new/multiplelocator_offset.rst b/doc/users/next_whats_new/multiplelocator_offset.rst\nnew file mode 100644\nindex 000000000000..863fdb3c4d7e\n--- /dev/null\n+++ b/doc/users/next_whats_new/multiplelocator_offset.rst\n@@ -0,0 +1,17 @@\n+``offset`` parameter for MultipleLocator\n+----------------------------------------\n+\n+An *offset* may now be specified to shift all the ticks by the given value.\n+\n+.. plot::\n+ :include-source: true\n+\n+ import matplotlib.pyplot as plt\n+ import matplotlib.ticker as mticker\n+\n+ _, ax = plt.subplots()\n+ ax.plot(range(10))\n+ locator = mticker.MultipleLocator(base=3, offset=0.3)\n+ ax.xaxis.set_major_locator(locator)\n+\n+ plt.show()\n"
}
] |
3.7
|
7b821ce6b4a4474b1013435954c05c63574e3814
|
[
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[1000-100-1000]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_offset_value[-0.492-0.492-0]",
"lib/matplotlib/tests/test_ticker.py::TestPercentFormatter::test_basic[autodecimal, x<100%, display_range=8.4 (autodecimal test 2)]",
"lib/matplotlib/tests/test_ticker.py::TestMultipleLocator::test_view_limits_round_numbers",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.001-0.015-0.001]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_cursor_dummy_axis[0.0123-0.012]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_invalid[-0.1]",
"lib/matplotlib/tests/test_ticker.py::TestEngFormatter::test_params[True-1001-expected21]",
"lib/matplotlib/tests/test_ticker.py::TestAsinhLocator::test_linear_values",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_minor[lims6-expected_low_ticks6]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_format_data[0.1-1e-1]",
"lib/matplotlib/tests/test_ticker.py::TestFormatStrFormatter::test_basic",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_format_data_short[253]",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_nonsingular_ok[lims0]",
"lib/matplotlib/tests/test_ticker.py::TestLogLocator::test_tick_values_not_empty",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterMathtext::test_min_exponent[3-1000.0-$\\\\mathdefault{10^{3}}$]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.003141592654-100-0]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_variablelength[0.02005753653785041]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.003141592654-0.001-3.142e-3]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.1-0.001-1e-1]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[1000-0.015-1000]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_basic[0.001]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.01-0.001-1e-2]",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_nonsingular_ok[lims8]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_invalid[-1]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterMathtext::test_min_exponent[0-1-$\\\\mathdefault{10^{0}}$]",
"lib/matplotlib/tests/test_ticker.py::TestEngFormatter::test_params[False--1234.56789-expected0]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterExponent::test_basic[2.718281828459045-False-50-locs2-positions2-expected2]",
"lib/matplotlib/tests/test_ticker.py::TestEngFormatter::test_params[True--999.9999-expected19]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.3141592654-0.015-0.314]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_variablelength[0.9956983447069072]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_minor_vs_major[False-lims3-cases3]",
"lib/matplotlib/tests/test_ticker.py::TestPercentFormatter::test_latex[True-True-50\\\\{t}%]",
"lib/matplotlib/tests/test_ticker.py::TestMaxNLocator::test_basic[0.001-0.0001-expected1]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[1000-0.001-1000]",
"lib/matplotlib/tests/test_ticker.py::test_small_range_loglocator[9]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterExponent::test_basic[5.0-False-50-locs2-positions2-expected2]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterExponent::test_basic[5.0-False-10-locs1-positions1-expected1]",
"lib/matplotlib/tests/test_ticker.py::TestPercentFormatter::test_basic[decimals=0, x>100%]",
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"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[314.1592654-0.5-314.159]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_LogFormatter_call_tiny[1.1e-322]",
"lib/matplotlib/tests/test_ticker.py::TestAutoMinorLocator::test_additional[lim1-ref1]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_offset_value[0.000721-0.0007243-0.00072]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_cursor_dummy_axis[0.123-0.123]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_basic[1e-06]",
"lib/matplotlib/tests/test_ticker.py::TestPercentFormatter::test_latex[False-True-50\\\\\\\\\\\\{t\\\\}\\\\%]",
"lib/matplotlib/tests/test_ticker.py::TestAutoMinorLocator::test_number_of_minor_ticks_auto[lim0-ref0-False]",
"lib/matplotlib/tests/test_ticker.py::TestStrMethodFormatter::test_basic[{x:03d}-{pos:02d}-input1-002-01]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.003141592654-1000000.0-3.1e-3]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_LogFormatter_call_tiny[1e-322]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[31415.92654-0.015-31415.927]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_invalid[1.1]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[314.1592654-100-314.2]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterSciNotation::test_basic[2-1-$\\\\mathdefault{2^{0}}$]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.01-0.5-0.01]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[100000-5-100000]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_basic[0.0001]",
"lib/matplotlib/tests/test_ticker.py::TestLinearLocator::test_basic",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_offset_value[-1234001--1233999--1234000]",
"lib/matplotlib/tests/test_ticker.py::TestEngFormatter::test_params[True-987654.321-expected23]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_offset_value[5.99-6.01-6]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[100000-0.015-100000]"
] |
[
"lib/matplotlib/tests/test_ticker.py::TestMultipleLocator::test_set_params",
"lib/matplotlib/tests/test_ticker.py::TestMultipleLocator::test_basic_with_offset",
"lib/matplotlib/tests/test_ticker.py::TestMultipleLocator::test_view_limits_round_numbers_with_offset"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/users/next_whats_new/multiplelocator_offset.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/multiplelocator_offset.rst",
"metadata": "diff --git a/doc/users/next_whats_new/multiplelocator_offset.rst b/doc/users/next_whats_new/multiplelocator_offset.rst\nnew file mode 100644\nindex 000000000000..863fdb3c4d7e\n--- /dev/null\n+++ b/doc/users/next_whats_new/multiplelocator_offset.rst\n@@ -0,0 +1,17 @@\n+``offset`` parameter for MultipleLocator\n+----------------------------------------\n+\n+An *offset* may now be specified to shift all the ticks by the given value.\n+\n+.. plot::\n+ :include-source: true\n+\n+ import matplotlib.pyplot as plt\n+ import matplotlib.ticker as mticker\n+\n+ _, ax = plt.subplots()\n+ ax.plot(range(10))\n+ locator = mticker.MultipleLocator(base=3, offset=0.3)\n+ ax.xaxis.set_major_locator(locator)\n+\n+ plt.show()\n"
}
] |
diff --git a/doc/users/next_whats_new/multiplelocator_offset.rst b/doc/users/next_whats_new/multiplelocator_offset.rst
new file mode 100644
index 000000000000..863fdb3c4d7e
--- /dev/null
+++ b/doc/users/next_whats_new/multiplelocator_offset.rst
@@ -0,0 +1,17 @@
+``offset`` parameter for MultipleLocator
+----------------------------------------
+
+An *offset* may now be specified to shift all the ticks by the given value.
+
+.. plot::
+ :include-source: true
+
+ import matplotlib.pyplot as plt
+ import matplotlib.ticker as mticker
+
+ _, ax = plt.subplots()
+ ax.plot(range(10))
+ locator = mticker.MultipleLocator(base=3, offset=0.3)
+ ax.xaxis.set_major_locator(locator)
+
+ plt.show()
|
matplotlib/matplotlib
|
matplotlib__matplotlib-25779
|
https://github.com/matplotlib/matplotlib/pull/25779
|
diff --git a/doc/users/next_whats_new/get_vertices_co_vertices.rst b/doc/users/next_whats_new/get_vertices_co_vertices.rst
new file mode 100644
index 000000000000..98254a82ce63
--- /dev/null
+++ b/doc/users/next_whats_new/get_vertices_co_vertices.rst
@@ -0,0 +1,7 @@
+``Ellipse.get_vertices()``, ``Ellipse.get_co_vertices()``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+These methods return the coordinates of ellipse vertices of
+major and minor axis. Additionally, an example gallery demo is added which
+shows how to add an arrow to an ellipse showing a clockwise or counter-clockwise
+rotation of the ellipse. To place the arrow exactly on the ellipse,
+the coordinates of the vertices are used.
diff --git a/galleries/examples/shapes_and_collections/ellipse_arrow.py b/galleries/examples/shapes_and_collections/ellipse_arrow.py
new file mode 100644
index 000000000000..4bcdc016faa6
--- /dev/null
+++ b/galleries/examples/shapes_and_collections/ellipse_arrow.py
@@ -0,0 +1,53 @@
+"""
+===================================
+Ellipse with orientation arrow demo
+===================================
+
+This demo shows how to draw an ellipse with
+an orientation arrow (clockwise or counterclockwise).
+Compare this to the :doc:`Ellipse collection example
+</gallery/shapes_and_collections/ellipse_collection>`.
+"""
+
+import matplotlib.pyplot as plt
+
+from matplotlib.markers import MarkerStyle
+from matplotlib.patches import Ellipse
+from matplotlib.transforms import Affine2D
+
+# Create a figure and axis
+fig, ax = plt.subplots(subplot_kw={"aspect": "equal"})
+
+ellipse = Ellipse(
+ xy=(2, 4),
+ width=30,
+ height=20,
+ angle=35,
+ facecolor="none",
+ edgecolor="b"
+)
+ax.add_patch(ellipse)
+
+# Plot an arrow marker at the end point of minor axis
+vertices = ellipse.get_co_vertices()
+t = Affine2D().rotate_deg(ellipse.angle)
+ax.plot(
+ vertices[0][0],
+ vertices[0][1],
+ color="b",
+ marker=MarkerStyle(">", "full", t),
+ markersize=10
+)
+# Note: To reverse the orientation arrow, switch the marker type from > to <.
+
+plt.show()
+
+# %%
+#
+# .. admonition:: References
+#
+# The use of the following functions, methods, classes and modules is shown
+# in this example:
+#
+# - `matplotlib.patches`
+# - `matplotlib.patches.Ellipse`
diff --git a/lib/matplotlib/patches.py b/lib/matplotlib/patches.py
index 245bb7b777c8..ecf03ca4051b 100644
--- a/lib/matplotlib/patches.py
+++ b/lib/matplotlib/patches.py
@@ -1654,6 +1654,37 @@ def get_corners(self):
return self.get_patch_transform().transform(
[(-1, -1), (1, -1), (1, 1), (-1, 1)])
+ def _calculate_length_between_points(self, x0, y0, x1, y1):
+ return np.sqrt((x1 - x0)**2 + (y1 - y0)**2)
+
+ def get_vertices(self):
+ """
+ Return the vertices coordinates of the ellipse.
+
+ The definition can be found `here <https://en.wikipedia.org/wiki/Ellipse>`_
+
+ .. versionadded:: 3.8
+ """
+ if self.width < self.height:
+ ret = self.get_patch_transform().transform([(0, 1), (0, -1)])
+ else:
+ ret = self.get_patch_transform().transform([(1, 0), (-1, 0)])
+ return [tuple(x) for x in ret]
+
+ def get_co_vertices(self):
+ """
+ Return the co-vertices coordinates of the ellipse.
+
+ The definition can be found `here <https://en.wikipedia.org/wiki/Ellipse>`_
+
+ .. versionadded:: 3.8
+ """
+ if self.width < self.height:
+ ret = self.get_patch_transform().transform([(1, 0), (-1, 0)])
+ else:
+ ret = self.get_patch_transform().transform([(0, 1), (0, -1)])
+ return [tuple(x) for x in ret]
+
class Annulus(Patch):
"""
diff --git a/lib/matplotlib/patches.pyi b/lib/matplotlib/patches.pyi
index 1e70a1efc3be..e9302563083c 100644
--- a/lib/matplotlib/patches.pyi
+++ b/lib/matplotlib/patches.pyi
@@ -259,6 +259,10 @@ class Ellipse(Patch):
def get_corners(self) -> np.ndarray: ...
+ def get_vertices(self) -> list[tuple[float, float]]: ...
+ def get_co_vertices(self) -> list[tuple[float, float]]: ...
+
+
class Annulus(Patch):
a: float
b: float
|
diff --git a/lib/matplotlib/tests/test_patches.py b/lib/matplotlib/tests/test_patches.py
index b9e1db32d419..fd872bac98d4 100644
--- a/lib/matplotlib/tests/test_patches.py
+++ b/lib/matplotlib/tests/test_patches.py
@@ -104,6 +104,57 @@ def test_corner_center():
assert_almost_equal(ellipse.get_corners(), corners_rot)
+def test_ellipse_vertices():
+ # expect 0 for 0 ellipse width, height
+ ellipse = Ellipse(xy=(0, 0), width=0, height=0, angle=0)
+ assert_almost_equal(
+ ellipse.get_vertices(),
+ [(0.0, 0.0), (0.0, 0.0)],
+ )
+ assert_almost_equal(
+ ellipse.get_co_vertices(),
+ [(0.0, 0.0), (0.0, 0.0)],
+ )
+
+ ellipse = Ellipse(xy=(0, 0), width=2, height=1, angle=30)
+ assert_almost_equal(
+ ellipse.get_vertices(),
+ [
+ (
+ ellipse.center[0] + ellipse.width / 4 * np.sqrt(3),
+ ellipse.center[1] + ellipse.width / 4,
+ ),
+ (
+ ellipse.center[0] - ellipse.width / 4 * np.sqrt(3),
+ ellipse.center[1] - ellipse.width / 4,
+ ),
+ ],
+ )
+ assert_almost_equal(
+ ellipse.get_co_vertices(),
+ [
+ (
+ ellipse.center[0] - ellipse.height / 4,
+ ellipse.center[1] + ellipse.height / 4 * np.sqrt(3),
+ ),
+ (
+ ellipse.center[0] + ellipse.height / 4,
+ ellipse.center[1] - ellipse.height / 4 * np.sqrt(3),
+ ),
+ ],
+ )
+ v1, v2 = np.array(ellipse.get_vertices())
+ np.testing.assert_almost_equal((v1 + v2) / 2, ellipse.center)
+ v1, v2 = np.array(ellipse.get_co_vertices())
+ np.testing.assert_almost_equal((v1 + v2) / 2, ellipse.center)
+
+ ellipse = Ellipse(xy=(2.252, -10.859), width=2.265, height=1.98, angle=68.78)
+ v1, v2 = np.array(ellipse.get_vertices())
+ np.testing.assert_almost_equal((v1 + v2) / 2, ellipse.center)
+ v1, v2 = np.array(ellipse.get_co_vertices())
+ np.testing.assert_almost_equal((v1 + v2) / 2, ellipse.center)
+
+
def test_rotate_rect():
loc = np.asarray([1.0, 2.0])
width = 2
|
[
{
"path": "doc/users/next_whats_new/get_vertices_co_vertices.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/get_vertices_co_vertices.rst",
"metadata": "diff --git a/doc/users/next_whats_new/get_vertices_co_vertices.rst b/doc/users/next_whats_new/get_vertices_co_vertices.rst\nnew file mode 100644\nindex 000000000000..98254a82ce63\n--- /dev/null\n+++ b/doc/users/next_whats_new/get_vertices_co_vertices.rst\n@@ -0,0 +1,7 @@\n+``Ellipse.get_vertices()``, ``Ellipse.get_co_vertices()``\n+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n+These methods return the coordinates of ellipse vertices of\n+major and minor axis. Additionally, an example gallery demo is added which\n+shows how to add an arrow to an ellipse showing a clockwise or counter-clockwise\n+rotation of the ellipse. To place the arrow exactly on the ellipse,\n+the coordinates of the vertices are used.\n"
}
] |
3.7
|
06305a2f5dc589888697b3b909859103b8259153
|
[
"lib/matplotlib/tests/test_patches.py::test_patch_alpha_override[pdf]",
"lib/matplotlib/tests/test_patches.py::test_clip_to_bbox[png]",
"lib/matplotlib/tests/test_patches.py::test_contains_points",
"lib/matplotlib/tests/test_patches.py::test_units_rectangle[png]",
"lib/matplotlib/tests/test_patches.py::test_connection_patch[png]",
"lib/matplotlib/tests/test_patches.py::test_wedge_range[png]",
"lib/matplotlib/tests/test_patches.py::test_datetime_datetime_fails",
"lib/matplotlib/tests/test_patches.py::test_fancyarrow_shape_error",
"lib/matplotlib/tests/test_patches.py::test_datetime_rectangle",
"lib/matplotlib/tests/test_patches.py::test_boxstyle_errors[Round,foo-Incorrect style argument: 'Round,foo']",
"lib/matplotlib/tests/test_patches.py::test_negative_rect",
"lib/matplotlib/tests/test_patches.py::test_multi_color_hatch[pdf]",
"lib/matplotlib/tests/test_patches.py::test_connection_patch_fig[png]",
"lib/matplotlib/tests/test_patches.py::test_autoscale_arc[svg]",
"lib/matplotlib/tests/test_patches.py::test_patch_alpha_override[svg]",
"lib/matplotlib/tests/test_patches.py::test_large_arc[svg]",
"lib/matplotlib/tests/test_patches.py::test_patch_linestyle_accents",
"lib/matplotlib/tests/test_patches.py::test_rotated_arcs[svg]",
"lib/matplotlib/tests/test_patches.py::test_patch_custom_linestyle[pdf]",
"lib/matplotlib/tests/test_patches.py::test_modifying_arc[svg]",
"lib/matplotlib/tests/test_patches.py::test_Polygon_close",
"lib/matplotlib/tests/test_patches.py::test_modifying_arc[png]",
"lib/matplotlib/tests/test_patches.py::test_autoscale_arc[png]",
"lib/matplotlib/tests/test_patches.py::test_patch_alpha_coloring[svg]",
"lib/matplotlib/tests/test_patches.py::test_color_override_warning[edgecolor]",
"lib/matplotlib/tests/test_patches.py::test_rotate_rect",
"lib/matplotlib/tests/test_patches.py::test_patch_linestyle_none[png]",
"lib/matplotlib/tests/test_patches.py::test_annulus_setters[png]",
"lib/matplotlib/tests/test_patches.py::test_patch_str",
"lib/matplotlib/tests/test_patches.py::test_multi_color_hatch[svg]",
"lib/matplotlib/tests/test_patches.py::test_patch_custom_linestyle[svg]",
"lib/matplotlib/tests/test_patches.py::test_dash_offset_patch_draw[png]",
"lib/matplotlib/tests/test_patches.py::test_clip_to_bbox[svg]",
"lib/matplotlib/tests/test_patches.py::test_multi_color_hatch[png]",
"lib/matplotlib/tests/test_patches.py::test_fancyarrow_setdata",
"lib/matplotlib/tests/test_patches.py::test_patch_alpha_coloring[png]",
"lib/matplotlib/tests/test_patches.py::test_wedge_range[pdf]",
"lib/matplotlib/tests/test_patches.py::test_wedge_range[svg]",
"lib/matplotlib/tests/test_patches.py::test_corner_center",
"lib/matplotlib/tests/test_patches.py::test_default_linestyle",
"lib/matplotlib/tests/test_patches.py::test_empty_verts",
"lib/matplotlib/tests/test_patches.py::test_patch_alpha_override[png]",
"lib/matplotlib/tests/test_patches.py::test_default_capstyle",
"lib/matplotlib/tests/test_patches.py::test_contains_point",
"lib/matplotlib/tests/test_patches.py::test_modifying_arc[pdf]",
"lib/matplotlib/tests/test_patches.py::test_color_override_warning[facecolor]",
"lib/matplotlib/tests/test_patches.py::test_default_joinstyle",
"lib/matplotlib/tests/test_patches.py::test_arc_in_collection[pdf]",
"lib/matplotlib/tests/test_patches.py::test_wedge_movement",
"lib/matplotlib/tests/test_patches.py::test_annulus[png]",
"lib/matplotlib/tests/test_patches.py::test_clip_to_bbox[pdf]",
"lib/matplotlib/tests/test_patches.py::test_arc_in_collection[svg]",
"lib/matplotlib/tests/test_patches.py::test_degenerate_polygon",
"lib/matplotlib/tests/test_patches.py::test_arc_in_collection[png]",
"lib/matplotlib/tests/test_patches.py::test_shadow[png]",
"lib/matplotlib/tests/test_patches.py::test_rotate_rect_draw[png]",
"lib/matplotlib/tests/test_patches.py::test_patch_color_none",
"lib/matplotlib/tests/test_patches.py::test_arc_in_collection[eps]",
"lib/matplotlib/tests/test_patches.py::test_default_antialiased",
"lib/matplotlib/tests/test_patches.py::test_annulus_setters2[png]",
"lib/matplotlib/tests/test_patches.py::test_fancyarrow_units",
"lib/matplotlib/tests/test_patches.py::test_patch_custom_linestyle[png]",
"lib/matplotlib/tests/test_patches.py::test_patch_alpha_coloring[pdf]",
"lib/matplotlib/tests/test_patches.py::test_boxstyle_errors[foo-Unknown style: 'foo']",
"lib/matplotlib/tests/test_patches.py::test_modifying_arc[eps]"
] |
[
"lib/matplotlib/tests/test_patches.py::test_ellipse_vertices"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": [
{
"type": "file",
"name": "galleries/examples/shapes_and_collections/ellipse_arrow.py"
}
]
}
|
[
{
"path": "doc/users/next_whats_new/get_vertices_co_vertices.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/get_vertices_co_vertices.rst",
"metadata": "diff --git a/doc/users/next_whats_new/get_vertices_co_vertices.rst b/doc/users/next_whats_new/get_vertices_co_vertices.rst\nnew file mode 100644\nindex 000000000000..98254a82ce63\n--- /dev/null\n+++ b/doc/users/next_whats_new/get_vertices_co_vertices.rst\n@@ -0,0 +1,7 @@\n+``Ellipse.get_vertices()``, ``Ellipse.get_co_vertices()``\n+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n+These methods return the coordinates of ellipse vertices of\n+major and minor axis. Additionally, an example gallery demo is added which\n+shows how to add an arrow to an ellipse showing a clockwise or counter-clockwise\n+rotation of the ellipse. To place the arrow exactly on the ellipse,\n+the coordinates of the vertices are used.\n"
}
] |
diff --git a/doc/users/next_whats_new/get_vertices_co_vertices.rst b/doc/users/next_whats_new/get_vertices_co_vertices.rst
new file mode 100644
index 000000000000..98254a82ce63
--- /dev/null
+++ b/doc/users/next_whats_new/get_vertices_co_vertices.rst
@@ -0,0 +1,7 @@
+``Ellipse.get_vertices()``, ``Ellipse.get_co_vertices()``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+These methods return the coordinates of ellipse vertices of
+major and minor axis. Additionally, an example gallery demo is added which
+shows how to add an arrow to an ellipse showing a clockwise or counter-clockwise
+rotation of the ellipse. To place the arrow exactly on the ellipse,
+the coordinates of the vertices are used.
If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:
[{'type': 'file', 'name': 'galleries/examples/shapes_and_collections/ellipse_arrow.py'}]
|
matplotlib/matplotlib
|
matplotlib__matplotlib-26089
|
https://github.com/matplotlib/matplotlib/pull/26089
|
diff --git a/doc/users/next_whats_new/set_loc.rst b/doc/users/next_whats_new/set_loc.rst
new file mode 100644
index 000000000000..2a8722a18da0
--- /dev/null
+++ b/doc/users/next_whats_new/set_loc.rst
@@ -0,0 +1,23 @@
+Add a public method to modify the location of ``Legend``
+--------------------------------------------------------
+
+`~matplotlib.legend.Legend` locations now can be tweaked after they've been defined.
+
+.. plot::
+ :include-source: true
+
+ from matplotlib import pyplot as plt
+
+ fig = plt.figure()
+ ax = fig.add_subplot(1, 1, 1)
+
+ x = list(range(-100, 101))
+ y = [i**2 for i in x]
+
+ ax.plot(x, y, label="f(x)")
+ ax.legend()
+ ax.get_legend().set_loc("right")
+ # Or
+ # ax.get_legend().set(loc="right")
+
+ plt.show()
diff --git a/lib/matplotlib/legend.py b/lib/matplotlib/legend.py
index b0e50d67f9b7..a0ad612e7084 100644
--- a/lib/matplotlib/legend.py
+++ b/lib/matplotlib/legend.py
@@ -330,6 +330,12 @@ def _update_bbox_to_anchor(self, loc_in_canvas):
_legend_kw_doc_base)
_docstring.interpd.update(_legend_kw_doc=_legend_kw_both_st)
+_legend_kw_set_loc_st = (
+ _loc_doc_base.format(parent='axes/figure',
+ default=":rc:`legend.loc` for Axes, 'upper right' for Figure",
+ best=_loc_doc_best, outside=_outside_doc))
+_docstring.interpd.update(_legend_kw_set_loc_doc=_legend_kw_set_loc_st)
+
class Legend(Artist):
"""
@@ -503,58 +509,6 @@ def val_or_rc(val, rc_name):
)
self.parent = parent
- loc0 = loc
- self._loc_used_default = loc is None
- if loc is None:
- loc = mpl.rcParams["legend.loc"]
- if not self.isaxes and loc in [0, 'best']:
- loc = 'upper right'
-
- type_err_message = ("loc must be string, coordinate tuple, or"
- f" an integer 0-10, not {loc!r}")
-
- # handle outside legends:
- self._outside_loc = None
- if isinstance(loc, str):
- if loc.split()[0] == 'outside':
- # strip outside:
- loc = loc.split('outside ')[1]
- # strip "center" at the beginning
- self._outside_loc = loc.replace('center ', '')
- # strip first
- self._outside_loc = self._outside_loc.split()[0]
- locs = loc.split()
- if len(locs) > 1 and locs[0] in ('right', 'left'):
- # locs doesn't accept "left upper", etc, so swap
- if locs[0] != 'center':
- locs = locs[::-1]
- loc = locs[0] + ' ' + locs[1]
- # check that loc is in acceptable strings
- loc = _api.check_getitem(self.codes, loc=loc)
- elif np.iterable(loc):
- # coerce iterable into tuple
- loc = tuple(loc)
- # validate the tuple represents Real coordinates
- if len(loc) != 2 or not all(isinstance(e, numbers.Real) for e in loc):
- raise ValueError(type_err_message)
- elif isinstance(loc, int):
- # validate the integer represents a string numeric value
- if loc < 0 or loc > 10:
- raise ValueError(type_err_message)
- else:
- # all other cases are invalid values of loc
- raise ValueError(type_err_message)
-
- if self.isaxes and self._outside_loc:
- raise ValueError(
- f"'outside' option for loc='{loc0}' keyword argument only "
- "works for figure legends")
-
- if not self.isaxes and loc == 0:
- raise ValueError(
- "Automatic legend placement (loc='best') not implemented for "
- "figure legend")
-
self._mode = mode
self.set_bbox_to_anchor(bbox_to_anchor, bbox_transform)
@@ -598,9 +552,8 @@ def val_or_rc(val, rc_name):
# init with null renderer
self._init_legend_box(handles, labels, markerfirst)
- tmp = self._loc_used_default
- self._set_loc(loc)
- self._loc_used_default = tmp # ignore changes done by _set_loc
+ # Set legend location
+ self.set_loc(loc)
# figure out title font properties:
if title_fontsize is not None and title_fontproperties is not None:
@@ -686,6 +639,73 @@ def _set_artist_props(self, a):
a.set_transform(self.get_transform())
+ @_docstring.dedent_interpd
+ def set_loc(self, loc=None):
+ """
+ Set the location of the legend.
+
+ .. versionadded:: 3.8
+
+ Parameters
+ ----------
+ %(_legend_kw_set_loc_doc)s
+ """
+ loc0 = loc
+ self._loc_used_default = loc is None
+ if loc is None:
+ loc = mpl.rcParams["legend.loc"]
+ if not self.isaxes and loc in [0, 'best']:
+ loc = 'upper right'
+
+ type_err_message = ("loc must be string, coordinate tuple, or"
+ f" an integer 0-10, not {loc!r}")
+
+ # handle outside legends:
+ self._outside_loc = None
+ if isinstance(loc, str):
+ if loc.split()[0] == 'outside':
+ # strip outside:
+ loc = loc.split('outside ')[1]
+ # strip "center" at the beginning
+ self._outside_loc = loc.replace('center ', '')
+ # strip first
+ self._outside_loc = self._outside_loc.split()[0]
+ locs = loc.split()
+ if len(locs) > 1 and locs[0] in ('right', 'left'):
+ # locs doesn't accept "left upper", etc, so swap
+ if locs[0] != 'center':
+ locs = locs[::-1]
+ loc = locs[0] + ' ' + locs[1]
+ # check that loc is in acceptable strings
+ loc = _api.check_getitem(self.codes, loc=loc)
+ elif np.iterable(loc):
+ # coerce iterable into tuple
+ loc = tuple(loc)
+ # validate the tuple represents Real coordinates
+ if len(loc) != 2 or not all(isinstance(e, numbers.Real) for e in loc):
+ raise ValueError(type_err_message)
+ elif isinstance(loc, int):
+ # validate the integer represents a string numeric value
+ if loc < 0 or loc > 10:
+ raise ValueError(type_err_message)
+ else:
+ # all other cases are invalid values of loc
+ raise ValueError(type_err_message)
+
+ if self.isaxes and self._outside_loc:
+ raise ValueError(
+ f"'outside' option for loc='{loc0}' keyword argument only "
+ "works for figure legends")
+
+ if not self.isaxes and loc == 0:
+ raise ValueError(
+ "Automatic legend placement (loc='best') not implemented for "
+ "figure legend")
+
+ tmp = self._loc_used_default
+ self._set_loc(loc)
+ self._loc_used_default = tmp # ignore changes done by _set_loc
+
def _set_loc(self, loc):
# find_offset function will be provided to _legend_box and
# _legend_box will draw itself at the location of the return
diff --git a/lib/matplotlib/legend.pyi b/lib/matplotlib/legend.pyi
index 77ef273766c2..7116f40f3e0c 100644
--- a/lib/matplotlib/legend.pyi
+++ b/lib/matplotlib/legend.pyi
@@ -118,6 +118,7 @@ class Legend(Artist):
def get_texts(self) -> list[Text]: ...
def set_alignment(self, alignment: Literal["center", "left", "right"]) -> None: ...
def get_alignment(self) -> Literal["center", "left", "right"]: ...
+ def set_loc(self, loc: str | tuple[float, float] | int | None = ...) -> None: ...
def set_title(
self, title: str, prop: FontProperties | str | pathlib.Path | None = ...
) -> None: ...
|
diff --git a/lib/matplotlib/tests/test_legend.py b/lib/matplotlib/tests/test_legend.py
index c94a0f5f6169..720dfc3e6c65 100644
--- a/lib/matplotlib/tests/test_legend.py
+++ b/lib/matplotlib/tests/test_legend.py
@@ -755,6 +755,26 @@ def test_legend_alignment(alignment):
assert leg.get_alignment() == alignment
+@pytest.mark.parametrize('loc', ('center', 'best',))
+def test_ax_legend_set_loc(loc):
+ fig, ax = plt.subplots()
+ ax.plot(range(10), label='test')
+ leg = ax.legend()
+ leg.set_loc(loc)
+ assert leg._get_loc() == mlegend.Legend.codes[loc]
+
+
+@pytest.mark.parametrize('loc', ('outside right', 'right',))
+def test_fig_legend_set_loc(loc):
+ fig, ax = plt.subplots()
+ ax.plot(range(10), label='test')
+ leg = fig.legend()
+ leg.set_loc(loc)
+
+ loc = loc.split()[1] if loc.startswith("outside") else loc
+ assert leg._get_loc() == mlegend.Legend.codes[loc]
+
+
@pytest.mark.parametrize('alignment', ('center', 'left', 'right'))
def test_legend_set_alignment(alignment):
fig, ax = plt.subplots()
|
[
{
"path": "doc/users/next_whats_new/set_loc.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/set_loc.rst",
"metadata": "diff --git a/doc/users/next_whats_new/set_loc.rst b/doc/users/next_whats_new/set_loc.rst\nnew file mode 100644\nindex 000000000000..2a8722a18da0\n--- /dev/null\n+++ b/doc/users/next_whats_new/set_loc.rst\n@@ -0,0 +1,23 @@\n+Add a public method to modify the location of ``Legend``\n+--------------------------------------------------------\n+\n+`~matplotlib.legend.Legend` locations now can be tweaked after they've been defined.\n+\n+.. plot::\n+ :include-source: true\n+\n+ from matplotlib import pyplot as plt\n+\n+ fig = plt.figure()\n+ ax = fig.add_subplot(1, 1, 1)\n+\n+ x = list(range(-100, 101))\n+ y = [i**2 for i in x]\n+\n+ ax.plot(x, y, label=\"f(x)\")\n+ ax.legend()\n+ ax.get_legend().set_loc(\"right\")\n+ # Or\n+ # ax.get_legend().set(loc=\"right\")\n+\n+ plt.show()\n"
}
] |
3.7
|
f588d2b06e5b3c3296046d2ee9f0c13831cafe1c
|
[
"lib/matplotlib/tests/test_legend.py::test_plot_single_input_multiple_label[label_array0]",
"lib/matplotlib/tests/test_legend.py::test_not_covering_scatter[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_auto1[svg]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_single[color2]",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_legend_label_arg",
"lib/matplotlib/tests/test_legend.py::test_text_nohandler_warning",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_kwargs_handles_labels",
"lib/matplotlib/tests/test_legend.py::test_loc_invalid_tuple_exception",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_markeredgecolor_cmap",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_input_single_label[one]",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_kwargs_handles_only",
"lib/matplotlib/tests/test_legend.py::test_legend_auto2[svg]",
"lib/matplotlib/tests/test_legend.py::test_warn_big_data_best_loc",
"lib/matplotlib/tests/test_legend.py::test_fancy[png]",
"lib/matplotlib/tests/test_legend.py::test_loc_valid_tuple",
"lib/matplotlib/tests/test_legend.py::test_legend_expand[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_markfacecolor_cmap",
"lib/matplotlib/tests/test_legend.py::test_various_labels[pdf]",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_linecolor_iterable",
"lib/matplotlib/tests/test_legend.py::test_legend_alignment[right]",
"lib/matplotlib/tests/test_legend.py::test_ncol_ncols[pdf]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_single[red]",
"lib/matplotlib/tests/test_legend.py::test_legend_auto3[pdf]",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_legend_label_three_args",
"lib/matplotlib/tests/test_legend.py::test_framealpha[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_markerfacecolor",
"lib/matplotlib/tests/test_legend.py::test_legend_auto2[png]",
"lib/matplotlib/tests/test_legend.py::test_loc_validation_numeric_value",
"lib/matplotlib/tests/test_legend.py::test_rc[svg]",
"lib/matplotlib/tests/test_legend.py::test_legend_label_with_leading_underscore",
"lib/matplotlib/tests/test_legend.py::test_setting_alpha_keeps_polycollection_color",
"lib/matplotlib/tests/test_legend.py::test_legend_expand[svg]",
"lib/matplotlib/tests/test_legend.py::test_get_set_draggable",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_label_incorrect_length_exception",
"lib/matplotlib/tests/test_legend.py::test_legend_text_axes",
"lib/matplotlib/tests/test_legend.py::test_cross_figure_patch_legend",
"lib/matplotlib/tests/test_legend.py::test_alpha_rcparam[png]",
"lib/matplotlib/tests/test_legend.py::test_linecollection_scaled_dashes",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_three_args",
"lib/matplotlib/tests/test_legend.py::test_legend_auto3[svg]",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_legend_handle_label",
"lib/matplotlib/tests/test_legend.py::test_handlerline2d",
"lib/matplotlib/tests/test_legend.py::test_legend_title_empty",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_markeredgecolor",
"lib/matplotlib/tests/test_legend.py::test_rc[png]",
"lib/matplotlib/tests/test_legend.py::test_fancy[svg]",
"lib/matplotlib/tests/test_legend.py::test_legend_title_fontprop_fontsize",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_markeredgecolor",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_markerfacecolor",
"lib/matplotlib/tests/test_legend.py::test_shadow_invalid_argument",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_single[none]",
"lib/matplotlib/tests/test_legend.py::test_hatching[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_list",
"lib/matplotlib/tests/test_legend.py::test_hatching[pdf]",
"lib/matplotlib/tests/test_legend.py::test_plot_single_input_multiple_label[label_array1]",
"lib/matplotlib/tests/test_legend.py::test_handler_numpoints",
"lib/matplotlib/tests/test_legend.py::test_alpha_handles",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_markeredgecolor_iterable",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_input_multiple_label[label_array2]",
"lib/matplotlib/tests/test_legend.py::test_labels_first[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_stackplot[png]",
"lib/matplotlib/tests/test_legend.py::test_shadow_argument_types[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_set_alignment[center]",
"lib/matplotlib/tests/test_legend.py::test_legend_auto1[pdf]",
"lib/matplotlib/tests/test_legend.py::test_hatching[svg]",
"lib/matplotlib/tests/test_legend.py::test_nanscatter",
"lib/matplotlib/tests/test_legend.py::test_fancy[pdf]",
"lib/matplotlib/tests/test_legend.py::test_empty_bar_chart_with_legend",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_legend_label_three_args_pluskw",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_input_single_label[int]",
"lib/matplotlib/tests/test_legend.py::test_loc_validation_string_value",
"lib/matplotlib/tests/test_legend.py::test_legend_proper_window_extent",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_input_multiple_label[label_array0]",
"lib/matplotlib/tests/test_legend.py::test_legend_auto4",
"lib/matplotlib/tests/test_legend.py::test_not_covering_scatter_transform[png]",
"lib/matplotlib/tests/test_legend.py::test_subfigure_legend",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_positional_labels_only",
"lib/matplotlib/tests/test_legend.py::test_various_labels[svg]",
"lib/matplotlib/tests/test_legend.py::test_legend_set_alignment[right]",
"lib/matplotlib/tests/test_legend.py::test_alpha_rgba[png]",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_positional_handles_only",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_no_args",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_single[none]",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_parasite",
"lib/matplotlib/tests/test_legend.py::test_legend_draggable[False]",
"lib/matplotlib/tests/test_legend.py::test_legend_auto2[pdf]",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_legend_no_args",
"lib/matplotlib/tests/test_legend.py::test_legend_auto1[png]",
"lib/matplotlib/tests/test_legend.py::test_rc[pdf]",
"lib/matplotlib/tests/test_legend.py::test_legend_repeatcheckok",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_markeredgecolor",
"lib/matplotlib/tests/test_legend.py::test_framealpha[svg]",
"lib/matplotlib/tests/test_legend.py::test_window_extent_cached_renderer",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_markerfacecolor_iterable",
"lib/matplotlib/tests/test_legend.py::test_legend_set_alignment[left]",
"lib/matplotlib/tests/test_legend.py::test_reverse_legend_handles_and_labels",
"lib/matplotlib/tests/test_legend.py::test_legend_alignment[left]",
"lib/matplotlib/tests/test_legend.py::test_figure_legend_outside",
"lib/matplotlib/tests/test_legend.py::test_legend_expand[pdf]",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_input_single_label[1]",
"lib/matplotlib/tests/test_legend.py::test_reverse_legend_display[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_remove",
"lib/matplotlib/tests/test_legend.py::test_multiple_keys[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_markers_from_line2d",
"lib/matplotlib/tests/test_legend.py::test_loc_valid_list",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_single[red]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_markerfacecolor_short",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_positional_handles_labels",
"lib/matplotlib/tests/test_legend.py::test_legend_auto3[png]",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_warn_args_kwargs",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_input_multiple_label[label_array1]",
"lib/matplotlib/tests/test_legend.py::test_plot_single_input_multiple_label[label_array2]",
"lib/matplotlib/tests/test_legend.py::test_loc_invalid_type",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_single[color2]",
"lib/matplotlib/tests/test_legend.py::test_legend_ordereddict",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_kwargs_labels_only",
"lib/matplotlib/tests/test_legend.py::test_legend_draggable[True]",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_warn_mixed_args_and_kwargs",
"lib/matplotlib/tests/test_legend.py::test_loc_invalid_list_exception",
"lib/matplotlib/tests/test_legend.py::test_shadow_framealpha",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_legend_kw_args",
"lib/matplotlib/tests/test_legend.py::test_no_warn_big_data_when_loc_specified",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_linecolor",
"lib/matplotlib/tests/test_legend.py::test_framealpha[pdf]",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_handler_map",
"lib/matplotlib/tests/test_legend.py::test_legend_auto5",
"lib/matplotlib/tests/test_legend.py::test_legend_alignment[center]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_linecolor",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_markeredgecolor_short",
"lib/matplotlib/tests/test_legend.py::test_ncol_ncols[png]",
"lib/matplotlib/tests/test_legend.py::test_ncol_ncols[svg]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_linecolor",
"lib/matplotlib/tests/test_legend.py::test_legend_face_edgecolor",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_markerfacecolor",
"lib/matplotlib/tests/test_legend.py::test_various_labels[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_linecolor_cmap"
] |
[
"lib/matplotlib/tests/test_legend.py::test_fig_legend_set_loc[right]",
"lib/matplotlib/tests/test_legend.py::test_ax_legend_set_loc[center]",
"lib/matplotlib/tests/test_legend.py::test_fig_legend_set_loc[outside right]",
"lib/matplotlib/tests/test_legend.py::test_ax_legend_set_loc[best]"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/users/next_whats_new/set_loc.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/set_loc.rst",
"metadata": "diff --git a/doc/users/next_whats_new/set_loc.rst b/doc/users/next_whats_new/set_loc.rst\nnew file mode 100644\nindex 000000000000..2a8722a18da0\n--- /dev/null\n+++ b/doc/users/next_whats_new/set_loc.rst\n@@ -0,0 +1,23 @@\n+Add a public method to modify the location of ``Legend``\n+--------------------------------------------------------\n+\n+`~matplotlib.legend.Legend` locations now can be tweaked after they've been defined.\n+\n+.. plot::\n+ :include-source: true\n+\n+ from matplotlib import pyplot as plt\n+\n+ fig = plt.figure()\n+ ax = fig.add_subplot(1, 1, 1)\n+\n+ x = list(range(-100, 101))\n+ y = [i**2 for i in x]\n+\n+ ax.plot(x, y, label=\"f(x)\")\n+ ax.legend()\n+ ax.get_legend().set_loc(\"right\")\n+ # Or\n+ # ax.get_legend().set(loc=\"right\")\n+\n+ plt.show()\n"
}
] |
diff --git a/doc/users/next_whats_new/set_loc.rst b/doc/users/next_whats_new/set_loc.rst
new file mode 100644
index 000000000000..2a8722a18da0
--- /dev/null
+++ b/doc/users/next_whats_new/set_loc.rst
@@ -0,0 +1,23 @@
+Add a public method to modify the location of ``Legend``
+--------------------------------------------------------
+
+`~matplotlib.legend.Legend` locations now can be tweaked after they've been defined.
+
+.. plot::
+ :include-source: true
+
+ from matplotlib import pyplot as plt
+
+ fig = plt.figure()
+ ax = fig.add_subplot(1, 1, 1)
+
+ x = list(range(-100, 101))
+ y = [i**2 for i in x]
+
+ ax.plot(x, y, label="f(x)")
+ ax.legend()
+ ax.get_legend().set_loc("right")
+ # Or
+ # ax.get_legend().set(loc="right")
+
+ plt.show()
|
matplotlib/matplotlib
|
matplotlib__matplotlib-24691
|
https://github.com/matplotlib/matplotlib/pull/24691
|
diff --git a/doc/users/next_whats_new/new_color_spec_tuple.rst b/doc/users/next_whats_new/new_color_spec_tuple.rst
new file mode 100644
index 000000000000..9f8d0ecabc3e
--- /dev/null
+++ b/doc/users/next_whats_new/new_color_spec_tuple.rst
@@ -0,0 +1,21 @@
+Add a new valid color format ``(matplotlib_color, alpha)``
+----------------------------------------------------------
+
+
+.. plot::
+ :include-source: true
+
+ import matplotlib.pyplot as plt
+ from matplotlib.patches import Rectangle
+
+ fig, ax = plt.subplots()
+
+ rectangle = Rectangle((.2, .2), .6, .6,
+ facecolor=('blue', 0.2),
+ edgecolor=('green', 0.5))
+ ax.add_patch(rectangle)
+
+
+Users can define a color using the new color specification, *(matplotlib_color, alpha)*.
+Note that an explicit alpha keyword argument will override an alpha value from
+*(matplotlib_color, alpha)*.
diff --git a/galleries/examples/color/set_alpha.py b/galleries/examples/color/set_alpha.py
new file mode 100644
index 000000000000..4130fe1109ef
--- /dev/null
+++ b/galleries/examples/color/set_alpha.py
@@ -0,0 +1,53 @@
+"""
+=================================
+Ways to set a color's alpha value
+=================================
+
+Compare setting alpha by the *alpha* keyword argument and by one of the Matplotlib color
+formats. Often, the *alpha* keyword is the only tool needed to add transparency to a
+color. In some cases, the *(matplotlib_color, alpha)* color format provides an easy way
+to fine-tune the appearance of a Figure.
+
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+# Fixing random state for reproducibility.
+np.random.seed(19680801)
+
+fig, (ax1, ax2) = plt.subplots(ncols=2, figsize=(8, 4))
+
+x_values = [n for n in range(20)]
+y_values = np.random.randn(20)
+
+facecolors = ['green' if y > 0 else 'red' for y in y_values]
+edgecolors = facecolors
+
+ax1.bar(x_values, y_values, color=facecolors, edgecolor=edgecolors, alpha=0.5)
+ax1.set_title("Explicit 'alpha' keyword value\nshared by all bars and edges")
+
+
+# Normalize y values to get distinct face alpha values.
+abs_y = [abs(y) for y in y_values]
+face_alphas = [n / max(abs_y) for n in abs_y]
+edge_alphas = [1 - alpha for alpha in face_alphas]
+
+colors_with_alphas = list(zip(facecolors, face_alphas))
+edgecolors_with_alphas = list(zip(edgecolors, edge_alphas))
+
+ax2.bar(x_values, y_values, color=colors_with_alphas,
+ edgecolor=edgecolors_with_alphas)
+ax2.set_title('Normalized alphas for\neach bar and each edge')
+
+plt.show()
+
+# %%
+#
+# .. admonition:: References
+#
+# The use of the following functions, methods, classes and modules is shown
+# in this example:
+#
+# - `matplotlib.axes.Axes.bar`
+# - `matplotlib.pyplot.subplots`
diff --git a/galleries/users_explain/colors/colors.py b/galleries/users_explain/colors/colors.py
index bd8cdb299a85..d308f0fb1859 100644
--- a/galleries/users_explain/colors/colors.py
+++ b/galleries/users_explain/colors/colors.py
@@ -68,6 +68,9 @@
| to black if cycle does not | |
| include color. | |
+--------------------------------------+--------------------------------------+
+| Tuple of one of the above color | - ``('green', 0.3)`` |
+| formats and an alpha float. | - ``('#f00', 0.9)`` |
++--------------------------------------+--------------------------------------+
.. _xkcd color survey: https://xkcd.com/color/rgb/
diff --git a/lib/matplotlib/colors.py b/lib/matplotlib/colors.py
index 304eccca1bd7..d9a60afd0f3f 100644
--- a/lib/matplotlib/colors.py
+++ b/lib/matplotlib/colors.py
@@ -315,6 +315,13 @@ def _to_rgba_no_colorcycle(c, alpha=None):
*alpha* is ignored for the color value ``"none"`` (case-insensitive),
which always maps to ``(0, 0, 0, 0)``.
"""
+ if isinstance(c, tuple) and len(c) == 2:
+ if alpha is None:
+ c, alpha = c
+ else:
+ c = c[0]
+ if alpha is not None and not 0 <= alpha <= 1:
+ raise ValueError("'alpha' must be between 0 and 1, inclusive")
orig_c = c
if c is np.ma.masked:
return (0., 0., 0., 0.)
@@ -425,6 +432,11 @@ def to_rgba_array(c, alpha=None):
(n, 4) array of RGBA colors, where each channel (red, green, blue,
alpha) can assume values between 0 and 1.
"""
+ if isinstance(c, tuple) and len(c) == 2:
+ if alpha is None:
+ c, alpha = c
+ else:
+ c = c[0]
# Special-case inputs that are already arrays, for performance. (If the
# array has the wrong kind or shape, raise the error during one-at-a-time
# conversion.)
@@ -464,9 +476,12 @@ def to_rgba_array(c, alpha=None):
return np.array([to_rgba(c, a) for a in alpha], float)
else:
return np.array([to_rgba(c, alpha)], float)
- except (ValueError, TypeError):
+ except TypeError:
pass
-
+ except ValueError as e:
+ if e.args == ("'alpha' must be between 0 and 1, inclusive", ):
+ # ValueError is from _to_rgba_no_colorcycle().
+ raise e
if isinstance(c, str):
raise ValueError(f"{c!r} is not a valid color value.")
|
diff --git a/lib/matplotlib/tests/test_colors.py b/lib/matplotlib/tests/test_colors.py
index 14dd4ced77db..21e76bcd18b4 100644
--- a/lib/matplotlib/tests/test_colors.py
+++ b/lib/matplotlib/tests/test_colors.py
@@ -1307,6 +1307,51 @@ def test_to_rgba_array_alpha_array():
assert_array_equal(c[:, 3], alpha)
+def test_to_rgba_array_accepts_color_alpha_tuple():
+ assert_array_equal(
+ mcolors.to_rgba_array(('black', 0.9)),
+ [[0, 0, 0, 0.9]])
+
+
+def test_to_rgba_array_explicit_alpha_overrides_tuple_alpha():
+ assert_array_equal(
+ mcolors.to_rgba_array(('black', 0.9), alpha=0.5),
+ [[0, 0, 0, 0.5]])
+
+
+def test_to_rgba_array_accepts_color_alpha_tuple_with_multiple_colors():
+ color_array = np.array([[1., 1., 1., 1.], [0., 0., 1., 0.]])
+ assert_array_equal(
+ mcolors.to_rgba_array((color_array, 0.2)),
+ [[1., 1., 1., 0.2], [0., 0., 1., 0.2]])
+
+ color_sequence = [[1., 1., 1., 1.], [0., 0., 1., 0.]]
+ assert_array_equal(
+ mcolors.to_rgba_array((color_sequence, 0.4)),
+ [[1., 1., 1., 0.4], [0., 0., 1., 0.4]])
+
+
+def test_to_rgba_array_error_with_color_invalid_alpha_tuple():
+ with pytest.raises(ValueError, match="'alpha' must be between 0 and 1,"):
+ mcolors.to_rgba_array(('black', 2.0))
+
+
+@pytest.mark.parametrize('rgba_alpha',
+ [('white', 0.5), ('#ffffff', 0.5), ('#ffffff00', 0.5),
+ ((1.0, 1.0, 1.0, 1.0), 0.5)])
+def test_to_rgba_accepts_color_alpha_tuple(rgba_alpha):
+ assert mcolors.to_rgba(rgba_alpha) == (1, 1, 1, 0.5)
+
+
+def test_to_rgba_explicit_alpha_overrides_tuple_alpha():
+ assert mcolors.to_rgba(('red', 0.1), alpha=0.9) == (1, 0, 0, 0.9)
+
+
+def test_to_rgba_error_with_color_invalid_alpha_tuple():
+ with pytest.raises(ValueError, match="'alpha' must be between 0 and 1"):
+ mcolors.to_rgba(('blue', 2.0))
+
+
def test_failed_conversions():
with pytest.raises(ValueError):
mcolors.to_rgba('5')
|
[
{
"path": "doc/users/next_whats_new/new_color_spec_tuple.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/new_color_spec_tuple.rst",
"metadata": "diff --git a/doc/users/next_whats_new/new_color_spec_tuple.rst b/doc/users/next_whats_new/new_color_spec_tuple.rst\nnew file mode 100644\nindex 000000000000..9f8d0ecabc3e\n--- /dev/null\n+++ b/doc/users/next_whats_new/new_color_spec_tuple.rst\n@@ -0,0 +1,21 @@\n+Add a new valid color format ``(matplotlib_color, alpha)``\n+----------------------------------------------------------\n+\n+\n+.. plot::\n+ :include-source: true\n+\n+ import matplotlib.pyplot as plt\n+ from matplotlib.patches import Rectangle\n+\n+ fig, ax = plt.subplots()\n+\n+ rectangle = Rectangle((.2, .2), .6, .6,\n+ facecolor=('blue', 0.2),\n+ edgecolor=('green', 0.5))\n+ ax.add_patch(rectangle)\n+\n+\n+Users can define a color using the new color specification, *(matplotlib_color, alpha)*.\n+Note that an explicit alpha keyword argument will override an alpha value from\n+*(matplotlib_color, alpha)*.\n"
}
] |
3.7
|
78bf53caacbb5ce0dc7aa73f07a74c99f1ed919b
|
[
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdBu]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PuOr]",
"lib/matplotlib/tests/test_colors.py::test_LogNorm",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[BrBG]",
"lib/matplotlib/tests/test_colors.py::test_create_lookup_table[1-result2]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_ncar]",
"lib/matplotlib/tests/test_colors.py::test_colormap_copy",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_yarg_r]",
"lib/matplotlib/tests/test_colors.py::test_light_source_shading_default",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[nipy_spectral]",
"lib/matplotlib/tests/test_colors.py::test_colormap_endian",
"lib/matplotlib/tests/test_colors.py::test_autoscale_masked",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[summer]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gray]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_scaleout_center",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[CMRmap_r]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_VmaxEqualsVcenter",
"lib/matplotlib/tests/test_colors.py::test_norm_callback",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[flag_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_stern_r]",
"lib/matplotlib/tests/test_colors.py::test_non_mutable_get_values[under]",
"lib/matplotlib/tests/test_colors.py::test_unregister_builtin_cmap",
"lib/matplotlib/tests/test_colors.py::test_Normalize",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Greens]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[pink]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[rainbow_r]",
"lib/matplotlib/tests/test_colors.py::test_conversions",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Dark2_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdPu_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[YlOrBr]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[brg_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Greys_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_rainbow_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[OrRd_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Set1_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[autumn]",
"lib/matplotlib/tests/test_colors.py::test_SymLogNorm_colorbar",
"lib/matplotlib/tests/test_colors.py::test_light_source_topo_surface[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_gray_r]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_TwoSlopeNorm_VminGTVmax",
"lib/matplotlib/tests/test_colors.py::test_CenteredNorm",
"lib/matplotlib/tests/test_colors.py::test_cmap_and_norm_from_levels_and_colors[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[magma_r]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_scaleout_center_max",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[GnBu]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_ncar_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_bad_data_with_alpha",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[twilight_shifted]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[YlOrBr_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PiYG]",
"lib/matplotlib/tests/test_colors.py::test_index_dtype[int]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[bwr]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[winter_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Paired]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Oranges]",
"lib/matplotlib/tests/test_colors.py::test_conversions_masked",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PuRd]",
"lib/matplotlib/tests/test_colors.py::test_LogNorm_inverse",
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"lib/matplotlib/tests/test_colors.py::test_grey_gray",
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"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Pastel1_r]",
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"lib/matplotlib/tests/test_colors.py::test_norm_update_figs[pdf]",
"lib/matplotlib/tests/test_colors.py::test_register_cmap",
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"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Wistia]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[hot]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_autoscale_None_vmax",
"lib/matplotlib/tests/test_colors.py::test_pandas_iterable",
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"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[cool_r]",
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"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[rainbow]",
"lib/matplotlib/tests/test_colors.py::test_light_source_shading_empty_mask",
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"lib/matplotlib/tests/test_colors.py::test_boundarynorm_and_colorbarbase[png]",
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"lib/matplotlib/tests/test_colors.py::test_set_dict_to_rgba",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[tab20]",
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"lib/matplotlib/tests/test_colors.py::test_lognorm_invalid[-1-2]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_VcenterGTVmax",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Spectral]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_gray]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[tab20_r]",
"lib/matplotlib/tests/test_colors.py::test_norm_update_figs[svg]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Pastel1]",
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"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[YlGnBu]",
"lib/matplotlib/tests/test_colors.py::test_SymLogNorm",
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"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[inferno_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[prism]",
"lib/matplotlib/tests/test_colors.py::test_PowerNorm_translation_invariance",
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"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[magma]",
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"lib/matplotlib/tests/test_colors.py::test_non_mutable_get_values[bad]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[BuPu]",
"lib/matplotlib/tests/test_colors.py::test_repr_html",
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"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[twilight_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[jet_r]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_autoscale",
"lib/matplotlib/tests/test_colors.py::test_failed_conversions",
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"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_earth_r]",
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"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[flag]",
"lib/matplotlib/tests/test_colors.py::test_rgb_hsv_round_trip",
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"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gray_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[nipy_spectral_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Purples]",
"lib/matplotlib/tests/test_colors.py::test_repr_png",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Spectral_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_alpha_array",
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"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_VminGTVcenter",
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"lib/matplotlib/tests/test_colors.py::test_to_rgba_array_single_str",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[jet]",
"lib/matplotlib/tests/test_colors.py::test_resampled",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[plasma]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Wistia_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdYlBu_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[winter]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdPu]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[autumn_r]",
"lib/matplotlib/tests/test_colors.py::test_tableau_order",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[YlGn]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gnuplot]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[tab10_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_earth]",
"lib/matplotlib/tests/test_colors.py::test_colormaps_get_cmap",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[twilight_shifted_r]",
"lib/matplotlib/tests/test_colors.py::test_PowerNorm",
"lib/matplotlib/tests/test_colors.py::test_norm_update_figs[png]",
"lib/matplotlib/tests/test_colors.py::test_to_rgba_array_alpha_array",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[BuGn_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[viridis_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[copper]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdBu_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Dark2]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_autoscale_None_vmin",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdYlBu]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[YlOrRd_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Reds]",
"lib/matplotlib/tests/test_colors.py::test_index_dtype[float]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Set3]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_premature_scaling",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PuOr_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_heat_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_equals",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[binary]",
"lib/matplotlib/tests/test_colors.py::TestAsinhNorm::test_norm",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdGy_r]",
"lib/matplotlib/tests/test_colors.py::test_cmap_and_norm_from_levels_and_colors2",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[summer_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[viridis]",
"lib/matplotlib/tests/test_colors.py::test_color_sequences",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[YlOrRd]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[terrain_r]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_VminEqualsVcenter",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PiYG_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gnuplot2]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Purples_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PRGn_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PuBuGn]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[binary_r]",
"lib/matplotlib/tests/test_colors.py::test_cn",
"lib/matplotlib/tests/test_colors.py::test_get_under_over_bad",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_stern]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[CMRmap]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_Even",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[bone_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[tab20c_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdYlGn]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Set3_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Greens_r]",
"lib/matplotlib/tests/test_colors.py::test_FuncNorm",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[BuGn]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_heat]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[turbo_r]"
] |
[
"lib/matplotlib/tests/test_colors.py::test_to_rgba_array_accepts_color_alpha_tuple",
"lib/matplotlib/tests/test_colors.py::test_to_rgba_array_explicit_alpha_overrides_tuple_alpha",
"lib/matplotlib/tests/test_colors.py::test_to_rgba_error_with_color_invalid_alpha_tuple",
"lib/matplotlib/tests/test_colors.py::test_to_rgba_accepts_color_alpha_tuple[rgba_alpha1]",
"lib/matplotlib/tests/test_colors.py::test_to_rgba_accepts_color_alpha_tuple[rgba_alpha3]",
"lib/matplotlib/tests/test_colors.py::test_to_rgba_accepts_color_alpha_tuple[rgba_alpha0]",
"lib/matplotlib/tests/test_colors.py::test_to_rgba_array_accepts_color_alpha_tuple_with_multiple_colors",
"lib/matplotlib/tests/test_colors.py::test_to_rgba_array_error_with_color_invalid_alpha_tuple",
"lib/matplotlib/tests/test_colors.py::test_to_rgba_accepts_color_alpha_tuple[rgba_alpha2]",
"lib/matplotlib/tests/test_colors.py::test_to_rgba_explicit_alpha_overrides_tuple_alpha"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": [
{
"type": "file",
"name": "galleries/examples/color/set_alpha.py"
}
]
}
|
[
{
"path": "doc/users/next_whats_new/new_color_spec_tuple.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/new_color_spec_tuple.rst",
"metadata": "diff --git a/doc/users/next_whats_new/new_color_spec_tuple.rst b/doc/users/next_whats_new/new_color_spec_tuple.rst\nnew file mode 100644\nindex 000000000000..9f8d0ecabc3e\n--- /dev/null\n+++ b/doc/users/next_whats_new/new_color_spec_tuple.rst\n@@ -0,0 +1,21 @@\n+Add a new valid color format ``(matplotlib_color, alpha)``\n+----------------------------------------------------------\n+\n+\n+.. plot::\n+ :include-source: true\n+\n+ import matplotlib.pyplot as plt\n+ from matplotlib.patches import Rectangle\n+\n+ fig, ax = plt.subplots()\n+\n+ rectangle = Rectangle((.2, .2), .6, .6,\n+ facecolor=('blue', 0.2),\n+ edgecolor=('green', 0.5))\n+ ax.add_patch(rectangle)\n+\n+\n+Users can define a color using the new color specification, *(matplotlib_color, alpha)*.\n+Note that an explicit alpha keyword argument will override an alpha value from\n+*(matplotlib_color, alpha)*.\n"
}
] |
diff --git a/doc/users/next_whats_new/new_color_spec_tuple.rst b/doc/users/next_whats_new/new_color_spec_tuple.rst
new file mode 100644
index 000000000000..9f8d0ecabc3e
--- /dev/null
+++ b/doc/users/next_whats_new/new_color_spec_tuple.rst
@@ -0,0 +1,21 @@
+Add a new valid color format ``(matplotlib_color, alpha)``
+----------------------------------------------------------
+
+
+.. plot::
+ :include-source: true
+
+ import matplotlib.pyplot as plt
+ from matplotlib.patches import Rectangle
+
+ fig, ax = plt.subplots()
+
+ rectangle = Rectangle((.2, .2), .6, .6,
+ facecolor=('blue', 0.2),
+ edgecolor=('green', 0.5))
+ ax.add_patch(rectangle)
+
+
+Users can define a color using the new color specification, *(matplotlib_color, alpha)*.
+Note that an explicit alpha keyword argument will override an alpha value from
+*(matplotlib_color, alpha)*.
If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:
[{'type': 'file', 'name': 'galleries/examples/color/set_alpha.py'}]
|
matplotlib/matplotlib
|
matplotlib__matplotlib-24759
|
https://github.com/matplotlib/matplotlib/pull/24759
|
diff --git a/doc/users/next_whats_new/reverse_legend.rst b/doc/users/next_whats_new/reverse_legend.rst
new file mode 100644
index 000000000000..00f2c0dbeac7
--- /dev/null
+++ b/doc/users/next_whats_new/reverse_legend.rst
@@ -0,0 +1,4 @@
+Reversed order of legend entries
+--------------------------------
+The order of legend entries can now be reversed by passing ``reverse=True`` to
+`~.Axes.legend`.
diff --git a/lib/matplotlib/legend.py b/lib/matplotlib/legend.py
index 82f92167c55c..c61be2c5550a 100644
--- a/lib/matplotlib/legend.py
+++ b/lib/matplotlib/legend.py
@@ -209,6 +209,12 @@ def _update_bbox_to_anchor(self, loc_in_canvas):
If *True*, legend marker is placed to the left of the legend label.
If *False*, legend marker is placed to the right of the legend label.
+reverse : bool, default: False
+ If *True*, the legend labels are displayed in reverse order from the input.
+ If *False*, the legend labels are displayed in the same order as the input.
+
+ ..versionadded:: 3.7
+
frameon : bool, default: :rc:`legend.frameon`
Whether the legend should be drawn on a patch (frame).
@@ -312,6 +318,7 @@ def __init__(
numpoints=None, # number of points in the legend line
markerscale=None, # relative size of legend markers vs. original
markerfirst=True, # left/right ordering of legend marker and label
+ reverse=False, # reverse ordering of legend marker and label
scatterpoints=None, # number of scatter points
scatteryoffsets=None,
prop=None, # properties for the legend texts
@@ -437,6 +444,10 @@ def val_or_rc(val, rc_name):
_hand.append(handle)
labels, handles = _lab, _hand
+ if reverse:
+ labels.reverse()
+ handles.reverse()
+
handles = list(handles)
if len(handles) < 2:
ncols = 1
|
diff --git a/lib/matplotlib/tests/test_legend.py b/lib/matplotlib/tests/test_legend.py
index 0016dc4d2d14..56794a3428b8 100644
--- a/lib/matplotlib/tests/test_legend.py
+++ b/lib/matplotlib/tests/test_legend.py
@@ -294,6 +294,38 @@ def test_legend_remove():
assert ax.get_legend() is None
+def test_reverse_legend_handles_and_labels():
+ """Check that the legend handles and labels are reversed."""
+ fig, ax = plt.subplots()
+ x = 1
+ y = 1
+ labels = ["First label", "Second label", "Third label"]
+ markers = ['.', ',', 'o']
+
+ ax.plot(x, y, markers[0], label=labels[0])
+ ax.plot(x, y, markers[1], label=labels[1])
+ ax.plot(x, y, markers[2], label=labels[2])
+ leg = ax.legend(reverse=True)
+ actual_labels = [t.get_text() for t in leg.get_texts()]
+ actual_markers = [h.get_marker() for h in leg.legend_handles]
+ assert actual_labels == list(reversed(labels))
+ assert actual_markers == list(reversed(markers))
+
+
+@check_figures_equal(extensions=["png"])
+def test_reverse_legend_display(fig_test, fig_ref):
+ """Check that the rendered legend entries are reversed"""
+ ax = fig_test.subplots()
+ ax.plot([1], 'ro', label="first")
+ ax.plot([2], 'bx', label="second")
+ ax.legend(reverse=True)
+
+ ax = fig_ref.subplots()
+ ax.plot([2], 'bx', label="second")
+ ax.plot([1], 'ro', label="first")
+ ax.legend()
+
+
class TestLegendFunction:
# Tests the legend function on the Axes and pyplot.
def test_legend_no_args(self):
|
[
{
"path": "doc/users/next_whats_new/reverse_legend.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/reverse_legend.rst",
"metadata": "diff --git a/doc/users/next_whats_new/reverse_legend.rst b/doc/users/next_whats_new/reverse_legend.rst\nnew file mode 100644\nindex 000000000000..00f2c0dbeac7\n--- /dev/null\n+++ b/doc/users/next_whats_new/reverse_legend.rst\n@@ -0,0 +1,4 @@\n+Reversed order of legend entries\n+--------------------------------\n+The order of legend entries can now be reversed by passing ``reverse=True`` to\n+`~.Axes.legend`.\n"
}
] |
3.5
|
b62376ce3b7a87d163b0482df94ae11601b66965
|
[
"lib/matplotlib/tests/test_legend.py::test_legend_auto1[png]",
"lib/matplotlib/tests/test_legend.py::test_framealpha[png]",
"lib/matplotlib/tests/test_legend.py::test_alpha_rcparam[png]",
"lib/matplotlib/tests/test_legend.py::test_cross_figure_patch_legend",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_single[red]",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_markerfacecolor_iterable",
"lib/matplotlib/tests/test_legend.py::test_legend_draggable[False]",
"lib/matplotlib/tests/test_legend.py::test_rc[pdf]",
"lib/matplotlib/tests/test_legend.py::test_legend_title_fontprop_fontsize",
"lib/matplotlib/tests/test_legend.py::test_plot_single_input_multiple_label[label_array0]",
"lib/matplotlib/tests/test_legend.py::test_setting_alpha_keeps_polycollection_color",
"lib/matplotlib/tests/test_legend.py::test_not_covering_scatter_transform[png]",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_input_single_label[int]",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_three_args",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_positional_handles_only",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_markerfacecolor_short",
"lib/matplotlib/tests/test_legend.py::test_legend_label_with_leading_underscore",
"lib/matplotlib/tests/test_legend.py::test_legend_title_empty",
"lib/matplotlib/tests/test_legend.py::test_legend_alignment[right]",
"lib/matplotlib/tests/test_legend.py::test_framealpha[pdf]",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_markerfacecolor",
"lib/matplotlib/tests/test_legend.py::test_legend_expand[pdf]",
"lib/matplotlib/tests/test_legend.py::test_various_labels[pdf]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_list",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_handler_map",
"lib/matplotlib/tests/test_legend.py::test_alpha_rgba[png]",
"lib/matplotlib/tests/test_legend.py::test_fancy[pdf]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_single[none]",
"lib/matplotlib/tests/test_legend.py::test_get_set_draggable",
"lib/matplotlib/tests/test_legend.py::test_window_extent_cached_renderer",
"lib/matplotlib/tests/test_legend.py::test_subfigure_legend",
"lib/matplotlib/tests/test_legend.py::test_nanscatter",
"lib/matplotlib/tests/test_legend.py::test_empty_bar_chart_with_legend",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_single[none]",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_markeredgecolor_iterable",
"lib/matplotlib/tests/test_legend.py::test_legend_auto3[svg]",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_legend_handle_label",
"lib/matplotlib/tests/test_legend.py::test_linecollection_scaled_dashes",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_markeredgecolor",
"lib/matplotlib/tests/test_legend.py::test_legend_markers_from_line2d",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_kwargs_labels_only",
"lib/matplotlib/tests/test_legend.py::test_fancy[png]",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_positional_handles_labels",
"lib/matplotlib/tests/test_legend.py::test_alpha_handles",
"lib/matplotlib/tests/test_legend.py::test_multiple_keys[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_ordereddict",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_input_multiple_label[label_array2]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_single[red]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_markeredgecolor",
"lib/matplotlib/tests/test_legend.py::test_various_labels[svg]",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_legend_kw_args",
"lib/matplotlib/tests/test_legend.py::test_legend_expand[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_linecolor_iterable",
"lib/matplotlib/tests/test_legend.py::test_fancy[svg]",
"lib/matplotlib/tests/test_legend.py::test_text_nohandler_warning",
"lib/matplotlib/tests/test_legend.py::test_legend_auto2[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_linecolor",
"lib/matplotlib/tests/test_legend.py::test_legend_auto2[pdf]",
"lib/matplotlib/tests/test_legend.py::test_not_covering_scatter[png]",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_legend_label_arg",
"lib/matplotlib/tests/test_legend.py::test_rc[png]",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_legend_label_three_args_pluskw",
"lib/matplotlib/tests/test_legend.py::test_hatching[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_single[color2]",
"lib/matplotlib/tests/test_legend.py::test_warn_big_data_best_loc",
"lib/matplotlib/tests/test_legend.py::test_plot_single_input_multiple_label[label_array1]",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_warn_mixed_args_and_kwargs",
"lib/matplotlib/tests/test_legend.py::test_legend_proper_window_extent",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_parasite",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_label_incorrect_length_exception",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_markeredgecolor_cmap",
"lib/matplotlib/tests/test_legend.py::test_legend_face_edgecolor",
"lib/matplotlib/tests/test_legend.py::test_legend_auto3[pdf]",
"lib/matplotlib/tests/test_legend.py::test_legend_stackplot[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_repeatcheckok",
"lib/matplotlib/tests/test_legend.py::test_handler_numpoints",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_legend_no_args",
"lib/matplotlib/tests/test_legend.py::test_rc[svg]",
"lib/matplotlib/tests/test_legend.py::test_handlerline2d",
"lib/matplotlib/tests/test_legend.py::test_plot_single_input_multiple_label[label_array2]",
"lib/matplotlib/tests/test_legend.py::test_legend_auto5",
"lib/matplotlib/tests/test_legend.py::test_legend_auto1[pdf]",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_no_args",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_single[color2]",
"lib/matplotlib/tests/test_legend.py::test_ncol_ncols[pdf]",
"lib/matplotlib/tests/test_legend.py::test_legend_auto4",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_markfacecolor_cmap",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_input_multiple_label[label_array1]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_markerfacecolor",
"lib/matplotlib/tests/test_legend.py::test_no_warn_big_data_when_loc_specified",
"lib/matplotlib/tests/test_legend.py::test_framealpha[svg]",
"lib/matplotlib/tests/test_legend.py::test_legend_expand[svg]",
"lib/matplotlib/tests/test_legend.py::test_legend_auto3[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_markeredgecolor",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_kwargs_handles_only",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_kwargs_handles_labels",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_markeredgecolor_short",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_markerfacecolor",
"lib/matplotlib/tests/test_legend.py::test_legend_draggable[True]",
"lib/matplotlib/tests/test_legend.py::test_legend_auto1[svg]",
"lib/matplotlib/tests/test_legend.py::test_legend_set_alignment[left]",
"lib/matplotlib/tests/test_legend.py::test_legend_set_alignment[right]",
"lib/matplotlib/tests/test_legend.py::test_legend_set_alignment[center]",
"lib/matplotlib/tests/test_legend.py::test_ncol_ncols[png]",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_legend_label_three_args",
"lib/matplotlib/tests/test_legend.py::test_labels_first[png]",
"lib/matplotlib/tests/test_legend.py::test_hatching[svg]",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_input_single_label[1]",
"lib/matplotlib/tests/test_legend.py::test_legend_auto2[svg]",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_linecolor_cmap",
"lib/matplotlib/tests/test_legend.py::test_legend_text_axes",
"lib/matplotlib/tests/test_legend.py::test_legend_remove",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_positional_labels_only",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_linecolor",
"lib/matplotlib/tests/test_legend.py::test_hatching[pdf]",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_input_single_label[one]",
"lib/matplotlib/tests/test_legend.py::test_various_labels[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_linecolor",
"lib/matplotlib/tests/test_legend.py::test_shadow_framealpha",
"lib/matplotlib/tests/test_legend.py::test_legend_alignment[center]",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_input_multiple_label[label_array0]",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_warn_args_kwargs",
"lib/matplotlib/tests/test_legend.py::test_ncol_ncols[svg]",
"lib/matplotlib/tests/test_legend.py::test_legend_alignment[left]"
] |
[
"lib/matplotlib/tests/test_legend.py::test_reverse_legend_handles_and_labels",
"lib/matplotlib/tests/test_legend.py::test_reverse_legend_display[png]"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/users/next_whats_new/reverse_legend.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/reverse_legend.rst",
"metadata": "diff --git a/doc/users/next_whats_new/reverse_legend.rst b/doc/users/next_whats_new/reverse_legend.rst\nnew file mode 100644\nindex 000000000000..00f2c0dbeac7\n--- /dev/null\n+++ b/doc/users/next_whats_new/reverse_legend.rst\n@@ -0,0 +1,4 @@\n+Reversed order of legend entries\n+--------------------------------\n+The order of legend entries can now be reversed by passing ``reverse=True`` to\n+`~.Axes.legend`.\n"
}
] |
diff --git a/doc/users/next_whats_new/reverse_legend.rst b/doc/users/next_whats_new/reverse_legend.rst
new file mode 100644
index 000000000000..00f2c0dbeac7
--- /dev/null
+++ b/doc/users/next_whats_new/reverse_legend.rst
@@ -0,0 +1,4 @@
+Reversed order of legend entries
+--------------------------------
+The order of legend entries can now be reversed by passing ``reverse=True`` to
+`~.Axes.legend`.
|
matplotlib/matplotlib
|
matplotlib__matplotlib-25821
|
https://github.com/matplotlib/matplotlib/pull/25821
|
diff --git a/doc/api/toolkits/mplot3d/axes3d.rst b/doc/api/toolkits/mplot3d/axes3d.rst
index 99c57db64d9a..f6d8e2529896 100644
--- a/doc/api/toolkits/mplot3d/axes3d.rst
+++ b/doc/api/toolkits/mplot3d/axes3d.rst
@@ -209,6 +209,7 @@ Sharing
:nosignatures:
sharez
+ shareview
Interactive
diff --git a/doc/users/next_whats_new/3d_plots_shareview.rst b/doc/users/next_whats_new/3d_plots_shareview.rst
new file mode 100644
index 000000000000..e71d06fd9297
--- /dev/null
+++ b/doc/users/next_whats_new/3d_plots_shareview.rst
@@ -0,0 +1,7 @@
+3D plots can share view angles
+------------------------------
+
+3D plots can now share the same view angles, so that when you rotate one plot
+the other plots also rotate. This can be done with the *shareview* keyword
+argument when adding an axes, or by using the *ax1.shareview(ax2)* method of
+existing 3D axes.
diff --git a/lib/mpl_toolkits/mplot3d/axes3d.py b/lib/mpl_toolkits/mplot3d/axes3d.py
index 35b0aaa01f97..cf2722eb4aae 100644
--- a/lib/mpl_toolkits/mplot3d/axes3d.py
+++ b/lib/mpl_toolkits/mplot3d/axes3d.py
@@ -56,6 +56,7 @@ class Axes3D(Axes):
_axis_names = ("x", "y", "z")
Axes._shared_axes["z"] = cbook.Grouper()
+ Axes._shared_axes["view"] = cbook.Grouper()
vvec = _api.deprecate_privatize_attribute("3.7")
eye = _api.deprecate_privatize_attribute("3.7")
@@ -66,6 +67,7 @@ def __init__(
self, fig, rect=None, *args,
elev=30, azim=-60, roll=0, sharez=None, proj_type='persp',
box_aspect=None, computed_zorder=True, focal_length=None,
+ shareview=None,
**kwargs):
"""
Parameters
@@ -111,6 +113,8 @@ def __init__(
or infinity (numpy.inf). If None, defaults to infinity.
The focal length can be computed from a desired Field Of View via
the equation: focal_length = 1/tan(FOV/2)
+ shareview : Axes3D, optional
+ Other Axes to share view angles with.
**kwargs
Other optional keyword arguments:
@@ -142,6 +146,10 @@ def __init__(
self._shared_axes["z"].join(self, sharez)
self._adjustable = 'datalim'
+ self._shareview = shareview
+ if shareview is not None:
+ self._shared_axes["view"].join(self, shareview)
+
if kwargs.pop('auto_add_to_figure', False):
raise AttributeError(
'auto_add_to_figure is no longer supported for Axes3D. '
@@ -757,7 +765,8 @@ def clabel(self, *args, **kwargs):
"""Currently not implemented for 3D axes, and returns *None*."""
return None
- def view_init(self, elev=None, azim=None, roll=None, vertical_axis="z"):
+ def view_init(self, elev=None, azim=None, roll=None, vertical_axis="z",
+ share=False):
"""
Set the elevation and azimuth of the axes in degrees (not radians).
@@ -804,29 +813,34 @@ def view_init(self, elev=None, azim=None, roll=None, vertical_axis="z"):
constructor is used.
vertical_axis : {"z", "x", "y"}, default: "z"
The axis to align vertically. *azim* rotates about this axis.
+ share : bool, default: False
+ If ``True``, apply the settings to all Axes with shared views.
"""
self._dist = 10 # The camera distance from origin. Behaves like zoom
if elev is None:
- self.elev = self.initial_elev
- else:
- self.elev = elev
-
+ elev = self.initial_elev
if azim is None:
- self.azim = self.initial_azim
- else:
- self.azim = azim
-
+ azim = self.initial_azim
if roll is None:
- self.roll = self.initial_roll
- else:
- self.roll = roll
-
- self._vertical_axis = _api.check_getitem(
+ roll = self.initial_roll
+ vertical_axis = _api.check_getitem(
dict(x=0, y=1, z=2), vertical_axis=vertical_axis
)
+ if share:
+ axes = {sibling for sibling
+ in self._shared_axes['view'].get_siblings(self)}
+ else:
+ axes = [self]
+
+ for ax in axes:
+ ax.elev = elev
+ ax.azim = azim
+ ax.roll = roll
+ ax._vertical_axis = vertical_axis
+
def set_proj_type(self, proj_type, focal_length=None):
"""
Set the projection type.
@@ -964,7 +978,7 @@ def sharez(self, other):
Axes, and cannot be used if the z-axis is already being shared with
another Axes.
"""
- _api.check_isinstance(maxes._base._AxesBase, other=other)
+ _api.check_isinstance(Axes3D, other=other)
if self._sharez is not None and other is not self._sharez:
raise ValueError("z-axis is already shared")
self._shared_axes["z"].join(self, other)
@@ -975,6 +989,23 @@ def sharez(self, other):
self.set_zlim(z0, z1, emit=False, auto=other.get_autoscalez_on())
self.zaxis._scale = other.zaxis._scale
+ def shareview(self, other):
+ """
+ Share the view angles with *other*.
+
+ This is equivalent to passing ``shareview=other`` when
+ constructing the Axes, and cannot be used if the view angles are
+ already being shared with another Axes.
+ """
+ _api.check_isinstance(Axes3D, other=other)
+ if self._shareview is not None and other is not self._shareview:
+ raise ValueError("view angles are already shared")
+ self._shared_axes["view"].join(self, other)
+ self._shareview = other
+ vertical_axis = {0: "x", 1: "y", 2: "z"}[other._vertical_axis]
+ self.view_init(elev=other.elev, azim=other.azim, roll=other.roll,
+ vertical_axis=vertical_axis, share=True)
+
def clear(self):
# docstring inherited.
super().clear()
@@ -1107,8 +1138,9 @@ def _on_move(self, event):
roll = np.deg2rad(self.roll)
delev = -(dy/h)*180*np.cos(roll) + (dx/w)*180*np.sin(roll)
dazim = -(dy/h)*180*np.sin(roll) - (dx/w)*180*np.cos(roll)
- self.elev = self.elev + delev
- self.azim = self.azim + dazim
+ elev = self.elev + delev
+ azim = self.azim + dazim
+ self.view_init(elev=elev, azim=azim, roll=roll, share=True)
self.stale = True
elif self.button_pressed in self._pan_btn:
|
diff --git a/lib/mpl_toolkits/mplot3d/tests/test_axes3d.py b/lib/mpl_toolkits/mplot3d/tests/test_axes3d.py
index 3b890d31ae44..f4114e7be511 100644
--- a/lib/mpl_toolkits/mplot3d/tests/test_axes3d.py
+++ b/lib/mpl_toolkits/mplot3d/tests/test_axes3d.py
@@ -1689,6 +1689,20 @@ def test_set_zlim():
ax.set_zlim(top=0, zmax=1)
+@check_figures_equal(extensions=["png"])
+def test_shared_view(fig_test, fig_ref):
+ elev, azim, roll = 5, 20, 30
+ ax1 = fig_test.add_subplot(131, projection="3d")
+ ax2 = fig_test.add_subplot(132, projection="3d", shareview=ax1)
+ ax3 = fig_test.add_subplot(133, projection="3d")
+ ax3.shareview(ax1)
+ ax2.view_init(elev=elev, azim=azim, roll=roll, share=True)
+
+ for subplot_num in (131, 132, 133):
+ ax = fig_ref.add_subplot(subplot_num, projection="3d")
+ ax.view_init(elev=elev, azim=azim, roll=roll)
+
+
def test_shared_axes_retick():
fig = plt.figure()
ax1 = fig.add_subplot(211, projection="3d")
|
[
{
"path": "doc/api/toolkits/mplot3d/axes3d.rst",
"old_path": "a/doc/api/toolkits/mplot3d/axes3d.rst",
"new_path": "b/doc/api/toolkits/mplot3d/axes3d.rst",
"metadata": "diff --git a/doc/api/toolkits/mplot3d/axes3d.rst b/doc/api/toolkits/mplot3d/axes3d.rst\nindex 99c57db64d9a..f6d8e2529896 100644\n--- a/doc/api/toolkits/mplot3d/axes3d.rst\n+++ b/doc/api/toolkits/mplot3d/axes3d.rst\n@@ -209,6 +209,7 @@ Sharing\n :nosignatures:\n \n sharez\n+ shareview\n \n \n Interactive\n"
},
{
"path": "doc/users/next_whats_new/3d_plots_shareview.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/3d_plots_shareview.rst",
"metadata": "diff --git a/doc/users/next_whats_new/3d_plots_shareview.rst b/doc/users/next_whats_new/3d_plots_shareview.rst\nnew file mode 100644\nindex 000000000000..e71d06fd9297\n--- /dev/null\n+++ b/doc/users/next_whats_new/3d_plots_shareview.rst\n@@ -0,0 +1,7 @@\n+3D plots can share view angles\n+------------------------------\n+\n+3D plots can now share the same view angles, so that when you rotate one plot\n+the other plots also rotate. This can be done with the *shareview* keyword\n+argument when adding an axes, or by using the *ax1.shareview(ax2)* method of\n+existing 3D axes.\n"
}
] |
3.7
|
4bdae2e004b29d075f96a7dbbee918f7dfb13ed1
|
[
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_ax3d_tickcolour",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_view_init_vertical_axis[x-proj_expected2-axis_lines_expected2-tickdirs_expected2]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_scatter3d_modification[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_scatter3d_sorting[png-True]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_invalid_axes_limits[set_ylim3d-top-inf]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::TestVoxels::test_rgb_data[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_view_init_vertical_axis[z-proj_expected0-axis_lines_expected0-tickdirs_expected0]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_proj_transform",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_contour3d_1d_input",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_panecolor_rcparams[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_invalid_axes_limits[set_zlim3d-bottom-nan]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_plotsurface_1d_raises",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_invalid_axes_limits[set_xlim3d-right-inf]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_tight_layout_text[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_bar3d[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_invalid_axes_limits[set_ylim3d-bottom-inf]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_world",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_set_zlim",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::TestVoxels::test_calling_conventions",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_stem3d[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_lines3d[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_shared_axes_retick",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_invalid_axes_limits[set_zlim3d-bottom-inf]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_arc_pathpatch[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::TestVoxels::test_named_colors[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_margins_errors[ValueError-args1-kwargs1-margin must be greater than -0\\\\.5]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_unautoscale[True-x]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_contourf3d[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_axes3d_cla[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_aspects_adjust_box[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_proj_axes_cube_ortho[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_aspects[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_axes3d_rotated[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_contourf3d_extend[png-min-levels1]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_bar3d_shaded[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_surface3d_masked_strides[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_toolbar_zoom_pan[pan-1-None-expected4]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_plot_scalar[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_axes3d_primary_views[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_scatter3d_color[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_lines_dists_nowarning",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_quiver3d_empty[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_margins_errors[ValueError-args5-kwargs5-margin must be greater than -0\\\\.5]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_pathpatch_3d[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_mutating_input_arrays_y_and_z[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_patch_modification",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_minor_ticks[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_equal_box_aspect[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_marker_draw_order_view_rotated[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_add_collection3d_zs_scalar[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_errorbar3d_errorevery[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_bar3d_notshaded[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_axes3d_ortho[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_contourf3d_extend[png-both-levels0]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_invisible_axes[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_wireframe3dzerocstride[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_mixedsamplesraises",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_margins_errors[TypeError-args7-kwargs7-Cannot pass both positional and keyword]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_ticklabel_format[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_bar3d_colors",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_axes3d_focal_length[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_quiver3d[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_scatter_spiral[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_toolbar_zoom_pan[zoom-1-None-expected0]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::TestVoxels::test_simple[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_toolbar_zoom_pan[zoom-1-y-expected2]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_unautoscale[True-z]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_axes3d_repr",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_inverted_cla",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_poly3dcollection_closed[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_poly3dcollection_alpha[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_tricontour[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_trisurf3d[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_contourf3d_extend[png-max-levels2]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_invalid_axes_limits[set_ylim3d-bottom-nan]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_bar3d_lightsource",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_scatter3d_linewidth_modification[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_invisible_ticks_axis[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_invalid_line_data",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_text_3d[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_get_axis_position",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_Poly3DCollection_get_edgecolor",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_margins_errors[ValueError-args3-kwargs3-margin must be greater than -0\\\\.5]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_plot_3d_from_2d[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::TestVoxels::test_alpha[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_lines_dists[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_line3d_set_get_data_3d",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_poly_collection_2d_to_3d_empty",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_text3d[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_add_collection3d_zs_array[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_margins",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_surface3d_masked[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_unautoscale[True-y]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_margins_errors[ValueError-args4-kwargs4-margin must be greater than -0\\\\.5]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_unautoscale[None-x]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_plot_surface_None_arg[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_invalid_axes_limits[set_xlim3d-left-nan]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_scatter3d[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_axes3d_labelpad[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_trisurf3d_shaded[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_wireframe3dzerostrideraises",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_inverted[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_invalid_axes_limits[set_zlim3d-top-inf]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_unautoscale[False-z]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::TestVoxels::test_xyz[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_invalid_axes_limits[set_ylim3d-top-nan]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_scatter3d_linewidth[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_pan",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_draw_single_lines_from_Nx1",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_subfigure_simple",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_surface3d[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_toolbar_zoom_pan[zoom-1-x-expected1]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_quiver3d_masked[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_axes3d_focal_length_checks",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_marker_draw_order_data_reversed[png-130]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_Poly3DCollection_get_facecolor",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_autoscale",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_grid_off[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_surface3d_shaded[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_contour3d_extend3d[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_computed_zorder[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_margins_errors[ValueError-args0-kwargs0-margin must be greater than -0\\\\.5]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_invalid_axes_limits[set_xlim3d-left-inf]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_text3d_modification[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_patch_collection_modification[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_axes3d_isometric[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_quiver3D_smoke[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_unautoscale[False-y]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_colorbar_pos",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_unautoscale[False-x]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_wireframe3d[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_inverted_zaxis",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_margins_errors[TypeError-args9-kwargs9-Must pass a single positional argument for]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_format_coord",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_errorbar3d[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_margins_errors[ValueError-args2-kwargs2-margin must be greater than -0\\\\.5]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_invalid_axes_limits[set_xlim3d-right-nan]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_unautoscale[None-y]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_scalarmap_update[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_wireframe3dzerorstride[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_margins_errors[TypeError-args8-kwargs8-Cannot pass both positional and keyword]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_mixedsubplots[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_proj_axes_cube[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_toolbar_zoom_pan[pan-1-y-expected6]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_contourf3d_fill[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_unautoscale[None-z]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_toolbar_zoom_pan[pan-1-x-expected5]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::TestVoxels::test_edge_style[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_poly3dcollection_verts_validation",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_invalid_axes_limits[set_zlim3d-top-nan]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_contour3d[png]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_toolbar_zoom_pan[zoom-3-None-expected3]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_margins_errors[TypeError-args6-kwargs6-Cannot pass both positional and keyword]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_scatter3d_sorting[png-False]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_view_init_vertical_axis[y-proj_expected1-axis_lines_expected1-tickdirs_expected1]",
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_marker_draw_order_data_reversed[png--50]"
] |
[
"lib/mpl_toolkits/mplot3d/tests/test_axes3d.py::test_shared_view[png]"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/api/toolkits/mplot3d/axes3d.rst",
"old_path": "a/doc/api/toolkits/mplot3d/axes3d.rst",
"new_path": "b/doc/api/toolkits/mplot3d/axes3d.rst",
"metadata": "diff --git a/doc/api/toolkits/mplot3d/axes3d.rst b/doc/api/toolkits/mplot3d/axes3d.rst\nindex 99c57db64d9a..f6d8e2529896 100644\n--- a/doc/api/toolkits/mplot3d/axes3d.rst\n+++ b/doc/api/toolkits/mplot3d/axes3d.rst\n@@ -209,6 +209,7 @@ Sharing\n :nosignatures:\n \n sharez\n+ shareview\n \n \n Interactive\n"
},
{
"path": "doc/users/next_whats_new/3d_plots_shareview.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/3d_plots_shareview.rst",
"metadata": "diff --git a/doc/users/next_whats_new/3d_plots_shareview.rst b/doc/users/next_whats_new/3d_plots_shareview.rst\nnew file mode 100644\nindex 000000000000..e71d06fd9297\n--- /dev/null\n+++ b/doc/users/next_whats_new/3d_plots_shareview.rst\n@@ -0,0 +1,7 @@\n+3D plots can share view angles\n+------------------------------\n+\n+3D plots can now share the same view angles, so that when you rotate one plot\n+the other plots also rotate. This can be done with the *shareview* keyword\n+argument when adding an axes, or by using the *ax1.shareview(ax2)* method of\n+existing 3D axes.\n"
}
] |
diff --git a/doc/api/toolkits/mplot3d/axes3d.rst b/doc/api/toolkits/mplot3d/axes3d.rst
index 99c57db64d9a..f6d8e2529896 100644
--- a/doc/api/toolkits/mplot3d/axes3d.rst
+++ b/doc/api/toolkits/mplot3d/axes3d.rst
@@ -209,6 +209,7 @@ Sharing
:nosignatures:
sharez
+ shareview
Interactive
diff --git a/doc/users/next_whats_new/3d_plots_shareview.rst b/doc/users/next_whats_new/3d_plots_shareview.rst
new file mode 100644
index 000000000000..e71d06fd9297
--- /dev/null
+++ b/doc/users/next_whats_new/3d_plots_shareview.rst
@@ -0,0 +1,7 @@
+3D plots can share view angles
+------------------------------
+
+3D plots can now share the same view angles, so that when you rotate one plot
+the other plots also rotate. This can be done with the *shareview* keyword
+argument when adding an axes, or by using the *ax1.shareview(ax2)* method of
+existing 3D axes.
|
matplotlib/matplotlib
|
matplotlib__matplotlib-25686
|
https://github.com/matplotlib/matplotlib/pull/25686
|
diff --git a/doc/users/next_whats_new/get_suptitle.rst b/doc/users/next_whats_new/get_suptitle.rst
new file mode 100644
index 000000000000..b03ad10b1b4c
--- /dev/null
+++ b/doc/users/next_whats_new/get_suptitle.rst
@@ -0,0 +1,4 @@
+``Figure.get_suptitle()``, ``Figure.get_supxlabel()``, ``Figure.get_supylabel()``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+These methods return the strings set by ``Figure.suptitle()``, ``Figure.supxlabel()``
+and ``Figure.supylabel()`` respectively.
diff --git a/lib/matplotlib/figure.py b/lib/matplotlib/figure.py
index 7fdcc8cb6627..970bf957d4bf 100644
--- a/lib/matplotlib/figure.py
+++ b/lib/matplotlib/figure.py
@@ -388,6 +388,11 @@ def suptitle(self, t, **kwargs):
'size': 'figure.titlesize', 'weight': 'figure.titleweight'}
return self._suplabels(t, info, **kwargs)
+ def get_suptitle(self):
+ """Return the suptitle as string or an empty string if not set."""
+ text_obj = self._suptitle
+ return "" if text_obj is None else text_obj.get_text()
+
@_docstring.Substitution(x0=0.5, y0=0.01, name='supxlabel', ha='center',
va='bottom', rc='label')
@_docstring.copy(_suplabels)
@@ -398,6 +403,11 @@ def supxlabel(self, t, **kwargs):
'size': 'figure.labelsize', 'weight': 'figure.labelweight'}
return self._suplabels(t, info, **kwargs)
+ def get_supxlabel(self):
+ """Return the supxlabel as string or an empty string if not set."""
+ text_obj = self._supxlabel
+ return "" if text_obj is None else text_obj.get_text()
+
@_docstring.Substitution(x0=0.02, y0=0.5, name='supylabel', ha='left',
va='center', rc='label')
@_docstring.copy(_suplabels)
@@ -409,6 +419,11 @@ def supylabel(self, t, **kwargs):
'weight': 'figure.labelweight'}
return self._suplabels(t, info, **kwargs)
+ def get_supylabel(self):
+ """Return the supylabel as string or an empty string if not set."""
+ text_obj = self._supylabel
+ return "" if text_obj is None else text_obj.get_text()
+
def get_edgecolor(self):
"""Get the edge color of the Figure rectangle."""
return self.patch.get_edgecolor()
diff --git a/lib/matplotlib/figure.pyi b/lib/matplotlib/figure.pyi
index ee21892f32ac..f4c31506a2e1 100644
--- a/lib/matplotlib/figure.pyi
+++ b/lib/matplotlib/figure.pyi
@@ -90,8 +90,11 @@ class FigureBase(Artist):
def get_children(self) -> list[Artist]: ...
def contains(self, mouseevent: MouseEvent) -> tuple[bool, dict[Any, Any]]: ...
def suptitle(self, t: str, **kwargs) -> Text: ...
+ def get_suptitle(self) -> str: ...
def supxlabel(self, t: str, **kwargs) -> Text: ...
+ def get_supxlabel(self) -> str: ...
def supylabel(self, t: str, **kwargs) -> Text: ...
+ def get_supylabel(self) -> str: ...
def get_edgecolor(self) -> ColorType: ...
def get_facecolor(self) -> ColorType: ...
def get_frameon(self) -> bool: ...
|
diff --git a/lib/matplotlib/tests/test_figure.py b/lib/matplotlib/tests/test_figure.py
index 4188ca878fed..d8f137ddd61a 100644
--- a/lib/matplotlib/tests/test_figure.py
+++ b/lib/matplotlib/tests/test_figure.py
@@ -302,6 +302,19 @@ def test_suptitle_subfigures():
assert sf2.get_facecolor() == (1.0, 1.0, 1.0, 1.0)
+def test_get_suptitle_supxlabel_supylabel():
+ fig, ax = plt.subplots()
+ assert fig.get_suptitle() == ""
+ assert fig.get_supxlabel() == ""
+ assert fig.get_supylabel() == ""
+ fig.suptitle('suptitle')
+ assert fig.get_suptitle() == 'suptitle'
+ fig.supxlabel('supxlabel')
+ assert fig.get_supxlabel() == 'supxlabel'
+ fig.supylabel('supylabel')
+ assert fig.get_supylabel() == 'supylabel'
+
+
@image_comparison(['alpha_background'],
# only test png and svg. The PDF output appears correct,
# but Ghostscript does not preserve the background color.
|
[
{
"path": "doc/users/next_whats_new/get_suptitle.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/get_suptitle.rst",
"metadata": "diff --git a/doc/users/next_whats_new/get_suptitle.rst b/doc/users/next_whats_new/get_suptitle.rst\nnew file mode 100644\nindex 000000000000..b03ad10b1b4c\n--- /dev/null\n+++ b/doc/users/next_whats_new/get_suptitle.rst\n@@ -0,0 +1,4 @@\n+``Figure.get_suptitle()``, ``Figure.get_supxlabel()``, ``Figure.get_supylabel()``\n+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n+These methods return the strings set by ``Figure.suptitle()``, ``Figure.supxlabel()``\n+and ``Figure.supylabel()`` respectively.\n"
}
] |
3.7
|
b86ebbafe4673583345d0a01a6ea205af34c58dc
|
[
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"lib/matplotlib/tests/test_figure.py::test_tightbbox_box_aspect[svg]",
"lib/matplotlib/tests/test_figure.py::test_iterability_axes_argument",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_basic[x3-png]",
"lib/matplotlib/tests/test_figure.py::test_savefig",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_nested_width_ratios",
"lib/matplotlib/tests/test_figure.py::test_change_dpi",
"lib/matplotlib/tests/test_figure.py::test_too_many_figures",
"lib/matplotlib/tests/test_figure.py::test_animated_with_canvas_change[svg]",
"lib/matplotlib/tests/test_figure.py::test_figure_legend[pdf]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_basic[x1-png]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_empty[x1-SKIP-png]",
"lib/matplotlib/tests/test_figure.py::test_invalid_figure_size[1-nan]",
"lib/matplotlib/tests/test_figure.py::test_figaspect",
"lib/matplotlib/tests/test_figure.py::test_subplots_shareax_loglabels",
"lib/matplotlib/tests/test_figure.py::test_figure_legend[svg]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_user_order[acb]",
"lib/matplotlib/tests/test_figure.py::test_add_subplot_subclass",
"lib/matplotlib/tests/test_figure.py::test_alpha[png]",
"lib/matplotlib/tests/test_figure.py::test_set_fig_size",
"lib/matplotlib/tests/test_figure.py::test_invalid_figure_add_axes",
"lib/matplotlib/tests/test_figure.py::test_figure_label",
"lib/matplotlib/tests/test_figure.py::test_valid_layouts",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_subplot_kw[subplot_kw1-png]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_fail[AAA\\nc\\nBBB-All of the rows must be the same length]",
"lib/matplotlib/tests/test_figure.py::test_invalid_figure_size[inf-1]",
"lib/matplotlib/tests/test_figure.py::test_gridspec_no_mutate_input",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_hashable_keys[png]",
"lib/matplotlib/tests/test_figure.py::test_figure[pdf]",
"lib/matplotlib/tests/test_figure.py::test_gca",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_fail[x3-All of the rows must be the same length]",
"lib/matplotlib/tests/test_figure.py::test_subfigure_dpi",
"lib/matplotlib/tests/test_figure.py::test_axes_removal",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_nested_tuple[png]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_fail[x1-There are duplicate keys .* between the outer layout]",
"lib/matplotlib/tests/test_figure.py::test_autofmt_xdate[both]",
"lib/matplotlib/tests/test_figure.py::test_add_axes_kwargs",
"lib/matplotlib/tests/test_figure.py::test_tightbbox",
"lib/matplotlib/tests/test_figure.py::test_add_subplot_invalid",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_empty[x3-None-png]",
"lib/matplotlib/tests/test_figure.py::test_clf_not_redefined",
"lib/matplotlib/tests/test_figure.py::test_add_subplot_twotuple",
"lib/matplotlib/tests/test_figure.py::test_animated_with_canvas_change[pdf]",
"lib/matplotlib/tests/test_figure.py::test_figure[png]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_nested[png]",
"lib/matplotlib/tests/test_figure.py::test_savefig_preserve_layout_engine",
"lib/matplotlib/tests/test_figure.py::test_subfigure_scatter_size[png]",
"lib/matplotlib/tests/test_figure.py::test_figure[svg]",
"lib/matplotlib/tests/test_figure.py::test_savefig_transparent[png]",
"lib/matplotlib/tests/test_figure.py::test_fspath[ps]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_single_str_input[\\nAAA\\nBBB\\n-png]",
"lib/matplotlib/tests/test_figure.py::test_deepcopy",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_user_order[cab]",
"lib/matplotlib/tests/test_figure.py::test_savefig_metadata_error[tiff]",
"lib/matplotlib/tests/test_figure.py::test_picking_does_not_stale",
"lib/matplotlib/tests/test_figure.py::test_savefig_metadata_error[rgba]",
"lib/matplotlib/tests/test_figure.py::test_waitforbuttonpress",
"lib/matplotlib/tests/test_figure.py::test_subfigure_spanning",
"lib/matplotlib/tests/test_figure.py::test_layout_change_warning[compressed]",
"lib/matplotlib/tests/test_figure.py::test_invalid_figure_size[-1-1]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_user_order[abc]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_empty[x0-None-png]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_nested_user_order",
"lib/matplotlib/tests/test_figure.py::test_savefig_metadata_error[webp]",
"lib/matplotlib/tests/test_figure.py::test_subfigure[png]",
"lib/matplotlib/tests/test_figure.py::test_rcparams[png]",
"lib/matplotlib/tests/test_figure.py::test_animated_with_canvas_change[eps]",
"lib/matplotlib/tests/test_figure.py::test_alpha[svg]",
"lib/matplotlib/tests/test_figure.py::test_savefig_metadata_error[raw]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_basic[x0-png]",
"lib/matplotlib/tests/test_figure.py::test_suptitle_fontproperties",
"lib/matplotlib/tests/test_figure.py::test_fspath[png]",
"lib/matplotlib/tests/test_figure.py::test_reused_gridspec",
"lib/matplotlib/tests/test_figure.py::test_savefig_pixel_ratio[Agg]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_user_order[bac]",
"lib/matplotlib/tests/test_figure.py::test_align_labels[png]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_user_order[cba]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_fail_list_of_str",
"lib/matplotlib/tests/test_figure.py::test_savefig_metadata[ps]",
"lib/matplotlib/tests/test_figure.py::test_add_artist[png]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_subplot_kw[None-png]",
"lib/matplotlib/tests/test_figure.py::test_fignum_exists",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_share_all",
"lib/matplotlib/tests/test_figure.py::test_add_artist[pdf]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_string_parser",
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"lib/matplotlib/tests/test_figure.py::test_savefig_metadata_error[tif]",
"lib/matplotlib/tests/test_figure.py::test_savefig_metadata[svg]",
"lib/matplotlib/tests/test_figure.py::test_layout_change_warning[constrained]",
"lib/matplotlib/tests/test_figure.py::test_figure_clear[clear]",
"lib/matplotlib/tests/test_figure.py::test_suptitle[png]",
"lib/matplotlib/tests/test_figure.py::test_savefig_locate_colorbar",
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"lib/matplotlib/tests/test_figure.py::test_savefig_metadata[svgz]",
"lib/matplotlib/tests/test_figure.py::test_suptitle[pdf]",
"lib/matplotlib/tests/test_figure.py::test_clf_keyword",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_empty[x2-0-png]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_extra_per_subplot_kw",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_nested_height_ratios",
"lib/matplotlib/tests/test_figure.py::test_savefig_metadata[pdf]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_per_subplot_kw_expander",
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"lib/matplotlib/tests/test_figure.py::test_savefig_warns",
"lib/matplotlib/tests/test_figure.py::test_kwargs_pass",
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"lib/matplotlib/tests/test_figure.py::test_figure_repr",
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"lib/matplotlib/tests/test_figure.py::test_fspath[eps]",
"lib/matplotlib/tests/test_figure.py::test_autofmt_xdate[minor]",
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"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_fail[x0-(?m)we found that the label .A. specifies a non-rectangular or non-contiguous area.]",
"lib/matplotlib/tests/test_figure.py::test_axes_remove",
"lib/matplotlib/tests/test_figure.py::test_subfigure_tightbbox",
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"lib/matplotlib/tests/test_figure.py::test_align_labels_stray_axes",
"lib/matplotlib/tests/test_figure.py::test_subfigure_ss[png]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_single_str_input[ABC\\nDEF-png]",
"lib/matplotlib/tests/test_figure.py::test_subfigure_pdf",
"lib/matplotlib/tests/test_figure.py::test_removed_axis",
"lib/matplotlib/tests/test_figure.py::test_unpickle_with_device_pixel_ratio",
"lib/matplotlib/tests/test_figure.py::test_figure_clear[clf]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_user_order[bca]",
"lib/matplotlib/tests/test_figure.py::test_savefig_metadata[png]",
"lib/matplotlib/tests/test_figure.py::test_add_subplot_kwargs",
"lib/matplotlib/tests/test_figure.py::test_suptitle[svg]",
"lib/matplotlib/tests/test_figure.py::TestSubplotMosaic::test_basic[x2-png]",
"lib/matplotlib/tests/test_figure.py::test_savefig_metadata_error[jpeg]"
] |
[
"lib/matplotlib/tests/test_figure.py::test_get_suptitle_supxlabel_supylabel"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/users/next_whats_new/get_suptitle.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/get_suptitle.rst",
"metadata": "diff --git a/doc/users/next_whats_new/get_suptitle.rst b/doc/users/next_whats_new/get_suptitle.rst\nnew file mode 100644\nindex 000000000000..b03ad10b1b4c\n--- /dev/null\n+++ b/doc/users/next_whats_new/get_suptitle.rst\n@@ -0,0 +1,4 @@\n+``Figure.get_suptitle()``, ``Figure.get_supxlabel()``, ``Figure.get_supylabel()``\n+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n+These methods return the strings set by ``Figure.suptitle()``, ``Figure.supxlabel()``\n+and ``Figure.supylabel()`` respectively.\n"
}
] |
diff --git a/doc/users/next_whats_new/get_suptitle.rst b/doc/users/next_whats_new/get_suptitle.rst
new file mode 100644
index 000000000000..b03ad10b1b4c
--- /dev/null
+++ b/doc/users/next_whats_new/get_suptitle.rst
@@ -0,0 +1,4 @@
+``Figure.get_suptitle()``, ``Figure.get_supxlabel()``, ``Figure.get_supylabel()``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+These methods return the strings set by ``Figure.suptitle()``, ``Figure.supxlabel()``
+and ``Figure.supylabel()`` respectively.
|
matplotlib/matplotlib
|
matplotlib__matplotlib-23191
|
https://github.com/matplotlib/matplotlib/pull/23191
|
diff --git a/doc/users/next_whats_new/width_height_ratios.rst b/doc/users/next_whats_new/width_height_ratios.rst
new file mode 100644
index 000000000000..017c34a55cc4
--- /dev/null
+++ b/doc/users/next_whats_new/width_height_ratios.rst
@@ -0,0 +1,7 @@
+``subplots``, ``subplot_mosaic`` accept *height_ratios* and *width_ratios* arguments
+------------------------------------------------------------------------------------
+
+The relative width and height of columns and rows in `~.Figure.subplots` and
+`~.Figure.subplot_mosaic` can be controlled by passing *height_ratios* and
+*width_ratios* keyword arguments to the methods. Previously, this required
+passing the ratios in *gridspec_kws* arguments.
diff --git a/lib/matplotlib/figure.py b/lib/matplotlib/figure.py
index f8aa99d48a09..dedaaa7dcf5a 100644
--- a/lib/matplotlib/figure.py
+++ b/lib/matplotlib/figure.py
@@ -764,7 +764,8 @@ def _add_axes_internal(self, ax, key):
return ax
def subplots(self, nrows=1, ncols=1, *, sharex=False, sharey=False,
- squeeze=True, subplot_kw=None, gridspec_kw=None):
+ squeeze=True, width_ratios=None, height_ratios=None,
+ subplot_kw=None, gridspec_kw=None):
"""
Add a set of subplots to this figure.
@@ -807,6 +808,18 @@ def subplots(self, nrows=1, ncols=1, *, sharex=False, sharey=False,
is always a 2D array containing Axes instances, even if it ends
up being 1x1.
+ width_ratios : array-like of length *ncols*, optional
+ Defines the relative widths of the columns. Each column gets a
+ relative width of ``width_ratios[i] / sum(width_ratios)``.
+ If not given, all columns will have the same width. Equivalent
+ to ``gridspec_kw={'width_ratios': [...]}``.
+
+ height_ratios : array-like of length *nrows*, optional
+ Defines the relative heights of the rows. Each row gets a
+ relative height of ``height_ratios[i] / sum(height_ratios)``.
+ If not given, all rows will have the same height. Equivalent
+ to ``gridspec_kw={'height_ratios': [...]}``.
+
subplot_kw : dict, optional
Dict with keywords passed to the `.Figure.add_subplot` call used to
create each subplot.
@@ -871,6 +884,17 @@ def subplots(self, nrows=1, ncols=1, *, sharex=False, sharey=False,
"""
if gridspec_kw is None:
gridspec_kw = {}
+ if height_ratios is not None:
+ if 'height_ratios' in gridspec_kw:
+ raise ValueError("'height_ratios' must not be defined both as "
+ "parameter and as key in 'gridspec_kw'")
+ gridspec_kw['height_ratios'] = height_ratios
+ if width_ratios is not None:
+ if 'width_ratios' in gridspec_kw:
+ raise ValueError("'width_ratios' must not be defined both as "
+ "parameter and as key in 'gridspec_kw'")
+ gridspec_kw['width_ratios'] = width_ratios
+
gs = self.add_gridspec(nrows, ncols, figure=self, **gridspec_kw)
axs = gs.subplots(sharex=sharex, sharey=sharey, squeeze=squeeze,
subplot_kw=subplot_kw)
@@ -1683,7 +1707,8 @@ def _normalize_grid_string(layout):
return [list(ln) for ln in layout.strip('\n').split('\n')]
def subplot_mosaic(self, mosaic, *, sharex=False, sharey=False,
- subplot_kw=None, gridspec_kw=None, empty_sentinel='.'):
+ width_ratios=None, height_ratios=None,
+ empty_sentinel='.', subplot_kw=None, gridspec_kw=None):
"""
Build a layout of Axes based on ASCII art or nested lists.
@@ -1739,6 +1764,18 @@ def subplot_mosaic(self, mosaic, *, sharex=False, sharey=False,
units behave as for `subplots`. If False, each subplot's x- or
y-axis will be independent.
+ width_ratios : array-like of length *ncols*, optional
+ Defines the relative widths of the columns. Each column gets a
+ relative width of ``width_ratios[i] / sum(width_ratios)``.
+ If not given, all columns will have the same width. Equivalent
+ to ``gridspec_kw={'width_ratios': [...]}``.
+
+ height_ratios : array-like of length *nrows*, optional
+ Defines the relative heights of the rows. Each row gets a
+ relative height of ``height_ratios[i] / sum(height_ratios)``.
+ If not given, all rows will have the same height. Equivalent
+ to ``gridspec_kw={'height_ratios': [...]}``.
+
subplot_kw : dict, optional
Dictionary with keywords passed to the `.Figure.add_subplot` call
used to create each subplot.
@@ -1763,6 +1800,17 @@ def subplot_mosaic(self, mosaic, *, sharex=False, sharey=False,
"""
subplot_kw = subplot_kw or {}
gridspec_kw = gridspec_kw or {}
+ if height_ratios is not None:
+ if 'height_ratios' in gridspec_kw:
+ raise ValueError("'height_ratios' must not be defined both as "
+ "parameter and as key in 'gridspec_kw'")
+ gridspec_kw['height_ratios'] = height_ratios
+ if width_ratios is not None:
+ if 'width_ratios' in gridspec_kw:
+ raise ValueError("'width_ratios' must not be defined both as "
+ "parameter and as key in 'gridspec_kw'")
+ gridspec_kw['width_ratios'] = width_ratios
+
# special-case string input
if isinstance(mosaic, str):
mosaic = self._normalize_grid_string(mosaic)
diff --git a/lib/matplotlib/pyplot.py b/lib/matplotlib/pyplot.py
index e3c66ea67cad..faa023f8c082 100644
--- a/lib/matplotlib/pyplot.py
+++ b/lib/matplotlib/pyplot.py
@@ -1323,6 +1323,7 @@ def subplot(*args, **kwargs):
def subplots(nrows=1, ncols=1, *, sharex=False, sharey=False, squeeze=True,
+ width_ratios=None, height_ratios=None,
subplot_kw=None, gridspec_kw=None, **fig_kw):
"""
Create a figure and a set of subplots.
@@ -1368,6 +1369,18 @@ def subplots(nrows=1, ncols=1, *, sharex=False, sharey=False, squeeze=True,
always a 2D array containing Axes instances, even if it ends up
being 1x1.
+ width_ratios : array-like of length *ncols*, optional
+ Defines the relative widths of the columns. Each column gets a
+ relative width of ``width_ratios[i] / sum(width_ratios)``.
+ If not given, all columns will have the same width. Equivalent
+ to ``gridspec_kw={'width_ratios': [...]}``.
+
+ height_ratios : array-like of length *nrows*, optional
+ Defines the relative heights of the rows. Each row gets a
+ relative height of ``height_ratios[i] / sum(height_ratios)``.
+ If not given, all rows will have the same height. Convenience
+ for ``gridspec_kw={'height_ratios': [...]}``.
+
subplot_kw : dict, optional
Dict with keywords passed to the
`~matplotlib.figure.Figure.add_subplot` call used to create each
@@ -1458,13 +1471,14 @@ def subplots(nrows=1, ncols=1, *, sharex=False, sharey=False, squeeze=True,
fig = figure(**fig_kw)
axs = fig.subplots(nrows=nrows, ncols=ncols, sharex=sharex, sharey=sharey,
squeeze=squeeze, subplot_kw=subplot_kw,
- gridspec_kw=gridspec_kw)
+ gridspec_kw=gridspec_kw, height_ratios=height_ratios,
+ width_ratios=width_ratios)
return fig, axs
def subplot_mosaic(mosaic, *, sharex=False, sharey=False,
- subplot_kw=None, gridspec_kw=None, empty_sentinel='.',
- **fig_kw):
+ width_ratios=None, height_ratios=None, empty_sentinel='.',
+ subplot_kw=None, gridspec_kw=None, **fig_kw):
"""
Build a layout of Axes based on ASCII art or nested lists.
@@ -1515,13 +1529,17 @@ def subplot_mosaic(mosaic, *, sharex=False, sharey=False,
behave as for `subplots`. If False, each subplot's x- or y-axis will
be independent.
- subplot_kw : dict, optional
- Dictionary with keywords passed to the `.Figure.add_subplot` call
- used to create each subplot.
+ width_ratios : array-like of length *ncols*, optional
+ Defines the relative widths of the columns. Each column gets a
+ relative width of ``width_ratios[i] / sum(width_ratios)``.
+ If not given, all columns will have the same width. Convenience
+ for ``gridspec_kw={'width_ratios': [...]}``.
- gridspec_kw : dict, optional
- Dictionary with keywords passed to the `.GridSpec` constructor used
- to create the grid the subplots are placed on.
+ height_ratios : array-like of length *nrows*, optional
+ Defines the relative heights of the rows. Each row gets a
+ relative height of ``height_ratios[i] / sum(height_ratios)``.
+ If not given, all rows will have the same height. Convenience
+ for ``gridspec_kw={'height_ratios': [...]}``.
empty_sentinel : object, optional
Entry in the layout to mean "leave this space empty". Defaults
@@ -1529,6 +1547,14 @@ def subplot_mosaic(mosaic, *, sharex=False, sharey=False,
`inspect.cleandoc` to remove leading white space, which may
interfere with using white-space as the empty sentinel.
+ subplot_kw : dict, optional
+ Dictionary with keywords passed to the `.Figure.add_subplot` call
+ used to create each subplot.
+
+ gridspec_kw : dict, optional
+ Dictionary with keywords passed to the `.GridSpec` constructor used
+ to create the grid the subplots are placed on.
+
**fig_kw
All additional keyword arguments are passed to the
`.pyplot.figure` call.
@@ -1547,6 +1573,7 @@ def subplot_mosaic(mosaic, *, sharex=False, sharey=False,
fig = figure(**fig_kw)
ax_dict = fig.subplot_mosaic(
mosaic, sharex=sharex, sharey=sharey,
+ height_ratios=height_ratios, width_ratios=width_ratios,
subplot_kw=subplot_kw, gridspec_kw=gridspec_kw,
empty_sentinel=empty_sentinel
)
diff --git a/tutorials/provisional/mosaic.py b/tutorials/provisional/mosaic.py
index 05623e852ed7..202ada6eb332 100644
--- a/tutorials/provisional/mosaic.py
+++ b/tutorials/provisional/mosaic.py
@@ -219,12 +219,10 @@ def identify_axes(ax_dict, fontsize=48):
bAc
.d.
""",
- gridspec_kw={
- # set the height ratios between the rows
- "height_ratios": [1, 3.5, 1],
- # set the width ratios between the columns
- "width_ratios": [1, 3.5, 1],
- },
+ # set the height ratios between the rows
+ height_ratios=[1, 3.5, 1],
+ # set the width ratios between the columns
+ width_ratios=[1, 3.5, 1],
)
identify_axes(axd)
@@ -301,7 +299,7 @@ def identify_axes(ax_dict, fontsize=48):
["main", "BLANK"],
],
empty_sentinel="BLANK",
- gridspec_kw={"width_ratios": [2, 1]},
+ width_ratios=[2, 1],
)
identify_axes(axd)
|
diff --git a/lib/matplotlib/tests/test_subplots.py b/lib/matplotlib/tests/test_subplots.py
index 8d707e014749..f299440ef53e 100644
--- a/lib/matplotlib/tests/test_subplots.py
+++ b/lib/matplotlib/tests/test_subplots.py
@@ -4,7 +4,7 @@
import pytest
import matplotlib.pyplot as plt
-from matplotlib.testing.decorators import image_comparison
+from matplotlib.testing.decorators import check_figures_equal, image_comparison
import matplotlib.axes as maxes
@@ -212,3 +212,42 @@ def test_dont_mutate_kwargs():
def test_subplot_factory_reapplication():
assert maxes.subplot_class_factory(maxes.Axes) is maxes.Subplot
assert maxes.subplot_class_factory(maxes.Subplot) is maxes.Subplot
+
+
+@pytest.mark.parametrize("width_ratios", [None, [1, 3, 2]])
+@pytest.mark.parametrize("height_ratios", [None, [1, 2]])
+@check_figures_equal(extensions=['png'])
+def test_width_and_height_ratios(fig_test, fig_ref,
+ height_ratios, width_ratios):
+ fig_test.subplots(2, 3, height_ratios=height_ratios,
+ width_ratios=width_ratios)
+ fig_ref.subplots(2, 3, gridspec_kw={
+ 'height_ratios': height_ratios,
+ 'width_ratios': width_ratios})
+
+
+@pytest.mark.parametrize("width_ratios", [None, [1, 3, 2]])
+@pytest.mark.parametrize("height_ratios", [None, [1, 2]])
+@check_figures_equal(extensions=['png'])
+def test_width_and_height_ratios_mosaic(fig_test, fig_ref,
+ height_ratios, width_ratios):
+ mosaic_spec = [['A', 'B', 'B'], ['A', 'C', 'D']]
+ fig_test.subplot_mosaic(mosaic_spec, height_ratios=height_ratios,
+ width_ratios=width_ratios)
+ fig_ref.subplot_mosaic(mosaic_spec, gridspec_kw={
+ 'height_ratios': height_ratios,
+ 'width_ratios': width_ratios})
+
+
+@pytest.mark.parametrize('method,args', [
+ ('subplots', (2, 3)),
+ ('subplot_mosaic', ('abc;def', ))
+ ]
+)
+def test_ratio_overlapping_kws(method, args):
+ with pytest.raises(ValueError, match='height_ratios'):
+ getattr(plt, method)(*args, height_ratios=[1, 2],
+ gridspec_kw={'height_ratios': [1, 2]})
+ with pytest.raises(ValueError, match='width_ratios'):
+ getattr(plt, method)(*args, width_ratios=[1, 2, 3],
+ gridspec_kw={'width_ratios': [1, 2, 3]})
|
[
{
"path": "doc/users/next_whats_new/width_height_ratios.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/width_height_ratios.rst",
"metadata": "diff --git a/doc/users/next_whats_new/width_height_ratios.rst b/doc/users/next_whats_new/width_height_ratios.rst\nnew file mode 100644\nindex 000000000000..017c34a55cc4\n--- /dev/null\n+++ b/doc/users/next_whats_new/width_height_ratios.rst\n@@ -0,0 +1,7 @@\n+``subplots``, ``subplot_mosaic`` accept *height_ratios* and *width_ratios* arguments\n+------------------------------------------------------------------------------------\n+\n+The relative width and height of columns and rows in `~.Figure.subplots` and\n+`~.Figure.subplot_mosaic` can be controlled by passing *height_ratios* and\n+*width_ratios* keyword arguments to the methods. Previously, this required\n+passing the ratios in *gridspec_kws* arguments.\n"
}
] |
3.5
|
3522217386b0ba888e47d931a79c87085d51137b
|
[
"lib/matplotlib/tests/test_subplots.py::test_subplots_hide_axislabels[right-top]",
"lib/matplotlib/tests/test_subplots.py::test_label_outer_span",
"lib/matplotlib/tests/test_subplots.py::test_subplots_hide_axislabels[left-bottom]",
"lib/matplotlib/tests/test_subplots.py::test_subplots_hide_ticklabels[True-True-True-False]",
"lib/matplotlib/tests/test_subplots.py::test_shared_and_moved",
"lib/matplotlib/tests/test_subplots.py::test_exceptions",
"lib/matplotlib/tests/test_subplots.py::test_subplots_hide_ticklabels[False-False-False-True]",
"lib/matplotlib/tests/test_subplots.py::test_subplots_hide_ticklabels[True-False-True-True]",
"lib/matplotlib/tests/test_subplots.py::test_subplots_offsettext[pdf]",
"lib/matplotlib/tests/test_subplots.py::test_subplot_factory_reapplication",
"lib/matplotlib/tests/test_subplots.py::test_subplots_hide_ticklabels[False-False-False-False]",
"lib/matplotlib/tests/test_subplots.py::test_subplots_hide_ticklabels[False-True-True-True]",
"lib/matplotlib/tests/test_subplots.py::test_subplots_hide_ticklabels[True-False-False-False]",
"lib/matplotlib/tests/test_subplots.py::test_subplots_hide_ticklabels[False-False-True-False]",
"lib/matplotlib/tests/test_subplots.py::test_subplots_hide_ticklabels[False-False-True-True]",
"lib/matplotlib/tests/test_subplots.py::test_subplots_hide_ticklabels[True-False-True-False]",
"lib/matplotlib/tests/test_subplots.py::test_shared",
"lib/matplotlib/tests/test_subplots.py::test_subplots_hide_ticklabels[False-True-True-False]",
"lib/matplotlib/tests/test_subplots.py::test_subplots_hide_ticklabels[True-True-False-False]",
"lib/matplotlib/tests/test_subplots.py::test_subplots_hide_ticklabels[True-True-False-True]",
"lib/matplotlib/tests/test_subplots.py::test_subplots_hide_axislabels[left-top]",
"lib/matplotlib/tests/test_subplots.py::test_subplots_hide_ticklabels[False-True-False-True]",
"lib/matplotlib/tests/test_subplots.py::test_subplots_hide_ticklabels[True-False-False-True]",
"lib/matplotlib/tests/test_subplots.py::test_subplots_offsettext[svg]",
"lib/matplotlib/tests/test_subplots.py::test_dont_mutate_kwargs",
"lib/matplotlib/tests/test_subplots.py::test_get_gridspec",
"lib/matplotlib/tests/test_subplots.py::test_subplots_hide_ticklabels[False-True-False-False]",
"lib/matplotlib/tests/test_subplots.py::test_subplots_offsettext[png]",
"lib/matplotlib/tests/test_subplots.py::test_subplots_hide_ticklabels[True-True-True-True]",
"lib/matplotlib/tests/test_subplots.py::test_subplots_hide_axislabels[right-bottom]"
] |
[
"lib/matplotlib/tests/test_subplots.py::test_width_and_height_ratios_mosaic[png-height_ratios1-width_ratios1]",
"lib/matplotlib/tests/test_subplots.py::test_ratio_overlapping_kws[subplot_mosaic-args1]",
"lib/matplotlib/tests/test_subplots.py::test_width_and_height_ratios[png-None-width_ratios1]",
"lib/matplotlib/tests/test_subplots.py::test_width_and_height_ratios_mosaic[png-None-None]",
"lib/matplotlib/tests/test_subplots.py::test_width_and_height_ratios_mosaic[png-height_ratios1-None]",
"lib/matplotlib/tests/test_subplots.py::test_width_and_height_ratios[png-None-None]",
"lib/matplotlib/tests/test_subplots.py::test_width_and_height_ratios[png-height_ratios1-width_ratios1]",
"lib/matplotlib/tests/test_subplots.py::test_width_and_height_ratios[png-height_ratios1-None]",
"lib/matplotlib/tests/test_subplots.py::test_width_and_height_ratios_mosaic[png-None-width_ratios1]",
"lib/matplotlib/tests/test_subplots.py::test_ratio_overlapping_kws[subplots-args0]"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/users/next_whats_new/width_height_ratios.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/width_height_ratios.rst",
"metadata": "diff --git a/doc/users/next_whats_new/width_height_ratios.rst b/doc/users/next_whats_new/width_height_ratios.rst\nnew file mode 100644\nindex 000000000000..017c34a55cc4\n--- /dev/null\n+++ b/doc/users/next_whats_new/width_height_ratios.rst\n@@ -0,0 +1,7 @@\n+``subplots``, ``subplot_mosaic`` accept *height_ratios* and *width_ratios* arguments\n+------------------------------------------------------------------------------------\n+\n+The relative width and height of columns and rows in `~.Figure.subplots` and\n+`~.Figure.subplot_mosaic` can be controlled by passing *height_ratios* and\n+*width_ratios* keyword arguments to the methods. Previously, this required\n+passing the ratios in *gridspec_kws* arguments.\n"
}
] |
diff --git a/doc/users/next_whats_new/width_height_ratios.rst b/doc/users/next_whats_new/width_height_ratios.rst
new file mode 100644
index 000000000000..017c34a55cc4
--- /dev/null
+++ b/doc/users/next_whats_new/width_height_ratios.rst
@@ -0,0 +1,7 @@
+``subplots``, ``subplot_mosaic`` accept *height_ratios* and *width_ratios* arguments
+------------------------------------------------------------------------------------
+
+The relative width and height of columns and rows in `~.Figure.subplots` and
+`~.Figure.subplot_mosaic` can be controlled by passing *height_ratios* and
+*width_ratios* keyword arguments to the methods. Previously, this required
+passing the ratios in *gridspec_kws* arguments.
|
matplotlib/matplotlib
|
matplotlib__matplotlib-21143
|
https://github.com/matplotlib/matplotlib/pull/21143
|
diff --git a/doc/api/next_api_changes/behavior/19515-GL.rst b/doc/api/next_api_changes/behavior/19515-GL.rst
new file mode 100644
index 000000000000..cb6d925b797c
--- /dev/null
+++ b/doc/api/next_api_changes/behavior/19515-GL.rst
@@ -0,0 +1,10 @@
+Colorbars now have pan and zoom functionality
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Interactive plots with colorbars can now be zoomed and panned on
+the colorbar axis. This adjusts the *vmin* and *vmax* of the
+``ScalarMappable`` associated with the colorbar. This is currently
+only enabled for continuous norms. Norms used with contourf and
+categoricals, such as ``BoundaryNorm`` and ``NoNorm``, have the
+interactive capability disabled by default. ``cb.ax.set_navigate()``
+can be used to set whether a colorbar axes is interactive or not.
diff --git a/lib/matplotlib/axes/_base.py b/lib/matplotlib/axes/_base.py
index 97ed781b00f6..7cea32d849d0 100644
--- a/lib/matplotlib/axes/_base.py
+++ b/lib/matplotlib/axes/_base.py
@@ -4255,41 +4255,14 @@ def _set_view(self, view):
self.set_xlim((xmin, xmax))
self.set_ylim((ymin, ymax))
- def _set_view_from_bbox(self, bbox, direction='in',
- mode=None, twinx=False, twiny=False):
+ def _prepare_view_from_bbox(self, bbox, direction='in',
+ mode=None, twinx=False, twiny=False):
"""
- Update view from a selection bbox.
-
- .. note::
-
- Intended to be overridden by new projection types, but if not, the
- default implementation sets the view limits to the bbox directly.
-
- Parameters
- ----------
- bbox : 4-tuple or 3 tuple
- * If bbox is a 4 tuple, it is the selected bounding box limits,
- in *display* coordinates.
- * If bbox is a 3 tuple, it is an (xp, yp, scl) triple, where
- (xp, yp) is the center of zooming and scl the scale factor to
- zoom by.
+ Helper function to prepare the new bounds from a bbox.
- direction : str
- The direction to apply the bounding box.
- * `'in'` - The bounding box describes the view directly, i.e.,
- it zooms in.
- * `'out'` - The bounding box describes the size to make the
- existing view, i.e., it zooms out.
-
- mode : str or None
- The selection mode, whether to apply the bounding box in only the
- `'x'` direction, `'y'` direction or both (`None`).
-
- twinx : bool
- Whether this axis is twinned in the *x*-direction.
-
- twiny : bool
- Whether this axis is twinned in the *y*-direction.
+ This helper function returns the new x and y bounds from the zoom
+ bbox. This a convenience method to abstract the bbox logic
+ out of the base setter.
"""
if len(bbox) == 3:
xp, yp, scl = bbox # Zooming code
@@ -4360,6 +4333,46 @@ def _set_view_from_bbox(self, bbox, direction='in',
symax1 = symax0 + factor * (symax0 - symax)
new_ybound = y_trf.inverted().transform([symin1, symax1])
+ return new_xbound, new_ybound
+
+ def _set_view_from_bbox(self, bbox, direction='in',
+ mode=None, twinx=False, twiny=False):
+ """
+ Update view from a selection bbox.
+
+ .. note::
+
+ Intended to be overridden by new projection types, but if not, the
+ default implementation sets the view limits to the bbox directly.
+
+ Parameters
+ ----------
+ bbox : 4-tuple or 3 tuple
+ * If bbox is a 4 tuple, it is the selected bounding box limits,
+ in *display* coordinates.
+ * If bbox is a 3 tuple, it is an (xp, yp, scl) triple, where
+ (xp, yp) is the center of zooming and scl the scale factor to
+ zoom by.
+
+ direction : str
+ The direction to apply the bounding box.
+ * `'in'` - The bounding box describes the view directly, i.e.,
+ it zooms in.
+ * `'out'` - The bounding box describes the size to make the
+ existing view, i.e., it zooms out.
+
+ mode : str or None
+ The selection mode, whether to apply the bounding box in only the
+ `'x'` direction, `'y'` direction or both (`None`).
+
+ twinx : bool
+ Whether this axis is twinned in the *x*-direction.
+
+ twiny : bool
+ Whether this axis is twinned in the *y*-direction.
+ """
+ new_xbound, new_ybound = self._prepare_view_from_bbox(
+ bbox, direction=direction, mode=mode, twinx=twinx, twiny=twiny)
if not twinx and mode != "y":
self.set_xbound(new_xbound)
self.set_autoscalex_on(False)
@@ -4400,22 +4413,13 @@ def end_pan(self):
"""
del self._pan_start
- def drag_pan(self, button, key, x, y):
+ def _get_pan_points(self, button, key, x, y):
"""
- Called when the mouse moves during a pan operation.
+ Helper function to return the new points after a pan.
- Parameters
- ----------
- button : `.MouseButton`
- The pressed mouse button.
- key : str or None
- The pressed key, if any.
- x, y : float
- The mouse coordinates in display coords.
-
- Notes
- -----
- This is intended to be overridden by new projection types.
+ This helper function returns the points on the axis after a pan has
+ occurred. This is a convenience method to abstract the pan logic
+ out of the base setter.
"""
def format_deltas(key, dx, dy):
if key == 'control':
@@ -4469,8 +4473,29 @@ def format_deltas(key, dx, dy):
points = result.get_points().astype(object)
# Just ignore invalid limits (typically, underflow in log-scale).
points[~valid] = None
- self.set_xlim(points[:, 0])
- self.set_ylim(points[:, 1])
+ return points
+
+ def drag_pan(self, button, key, x, y):
+ """
+ Called when the mouse moves during a pan operation.
+
+ Parameters
+ ----------
+ button : `.MouseButton`
+ The pressed mouse button.
+ key : str or None
+ The pressed key, if any.
+ x, y : float
+ The mouse coordinates in display coords.
+
+ Notes
+ -----
+ This is intended to be overridden by new projection types.
+ """
+ points = self._get_pan_points(button, key, x, y)
+ if points is not None:
+ self.set_xlim(points[:, 0])
+ self.set_ylim(points[:, 1])
def get_children(self):
# docstring inherited.
diff --git a/lib/matplotlib/backend_bases.py b/lib/matplotlib/backend_bases.py
index 89a3980de52a..42ac8d2a4164 100644
--- a/lib/matplotlib/backend_bases.py
+++ b/lib/matplotlib/backend_bases.py
@@ -3136,7 +3136,7 @@ def zoom(self, *args):
a.set_navigate_mode(self.mode._navigate_mode)
self.set_message(self.mode)
- _ZoomInfo = namedtuple("_ZoomInfo", "direction start_xy axes cid")
+ _ZoomInfo = namedtuple("_ZoomInfo", "direction start_xy axes cid cbar")
def press_zoom(self, event):
"""Callback for mouse button press in zoom to rect mode."""
@@ -3151,9 +3151,16 @@ def press_zoom(self, event):
self.push_current() # set the home button to this view
id_zoom = self.canvas.mpl_connect(
"motion_notify_event", self.drag_zoom)
+ # A colorbar is one-dimensional, so we extend the zoom rectangle out
+ # to the edge of the axes bbox in the other dimension. To do that we
+ # store the orientation of the colorbar for later.
+ if hasattr(axes[0], "_colorbar"):
+ cbar = axes[0]._colorbar.orientation
+ else:
+ cbar = None
self._zoom_info = self._ZoomInfo(
direction="in" if event.button == 1 else "out",
- start_xy=(event.x, event.y), axes=axes, cid=id_zoom)
+ start_xy=(event.x, event.y), axes=axes, cid=id_zoom, cbar=cbar)
def drag_zoom(self, event):
"""Callback for dragging in zoom mode."""
@@ -3161,10 +3168,17 @@ def drag_zoom(self, event):
ax = self._zoom_info.axes[0]
(x1, y1), (x2, y2) = np.clip(
[start_xy, [event.x, event.y]], ax.bbox.min, ax.bbox.max)
- if event.key == "x":
+ key = event.key
+ # Force the key on colorbars to extend the short-axis bbox
+ if self._zoom_info.cbar == "horizontal":
+ key = "x"
+ elif self._zoom_info.cbar == "vertical":
+ key = "y"
+ if key == "x":
y1, y2 = ax.bbox.intervaly
- elif event.key == "y":
+ elif key == "y":
x1, x2 = ax.bbox.intervalx
+
self.draw_rubberband(event, x1, y1, x2, y2)
def release_zoom(self, event):
@@ -3178,10 +3192,17 @@ def release_zoom(self, event):
self.remove_rubberband()
start_x, start_y = self._zoom_info.start_xy
+ key = event.key
+ # Force the key on colorbars to ignore the zoom-cancel on the
+ # short-axis side
+ if self._zoom_info.cbar == "horizontal":
+ key = "x"
+ elif self._zoom_info.cbar == "vertical":
+ key = "y"
# Ignore single clicks: 5 pixels is a threshold that allows the user to
# "cancel" a zoom action by zooming by less than 5 pixels.
- if ((abs(event.x - start_x) < 5 and event.key != "y")
- or (abs(event.y - start_y) < 5 and event.key != "x")):
+ if ((abs(event.x - start_x) < 5 and key != "y") or
+ (abs(event.y - start_y) < 5 and key != "x")):
self.canvas.draw_idle()
self._zoom_info = None
return
@@ -3195,7 +3216,7 @@ def release_zoom(self, event):
for prev in self._zoom_info.axes[:i])
ax._set_view_from_bbox(
(start_x, start_y, event.x, event.y),
- self._zoom_info.direction, event.key, twinx, twiny)
+ self._zoom_info.direction, key, twinx, twiny)
self.canvas.draw_idle()
self._zoom_info = None
diff --git a/lib/matplotlib/colorbar.py b/lib/matplotlib/colorbar.py
index a5439bf8ea75..ea5acffbe949 100644
--- a/lib/matplotlib/colorbar.py
+++ b/lib/matplotlib/colorbar.py
@@ -422,7 +422,6 @@ def __init__(self, ax, mappable=None, *, cmap=None,
self.ax = ax
self.ax._axes_locator = _ColorbarAxesLocator(self)
- ax.set(navigate=False)
if extend is None:
if (not isinstance(mappable, contour.ContourSet)
@@ -496,6 +495,29 @@ def __init__(self, ax, mappable=None, *, cmap=None,
if isinstance(mappable, contour.ContourSet) and not mappable.filled:
self.add_lines(mappable)
+ # Link the Axes and Colorbar for interactive use
+ self.ax._colorbar = self
+ # Don't navigate on any of these types of mappables
+ if (isinstance(self.norm, (colors.BoundaryNorm, colors.NoNorm)) or
+ isinstance(self.mappable, contour.ContourSet)):
+ self.ax.set_navigate(False)
+
+ # These are the functions that set up interactivity on this colorbar
+ self._interactive_funcs = ["_get_view", "_set_view",
+ "_set_view_from_bbox", "drag_pan"]
+ for x in self._interactive_funcs:
+ setattr(self.ax, x, getattr(self, x))
+ # Set the cla function to the cbar's method to override it
+ self.ax.cla = self._cbar_cla
+
+ def _cbar_cla(self):
+ """Function to clear the interactive colorbar state."""
+ for x in self._interactive_funcs:
+ delattr(self.ax, x)
+ # We now restore the old cla() back and can call it directly
+ del self.ax.cla
+ self.ax.cla()
+
# Also remove ._patch after deprecation elapses.
patch = _api.deprecate_privatize_attribute("3.5", alternative="ax")
@@ -1280,6 +1302,36 @@ def _short_axis(self):
return self.ax.xaxis
return self.ax.yaxis
+ def _get_view(self):
+ # docstring inherited
+ # An interactive view for a colorbar is the norm's vmin/vmax
+ return self.norm.vmin, self.norm.vmax
+
+ def _set_view(self, view):
+ # docstring inherited
+ # An interactive view for a colorbar is the norm's vmin/vmax
+ self.norm.vmin, self.norm.vmax = view
+
+ def _set_view_from_bbox(self, bbox, direction='in',
+ mode=None, twinx=False, twiny=False):
+ # docstring inherited
+ # For colorbars, we use the zoom bbox to scale the norm's vmin/vmax
+ new_xbound, new_ybound = self.ax._prepare_view_from_bbox(
+ bbox, direction=direction, mode=mode, twinx=twinx, twiny=twiny)
+ if self.orientation == 'horizontal':
+ self.norm.vmin, self.norm.vmax = new_xbound
+ elif self.orientation == 'vertical':
+ self.norm.vmin, self.norm.vmax = new_ybound
+
+ def drag_pan(self, button, key, x, y):
+ # docstring inherited
+ points = self.ax._get_pan_points(button, key, x, y)
+ if points is not None:
+ if self.orientation == 'horizontal':
+ self.norm.vmin, self.norm.vmax = points[:, 0]
+ elif self.orientation == 'vertical':
+ self.norm.vmin, self.norm.vmax = points[:, 1]
+
ColorbarBase = Colorbar # Backcompat API
|
diff --git a/lib/matplotlib/tests/test_backend_bases.py b/lib/matplotlib/tests/test_backend_bases.py
index 1550d3256c04..4abaf1a78ed5 100644
--- a/lib/matplotlib/tests/test_backend_bases.py
+++ b/lib/matplotlib/tests/test_backend_bases.py
@@ -181,6 +181,66 @@ def test_interactive_zoom():
assert not ax.get_autoscalex_on() and not ax.get_autoscaley_on()
+@pytest.mark.parametrize("plot_func", ["imshow", "contourf"])
+@pytest.mark.parametrize("orientation", ["vertical", "horizontal"])
+@pytest.mark.parametrize("tool,button,expected",
+ [("zoom", MouseButton.LEFT, (4, 6)), # zoom in
+ ("zoom", MouseButton.RIGHT, (-20, 30)), # zoom out
+ ("pan", MouseButton.LEFT, (-2, 8))])
+def test_interactive_colorbar(plot_func, orientation, tool, button, expected):
+ fig, ax = plt.subplots()
+ data = np.arange(12).reshape((4, 3))
+ vmin0, vmax0 = 0, 10
+ coll = getattr(ax, plot_func)(data, vmin=vmin0, vmax=vmax0)
+
+ cb = fig.colorbar(coll, ax=ax, orientation=orientation)
+ if plot_func == "contourf":
+ # Just determine we can't navigate and exit out of the test
+ assert not cb.ax.get_navigate()
+ return
+
+ assert cb.ax.get_navigate()
+
+ # Mouse from 4 to 6 (data coordinates, "d").
+ vmin, vmax = 4, 6
+ # The y coordinate doesn't matter, it just needs to be between 0 and 1
+ # However, we will set d0/d1 to the same y coordinate to test that small
+ # pixel changes in that coordinate doesn't cancel the zoom like a normal
+ # axes would.
+ d0 = (vmin, 0.5)
+ d1 = (vmax, 0.5)
+ # Swap them if the orientation is vertical
+ if orientation == "vertical":
+ d0 = d0[::-1]
+ d1 = d1[::-1]
+ # Convert to screen coordinates ("s"). Events are defined only with pixel
+ # precision, so round the pixel values, and below, check against the
+ # corresponding xdata/ydata, which are close but not equal to d0/d1.
+ s0 = cb.ax.transData.transform(d0).astype(int)
+ s1 = cb.ax.transData.transform(d1).astype(int)
+
+ # Set up the mouse movements
+ start_event = MouseEvent(
+ "button_press_event", fig.canvas, *s0, button)
+ stop_event = MouseEvent(
+ "button_release_event", fig.canvas, *s1, button)
+
+ tb = NavigationToolbar2(fig.canvas)
+ if tool == "zoom":
+ tb.zoom()
+ tb.press_zoom(start_event)
+ tb.drag_zoom(stop_event)
+ tb.release_zoom(stop_event)
+ else:
+ tb.pan()
+ tb.press_pan(start_event)
+ tb.drag_pan(stop_event)
+ tb.release_pan(stop_event)
+
+ # Should be close, but won't be exact due to screen integer resolution
+ assert (cb.vmin, cb.vmax) == pytest.approx(expected, abs=0.15)
+
+
def test_toolbar_zoompan():
expected_warning_regex = (
r"Treat the new Tool classes introduced in "
|
[
{
"path": "doc/api/next_api_changes/behavior/19515-GL.rst",
"old_path": "/dev/null",
"new_path": "b/doc/api/next_api_changes/behavior/19515-GL.rst",
"metadata": "diff --git a/doc/api/next_api_changes/behavior/19515-GL.rst b/doc/api/next_api_changes/behavior/19515-GL.rst\nnew file mode 100644\nindex 000000000000..cb6d925b797c\n--- /dev/null\n+++ b/doc/api/next_api_changes/behavior/19515-GL.rst\n@@ -0,0 +1,10 @@\n+Colorbars now have pan and zoom functionality\n+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n+\n+Interactive plots with colorbars can now be zoomed and panned on\n+the colorbar axis. This adjusts the *vmin* and *vmax* of the\n+``ScalarMappable`` associated with the colorbar. This is currently\n+only enabled for continuous norms. Norms used with contourf and\n+categoricals, such as ``BoundaryNorm`` and ``NoNorm``, have the\n+interactive capability disabled by default. ``cb.ax.set_navigate()``\n+can be used to set whether a colorbar axes is interactive or not.\n"
}
] |
3.4
|
eb7bcb41e272cad354e8ee703f5e276450cbf967
|
[
"lib/matplotlib/tests/test_backend_bases.py::test_draw[pdf]",
"lib/matplotlib/tests/test_backend_bases.py::test_uses_per_path",
"lib/matplotlib/tests/test_backend_bases.py::test_location_event_position[None-42]",
"lib/matplotlib/tests/test_backend_bases.py::test_location_event_position[205.75-2.0]",
"lib/matplotlib/tests/test_backend_bases.py::test_interactive_colorbar[zoom-MouseButton.LEFT-expected0-horizontal-contourf]",
"lib/matplotlib/tests/test_backend_bases.py::test_pick",
"lib/matplotlib/tests/test_backend_bases.py::test_non_gui_warning",
"lib/matplotlib/tests/test_backend_bases.py::test_interactive_colorbar[pan-MouseButton.LEFT-expected2-horizontal-contourf]",
"lib/matplotlib/tests/test_backend_bases.py::test_interactive_colorbar[zoom-MouseButton.RIGHT-expected1-horizontal-contourf]",
"lib/matplotlib/tests/test_backend_bases.py::test_draw[ps]",
"lib/matplotlib/tests/test_backend_bases.py::test_interactive_zoom",
"lib/matplotlib/tests/test_backend_bases.py::test_toolbar_zoompan",
"lib/matplotlib/tests/test_backend_bases.py::test_location_event_position[None-None]",
"lib/matplotlib/tests/test_backend_bases.py::test_location_event_position[42-24]",
"lib/matplotlib/tests/test_backend_bases.py::test_interactive_colorbar[pan-MouseButton.LEFT-expected2-vertical-contourf]",
"lib/matplotlib/tests/test_backend_bases.py::test_draw[svg]",
"lib/matplotlib/tests/test_backend_bases.py::test_interactive_colorbar[zoom-MouseButton.LEFT-expected0-vertical-contourf]",
"lib/matplotlib/tests/test_backend_bases.py::test_location_event_position[200-100.01]",
"lib/matplotlib/tests/test_backend_bases.py::test_get_default_filename",
"lib/matplotlib/tests/test_backend_bases.py::test_canvas_change",
"lib/matplotlib/tests/test_backend_bases.py::test_draw[pgf]",
"lib/matplotlib/tests/test_backend_bases.py::test_canvas_ctor",
"lib/matplotlib/tests/test_backend_bases.py::test_interactive_colorbar[zoom-MouseButton.RIGHT-expected1-vertical-contourf]"
] |
[
"lib/matplotlib/tests/test_backend_bases.py::test_interactive_colorbar[zoom-MouseButton.LEFT-expected0-vertical-imshow]",
"lib/matplotlib/tests/test_backend_bases.py::test_interactive_colorbar[pan-MouseButton.LEFT-expected2-horizontal-imshow]",
"lib/matplotlib/tests/test_backend_bases.py::test_interactive_colorbar[pan-MouseButton.LEFT-expected2-vertical-imshow]",
"lib/matplotlib/tests/test_backend_bases.py::test_interactive_colorbar[zoom-MouseButton.LEFT-expected0-horizontal-imshow]",
"lib/matplotlib/tests/test_backend_bases.py::test_interactive_colorbar[zoom-MouseButton.RIGHT-expected1-horizontal-imshow]",
"lib/matplotlib/tests/test_backend_bases.py::test_interactive_colorbar[zoom-MouseButton.RIGHT-expected1-vertical-imshow]"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": [
{
"type": "function",
"name": "drag_pan"
},
{
"type": "field",
"name": "button"
}
]
}
|
[
{
"path": "doc/api/next_api_changes/behavior/<PRID>-GL.rst",
"old_path": "/dev/null",
"new_path": "b/doc/api/next_api_changes/behavior/<PRID>-GL.rst",
"metadata": "diff --git a/doc/api/next_api_changes/behavior/<PRID>-GL.rst b/doc/api/next_api_changes/behavior/<PRID>-GL.rst\nnew file mode 100644\nindex 000000000000..cb6d925b797c\n--- /dev/null\n+++ b/doc/api/next_api_changes/behavior/<PRID>-GL.rst\n@@ -0,0 +1,10 @@\n+Colorbars now have pan and zoom functionality\n+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n+\n+Interactive plots with colorbars can now be zoomed and panned on\n+the colorbar axis. This adjusts the *vmin* and *vmax* of the\n+``ScalarMappable`` associated with the colorbar. This is currently\n+only enabled for continuous norms. Norms used with contourf and\n+categoricals, such as ``BoundaryNorm`` and ``NoNorm``, have the\n+interactive capability disabled by default. ``cb.ax.set_navigate()``\n+can be used to set whether a colorbar axes is interactive or not.\n"
}
] |
diff --git a/doc/api/next_api_changes/behavior/<PRID>-GL.rst b/doc/api/next_api_changes/behavior/<PRID>-GL.rst
new file mode 100644
index 000000000000..cb6d925b797c
--- /dev/null
+++ b/doc/api/next_api_changes/behavior/<PRID>-GL.rst
@@ -0,0 +1,10 @@
+Colorbars now have pan and zoom functionality
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Interactive plots with colorbars can now be zoomed and panned on
+the colorbar axis. This adjusts the *vmin* and *vmax* of the
+``ScalarMappable`` associated with the colorbar. This is currently
+only enabled for continuous norms. Norms used with contourf and
+categoricals, such as ``BoundaryNorm`` and ``NoNorm``, have the
+interactive capability disabled by default. ``cb.ax.set_navigate()``
+can be used to set whether a colorbar axes is interactive or not.
If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:
[{'type': 'function', 'name': 'drag_pan'}, {'type': 'field', 'name': 'button'}]
|
matplotlib/matplotlib
|
matplotlib__matplotlib-21374
|
https://github.com/matplotlib/matplotlib/pull/21374
|
diff --git a/doc/users/next_whats_new/snap_selector.rst b/doc/users/next_whats_new/snap_selector.rst
new file mode 100644
index 000000000000..9ff0ccd87e0c
--- /dev/null
+++ b/doc/users/next_whats_new/snap_selector.rst
@@ -0,0 +1,4 @@
+SpanSelector widget can now be snapped to specified values
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+The SpanSelector widget can now be snapped to values specified by the *snap_values*
+argument.
diff --git a/lib/matplotlib/widgets.py b/lib/matplotlib/widgets.py
index 78d484168263..cd79e9523a04 100644
--- a/lib/matplotlib/widgets.py
+++ b/lib/matplotlib/widgets.py
@@ -2238,6 +2238,9 @@ def on_select(min: float, max: float) -> Any
If `True`, the event triggered outside the span selector will be
ignored.
+ snap_values : 1D array-like, optional
+ Snap the selector edges to the given values.
+
Examples
--------
>>> import matplotlib.pyplot as plt
@@ -2259,7 +2262,7 @@ def __init__(self, ax, onselect, direction, minspan=0, useblit=False,
props=None, onmove_callback=None, interactive=False,
button=None, handle_props=None, grab_range=10,
state_modifier_keys=None, drag_from_anywhere=False,
- ignore_event_outside=False):
+ ignore_event_outside=False, snap_values=None):
if state_modifier_keys is None:
state_modifier_keys = dict(clear='escape',
@@ -2278,6 +2281,7 @@ def __init__(self, ax, onselect, direction, minspan=0, useblit=False,
self.visible = True
self._extents_on_press = None
+ self.snap_values = snap_values
# self._pressv is deprecated and we don't use it internally anymore
# but we maintain it until it is removed
@@ -2577,6 +2581,15 @@ def _contains(self, event):
"""Return True if event is within the patch."""
return self._selection_artist.contains(event, radius=0)[0]
+ @staticmethod
+ def _snap(values, snap_values):
+ """Snap values to a given array values (snap_values)."""
+ # take into account machine precision
+ eps = np.min(np.abs(np.diff(snap_values))) * 1e-12
+ return tuple(
+ snap_values[np.abs(snap_values - v + np.sign(v) * eps).argmin()]
+ for v in values)
+
@property
def extents(self):
"""Return extents of the span selector."""
@@ -2591,6 +2604,8 @@ def extents(self):
@extents.setter
def extents(self, extents):
# Update displayed shape
+ if self.snap_values is not None:
+ extents = tuple(self._snap(extents, self.snap_values))
self._draw_shape(*extents)
if self._interactive:
# Update displayed handles
|
diff --git a/lib/matplotlib/tests/test_widgets.py b/lib/matplotlib/tests/test_widgets.py
index cf98e3aea85e..11db0493a711 100644
--- a/lib/matplotlib/tests/test_widgets.py
+++ b/lib/matplotlib/tests/test_widgets.py
@@ -67,8 +67,7 @@ def test_rectangle_selector():
@pytest.mark.parametrize('spancoords', ['data', 'pixels'])
@pytest.mark.parametrize('minspanx, x1', [[0, 10], [1, 10.5], [1, 11]])
@pytest.mark.parametrize('minspany, y1', [[0, 10], [1, 10.5], [1, 11]])
-def test_rectangle_minspan(spancoords, minspanx, x1, minspany, y1):
- ax = get_ax()
+def test_rectangle_minspan(ax, spancoords, minspanx, x1, minspany, y1):
# attribute to track number of onselect calls
ax._n_onselect = 0
@@ -924,6 +923,37 @@ def mean(vmin, vmax):
assert ln2.stale is False
+def test_snapping_values_span_selector(ax):
+ def onselect(*args):
+ pass
+
+ tool = widgets.SpanSelector(ax, onselect, direction='horizontal',)
+ snap_function = tool._snap
+
+ snap_values = np.linspace(0, 5, 11)
+ values = np.array([-0.1, 0.1, 0.2, 0.5, 0.6, 0.7, 0.9, 4.76, 5.0, 5.5])
+ expect = np.array([00.0, 0.0, 0.0, 0.5, 0.5, 0.5, 1.0, 5.00, 5.0, 5.0])
+ values = snap_function(values, snap_values)
+ assert_allclose(values, expect)
+
+
+def test_span_selector_snap(ax):
+ def onselect(vmin, vmax):
+ ax._got_onselect = True
+
+ snap_values = np.arange(50) * 4
+
+ tool = widgets.SpanSelector(ax, onselect, direction='horizontal',
+ snap_values=snap_values)
+ tool.extents = (17, 35)
+ assert tool.extents == (16, 36)
+
+ tool.snap_values = None
+ assert tool.snap_values is None
+ tool.extents = (17, 35)
+ assert tool.extents == (17, 35)
+
+
def check_lasso_selector(**kwargs):
ax = get_ax()
|
[
{
"path": "doc/users/next_whats_new/snap_selector.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/snap_selector.rst",
"metadata": "diff --git a/doc/users/next_whats_new/snap_selector.rst b/doc/users/next_whats_new/snap_selector.rst\nnew file mode 100644\nindex 000000000000..9ff0ccd87e0c\n--- /dev/null\n+++ b/doc/users/next_whats_new/snap_selector.rst\n@@ -0,0 +1,4 @@\n+SpanSelector widget can now be snapped to specified values\n+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n+The SpanSelector widget can now be snapped to values specified by the *snap_values*\n+argument.\n"
}
] |
3.5
|
574580c7d173bf08a23678d302b711492b971f3c
|
[
"lib/matplotlib/tests/test_widgets.py::test_rectangle_minspan[1-11-0-10-pixels]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_minspan[0-10-0-10-data]",
"lib/matplotlib/tests/test_widgets.py::test_span_selector_onselect[True]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_selector_ignore_outside[False]",
"lib/matplotlib/tests/test_widgets.py::test_span_selector_direction",
"lib/matplotlib/tests/test_widgets.py::test_range_slider[vertical]",
"lib/matplotlib/tests/test_widgets.py::test_polygon_selector_remove[True-1]",
"lib/matplotlib/tests/test_widgets.py::test_selector_clear[rectangle]",
"lib/matplotlib/tests/test_widgets.py::test_TextBox[none]",
"lib/matplotlib/tests/test_widgets.py::test_polygon_selector_remove[True-2]",
"lib/matplotlib/tests/test_widgets.py::test_MultiCursor[True-False]",
"lib/matplotlib/tests/test_widgets.py::test_polygon_selector[True]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_handles",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_minspan[1-10.5-0-10-data]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_rotate[RectangleSelector]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_minspan[0-10-1-10.5-pixels]",
"lib/matplotlib/tests/test_widgets.py::test_polygon_selector_remove[False-3]",
"lib/matplotlib/tests/test_widgets.py::test_polygon_selector_set_props_handle_props[True]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_minspan[0-10-1-10.5-data]",
"lib/matplotlib/tests/test_widgets.py::test_span_selector_drag[True]",
"lib/matplotlib/tests/test_widgets.py::test_span_selector_bound[vertical]",
"lib/matplotlib/tests/test_widgets.py::test_selector_clear_method[span]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_minspan[1-10.5-1-10.5-data]",
"lib/matplotlib/tests/test_widgets.py::test_check_radio_buttons_image[png]",
"lib/matplotlib/tests/test_widgets.py::test_slider_valstep_snapping",
"lib/matplotlib/tests/test_widgets.py::test_CheckButtons",
"lib/matplotlib/tests/test_widgets.py::test_slider_valmin_valmax",
"lib/matplotlib/tests/test_widgets.py::test_polygon_selector_set_props_handle_props[False]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_minspan[1-11-0-10-data]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_resize_square_center_aspect[False]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_add_state",
"lib/matplotlib/tests/test_widgets.py::test_slider_slidermin_slidermax",
"lib/matplotlib/tests/test_widgets.py::test_range_slider[horizontal]",
"lib/matplotlib/tests/test_widgets.py::test_polygon_selector_verts_setter[png-False]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_resize_center[True]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_selector_set_props_handle_props",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_minspan[1-10.5-1-10.5-pixels]",
"lib/matplotlib/tests/test_widgets.py::test_selector_clear_method[rectangle]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_minspan[1-10.5-1-11-data]",
"lib/matplotlib/tests/test_widgets.py::test_polygon_selector_remove[False-1]",
"lib/matplotlib/tests/test_widgets.py::test_polygon_selector_remove_first_point[False]",
"lib/matplotlib/tests/test_widgets.py::test_span_selector",
"lib/matplotlib/tests/test_widgets.py::test_polygon_selector[False]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_minspan[0-10-1-11-pixels]",
"lib/matplotlib/tests/test_widgets.py::test_ellipse",
"lib/matplotlib/tests/test_widgets.py::test_slider_slidermin_slidermax_invalid",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_minspan[1-10.5-0-10-pixels]",
"lib/matplotlib/tests/test_widgets.py::test_slider_horizontal_vertical",
"lib/matplotlib/tests/test_widgets.py::test_span_selector_ignore_outside[False]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_drag[True-new_center0]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_selector_onselect[True]",
"lib/matplotlib/tests/test_widgets.py::test_span_selector_bound[horizontal]",
"lib/matplotlib/tests/test_widgets.py::test_rect_visibility[svg]",
"lib/matplotlib/tests/test_widgets.py::test_selector_clear[span]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_minspan[1-11-1-11-pixels]",
"lib/matplotlib/tests/test_widgets.py::test_polygon_selector_remove[False-2]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_selector_ignore_outside[True]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_selector_onselect[False]",
"lib/matplotlib/tests/test_widgets.py::test_check_bunch_of_radio_buttons[png]",
"lib/matplotlib/tests/test_widgets.py::test_tool_line_handle",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_resize_square[False]",
"lib/matplotlib/tests/test_widgets.py::test_TextBox[toolbar2]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_resize_square_center",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_minspan[1-11-1-10.5-pixels]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_minspan[1-10.5-1-11-pixels]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_resize",
"lib/matplotlib/tests/test_widgets.py::test_slider_reset",
"lib/matplotlib/tests/test_widgets.py::test_lasso_selector",
"lib/matplotlib/tests/test_widgets.py::test_TextBox[toolmanager]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_minspan[1-11-1-10.5-data]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_resize_square[True]",
"lib/matplotlib/tests/test_widgets.py::test_polygon_selector_box",
"lib/matplotlib/tests/test_widgets.py::test_span_selector_drag[False]",
"lib/matplotlib/tests/test_widgets.py::test_span_selector_onselect[False]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_minspan[0-10-0-10-pixels]",
"lib/matplotlib/tests/test_widgets.py::test_rect_visibility[pdf]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_resize_center[False]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_minspan[0-10-1-11-data]",
"lib/matplotlib/tests/test_widgets.py::test_polygon_selector_verts_setter[png-True]",
"lib/matplotlib/tests/test_widgets.py::test_polygon_selector_remove_first_point[True]",
"lib/matplotlib/tests/test_widgets.py::test_polygon_selector_redraw[True]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_drag[False-new_center1]",
"lib/matplotlib/tests/test_widgets.py::test_polygon_selector_redraw[False]",
"lib/matplotlib/tests/test_widgets.py::test_rectange_add_remove_set",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_rotate[EllipseSelector]",
"lib/matplotlib/tests/test_widgets.py::test_MultiCursor[True-True]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_minspan[1-11-1-11-data]",
"lib/matplotlib/tests/test_widgets.py::test_span_selector_ignore_outside[True]",
"lib/matplotlib/tests/test_widgets.py::test_span_selector_set_props_handle_props",
"lib/matplotlib/tests/test_widgets.py::test_rect_visibility[png]",
"lib/matplotlib/tests/test_widgets.py::test_polygon_selector_remove[True-3]",
"lib/matplotlib/tests/test_widgets.py::test_span_selector_add_state",
"lib/matplotlib/tests/test_widgets.py::test_MultiCursor[False-True]",
"lib/matplotlib/tests/test_widgets.py::test_rectangle_resize_square_center_aspect[True]"
] |
[
"lib/matplotlib/tests/test_widgets.py::test_span_selector_snap",
"lib/matplotlib/tests/test_widgets.py::test_snapping_values_span_selector"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": [
{
"type": "field",
"name": "_snap"
},
{
"type": "function",
"name": "_snap"
}
]
}
|
[
{
"path": "doc/users/next_whats_new/snap_selector.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/snap_selector.rst",
"metadata": "diff --git a/doc/users/next_whats_new/snap_selector.rst b/doc/users/next_whats_new/snap_selector.rst\nnew file mode 100644\nindex 000000000000..9ff0ccd87e0c\n--- /dev/null\n+++ b/doc/users/next_whats_new/snap_selector.rst\n@@ -0,0 +1,4 @@\n+SpanSelector widget can now be snapped to specified values\n+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n+The SpanSelector widget can now be snapped to values specified by the *snap_values*\n+argument.\n"
}
] |
diff --git a/doc/users/next_whats_new/snap_selector.rst b/doc/users/next_whats_new/snap_selector.rst
new file mode 100644
index 000000000000..9ff0ccd87e0c
--- /dev/null
+++ b/doc/users/next_whats_new/snap_selector.rst
@@ -0,0 +1,4 @@
+SpanSelector widget can now be snapped to specified values
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+The SpanSelector widget can now be snapped to values specified by the *snap_values*
+argument.
If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:
[{'type': 'field', 'name': '_snap'}, {'type': 'function', 'name': '_snap'}]
|
matplotlib/matplotlib
|
matplotlib__matplotlib-20816
|
https://github.com/matplotlib/matplotlib/pull/20816
|
diff --git a/doc/users/next_whats_new/callback_blocking.rst b/doc/users/next_whats_new/callback_blocking.rst
new file mode 100644
index 000000000000..090e06c61bbf
--- /dev/null
+++ b/doc/users/next_whats_new/callback_blocking.rst
@@ -0,0 +1,25 @@
+``CallbackRegistry`` objects gain a method to temporarily block signals
+-----------------------------------------------------------------------
+
+The context manager `~matplotlib.cbook.CallbackRegistry.blocked` can be used
+to block callback signals from being processed by the ``CallbackRegistry``.
+The optional keyword, *signal*, can be used to block a specific signal
+from being processed and let all other signals pass.
+
+.. code-block::
+
+ import matplotlib.pyplot as plt
+
+ fig, ax = plt.subplots()
+ ax.imshow([[0, 1], [2, 3]])
+
+ # Block all interactivity through the canvas callbacks
+ with fig.canvas.callbacks.blocked():
+ plt.show()
+
+ fig, ax = plt.subplots()
+ ax.imshow([[0, 1], [2, 3]])
+
+ # Only block key press events
+ with fig.canvas.callbacks.blocked(signal="key_press_event"):
+ plt.show()
diff --git a/lib/matplotlib/cbook/__init__.py b/lib/matplotlib/cbook/__init__.py
index ae7e5cd056e0..109b9ea69cc9 100644
--- a/lib/matplotlib/cbook/__init__.py
+++ b/lib/matplotlib/cbook/__init__.py
@@ -122,7 +122,8 @@ def _weak_or_strong_ref(func, callback):
class CallbackRegistry:
"""
- Handle registering and disconnecting for a set of signals and callbacks:
+ Handle registering, processing, blocking, and disconnecting
+ for a set of signals and callbacks:
>>> def oneat(x):
... print('eat', x)
@@ -140,9 +141,15 @@ class CallbackRegistry:
>>> callbacks.process('eat', 456)
eat 456
>>> callbacks.process('be merry', 456) # nothing will be called
+
>>> callbacks.disconnect(id_eat)
>>> callbacks.process('eat', 456) # nothing will be called
+ >>> with callbacks.blocked(signal='drink'):
+ ... callbacks.process('drink', 123) # nothing will be called
+ >>> callbacks.process('drink', 123)
+ drink 123
+
In practice, one should always disconnect all callbacks when they are
no longer needed to avoid dangling references (and thus memory leaks).
However, real code in Matplotlib rarely does so, and due to its design,
@@ -280,6 +287,31 @@ def process(self, s, *args, **kwargs):
else:
raise
+ @contextlib.contextmanager
+ def blocked(self, *, signal=None):
+ """
+ Block callback signals from being processed.
+
+ A context manager to temporarily block/disable callback signals
+ from being processed by the registered listeners.
+
+ Parameters
+ ----------
+ signal : str, optional
+ The callback signal to block. The default is to block all signals.
+ """
+ orig = self.callbacks
+ try:
+ if signal is None:
+ # Empty out the callbacks
+ self.callbacks = {}
+ else:
+ # Only remove the specific signal
+ self.callbacks = {k: orig[k] for k in orig if k != signal}
+ yield
+ finally:
+ self.callbacks = orig
+
class silent_list(list):
"""
|
diff --git a/lib/matplotlib/tests/test_cbook.py b/lib/matplotlib/tests/test_cbook.py
index 47287524afde..474ea1a41d93 100644
--- a/lib/matplotlib/tests/test_cbook.py
+++ b/lib/matplotlib/tests/test_cbook.py
@@ -361,6 +361,39 @@ def test_callbackregistry_custom_exception_handler(monkeypatch, cb, excp):
cb.process('foo')
+def test_callbackregistry_blocking():
+ # Needs an exception handler for interactive testing environments
+ # that would only print this out instead of raising the exception
+ def raise_handler(excp):
+ raise excp
+ cb = cbook.CallbackRegistry(exception_handler=raise_handler)
+ def test_func1():
+ raise ValueError("1 should be blocked")
+ def test_func2():
+ raise ValueError("2 should be blocked")
+ cb.connect("test1", test_func1)
+ cb.connect("test2", test_func2)
+
+ # block all of the callbacks to make sure they aren't processed
+ with cb.blocked():
+ cb.process("test1")
+ cb.process("test2")
+
+ # block individual callbacks to make sure the other is still processed
+ with cb.blocked(signal="test1"):
+ # Blocked
+ cb.process("test1")
+ # Should raise
+ with pytest.raises(ValueError, match="2 should be blocked"):
+ cb.process("test2")
+
+ # Make sure the original callback functions are there after blocking
+ with pytest.raises(ValueError, match="1 should be blocked"):
+ cb.process("test1")
+ with pytest.raises(ValueError, match="2 should be blocked"):
+ cb.process("test2")
+
+
def test_sanitize_sequence():
d = {'a': 1, 'b': 2, 'c': 3}
k = ['a', 'b', 'c']
|
[
{
"path": "doc/users/next_whats_new/callback_blocking.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/callback_blocking.rst",
"metadata": "diff --git a/doc/users/next_whats_new/callback_blocking.rst b/doc/users/next_whats_new/callback_blocking.rst\nnew file mode 100644\nindex 000000000000..090e06c61bbf\n--- /dev/null\n+++ b/doc/users/next_whats_new/callback_blocking.rst\n@@ -0,0 +1,25 @@\n+``CallbackRegistry`` objects gain a method to temporarily block signals\n+-----------------------------------------------------------------------\n+\n+The context manager `~matplotlib.cbook.CallbackRegistry.blocked` can be used\n+to block callback signals from being processed by the ``CallbackRegistry``.\n+The optional keyword, *signal*, can be used to block a specific signal\n+from being processed and let all other signals pass.\n+\n+.. code-block::\n+\n+ import matplotlib.pyplot as plt\n+ \n+ fig, ax = plt.subplots()\n+ ax.imshow([[0, 1], [2, 3]])\n+\n+ # Block all interactivity through the canvas callbacks\n+ with fig.canvas.callbacks.blocked():\n+ plt.show()\n+\n+ fig, ax = plt.subplots()\n+ ax.imshow([[0, 1], [2, 3]])\n+\n+ # Only block key press events\n+ with fig.canvas.callbacks.blocked(signal=\"key_press_event\"):\n+ plt.show()\n"
}
] |
3.4
|
586fcffaae03e40f851c5bc854de290b89bae18e
|
[
"lib/matplotlib/tests/test_cbook.py::test_normalize_kwargs_pass[inp1-expected1-kwargs_to_norm1]",
"lib/matplotlib/tests/test_cbook.py::test_normalize_kwargs_fail[inp1-kwargs_to_norm1]",
"lib/matplotlib/tests/test_cbook.py::Test_boxplot_stats::test_boxplot_stats_autorange_false",
"lib/matplotlib/tests/test_cbook.py::test_grouper_private",
"lib/matplotlib/tests/test_cbook.py::Test_boxplot_stats::test_bad_dims",
"lib/matplotlib/tests/test_cbook.py::test_flatiter",
"lib/matplotlib/tests/test_cbook.py::test_normalize_kwargs_pass[None-expected0-kwargs_to_norm0]",
"lib/matplotlib/tests/test_cbook.py::Test_delete_masked_points::test_datetime",
"lib/matplotlib/tests/test_cbook.py::test_normalize_kwargs_pass[inp2-expected2-kwargs_to_norm2]",
"lib/matplotlib/tests/test_cbook.py::test_safe_first_element_pandas_series",
"lib/matplotlib/tests/test_cbook.py::test_to_poststep",
"lib/matplotlib/tests/test_cbook.py::test_array_patch_perimeters",
"lib/matplotlib/tests/test_cbook.py::test_format_approx",
"lib/matplotlib/tests/test_cbook.py::Test_callback_registry::test_pickling",
"lib/matplotlib/tests/test_cbook.py::Test_delete_masked_points::test_bad_first_arg",
"lib/matplotlib/tests/test_cbook.py::test_warn_external",
"lib/matplotlib/tests/test_cbook.py::test_callbackregistry_custom_exception_handler[cb1-TestException]",
"lib/matplotlib/tests/test_cbook.py::Test_delete_masked_points::test_string_seq",
"lib/matplotlib/tests/test_cbook.py::test_step_fails[args1]",
"lib/matplotlib/tests/test_cbook.py::test_contiguous_regions",
"lib/matplotlib/tests/test_cbook.py::test_callbackregistry_custom_exception_handler[cb2-ValueError]",
"lib/matplotlib/tests/test_cbook.py::test_warn_external_frame_embedded_python",
"lib/matplotlib/tests/test_cbook.py::test_grouper",
"lib/matplotlib/tests/test_cbook.py::test_step_fails[args0]",
"lib/matplotlib/tests/test_cbook.py::test_reshape2d",
"lib/matplotlib/tests/test_cbook.py::test_to_prestep_empty",
"lib/matplotlib/tests/test_cbook.py::test_reshape2d_pandas",
"lib/matplotlib/tests/test_cbook.py::test_to_prestep",
"lib/matplotlib/tests/test_cbook.py::test_normalize_kwargs_fail[inp0-kwargs_to_norm0]",
"lib/matplotlib/tests/test_cbook.py::test_callbackregistry_custom_exception_handler[cb0-RuntimeError]",
"lib/matplotlib/tests/test_cbook.py::Test_delete_masked_points::test_rgba",
"lib/matplotlib/tests/test_cbook.py::test_callbackregistry_default_exception_handler",
"lib/matplotlib/tests/test_cbook.py::test_to_poststep_empty",
"lib/matplotlib/tests/test_cbook.py::test_to_midstep",
"lib/matplotlib/tests/test_cbook.py::test_to_midstep_empty",
"lib/matplotlib/tests/test_cbook.py::test_step_fails[args2]",
"lib/matplotlib/tests/test_cbook.py::test_sanitize_sequence",
"lib/matplotlib/tests/test_cbook.py::test_setattr_cm"
] |
[
"lib/matplotlib/tests/test_cbook.py::test_callbackregistry_blocking"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/users/next_whats_new/callback_blocking.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/callback_blocking.rst",
"metadata": "diff --git a/doc/users/next_whats_new/callback_blocking.rst b/doc/users/next_whats_new/callback_blocking.rst\nnew file mode 100644\nindex 000000000000..090e06c61bbf\n--- /dev/null\n+++ b/doc/users/next_whats_new/callback_blocking.rst\n@@ -0,0 +1,25 @@\n+``CallbackRegistry`` objects gain a method to temporarily block signals\n+-----------------------------------------------------------------------\n+\n+The context manager `~matplotlib.cbook.CallbackRegistry.blocked` can be used\n+to block callback signals from being processed by the ``CallbackRegistry``.\n+The optional keyword, *signal*, can be used to block a specific signal\n+from being processed and let all other signals pass.\n+\n+.. code-block::\n+\n+ import matplotlib.pyplot as plt\n+ \n+ fig, ax = plt.subplots()\n+ ax.imshow([[0, 1], [2, 3]])\n+\n+ # Block all interactivity through the canvas callbacks\n+ with fig.canvas.callbacks.blocked():\n+ plt.show()\n+\n+ fig, ax = plt.subplots()\n+ ax.imshow([[0, 1], [2, 3]])\n+\n+ # Only block key press events\n+ with fig.canvas.callbacks.blocked(signal=\"key_press_event\"):\n+ plt.show()\n"
}
] |
diff --git a/doc/users/next_whats_new/callback_blocking.rst b/doc/users/next_whats_new/callback_blocking.rst
new file mode 100644
index 000000000000..090e06c61bbf
--- /dev/null
+++ b/doc/users/next_whats_new/callback_blocking.rst
@@ -0,0 +1,25 @@
+``CallbackRegistry`` objects gain a method to temporarily block signals
+-----------------------------------------------------------------------
+
+The context manager `~matplotlib.cbook.CallbackRegistry.blocked` can be used
+to block callback signals from being processed by the ``CallbackRegistry``.
+The optional keyword, *signal*, can be used to block a specific signal
+from being processed and let all other signals pass.
+
+.. code-block::
+
+ import matplotlib.pyplot as plt
+
+ fig, ax = plt.subplots()
+ ax.imshow([[0, 1], [2, 3]])
+
+ # Block all interactivity through the canvas callbacks
+ with fig.canvas.callbacks.blocked():
+ plt.show()
+
+ fig, ax = plt.subplots()
+ ax.imshow([[0, 1], [2, 3]])
+
+ # Only block key press events
+ with fig.canvas.callbacks.blocked(signal="key_press_event"):
+ plt.show()
|
matplotlib/matplotlib
|
matplotlib__matplotlib-23690
|
https://github.com/matplotlib/matplotlib/pull/23690
|
diff --git a/doc/users/next_whats_new/bar_label_formatting.rst b/doc/users/next_whats_new/bar_label_formatting.rst
new file mode 100644
index 000000000000..cf64436086d4
--- /dev/null
+++ b/doc/users/next_whats_new/bar_label_formatting.rst
@@ -0,0 +1,31 @@
+Additional format string options in `~matplotlib.axes.Axes.bar_label`
+---------------------------------------------------------------------
+
+The ``fmt`` argument of `~matplotlib.axes.Axes.bar_label` now accepts
+{}-style format strings:
+
+.. code-block:: python
+
+ import matplotlib.pyplot as plt
+
+ fruit_names = ['Coffee', 'Salted Caramel', 'Pistachio']
+ fruit_counts = [4000, 2000, 7000]
+
+ fig, ax = plt.subplots()
+ bar_container = ax.bar(fruit_names, fruit_counts)
+ ax.set(ylabel='pints sold', title='Gelato sales by flavor', ylim=(0, 8000))
+ ax.bar_label(bar_container, fmt='{:,.0f}')
+
+It also accepts callables:
+
+.. code-block:: python
+
+ animal_names = ['Lion', 'Gazelle', 'Cheetah']
+ mph_speed = [50, 60, 75]
+
+ fig, ax = plt.subplots()
+ bar_container = ax.bar(animal_names, mph_speed)
+ ax.set(ylabel='speed in MPH', title='Running speeds', ylim=(0, 80))
+ ax.bar_label(
+ bar_container, fmt=lambda x: '{:.1f} km/h'.format(x * 1.61)
+ )
diff --git a/examples/lines_bars_and_markers/bar_label_demo.py b/examples/lines_bars_and_markers/bar_label_demo.py
index 3ed3f79018cc..2bf0be68af63 100644
--- a/examples/lines_bars_and_markers/bar_label_demo.py
+++ b/examples/lines_bars_and_markers/bar_label_demo.py
@@ -94,6 +94,30 @@
plt.show()
+###############################################################################
+# Bar labels using {}-style format string
+
+fruit_names = ['Coffee', 'Salted Caramel', 'Pistachio']
+fruit_counts = [4000, 2000, 7000]
+
+fig, ax = plt.subplots()
+bar_container = ax.bar(fruit_names, fruit_counts)
+ax.set(ylabel='pints sold', title='Gelato sales by flavor', ylim=(0, 8000))
+ax.bar_label(bar_container, fmt='{:,.0f}')
+
+###############################################################################
+# Bar labels using a callable
+
+animal_names = ['Lion', 'Gazelle', 'Cheetah']
+mph_speed = [50, 60, 75]
+
+fig, ax = plt.subplots()
+bar_container = ax.bar(animal_names, mph_speed)
+ax.set(ylabel='speed in MPH', title='Running speeds', ylim=(0, 80))
+ax.bar_label(
+ bar_container, fmt=lambda x: '{:.1f} km/h'.format(x * 1.61)
+)
+
#############################################################################
#
# .. admonition:: References
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
index cb1d4c989c23..a353e70e21b2 100644
--- a/lib/matplotlib/axes/_axes.py
+++ b/lib/matplotlib/axes/_axes.py
@@ -2622,8 +2622,11 @@ def bar_label(self, container, labels=None, *, fmt="%g", label_type="edge",
A list of label texts, that should be displayed. If not given, the
label texts will be the data values formatted with *fmt*.
- fmt : str, default: '%g'
- A format string for the label.
+ fmt : str or callable, default: '%g'
+ An unnamed %-style or {}-style format string for the label or a
+ function to call with the value as the first argument.
+ When *fmt* is a string and can be interpreted in both formats,
+ %-style takes precedence over {}-style.
label_type : {'edge', 'center'}, default: 'edge'
The label type. Possible values:
@@ -2745,7 +2748,14 @@ def sign(x):
if np.isnan(dat):
lbl = ''
- annotation = self.annotate(fmt % value if lbl is None else lbl,
+ if lbl is None:
+ if isinstance(fmt, str):
+ lbl = cbook._auto_format_str(fmt, value)
+ elif callable(fmt):
+ lbl = fmt(value)
+ else:
+ raise TypeError("fmt must be a str or callable")
+ annotation = self.annotate(lbl,
xy, xytext, textcoords="offset points",
ha=ha, va=va, **kwargs)
annotations.append(annotation)
diff --git a/lib/matplotlib/cbook/__init__.py b/lib/matplotlib/cbook/__init__.py
index f364b8d178f2..664fcc71a262 100644
--- a/lib/matplotlib/cbook/__init__.py
+++ b/lib/matplotlib/cbook/__init__.py
@@ -2312,3 +2312,30 @@ def _unpack_to_numpy(x):
if isinstance(xtmp, np.ndarray):
return xtmp
return x
+
+
+def _auto_format_str(fmt, value):
+ """
+ Apply *value* to the format string *fmt*.
+
+ This works both with unnamed %-style formatting and
+ unnamed {}-style formatting. %-style formatting has priority.
+ If *fmt* is %-style formattable that will be used. Otherwise,
+ {}-formatting is applied. Strings without formatting placeholders
+ are passed through as is.
+
+ Examples
+ --------
+ >>> _auto_format_str('%.2f m', 0.2)
+ '0.20 m'
+ >>> _auto_format_str('{} m', 0.2)
+ '0.2 m'
+ >>> _auto_format_str('const', 0.2)
+ 'const'
+ >>> _auto_format_str('%d or {}', 0.2)
+ '0 or {}'
+ """
+ try:
+ return fmt % (value,)
+ except (TypeError, ValueError):
+ return fmt.format(value)
|
diff --git a/lib/matplotlib/tests/test_axes.py b/lib/matplotlib/tests/test_axes.py
index 268eb957f470..6141d3220d06 100644
--- a/lib/matplotlib/tests/test_axes.py
+++ b/lib/matplotlib/tests/test_axes.py
@@ -7762,14 +7762,24 @@ def test_bar_label_location_errorbars():
assert labels[1].get_va() == 'top'
-def test_bar_label_fmt():
+@pytest.mark.parametrize('fmt', [
+ '%.2f', '{:.2f}', '{:.2f}'.format
+])
+def test_bar_label_fmt(fmt):
ax = plt.gca()
rects = ax.bar([1, 2], [3, -4])
- labels = ax.bar_label(rects, fmt='%.2f')
+ labels = ax.bar_label(rects, fmt=fmt)
assert labels[0].get_text() == '3.00'
assert labels[1].get_text() == '-4.00'
+def test_bar_label_fmt_error():
+ ax = plt.gca()
+ rects = ax.bar([1, 2], [3, -4])
+ with pytest.raises(TypeError, match='str or callable'):
+ _ = ax.bar_label(rects, fmt=10)
+
+
def test_bar_label_labels():
ax = plt.gca()
rects = ax.bar([1, 2], [3, -4])
diff --git a/lib/matplotlib/tests/test_cbook.py b/lib/matplotlib/tests/test_cbook.py
index 70f2c2499418..c2f7c8d17ab2 100644
--- a/lib/matplotlib/tests/test_cbook.py
+++ b/lib/matplotlib/tests/test_cbook.py
@@ -895,3 +895,19 @@ def test_safe_first_element_with_none():
datetime_lst[0] = None
actual = cbook._safe_first_non_none(datetime_lst)
assert actual is not None and actual == datetime_lst[1]
+
+
+@pytest.mark.parametrize('fmt, value, result', [
+ ('%.2f m', 0.2, '0.20 m'),
+ ('{:.2f} m', 0.2, '0.20 m'),
+ ('{} m', 0.2, '0.2 m'),
+ ('const', 0.2, 'const'),
+ ('%d or {}', 0.2, '0 or {}'),
+ ('{{{:,.0f}}}', 2e5, '{200,000}'),
+ ('{:.2%}', 2/3, '66.67%'),
+ ('$%g', 2.54, '$2.54'),
+])
+def test_auto_format_str(fmt, value, result):
+ """Apply *value* to the format string *fmt*."""
+ assert cbook._auto_format_str(fmt, value) == result
+ assert cbook._auto_format_str(fmt, np.float64(value)) == result
|
[
{
"path": "doc/users/next_whats_new/bar_label_formatting.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/bar_label_formatting.rst",
"metadata": "diff --git a/doc/users/next_whats_new/bar_label_formatting.rst b/doc/users/next_whats_new/bar_label_formatting.rst\nnew file mode 100644\nindex 000000000000..cf64436086d4\n--- /dev/null\n+++ b/doc/users/next_whats_new/bar_label_formatting.rst\n@@ -0,0 +1,31 @@\n+Additional format string options in `~matplotlib.axes.Axes.bar_label`\n+---------------------------------------------------------------------\n+\n+The ``fmt`` argument of `~matplotlib.axes.Axes.bar_label` now accepts\n+{}-style format strings:\n+\n+.. code-block:: python\n+\n+ import matplotlib.pyplot as plt\n+\n+ fruit_names = ['Coffee', 'Salted Caramel', 'Pistachio']\n+ fruit_counts = [4000, 2000, 7000]\n+\n+ fig, ax = plt.subplots()\n+ bar_container = ax.bar(fruit_names, fruit_counts)\n+ ax.set(ylabel='pints sold', title='Gelato sales by flavor', ylim=(0, 8000))\n+ ax.bar_label(bar_container, fmt='{:,.0f}')\n+\n+It also accepts callables:\n+\n+.. code-block:: python\n+\n+ animal_names = ['Lion', 'Gazelle', 'Cheetah']\n+ mph_speed = [50, 60, 75]\n+\n+ fig, ax = plt.subplots()\n+ bar_container = ax.bar(animal_names, mph_speed)\n+ ax.set(ylabel='speed in MPH', title='Running speeds', ylim=(0, 80))\n+ ax.bar_label(\n+ bar_container, fmt=lambda x: '{:.1f} km/h'.format(x * 1.61)\n+ )\n"
}
] |
3.5
|
9b1fcf67c4228c4a2788af5bcaf0c6fde09a55bf
|
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"lib/matplotlib/tests/test_axes.py::test_twinx_axis_scales[png]",
"lib/matplotlib/tests/test_axes.py::test_annotate_across_transforms[png]",
"lib/matplotlib/tests/test_axes.py::test_eventplot_orientation[vertical-data0]",
"lib/matplotlib/tests/test_axes.py::test_boxplot[png]",
"lib/matplotlib/tests/test_axes.py::test_minorticks_on[symlog-symlog]",
"lib/matplotlib/tests/test_axes.py::test_fill_between_interpolate_decreasing[png]",
"lib/matplotlib/tests/test_cbook.py::test_normalize_kwargs_fail[inp1-kwargs_to_norm1]",
"lib/matplotlib/tests/test_axes.py::test_label_loc_horizontal[pdf]",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_weighted[svg]",
"lib/matplotlib/tests/test_axes.py::test_remove_shared_axes[add_axes-y]",
"lib/matplotlib/tests/test_axes.py::test_inverted_limits",
"lib/matplotlib/tests/test_axes.py::test_color_length_mismatch",
"lib/matplotlib/tests/test_cbook.py::test_warn_external",
"lib/matplotlib/tests/test_axes.py::test_boxplot_sym2[png]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_marker[png]",
"lib/matplotlib/tests/test_axes.py::test_spy[png]",
"lib/matplotlib/tests/test_axes.py::test_secondary_formatter",
"lib/matplotlib/tests/test_axes.py::test_remove_shared_axes[subplots_shared-y]",
"lib/matplotlib/tests/test_axes.py::test_axis_errors[TypeError-args0-kwargs0-axis\\\\(\\\\) takes 0 or 1 positional arguments but 2 were given]",
"lib/matplotlib/tests/test_axes.py::test_log_scales_invalid",
"lib/matplotlib/tests/test_axes.py::test_axhspan_epoch[svg]",
"lib/matplotlib/tests/test_axes.py::test_twin_with_aspect[y]",
"lib/matplotlib/tests/test_axes.py::test_relative_ticklabel_sizes[medium]",
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"lib/matplotlib/tests/test_cbook.py::test_to_midstep_empty",
"lib/matplotlib/tests/test_axes.py::test_markevery_linear_scales_zoomed[png]",
"lib/matplotlib/tests/test_axes.py::test_plot_format_errors[data1-:--':-' is not a valid format string \\\\(two linestyle symbols\\\\)]",
"lib/matplotlib/tests/test_cbook.py::test_safe_first_element_pandas_series",
"lib/matplotlib/tests/test_axes.py::test_loglog[png]",
"lib/matplotlib/tests/test_axes.py::test_boxplot_custom_capwidths[png]",
"lib/matplotlib/tests/test_axes.py::test_canonical[svg]",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_step_bottom_geometry",
"lib/matplotlib/tests/test_axes.py::test_alpha[png]",
"lib/matplotlib/tests/test_axes.py::test_marker_edges[svg]",
"lib/matplotlib/tests/test_axes.py::test_stem[png-w/ line collection]",
"lib/matplotlib/tests/test_axes.py::test_plot_format_errors[None-f-'f' is not a valid format string \\\\(unrecognized character 'f'\\\\)]",
"lib/matplotlib/tests/test_axes.py::test_fill_between_interpolate_decreasing[svg]",
"lib/matplotlib/tests/test_axes.py::test_bxp_nobox[png]",
"lib/matplotlib/tests/test_axes.py::test_axvspan_epoch[png]",
"lib/matplotlib/tests/test_axes.py::test_relative_ticklabel_sizes[12]",
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"lib/matplotlib/tests/test_axes.py::test_errorbar_every_invalid",
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"lib/matplotlib/tests/test_axes.py::test_title_above_offset[center title kept]",
"lib/matplotlib/tests/test_axes.py::test_bar_hatches[svg]",
"lib/matplotlib/tests/test_axes.py::test_relim_visible_only",
"lib/matplotlib/tests/test_cbook.py::test_strip_comment[a : \"quoted str\" # comment-a : \"quoted str\"]",
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"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_plot[svg]",
"lib/matplotlib/tests/test_axes.py::test_horiz_violinplot_baseline[png]",
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"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs51]",
"lib/matplotlib/tests/test_axes.py::test_bar_timedelta",
"lib/matplotlib/tests/test_axes.py::test_specgram_origin_kwarg",
"lib/matplotlib/tests/test_axes.py::test_twinx_cla",
"lib/matplotlib/tests/test_axes.py::test_marker_as_markerstyle",
"lib/matplotlib/tests/test_axes.py::test_titlesetpos",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_step[pdf]",
"lib/matplotlib/tests/test_axes.py::test_markevery_linear_scales_nans[svg]",
"lib/matplotlib/tests/test_axes.py::test_relative_ticklabel_sizes[x-small]",
"lib/matplotlib/tests/test_axes.py::test_single_point[svg]",
"lib/matplotlib/tests/test_axes.py::test_step_linestyle[pdf]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs13]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs6]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case15-None]",
"lib/matplotlib/tests/test_axes.py::test_parse_scatter_color_args_edgecolors[kwargs2-r]",
"lib/matplotlib/tests/test_axes.py::test_hist2d[pdf]",
"lib/matplotlib/tests/test_axes.py::test_color_alias",
"lib/matplotlib/tests/test_axes.py::test_parse_scatter_color_args_edgecolors[kwargs7-r]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs15]",
"lib/matplotlib/tests/test_axes.py::test_vert_violinplot_showall[png]",
"lib/matplotlib/tests/test_axes.py::test_boxplot_sym[png]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_with_prop_cycle[png]",
"lib/matplotlib/tests/test_axes.py::test_bar_labels[x2-width2-label2-expected_labels2-_nolegend_]",
"lib/matplotlib/tests/test_axes.py::test_arc_ellipse[pdf]",
"lib/matplotlib/tests/test_axes.py::test_hist2d_density",
"lib/matplotlib/tests/test_axes.py::test_errorbar_cycle_ecolor[svg]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs18]",
"lib/matplotlib/tests/test_axes.py::test_eventplot_legend",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_stepfilled_alpha[svg]",
"lib/matplotlib/tests/test_axes.py::test_pandas_index_shape",
"lib/matplotlib/tests/test_axes.py::test_marker_edges[pdf]",
"lib/matplotlib/tests/test_axes.py::test_margins_errors[ValueError-args1-kwargs1-margin must be greater than -0\\\\.5]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs42]",
"lib/matplotlib/tests/test_axes.py::test_box_aspect_custom_position",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs2]",
"lib/matplotlib/tests/test_axes.py::test_vert_violinplot_showmedians[png]",
"lib/matplotlib/tests/test_axes.py::test_arc_ellipse[png]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_size_arg_size",
"lib/matplotlib/tests/test_axes.py::test_tickdirs",
"lib/matplotlib/tests/test_axes.py::test_set_margin_updates_limits",
"lib/matplotlib/tests/test_axes.py::test_remove_shared_axes[subplots_shared-x]",
"lib/matplotlib/tests/test_cbook.py::test_index_of_pandas",
"lib/matplotlib/tests/test_axes.py::test_bxp_custombox[png]",
"lib/matplotlib/tests/test_axes.py::test_twin_spines_on_top[png]",
"lib/matplotlib/tests/test_axes.py::test_eb_line_zorder[png]",
"lib/matplotlib/tests/test_axes.py::test_axline_transaxes_panzoom[svg]",
"lib/matplotlib/tests/test_axes.py::test_formatter_ticker[svg]",
"lib/matplotlib/tests/test_axes.py::test_violinplot_bad_widths",
"lib/matplotlib/tests/test_axes.py::test_plot_format_errors[None-:o-r-':o-r' is not a valid format string \\\\(two linestyle symbols\\\\)]",
"lib/matplotlib/tests/test_axes.py::test_plot_errors",
"lib/matplotlib/tests/test_axes.py::test_indicate_inset_inverted[True-False]",
"lib/matplotlib/tests/test_axes.py::test_eventplot_orientation[horizontal-data1]",
"lib/matplotlib/tests/test_axes.py::test_pcolorflaterror",
"lib/matplotlib/tests/test_axes.py::test_rcparam_grid_minor[major-True-False]",
"lib/matplotlib/tests/test_axes.py::test_single_point[png]",
"lib/matplotlib/tests/test_axes.py::test_invalid_axis_limits",
"lib/matplotlib/tests/test_axes.py::test_stackplot_baseline[pdf]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs31]",
"lib/matplotlib/tests/test_axes.py::test_pcolornearestunits[png]",
"lib/matplotlib/tests/test_axes.py::test_displaced_spine",
"lib/matplotlib/tests/test_axes.py::test_pcolornearest[png]",
"lib/matplotlib/tests/test_axes.py::test_unautoscale[None-y]",
"lib/matplotlib/tests/test_axes.py::test_eventplot_units_list[png]",
"lib/matplotlib/tests/test_axes.py::test_markevery_linear_scales[png]",
"lib/matplotlib/tests/test_axes.py::test_pcolorfast[data0-xy1-AxesImage]",
"lib/matplotlib/tests/test_axes.py::test_hist_with_empty_input[data0-1]",
"lib/matplotlib/tests/test_axes.py::test_boxplot_not_single",
"lib/matplotlib/tests/test_axes.py::test_alpha[pdf]",
"lib/matplotlib/tests/test_axes.py::test_auto_numticks_log",
"lib/matplotlib/tests/test_axes.py::test_log_scales",
"lib/matplotlib/tests/test_axes.py::test_autoscale_tiny_range[svg]",
"lib/matplotlib/tests/test_axes.py::test_bar_labels[x1-width1-label1-expected_labels1-_nolegend_]",
"lib/matplotlib/tests/test_axes.py::test_tick_label_update",
"lib/matplotlib/tests/test_axes.py::test_markerfacecolor_none_alpha[png]",
"lib/matplotlib/tests/test_axes.py::test_mixed_collection[png]",
"lib/matplotlib/tests/test_axes.py::test_none_kwargs",
"lib/matplotlib/tests/test_axes.py::test_remove_shared_axes[subplots-y]",
"lib/matplotlib/tests/test_axes.py::test_pcolorfast[data1-xy3-PcolorImage]",
"lib/matplotlib/tests/test_axes.py::test_hist_nan_data",
"lib/matplotlib/tests/test_axes.py::test_axis_extent_arg2",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[0.5-None]",
"lib/matplotlib/tests/test_axes.py::test_hist_unequal_bins_density",
"lib/matplotlib/tests/test_axes.py::test_secondary_minorloc",
"lib/matplotlib/tests/test_axes.py::test_hexbin_log[png]",
"lib/matplotlib/tests/test_axes.py::test_xtickcolor_is_not_markercolor",
"lib/matplotlib/tests/test_axes.py::test_barh_decimal_center[png]",
"lib/matplotlib/tests/test_axes.py::test_axis_errors[ValueError-args1-kwargs1-Unrecognized string 'foo' to axis; try 'on' or 'off']",
"lib/matplotlib/tests/test_axes.py::test_fill_between_interpolate[pdf]",
"lib/matplotlib/tests/test_axes.py::test_eb_line_zorder[svg]",
"lib/matplotlib/tests/test_axes.py::test_axline_args",
"lib/matplotlib/tests/test_axes.py::test_parse_scatter_color_args_edgecolors[kwargs6-none]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs29]",
"lib/matplotlib/tests/test_axes.py::test_pcolorfast[data0-xy3-PcolorImage]",
"lib/matplotlib/tests/test_cbook.py::test_grouper_private",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[jaune-conversion]",
"lib/matplotlib/tests/test_axes.py::test_boxplot_capwidths",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_norm_vminvmax",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs38]",
"lib/matplotlib/tests/test_axes.py::test_pandas_minimal_plot",
"lib/matplotlib/tests/test_cbook.py::test_safe_first_element_with_none",
"lib/matplotlib/tests/test_axes.py::test_pcolor_regression",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case9-None]",
"lib/matplotlib/tests/test_axes.py::test_fill_between_interpolate[png]",
"lib/matplotlib/tests/test_axes.py::test_margins_errors[TypeError-args6-kwargs6-Must pass a single positional argument]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs22]",
"lib/matplotlib/tests/test_axes.py::test_rgba_markers[pdf]",
"lib/matplotlib/tests/test_axes.py::test_numerical_hist_label",
"lib/matplotlib/tests/test_axes.py::test_alpha[svg]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs41]",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_stepfilled_geometry",
"lib/matplotlib/tests/test_axes.py::test_specgram_angle[png]",
"lib/matplotlib/tests/test_axes.py::test_label_loc_rc[svg]",
"lib/matplotlib/tests/test_axes.py::test_hist_auto_bins",
"lib/matplotlib/tests/test_axes.py::test_pie_nolabel_but_legend[png]",
"lib/matplotlib/tests/test_axes.py::test_markevery_polar[pdf]",
"lib/matplotlib/tests/test_axes.py::test_title_above_offset[both titles aligned]",
"lib/matplotlib/tests/test_axes.py::test_bxp_custom_capwidths[png]",
"lib/matplotlib/tests/test_axes.py::test_bxp_customwhisker[png]",
"lib/matplotlib/tests/test_axes.py::test_hlines_default",
"lib/matplotlib/tests/test_axes.py::test_subsampled_ticklabels",
"lib/matplotlib/tests/test_axes.py::test_arc_angles[png]",
"lib/matplotlib/tests/test_axes.py::test_single_point[pdf]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_decimal[png]",
"lib/matplotlib/tests/test_axes.py::test_hist_float16",
"lib/matplotlib/tests/test_axes.py::test_bar_label_location_horizontal_yinverted",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_color_warning[kwargs2]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs47]",
"lib/matplotlib/tests/test_axes.py::test_transparent_markers[pdf]",
"lib/matplotlib/tests/test_axes.py::test_stairs_invalid_update2",
"lib/matplotlib/tests/test_axes.py::test_bxp_scalarwidth[png]",
"lib/matplotlib/tests/test_axes.py::test_twinx_knows_limits",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs3]",
"lib/matplotlib/tests/test_axes.py::test_eventplot_colors[colors1]",
"lib/matplotlib/tests/test_axes.py::test_bxp_showmean[png]",
"lib/matplotlib/tests/test_axes.py::test_violin_point_mass",
"lib/matplotlib/tests/test_axes.py::test_bar_broadcast_args",
"lib/matplotlib/tests/test_axes.py::test_relative_ticklabel_sizes[smaller]",
"lib/matplotlib/tests/test_axes.py::test_pcolorfast[data1-xy1-AxesImage]",
"lib/matplotlib/tests/test_cbook.py::test_callbackregistry_signals",
"lib/matplotlib/tests/test_axes.py::test_tick_apply_tickdir_deprecation",
"lib/matplotlib/tests/test_axes.py::test_fill_between_interpolate_nan[png]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case25-None]",
"lib/matplotlib/tests/test_axes.py::test_eb_line_zorder[pdf]",
"lib/matplotlib/tests/test_axes.py::test_strmethodformatter_auto_formatter",
"lib/matplotlib/tests/test_axes.py::test_step_linestyle[png]",
"lib/matplotlib/tests/test_axes.py::test_marker_styles[png]",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_density[svg]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs1]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case24-shape]",
"lib/matplotlib/tests/test_axes.py::test_markevery_linear_scales_zoomed[pdf]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_every[pdf]",
"lib/matplotlib/tests/test_axes.py::test_axvspan_epoch[svg]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs37]",
"lib/matplotlib/tests/test_axes.py::test_single_date[png]",
"lib/matplotlib/tests/test_axes.py::test_markevery[png]",
"lib/matplotlib/tests/test_axes.py::test_bxp_bad_capwidths",
"lib/matplotlib/tests/test_axes.py::test_contour_colorbar[pdf]",
"lib/matplotlib/tests/test_axes.py::test_bar_tick_label_multiple_old_alignment[png]",
"lib/matplotlib/tests/test_axes.py::test_secondary_fail",
"lib/matplotlib/tests/test_axes.py::test_eventplot_orientation[horizontal-data2]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_cycle_ecolor[pdf]",
"lib/matplotlib/tests/test_axes.py::test_minorticks_on_rcParams_both[png]",
"lib/matplotlib/tests/test_cbook.py::Test_callback_registry::test_pickling",
"lib/matplotlib/tests/test_axes.py::test_hist_datetime_datasets_bins[date2num]",
"lib/matplotlib/tests/test_axes.py::test_autoscale_tiny_range[pdf]",
"lib/matplotlib/tests/test_axes.py::test_broken_barh_empty",
"lib/matplotlib/tests/test_cbook.py::test_strip_comment_invalid",
"lib/matplotlib/tests/test_axes.py::test_pcolormesh[svg]",
"lib/matplotlib/tests/test_axes.py::test_hlines[png]",
"lib/matplotlib/tests/test_axes.py::test_shared_with_aspect_2",
"lib/matplotlib/tests/test_cbook.py::test_format_approx",
"lib/matplotlib/tests/test_axes.py::test_hist_with_empty_input[data2-2]",
"lib/matplotlib/tests/test_axes.py::test_shared_aspect_error",
"lib/matplotlib/tests/test_axes.py::test_parse_scatter_color_args_edgecolors[kwargs1-None]"
] |
[
"lib/matplotlib/tests/test_cbook.py::test_auto_format_str[%d or {}-0.2-0 or {}]",
"lib/matplotlib/tests/test_axes.py::test_bar_label_fmt_error",
"lib/matplotlib/tests/test_cbook.py::test_auto_format_str[{:.2f} m-0.2-0.20 m]",
"lib/matplotlib/tests/test_cbook.py::test_auto_format_str[{:.2%}-0.6666666666666666-66.67%]",
"lib/matplotlib/tests/test_cbook.py::test_auto_format_str[%.2f m-0.2-0.20 m]",
"lib/matplotlib/tests/test_cbook.py::test_auto_format_str[const-0.2-const]",
"lib/matplotlib/tests/test_cbook.py::test_auto_format_str[{{{:,.0f}}}-200000.0-{200,000}]",
"lib/matplotlib/tests/test_cbook.py::test_auto_format_str[$%g-2.54-$2.54]",
"lib/matplotlib/tests/test_axes.py::test_bar_label_fmt[{:.2f}]",
"lib/matplotlib/tests/test_axes.py::test_bar_label_fmt[format]",
"lib/matplotlib/tests/test_cbook.py::test_auto_format_str[{} m-0.2-0.2 m]"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": [
{
"type": "function",
"name": "_auto_format_str"
},
{
"type": "field",
"name": "_auto_format_str"
}
]
}
|
[
{
"path": "doc/users/next_whats_new/bar_label_formatting.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/bar_label_formatting.rst",
"metadata": "diff --git a/doc/users/next_whats_new/bar_label_formatting.rst b/doc/users/next_whats_new/bar_label_formatting.rst\nnew file mode 100644\nindex 000000000000..cf64436086d4\n--- /dev/null\n+++ b/doc/users/next_whats_new/bar_label_formatting.rst\n@@ -0,0 +1,31 @@\n+Additional format string options in `~matplotlib.axes.Axes.bar_label`\n+---------------------------------------------------------------------\n+\n+The ``fmt`` argument of `~matplotlib.axes.Axes.bar_label` now accepts\n+{}-style format strings:\n+\n+.. code-block:: python\n+\n+ import matplotlib.pyplot as plt\n+\n+ fruit_names = ['Coffee', 'Salted Caramel', 'Pistachio']\n+ fruit_counts = [4000, 2000, 7000]\n+\n+ fig, ax = plt.subplots()\n+ bar_container = ax.bar(fruit_names, fruit_counts)\n+ ax.set(ylabel='pints sold', title='Gelato sales by flavor', ylim=(0, 8000))\n+ ax.bar_label(bar_container, fmt='{:,.0f}')\n+\n+It also accepts callables:\n+\n+.. code-block:: python\n+\n+ animal_names = ['Lion', 'Gazelle', 'Cheetah']\n+ mph_speed = [50, 60, 75]\n+\n+ fig, ax = plt.subplots()\n+ bar_container = ax.bar(animal_names, mph_speed)\n+ ax.set(ylabel='speed in MPH', title='Running speeds', ylim=(0, 80))\n+ ax.bar_label(\n+ bar_container, fmt=lambda x: '{:.1f} km/h'.format(x * 1.61)\n+ )\n"
}
] |
diff --git a/doc/users/next_whats_new/bar_label_formatting.rst b/doc/users/next_whats_new/bar_label_formatting.rst
new file mode 100644
index 000000000000..cf64436086d4
--- /dev/null
+++ b/doc/users/next_whats_new/bar_label_formatting.rst
@@ -0,0 +1,31 @@
+Additional format string options in `~matplotlib.axes.Axes.bar_label`
+---------------------------------------------------------------------
+
+The ``fmt`` argument of `~matplotlib.axes.Axes.bar_label` now accepts
+{}-style format strings:
+
+.. code-block:: python
+
+ import matplotlib.pyplot as plt
+
+ fruit_names = ['Coffee', 'Salted Caramel', 'Pistachio']
+ fruit_counts = [4000, 2000, 7000]
+
+ fig, ax = plt.subplots()
+ bar_container = ax.bar(fruit_names, fruit_counts)
+ ax.set(ylabel='pints sold', title='Gelato sales by flavor', ylim=(0, 8000))
+ ax.bar_label(bar_container, fmt='{:,.0f}')
+
+It also accepts callables:
+
+.. code-block:: python
+
+ animal_names = ['Lion', 'Gazelle', 'Cheetah']
+ mph_speed = [50, 60, 75]
+
+ fig, ax = plt.subplots()
+ bar_container = ax.bar(animal_names, mph_speed)
+ ax.set(ylabel='speed in MPH', title='Running speeds', ylim=(0, 80))
+ ax.bar_label(
+ bar_container, fmt=lambda x: '{:.1f} km/h'.format(x * 1.61)
+ )
If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:
[{'type': 'function', 'name': '_auto_format_str'}, {'type': 'field', 'name': '_auto_format_str'}]
|
matplotlib/matplotlib
|
matplotlib__matplotlib-20966
|
https://github.com/matplotlib/matplotlib/pull/20966
|
diff --git a/doc/users/next_whats_new/callbacks_on_norms.rst b/doc/users/next_whats_new/callbacks_on_norms.rst
new file mode 100644
index 000000000000..1904a92d2fba
--- /dev/null
+++ b/doc/users/next_whats_new/callbacks_on_norms.rst
@@ -0,0 +1,8 @@
+A callback registry has been added to Normalize objects
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+`.colors.Normalize` objects now have a callback registry, ``callbacks``,
+that can be connected to by other objects to be notified when the norm is
+updated. The callback emits the key ``changed`` when the norm is modified.
+`.cm.ScalarMappable` is now a listener and will register a change
+when the norm's vmin, vmax or other attributes are changed.
diff --git a/lib/matplotlib/cm.py b/lib/matplotlib/cm.py
index 0af2f0f327d9..76c1c5d4f7f2 100644
--- a/lib/matplotlib/cm.py
+++ b/lib/matplotlib/cm.py
@@ -337,7 +337,7 @@ def __init__(self, norm=None, cmap=None):
The colormap used to map normalized data values to RGBA colors.
"""
self._A = None
- self.norm = None # So that the setter knows we're initializing.
+ self._norm = None # So that the setter knows we're initializing.
self.set_norm(norm) # The Normalize instance of this ScalarMappable.
self.cmap = None # So that the setter knows we're initializing.
self.set_cmap(cmap) # The Colormap instance of this ScalarMappable.
@@ -496,6 +496,8 @@ def set_clim(self, vmin=None, vmax=None):
.. ACCEPTS: (vmin: float, vmax: float)
"""
+ # If the norm's limits are updated self.changed() will be called
+ # through the callbacks attached to the norm
if vmax is None:
try:
vmin, vmax = vmin
@@ -505,7 +507,6 @@ def set_clim(self, vmin=None, vmax=None):
self.norm.vmin = colors._sanitize_extrema(vmin)
if vmax is not None:
self.norm.vmax = colors._sanitize_extrema(vmax)
- self.changed()
def get_alpha(self):
"""
@@ -531,6 +532,30 @@ def set_cmap(self, cmap):
if not in_init:
self.changed() # Things are not set up properly yet.
+ @property
+ def norm(self):
+ return self._norm
+
+ @norm.setter
+ def norm(self, norm):
+ _api.check_isinstance((colors.Normalize, None), norm=norm)
+ if norm is None:
+ norm = colors.Normalize()
+
+ if norm is self.norm:
+ # We aren't updating anything
+ return
+
+ in_init = self.norm is None
+ # Remove the current callback and connect to the new one
+ if not in_init:
+ self.norm.callbacks.disconnect(self._id_norm)
+ self._norm = norm
+ self._id_norm = self.norm.callbacks.connect('changed',
+ self.changed)
+ if not in_init:
+ self.changed()
+
def set_norm(self, norm):
"""
Set the normalization instance.
@@ -545,13 +570,7 @@ def set_norm(self, norm):
the norm of the mappable will reset the norm, locator, and formatters
on the colorbar to default.
"""
- _api.check_isinstance((colors.Normalize, None), norm=norm)
- in_init = self.norm is None
- if norm is None:
- norm = colors.Normalize()
self.norm = norm
- if not in_init:
- self.changed() # Things are not set up properly yet.
def autoscale(self):
"""
@@ -560,8 +579,9 @@ def autoscale(self):
"""
if self._A is None:
raise TypeError('You must first set_array for mappable')
+ # If the norm's limits are updated self.changed() will be called
+ # through the callbacks attached to the norm
self.norm.autoscale(self._A)
- self.changed()
def autoscale_None(self):
"""
@@ -570,8 +590,9 @@ def autoscale_None(self):
"""
if self._A is None:
raise TypeError('You must first set_array for mappable')
+ # If the norm's limits are updated self.changed() will be called
+ # through the callbacks attached to the norm
self.norm.autoscale_None(self._A)
- self.changed()
def changed(self):
"""
diff --git a/lib/matplotlib/colorbar.py b/lib/matplotlib/colorbar.py
index 459b14f6c5a7..9d40ac8e5e9c 100644
--- a/lib/matplotlib/colorbar.py
+++ b/lib/matplotlib/colorbar.py
@@ -471,6 +471,7 @@ def __init__(self, ax, mappable=None, *, cmap=None,
self.ax.add_collection(self.dividers)
self.locator = None
+ self.minorlocator = None
self.formatter = None
self.__scale = None # linear, log10 for now. Hopefully more?
@@ -1096,7 +1097,7 @@ def _mesh(self):
# vmax of the colorbar, not the norm. This allows the situation
# where the colormap has a narrower range than the colorbar, to
# accommodate extra contours:
- norm = copy.copy(self.norm)
+ norm = copy.deepcopy(self.norm)
norm.vmin = self.vmin
norm.vmax = self.vmax
x = np.array([0.0, 1.0])
diff --git a/lib/matplotlib/colors.py b/lib/matplotlib/colors.py
index c5db6117f1bc..58e3fe198498 100644
--- a/lib/matplotlib/colors.py
+++ b/lib/matplotlib/colors.py
@@ -1123,10 +1123,50 @@ def __init__(self, vmin=None, vmax=None, clip=False):
-----
Returns 0 if ``vmin == vmax``.
"""
- self.vmin = _sanitize_extrema(vmin)
- self.vmax = _sanitize_extrema(vmax)
- self.clip = clip
- self._scale = None # will default to LinearScale for colorbar
+ self._vmin = _sanitize_extrema(vmin)
+ self._vmax = _sanitize_extrema(vmax)
+ self._clip = clip
+ self._scale = None
+ self.callbacks = cbook.CallbackRegistry()
+
+ @property
+ def vmin(self):
+ return self._vmin
+
+ @vmin.setter
+ def vmin(self, value):
+ value = _sanitize_extrema(value)
+ if value != self._vmin:
+ self._vmin = value
+ self._changed()
+
+ @property
+ def vmax(self):
+ return self._vmax
+
+ @vmax.setter
+ def vmax(self, value):
+ value = _sanitize_extrema(value)
+ if value != self._vmax:
+ self._vmax = value
+ self._changed()
+
+ @property
+ def clip(self):
+ return self._clip
+
+ @clip.setter
+ def clip(self, value):
+ if value != self._clip:
+ self._clip = value
+ self._changed()
+
+ def _changed(self):
+ """
+ Call this whenever the norm is changed to notify all the
+ callback listeners to the 'changed' signal.
+ """
+ self.callbacks.process('changed')
@staticmethod
def process_value(value):
@@ -1273,7 +1313,7 @@ def __init__(self, vcenter, vmin=None, vmax=None):
"""
super().__init__(vmin=vmin, vmax=vmax)
- self.vcenter = vcenter
+ self._vcenter = vcenter
if vcenter is not None and vmax is not None and vcenter >= vmax:
raise ValueError('vmin, vcenter, and vmax must be in '
'ascending order')
@@ -1281,6 +1321,16 @@ def __init__(self, vcenter, vmin=None, vmax=None):
raise ValueError('vmin, vcenter, and vmax must be in '
'ascending order')
+ @property
+ def vcenter(self):
+ return self._vcenter
+
+ @vcenter.setter
+ def vcenter(self, value):
+ if value != self._vcenter:
+ self._vcenter = value
+ self._changed()
+
def autoscale_None(self, A):
"""
Get vmin and vmax, and then clip at vcenter
@@ -1387,7 +1437,9 @@ def vcenter(self):
@vcenter.setter
def vcenter(self, vcenter):
- self._vcenter = vcenter
+ if vcenter != self._vcenter:
+ self._vcenter = vcenter
+ self._changed()
if self.vmax is not None:
# recompute halfrange assuming vmin and vmax represent
# min and max of data
diff --git a/lib/matplotlib/contour.py b/lib/matplotlib/contour.py
index 7dec80943993..4d124ce8c57c 100644
--- a/lib/matplotlib/contour.py
+++ b/lib/matplotlib/contour.py
@@ -1090,6 +1090,15 @@ def _make_paths(self, segs, kinds):
in zip(segs, kinds)]
def changed(self):
+ if not hasattr(self, "cvalues"):
+ # Just return after calling the super() changed function
+ cm.ScalarMappable.changed(self)
+ return
+ # Force an autoscale immediately because self.to_rgba() calls
+ # autoscale_None() internally with the data passed to it,
+ # so if vmin/vmax are not set yet, this would override them with
+ # content from *cvalues* rather than levels like we want
+ self.norm.autoscale_None(self.levels)
tcolors = [(tuple(rgba),)
for rgba in self.to_rgba(self.cvalues, alpha=self.alpha)]
self.tcolors = tcolors
diff --git a/lib/matplotlib/image.py b/lib/matplotlib/image.py
index ca5b7da5f808..2036bf7e17c9 100644
--- a/lib/matplotlib/image.py
+++ b/lib/matplotlib/image.py
@@ -537,11 +537,14 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
if isinstance(self.norm, mcolors.LogNorm) and s_vmin <= 0:
# Don't give 0 or negative values to LogNorm
s_vmin = np.finfo(scaled_dtype).eps
- with cbook._setattr_cm(self.norm,
- vmin=s_vmin,
- vmax=s_vmax,
- ):
- output = self.norm(resampled_masked)
+ # Block the norm from sending an update signal during the
+ # temporary vmin/vmax change
+ with self.norm.callbacks.blocked():
+ with cbook._setattr_cm(self.norm,
+ vmin=s_vmin,
+ vmax=s_vmax,
+ ):
+ output = self.norm(resampled_masked)
else:
if A.ndim == 2: # _interpolation_stage == 'rgba'
self.norm.autoscale_None(A)
|
diff --git a/lib/matplotlib/tests/test_colors.py b/lib/matplotlib/tests/test_colors.py
index ae004e957591..bf89a3a82364 100644
--- a/lib/matplotlib/tests/test_colors.py
+++ b/lib/matplotlib/tests/test_colors.py
@@ -1,5 +1,6 @@
import copy
import itertools
+import unittest.mock
from io import BytesIO
import numpy as np
@@ -17,7 +18,7 @@
import matplotlib.cbook as cbook
import matplotlib.pyplot as plt
import matplotlib.scale as mscale
-from matplotlib.testing.decorators import image_comparison
+from matplotlib.testing.decorators import image_comparison, check_figures_equal
@pytest.mark.parametrize('N, result', [
@@ -1408,3 +1409,69 @@ def test_norm_deepcopy():
norm2 = copy.deepcopy(norm)
assert norm2._scale is None
assert norm2.vmin == norm.vmin
+
+
+def test_norm_callback():
+ increment = unittest.mock.Mock(return_value=None)
+
+ norm = mcolors.Normalize()
+ norm.callbacks.connect('changed', increment)
+ # Haven't updated anything, so call count should be 0
+ assert increment.call_count == 0
+
+ # Now change vmin and vmax to test callbacks
+ norm.vmin = 1
+ assert increment.call_count == 1
+ norm.vmax = 5
+ assert increment.call_count == 2
+ # callback shouldn't be called if setting to the same value
+ norm.vmin = 1
+ assert increment.call_count == 2
+ norm.vmax = 5
+ assert increment.call_count == 2
+
+
+def test_scalarmappable_norm_update():
+ norm = mcolors.Normalize()
+ sm = matplotlib.cm.ScalarMappable(norm=norm, cmap='plasma')
+ # sm doesn't have a stale attribute at first, set it to False
+ sm.stale = False
+ # The mappable should be stale after updating vmin/vmax
+ norm.vmin = 5
+ assert sm.stale
+ sm.stale = False
+ norm.vmax = 5
+ assert sm.stale
+ sm.stale = False
+ norm.clip = True
+ assert sm.stale
+ # change to the CenteredNorm and TwoSlopeNorm to test those
+ # Also make sure that updating the norm directly and with
+ # set_norm both update the Norm callback
+ norm = mcolors.CenteredNorm()
+ sm.norm = norm
+ sm.stale = False
+ norm.vcenter = 1
+ assert sm.stale
+ norm = mcolors.TwoSlopeNorm(vcenter=0, vmin=-1, vmax=1)
+ sm.set_norm(norm)
+ sm.stale = False
+ norm.vcenter = 1
+ assert sm.stale
+
+
+@check_figures_equal()
+def test_norm_update_figs(fig_test, fig_ref):
+ ax_ref = fig_ref.add_subplot()
+ ax_test = fig_test.add_subplot()
+
+ z = np.arange(100).reshape((10, 10))
+ ax_ref.imshow(z, norm=mcolors.Normalize(10, 90))
+
+ # Create the norm beforehand with different limits and then update
+ # after adding to the plot
+ norm = mcolors.Normalize(0, 1)
+ ax_test.imshow(z, norm=norm)
+ # Force initial draw to make sure it isn't already stale
+ fig_test.canvas.draw()
+ norm.vmin, norm.vmax = 10, 90
diff --git a/lib/matplotlib/tests/test_image.py b/lib/matplotlib/tests/test_image.py
index 37dddd4e4706..2e7fae6c58d8 100644
--- a/lib/matplotlib/tests/test_image.py
+++ b/lib/matplotlib/tests/test_image.py
@@ -1017,8 +1017,8 @@ def test_imshow_bool():
def test_full_invalid():
fig, ax = plt.subplots()
ax.imshow(np.full((10, 10), np.nan))
- with pytest.warns(UserWarning):
- fig.canvas.draw()
+
+ fig.canvas.draw()
@pytest.mark.parametrize("fmt,counted",
|
[
{
"path": "doc/users/next_whats_new/callbacks_on_norms.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/callbacks_on_norms.rst",
"metadata": "diff --git a/doc/users/next_whats_new/callbacks_on_norms.rst b/doc/users/next_whats_new/callbacks_on_norms.rst\nnew file mode 100644\nindex 000000000000..1904a92d2fba\n--- /dev/null\n+++ b/doc/users/next_whats_new/callbacks_on_norms.rst\n@@ -0,0 +1,8 @@\n+A callback registry has been added to Normalize objects\n+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n+\n+`.colors.Normalize` objects now have a callback registry, ``callbacks``,\n+that can be connected to by other objects to be notified when the norm is\n+updated. The callback emits the key ``changed`` when the norm is modified.\n+`.cm.ScalarMappable` is now a listener and will register a change\n+when the norm's vmin, vmax or other attributes are changed.\n"
}
] |
3.4
|
1dff078a4645666af374dc55812788d37bea7612
|
[
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[OrRd_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[cubehelix]",
"lib/matplotlib/tests/test_image.py::test_imsave_fspath[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[summer]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Blues]",
"lib/matplotlib/tests/test_image.py::test_load_from_url",
"lib/matplotlib/tests/test_image.py::test_composite[False-2-ps- colorimage]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[BuGn_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[YlOrBr_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_heat_r]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_VminGTVcenter",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[YlGn_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[seismic]",
"lib/matplotlib/tests/test_colors.py::test_conversions",
"lib/matplotlib/tests/test_colors.py::test_to_rgba_array_alpha_array",
"lib/matplotlib/tests/test_colors.py::test_LogNorm",
"lib/matplotlib/tests/test_image.py::test_image_alpha[pdf]",
"lib/matplotlib/tests/test_image.py::test_image_cursor_formatting",
"lib/matplotlib/tests/test_colors.py::test_colormap_equals",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[winter_r]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_VcenterGTVmax",
"lib/matplotlib/tests/test_image.py::test_image_composite_alpha[pdf]",
"lib/matplotlib/tests/test_image.py::test_no_interpolation_origin[png]",
"lib/matplotlib/tests/test_colors.py::test_light_source_shading_empty_mask",
"lib/matplotlib/tests/test_image.py::test_image_array_alpha[pdf]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[coolwarm]",
"lib/matplotlib/tests/test_colors.py::test_cn",
"lib/matplotlib/tests/test_image.py::test_axesimage_setdata",
"lib/matplotlib/tests/test_image.py::test_image_clip[svg]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[twilight_shifted_r]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_Even",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Oranges]",
"lib/matplotlib/tests/test_colors.py::test_pandas_iterable",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[magma]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Dark2_r]",
"lib/matplotlib/tests/test_image.py::test_imshow_float128",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Greys_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gnuplot_r]",
"lib/matplotlib/tests/test_image.py::test_imshow_masked_interpolation[pdf]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_scaleout_center",
"lib/matplotlib/tests/test_image.py::test_imsave[png]",
"lib/matplotlib/tests/test_image.py::test_imshow[png]",
"lib/matplotlib/tests/test_image.py::test_empty_imshow[<lambda>1]",
"lib/matplotlib/tests/test_colors.py::test_light_source_planar_hillshading",
"lib/matplotlib/tests/test_image.py::test_rotate_image[svg]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[inferno_r]",
"lib/matplotlib/tests/test_colors.py::test_BoundaryNorm",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[jet]",
"lib/matplotlib/tests/test_image.py::test_imshow_antialiased[png-5-10-nearest]",
"lib/matplotlib/tests/test_image.py::test_imshow_pil[pdf]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[bwr_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdBu_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[cubehelix_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[CMRmap_r]",
"lib/matplotlib/tests/test_image.py::test_imread_pil_uint16",
"lib/matplotlib/tests/test_image.py::test_jpeg_2d",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[twilight_shifted]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[coolwarm_r]",
"lib/matplotlib/tests/test_colors.py::test_norm_update_figs[png]",
"lib/matplotlib/tests/test_image.py::test_spy_box[pdf]",
"lib/matplotlib/tests/test_colors.py::test_create_lookup_table[1-result2]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[bone]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[BrBG]",
"lib/matplotlib/tests/test_image.py::test_imsave_pil_kwargs_tiff",
"lib/matplotlib/tests/test_colors.py::test_FuncNorm",
"lib/matplotlib/tests/test_image.py::test_figimage[png-True]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Set3]",
"lib/matplotlib/tests/test_colors.py::test_Normalize",
"lib/matplotlib/tests/test_image.py::test_imshow_bignumbers[png]",
"lib/matplotlib/tests/test_image.py::test_spy_box[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[rainbow]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[tab20c]",
"lib/matplotlib/tests/test_image.py::test_imshow_pil[svg]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_rainbow_r]",
"lib/matplotlib/tests/test_image.py::test_imshow_endianess[png]",
"lib/matplotlib/tests/test_image.py::test_imsave[tiff]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_VmaxEqualsVcenter",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[spring]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[magma_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[YlOrRd]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[binary_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[flag_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[turbo_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_copy",
"lib/matplotlib/tests/test_image.py::test_imshow_antialiased[png-3-9.1-nearest]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_VminEqualsVcenter",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_scale",
"lib/matplotlib/tests/test_image.py::test_no_interpolation_origin[svg]",
"lib/matplotlib/tests/test_colors.py::test_create_lookup_table[2-result1]",
"lib/matplotlib/tests/test_colors.py::test_light_source_hillshading",
"lib/matplotlib/tests/test_image.py::test_mask_image[svg]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[viridis]",
"lib/matplotlib/tests/test_image.py::test_imshow_clips_rgb_to_valid_range[dtype1]",
"lib/matplotlib/tests/test_image.py::test_imshow_10_10_5",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PRGn]",
"lib/matplotlib/tests/test_image.py::test_bbox_image_inverted[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PiYG]",
"lib/matplotlib/tests/test_colors.py::test_norm_deepcopy",
"lib/matplotlib/tests/test_colors.py::test_SymLogNorm",
"lib/matplotlib/tests/test_image.py::test_norm_change[png]",
"lib/matplotlib/tests/test_image.py::test_empty_imshow[Normalize]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[copper_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Oranges_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdYlGn]",
"lib/matplotlib/tests/test_image.py::test_cursor_data",
"lib/matplotlib/tests/test_image.py::test_unclipped",
"lib/matplotlib/tests/test_image.py::test_nonuniformimage_setnorm",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_autoscale_None_vmax",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[prism_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[terrain_r]",
"lib/matplotlib/tests/test_image.py::test_log_scale_image[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[cool_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[pink_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_stern_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[brg_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdYlGn_r]",
"lib/matplotlib/tests/test_colors.py::test_create_lookup_table[5-result0]",
"lib/matplotlib/tests/test_image.py::test_imshow_clips_rgb_to_valid_range[dtype3]",
"lib/matplotlib/tests/test_image.py::test_huge_range_log[png--1]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[copper]",
"lib/matplotlib/tests/test_image.py::test_format_cursor_data[data1-[0.123]-[0.123]]",
"lib/matplotlib/tests/test_image.py::test_imsave_pil_kwargs_png",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Greens_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Wistia]",
"lib/matplotlib/tests/test_colors.py::test_double_register_builtin_cmap",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdYlBu_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PRGn_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_ncar_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[seismic_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_yarg_r]",
"lib/matplotlib/tests/test_image.py::test_zoom_and_clip_upper_origin[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[tab20_r]",
"lib/matplotlib/tests/test_colors.py::test_resample",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[winter]",
"lib/matplotlib/tests/test_colors.py::test_PowerNorm",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[tab10_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[binary]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gray_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_dict_deprecate",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gnuplot2]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdPu_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_earth]",
"lib/matplotlib/tests/test_image.py::test_exact_vmin",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[YlGn]",
"lib/matplotlib/tests/test_image.py::test_image_interps[pdf]",
"lib/matplotlib/tests/test_colors.py::test_to_rgba_array_single_str",
"lib/matplotlib/tests/test_image.py::test_full_invalid",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_earth_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PuOr_r]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_TwoSlopeNorm_VminGTVmax",
"lib/matplotlib/tests/test_image.py::test_imshow_zoom[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[cool]",
"lib/matplotlib/tests/test_image.py::test_figimage[pdf-True]",
"lib/matplotlib/tests/test_image.py::test_imshow_no_warn_invalid",
"lib/matplotlib/tests/test_image.py::test_huge_range_log[png-1]",
"lib/matplotlib/tests/test_colors.py::test_colormap_endian",
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"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[YlOrRd_r]",
"lib/matplotlib/tests/test_image.py::test_figureimage_setdata"
] |
[
"lib/matplotlib/tests/test_colors.py::test_norm_callback",
"lib/matplotlib/tests/test_colors.py::test_scalarmappable_norm_update"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/users/next_whats_new/callbacks_on_norms.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/callbacks_on_norms.rst",
"metadata": "diff --git a/doc/users/next_whats_new/callbacks_on_norms.rst b/doc/users/next_whats_new/callbacks_on_norms.rst\nnew file mode 100644\nindex 000000000000..1904a92d2fba\n--- /dev/null\n+++ b/doc/users/next_whats_new/callbacks_on_norms.rst\n@@ -0,0 +1,8 @@\n+A callback registry has been added to Normalize objects\n+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n+\n+`.colors.Normalize` objects now have a callback registry, ``callbacks``,\n+that can be connected to by other objects to be notified when the norm is\n+updated. The callback emits the key ``changed`` when the norm is modified.\n+`.cm.ScalarMappable` is now a listener and will register a change\n+when the norm's vmin, vmax or other attributes are changed.\n"
}
] |
diff --git a/doc/users/next_whats_new/callbacks_on_norms.rst b/doc/users/next_whats_new/callbacks_on_norms.rst
new file mode 100644
index 000000000000..1904a92d2fba
--- /dev/null
+++ b/doc/users/next_whats_new/callbacks_on_norms.rst
@@ -0,0 +1,8 @@
+A callback registry has been added to Normalize objects
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+`.colors.Normalize` objects now have a callback registry, ``callbacks``,
+that can be connected to by other objects to be notified when the norm is
+updated. The callback emits the key ``changed`` when the norm is modified.
+`.cm.ScalarMappable` is now a listener and will register a change
+when the norm's vmin, vmax or other attributes are changed.
|
matplotlib/matplotlib
|
matplotlib__matplotlib-24728
|
https://github.com/matplotlib/matplotlib/pull/24728
|
diff --git a/doc/api/axes_api.rst b/doc/api/axes_api.rst
index 07586690347f..3457368fa51c 100644
--- a/doc/api/axes_api.rst
+++ b/doc/api/axes_api.rst
@@ -110,11 +110,12 @@ Statistics
:template: autosummary.rst
:nosignatures:
+ Axes.ecdf
Axes.boxplot
Axes.violinplot
- Axes.violin
Axes.bxp
+ Axes.violin
Binned
------
diff --git a/doc/api/pyplot_summary.rst b/doc/api/pyplot_summary.rst
index 616e9c257aa5..d0def34c4995 100644
--- a/doc/api/pyplot_summary.rst
+++ b/doc/api/pyplot_summary.rst
@@ -114,6 +114,7 @@ Statistics
:template: autosummary.rst
:nosignatures:
+ ecdf
boxplot
violinplot
diff --git a/doc/users/next_whats_new/ecdf.rst b/doc/users/next_whats_new/ecdf.rst
new file mode 100644
index 000000000000..01f639aa737b
--- /dev/null
+++ b/doc/users/next_whats_new/ecdf.rst
@@ -0,0 +1,13 @@
+``Axes.ecdf``
+~~~~~~~~~~~~~
+A new Axes method, `~.Axes.ecdf`, allows plotting empirical cumulative
+distribution functions without any binning.
+
+.. plot::
+ :include-source:
+
+ import matplotlib.pyplot as plt
+ import numpy as np
+
+ fig, ax = plt.subplots()
+ ax.ecdf(np.random.randn(100))
diff --git a/galleries/examples/statistics/histogram_cumulative.py b/galleries/examples/statistics/histogram_cumulative.py
index cbe786f2e970..9ce16568d126 100644
--- a/galleries/examples/statistics/histogram_cumulative.py
+++ b/galleries/examples/statistics/histogram_cumulative.py
@@ -1,36 +1,27 @@
"""
-==================================================
-Using histograms to plot a cumulative distribution
-==================================================
-
-This shows how to plot a cumulative, normalized histogram as a
-step function in order to visualize the empirical cumulative
-distribution function (CDF) of a sample. We also show the theoretical CDF.
-
-A couple of other options to the ``hist`` function are demonstrated. Namely, we
-use the *density* parameter to normalize the histogram and a couple of different
-options to the *cumulative* parameter. The *density* parameter takes a boolean
-value. When ``True``, the bin heights are scaled such that the total area of
-the histogram is 1. The *cumulative* keyword argument is a little more nuanced.
-Like *density*, you can pass it True or False, but you can also pass it -1 to
-reverse the distribution.
-
-Since we're showing a normalized and cumulative histogram, these curves
-are effectively the cumulative distribution functions (CDFs) of the
-samples. In engineering, empirical CDFs are sometimes called
-"non-exceedance" curves. In other words, you can look at the
-y-value for a given-x-value to get the probability of and observation
-from the sample not exceeding that x-value. For example, the value of
-225 on the x-axis corresponds to about 0.85 on the y-axis, so there's an
-85% chance that an observation in the sample does not exceed 225.
-Conversely, setting, ``cumulative`` to -1 as is done in the
-last series for this example, creates an "exceedance" curve.
-
-Selecting different bin counts and sizes can significantly affect the
-shape of a histogram. The Astropy docs have a great section on how to
-select these parameters:
-http://docs.astropy.org/en/stable/visualization/histogram.html
-
+=================================
+Plotting cumulative distributions
+=================================
+
+This example shows how to plot the empirical cumulative distribution function
+(ECDF) of a sample. We also show the theoretical CDF.
+
+In engineering, ECDFs are sometimes called "non-exceedance" curves: the y-value
+for a given x-value gives probability that an observation from the sample is
+below that x-value. For example, the value of 220 on the x-axis corresponds to
+about 0.80 on the y-axis, so there is an 80% chance that an observation in the
+sample does not exceed 220. Conversely, the empirical *complementary*
+cumulative distribution function (the ECCDF, or "exceedance" curve) shows the
+probability y that an observation from the sample is above a value x.
+
+A direct method to plot ECDFs is `.Axes.ecdf`. Passing ``complementary=True``
+results in an ECCDF instead.
+
+Alternatively, one can use ``ax.hist(data, density=True, cumulative=True)`` to
+first bin the data, as if plotting a histogram, and then compute and plot the
+cumulative sums of the frequencies of entries in each bin. Here, to plot the
+ECCDF, pass ``cumulative=-1``. Note that this approach results in an
+approximation of the E(C)CDF, whereas `.Axes.ecdf` is exact.
"""
import matplotlib.pyplot as plt
@@ -40,33 +31,37 @@
mu = 200
sigma = 25
-n_bins = 50
-x = np.random.normal(mu, sigma, size=100)
+n_bins = 25
+data = np.random.normal(mu, sigma, size=100)
-fig, ax = plt.subplots(figsize=(8, 4))
+fig = plt.figure(figsize=(9, 4), layout="constrained")
+axs = fig.subplots(1, 2, sharex=True, sharey=True)
-# plot the cumulative histogram
-n, bins, patches = ax.hist(x, n_bins, density=True, histtype='step',
- cumulative=True, label='Empirical')
-
-# Add a line showing the expected distribution.
+# Cumulative distributions.
+axs[0].ecdf(data, label="CDF")
+n, bins, patches = axs[0].hist(data, n_bins, density=True, histtype="step",
+ cumulative=True, label="Cumulative histogram")
+x = np.linspace(data.min(), data.max())
y = ((1 / (np.sqrt(2 * np.pi) * sigma)) *
- np.exp(-0.5 * (1 / sigma * (bins - mu))**2))
+ np.exp(-0.5 * (1 / sigma * (x - mu))**2))
y = y.cumsum()
y /= y[-1]
-
-ax.plot(bins, y, 'k--', linewidth=1.5, label='Theoretical')
-
-# Overlay a reversed cumulative histogram.
-ax.hist(x, bins=bins, density=True, histtype='step', cumulative=-1,
- label='Reversed emp.')
-
-# tidy up the figure
-ax.grid(True)
-ax.legend(loc='right')
-ax.set_title('Cumulative step histograms')
-ax.set_xlabel('Annual rainfall (mm)')
-ax.set_ylabel('Likelihood of occurrence')
+axs[0].plot(x, y, "k--", linewidth=1.5, label="Theory")
+
+# Complementary cumulative distributions.
+axs[1].ecdf(data, complementary=True, label="CCDF")
+axs[1].hist(data, bins=bins, density=True, histtype="step", cumulative=-1,
+ label="Reversed cumulative histogram")
+axs[1].plot(x, 1 - y, "k--", linewidth=1.5, label="Theory")
+
+# Label the figure.
+fig.suptitle("Cumulative distributions")
+for ax in axs:
+ ax.grid(True)
+ ax.legend()
+ ax.set_xlabel("Annual rainfall (mm)")
+ ax.set_ylabel("Probability of occurrence")
+ ax.label_outer()
plt.show()
@@ -78,3 +73,4 @@
# in this example:
#
# - `matplotlib.axes.Axes.hist` / `matplotlib.pyplot.hist`
+# - `matplotlib.axes.Axes.ecdf` / `matplotlib.pyplot.ecdf`
diff --git a/galleries/plot_types/stats/ecdf.py b/galleries/plot_types/stats/ecdf.py
new file mode 100644
index 000000000000..bd5f9fa9e5b2
--- /dev/null
+++ b/galleries/plot_types/stats/ecdf.py
@@ -0,0 +1,21 @@
+"""
+=======
+ecdf(x)
+=======
+
+See `~matplotlib.axes.Axes.ecdf`.
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+plt.style.use('_mpl-gallery')
+
+# make data
+np.random.seed(1)
+x = 4 + np.random.normal(0, 1.5, 200)
+
+# plot:
+fig, ax = plt.subplots()
+ax.ecdf(x)
+plt.show()
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
index 23c57105ca5e..99a8a9f6fc51 100644
--- a/lib/matplotlib/axes/_axes.py
+++ b/lib/matplotlib/axes/_axes.py
@@ -7112,6 +7112,108 @@ def hist2d(self, x, y, bins=10, range=None, density=False, weights=None,
return h, xedges, yedges, pc
+ @_preprocess_data(replace_names=["x", "weights"], label_namer="x")
+ @_docstring.dedent_interpd
+ def ecdf(self, x, weights=None, *, complementary=False,
+ orientation="vertical", compress=False, **kwargs):
+ """
+ Compute and plot the empirical cumulative distribution function of *x*.
+
+ .. versionadded:: 3.8
+
+ Parameters
+ ----------
+ x : 1d array-like
+ The input data. Infinite entries are kept (and move the relevant
+ end of the ecdf from 0/1), but NaNs and masked values are errors.
+
+ weights : 1d array-like or None, default: None
+ The weights of the entries; must have the same shape as *x*.
+ Weights corresponding to NaN data points are dropped, and then the
+ remaining weights are normalized to sum to 1. If unset, all
+ entries have the same weight.
+
+ complementary : bool, default: False
+ Whether to plot a cumulative distribution function, which increases
+ from 0 to 1 (the default), or a complementary cumulative
+ distribution function, which decreases from 1 to 0.
+
+ orientation : {"vertical", "horizontal"}, default: "vertical"
+ Whether the entries are plotted along the x-axis ("vertical", the
+ default) or the y-axis ("horizontal"). This parameter takes the
+ same values as in `~.Axes.hist`.
+
+ compress : bool, default: False
+ Whether multiple entries with the same values are grouped together
+ (with a summed weight) before plotting. This is mainly useful if
+ *x* contains many identical data points, to decrease the rendering
+ complexity of the plot. If *x* contains no duplicate points, this
+ has no effect and just uses some time and memory.
+
+ Other Parameters
+ ----------------
+ data : indexable object, optional
+ DATA_PARAMETER_PLACEHOLDER
+
+ **kwargs
+ Keyword arguments control the `.Line2D` properties:
+
+ %(Line2D:kwdoc)s
+
+ Returns
+ -------
+ `.Line2D`
+
+ Notes
+ -----
+ The ecdf plot can be thought of as a cumulative histogram with one bin
+ per data entry; i.e. it reports on the entire dataset without any
+ arbitrary binning.
+
+ If *x* contains NaNs or masked entries, either remove them first from
+ the array (if they should not taken into account), or replace them by
+ -inf or +inf (if they should be sorted at the beginning or the end of
+ the array).
+ """
+ _api.check_in_list(["horizontal", "vertical"], orientation=orientation)
+ if "drawstyle" in kwargs or "ds" in kwargs:
+ raise TypeError("Cannot pass 'drawstyle' or 'ds' to ecdf()")
+ if np.ma.getmask(x).any():
+ raise ValueError("ecdf() does not support masked entries")
+ x = np.asarray(x)
+ if np.isnan(x).any():
+ raise ValueError("ecdf() does not support NaNs")
+ argsort = np.argsort(x)
+ x = x[argsort]
+ if weights is None:
+ # Ensure that we end at exactly 1, avoiding floating point errors.
+ cum_weights = (1 + np.arange(len(x))) / len(x)
+ else:
+ weights = np.take(weights, argsort) # Reorder weights like we reordered x.
+ cum_weights = np.cumsum(weights / np.sum(weights))
+ if compress:
+ # Get indices of unique x values.
+ compress_idxs = [0, *(x[:-1] != x[1:]).nonzero()[0] + 1]
+ x = x[compress_idxs]
+ cum_weights = cum_weights[compress_idxs]
+ if orientation == "vertical":
+ if not complementary:
+ line, = self.plot([x[0], *x], [0, *cum_weights],
+ drawstyle="steps-post", **kwargs)
+ else:
+ line, = self.plot([*x, x[-1]], [1, *1 - cum_weights],
+ drawstyle="steps-pre", **kwargs)
+ line.sticky_edges.y[:] = [0, 1]
+ else: # orientation == "horizontal":
+ if not complementary:
+ line, = self.plot([0, *cum_weights], [x[0], *x],
+ drawstyle="steps-pre", **kwargs)
+ else:
+ line, = self.plot([1, *1 - cum_weights], [*x, x[-1]],
+ drawstyle="steps-post", **kwargs)
+ line.sticky_edges.x[:] = [0, 1]
+ return line
+
@_preprocess_data(replace_names=["x"])
@_docstring.dedent_interpd
def psd(self, x, NFFT=None, Fs=None, Fc=None, detrend=None,
diff --git a/lib/matplotlib/pyplot.py b/lib/matplotlib/pyplot.py
index 60e0a91a5860..f1e2918080c9 100644
--- a/lib/matplotlib/pyplot.py
+++ b/lib/matplotlib/pyplot.py
@@ -2515,6 +2515,17 @@ def csd(
**({"data": data} if data is not None else {}), **kwargs)
+# Autogenerated by boilerplate.py. Do not edit as changes will be lost.
+@_copy_docstring_and_deprecators(Axes.ecdf)
+def ecdf(
+ x, weights=None, *, complementary=False,
+ orientation='vertical', compress=False, data=None, **kwargs):
+ return gca().ecdf(
+ x, weights=weights, complementary=complementary,
+ orientation=orientation, compress=compress,
+ **({"data": data} if data is not None else {}), **kwargs)
+
+
# Autogenerated by boilerplate.py. Do not edit as changes will be lost.
@_copy_docstring_and_deprecators(Axes.errorbar)
def errorbar(
diff --git a/tools/boilerplate.py b/tools/boilerplate.py
index 0b00d7a12b4a..ee61459b3cd3 100644
--- a/tools/boilerplate.py
+++ b/tools/boilerplate.py
@@ -246,6 +246,7 @@ def boilerplate_gen():
'contour',
'contourf',
'csd',
+ 'ecdf',
'errorbar',
'eventplot',
'fill',
|
diff --git a/lib/matplotlib/tests/test_axes.py b/lib/matplotlib/tests/test_axes.py
index bd26419dee4d..b68ebcf57ba7 100644
--- a/lib/matplotlib/tests/test_axes.py
+++ b/lib/matplotlib/tests/test_axes.py
@@ -8448,3 +8448,36 @@ def test_rc_axes_label_formatting():
assert ax.xaxis.label.get_color() == 'red'
assert ax.xaxis.label.get_fontsize() == 20
assert ax.xaxis.label.get_fontweight() == 'bold'
+
+
+@check_figures_equal(extensions=["png"])
+def test_ecdf(fig_test, fig_ref):
+ data = np.array([0, -np.inf, -np.inf, np.inf, 1, 1, 2])
+ weights = range(len(data))
+ axs_test = fig_test.subplots(1, 2)
+ for ax, orientation in zip(axs_test, ["vertical", "horizontal"]):
+ l0 = ax.ecdf(data, orientation=orientation)
+ l1 = ax.ecdf("d", "w", data={"d": np.ma.array(data), "w": weights},
+ orientation=orientation,
+ complementary=True, compress=True, ls=":")
+ assert len(l0.get_xdata()) == (~np.isnan(data)).sum() + 1
+ assert len(l1.get_xdata()) == len({*data[~np.isnan(data)]}) + 1
+ axs_ref = fig_ref.subplots(1, 2)
+ axs_ref[0].plot([-np.inf, -np.inf, -np.inf, 0, 1, 1, 2, np.inf],
+ np.arange(8) / 7, ds="steps-post")
+ axs_ref[0].plot([-np.inf, 0, 1, 2, np.inf, np.inf],
+ np.array([21, 20, 18, 14, 3, 0]) / 21,
+ ds="steps-pre", ls=":")
+ axs_ref[1].plot(np.arange(8) / 7,
+ [-np.inf, -np.inf, -np.inf, 0, 1, 1, 2, np.inf],
+ ds="steps-pre")
+ axs_ref[1].plot(np.array([21, 20, 18, 14, 3, 0]) / 21,
+ [-np.inf, 0, 1, 2, np.inf, np.inf],
+ ds="steps-post", ls=":")
+
+
+def test_ecdf_invalid():
+ with pytest.raises(ValueError):
+ plt.ecdf([1, np.nan])
+ with pytest.raises(ValueError):
+ plt.ecdf(np.ma.array([1, 2], mask=[True, False]))
|
[
{
"path": "doc/api/axes_api.rst",
"old_path": "a/doc/api/axes_api.rst",
"new_path": "b/doc/api/axes_api.rst",
"metadata": "diff --git a/doc/api/axes_api.rst b/doc/api/axes_api.rst\nindex 07586690347f..3457368fa51c 100644\n--- a/doc/api/axes_api.rst\n+++ b/doc/api/axes_api.rst\n@@ -110,11 +110,12 @@ Statistics\n :template: autosummary.rst\n :nosignatures:\n \n+ Axes.ecdf\n Axes.boxplot\n Axes.violinplot\n \n- Axes.violin\n Axes.bxp\n+ Axes.violin\n \n Binned\n ------\n"
},
{
"path": "doc/api/pyplot_summary.rst",
"old_path": "a/doc/api/pyplot_summary.rst",
"new_path": "b/doc/api/pyplot_summary.rst",
"metadata": "diff --git a/doc/api/pyplot_summary.rst b/doc/api/pyplot_summary.rst\nindex 616e9c257aa5..d0def34c4995 100644\n--- a/doc/api/pyplot_summary.rst\n+++ b/doc/api/pyplot_summary.rst\n@@ -114,6 +114,7 @@ Statistics\n :template: autosummary.rst\n :nosignatures:\n \n+ ecdf\n boxplot\n violinplot\n \n"
},
{
"path": "doc/users/next_whats_new/ecdf.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/ecdf.rst",
"metadata": "diff --git a/doc/users/next_whats_new/ecdf.rst b/doc/users/next_whats_new/ecdf.rst\nnew file mode 100644\nindex 000000000000..01f639aa737b\n--- /dev/null\n+++ b/doc/users/next_whats_new/ecdf.rst\n@@ -0,0 +1,13 @@\n+``Axes.ecdf``\n+~~~~~~~~~~~~~\n+A new Axes method, `~.Axes.ecdf`, allows plotting empirical cumulative\n+distribution functions without any binning.\n+\n+.. plot::\n+ :include-source:\n+\n+ import matplotlib.pyplot as plt\n+ import numpy as np\n+\n+ fig, ax = plt.subplots()\n+ ax.ecdf(np.random.randn(100))\n"
}
] |
3.7
|
5a34696d712dcb9c939e726e234e28a3135974ff
|
[
"lib/matplotlib/tests/test_axes.py::test_stem_dates",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs12]",
"lib/matplotlib/tests/test_axes.py::test_hist_zorder[stepfilled-1]",
"lib/matplotlib/tests/test_axes.py::test_xaxis_offsetText_color",
"lib/matplotlib/tests/test_axes.py::test_axline_transaxes_panzoom[png]",
"lib/matplotlib/tests/test_axes.py::test_annotate_signature",
"lib/matplotlib/tests/test_axes.py::test_boxplot[png]",
"lib/matplotlib/tests/test_axes.py::test_bxp_custommedian[png]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_invalid_color[png]",
"lib/matplotlib/tests/test_axes.py::test_empty_eventplot",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case11-shape]",
"lib/matplotlib/tests/test_axes.py::test_twin_logscale[png-y]",
"lib/matplotlib/tests/test_axes.py::test_autoscale_tiny_range[svg]",
"lib/matplotlib/tests/test_axes.py::test_mollweide_inverse_forward_closure",
"lib/matplotlib/tests/test_axes.py::test_errorbar_cycle_ecolor[svg]",
"lib/matplotlib/tests/test_axes.py::test_bar_label_fmt[{:.2f}]",
"lib/matplotlib/tests/test_axes.py::test_contour_colorbar[png]",
"lib/matplotlib/tests/test_axes.py::test_color_alias",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_single_point[png]",
"lib/matplotlib/tests/test_axes.py::test_bar_edgecolor_none_alpha",
"lib/matplotlib/tests/test_axes.py::test_lines_with_colors[png-data1]",
"lib/matplotlib/tests/test_axes.py::test_shared_axes_retick",
"lib/matplotlib/tests/test_axes.py::test_violinplot_bad_quantiles",
"lib/matplotlib/tests/test_axes.py::test_pandas_indexing_hist",
"lib/matplotlib/tests/test_axes.py::test_lines_with_colors[png-data0]",
"lib/matplotlib/tests/test_axes.py::test_bar_color_none_alpha",
"lib/matplotlib/tests/test_axes.py::test_bar_errbar_zorder",
"lib/matplotlib/tests/test_axes.py::test_step_linestyle[pdf]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_cycle_ecolor[png]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs5]",
"lib/matplotlib/tests/test_axes.py::test_bxp_baseline[png]",
"lib/matplotlib/tests/test_axes.py::test_bxp_horizontal[png]",
"lib/matplotlib/tests/test_axes.py::test_arrow_empty",
"lib/matplotlib/tests/test_axes.py::test_hist2d[svg]",
"lib/matplotlib/tests/test_axes.py::test_remove_shared_axes[gca-x]",
"lib/matplotlib/tests/test_axes.py::test_hist_log[png]",
"lib/matplotlib/tests/test_axes.py::test_pcolorfast[data1-xy0-AxesImage]",
"lib/matplotlib/tests/test_axes.py::test_mixed_collection[svg]",
"lib/matplotlib/tests/test_axes.py::test_hlines[png]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_no_invalid_color[png]",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_weighted[png]",
"lib/matplotlib/tests/test_axes.py::test_ytickcolor_is_not_markercolor",
"lib/matplotlib/tests/test_axes.py::test_relative_ticklabel_sizes[small]",
"lib/matplotlib/tests/test_axes.py::test_set_ticks_kwargs_raise_error_without_labels",
"lib/matplotlib/tests/test_axes.py::test_color_None",
"lib/matplotlib/tests/test_axes.py::test_basic_annotate[pdf]",
"lib/matplotlib/tests/test_axes.py::test_stairs_datetime[png]",
"lib/matplotlib/tests/test_axes.py::test_margins",
"lib/matplotlib/tests/test_axes.py::test_axvspan_epoch[pdf]",
"lib/matplotlib/tests/test_axes.py::test_parse_scatter_color_args_edgecolors[kwargs3-expected_edgecolors3]",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_step[svg]",
"lib/matplotlib/tests/test_axes.py::test_mollweide_grid[svg]",
"lib/matplotlib/tests/test_axes.py::test_bxp_customoutlier[png]",
"lib/matplotlib/tests/test_axes.py::test_eventplot_units_list[png]",
"lib/matplotlib/tests/test_axes.py::test_hist_step_bottom[png]",
"lib/matplotlib/tests/test_axes.py::test_imshow[svg]",
"lib/matplotlib/tests/test_axes.py::test_stairs_invalid_update",
"lib/matplotlib/tests/test_axes.py::test_remove_shared_axes[subplots_shared-x]",
"lib/matplotlib/tests/test_axes.py::test_remove_shared_axes_relim",
"lib/matplotlib/tests/test_axes.py::test_symlog[pdf]",
"lib/matplotlib/tests/test_axes.py::test_strmethodformatter_auto_formatter",
"lib/matplotlib/tests/test_axes.py::test_hist_density[png]",
"lib/matplotlib/tests/test_axes.py::test_stem_markerfmt",
"lib/matplotlib/tests/test_axes.py::test_eventplot_colors[colors2]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs22]",
"lib/matplotlib/tests/test_axes.py::test_multiplot_autoscale",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[none-None]",
"lib/matplotlib/tests/test_axes.py::test_parse_scatter_color_args_edgecolors[kwargs2-r]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_colorcycle",
"lib/matplotlib/tests/test_axes.py::test_secondary_xy[png]",
"lib/matplotlib/tests/test_axes.py::test_auto_numticks",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs36]",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_density[svg]",
"lib/matplotlib/tests/test_axes.py::test_title_location_shared[True]",
"lib/matplotlib/tests/test_axes.py::test_hist_step_bottom_geometry",
"lib/matplotlib/tests/test_axes.py::test_artist_sublists",
"lib/matplotlib/tests/test_axes.py::test_fill_between_interpolate[png]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs38]",
"lib/matplotlib/tests/test_axes.py::test_eventplot[svg]",
"lib/matplotlib/tests/test_axes.py::test_single_date[png]",
"lib/matplotlib/tests/test_axes.py::test_bxp_with_ylabels[png]",
"lib/matplotlib/tests/test_axes.py::test_eventplot_colors[colors1]",
"lib/matplotlib/tests/test_axes.py::test_axis_errors[ValueError-args1-kwargs1-Unrecognized string 'foo' to axis; try 'on' or 'off']",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs10]",
"lib/matplotlib/tests/test_axes.py::test_date_timezone_x_and_y[png]",
"lib/matplotlib/tests/test_axes.py::test_axline[svg]",
"lib/matplotlib/tests/test_axes.py::test_set_get_ticklabels[png]",
"lib/matplotlib/tests/test_axes.py::test_box_aspect_custom_position",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case5-None]",
"lib/matplotlib/tests/test_axes.py::test_markers_fillstyle_rcparams[png]",
"lib/matplotlib/tests/test_axes.py::test_rc_grid[png]",
"lib/matplotlib/tests/test_axes.py::test_inset_subclass",
"lib/matplotlib/tests/test_axes.py::test_mixed_collection[pdf]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs6]",
"lib/matplotlib/tests/test_axes.py::test_spectrum[png]",
"lib/matplotlib/tests/test_axes.py::test_markevery[pdf]",
"lib/matplotlib/tests/test_axes.py::test_dash_offset[pdf]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[red-None]",
"lib/matplotlib/tests/test_axes.py::test_eventplot[pdf]",
"lib/matplotlib/tests/test_axes.py::test_bar_tick_label_multiple_old_alignment[png]",
"lib/matplotlib/tests/test_axes.py::test_relative_ticklabel_sizes[x-large]",
"lib/matplotlib/tests/test_axes.py::test_eventplot[png]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs29]",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_step_geometry",
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"lib/matplotlib/tests/test_axes.py::test_axline_transaxes_panzoom[pdf]",
"lib/matplotlib/tests/test_axes.py::test_unautoscale[True-x]",
"lib/matplotlib/tests/test_axes.py::test_autoscale_tiny_range[pdf]",
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"lib/matplotlib/tests/test_axes.py::test_contour_colorbar[pdf]",
"lib/matplotlib/tests/test_axes.py::test_pcolormesh[png]",
"lib/matplotlib/tests/test_axes.py::test_hist_stepfilled_bottom_geometry",
"lib/matplotlib/tests/test_axes.py::test_fillbetween_cycle",
"lib/matplotlib/tests/test_axes.py::test_shared_with_aspect_1",
"lib/matplotlib/tests/test_axes.py::test_pcolormesh_alpha[pdf]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case22-shape]",
"lib/matplotlib/tests/test_axes.py::test_boxplot_sym[png]",
"lib/matplotlib/tests/test_axes.py::test_structured_data",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_plot[svg]",
"lib/matplotlib/tests/test_axes.py::test_hist2d[png]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs13]",
"lib/matplotlib/tests/test_axes.py::test_pcolor_datetime_axis[png]",
"lib/matplotlib/tests/test_axes.py::test_horiz_violinplot_baseline[png]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs44]",
"lib/matplotlib/tests/test_axes.py::test_pandas_bar_align_center",
"lib/matplotlib/tests/test_axes.py::test_horiz_violinplot_custompoints_200[png]",
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"lib/matplotlib/tests/test_axes.py::test_axline_args",
"lib/matplotlib/tests/test_axes.py::test_spines_properbbox_after_zoom",
"lib/matplotlib/tests/test_axes.py::test_get_labels",
"lib/matplotlib/tests/test_axes.py::test_bar_label_location_center",
"lib/matplotlib/tests/test_axes.py::test_secondary_minorloc",
"lib/matplotlib/tests/test_axes.py::test_twin_with_aspect[x]",
"lib/matplotlib/tests/test_axes.py::test_axis_errors[TypeError-args0-kwargs0-axis\\\\(\\\\) takes from 0 to 1 positional arguments but 2 were given]",
"lib/matplotlib/tests/test_axes.py::test_relative_ticklabel_sizes[larger]",
"lib/matplotlib/tests/test_axes.py::test_title_location_shared[False]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs21]",
"lib/matplotlib/tests/test_axes.py::test_normal_axes",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[None-None]",
"lib/matplotlib/tests/test_axes.py::test_boxplot_rc_parameters[png]",
"lib/matplotlib/tests/test_axes.py::test_fill_units[png]",
"lib/matplotlib/tests/test_axes.py::test_small_autoscale",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case10-None]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs17]",
"lib/matplotlib/tests/test_axes.py::test_single_point[png]",
"lib/matplotlib/tests/test_axes.py::test_bar_timedelta",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_bar[png]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_line_specific_kwargs",
"lib/matplotlib/tests/test_axes.py::test_axisbelow[png]",
"lib/matplotlib/tests/test_axes.py::test_marker_edges[svg]",
"lib/matplotlib/tests/test_axes.py::test_imshow_clip[pdf]",
"lib/matplotlib/tests/test_axes.py::test_relative_ticklabel_sizes[smaller]",
"lib/matplotlib/tests/test_axes.py::test_fill_between_input[2d_x_input]",
"lib/matplotlib/tests/test_axes.py::test_boxplot[pdf]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs27]",
"lib/matplotlib/tests/test_axes.py::test_axis_method_errors",
"lib/matplotlib/tests/test_axes.py::test_date_timezone_x[png]",
"lib/matplotlib/tests/test_axes.py::test_bxp_bad_capwidths",
"lib/matplotlib/tests/test_axes.py::test_canonical[svg]",
"lib/matplotlib/tests/test_axes.py::test_eventplot_orientation[None-data1]",
"lib/matplotlib/tests/test_axes.py::test_markevery_linear_scales_nans[png]",
"lib/matplotlib/tests/test_axes.py::test_2dcolor_plot[pdf]",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_stepfilled[png]",
"lib/matplotlib/tests/test_axes.py::test_pcolorauto[png-False]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_shape",
"lib/matplotlib/tests/test_axes.py::test_twin_spines[png]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_limits[png]",
"lib/matplotlib/tests/test_axes.py::test_margins_errors[ValueError-args0-kwargs0-margin must be greater than -0\\\\.5]",
"lib/matplotlib/tests/test_axes.py::test_violin_point_mass",
"lib/matplotlib/tests/test_axes.py::test_remove_shared_axes[subplots_shared-y]",
"lib/matplotlib/tests/test_axes.py::test_indicate_inset_inverted[False-False]",
"lib/matplotlib/tests/test_axes.py::test_bxp_custom_capwidth[png]",
"lib/matplotlib/tests/test_axes.py::test_bxp_bad_widths",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs31]",
"lib/matplotlib/tests/test_axes.py::test_bar_label_location_errorbars",
"lib/matplotlib/tests/test_axes.py::test_inset_polar[png]",
"lib/matplotlib/tests/test_axes.py::test_boxplot_bad_medians",
"lib/matplotlib/tests/test_axes.py::test_aspect_nonlinear_adjustable_datalim",
"lib/matplotlib/tests/test_axes.py::test_boxplot_marker_behavior",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_single_color_c[png]",
"lib/matplotlib/tests/test_axes.py::test_markevery_linear_scales[svg]",
"lib/matplotlib/tests/test_axes.py::test_axline_minmax[axvspan-axhspan-args1]",
"lib/matplotlib/tests/test_axes.py::test_markevery[svg]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs26]",
"lib/matplotlib/tests/test_axes.py::test_bezier_autoscale",
"lib/matplotlib/tests/test_axes.py::test_pie_textprops",
"lib/matplotlib/tests/test_axes.py::test_zorder_and_explicit_rasterization",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs2]",
"lib/matplotlib/tests/test_axes.py::test_nonfinite_limits[pdf]",
"lib/matplotlib/tests/test_axes.py::test_ylabel_ha_with_position[left]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_color_warning[kwargs0]",
"lib/matplotlib/tests/test_axes.py::test_label_loc_horizontal[pdf]",
"lib/matplotlib/tests/test_axes.py::test_psd_csd_edge_cases",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs3]",
"lib/matplotlib/tests/test_axes.py::test_annotate_across_transforms[png]",
"lib/matplotlib/tests/test_axes.py::test_fill_betweenx_input[2d_x2_input]",
"lib/matplotlib/tests/test_axes.py::test_log_scales",
"lib/matplotlib/tests/test_axes.py::test_unautoscale[False-y]",
"lib/matplotlib/tests/test_axes.py::test_plot_format_errors[data1-:--':-' is not a valid format string \\\\(two linestyle symbols\\\\)]",
"lib/matplotlib/tests/test_axes.py::test_step_linestyle[png]",
"lib/matplotlib/tests/test_axes.py::test_plot_format_errors[None-o+-'o\\\\+' is not a valid format string \\\\(two marker symbols\\\\)]",
"lib/matplotlib/tests/test_axes.py::test_markevery_linear_scales_nans[pdf]",
"lib/matplotlib/tests/test_axes.py::test_pcolorargs",
"lib/matplotlib/tests/test_axes.py::test_eventplot_orientation[None-data2]",
"lib/matplotlib/tests/test_axes.py::test_empty_ticks_fixed_loc",
"lib/matplotlib/tests/test_axes.py::test_bad_plot_args",
"lib/matplotlib/tests/test_axes.py::test_spy_invalid_kwargs",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs42]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs46]",
"lib/matplotlib/tests/test_axes.py::test_basic_annotate[svg]",
"lib/matplotlib/tests/test_axes.py::test_gettightbbox_ignore_nan",
"lib/matplotlib/tests/test_axes.py::test_pie_hatch_single[svg]",
"lib/matplotlib/tests/test_axes.py::test_axhspan_epoch[png]",
"lib/matplotlib/tests/test_axes.py::test_plot_decimal[png]",
"lib/matplotlib/tests/test_axes.py::test_secondary_repr",
"lib/matplotlib/tests/test_axes.py::test_pcolorfast[data1-xy1-AxesImage]",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_weighted[svg]",
"lib/matplotlib/tests/test_axes.py::test_bxp_with_xlabels[png]",
"lib/matplotlib/tests/test_axes.py::test_twin_remove[png]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_plot[pdf]",
"lib/matplotlib/tests/test_axes.py::test_parse_scatter_color_args[params3-expected_result3]",
"lib/matplotlib/tests/test_axes.py::test_tick_padding_tightbbox",
"lib/matplotlib/tests/test_axes.py::test_markevery_polar[svg]",
"lib/matplotlib/tests/test_axes.py::test_twinx_cla",
"lib/matplotlib/tests/test_axes.py::test_hist_offset[svg]",
"lib/matplotlib/tests/test_axes.py::test_autoscale_log_shared",
"lib/matplotlib/tests/test_axes.py::test_errorbar_linewidth_type[elinewidth1]",
"lib/matplotlib/tests/test_axes.py::test_pie_hatch_single[png]",
"lib/matplotlib/tests/test_axes.py::test_fill_between_interpolate[pdf]",
"lib/matplotlib/tests/test_axes.py::test_contour_hatching[pdf]",
"lib/matplotlib/tests/test_axes.py::test_set_ticks_with_labels[png]",
"lib/matplotlib/tests/test_axes.py::test_minorticks_on[symlog-symlog]",
"lib/matplotlib/tests/test_axes.py::test_horiz_violinplot_showmeans[png]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case7-conversion]",
"lib/matplotlib/tests/test_axes.py::test_title_above_offset[center title kept]",
"lib/matplotlib/tests/test_axes.py::test_pie_get_negative_values",
"lib/matplotlib/tests/test_axes.py::test_aitoff_proj[png]",
"lib/matplotlib/tests/test_axes.py::test_polar_interpolation_steps_variable_r[png]",
"lib/matplotlib/tests/test_axes.py::test_barh_decimal_height[png]",
"lib/matplotlib/tests/test_axes.py::test_margins_errors[TypeError-args6-kwargs6-Must pass a single positional argument]",
"lib/matplotlib/tests/test_axes.py::test_inverted_limits",
"lib/matplotlib/tests/test_axes.py::test_boxplot_capwidths",
"lib/matplotlib/tests/test_axes.py::test_auto_numticks_log",
"lib/matplotlib/tests/test_axes.py::test_axes_tick_params_ylabelside",
"lib/matplotlib/tests/test_axes.py::test_hist_barstacked_bottom_unchanged",
"lib/matplotlib/tests/test_axes.py::test_eventplot_defaults[png]",
"lib/matplotlib/tests/test_axes.py::test_bxp_nocaps[png]",
"lib/matplotlib/tests/test_axes.py::test_set_aspect_negative",
"lib/matplotlib/tests/test_axes.py::test_vert_violinplot_showmeans[png]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[jaune-conversion]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_nonefmt",
"lib/matplotlib/tests/test_axes.py::test_horiz_violinplot_custompoints_10[png]",
"lib/matplotlib/tests/test_axes.py::test_boxplot_with_CIarray[png]",
"lib/matplotlib/tests/test_axes.py::test_boxplot_autorange_whiskers[png]",
"lib/matplotlib/tests/test_axes.py::test_boxplot_rc_parameters[svg]",
"lib/matplotlib/tests/test_axes.py::test_redraw_in_frame",
"lib/matplotlib/tests/test_axes.py::test_fill_between_interpolate_decreasing[pdf]",
"lib/matplotlib/tests/test_axes.py::test_shared_bool",
"lib/matplotlib/tests/test_axes.py::test_title_no_move_off_page",
"lib/matplotlib/tests/test_axes.py::test_titletwiny",
"lib/matplotlib/tests/test_axes.py::test_stairs_edge_handling[png]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs30]",
"lib/matplotlib/tests/test_axes.py::test_plot_format_errors[None-:o-r-':o-r' is not a valid format string \\\\(two linestyle symbols\\\\)]",
"lib/matplotlib/tests/test_axes.py::test_remove_shared_axes[gca-y]",
"lib/matplotlib/tests/test_axes.py::test_markevery_line[png]",
"lib/matplotlib/tests/test_axes.py::test_pcolormesh_small[eps]",
"lib/matplotlib/tests/test_axes.py::test_remove_shared_axes[add_axes-x]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case27-conversion]",
"lib/matplotlib/tests/test_axes.py::test_nonfinite_limits[png]",
"lib/matplotlib/tests/test_axes.py::test_fill_between_input[2d_y1_input]",
"lib/matplotlib/tests/test_axes.py::test_bxp_customwhisker[png]",
"lib/matplotlib/tests/test_axes.py::test_alpha[png]",
"lib/matplotlib/tests/test_axes.py::test_subclass_clear_cla",
"lib/matplotlib/tests/test_axes.py::test_normalize_kwarg_pie",
"lib/matplotlib/tests/test_axes.py::test_vlines_default",
"lib/matplotlib/tests/test_axes.py::test_stairs_baseline_0[png]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case29-conversion]",
"lib/matplotlib/tests/test_axes.py::test_ylabel_ha_with_position[right]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case1-conversion]",
"lib/matplotlib/tests/test_axes.py::test_yaxis_offsetText_color"
] |
[
"lib/matplotlib/tests/test_axes.py::test_ecdf[png]",
"lib/matplotlib/tests/test_axes.py::test_ecdf_invalid"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": [
{
"type": "field",
"name": "compress"
},
{
"type": "field",
"name": "compress"
},
{
"type": "field",
"name": "complementary"
},
{
"type": "field",
"name": "complementary"
},
{
"type": "file",
"name": "galleries/plot_types/stats/ecdf.py"
},
{
"type": "field",
"name": "complementary"
}
]
}
|
[
{
"path": "doc/api/axes_api.rst",
"old_path": "a/doc/api/axes_api.rst",
"new_path": "b/doc/api/axes_api.rst",
"metadata": "diff --git a/doc/api/axes_api.rst b/doc/api/axes_api.rst\nindex 07586690347f..3457368fa51c 100644\n--- a/doc/api/axes_api.rst\n+++ b/doc/api/axes_api.rst\n@@ -110,11 +110,12 @@ Statistics\n :template: autosummary.rst\n :nosignatures:\n \n+ Axes.ecdf\n Axes.boxplot\n Axes.violinplot\n \n- Axes.violin\n Axes.bxp\n+ Axes.violin\n \n Binned\n ------\n"
},
{
"path": "doc/api/pyplot_summary.rst",
"old_path": "a/doc/api/pyplot_summary.rst",
"new_path": "b/doc/api/pyplot_summary.rst",
"metadata": "diff --git a/doc/api/pyplot_summary.rst b/doc/api/pyplot_summary.rst\nindex 616e9c257aa5..d0def34c4995 100644\n--- a/doc/api/pyplot_summary.rst\n+++ b/doc/api/pyplot_summary.rst\n@@ -114,6 +114,7 @@ Statistics\n :template: autosummary.rst\n :nosignatures:\n \n+ ecdf\n boxplot\n violinplot\n \n"
},
{
"path": "doc/users/next_whats_new/ecdf.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/ecdf.rst",
"metadata": "diff --git a/doc/users/next_whats_new/ecdf.rst b/doc/users/next_whats_new/ecdf.rst\nnew file mode 100644\nindex 000000000000..01f639aa737b\n--- /dev/null\n+++ b/doc/users/next_whats_new/ecdf.rst\n@@ -0,0 +1,13 @@\n+``Axes.ecdf``\n+~~~~~~~~~~~~~\n+A new Axes method, `~.Axes.ecdf`, allows plotting empirical cumulative\n+distribution functions without any binning.\n+\n+.. plot::\n+ :include-source:\n+\n+ import matplotlib.pyplot as plt\n+ import numpy as np\n+\n+ fig, ax = plt.subplots()\n+ ax.ecdf(np.random.randn(100))\n"
}
] |
diff --git a/doc/api/axes_api.rst b/doc/api/axes_api.rst
index 07586690347f..3457368fa51c 100644
--- a/doc/api/axes_api.rst
+++ b/doc/api/axes_api.rst
@@ -110,11 +110,12 @@ Statistics
:template: autosummary.rst
:nosignatures:
+ Axes.ecdf
Axes.boxplot
Axes.violinplot
- Axes.violin
Axes.bxp
+ Axes.violin
Binned
------
diff --git a/doc/api/pyplot_summary.rst b/doc/api/pyplot_summary.rst
index 616e9c257aa5..d0def34c4995 100644
--- a/doc/api/pyplot_summary.rst
+++ b/doc/api/pyplot_summary.rst
@@ -114,6 +114,7 @@ Statistics
:template: autosummary.rst
:nosignatures:
+ ecdf
boxplot
violinplot
diff --git a/doc/users/next_whats_new/ecdf.rst b/doc/users/next_whats_new/ecdf.rst
new file mode 100644
index 000000000000..01f639aa737b
--- /dev/null
+++ b/doc/users/next_whats_new/ecdf.rst
@@ -0,0 +1,13 @@
+``Axes.ecdf``
+~~~~~~~~~~~~~
+A new Axes method, `~.Axes.ecdf`, allows plotting empirical cumulative
+distribution functions without any binning.
+
+.. plot::
+ :include-source:
+
+ import matplotlib.pyplot as plt
+ import numpy as np
+
+ fig, ax = plt.subplots()
+ ax.ecdf(np.random.randn(100))
If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:
[{'type': 'field', 'name': 'compress'}, {'type': 'field', 'name': 'compress'}, {'type': 'field', 'name': 'complementary'}, {'type': 'field', 'name': 'complementary'}, {'type': 'file', 'name': 'galleries/plot_types/stats/ecdf.py'}, {'type': 'field', 'name': 'complementary'}]
|
matplotlib/matplotlib
|
matplotlib__matplotlib-24937
|
https://github.com/matplotlib/matplotlib/pull/24937
|
diff --git a/doc/users/next_whats_new/pie_hatch.rst b/doc/users/next_whats_new/pie_hatch.rst
new file mode 100644
index 000000000000..f54def10e954
--- /dev/null
+++ b/doc/users/next_whats_new/pie_hatch.rst
@@ -0,0 +1,18 @@
+``hatch`` parameter for pie
+-------------------------------------------
+
+`~matplotlib.axes.Axes.pie` now accepts a *hatch* keyword that takes as input
+a hatch or list of hatches:
+
+.. plot::
+ :include-source: true
+ :alt: Two pie charts, identified as ax1 and ax2, both have a small blue slice, a medium orange slice, and a large green slice. ax1 has a dot hatching on the small slice, a small open circle hatching on the medium slice, and a large open circle hatching on the large slice. ax2 has the same large open circle with a dot hatch on every slice.
+
+ fig, (ax1, ax2) = plt.subplots(ncols=2)
+ x = [10, 30, 60]
+
+ ax1.pie(x, hatch=['.', 'o', 'O'])
+ ax2.pie(x, hatch='.O')
+
+ ax1.set_title("hatch=['.', 'o', 'O']")
+ ax2.set_title("hatch='.O'")
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
index e615305793b4..a6fecd374fba 100644
--- a/lib/matplotlib/axes/_axes.py
+++ b/lib/matplotlib/axes/_axes.py
@@ -3075,7 +3075,7 @@ def pie(self, x, explode=None, labels=None, colors=None,
autopct=None, pctdistance=0.6, shadow=False, labeldistance=1.1,
startangle=0, radius=1, counterclock=True,
wedgeprops=None, textprops=None, center=(0, 0),
- frame=False, rotatelabels=False, *, normalize=True):
+ frame=False, rotatelabels=False, *, normalize=True, hatch=None):
"""
Plot a pie chart.
@@ -3101,29 +3101,34 @@ def pie(self, x, explode=None, labels=None, colors=None,
A sequence of colors through which the pie chart will cycle. If
*None*, will use the colors in the currently active cycle.
+ hatch : str or list, default: None
+ Hatching pattern applied to all pie wedges or sequence of patterns
+ through which the chart will cycle. For a list of valid patterns,
+ see :doc:`/gallery/shapes_and_collections/hatch_style_reference`.
+
+ .. versionadded:: 3.7
+
autopct : None or str or callable, default: None
- If not *None*, is a string or function used to label the wedges
- with their numeric value. The label will be placed inside the
- wedge. If it is a format string, the label will be ``fmt % pct``.
- If it is a function, it will be called.
+ If not *None*, *autopct* is a string or function used to label the
+ wedges with their numeric value. The label will be placed inside
+ the wedge. If *autopct* is a format string, the label will be
+ ``fmt % pct``. If *autopct* is a function, then it will be called.
pctdistance : float, default: 0.6
- The ratio between the center of each pie slice and the start of
- the text generated by *autopct*. Ignored if *autopct* is *None*.
+ The relative distance along the radius at which the the text
+ generated by *autopct* is drawn. To draw the text outside the pie,
+ set *pctdistance* > 1. This parameter is ignored if *autopct* is
+ ``None``.
+
+ labeldistance : float or None, default: 1.1
+ The relative distance along the radius at which the labels are
+ drawn. To draw the labels inside the pie, set *labeldistance* < 1.
+ If set to ``None``, labels are not drawn but are still stored for
+ use in `.legend`.
shadow : bool, default: False
Draw a shadow beneath the pie.
- normalize : bool, default: True
- When *True*, always make a full pie by normalizing x so that
- ``sum(x) == 1``. *False* makes a partial pie if ``sum(x) <= 1``
- and raises a `ValueError` for ``sum(x) > 1``.
-
- labeldistance : float or None, default: 1.1
- The radial distance at which the pie labels are drawn.
- If set to ``None``, label are not drawn, but are stored for use in
- ``legend()``
-
startangle : float, default: 0 degrees
The angle by which the start of the pie is rotated,
counterclockwise from the x-axis.
@@ -3135,11 +3140,11 @@ def pie(self, x, explode=None, labels=None, colors=None,
Specify fractions direction, clockwise or counterclockwise.
wedgeprops : dict, default: None
- Dict of arguments passed to the wedge objects making the pie.
- For example, you can pass in ``wedgeprops = {'linewidth': 3}``
- to set the width of the wedge border lines equal to 3.
- For more details, look at the doc/arguments of the wedge object.
- By default, ``clip_on=False``.
+ Dict of arguments passed to each `.patches.Wedge` of the pie.
+ For example, ``wedgeprops = {'linewidth': 3}`` sets the width of
+ the wedge border lines equal to 3. By default, ``clip_on=False``.
+ When there is a conflict between these properties and other
+ keywords, properties passed to *wedgeprops* take precedence.
textprops : dict, default: None
Dict of arguments to pass to the text objects.
@@ -3153,6 +3158,11 @@ def pie(self, x, explode=None, labels=None, colors=None,
rotatelabels : bool, default: False
Rotate each label to the angle of the corresponding slice if true.
+ normalize : bool, default: True
+ When *True*, always make a full pie by normalizing x so that
+ ``sum(x) == 1``. *False* makes a partial pie if ``sum(x) <= 1``
+ and raises a `ValueError` for ``sum(x) > 1``.
+
data : indexable object, optional
DATA_PARAMETER_PLACEHOLDER
@@ -3207,6 +3217,8 @@ def pie(self, x, explode=None, labels=None, colors=None,
def get_next_color():
return next(color_cycle)
+ hatch_cycle = itertools.cycle(np.atleast_1d(hatch))
+
_api.check_isinstance(Number, radius=radius, startangle=startangle)
if radius <= 0:
raise ValueError(f'radius must be a positive number, not {radius}')
@@ -3233,6 +3245,7 @@ def get_next_color():
w = mpatches.Wedge((x, y), radius, 360. * min(theta1, theta2),
360. * max(theta1, theta2),
facecolor=get_next_color(),
+ hatch=next(hatch_cycle),
clip_on=False,
label=label)
w.set(**wedgeprops)
diff --git a/lib/matplotlib/pyplot.py b/lib/matplotlib/pyplot.py
index 36172522e0d0..acd187d5d1c9 100644
--- a/lib/matplotlib/pyplot.py
+++ b/lib/matplotlib/pyplot.py
@@ -2779,7 +2779,7 @@ def pie(
pctdistance=0.6, shadow=False, labeldistance=1.1,
startangle=0, radius=1, counterclock=True, wedgeprops=None,
textprops=None, center=(0, 0), frame=False,
- rotatelabels=False, *, normalize=True, data=None):
+ rotatelabels=False, *, normalize=True, hatch=None, data=None):
return gca().pie(
x, explode=explode, labels=labels, colors=colors,
autopct=autopct, pctdistance=pctdistance, shadow=shadow,
@@ -2787,7 +2787,7 @@ def pie(
radius=radius, counterclock=counterclock,
wedgeprops=wedgeprops, textprops=textprops, center=center,
frame=frame, rotatelabels=rotatelabels, normalize=normalize,
- **({"data": data} if data is not None else {}))
+ hatch=hatch, **({"data": data} if data is not None else {}))
# Autogenerated by boilerplate.py. Do not edit as changes will be lost.
|
diff --git a/lib/matplotlib/tests/test_axes.py b/lib/matplotlib/tests/test_axes.py
index f3f6b8938eb5..642316e4c000 100644
--- a/lib/matplotlib/tests/test_axes.py
+++ b/lib/matplotlib/tests/test_axes.py
@@ -5744,6 +5744,24 @@ def test_normalize_kwarg_pie():
assert abs(t2[0][-1].theta2 - 360.) > 1e-3
+@check_figures_equal()
+def test_pie_hatch_single(fig_test, fig_ref):
+ x = [0.3, 0.3, 0.1]
+ hatch = '+'
+ fig_test.subplots().pie(x, hatch=hatch)
+ wedges, _ = fig_ref.subplots().pie(x)
+ [w.set_hatch(hatch) for w in wedges]
+
+
+@check_figures_equal()
+def test_pie_hatch_multi(fig_test, fig_ref):
+ x = [0.3, 0.3, 0.1]
+ hatch = ['/', '+', '.']
+ fig_test.subplots().pie(x, hatch=hatch)
+ wedges, _ = fig_ref.subplots().pie(x)
+ [w.set_hatch(hp) for w, hp in zip(wedges, hatch)]
+
+
@image_comparison(['set_get_ticklabels.png'])
def test_set_get_ticklabels():
# test issue 2246
|
[
{
"path": "doc/users/next_whats_new/pie_hatch.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/pie_hatch.rst",
"metadata": "diff --git a/doc/users/next_whats_new/pie_hatch.rst b/doc/users/next_whats_new/pie_hatch.rst\nnew file mode 100644\nindex 000000000000..f54def10e954\n--- /dev/null\n+++ b/doc/users/next_whats_new/pie_hatch.rst\n@@ -0,0 +1,18 @@\n+``hatch`` parameter for pie\n+-------------------------------------------\n+\n+`~matplotlib.axes.Axes.pie` now accepts a *hatch* keyword that takes as input\n+a hatch or list of hatches:\n+\n+.. plot::\n+ :include-source: true\n+ :alt: Two pie charts, identified as ax1 and ax2, both have a small blue slice, a medium orange slice, and a large green slice. ax1 has a dot hatching on the small slice, a small open circle hatching on the medium slice, and a large open circle hatching on the large slice. ax2 has the same large open circle with a dot hatch on every slice.\n+\n+ fig, (ax1, ax2) = plt.subplots(ncols=2)\n+ x = [10, 30, 60]\n+\n+ ax1.pie(x, hatch=['.', 'o', 'O'])\n+ ax2.pie(x, hatch='.O')\n+\n+ ax1.set_title(\"hatch=['.', 'o', 'O']\")\n+ ax2.set_title(\"hatch='.O'\")\n"
}
] |
3.5
|
c19b6f5e9dc011c3b31d9996368c0fea4dcd3594
|
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"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs12]",
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"lib/matplotlib/tests/test_axes.py::test_autoscale_tiny_range[svg]",
"lib/matplotlib/tests/test_axes.py::test_mollweide_inverse_forward_closure",
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"lib/matplotlib/tests/test_axes.py::test_bar_label_fmt[{:.2f}]",
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"lib/matplotlib/tests/test_axes.py::test_lines_with_colors[png-data0]",
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"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_plot[pdf]",
"lib/matplotlib/tests/test_axes.py::test_parse_scatter_color_args[params3-expected_result3]",
"lib/matplotlib/tests/test_axes.py::test_tick_padding_tightbbox",
"lib/matplotlib/tests/test_axes.py::test_markevery_polar[svg]",
"lib/matplotlib/tests/test_axes.py::test_twinx_cla",
"lib/matplotlib/tests/test_axes.py::test_hist_offset[svg]",
"lib/matplotlib/tests/test_axes.py::test_autoscale_log_shared",
"lib/matplotlib/tests/test_axes.py::test_errorbar_linewidth_type[elinewidth1]",
"lib/matplotlib/tests/test_axes.py::test_fill_between_interpolate[pdf]",
"lib/matplotlib/tests/test_axes.py::test_contour_hatching[pdf]",
"lib/matplotlib/tests/test_axes.py::test_set_ticks_with_labels[png]",
"lib/matplotlib/tests/test_axes.py::test_minorticks_on[symlog-symlog]",
"lib/matplotlib/tests/test_axes.py::test_horiz_violinplot_showmeans[png]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case7-conversion]",
"lib/matplotlib/tests/test_axes.py::test_title_above_offset[center title kept]",
"lib/matplotlib/tests/test_axes.py::test_pie_get_negative_values",
"lib/matplotlib/tests/test_axes.py::test_aitoff_proj[png]",
"lib/matplotlib/tests/test_axes.py::test_polar_interpolation_steps_variable_r[png]",
"lib/matplotlib/tests/test_axes.py::test_barh_decimal_height[png]",
"lib/matplotlib/tests/test_axes.py::test_margins_errors[TypeError-args6-kwargs6-Must pass a single positional argument]",
"lib/matplotlib/tests/test_axes.py::test_inverted_limits",
"lib/matplotlib/tests/test_axes.py::test_boxplot_capwidths",
"lib/matplotlib/tests/test_axes.py::test_auto_numticks_log",
"lib/matplotlib/tests/test_axes.py::test_axes_tick_params_ylabelside",
"lib/matplotlib/tests/test_axes.py::test_hist_barstacked_bottom_unchanged",
"lib/matplotlib/tests/test_axes.py::test_eventplot_defaults[png]",
"lib/matplotlib/tests/test_axes.py::test_bxp_nocaps[png]",
"lib/matplotlib/tests/test_axes.py::test_set_aspect_negative",
"lib/matplotlib/tests/test_axes.py::test_vert_violinplot_showmeans[png]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[jaune-conversion]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_nonefmt",
"lib/matplotlib/tests/test_axes.py::test_horiz_violinplot_custompoints_10[png]",
"lib/matplotlib/tests/test_axes.py::test_boxplot_with_CIarray[png]",
"lib/matplotlib/tests/test_axes.py::test_boxplot_autorange_whiskers[png]",
"lib/matplotlib/tests/test_axes.py::test_boxplot_rc_parameters[svg]",
"lib/matplotlib/tests/test_axes.py::test_redraw_in_frame",
"lib/matplotlib/tests/test_axes.py::test_fill_between_interpolate_decreasing[pdf]",
"lib/matplotlib/tests/test_axes.py::test_shared_bool",
"lib/matplotlib/tests/test_axes.py::test_title_no_move_off_page",
"lib/matplotlib/tests/test_axes.py::test_titletwiny",
"lib/matplotlib/tests/test_axes.py::test_stairs_edge_handling[png]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs30]",
"lib/matplotlib/tests/test_axes.py::test_plot_format_errors[None-:o-r-':o-r' is not a valid format string \\\\(two linestyle symbols\\\\)]",
"lib/matplotlib/tests/test_axes.py::test_remove_shared_axes[gca-y]",
"lib/matplotlib/tests/test_axes.py::test_markevery_line[png]",
"lib/matplotlib/tests/test_axes.py::test_pcolormesh_small[eps]",
"lib/matplotlib/tests/test_axes.py::test_remove_shared_axes[add_axes-x]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case27-conversion]",
"lib/matplotlib/tests/test_axes.py::test_nonfinite_limits[png]",
"lib/matplotlib/tests/test_axes.py::test_fill_between_input[2d_y1_input]",
"lib/matplotlib/tests/test_axes.py::test_bxp_customwhisker[png]",
"lib/matplotlib/tests/test_axes.py::test_alpha[png]",
"lib/matplotlib/tests/test_axes.py::test_subclass_clear_cla",
"lib/matplotlib/tests/test_axes.py::test_normalize_kwarg_pie",
"lib/matplotlib/tests/test_axes.py::test_vlines_default",
"lib/matplotlib/tests/test_axes.py::test_stairs_baseline_0[png]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case29-conversion]",
"lib/matplotlib/tests/test_axes.py::test_ylabel_ha_with_position[right]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case1-conversion]"
] |
[
"lib/matplotlib/tests/test_axes.py::test_pie_hatch_multi[pdf]",
"lib/matplotlib/tests/test_axes.py::test_pie_hatch_single[pdf]",
"lib/matplotlib/tests/test_axes.py::test_pie_hatch_multi[svg]",
"lib/matplotlib/tests/test_axes.py::test_pie_hatch_multi[png]",
"lib/matplotlib/tests/test_axes.py::test_pie_hatch_single[svg]",
"lib/matplotlib/tests/test_axes.py::test_pie_hatch_single[png]"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/users/next_whats_new/pie_hatch.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/pie_hatch.rst",
"metadata": "diff --git a/doc/users/next_whats_new/pie_hatch.rst b/doc/users/next_whats_new/pie_hatch.rst\nnew file mode 100644\nindex 000000000000..f54def10e954\n--- /dev/null\n+++ b/doc/users/next_whats_new/pie_hatch.rst\n@@ -0,0 +1,18 @@\n+``hatch`` parameter for pie\n+-------------------------------------------\n+\n+`~matplotlib.axes.Axes.pie` now accepts a *hatch* keyword that takes as input\n+a hatch or list of hatches:\n+\n+.. plot::\n+ :include-source: true\n+ :alt: Two pie charts, identified as ax1 and ax2, both have a small blue slice, a medium orange slice, and a large green slice. ax1 has a dot hatching on the small slice, a small open circle hatching on the medium slice, and a large open circle hatching on the large slice. ax2 has the same large open circle with a dot hatch on every slice.\n+\n+ fig, (ax1, ax2) = plt.subplots(ncols=2)\n+ x = [10, 30, 60]\n+\n+ ax1.pie(x, hatch=['.', 'o', 'O'])\n+ ax2.pie(x, hatch='.O')\n+\n+ ax1.set_title(\"hatch=['.', 'o', 'O']\")\n+ ax2.set_title(\"hatch='.O'\")\n"
}
] |
diff --git a/doc/users/next_whats_new/pie_hatch.rst b/doc/users/next_whats_new/pie_hatch.rst
new file mode 100644
index 000000000000..f54def10e954
--- /dev/null
+++ b/doc/users/next_whats_new/pie_hatch.rst
@@ -0,0 +1,18 @@
+``hatch`` parameter for pie
+-------------------------------------------
+
+`~matplotlib.axes.Axes.pie` now accepts a *hatch* keyword that takes as input
+a hatch or list of hatches:
+
+.. plot::
+ :include-source: true
+ :alt: Two pie charts, identified as ax1 and ax2, both have a small blue slice, a medium orange slice, and a large green slice. ax1 has a dot hatching on the small slice, a small open circle hatching on the medium slice, and a large open circle hatching on the large slice. ax2 has the same large open circle with a dot hatch on every slice.
+
+ fig, (ax1, ax2) = plt.subplots(ncols=2)
+ x = [10, 30, 60]
+
+ ax1.pie(x, hatch=['.', 'o', 'O'])
+ ax2.pie(x, hatch='.O')
+
+ ax1.set_title("hatch=['.', 'o', 'O']")
+ ax2.set_title("hatch='.O'")
|
matplotlib/matplotlib
|
matplotlib__matplotlib-24470
|
https://github.com/matplotlib/matplotlib/pull/24470
|
diff --git a/doc/users/next_whats_new/pie_hatch.rst b/doc/users/next_whats_new/pie_hatch.rst
new file mode 100644
index 000000000000..f54def10e954
--- /dev/null
+++ b/doc/users/next_whats_new/pie_hatch.rst
@@ -0,0 +1,18 @@
+``hatch`` parameter for pie
+-------------------------------------------
+
+`~matplotlib.axes.Axes.pie` now accepts a *hatch* keyword that takes as input
+a hatch or list of hatches:
+
+.. plot::
+ :include-source: true
+ :alt: Two pie charts, identified as ax1 and ax2, both have a small blue slice, a medium orange slice, and a large green slice. ax1 has a dot hatching on the small slice, a small open circle hatching on the medium slice, and a large open circle hatching on the large slice. ax2 has the same large open circle with a dot hatch on every slice.
+
+ fig, (ax1, ax2) = plt.subplots(ncols=2)
+ x = [10, 30, 60]
+
+ ax1.pie(x, hatch=['.', 'o', 'O'])
+ ax2.pie(x, hatch='.O')
+
+ ax1.set_title("hatch=['.', 'o', 'O']")
+ ax2.set_title("hatch='.O'")
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
index 58d95912665b..c46c1b467fc1 100644
--- a/lib/matplotlib/axes/_axes.py
+++ b/lib/matplotlib/axes/_axes.py
@@ -3083,7 +3083,7 @@ def pie(self, x, explode=None, labels=None, colors=None,
autopct=None, pctdistance=0.6, shadow=False, labeldistance=1.1,
startangle=0, radius=1, counterclock=True,
wedgeprops=None, textprops=None, center=(0, 0),
- frame=False, rotatelabels=False, *, normalize=True):
+ frame=False, rotatelabels=False, *, normalize=True, hatch=None):
"""
Plot a pie chart.
@@ -3109,29 +3109,34 @@ def pie(self, x, explode=None, labels=None, colors=None,
A sequence of colors through which the pie chart will cycle. If
*None*, will use the colors in the currently active cycle.
+ hatch : str or list, default: None
+ Hatching pattern applied to all pie wedges or sequence of patterns
+ through which the chart will cycle. For a list of valid patterns,
+ see :doc:`/gallery/shapes_and_collections/hatch_style_reference`.
+
+ .. versionadded:: 3.7
+
autopct : None or str or callable, default: None
- If not *None*, is a string or function used to label the wedges
- with their numeric value. The label will be placed inside the
- wedge. If it is a format string, the label will be ``fmt % pct``.
- If it is a function, it will be called.
+ If not *None*, *autopct* is a string or function used to label the
+ wedges with their numeric value. The label will be placed inside
+ the wedge. If *autopct* is a format string, the label will be
+ ``fmt % pct``. If *autopct* is a function, then it will be called.
pctdistance : float, default: 0.6
- The ratio between the center of each pie slice and the start of
- the text generated by *autopct*. Ignored if *autopct* is *None*.
+ The relative distance along the radius at which the the text
+ generated by *autopct* is drawn. To draw the text outside the pie,
+ set *pctdistance* > 1. This parameter is ignored if *autopct* is
+ ``None``.
+
+ labeldistance : float or None, default: 1.1
+ The relative distance along the radius at which the labels are
+ drawn. To draw the labels inside the pie, set *labeldistance* < 1.
+ If set to ``None``, labels are not drawn but are still stored for
+ use in `.legend`.
shadow : bool, default: False
Draw a shadow beneath the pie.
- normalize : bool, default: True
- When *True*, always make a full pie by normalizing x so that
- ``sum(x) == 1``. *False* makes a partial pie if ``sum(x) <= 1``
- and raises a `ValueError` for ``sum(x) > 1``.
-
- labeldistance : float or None, default: 1.1
- The radial distance at which the pie labels are drawn.
- If set to ``None``, label are not drawn, but are stored for use in
- ``legend()``
-
startangle : float, default: 0 degrees
The angle by which the start of the pie is rotated,
counterclockwise from the x-axis.
@@ -3143,11 +3148,11 @@ def pie(self, x, explode=None, labels=None, colors=None,
Specify fractions direction, clockwise or counterclockwise.
wedgeprops : dict, default: None
- Dict of arguments passed to the wedge objects making the pie.
- For example, you can pass in ``wedgeprops = {'linewidth': 3}``
- to set the width of the wedge border lines equal to 3.
- For more details, look at the doc/arguments of the wedge object.
- By default, ``clip_on=False``.
+ Dict of arguments passed to each `.patches.Wedge` of the pie.
+ For example, ``wedgeprops = {'linewidth': 3}`` sets the width of
+ the wedge border lines equal to 3. By default, ``clip_on=False``.
+ When there is a conflict between these properties and other
+ keywords, properties passed to *wedgeprops* take precedence.
textprops : dict, default: None
Dict of arguments to pass to the text objects.
@@ -3161,6 +3166,11 @@ def pie(self, x, explode=None, labels=None, colors=None,
rotatelabels : bool, default: False
Rotate each label to the angle of the corresponding slice if true.
+ normalize : bool, default: True
+ When *True*, always make a full pie by normalizing x so that
+ ``sum(x) == 1``. *False* makes a partial pie if ``sum(x) <= 1``
+ and raises a `ValueError` for ``sum(x) > 1``.
+
data : indexable object, optional
DATA_PARAMETER_PLACEHOLDER
@@ -3215,6 +3225,8 @@ def pie(self, x, explode=None, labels=None, colors=None,
def get_next_color():
return next(color_cycle)
+ hatch_cycle = itertools.cycle(np.atleast_1d(hatch))
+
_api.check_isinstance(Number, radius=radius, startangle=startangle)
if radius <= 0:
raise ValueError(f'radius must be a positive number, not {radius}')
@@ -3241,6 +3253,7 @@ def get_next_color():
w = mpatches.Wedge((x, y), radius, 360. * min(theta1, theta2),
360. * max(theta1, theta2),
facecolor=get_next_color(),
+ hatch=next(hatch_cycle),
clip_on=False,
label=label)
w.set(**wedgeprops)
diff --git a/lib/matplotlib/pyplot.py b/lib/matplotlib/pyplot.py
index 4e9734e184dc..e62d4f0b7481 100644
--- a/lib/matplotlib/pyplot.py
+++ b/lib/matplotlib/pyplot.py
@@ -2784,7 +2784,7 @@ def pie(
pctdistance=0.6, shadow=False, labeldistance=1.1,
startangle=0, radius=1, counterclock=True, wedgeprops=None,
textprops=None, center=(0, 0), frame=False,
- rotatelabels=False, *, normalize=True, data=None):
+ rotatelabels=False, *, normalize=True, hatch=None, data=None):
return gca().pie(
x, explode=explode, labels=labels, colors=colors,
autopct=autopct, pctdistance=pctdistance, shadow=shadow,
@@ -2792,7 +2792,7 @@ def pie(
radius=radius, counterclock=counterclock,
wedgeprops=wedgeprops, textprops=textprops, center=center,
frame=frame, rotatelabels=rotatelabels, normalize=normalize,
- **({"data": data} if data is not None else {}))
+ hatch=hatch, **({"data": data} if data is not None else {}))
# Autogenerated by boilerplate.py. Do not edit as changes will be lost.
|
diff --git a/lib/matplotlib/tests/test_axes.py b/lib/matplotlib/tests/test_axes.py
index 3b471d4e0d92..7acd1040c5d6 100644
--- a/lib/matplotlib/tests/test_axes.py
+++ b/lib/matplotlib/tests/test_axes.py
@@ -5744,6 +5744,24 @@ def test_normalize_kwarg_pie():
assert abs(t2[0][-1].theta2 - 360.) > 1e-3
+@check_figures_equal()
+def test_pie_hatch_single(fig_test, fig_ref):
+ x = [0.3, 0.3, 0.1]
+ hatch = '+'
+ fig_test.subplots().pie(x, hatch=hatch)
+ wedges, _ = fig_ref.subplots().pie(x)
+ [w.set_hatch(hatch) for w in wedges]
+
+
+@check_figures_equal()
+def test_pie_hatch_multi(fig_test, fig_ref):
+ x = [0.3, 0.3, 0.1]
+ hatch = ['/', '+', '.']
+ fig_test.subplots().pie(x, hatch=hatch)
+ wedges, _ = fig_ref.subplots().pie(x)
+ [w.set_hatch(hp) for w, hp in zip(wedges, hatch)]
+
+
@image_comparison(['set_get_ticklabels.png'])
def test_set_get_ticklabels():
# test issue 2246
|
[
{
"path": "doc/users/next_whats_new/pie_hatch.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/pie_hatch.rst",
"metadata": "diff --git a/doc/users/next_whats_new/pie_hatch.rst b/doc/users/next_whats_new/pie_hatch.rst\nnew file mode 100644\nindex 000000000000..f54def10e954\n--- /dev/null\n+++ b/doc/users/next_whats_new/pie_hatch.rst\n@@ -0,0 +1,18 @@\n+``hatch`` parameter for pie\n+-------------------------------------------\n+\n+`~matplotlib.axes.Axes.pie` now accepts a *hatch* keyword that takes as input\n+a hatch or list of hatches:\n+\n+.. plot::\n+ :include-source: true\n+ :alt: Two pie charts, identified as ax1 and ax2, both have a small blue slice, a medium orange slice, and a large green slice. ax1 has a dot hatching on the small slice, a small open circle hatching on the medium slice, and a large open circle hatching on the large slice. ax2 has the same large open circle with a dot hatch on every slice.\n+\n+ fig, (ax1, ax2) = plt.subplots(ncols=2)\n+ x = [10, 30, 60]\n+\n+ ax1.pie(x, hatch=['.', 'o', 'O'])\n+ ax2.pie(x, hatch='.O')\n+\n+ ax1.set_title(\"hatch=['.', 'o', 'O']\")\n+ ax2.set_title(\"hatch='.O'\")\n"
}
] |
3.5
|
e0dc18d51ef29118cc13e394f76641dcb5198846
|
[
"lib/matplotlib/tests/test_axes.py::test_stem_dates",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs12]",
"lib/matplotlib/tests/test_axes.py::test_hist_zorder[stepfilled-1]",
"lib/matplotlib/tests/test_axes.py::test_axline_transaxes_panzoom[png]",
"lib/matplotlib/tests/test_axes.py::test_annotate_signature",
"lib/matplotlib/tests/test_axes.py::test_boxplot[png]",
"lib/matplotlib/tests/test_axes.py::test_bxp_custommedian[png]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_invalid_color[png]",
"lib/matplotlib/tests/test_axes.py::test_empty_eventplot",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case11-shape]",
"lib/matplotlib/tests/test_axes.py::test_twin_logscale[png-y]",
"lib/matplotlib/tests/test_axes.py::test_autoscale_tiny_range[svg]",
"lib/matplotlib/tests/test_axes.py::test_mollweide_inverse_forward_closure",
"lib/matplotlib/tests/test_axes.py::test_errorbar_cycle_ecolor[svg]",
"lib/matplotlib/tests/test_axes.py::test_bar_label_fmt[{:.2f}]",
"lib/matplotlib/tests/test_axes.py::test_contour_colorbar[png]",
"lib/matplotlib/tests/test_axes.py::test_color_alias",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_single_point[png]",
"lib/matplotlib/tests/test_axes.py::test_bar_edgecolor_none_alpha",
"lib/matplotlib/tests/test_axes.py::test_lines_with_colors[png-data1]",
"lib/matplotlib/tests/test_axes.py::test_shared_axes_retick",
"lib/matplotlib/tests/test_axes.py::test_violinplot_bad_quantiles",
"lib/matplotlib/tests/test_axes.py::test_pandas_indexing_hist",
"lib/matplotlib/tests/test_axes.py::test_lines_with_colors[png-data0]",
"lib/matplotlib/tests/test_axes.py::test_bar_color_none_alpha",
"lib/matplotlib/tests/test_axes.py::test_bar_errbar_zorder",
"lib/matplotlib/tests/test_axes.py::test_step_linestyle[pdf]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_cycle_ecolor[png]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs5]",
"lib/matplotlib/tests/test_axes.py::test_bxp_baseline[png]",
"lib/matplotlib/tests/test_axes.py::test_bxp_horizontal[png]",
"lib/matplotlib/tests/test_axes.py::test_arrow_empty",
"lib/matplotlib/tests/test_axes.py::test_hist2d[svg]",
"lib/matplotlib/tests/test_axes.py::test_remove_shared_axes[gca-x]",
"lib/matplotlib/tests/test_axes.py::test_hist_log[png]",
"lib/matplotlib/tests/test_axes.py::test_pcolorfast[data1-xy0-AxesImage]",
"lib/matplotlib/tests/test_axes.py::test_mixed_collection[svg]",
"lib/matplotlib/tests/test_axes.py::test_hlines[png]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_no_invalid_color[png]",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_weighted[png]",
"lib/matplotlib/tests/test_axes.py::test_ytickcolor_is_not_markercolor",
"lib/matplotlib/tests/test_axes.py::test_relative_ticklabel_sizes[small]",
"lib/matplotlib/tests/test_axes.py::test_set_ticks_kwargs_raise_error_without_labels",
"lib/matplotlib/tests/test_axes.py::test_color_None",
"lib/matplotlib/tests/test_axes.py::test_basic_annotate[pdf]",
"lib/matplotlib/tests/test_axes.py::test_stairs_datetime[png]",
"lib/matplotlib/tests/test_axes.py::test_margins",
"lib/matplotlib/tests/test_axes.py::test_axvspan_epoch[pdf]",
"lib/matplotlib/tests/test_axes.py::test_parse_scatter_color_args_edgecolors[kwargs3-expected_edgecolors3]",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_step[svg]",
"lib/matplotlib/tests/test_axes.py::test_mollweide_grid[svg]",
"lib/matplotlib/tests/test_axes.py::test_bxp_customoutlier[png]",
"lib/matplotlib/tests/test_axes.py::test_eventplot_units_list[png]",
"lib/matplotlib/tests/test_axes.py::test_hist_step_bottom[png]",
"lib/matplotlib/tests/test_axes.py::test_imshow[svg]",
"lib/matplotlib/tests/test_axes.py::test_stairs_invalid_update",
"lib/matplotlib/tests/test_axes.py::test_remove_shared_axes[subplots_shared-x]",
"lib/matplotlib/tests/test_axes.py::test_remove_shared_axes_relim",
"lib/matplotlib/tests/test_axes.py::test_symlog[pdf]",
"lib/matplotlib/tests/test_axes.py::test_strmethodformatter_auto_formatter",
"lib/matplotlib/tests/test_axes.py::test_hist_density[png]",
"lib/matplotlib/tests/test_axes.py::test_stem_markerfmt",
"lib/matplotlib/tests/test_axes.py::test_eventplot_colors[colors2]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs22]",
"lib/matplotlib/tests/test_axes.py::test_multiplot_autoscale",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[none-None]",
"lib/matplotlib/tests/test_axes.py::test_parse_scatter_color_args_edgecolors[kwargs2-r]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_colorcycle",
"lib/matplotlib/tests/test_axes.py::test_secondary_xy[png]",
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] |
[
"lib/matplotlib/tests/test_axes.py::test_pie_hatch_multi[pdf]",
"lib/matplotlib/tests/test_axes.py::test_pie_hatch_single[pdf]",
"lib/matplotlib/tests/test_axes.py::test_pie_hatch_multi[svg]",
"lib/matplotlib/tests/test_axes.py::test_pie_hatch_multi[png]",
"lib/matplotlib/tests/test_axes.py::test_pie_hatch_single[svg]",
"lib/matplotlib/tests/test_axes.py::test_pie_hatch_single[png]"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/users/next_whats_new/pie_hatch.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/pie_hatch.rst",
"metadata": "diff --git a/doc/users/next_whats_new/pie_hatch.rst b/doc/users/next_whats_new/pie_hatch.rst\nnew file mode 100644\nindex 000000000000..f54def10e954\n--- /dev/null\n+++ b/doc/users/next_whats_new/pie_hatch.rst\n@@ -0,0 +1,18 @@\n+``hatch`` parameter for pie\n+-------------------------------------------\n+\n+`~matplotlib.axes.Axes.pie` now accepts a *hatch* keyword that takes as input\n+a hatch or list of hatches:\n+\n+.. plot::\n+ :include-source: true\n+ :alt: Two pie charts, identified as ax1 and ax2, both have a small blue slice, a medium orange slice, and a large green slice. ax1 has a dot hatching on the small slice, a small open circle hatching on the medium slice, and a large open circle hatching on the large slice. ax2 has the same large open circle with a dot hatch on every slice.\n+\n+ fig, (ax1, ax2) = plt.subplots(ncols=2)\n+ x = [10, 30, 60]\n+\n+ ax1.pie(x, hatch=['.', 'o', 'O'])\n+ ax2.pie(x, hatch='.O')\n+\n+ ax1.set_title(\"hatch=['.', 'o', 'O']\")\n+ ax2.set_title(\"hatch='.O'\")\n"
}
] |
diff --git a/doc/users/next_whats_new/pie_hatch.rst b/doc/users/next_whats_new/pie_hatch.rst
new file mode 100644
index 000000000000..f54def10e954
--- /dev/null
+++ b/doc/users/next_whats_new/pie_hatch.rst
@@ -0,0 +1,18 @@
+``hatch`` parameter for pie
+-------------------------------------------
+
+`~matplotlib.axes.Axes.pie` now accepts a *hatch* keyword that takes as input
+a hatch or list of hatches:
+
+.. plot::
+ :include-source: true
+ :alt: Two pie charts, identified as ax1 and ax2, both have a small blue slice, a medium orange slice, and a large green slice. ax1 has a dot hatching on the small slice, a small open circle hatching on the medium slice, and a large open circle hatching on the large slice. ax2 has the same large open circle with a dot hatch on every slice.
+
+ fig, (ax1, ax2) = plt.subplots(ncols=2)
+ x = [10, 30, 60]
+
+ ax1.pie(x, hatch=['.', 'o', 'O'])
+ ax2.pie(x, hatch='.O')
+
+ ax1.set_title("hatch=['.', 'o', 'O']")
+ ax2.set_title("hatch='.O'")
|
matplotlib/matplotlib
|
matplotlib__matplotlib-23525
|
https://github.com/matplotlib/matplotlib/pull/23525
|
diff --git a/doc/users/next_whats_new/bar_plot_labels.rst b/doc/users/next_whats_new/bar_plot_labels.rst
new file mode 100644
index 000000000000..6da57a317f59
--- /dev/null
+++ b/doc/users/next_whats_new/bar_plot_labels.rst
@@ -0,0 +1,16 @@
+Easier labelling of bars in bar plot
+------------------------------------
+
+The ``label`` argument of `~matplotlib.axes.Axes.bar` can now
+be passed a list of labels for the bars.
+
+.. code-block:: python
+
+ import matplotlib.pyplot as plt
+
+ x = ["a", "b", "c"]
+ y = [10, 20, 15]
+
+ fig, ax = plt.subplots()
+ bar_container = ax.barh(x, y, label=x)
+ [bar.get_label() for bar in bar_container]
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
index 25b3cf36651f..3159a55b7e83 100644
--- a/lib/matplotlib/axes/_axes.py
+++ b/lib/matplotlib/axes/_axes.py
@@ -2256,6 +2256,14 @@ def bar(self, x, height, width=0.8, bottom=None, *, align="center",
The tick labels of the bars.
Default: None (Use default numeric labels.)
+ label : str or list of str, optional
+ A single label is attached to the resulting `.BarContainer` as a
+ label for the whole dataset.
+ If a list is provided, it must be the same length as *x* and
+ labels the individual bars. Repeated labels are not de-duplicated
+ and will cause repeated label entries, so this is best used when
+ bars also differ in style (e.g., by passing a list to *color*.)
+
xerr, yerr : float or array-like of shape(N,) or shape(2, N), optional
If not *None*, add horizontal / vertical errorbars to the bar tips.
The values are +/- sizes relative to the data:
@@ -2381,6 +2389,16 @@ def bar(self, x, height, width=0.8, bottom=None, *, align="center",
tick_label_axis = self.yaxis
tick_label_position = y
+ if not isinstance(label, str) and np.iterable(label):
+ bar_container_label = '_nolegend_'
+ patch_labels = label
+ else:
+ bar_container_label = label
+ patch_labels = ['_nolegend_'] * len(x)
+ if len(patch_labels) != len(x):
+ raise ValueError(f'number of labels ({len(patch_labels)}) '
+ f'does not match number of bars ({len(x)}).')
+
linewidth = itertools.cycle(np.atleast_1d(linewidth))
hatch = itertools.cycle(np.atleast_1d(hatch))
color = itertools.chain(itertools.cycle(mcolors.to_rgba_array(color)),
@@ -2420,14 +2438,14 @@ def bar(self, x, height, width=0.8, bottom=None, *, align="center",
patches = []
args = zip(left, bottom, width, height, color, edgecolor, linewidth,
- hatch)
- for l, b, w, h, c, e, lw, htch in args:
+ hatch, patch_labels)
+ for l, b, w, h, c, e, lw, htch, lbl in args:
r = mpatches.Rectangle(
xy=(l, b), width=w, height=h,
facecolor=c,
edgecolor=e,
linewidth=lw,
- label='_nolegend_',
+ label=lbl,
hatch=htch,
)
r._internal_update(kwargs)
@@ -2466,7 +2484,8 @@ def bar(self, x, height, width=0.8, bottom=None, *, align="center",
datavalues = width
bar_container = BarContainer(patches, errorbar, datavalues=datavalues,
- orientation=orientation, label=label)
+ orientation=orientation,
+ label=bar_container_label)
self.add_container(bar_container)
if tick_labels is not None:
|
diff --git a/lib/matplotlib/tests/test_axes.py b/lib/matplotlib/tests/test_axes.py
index 51fbea3cfaaa..3a1ba341b2e0 100644
--- a/lib/matplotlib/tests/test_axes.py
+++ b/lib/matplotlib/tests/test_axes.py
@@ -1886,6 +1886,35 @@ def test_bar_hatches(fig_test, fig_ref):
ax_test.bar(x, y, hatch=hatches)
+@pytest.mark.parametrize(
+ ("x", "width", "label", "expected_labels", "container_label"),
+ [
+ ("x", 1, "x", ["_nolegend_"], "x"),
+ (["a", "b", "c"], [10, 20, 15], ["A", "B", "C"],
+ ["A", "B", "C"], "_nolegend_"),
+ (["a", "b", "c"], [10, 20, 15], ["R", "Y", "_nolegend_"],
+ ["R", "Y", "_nolegend_"], "_nolegend_"),
+ (["a", "b", "c"], [10, 20, 15], "bars",
+ ["_nolegend_", "_nolegend_", "_nolegend_"], "bars"),
+ ]
+)
+def test_bar_labels(x, width, label, expected_labels, container_label):
+ _, ax = plt.subplots()
+ bar_container = ax.bar(x, width, label=label)
+ bar_labels = [bar.get_label() for bar in bar_container]
+ assert expected_labels == bar_labels
+ assert bar_container.get_label() == container_label
+
+
+def test_bar_labels_length():
+ _, ax = plt.subplots()
+ with pytest.raises(ValueError):
+ ax.bar(["x", "y"], [1, 2], label=["X", "Y", "Z"])
+ _, ax = plt.subplots()
+ with pytest.raises(ValueError):
+ ax.bar(["x", "y"], [1, 2], label=["X"])
+
+
def test_pandas_minimal_plot(pd):
# smoke test that series and index objects do not warn
for x in [pd.Series([1, 2], dtype="float64"),
|
[
{
"path": "doc/users/next_whats_new/bar_plot_labels.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/bar_plot_labels.rst",
"metadata": "diff --git a/doc/users/next_whats_new/bar_plot_labels.rst b/doc/users/next_whats_new/bar_plot_labels.rst\nnew file mode 100644\nindex 000000000000..6da57a317f59\n--- /dev/null\n+++ b/doc/users/next_whats_new/bar_plot_labels.rst\n@@ -0,0 +1,16 @@\n+Easier labelling of bars in bar plot\n+------------------------------------\n+\n+The ``label`` argument of `~matplotlib.axes.Axes.bar` can now\n+be passed a list of labels for the bars.\n+\n+.. code-block:: python\n+\n+ import matplotlib.pyplot as plt\n+\n+ x = [\"a\", \"b\", \"c\"]\n+ y = [10, 20, 15]\n+\n+ fig, ax = plt.subplots()\n+ bar_container = ax.barh(x, y, label=x)\n+ [bar.get_label() for bar in bar_container]\n"
}
] |
3.5
|
23100c42b274898f983011c12d5399a96982fe71
|
[
"lib/matplotlib/tests/test_axes.py::test_stem_dates",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs12]",
"lib/matplotlib/tests/test_axes.py::test_hist_zorder[stepfilled-1]",
"lib/matplotlib/tests/test_axes.py::test_axline_transaxes_panzoom[png]",
"lib/matplotlib/tests/test_axes.py::test_annotate_signature",
"lib/matplotlib/tests/test_axes.py::test_boxplot[png]",
"lib/matplotlib/tests/test_axes.py::test_bxp_custommedian[png]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_invalid_color[png]",
"lib/matplotlib/tests/test_axes.py::test_empty_eventplot",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case11-shape]",
"lib/matplotlib/tests/test_axes.py::test_twin_logscale[png-y]",
"lib/matplotlib/tests/test_axes.py::test_autoscale_tiny_range[svg]",
"lib/matplotlib/tests/test_axes.py::test_mollweide_inverse_forward_closure",
"lib/matplotlib/tests/test_axes.py::test_errorbar_cycle_ecolor[svg]",
"lib/matplotlib/tests/test_axes.py::test_contour_colorbar[png]",
"lib/matplotlib/tests/test_axes.py::test_color_alias",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_single_point[png]",
"lib/matplotlib/tests/test_axes.py::test_bar_edgecolor_none_alpha",
"lib/matplotlib/tests/test_axes.py::test_lines_with_colors[png-data1]",
"lib/matplotlib/tests/test_axes.py::test_shared_axes_retick",
"lib/matplotlib/tests/test_axes.py::test_violinplot_bad_quantiles",
"lib/matplotlib/tests/test_axes.py::test_pandas_indexing_hist",
"lib/matplotlib/tests/test_axes.py::test_lines_with_colors[png-data0]",
"lib/matplotlib/tests/test_axes.py::test_bar_color_none_alpha",
"lib/matplotlib/tests/test_axes.py::test_bar_errbar_zorder",
"lib/matplotlib/tests/test_axes.py::test_step_linestyle[pdf]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_cycle_ecolor[png]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs5]",
"lib/matplotlib/tests/test_axes.py::test_bxp_baseline[png]",
"lib/matplotlib/tests/test_axes.py::test_bxp_horizontal[png]",
"lib/matplotlib/tests/test_axes.py::test_arrow_empty",
"lib/matplotlib/tests/test_axes.py::test_hist2d[svg]",
"lib/matplotlib/tests/test_axes.py::test_remove_shared_axes[gca-x]",
"lib/matplotlib/tests/test_axes.py::test_hist_log[png]",
"lib/matplotlib/tests/test_axes.py::test_pcolorfast[data1-xy0-AxesImage]",
"lib/matplotlib/tests/test_axes.py::test_mixed_collection[svg]",
"lib/matplotlib/tests/test_axes.py::test_hlines[png]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_no_invalid_color[png]",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_weighted[png]",
"lib/matplotlib/tests/test_axes.py::test_ytickcolor_is_not_markercolor",
"lib/matplotlib/tests/test_axes.py::test_relative_ticklabel_sizes[small]",
"lib/matplotlib/tests/test_axes.py::test_color_None",
"lib/matplotlib/tests/test_axes.py::test_basic_annotate[pdf]",
"lib/matplotlib/tests/test_axes.py::test_stairs_datetime[png]",
"lib/matplotlib/tests/test_axes.py::test_margins",
"lib/matplotlib/tests/test_axes.py::test_axvspan_epoch[pdf]",
"lib/matplotlib/tests/test_axes.py::test_parse_scatter_color_args_edgecolors[kwargs3-expected_edgecolors3]",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_step[svg]",
"lib/matplotlib/tests/test_axes.py::test_mollweide_grid[svg]",
"lib/matplotlib/tests/test_axes.py::test_bxp_customoutlier[png]",
"lib/matplotlib/tests/test_axes.py::test_eventplot_units_list[png]",
"lib/matplotlib/tests/test_axes.py::test_hist_step_bottom[png]",
"lib/matplotlib/tests/test_axes.py::test_imshow[svg]",
"lib/matplotlib/tests/test_axes.py::test_stairs_invalid_update",
"lib/matplotlib/tests/test_axes.py::test_remove_shared_axes[subplots_shared-x]",
"lib/matplotlib/tests/test_axes.py::test_remove_shared_axes_relim",
"lib/matplotlib/tests/test_axes.py::test_symlog[pdf]",
"lib/matplotlib/tests/test_axes.py::test_strmethodformatter_auto_formatter",
"lib/matplotlib/tests/test_axes.py::test_hist_density[png]",
"lib/matplotlib/tests/test_axes.py::test_stem_markerfmt",
"lib/matplotlib/tests/test_axes.py::test_eventplot_colors[colors2]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs22]",
"lib/matplotlib/tests/test_axes.py::test_multiplot_autoscale",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[none-None]",
"lib/matplotlib/tests/test_axes.py::test_parse_scatter_color_args_edgecolors[kwargs2-r]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_colorcycle",
"lib/matplotlib/tests/test_axes.py::test_secondary_xy[png]",
"lib/matplotlib/tests/test_axes.py::test_auto_numticks",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs36]",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_density[svg]",
"lib/matplotlib/tests/test_axes.py::test_title_location_shared[True]",
"lib/matplotlib/tests/test_axes.py::test_hist_step_bottom_geometry",
"lib/matplotlib/tests/test_axes.py::test_artist_sublists",
"lib/matplotlib/tests/test_axes.py::test_fill_between_interpolate[png]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs38]",
"lib/matplotlib/tests/test_axes.py::test_eventplot[svg]",
"lib/matplotlib/tests/test_axes.py::test_single_date[png]",
"lib/matplotlib/tests/test_axes.py::test_bxp_with_ylabels[png]",
"lib/matplotlib/tests/test_axes.py::test_eventplot_colors[colors1]",
"lib/matplotlib/tests/test_axes.py::test_axis_errors[ValueError-args1-kwargs1-Unrecognized string 'foo' to axis; try 'on' or 'off']",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs10]",
"lib/matplotlib/tests/test_axes.py::test_date_timezone_x_and_y[png]",
"lib/matplotlib/tests/test_axes.py::test_axline[svg]",
"lib/matplotlib/tests/test_axes.py::test_set_get_ticklabels[png]",
"lib/matplotlib/tests/test_axes.py::test_box_aspect_custom_position",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case5-None]",
"lib/matplotlib/tests/test_axes.py::test_markers_fillstyle_rcparams[png]",
"lib/matplotlib/tests/test_axes.py::test_rc_grid[png]",
"lib/matplotlib/tests/test_axes.py::test_inset_subclass",
"lib/matplotlib/tests/test_axes.py::test_mixed_collection[pdf]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs6]",
"lib/matplotlib/tests/test_axes.py::test_spectrum[png]",
"lib/matplotlib/tests/test_axes.py::test_markevery[pdf]",
"lib/matplotlib/tests/test_axes.py::test_dash_offset[pdf]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[red-None]",
"lib/matplotlib/tests/test_axes.py::test_eventplot[pdf]",
"lib/matplotlib/tests/test_axes.py::test_bar_tick_label_multiple_old_alignment[png]",
"lib/matplotlib/tests/test_axes.py::test_relative_ticklabel_sizes[x-large]",
"lib/matplotlib/tests/test_axes.py::test_eventplot[png]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs29]",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_step_geometry",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs43]",
"lib/matplotlib/tests/test_axes.py::test_pcolorfast[data0-xy4-QuadMesh]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case25-None]",
"lib/matplotlib/tests/test_axes.py::test_eventplot_legend",
"lib/matplotlib/tests/test_axes.py::test_invisible_axes_events",
"lib/matplotlib/tests/test_axes.py::test_bxp_custombox[png]",
"lib/matplotlib/tests/test_axes.py::test_bxp_rangewhis[png]",
"lib/matplotlib/tests/test_axes.py::test_remove_shared_axes[subplots-x]",
"lib/matplotlib/tests/test_axes.py::test_hist_datetime_datasets_bins[datetime.datetime]",
"lib/matplotlib/tests/test_axes.py::test_hist_labels",
"lib/matplotlib/tests/test_axes.py::test_vert_violinplot_baseline[png]",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_stepfilled[pdf]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs40]",
"lib/matplotlib/tests/test_axes.py::test_violinplot_bad_widths",
"lib/matplotlib/tests/test_axes.py::test_stairs_invalid_update2",
"lib/matplotlib/tests/test_axes.py::test_tick_space_size_0",
"lib/matplotlib/tests/test_axes.py::test_rgba_markers[svg]",
"lib/matplotlib/tests/test_axes.py::test_specgram_magnitude[png]",
"lib/matplotlib/tests/test_axes.py::test_bar_uint8",
"lib/matplotlib/tests/test_axes.py::test_barb_units",
"lib/matplotlib/tests/test_axes.py::test_hist_auto_bins",
"lib/matplotlib/tests/test_axes.py::test_relative_ticklabel_sizes[12]",
"lib/matplotlib/tests/test_axes.py::test_axes_tick_params_gridlines",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs48]",
"lib/matplotlib/tests/test_axes.py::test_title_above_offset[both titles aligned]",
"lib/matplotlib/tests/test_axes.py::test_hist_with_empty_input[data1-1]",
"lib/matplotlib/tests/test_axes.py::test_stackplot[svg]",
"lib/matplotlib/tests/test_axes.py::test_shared_axes_autoscale",
"lib/matplotlib/tests/test_axes.py::test_stairs_empty",
"lib/matplotlib/tests/test_axes.py::test_pie_nolabel_but_legend[png]",
"lib/matplotlib/tests/test_axes.py::test_arrow_in_view",
"lib/matplotlib/tests/test_axes.py::test_imshow_norm_vminvmax",
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"lib/matplotlib/tests/test_axes.py::test_parse_scatter_color_args[params2-expected_result2]",
"lib/matplotlib/tests/test_axes.py::test_bxp_showmeanasline[png]",
"lib/matplotlib/tests/test_axes.py::test_offset_text_visible",
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"lib/matplotlib/tests/test_axes.py::test_annotate_default_arrow",
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"lib/matplotlib/tests/test_axes.py::test_relim_visible_only",
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"lib/matplotlib/tests/test_axes.py::test_contour_hatching[svg]",
"lib/matplotlib/tests/test_axes.py::test_contour_colorbar[svg]",
"lib/matplotlib/tests/test_axes.py::test_pandas_pcolormesh",
"lib/matplotlib/tests/test_axes.py::test_pcolormesh[svg]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs20]",
"lib/matplotlib/tests/test_axes.py::test_axline[pdf]",
"lib/matplotlib/tests/test_axes.py::test_length_one_hist",
"lib/matplotlib/tests/test_axes.py::test_fill_between_interpolate_decreasing[png]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_cycle_ecolor[pdf]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_every[svg]",
"lib/matplotlib/tests/test_axes.py::test_alpha[pdf]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[0.5-None]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs39]",
"lib/matplotlib/tests/test_axes.py::test_label_loc_horizontal[svg]",
"lib/matplotlib/tests/test_axes.py::test_violinplot_outofrange_quantiles",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case9-None]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_limits[svg]",
"lib/matplotlib/tests/test_axes.py::test_get_xticklabel",
"lib/matplotlib/tests/test_axes.py::test_reset_grid",
"lib/matplotlib/tests/test_axes.py::test_errorbar[png]",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs9]",
"lib/matplotlib/tests/test_axes.py::test_fill_between_interpolate_nan[svg]",
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"lib/matplotlib/tests/test_axes.py::test_eventplot_orientation[vertical-data2]",
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"lib/matplotlib/tests/test_axes.py::test_set_xy_bound",
"lib/matplotlib/tests/test_axes.py::test_bar_label_location_horizontal",
"lib/matplotlib/tests/test_axes.py::test_margins_errors[ValueError-args1-kwargs1-margin must be greater than -0\\\\.5]",
"lib/matplotlib/tests/test_axes.py::test_remove_shared_axes[add_axes-y]",
"lib/matplotlib/tests/test_axes.py::test_hist_stacked_density[pdf]",
"lib/matplotlib/tests/test_axes.py::test_scatter_series_non_zero_index",
"lib/matplotlib/tests/test_axes.py::test_label_shift",
"lib/matplotlib/tests/test_axes.py::test_pcolor_regression",
"lib/matplotlib/tests/test_axes.py::test_hist_stepfilled_geometry",
"lib/matplotlib/tests/test_axes.py::test_errorbar_inputs_shotgun[kwargs49]",
"lib/matplotlib/tests/test_axes.py::test_aspect_nonlinear_adjustable_box",
"lib/matplotlib/tests/test_axes.py::test_specgram_origin_kwarg",
"lib/matplotlib/tests/test_axes.py::test_hist2d[pdf]",
"lib/matplotlib/tests/test_axes.py::test_plot_format_kwarg_redundant",
"lib/matplotlib/tests/test_axes.py::test_pie_center_radius[png]",
"lib/matplotlib/tests/test_axes.py::test_set_margin_updates_limits",
"lib/matplotlib/tests/test_axes.py::test_markevery_polar[png]",
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"lib/matplotlib/tests/test_axes.py::test_rgba_markers[png]",
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"lib/matplotlib/tests/test_axes.py::test_bar_tick_label_single[png]",
"lib/matplotlib/tests/test_axes.py::test_stairs_options[png]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case20-shape]",
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"lib/matplotlib/tests/test_axes.py::test_stackplot_baseline[png]",
"lib/matplotlib/tests/test_axes.py::test_parse_scatter_color_args_edgecolors[kwargs10-g]",
"lib/matplotlib/tests/test_axes.py::test_boxplot_not_single",
"lib/matplotlib/tests/test_axes.py::test_relative_ticklabel_sizes[x-small]",
"lib/matplotlib/tests/test_axes.py::test_relative_ticklabel_sizes[large]",
"lib/matplotlib/tests/test_axes.py::test_hexbin_log_clim",
"lib/matplotlib/tests/test_axes.py::test_twin_inherit_autoscale_setting",
"lib/matplotlib/tests/test_axes.py::test_arc_ellipse[pdf]",
"lib/matplotlib/tests/test_axes.py::test_hist_step[png]",
"lib/matplotlib/tests/test_axes.py::test_axis_errors[TypeError-args3-kwargs3-axis\\\\(\\\\) got an unexpected keyword argument 'foo']",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case18-shape]",
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"lib/matplotlib/tests/test_axes.py::test_eb_line_zorder[svg]",
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"lib/matplotlib/tests/test_axes.py::test_hist_log[svg]",
"lib/matplotlib/tests/test_axes.py::test_pandas_indexing_dates",
"lib/matplotlib/tests/test_axes.py::test_tick_param_label_rotation",
"lib/matplotlib/tests/test_axes.py::test_margins_errors[ValueError-args2-kwargs2-margin must be greater than -0\\\\.5]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case15-None]",
"lib/matplotlib/tests/test_axes.py::test_bar_labels[x-1-x-expected_labels0-x]",
"lib/matplotlib/tests/test_axes.py::test_shared_aspect_error",
"lib/matplotlib/tests/test_axes.py::test_pie_rotatelabels_true[png]",
"lib/matplotlib/tests/test_axes.py::test_stackplot_baseline[svg]",
"lib/matplotlib/tests/test_axes.py::test_o_marker_path_snap[png]",
"lib/matplotlib/tests/test_axes.py::test_label_loc_vertical[pdf]",
"lib/matplotlib/tests/test_axes.py::test_broken_barh_timedelta",
"lib/matplotlib/tests/test_axes.py::test_vert_violinplot_custompoints_10[png]",
"lib/matplotlib/tests/test_axes.py::test_bar_label_location_vertical",
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"lib/matplotlib/tests/test_axes.py::test_unautoscale[None-y]",
"lib/matplotlib/tests/test_axes.py::test_single_point[svg]",
"lib/matplotlib/tests/test_axes.py::test_plot_format",
"lib/matplotlib/tests/test_axes.py::test_relative_ticklabel_sizes[xx-large]",
"lib/matplotlib/tests/test_axes.py::test_label_loc_vertical[svg]",
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"lib/matplotlib/tests/test_axes.py::test_specgram_origin_rcparam[png]",
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"lib/matplotlib/tests/test_axes.py::test_rcparam_grid_minor[minor-False-True]",
"lib/matplotlib/tests/test_axes.py::test_bar_hatches[svg]",
"lib/matplotlib/tests/test_axes.py::test_eventplot_colors[colors0]",
"lib/matplotlib/tests/test_axes.py::test_minorticks_on[symlog-log]",
"lib/matplotlib/tests/test_axes.py::test_markevery_log_scales[svg]",
"lib/matplotlib/tests/test_axes.py::test_axline_transaxes[pdf]",
"lib/matplotlib/tests/test_axes.py::test_ylabel_ha_with_position[center]",
"lib/matplotlib/tests/test_axes.py::test_pcolornearestunits[png]",
"lib/matplotlib/tests/test_axes.py::test_bar_color_cycle",
"lib/matplotlib/tests/test_axes.py::test_marker_edges[png]",
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"lib/matplotlib/tests/test_axes.py::test_bxp_customwhisker[png]",
"lib/matplotlib/tests/test_axes.py::test_alpha[png]",
"lib/matplotlib/tests/test_axes.py::test_normalize_kwarg_pie",
"lib/matplotlib/tests/test_axes.py::test_vlines_default",
"lib/matplotlib/tests/test_axes.py::test_stairs_baseline_0[png]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case29-conversion]",
"lib/matplotlib/tests/test_axes.py::test_ylabel_ha_with_position[right]",
"lib/matplotlib/tests/test_axes.py::TestScatter::test_scatter_c[c_case1-conversion]"
] |
[
"lib/matplotlib/tests/test_axes.py::test_bar_labels[x1-width1-label1-expected_labels1-_nolegend_]",
"lib/matplotlib/tests/test_axes.py::test_bar_labels_length",
"lib/matplotlib/tests/test_axes.py::test_bar_labels[x2-width2-label2-expected_labels2-_nolegend_]"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/users/next_whats_new/bar_plot_labels.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/bar_plot_labels.rst",
"metadata": "diff --git a/doc/users/next_whats_new/bar_plot_labels.rst b/doc/users/next_whats_new/bar_plot_labels.rst\nnew file mode 100644\nindex 000000000000..6da57a317f59\n--- /dev/null\n+++ b/doc/users/next_whats_new/bar_plot_labels.rst\n@@ -0,0 +1,16 @@\n+Easier labelling of bars in bar plot\n+------------------------------------\n+\n+The ``label`` argument of `~matplotlib.axes.Axes.bar` can now\n+be passed a list of labels for the bars.\n+\n+.. code-block:: python\n+\n+ import matplotlib.pyplot as plt\n+\n+ x = [\"a\", \"b\", \"c\"]\n+ y = [10, 20, 15]\n+\n+ fig, ax = plt.subplots()\n+ bar_container = ax.barh(x, y, label=x)\n+ [bar.get_label() for bar in bar_container]\n"
}
] |
diff --git a/doc/users/next_whats_new/bar_plot_labels.rst b/doc/users/next_whats_new/bar_plot_labels.rst
new file mode 100644
index 000000000000..6da57a317f59
--- /dev/null
+++ b/doc/users/next_whats_new/bar_plot_labels.rst
@@ -0,0 +1,16 @@
+Easier labelling of bars in bar plot
+------------------------------------
+
+The ``label`` argument of `~matplotlib.axes.Axes.bar` can now
+be passed a list of labels for the bars.
+
+.. code-block:: python
+
+ import matplotlib.pyplot as plt
+
+ x = ["a", "b", "c"]
+ y = [10, 20, 15]
+
+ fig, ax = plt.subplots()
+ bar_container = ax.barh(x, y, label=x)
+ [bar.get_label() for bar in bar_container]
|
matplotlib/matplotlib
|
matplotlib__matplotlib-18869
|
https://github.com/matplotlib/matplotlib/pull/18869
|
diff --git a/doc/users/next_whats_new/version_info.rst b/doc/users/next_whats_new/version_info.rst
new file mode 100644
index 000000000000..5c51f9fe7332
--- /dev/null
+++ b/doc/users/next_whats_new/version_info.rst
@@ -0,0 +1,15 @@
+Version information
+-------------------
+We switched to the `release-branch-semver`_ version scheme. This only affects,
+the version information for development builds. Their version number now
+describes the targeted release, i.e. 3.5.0.dev820+g6768ef8c4c.d20210520
+is 820 commits after the previous release and is scheduled to be officially
+released as 3.5.0 later.
+
+In addition to the string ``__version__``, there is now a namedtuple
+``__version_info__`` as well, which is modelled after `sys.version_info`_.
+Its primary use is safely comparing version information, e.g.
+``if __version_info__ >= (3, 4, 2)``.
+
+.. _release-branch-semver: https://github.com/pypa/setuptools_scm#version-number-construction
+.. _sys.version_info: https://docs.python.org/3/library/sys.html#sys.version_info
\ No newline at end of file
diff --git a/lib/matplotlib/__init__.py b/lib/matplotlib/__init__.py
index b657a35cf7ed..92ef93e0079c 100644
--- a/lib/matplotlib/__init__.py
+++ b/lib/matplotlib/__init__.py
@@ -129,25 +129,60 @@
year = 2007
}"""
+# modelled after sys.version_info
+_VersionInfo = namedtuple('_VersionInfo',
+ 'major, minor, micro, releaselevel, serial')
-def __getattr__(name):
- if name == "__version__":
+
+def _parse_to_version_info(version_str):
+ """
+ Parse a version string to a namedtuple analogous to sys.version_info.
+
+ See:
+ https://packaging.pypa.io/en/latest/version.html#packaging.version.parse
+ https://docs.python.org/3/library/sys.html#sys.version_info
+ """
+ v = parse_version(version_str)
+ if v.pre is None and v.post is None and v.dev is None:
+ return _VersionInfo(v.major, v.minor, v.micro, 'final', 0)
+ elif v.dev is not None:
+ return _VersionInfo(v.major, v.minor, v.micro, 'alpha', v.dev)
+ elif v.pre is not None:
+ releaselevel = {
+ 'a': 'alpha',
+ 'b': 'beta',
+ 'rc': 'candidate'}.get(v.pre[0], 'alpha')
+ return _VersionInfo(v.major, v.minor, v.micro, releaselevel, v.pre[1])
+ else:
+ # fallback for v.post: guess-next-dev scheme from setuptools_scm
+ return _VersionInfo(v.major, v.minor, v.micro + 1, 'alpha', v.post)
+
+
+def _get_version():
+ """Return the version string used for __version__."""
+ # Only shell out to a git subprocess if really needed, and not on a
+ # shallow clone, such as those used by CI, as the latter would trigger
+ # a warning from setuptools_scm.
+ root = Path(__file__).resolve().parents[2]
+ if (root / ".git").exists() and not (root / ".git/shallow").exists():
import setuptools_scm
+ return setuptools_scm.get_version(
+ root=root,
+ version_scheme="post-release",
+ local_scheme="node-and-date",
+ fallback_version=_version.version,
+ )
+ else: # Get the version from the _version.py setuptools_scm file.
+ return _version.version
+
+
+def __getattr__(name):
+ if name in ("__version__", "__version_info__"):
global __version__ # cache it.
- # Only shell out to a git subprocess if really needed, and not on a
- # shallow clone, such as those used by CI, as the latter would trigger
- # a warning from setuptools_scm.
- root = Path(__file__).resolve().parents[2]
- if (root / ".git").exists() and not (root / ".git/shallow").exists():
- __version__ = setuptools_scm.get_version(
- root=root,
- version_scheme="post-release",
- local_scheme="node-and-date",
- fallback_version=_version.version,
- )
- else: # Get the version from the _version.py setuptools_scm file.
- __version__ = _version.version
- return __version__
+ __version__ = _get_version()
+ global __version__info__ # cache it.
+ __version_info__ = _parse_to_version_info(__version__)
+ return __version__ if name == "__version__" else __version_info__
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
|
diff --git a/lib/matplotlib/tests/test_matplotlib.py b/lib/matplotlib/tests/test_matplotlib.py
index cad9433a562e..6f92b4ca0abd 100644
--- a/lib/matplotlib/tests/test_matplotlib.py
+++ b/lib/matplotlib/tests/test_matplotlib.py
@@ -7,6 +7,16 @@
import matplotlib
+@pytest.mark.parametrize('version_str, version_tuple', [
+ ('3.5.0', (3, 5, 0, 'final', 0)),
+ ('3.5.0rc2', (3, 5, 0, 'candidate', 2)),
+ ('3.5.0.dev820+g6768ef8c4c', (3, 5, 0, 'alpha', 820)),
+ ('3.5.0.post820+g6768ef8c4c', (3, 5, 1, 'alpha', 820)),
+])
+def test_parse_to_version_info(version_str, version_tuple):
+ assert matplotlib._parse_to_version_info(version_str) == version_tuple
+
+
@pytest.mark.skipif(
os.name == "nt", reason="chmod() doesn't work as is on Windows")
@pytest.mark.skipif(os.name != "nt" and os.geteuid() == 0,
|
[
{
"path": "doc/users/next_whats_new/version_info.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/version_info.rst",
"metadata": "diff --git a/doc/users/next_whats_new/version_info.rst b/doc/users/next_whats_new/version_info.rst\nnew file mode 100644\nindex 000000000000..5c51f9fe7332\n--- /dev/null\n+++ b/doc/users/next_whats_new/version_info.rst\n@@ -0,0 +1,15 @@\n+Version information\n+-------------------\n+We switched to the `release-branch-semver`_ version scheme. This only affects,\n+the version information for development builds. Their version number now\n+describes the targeted release, i.e. 3.5.0.dev820+g6768ef8c4c.d20210520\n+is 820 commits after the previous release and is scheduled to be officially\n+released as 3.5.0 later.\n+\n+In addition to the string ``__version__``, there is now a namedtuple\n+``__version_info__`` as well, which is modelled after `sys.version_info`_.\n+Its primary use is safely comparing version information, e.g.\n+``if __version_info__ >= (3, 4, 2)``.\n+\n+.. _release-branch-semver: https://github.com/pypa/setuptools_scm#version-number-construction\n+.. _sys.version_info: https://docs.python.org/3/library/sys.html#sys.version_info\n\\ No newline at end of file\n"
}
] |
3.4
|
b7d05919865fc0c37a0164cf467d5d5513bd0ede
|
[
"lib/matplotlib/tests/test_matplotlib.py::test_importable_with__OO",
"lib/matplotlib/tests/test_matplotlib.py::test_importable_with_no_home",
"lib/matplotlib/tests/test_matplotlib.py::test_use_doc_standard_backends"
] |
[
"lib/matplotlib/tests/test_matplotlib.py::test_parse_to_version_info[3.5.0.post820+g6768ef8c4c-version_tuple3]",
"lib/matplotlib/tests/test_matplotlib.py::test_parse_to_version_info[3.5.0-version_tuple0]",
"lib/matplotlib/tests/test_matplotlib.py::test_parse_to_version_info[3.5.0.dev820+g6768ef8c4c-version_tuple2]",
"lib/matplotlib/tests/test_matplotlib.py::test_parse_to_version_info[3.5.0rc2-version_tuple1]"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": [
{
"type": "function",
"name": "_parse_to_version_info"
},
{
"type": "field",
"name": "_parse_to_version_info"
},
{
"type": "field",
"name": "version_str"
}
]
}
|
[
{
"path": "doc/users/next_whats_new/version_info.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/version_info.rst",
"metadata": "diff --git a/doc/users/next_whats_new/version_info.rst b/doc/users/next_whats_new/version_info.rst\nnew file mode 100644\nindex 000000000000..5c51f9fe7332\n--- /dev/null\n+++ b/doc/users/next_whats_new/version_info.rst\n@@ -0,0 +1,15 @@\n+Version information\n+-------------------\n+We switched to the `release-branch-semver`_ version scheme. This only affects,\n+the version information for development builds. Their version number now\n+describes the targeted release, i.e. 3.5.0.dev820+g6768ef8c4c.d20210520\n+is 820 commits after the previous release and is scheduled to be officially\n+released as 3.5.0 later.\n+\n+In addition to the string ``__version__``, there is now a namedtuple\n+``__version_info__`` as well, which is modelled after `sys.version_info`_.\n+Its primary use is safely comparing version information, e.g.\n+``if __version_info__ >= (3, 4, 2)``.\n+\n+.. _release-branch-semver: https://github.com/pypa/setuptools_scm#version-number-construction\n+.. _sys.version_info: https://docs.python.org/3/library/sys.html#sys.version_info\n\\ No newline at end of file\n"
}
] |
diff --git a/doc/users/next_whats_new/version_info.rst b/doc/users/next_whats_new/version_info.rst
new file mode 100644
index 000000000000..5c51f9fe7332
--- /dev/null
+++ b/doc/users/next_whats_new/version_info.rst
@@ -0,0 +1,15 @@
+Version information
+-------------------
+We switched to the `release-branch-semver`_ version scheme. This only affects,
+the version information for development builds. Their version number now
+describes the targeted release, i.e. 3.5.0.dev820+g6768ef8c4c.d20210520
+is 820 commits after the previous release and is scheduled to be officially
+released as 3.5.0 later.
+
+In addition to the string ``__version__``, there is now a namedtuple
+``__version_info__`` as well, which is modelled after `sys.version_info`_.
+Its primary use is safely comparing version information, e.g.
+``if __version_info__ >= (3, 4, 2)``.
+
+.. _release-branch-semver: https://github.com/pypa/setuptools_scm#version-number-construction
+.. _sys.version_info: https://docs.python.org/3/library/sys.html#sys.version_info
\ No newline at end of file
If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:
[{'type': 'function', 'name': '_parse_to_version_info'}, {'type': 'field', 'name': '_parse_to_version_info'}, {'type': 'field', 'name': 'version_str'}]
|
matplotlib/matplotlib
|
matplotlib__matplotlib-19553
|
https://github.com/matplotlib/matplotlib/pull/19553
|
diff --git a/doc/users/next_whats_new/callbacks_on_norms.rst b/doc/users/next_whats_new/callbacks_on_norms.rst
new file mode 100644
index 000000000000..1904a92d2fba
--- /dev/null
+++ b/doc/users/next_whats_new/callbacks_on_norms.rst
@@ -0,0 +1,8 @@
+A callback registry has been added to Normalize objects
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+`.colors.Normalize` objects now have a callback registry, ``callbacks``,
+that can be connected to by other objects to be notified when the norm is
+updated. The callback emits the key ``changed`` when the norm is modified.
+`.cm.ScalarMappable` is now a listener and will register a change
+when the norm's vmin, vmax or other attributes are changed.
diff --git a/lib/matplotlib/cm.py b/lib/matplotlib/cm.py
index 0af2f0f327d9..76c1c5d4f7f2 100644
--- a/lib/matplotlib/cm.py
+++ b/lib/matplotlib/cm.py
@@ -337,7 +337,7 @@ def __init__(self, norm=None, cmap=None):
The colormap used to map normalized data values to RGBA colors.
"""
self._A = None
- self.norm = None # So that the setter knows we're initializing.
+ self._norm = None # So that the setter knows we're initializing.
self.set_norm(norm) # The Normalize instance of this ScalarMappable.
self.cmap = None # So that the setter knows we're initializing.
self.set_cmap(cmap) # The Colormap instance of this ScalarMappable.
@@ -496,6 +496,8 @@ def set_clim(self, vmin=None, vmax=None):
.. ACCEPTS: (vmin: float, vmax: float)
"""
+ # If the norm's limits are updated self.changed() will be called
+ # through the callbacks attached to the norm
if vmax is None:
try:
vmin, vmax = vmin
@@ -505,7 +507,6 @@ def set_clim(self, vmin=None, vmax=None):
self.norm.vmin = colors._sanitize_extrema(vmin)
if vmax is not None:
self.norm.vmax = colors._sanitize_extrema(vmax)
- self.changed()
def get_alpha(self):
"""
@@ -531,6 +532,30 @@ def set_cmap(self, cmap):
if not in_init:
self.changed() # Things are not set up properly yet.
+ @property
+ def norm(self):
+ return self._norm
+
+ @norm.setter
+ def norm(self, norm):
+ _api.check_isinstance((colors.Normalize, None), norm=norm)
+ if norm is None:
+ norm = colors.Normalize()
+
+ if norm is self.norm:
+ # We aren't updating anything
+ return
+
+ in_init = self.norm is None
+ # Remove the current callback and connect to the new one
+ if not in_init:
+ self.norm.callbacks.disconnect(self._id_norm)
+ self._norm = norm
+ self._id_norm = self.norm.callbacks.connect('changed',
+ self.changed)
+ if not in_init:
+ self.changed()
+
def set_norm(self, norm):
"""
Set the normalization instance.
@@ -545,13 +570,7 @@ def set_norm(self, norm):
the norm of the mappable will reset the norm, locator, and formatters
on the colorbar to default.
"""
- _api.check_isinstance((colors.Normalize, None), norm=norm)
- in_init = self.norm is None
- if norm is None:
- norm = colors.Normalize()
self.norm = norm
- if not in_init:
- self.changed() # Things are not set up properly yet.
def autoscale(self):
"""
@@ -560,8 +579,9 @@ def autoscale(self):
"""
if self._A is None:
raise TypeError('You must first set_array for mappable')
+ # If the norm's limits are updated self.changed() will be called
+ # through the callbacks attached to the norm
self.norm.autoscale(self._A)
- self.changed()
def autoscale_None(self):
"""
@@ -570,8 +590,9 @@ def autoscale_None(self):
"""
if self._A is None:
raise TypeError('You must first set_array for mappable')
+ # If the norm's limits are updated self.changed() will be called
+ # through the callbacks attached to the norm
self.norm.autoscale_None(self._A)
- self.changed()
def changed(self):
"""
diff --git a/lib/matplotlib/colorbar.py b/lib/matplotlib/colorbar.py
index 459b14f6c5a7..9d40ac8e5e9c 100644
--- a/lib/matplotlib/colorbar.py
+++ b/lib/matplotlib/colorbar.py
@@ -471,6 +471,7 @@ def __init__(self, ax, mappable=None, *, cmap=None,
self.ax.add_collection(self.dividers)
self.locator = None
+ self.minorlocator = None
self.formatter = None
self.__scale = None # linear, log10 for now. Hopefully more?
@@ -1096,7 +1097,7 @@ def _mesh(self):
# vmax of the colorbar, not the norm. This allows the situation
# where the colormap has a narrower range than the colorbar, to
# accommodate extra contours:
- norm = copy.copy(self.norm)
+ norm = copy.deepcopy(self.norm)
norm.vmin = self.vmin
norm.vmax = self.vmax
x = np.array([0.0, 1.0])
diff --git a/lib/matplotlib/colors.py b/lib/matplotlib/colors.py
index c5db6117f1bc..58e3fe198498 100644
--- a/lib/matplotlib/colors.py
+++ b/lib/matplotlib/colors.py
@@ -1123,10 +1123,50 @@ def __init__(self, vmin=None, vmax=None, clip=False):
-----
Returns 0 if ``vmin == vmax``.
"""
- self.vmin = _sanitize_extrema(vmin)
- self.vmax = _sanitize_extrema(vmax)
- self.clip = clip
- self._scale = None # will default to LinearScale for colorbar
+ self._vmin = _sanitize_extrema(vmin)
+ self._vmax = _sanitize_extrema(vmax)
+ self._clip = clip
+ self._scale = None
+ self.callbacks = cbook.CallbackRegistry()
+
+ @property
+ def vmin(self):
+ return self._vmin
+
+ @vmin.setter
+ def vmin(self, value):
+ value = _sanitize_extrema(value)
+ if value != self._vmin:
+ self._vmin = value
+ self._changed()
+
+ @property
+ def vmax(self):
+ return self._vmax
+
+ @vmax.setter
+ def vmax(self, value):
+ value = _sanitize_extrema(value)
+ if value != self._vmax:
+ self._vmax = value
+ self._changed()
+
+ @property
+ def clip(self):
+ return self._clip
+
+ @clip.setter
+ def clip(self, value):
+ if value != self._clip:
+ self._clip = value
+ self._changed()
+
+ def _changed(self):
+ """
+ Call this whenever the norm is changed to notify all the
+ callback listeners to the 'changed' signal.
+ """
+ self.callbacks.process('changed')
@staticmethod
def process_value(value):
@@ -1273,7 +1313,7 @@ def __init__(self, vcenter, vmin=None, vmax=None):
"""
super().__init__(vmin=vmin, vmax=vmax)
- self.vcenter = vcenter
+ self._vcenter = vcenter
if vcenter is not None and vmax is not None and vcenter >= vmax:
raise ValueError('vmin, vcenter, and vmax must be in '
'ascending order')
@@ -1281,6 +1321,16 @@ def __init__(self, vcenter, vmin=None, vmax=None):
raise ValueError('vmin, vcenter, and vmax must be in '
'ascending order')
+ @property
+ def vcenter(self):
+ return self._vcenter
+
+ @vcenter.setter
+ def vcenter(self, value):
+ if value != self._vcenter:
+ self._vcenter = value
+ self._changed()
+
def autoscale_None(self, A):
"""
Get vmin and vmax, and then clip at vcenter
@@ -1387,7 +1437,9 @@ def vcenter(self):
@vcenter.setter
def vcenter(self, vcenter):
- self._vcenter = vcenter
+ if vcenter != self._vcenter:
+ self._vcenter = vcenter
+ self._changed()
if self.vmax is not None:
# recompute halfrange assuming vmin and vmax represent
# min and max of data
diff --git a/lib/matplotlib/contour.py b/lib/matplotlib/contour.py
index 7dec80943993..4d124ce8c57c 100644
--- a/lib/matplotlib/contour.py
+++ b/lib/matplotlib/contour.py
@@ -1090,6 +1090,15 @@ def _make_paths(self, segs, kinds):
in zip(segs, kinds)]
def changed(self):
+ if not hasattr(self, "cvalues"):
+ # Just return after calling the super() changed function
+ cm.ScalarMappable.changed(self)
+ return
+ # Force an autoscale immediately because self.to_rgba() calls
+ # autoscale_None() internally with the data passed to it,
+ # so if vmin/vmax are not set yet, this would override them with
+ # content from *cvalues* rather than levels like we want
+ self.norm.autoscale_None(self.levels)
tcolors = [(tuple(rgba),)
for rgba in self.to_rgba(self.cvalues, alpha=self.alpha)]
self.tcolors = tcolors
diff --git a/lib/matplotlib/image.py b/lib/matplotlib/image.py
index ca5b7da5f808..2036bf7e17c9 100644
--- a/lib/matplotlib/image.py
+++ b/lib/matplotlib/image.py
@@ -537,11 +537,14 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
if isinstance(self.norm, mcolors.LogNorm) and s_vmin <= 0:
# Don't give 0 or negative values to LogNorm
s_vmin = np.finfo(scaled_dtype).eps
- with cbook._setattr_cm(self.norm,
- vmin=s_vmin,
- vmax=s_vmax,
- ):
- output = self.norm(resampled_masked)
+ # Block the norm from sending an update signal during the
+ # temporary vmin/vmax change
+ with self.norm.callbacks.blocked():
+ with cbook._setattr_cm(self.norm,
+ vmin=s_vmin,
+ vmax=s_vmax,
+ ):
+ output = self.norm(resampled_masked)
else:
if A.ndim == 2: # _interpolation_stage == 'rgba'
self.norm.autoscale_None(A)
|
diff --git a/lib/matplotlib/tests/test_colors.py b/lib/matplotlib/tests/test_colors.py
index ae004e957591..bf89a3a82364 100644
--- a/lib/matplotlib/tests/test_colors.py
+++ b/lib/matplotlib/tests/test_colors.py
@@ -1,5 +1,6 @@
import copy
import itertools
+import unittest.mock
from io import BytesIO
import numpy as np
@@ -17,7 +18,7 @@
import matplotlib.cbook as cbook
import matplotlib.pyplot as plt
import matplotlib.scale as mscale
-from matplotlib.testing.decorators import image_comparison
+from matplotlib.testing.decorators import image_comparison, check_figures_equal
@pytest.mark.parametrize('N, result', [
@@ -1408,3 +1409,69 @@ def test_norm_deepcopy():
norm2 = copy.deepcopy(norm)
assert norm2._scale is None
assert norm2.vmin == norm.vmin
+
+
+def test_norm_callback():
+ increment = unittest.mock.Mock(return_value=None)
+
+ norm = mcolors.Normalize()
+ norm.callbacks.connect('changed', increment)
+ # Haven't updated anything, so call count should be 0
+ assert increment.call_count == 0
+
+ # Now change vmin and vmax to test callbacks
+ norm.vmin = 1
+ assert increment.call_count == 1
+ norm.vmax = 5
+ assert increment.call_count == 2
+ # callback shouldn't be called if setting to the same value
+ norm.vmin = 1
+ assert increment.call_count == 2
+ norm.vmax = 5
+ assert increment.call_count == 2
+
+
+def test_scalarmappable_norm_update():
+ norm = mcolors.Normalize()
+ sm = matplotlib.cm.ScalarMappable(norm=norm, cmap='plasma')
+ # sm doesn't have a stale attribute at first, set it to False
+ sm.stale = False
+ # The mappable should be stale after updating vmin/vmax
+ norm.vmin = 5
+ assert sm.stale
+ sm.stale = False
+ norm.vmax = 5
+ assert sm.stale
+ sm.stale = False
+ norm.clip = True
+ assert sm.stale
+ # change to the CenteredNorm and TwoSlopeNorm to test those
+ # Also make sure that updating the norm directly and with
+ # set_norm both update the Norm callback
+ norm = mcolors.CenteredNorm()
+ sm.norm = norm
+ sm.stale = False
+ norm.vcenter = 1
+ assert sm.stale
+ norm = mcolors.TwoSlopeNorm(vcenter=0, vmin=-1, vmax=1)
+ sm.set_norm(norm)
+ sm.stale = False
+ norm.vcenter = 1
+ assert sm.stale
+
+
+@check_figures_equal()
+def test_norm_update_figs(fig_test, fig_ref):
+ ax_ref = fig_ref.add_subplot()
+ ax_test = fig_test.add_subplot()
+
+ z = np.arange(100).reshape((10, 10))
+ ax_ref.imshow(z, norm=mcolors.Normalize(10, 90))
+
+ # Create the norm beforehand with different limits and then update
+ # after adding to the plot
+ norm = mcolors.Normalize(0, 1)
+ ax_test.imshow(z, norm=norm)
+ # Force initial draw to make sure it isn't already stale
+ fig_test.canvas.draw()
+ norm.vmin, norm.vmax = 10, 90
diff --git a/lib/matplotlib/tests/test_image.py b/lib/matplotlib/tests/test_image.py
index 37dddd4e4706..2e7fae6c58d8 100644
--- a/lib/matplotlib/tests/test_image.py
+++ b/lib/matplotlib/tests/test_image.py
@@ -1017,8 +1017,8 @@ def test_imshow_bool():
def test_full_invalid():
fig, ax = plt.subplots()
ax.imshow(np.full((10, 10), np.nan))
- with pytest.warns(UserWarning):
- fig.canvas.draw()
+
+ fig.canvas.draw()
@pytest.mark.parametrize("fmt,counted",
|
[
{
"path": "doc/users/next_whats_new/callbacks_on_norms.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/callbacks_on_norms.rst",
"metadata": "diff --git a/doc/users/next_whats_new/callbacks_on_norms.rst b/doc/users/next_whats_new/callbacks_on_norms.rst\nnew file mode 100644\nindex 000000000000..1904a92d2fba\n--- /dev/null\n+++ b/doc/users/next_whats_new/callbacks_on_norms.rst\n@@ -0,0 +1,8 @@\n+A callback registry has been added to Normalize objects\n+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n+\n+`.colors.Normalize` objects now have a callback registry, ``callbacks``,\n+that can be connected to by other objects to be notified when the norm is\n+updated. The callback emits the key ``changed`` when the norm is modified.\n+`.cm.ScalarMappable` is now a listener and will register a change\n+when the norm's vmin, vmax or other attributes are changed.\n"
}
] |
3.4
|
ca275dca26d746fb1ce59a16e8c0f7db42d6813a
|
[
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[OrRd_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[cubehelix]",
"lib/matplotlib/tests/test_image.py::test_imsave_fspath[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[summer]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Blues]",
"lib/matplotlib/tests/test_image.py::test_load_from_url",
"lib/matplotlib/tests/test_image.py::test_composite[False-2-ps- colorimage]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[BuGn_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[YlOrBr_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_heat_r]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_VminGTVcenter",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[YlGn_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[seismic]",
"lib/matplotlib/tests/test_colors.py::test_conversions",
"lib/matplotlib/tests/test_colors.py::test_to_rgba_array_alpha_array",
"lib/matplotlib/tests/test_colors.py::test_LogNorm",
"lib/matplotlib/tests/test_image.py::test_image_alpha[pdf]",
"lib/matplotlib/tests/test_image.py::test_image_cursor_formatting",
"lib/matplotlib/tests/test_colors.py::test_colormap_equals",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[winter_r]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_VcenterGTVmax",
"lib/matplotlib/tests/test_image.py::test_image_composite_alpha[pdf]",
"lib/matplotlib/tests/test_image.py::test_no_interpolation_origin[png]",
"lib/matplotlib/tests/test_colors.py::test_light_source_shading_empty_mask",
"lib/matplotlib/tests/test_image.py::test_image_array_alpha[pdf]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[coolwarm]",
"lib/matplotlib/tests/test_colors.py::test_cn",
"lib/matplotlib/tests/test_image.py::test_axesimage_setdata",
"lib/matplotlib/tests/test_image.py::test_image_clip[svg]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[twilight_shifted_r]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_Even",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Oranges]",
"lib/matplotlib/tests/test_colors.py::test_pandas_iterable",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[magma]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Dark2_r]",
"lib/matplotlib/tests/test_image.py::test_imshow_float128",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Greys_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gnuplot_r]",
"lib/matplotlib/tests/test_image.py::test_imshow_masked_interpolation[pdf]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_scaleout_center",
"lib/matplotlib/tests/test_image.py::test_imsave[png]",
"lib/matplotlib/tests/test_image.py::test_imshow[png]",
"lib/matplotlib/tests/test_image.py::test_empty_imshow[<lambda>1]",
"lib/matplotlib/tests/test_colors.py::test_light_source_planar_hillshading",
"lib/matplotlib/tests/test_image.py::test_rotate_image[svg]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[inferno_r]",
"lib/matplotlib/tests/test_colors.py::test_BoundaryNorm",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[jet]",
"lib/matplotlib/tests/test_image.py::test_imshow_antialiased[png-5-10-nearest]",
"lib/matplotlib/tests/test_image.py::test_imshow_pil[pdf]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[bwr_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdBu_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[cubehelix_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[CMRmap_r]",
"lib/matplotlib/tests/test_image.py::test_imread_pil_uint16",
"lib/matplotlib/tests/test_image.py::test_jpeg_2d",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[twilight_shifted]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[coolwarm_r]",
"lib/matplotlib/tests/test_colors.py::test_norm_update_figs[png]",
"lib/matplotlib/tests/test_image.py::test_spy_box[pdf]",
"lib/matplotlib/tests/test_colors.py::test_create_lookup_table[1-result2]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[bone]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[BrBG]",
"lib/matplotlib/tests/test_image.py::test_imsave_pil_kwargs_tiff",
"lib/matplotlib/tests/test_colors.py::test_FuncNorm",
"lib/matplotlib/tests/test_image.py::test_figimage[png-True]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Set3]",
"lib/matplotlib/tests/test_colors.py::test_Normalize",
"lib/matplotlib/tests/test_image.py::test_imshow_bignumbers[png]",
"lib/matplotlib/tests/test_image.py::test_spy_box[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[rainbow]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[tab20c]",
"lib/matplotlib/tests/test_image.py::test_imshow_pil[svg]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_rainbow_r]",
"lib/matplotlib/tests/test_image.py::test_imshow_endianess[png]",
"lib/matplotlib/tests/test_image.py::test_imsave[tiff]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_VmaxEqualsVcenter",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[spring]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[magma_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[YlOrRd]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[binary_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[flag_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[turbo_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_copy",
"lib/matplotlib/tests/test_image.py::test_imshow_antialiased[png-3-9.1-nearest]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_VminEqualsVcenter",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_scale",
"lib/matplotlib/tests/test_image.py::test_no_interpolation_origin[svg]",
"lib/matplotlib/tests/test_colors.py::test_create_lookup_table[2-result1]",
"lib/matplotlib/tests/test_colors.py::test_light_source_hillshading",
"lib/matplotlib/tests/test_image.py::test_mask_image[svg]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[viridis]",
"lib/matplotlib/tests/test_image.py::test_imshow_clips_rgb_to_valid_range[dtype1]",
"lib/matplotlib/tests/test_image.py::test_imshow_10_10_5",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PRGn]",
"lib/matplotlib/tests/test_image.py::test_bbox_image_inverted[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PiYG]",
"lib/matplotlib/tests/test_colors.py::test_norm_deepcopy",
"lib/matplotlib/tests/test_colors.py::test_SymLogNorm",
"lib/matplotlib/tests/test_image.py::test_norm_change[png]",
"lib/matplotlib/tests/test_image.py::test_empty_imshow[Normalize]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[copper_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Oranges_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdYlGn]",
"lib/matplotlib/tests/test_image.py::test_cursor_data",
"lib/matplotlib/tests/test_image.py::test_unclipped",
"lib/matplotlib/tests/test_image.py::test_nonuniformimage_setnorm",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_autoscale_None_vmax",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[prism_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[terrain_r]",
"lib/matplotlib/tests/test_image.py::test_log_scale_image[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[cool_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[pink_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_stern_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[brg_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdYlGn_r]",
"lib/matplotlib/tests/test_colors.py::test_create_lookup_table[5-result0]",
"lib/matplotlib/tests/test_image.py::test_imshow_clips_rgb_to_valid_range[dtype3]",
"lib/matplotlib/tests/test_image.py::test_huge_range_log[png--1]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[copper]",
"lib/matplotlib/tests/test_image.py::test_format_cursor_data[data1-[0.123]-[0.123]]",
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"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Greens_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Wistia]",
"lib/matplotlib/tests/test_colors.py::test_double_register_builtin_cmap",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdYlBu_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PRGn_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_ncar_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[seismic_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_yarg_r]",
"lib/matplotlib/tests/test_image.py::test_zoom_and_clip_upper_origin[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[tab20_r]",
"lib/matplotlib/tests/test_colors.py::test_resample",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[winter]",
"lib/matplotlib/tests/test_colors.py::test_PowerNorm",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[tab10_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[binary]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gray_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_dict_deprecate",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gnuplot2]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdPu_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_earth]",
"lib/matplotlib/tests/test_image.py::test_exact_vmin",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[YlGn]",
"lib/matplotlib/tests/test_image.py::test_image_interps[pdf]",
"lib/matplotlib/tests/test_colors.py::test_to_rgba_array_single_str",
"lib/matplotlib/tests/test_image.py::test_full_invalid",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_earth_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PuOr_r]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_TwoSlopeNorm_VminGTVmax",
"lib/matplotlib/tests/test_image.py::test_imshow_zoom[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[cool]",
"lib/matplotlib/tests/test_image.py::test_figimage[pdf-True]",
"lib/matplotlib/tests/test_image.py::test_imshow_no_warn_invalid",
"lib/matplotlib/tests/test_image.py::test_huge_range_log[png-1]",
"lib/matplotlib/tests/test_colors.py::test_colormap_endian",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Set1]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[YlGnBu_r]",
"lib/matplotlib/tests/test_image.py::test_setdata_xya[PcolorImage-x1-y1-a1]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[BrBG_r]",
"lib/matplotlib/tests/test_colors.py::test_SymLogNorm_single_zero",
"lib/matplotlib/tests/test_image.py::test_imshow_float16",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Wistia_r]",
"lib/matplotlib/tests/test_image.py::test_image_preserve_size2",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[GnBu_r]",
"lib/matplotlib/tests/test_image.py::test_image_array_alpha_validation",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[GnBu]",
"lib/matplotlib/tests/test_colors.py::test_tableau_order",
"lib/matplotlib/tests/test_image.py::test_spy_box[svg]",
"lib/matplotlib/tests/test_colors.py::test_light_source_topo_surface[png]",
"lib/matplotlib/tests/test_colors.py::test_rgb_hsv_round_trip",
"lib/matplotlib/tests/test_colors.py::test_grey_gray",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[summer_r]",
"lib/matplotlib/tests/test_image.py::test_imsave_fspath[eps]",
"lib/matplotlib/tests/test_colors.py::test_colormap_bad_data_with_alpha",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Pastel1]",
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"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Reds]",
"lib/matplotlib/tests/test_colors.py::test_set_dict_to_rgba",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PuBuGn_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Purples]",
"lib/matplotlib/tests/test_colors.py::test_PowerNorm_translation_invariance",
"lib/matplotlib/tests/test_colors.py::test_colormap_return_types",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[nipy_spectral]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[terrain]",
"lib/matplotlib/tests/test_image.py::test_image_shift[pdf]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_scaleout_center_max",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[pink]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Pastel1_r]",
"lib/matplotlib/tests/test_colors.py::test_same_color",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Purples_r]",
"lib/matplotlib/tests/test_image.py::test_alpha_interp[png]",
"lib/matplotlib/tests/test_colors.py::test_autoscale_masked",
"lib/matplotlib/tests/test_image.py::test_figimage[pdf-False]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[BuPu_r]",
"lib/matplotlib/tests/test_image.py::test_imshow[svg]",
"lib/matplotlib/tests/test_colors.py::test_CenteredNorm",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PuBuGn]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_autoscale_None_vmin",
"lib/matplotlib/tests/test_image.py::test_imshow_masked_interpolation[png]",
"lib/matplotlib/tests/test_colors.py::test_repr_html",
"lib/matplotlib/tests/test_image.py::test_imshow_masked_interpolation[svg]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[nipy_spectral_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Set2_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[jet_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[tab20c_r]",
"lib/matplotlib/tests/test_image.py::test_image_composite_background[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[twilight]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Paired_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[hsv]",
"lib/matplotlib/tests/test_colors.py::test_2d_to_rgba",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[tab20b_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_gray]",
"lib/matplotlib/tests/test_colors.py::test_LogNorm_inverse",
"lib/matplotlib/tests/test_image.py::test_image_composite_alpha[png]",
"lib/matplotlib/tests/test_image.py::test_imsave_fspath[svg]",
"lib/matplotlib/tests/test_image.py::test_imshow_clips_rgb_to_valid_range[dtype4]",
"lib/matplotlib/tests/test_image.py::test_image_alpha[svg]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PuOr]",
"lib/matplotlib/tests/test_image.py::test_format_cursor_data[data0-[1e+04]-[10001]]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[tab20]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_Odd",
"lib/matplotlib/tests/test_image.py::test_image_interps[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[bwr]",
"lib/matplotlib/tests/test_colors.py::test_cmap_and_norm_from_levels_and_colors2",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[YlGnBu]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[turbo]",
"lib/matplotlib/tests/test_colors.py::test_repr_png",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[hsv_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PuBu_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[hot]",
"lib/matplotlib/tests/test_image.py::test_log_scale_image[pdf]",
"lib/matplotlib/tests/test_image.py::test_imshow_clips_rgb_to_valid_range[dtype5]",
"lib/matplotlib/tests/test_image.py::test_no_interpolation_origin[pdf]",
"lib/matplotlib/tests/test_image.py::test_imsave_fspath[ps]",
"lib/matplotlib/tests/test_colors.py::test_SymLogNorm_colorbar",
"lib/matplotlib/tests/test_colors.py::test_ndarray_subclass_norm",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdBu]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[plasma_r]",
"lib/matplotlib/tests/test_colors.py::test_lognorm_invalid[3-1]",
"lib/matplotlib/tests/test_colors.py::test_colormap_invalid",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdGy_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[plasma]",
"lib/matplotlib/tests/test_image.py::test_image_cliprect[svg]",
"lib/matplotlib/tests/test_colors.py::test_color_names",
"lib/matplotlib/tests/test_image.py::test_rasterize_dpi[svg]",
"lib/matplotlib/tests/test_image.py::test_mask_image[png]",
"lib/matplotlib/tests/test_image.py::test_imshow_clips_rgb_to_valid_range[dtype0]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Accent_r]",
"lib/matplotlib/tests/test_colors.py::test_register_cmap",
"lib/matplotlib/tests/test_image.py::test_imshow_pil[png]",
"lib/matplotlib/tests/test_image.py::test_imshow_flatfield[png]",
"lib/matplotlib/tests/test_image.py::test_imread_fspath",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_rainbow]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[BuGn]",
"lib/matplotlib/tests/test_colors.py::test_failed_conversions",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Pastel2_r]",
"lib/matplotlib/tests/test_image.py::test_log_scale_image[svg]",
"lib/matplotlib/tests/test_image.py::test_composite[True-1-svg-<image]",
"lib/matplotlib/tests/test_image.py::test_composite[True-1-ps- colorimage]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[autumn_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[ocean_r]",
"lib/matplotlib/tests/test_image.py::test_bbox_image_inverted[svg]",
"lib/matplotlib/tests/test_colors.py::test_light_source_shading_default",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[BuPu]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gnuplot]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Greys]",
"lib/matplotlib/tests/test_image.py::test_image_clip[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Spectral]",
"lib/matplotlib/tests/test_image.py::test_image_array_alpha[svg]",
"lib/matplotlib/tests/test_image.py::test_minimized_rasterized",
"lib/matplotlib/tests/test_colors.py::test_light_source_masked_shading",
"lib/matplotlib/tests/test_image.py::test_https_imread_smoketest",
"lib/matplotlib/tests/test_colors.py::test_norm_update_figs[svg]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[YlOrBr]",
"lib/matplotlib/tests/test_image.py::test_clip_path_disables_compositing[pdf]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Set3_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Paired]",
"lib/matplotlib/tests/test_image.py::test_image_composite_background[svg]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[prism]",
"lib/matplotlib/tests/test_colors.py::test_colormap_global_set_warn",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Blues_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_stern]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_gray_r]",
"lib/matplotlib/tests/test_image.py::test_imsave[jpg]",
"lib/matplotlib/tests/test_image.py::test_figimage[png-False]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[twilight_r]",
"lib/matplotlib/tests/test_image.py::test_mask_image_all",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Pastel2]",
"lib/matplotlib/tests/test_image.py::test_image_array_alpha[png]",
"lib/matplotlib/tests/test_image.py::test_get_window_extent_for_AxisImage",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[autumn]",
"lib/matplotlib/tests/test_colors.py::test_conversions_masked",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_ncar]",
"lib/matplotlib/tests/test_image.py::test_respects_bbox",
"lib/matplotlib/tests/test_colors.py::test_boundarynorm_and_colorbarbase[png]",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_premature_scaling",
"lib/matplotlib/tests/test_image.py::test_empty_imshow[LogNorm]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdPu]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Dark2]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[tab20b]",
"lib/matplotlib/tests/test_colors.py::test_get_under_over_bad",
"lib/matplotlib/tests/test_colors.py::test_non_mutable_get_values[bad]",
"lib/matplotlib/tests/test_image.py::test_image_alpha[png]",
"lib/matplotlib/tests/test_colors.py::test_norm_update_figs[pdf]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[afmhot_r]",
"lib/matplotlib/tests/test_image.py::test_image_cliprect[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[viridis_r]",
"lib/matplotlib/tests/test_image.py::test_rotate_image[pdf]",
"lib/matplotlib/tests/test_image.py::test_imsave_color_alpha",
"lib/matplotlib/tests/test_colors.py::test_TwoSlopeNorm_autoscale",
"lib/matplotlib/tests/test_image.py::test_relim",
"lib/matplotlib/tests/test_image.py::test_rotate_image[png]",
"lib/matplotlib/tests/test_colors.py::test_lognorm_invalid[-1-2]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Set2]",
"lib/matplotlib/tests/test_image.py::test_image_composite_alpha[svg]",
"lib/matplotlib/tests/test_image.py::test_imshow_antialiased[png-5-5-nearest]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdYlBu]",
"lib/matplotlib/tests/test_colors.py::test_hex_shorthand_notation",
"lib/matplotlib/tests/test_image.py::test_imshow_antialiased[png-5-2-hanning]",
"lib/matplotlib/tests/test_image.py::test_mask_image_over_under[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PuBu]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PuRd_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[afmhot]",
"lib/matplotlib/tests/test_image.py::test_image_shift[svg]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[spring_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Greens]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[brg]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Set1_r]",
"lib/matplotlib/tests/test_image.py::test_image_preserve_size",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Accent]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[inferno]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[OrRd]",
"lib/matplotlib/tests/test_image.py::test_imshow_clips_rgb_to_valid_range[dtype6]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PiYG_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gnuplot2_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gray]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[bone_r]",
"lib/matplotlib/tests/test_image.py::test_jpeg_alpha",
"lib/matplotlib/tests/test_image.py::test_setdata_xya[NonUniformImage-x0-y0-a0]",
"lib/matplotlib/tests/test_image.py::test_imshow_bignumbers_real[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[RdGy]",
"lib/matplotlib/tests/test_image.py::test_nonuniform_and_pcolor[png]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[flag]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Reds_r]",
"lib/matplotlib/tests/test_colors.py::test_cmap_and_norm_from_levels_and_colors[png]",
"lib/matplotlib/tests/test_image.py::test_interp_nearest_vs_none[svg]",
"lib/matplotlib/tests/test_colors.py::test_colormap_alpha_array",
"lib/matplotlib/tests/test_image.py::test_imshow[pdf]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[Spectral_r]",
"lib/matplotlib/tests/test_image.py::test_imshow_clips_rgb_to_valid_range[dtype2]",
"lib/matplotlib/tests/test_image.py::test_image_python_io",
"lib/matplotlib/tests/test_image.py::test_image_interps[svg]",
"lib/matplotlib/tests/test_image.py::test_quantitynd",
"lib/matplotlib/tests/test_image.py::test_imshow_10_10_2",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[tab10]",
"lib/matplotlib/tests/test_image.py::test_imsave_fspath[pdf]",
"lib/matplotlib/tests/test_colors.py::test_non_mutable_get_values[over]",
"lib/matplotlib/tests/test_image.py::test_empty_imshow[<lambda>0]",
"lib/matplotlib/tests/test_image.py::test_imshow_antialiased[png-3-2.9-hanning]",
"lib/matplotlib/tests/test_image.py::test_rgba_antialias[png]",
"lib/matplotlib/tests/test_image.py::test_image_edges",
"lib/matplotlib/tests/test_colors.py::test_non_mutable_get_values[under]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[rainbow_r]",
"lib/matplotlib/tests/test_image.py::test_imshow_10_10_1[png]",
"lib/matplotlib/tests/test_colors.py::test_unregister_builtin_cmap",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_yarg]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[hot_r]",
"lib/matplotlib/tests/test_image.py::test_composite[False-2-svg-<image]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[gist_heat]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[PuRd]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[cividis_r]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[CMRmap]",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[ocean]",
"lib/matplotlib/tests/test_image.py::test_imsave[jpeg]",
"lib/matplotlib/tests/test_image.py::test_imshow_bool",
"lib/matplotlib/tests/test_image.py::test_nonuniformimage_setcmap",
"lib/matplotlib/tests/test_colors.py::test_colormap_reversing[YlOrRd_r]",
"lib/matplotlib/tests/test_image.py::test_figureimage_setdata"
] |
[
"lib/matplotlib/tests/test_colors.py::test_norm_callback",
"lib/matplotlib/tests/test_colors.py::test_scalarmappable_norm_update"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/users/next_whats_new/callbacks_on_norms.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/callbacks_on_norms.rst",
"metadata": "diff --git a/doc/users/next_whats_new/callbacks_on_norms.rst b/doc/users/next_whats_new/callbacks_on_norms.rst\nnew file mode 100644\nindex 000000000000..1904a92d2fba\n--- /dev/null\n+++ b/doc/users/next_whats_new/callbacks_on_norms.rst\n@@ -0,0 +1,8 @@\n+A callback registry has been added to Normalize objects\n+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n+\n+`.colors.Normalize` objects now have a callback registry, ``callbacks``,\n+that can be connected to by other objects to be notified when the norm is\n+updated. The callback emits the key ``changed`` when the norm is modified.\n+`.cm.ScalarMappable` is now a listener and will register a change\n+when the norm's vmin, vmax or other attributes are changed.\n"
}
] |
diff --git a/doc/users/next_whats_new/callbacks_on_norms.rst b/doc/users/next_whats_new/callbacks_on_norms.rst
new file mode 100644
index 000000000000..1904a92d2fba
--- /dev/null
+++ b/doc/users/next_whats_new/callbacks_on_norms.rst
@@ -0,0 +1,8 @@
+A callback registry has been added to Normalize objects
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+`.colors.Normalize` objects now have a callback registry, ``callbacks``,
+that can be connected to by other objects to be notified when the norm is
+updated. The callback emits the key ``changed`` when the norm is modified.
+`.cm.ScalarMappable` is now a listener and will register a change
+when the norm's vmin, vmax or other attributes are changed.
|
matplotlib/matplotlib
|
matplotlib__matplotlib-19743
|
https://github.com/matplotlib/matplotlib/pull/19743
|
diff --git a/doc/users/next_whats_new/legend-figure-outside.rst b/doc/users/next_whats_new/legend-figure-outside.rst
new file mode 100644
index 000000000000..a78725b4e2b6
--- /dev/null
+++ b/doc/users/next_whats_new/legend-figure-outside.rst
@@ -0,0 +1,8 @@
+Figure legends can be placed outside figures using constrained_layout
+---------------------------------------------------------------------
+Constrained layout will make space for Figure legends if they are specified
+by a *loc* keyword argument that starts with the string "outside". The
+codes are unique from axes codes, in that "outside upper right" will
+make room at the top of the figure for the legend, whereas
+"outside right upper" will make room on the right-hand side of the figure.
+See :doc:`/tutorials/intermediate/legend_guide` for details.
diff --git a/examples/text_labels_and_annotations/figlegend_demo.py b/examples/text_labels_and_annotations/figlegend_demo.py
index 6fc31235f634..c749ae795cd5 100644
--- a/examples/text_labels_and_annotations/figlegend_demo.py
+++ b/examples/text_labels_and_annotations/figlegend_demo.py
@@ -28,3 +28,26 @@
plt.tight_layout()
plt.show()
+
+##############################################################################
+# Sometimes we do not want the legend to overlap the axes. If you use
+# constrained_layout you can specify "outside right upper", and
+# constrained_layout will make room for the legend.
+
+fig, axs = plt.subplots(1, 2, layout='constrained')
+
+x = np.arange(0.0, 2.0, 0.02)
+y1 = np.sin(2 * np.pi * x)
+y2 = np.exp(-x)
+l1, = axs[0].plot(x, y1)
+l2, = axs[0].plot(x, y2, marker='o')
+
+y3 = np.sin(4 * np.pi * x)
+y4 = np.exp(-2 * x)
+l3, = axs[1].plot(x, y3, color='tab:green')
+l4, = axs[1].plot(x, y4, color='tab:red', marker='^')
+
+fig.legend((l1, l2), ('Line 1', 'Line 2'), loc='upper left')
+fig.legend((l3, l4), ('Line 3', 'Line 4'), loc='outside right upper')
+
+plt.show()
diff --git a/lib/matplotlib/_constrained_layout.py b/lib/matplotlib/_constrained_layout.py
index 996603300620..9554a156f1ec 100644
--- a/lib/matplotlib/_constrained_layout.py
+++ b/lib/matplotlib/_constrained_layout.py
@@ -418,6 +418,25 @@ def make_layout_margins(layoutgrids, fig, renderer, *, w_pad=0, h_pad=0,
# pass the new margins down to the layout grid for the solution...
layoutgrids[gs].edit_outer_margin_mins(margin, ss)
+ # make margins for figure-level legends:
+ for leg in fig.legends:
+ inv_trans_fig = None
+ if leg._outside_loc and leg._bbox_to_anchor is None:
+ if inv_trans_fig is None:
+ inv_trans_fig = fig.transFigure.inverted().transform_bbox
+ bbox = inv_trans_fig(leg.get_tightbbox(renderer))
+ w = bbox.width + 2 * w_pad
+ h = bbox.height + 2 * h_pad
+ legendloc = leg._outside_loc
+ if legendloc == 'lower':
+ layoutgrids[fig].edit_margin_min('bottom', h)
+ elif legendloc == 'upper':
+ layoutgrids[fig].edit_margin_min('top', h)
+ if legendloc == 'right':
+ layoutgrids[fig].edit_margin_min('right', w)
+ elif legendloc == 'left':
+ layoutgrids[fig].edit_margin_min('left', w)
+
def make_margin_suptitles(layoutgrids, fig, renderer, *, w_pad=0, h_pad=0):
# Figure out how large the suptitle is and make the
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
index 58d95912665b..399a79e05cfe 100644
--- a/lib/matplotlib/axes/_axes.py
+++ b/lib/matplotlib/axes/_axes.py
@@ -294,7 +294,7 @@ def legend(self, *args, **kwargs):
Other Parameters
----------------
- %(_legend_kw_doc)s
+ %(_legend_kw_axes)s
See Also
--------
diff --git a/lib/matplotlib/figure.py b/lib/matplotlib/figure.py
index b006ca467be1..30e117183176 100644
--- a/lib/matplotlib/figure.py
+++ b/lib/matplotlib/figure.py
@@ -1085,7 +1085,8 @@ def legend(self, *args, **kwargs):
Other Parameters
----------------
- %(_legend_kw_doc)s
+ %(_legend_kw_figure)s
+
See Also
--------
diff --git a/lib/matplotlib/legend.py b/lib/matplotlib/legend.py
index 66182c68cb60..e9e0651066b3 100644
--- a/lib/matplotlib/legend.py
+++ b/lib/matplotlib/legend.py
@@ -94,51 +94,7 @@ def _update_bbox_to_anchor(self, loc_in_canvas):
self.legend.set_bbox_to_anchor(loc_in_bbox)
-_docstring.interpd.update(_legend_kw_doc="""
-loc : str or pair of floats, default: :rc:`legend.loc` ('best' for axes, \
-'upper right' for figures)
- The location of the legend.
-
- The strings
- ``'upper left', 'upper right', 'lower left', 'lower right'``
- place the legend at the corresponding corner of the axes/figure.
-
- The strings
- ``'upper center', 'lower center', 'center left', 'center right'``
- place the legend at the center of the corresponding edge of the
- axes/figure.
-
- The string ``'center'`` places the legend at the center of the axes/figure.
-
- The string ``'best'`` places the legend at the location, among the nine
- locations defined so far, with the minimum overlap with other drawn
- artists. This option can be quite slow for plots with large amounts of
- data; your plotting speed may benefit from providing a specific location.
-
- The location can also be a 2-tuple giving the coordinates of the lower-left
- corner of the legend in axes coordinates (in which case *bbox_to_anchor*
- will be ignored).
-
- For back-compatibility, ``'center right'`` (but no other location) can also
- be spelled ``'right'``, and each "string" locations can also be given as a
- numeric value:
-
- =============== =============
- Location String Location Code
- =============== =============
- 'best' 0
- 'upper right' 1
- 'upper left' 2
- 'lower left' 3
- 'lower right' 4
- 'right' 5
- 'center left' 6
- 'center right' 7
- 'lower center' 8
- 'upper center' 9
- 'center' 10
- =============== =============
-
+_legend_kw_doc_base = """
bbox_to_anchor : `.BboxBase`, 2-tuple, or 4-tuple of floats
Box that is used to position the legend in conjunction with *loc*.
Defaults to `axes.bbox` (if called as a method to `.Axes.legend`) or
@@ -295,7 +251,79 @@ def _update_bbox_to_anchor(self, loc_in_canvas):
draggable : bool, default: False
Whether the legend can be dragged with the mouse.
-""")
+"""
+
+_loc_doc_base = """
+loc : str or pair of floats, {0}
+ The location of the legend.
+
+ The strings
+ ``'upper left', 'upper right', 'lower left', 'lower right'``
+ place the legend at the corresponding corner of the axes/figure.
+
+ The strings
+ ``'upper center', 'lower center', 'center left', 'center right'``
+ place the legend at the center of the corresponding edge of the
+ axes/figure.
+
+ The string ``'center'`` places the legend at the center of the axes/figure.
+
+ The string ``'best'`` places the legend at the location, among the nine
+ locations defined so far, with the minimum overlap with other drawn
+ artists. This option can be quite slow for plots with large amounts of
+ data; your plotting speed may benefit from providing a specific location.
+
+ The location can also be a 2-tuple giving the coordinates of the lower-left
+ corner of the legend in axes coordinates (in which case *bbox_to_anchor*
+ will be ignored).
+
+ For back-compatibility, ``'center right'`` (but no other location) can also
+ be spelled ``'right'``, and each "string" locations can also be given as a
+ numeric value:
+
+ =============== =============
+ Location String Location Code
+ =============== =============
+ 'best' 0
+ 'upper right' 1
+ 'upper left' 2
+ 'lower left' 3
+ 'lower right' 4
+ 'right' 5
+ 'center left' 6
+ 'center right' 7
+ 'lower center' 8
+ 'upper center' 9
+ 'center' 10
+ =============== =============
+ {1}"""
+
+_legend_kw_axes_st = (_loc_doc_base.format("default: :rc:`legend.loc`", '') +
+ _legend_kw_doc_base)
+_docstring.interpd.update(_legend_kw_axes=_legend_kw_axes_st)
+
+_outside_doc = """
+ If a figure is using the constrained layout manager, the string codes
+ of the *loc* keyword argument can get better layout behaviour using the
+ prefix 'outside'. There is ambiguity at the corners, so 'outside
+ upper right' will make space for the legend above the rest of the
+ axes in the layout, and 'outside right upper' will make space on the
+ right side of the layout. In addition to the values of *loc*
+ listed above, we have 'outside right upper', 'outside right lower',
+ 'outside left upper', and 'outside left lower'. See
+ :doc:`/tutorials/intermediate/legend_guide` for more details.
+"""
+
+_legend_kw_figure_st = (_loc_doc_base.format("default: 'upper right'",
+ _outside_doc) +
+ _legend_kw_doc_base)
+_docstring.interpd.update(_legend_kw_figure=_legend_kw_figure_st)
+
+_legend_kw_both_st = (
+ _loc_doc_base.format("default: 'best' for axes, 'upper right' for figures",
+ _outside_doc) +
+ _legend_kw_doc_base)
+_docstring.interpd.update(_legend_kw_doc=_legend_kw_both_st)
class Legend(Artist):
@@ -482,13 +510,37 @@ def val_or_rc(val, rc_name):
)
self.parent = parent
+ loc0 = loc
self._loc_used_default = loc is None
if loc is None:
loc = mpl.rcParams["legend.loc"]
if not self.isaxes and loc in [0, 'best']:
loc = 'upper right'
+
+ # handle outside legends:
+ self._outside_loc = None
if isinstance(loc, str):
+ if loc.split()[0] == 'outside':
+ # strip outside:
+ loc = loc.split('outside ')[1]
+ # strip "center" at the beginning
+ self._outside_loc = loc.replace('center ', '')
+ # strip first
+ self._outside_loc = self._outside_loc.split()[0]
+ locs = loc.split()
+ if len(locs) > 1 and locs[0] in ('right', 'left'):
+ # locs doesn't accept "left upper", etc, so swap
+ if locs[0] != 'center':
+ locs = locs[::-1]
+ loc = locs[0] + ' ' + locs[1]
+ # check that loc is in acceptable strings
loc = _api.check_getitem(self.codes, loc=loc)
+
+ if self.isaxes and self._outside_loc:
+ raise ValueError(
+ f"'outside' option for loc='{loc0}' keyword argument only "
+ "works for figure legends")
+
if not self.isaxes and loc == 0:
raise ValueError(
"Automatic legend placement (loc='best') not implemented for "
diff --git a/tutorials/intermediate/legend_guide.py b/tutorials/intermediate/legend_guide.py
index 596d6df93b55..338fca72fbf1 100644
--- a/tutorials/intermediate/legend_guide.py
+++ b/tutorials/intermediate/legend_guide.py
@@ -135,7 +135,54 @@
ax_dict['bottom'].legend(bbox_to_anchor=(1.05, 1),
loc='upper left', borderaxespad=0.)
-plt.show()
+##############################################################################
+# Figure legends
+# --------------
+#
+# Sometimes it makes more sense to place a legend relative to the (sub)figure
+# rather than individual Axes. By using ``constrained_layout`` and
+# specifying "outside" at the beginning of the *loc* keyword argument,
+# the legend is drawn outside the Axes on the (sub)figure.
+
+fig, axs = plt.subplot_mosaic([['left', 'right']], layout='constrained')
+
+axs['left'].plot([1, 2, 3], label="test1")
+axs['left'].plot([3, 2, 1], label="test2")
+
+axs['right'].plot([1, 2, 3], 'C2', label="test3")
+axs['right'].plot([3, 2, 1], 'C3', label="test4")
+# Place a legend to the right of this smaller subplot.
+fig.legend(loc='outside upper right')
+
+##############################################################################
+# This accepts a slightly different grammar than the normal *loc* keyword,
+# where "outside right upper" is different from "outside upper right".
+#
+ucl = ['upper', 'center', 'lower']
+lcr = ['left', 'center', 'right']
+fig, ax = plt.subplots(figsize=(6, 4), layout='constrained', facecolor='0.7')
+
+ax.plot([1, 2], [1, 2], label='TEST')
+# Place a legend to the right of this smaller subplot.
+for loc in [
+ 'outside upper left',
+ 'outside upper center',
+ 'outside upper right',
+ 'outside lower left',
+ 'outside lower center',
+ 'outside lower right']:
+ fig.legend(loc=loc, title=loc)
+
+fig, ax = plt.subplots(figsize=(6, 4), layout='constrained', facecolor='0.7')
+ax.plot([1, 2], [1, 2], label='test')
+
+for loc in [
+ 'outside left upper',
+ 'outside right upper',
+ 'outside left lower',
+ 'outside right lower']:
+ fig.legend(loc=loc, title=loc)
+
###############################################################################
# Multiple legends on the same Axes
|
diff --git a/lib/matplotlib/tests/test_legend.py b/lib/matplotlib/tests/test_legend.py
index 56794a3428b8..a8d7fd107d8b 100644
--- a/lib/matplotlib/tests/test_legend.py
+++ b/lib/matplotlib/tests/test_legend.py
@@ -4,6 +4,7 @@
import warnings
import numpy as np
+from numpy.testing import assert_allclose
import pytest
from matplotlib.testing.decorators import check_figures_equal, image_comparison
@@ -18,7 +19,6 @@
import matplotlib.legend as mlegend
from matplotlib import rc_context
from matplotlib.font_manager import FontProperties
-from numpy.testing import assert_allclose
def test_legend_ordereddict():
@@ -486,6 +486,47 @@ def test_warn_args_kwargs(self):
"be discarded.")
+def test_figure_legend_outside():
+ todos = ['upper ' + pos for pos in ['left', 'center', 'right']]
+ todos += ['lower ' + pos for pos in ['left', 'center', 'right']]
+ todos += ['left ' + pos for pos in ['lower', 'center', 'upper']]
+ todos += ['right ' + pos for pos in ['lower', 'center', 'upper']]
+
+ upperext = [20.347556, 27.722556, 790.583, 545.499]
+ lowerext = [20.347556, 71.056556, 790.583, 588.833]
+ leftext = [151.681556, 27.722556, 790.583, 588.833]
+ rightext = [20.347556, 27.722556, 659.249, 588.833]
+ axbb = [upperext, upperext, upperext,
+ lowerext, lowerext, lowerext,
+ leftext, leftext, leftext,
+ rightext, rightext, rightext]
+
+ legbb = [[10., 555., 133., 590.], # upper left
+ [338.5, 555., 461.5, 590.], # upper center
+ [667, 555., 790., 590.], # upper right
+ [10., 10., 133., 45.], # lower left
+ [338.5, 10., 461.5, 45.], # lower center
+ [667., 10., 790., 45.], # lower right
+ [10., 10., 133., 45.], # left lower
+ [10., 282.5, 133., 317.5], # left center
+ [10., 555., 133., 590.], # left upper
+ [667, 10., 790., 45.], # right lower
+ [667., 282.5, 790., 317.5], # right center
+ [667., 555., 790., 590.]] # right upper
+
+ for nn, todo in enumerate(todos):
+ print(todo)
+ fig, axs = plt.subplots(constrained_layout=True, dpi=100)
+ axs.plot(range(10), label='Boo1')
+ leg = fig.legend(loc='outside ' + todo)
+ fig.draw_without_rendering()
+
+ assert_allclose(axs.get_window_extent().extents,
+ axbb[nn])
+ assert_allclose(leg.get_window_extent().extents,
+ legbb[nn])
+
+
@image_comparison(['legend_stackplot.png'])
def test_legend_stackplot():
"""Test legend for PolyCollection using stackplot."""
|
[
{
"path": "doc/users/next_whats_new/legend-figure-outside.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/legend-figure-outside.rst",
"metadata": "diff --git a/doc/users/next_whats_new/legend-figure-outside.rst b/doc/users/next_whats_new/legend-figure-outside.rst\nnew file mode 100644\nindex 000000000000..a78725b4e2b6\n--- /dev/null\n+++ b/doc/users/next_whats_new/legend-figure-outside.rst\n@@ -0,0 +1,8 @@\n+Figure legends can be placed outside figures using constrained_layout\n+---------------------------------------------------------------------\n+Constrained layout will make space for Figure legends if they are specified\n+by a *loc* keyword argument that starts with the string \"outside\". The\n+codes are unique from axes codes, in that \"outside upper right\" will\n+make room at the top of the figure for the legend, whereas\n+\"outside right upper\" will make room on the right-hand side of the figure.\n+See :doc:`/tutorials/intermediate/legend_guide` for details.\n"
}
] |
3.5
|
5793ebb2201bf778f08ac1d4cd0b8dd674c96053
|
[
"lib/matplotlib/tests/test_legend.py::test_legend_auto1[png]",
"lib/matplotlib/tests/test_legend.py::test_framealpha[png]",
"lib/matplotlib/tests/test_legend.py::test_alpha_rcparam[png]",
"lib/matplotlib/tests/test_legend.py::test_cross_figure_patch_legend",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_single[red]",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_markerfacecolor_iterable",
"lib/matplotlib/tests/test_legend.py::test_legend_draggable[False]",
"lib/matplotlib/tests/test_legend.py::test_rc[pdf]",
"lib/matplotlib/tests/test_legend.py::test_legend_title_fontprop_fontsize",
"lib/matplotlib/tests/test_legend.py::test_plot_single_input_multiple_label[label_array0]",
"lib/matplotlib/tests/test_legend.py::test_setting_alpha_keeps_polycollection_color",
"lib/matplotlib/tests/test_legend.py::test_not_covering_scatter_transform[png]",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_input_single_label[int]",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_three_args",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_positional_handles_only",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_markerfacecolor_short",
"lib/matplotlib/tests/test_legend.py::test_legend_label_with_leading_underscore",
"lib/matplotlib/tests/test_legend.py::test_legend_title_empty",
"lib/matplotlib/tests/test_legend.py::test_legend_alignment[right]",
"lib/matplotlib/tests/test_legend.py::test_framealpha[pdf]",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_markerfacecolor",
"lib/matplotlib/tests/test_legend.py::test_legend_expand[pdf]",
"lib/matplotlib/tests/test_legend.py::test_various_labels[pdf]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_list",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_handler_map",
"lib/matplotlib/tests/test_legend.py::test_alpha_rgba[png]",
"lib/matplotlib/tests/test_legend.py::test_fancy[pdf]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_single[none]",
"lib/matplotlib/tests/test_legend.py::test_get_set_draggable",
"lib/matplotlib/tests/test_legend.py::test_window_extent_cached_renderer",
"lib/matplotlib/tests/test_legend.py::test_subfigure_legend",
"lib/matplotlib/tests/test_legend.py::test_nanscatter",
"lib/matplotlib/tests/test_legend.py::test_empty_bar_chart_with_legend",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_single[none]",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_markeredgecolor_iterable",
"lib/matplotlib/tests/test_legend.py::test_legend_auto3[svg]",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_legend_handle_label",
"lib/matplotlib/tests/test_legend.py::test_linecollection_scaled_dashes",
"lib/matplotlib/tests/test_legend.py::test_reverse_legend_handles_and_labels",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_markeredgecolor",
"lib/matplotlib/tests/test_legend.py::test_legend_markers_from_line2d",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_kwargs_labels_only",
"lib/matplotlib/tests/test_legend.py::test_fancy[png]",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_positional_handles_labels",
"lib/matplotlib/tests/test_legend.py::test_alpha_handles",
"lib/matplotlib/tests/test_legend.py::test_multiple_keys[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_ordereddict",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_input_multiple_label[label_array2]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_single[red]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_markeredgecolor",
"lib/matplotlib/tests/test_legend.py::test_various_labels[svg]",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_legend_kw_args",
"lib/matplotlib/tests/test_legend.py::test_legend_expand[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_linecolor_iterable",
"lib/matplotlib/tests/test_legend.py::test_fancy[svg]",
"lib/matplotlib/tests/test_legend.py::test_text_nohandler_warning",
"lib/matplotlib/tests/test_legend.py::test_legend_auto2[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_linecolor",
"lib/matplotlib/tests/test_legend.py::test_legend_auto2[pdf]",
"lib/matplotlib/tests/test_legend.py::test_not_covering_scatter[png]",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_legend_label_arg",
"lib/matplotlib/tests/test_legend.py::test_rc[png]",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_legend_label_three_args_pluskw",
"lib/matplotlib/tests/test_legend.py::test_hatching[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_single[color2]",
"lib/matplotlib/tests/test_legend.py::test_warn_big_data_best_loc",
"lib/matplotlib/tests/test_legend.py::test_plot_single_input_multiple_label[label_array1]",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_warn_mixed_args_and_kwargs",
"lib/matplotlib/tests/test_legend.py::test_legend_proper_window_extent",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_parasite",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_label_incorrect_length_exception",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_markeredgecolor_cmap",
"lib/matplotlib/tests/test_legend.py::test_legend_face_edgecolor",
"lib/matplotlib/tests/test_legend.py::test_legend_auto3[pdf]",
"lib/matplotlib/tests/test_legend.py::test_legend_stackplot[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_repeatcheckok",
"lib/matplotlib/tests/test_legend.py::test_handler_numpoints",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_legend_no_args",
"lib/matplotlib/tests/test_legend.py::test_rc[svg]",
"lib/matplotlib/tests/test_legend.py::test_handlerline2d",
"lib/matplotlib/tests/test_legend.py::test_plot_single_input_multiple_label[label_array2]",
"lib/matplotlib/tests/test_legend.py::test_legend_auto5",
"lib/matplotlib/tests/test_legend.py::test_legend_auto1[pdf]",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_no_args",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_single[color2]",
"lib/matplotlib/tests/test_legend.py::test_ncol_ncols[pdf]",
"lib/matplotlib/tests/test_legend.py::test_legend_auto4",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_markfacecolor_cmap",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_input_multiple_label[label_array1]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_markerfacecolor",
"lib/matplotlib/tests/test_legend.py::test_no_warn_big_data_when_loc_specified",
"lib/matplotlib/tests/test_legend.py::test_framealpha[svg]",
"lib/matplotlib/tests/test_legend.py::test_legend_expand[svg]",
"lib/matplotlib/tests/test_legend.py::test_legend_auto3[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_markeredgecolor",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_kwargs_handles_only",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_kwargs_handles_labels",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_markeredgecolor_short",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_rcparam_markerfacecolor",
"lib/matplotlib/tests/test_legend.py::test_legend_draggable[True]",
"lib/matplotlib/tests/test_legend.py::test_legend_auto1[svg]",
"lib/matplotlib/tests/test_legend.py::test_legend_set_alignment[left]",
"lib/matplotlib/tests/test_legend.py::test_legend_set_alignment[right]",
"lib/matplotlib/tests/test_legend.py::test_legend_set_alignment[center]",
"lib/matplotlib/tests/test_legend.py::test_ncol_ncols[png]",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_legend_label_three_args",
"lib/matplotlib/tests/test_legend.py::test_labels_first[png]",
"lib/matplotlib/tests/test_legend.py::test_hatching[svg]",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_input_single_label[1]",
"lib/matplotlib/tests/test_legend.py::test_legend_auto2[svg]",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_linecolor_cmap",
"lib/matplotlib/tests/test_legend.py::test_legend_text_axes",
"lib/matplotlib/tests/test_legend.py::test_legend_remove",
"lib/matplotlib/tests/test_legend.py::TestLegendFunction::test_legend_positional_labels_only",
"lib/matplotlib/tests/test_legend.py::test_legend_pathcollection_labelcolor_linecolor",
"lib/matplotlib/tests/test_legend.py::test_reverse_legend_display[png]",
"lib/matplotlib/tests/test_legend.py::test_hatching[pdf]",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_input_single_label[one]",
"lib/matplotlib/tests/test_legend.py::test_various_labels[png]",
"lib/matplotlib/tests/test_legend.py::test_legend_labelcolor_linecolor",
"lib/matplotlib/tests/test_legend.py::test_shadow_framealpha",
"lib/matplotlib/tests/test_legend.py::test_legend_alignment[center]",
"lib/matplotlib/tests/test_legend.py::test_plot_multiple_input_multiple_label[label_array0]",
"lib/matplotlib/tests/test_legend.py::TestLegendFigureFunction::test_warn_args_kwargs",
"lib/matplotlib/tests/test_legend.py::test_ncol_ncols[svg]",
"lib/matplotlib/tests/test_legend.py::test_legend_alignment[left]"
] |
[
"lib/matplotlib/tests/test_legend.py::test_figure_legend_outside"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/users/next_whats_new/legend-figure-outside.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/legend-figure-outside.rst",
"metadata": "diff --git a/doc/users/next_whats_new/legend-figure-outside.rst b/doc/users/next_whats_new/legend-figure-outside.rst\nnew file mode 100644\nindex 000000000000..a78725b4e2b6\n--- /dev/null\n+++ b/doc/users/next_whats_new/legend-figure-outside.rst\n@@ -0,0 +1,8 @@\n+Figure legends can be placed outside figures using constrained_layout\n+---------------------------------------------------------------------\n+Constrained layout will make space for Figure legends if they are specified\n+by a *loc* keyword argument that starts with the string \"outside\". The\n+codes are unique from axes codes, in that \"outside upper right\" will\n+make room at the top of the figure for the legend, whereas\n+\"outside right upper\" will make room on the right-hand side of the figure.\n+See :doc:`/tutorials/intermediate/legend_guide` for details.\n"
}
] |
diff --git a/doc/users/next_whats_new/legend-figure-outside.rst b/doc/users/next_whats_new/legend-figure-outside.rst
new file mode 100644
index 000000000000..a78725b4e2b6
--- /dev/null
+++ b/doc/users/next_whats_new/legend-figure-outside.rst
@@ -0,0 +1,8 @@
+Figure legends can be placed outside figures using constrained_layout
+---------------------------------------------------------------------
+Constrained layout will make space for Figure legends if they are specified
+by a *loc* keyword argument that starts with the string "outside". The
+codes are unique from axes codes, in that "outside upper right" will
+make room at the top of the figure for the legend, whereas
+"outside right upper" will make room on the right-hand side of the figure.
+See :doc:`/tutorials/intermediate/legend_guide` for details.
|
matplotlib/matplotlib
|
matplotlib__matplotlib-18715
|
https://github.com/matplotlib/matplotlib/pull/18715
|
diff --git a/doc/users/next_whats_new/auto_minor_tick.rst b/doc/users/next_whats_new/auto_minor_tick.rst
new file mode 100644
index 000000000000..02db8f6beb38
--- /dev/null
+++ b/doc/users/next_whats_new/auto_minor_tick.rst
@@ -0,0 +1,5 @@
+rcParams for ``AutoMinorLocator`` divisions
+-------------------------------------------
+The rcParams :rc:`xtick.minor.ndivs` and :rc:`ytick.minor.ndivs` have been
+added to enable setting the default number of divisions; if set to ``auto``,
+the number of divisions will be chosen by the distance between major ticks.
diff --git a/lib/matplotlib/mpl-data/matplotlibrc b/lib/matplotlib/mpl-data/matplotlibrc
index 578777167d6c..86f70a23dacd 100644
--- a/lib/matplotlib/mpl-data/matplotlibrc
+++ b/lib/matplotlib/mpl-data/matplotlibrc
@@ -489,6 +489,7 @@
#xtick.major.bottom: True # draw x axis bottom major ticks
#xtick.minor.top: True # draw x axis top minor ticks
#xtick.minor.bottom: True # draw x axis bottom minor ticks
+#xtick.minor.ndivs: auto # number of minor ticks between the major ticks on x-axis
#xtick.alignment: center # alignment of xticks
#ytick.left: True # draw ticks on the left side
@@ -510,6 +511,7 @@
#ytick.major.right: True # draw y axis right major ticks
#ytick.minor.left: True # draw y axis left minor ticks
#ytick.minor.right: True # draw y axis right minor ticks
+#ytick.minor.ndivs: auto # number of minor ticks between the major ticks on y-axis
#ytick.alignment: center_baseline # alignment of yticks
diff --git a/lib/matplotlib/rcsetup.py b/lib/matplotlib/rcsetup.py
index b27ac35bcb4d..663ff4b70536 100644
--- a/lib/matplotlib/rcsetup.py
+++ b/lib/matplotlib/rcsetup.py
@@ -568,6 +568,14 @@ def _validate_greaterequal0_lessequal1(s):
raise RuntimeError(f'Value must be >=0 and <=1; got {s}')
+def _validate_int_greaterequal0(s):
+ s = validate_int(s)
+ if s >= 0:
+ return s
+ else:
+ raise RuntimeError(f'Value must be >=0; got {s}')
+
+
def validate_hatch(s):
r"""
Validate a hatch pattern.
@@ -587,6 +595,24 @@ def validate_hatch(s):
validate_dashlist = _listify_validator(validate_floatlist)
+def _validate_minor_tick_ndivs(n):
+ """
+ Validate ndiv parameter related to the minor ticks.
+ It controls the number of minor ticks to be placed between
+ two major ticks.
+ """
+
+ if isinstance(n, str) and n.lower() == 'auto':
+ return n
+ try:
+ n = _validate_int_greaterequal0(n)
+ return n
+ except (RuntimeError, ValueError):
+ pass
+
+ raise ValueError("'tick.minor.ndivs' must be 'auto' or non-negative int")
+
+
_prop_validators = {
'color': _listify_validator(validate_color_for_prop_cycle,
allow_stringlist=True),
@@ -1093,6 +1119,8 @@ def _convert_validator_spec(key, conv):
"xtick.minor.bottom": validate_bool, # draw bottom minor xticks
"xtick.major.top": validate_bool, # draw top major xticks
"xtick.major.bottom": validate_bool, # draw bottom major xticks
+ # number of minor xticks
+ "xtick.minor.ndivs": _validate_minor_tick_ndivs,
"xtick.labelsize": validate_fontsize, # fontsize of xtick labels
"xtick.direction": ["out", "in", "inout"], # direction of xticks
"xtick.alignment": ["center", "right", "left"],
@@ -1114,6 +1142,8 @@ def _convert_validator_spec(key, conv):
"ytick.minor.right": validate_bool, # draw right minor yticks
"ytick.major.left": validate_bool, # draw left major yticks
"ytick.major.right": validate_bool, # draw right major yticks
+ # number of minor yticks
+ "ytick.minor.ndivs": _validate_minor_tick_ndivs,
"ytick.labelsize": validate_fontsize, # fontsize of ytick labels
"ytick.direction": ["out", "in", "inout"], # direction of yticks
"ytick.alignment": [
diff --git a/lib/matplotlib/ticker.py b/lib/matplotlib/ticker.py
index a29343029f60..bf059567f5fe 100644
--- a/lib/matplotlib/ticker.py
+++ b/lib/matplotlib/ticker.py
@@ -2869,7 +2869,11 @@ def __init__(self, n=None):
major ticks; e.g., n=2 will place a single minor tick midway
between major ticks.
- If *n* is omitted or None, it will be set to 5 or 4.
+ If *n* is omitted or None, the value stored in rcParams will be used.
+ In case *n* is set to 'auto', it will be set to 4 or 5. If the distance
+ between the major ticks equals 1, 2.5, 5 or 10 it can be perfectly
+ divided in 5 equidistant sub-intervals with a length multiple of
+ 0.05. Otherwise it is divided in 4 sub-intervals.
"""
self.ndivs = n
@@ -2892,6 +2896,14 @@ def __call__(self):
if self.ndivs is None:
+ if self.axis.axis_name == 'y':
+ self.ndivs = mpl.rcParams['ytick.minor.ndivs']
+ else:
+ # for x and z axis
+ self.ndivs = mpl.rcParams['xtick.minor.ndivs']
+
+ if self.ndivs == 'auto':
+
majorstep_no_exponent = 10 ** (np.log10(majorstep) % 1)
if np.isclose(majorstep_no_exponent, [1.0, 2.5, 5.0, 10.0]).any():
|
diff --git a/lib/matplotlib/tests/test_ticker.py b/lib/matplotlib/tests/test_ticker.py
index 15981c4c9047..3d38df575f09 100644
--- a/lib/matplotlib/tests/test_ticker.py
+++ b/lib/matplotlib/tests/test_ticker.py
@@ -211,6 +211,60 @@ def test_additional(self, lim, ref):
assert_almost_equal(ax.yaxis.get_ticklocs(minor=True), ref)
+ @pytest.mark.parametrize('use_rcparam', [False, True])
+ @pytest.mark.parametrize(
+ 'lim, ref', [
+ ((0, 1.39),
+ [0.05, 0.1, 0.15, 0.25, 0.3, 0.35, 0.45, 0.5, 0.55, 0.65, 0.7,
+ 0.75, 0.85, 0.9, 0.95, 1.05, 1.1, 1.15, 1.25, 1.3, 1.35]),
+ ((0, 0.139),
+ [0.005, 0.01, 0.015, 0.025, 0.03, 0.035, 0.045, 0.05, 0.055,
+ 0.065, 0.07, 0.075, 0.085, 0.09, 0.095, 0.105, 0.11, 0.115,
+ 0.125, 0.13, 0.135]),
+ ])
+ def test_number_of_minor_ticks_auto(self, lim, ref, use_rcparam):
+ if use_rcparam:
+ context = {'xtick.minor.ndivs': 'auto', 'ytick.minor.ndivs': 'auto'}
+ kwargs = {}
+ else:
+ context = {}
+ kwargs = {'n': 'auto'}
+
+ with mpl.rc_context(context):
+ fig, ax = plt.subplots()
+ ax.set_xlim(*lim)
+ ax.set_ylim(*lim)
+ ax.xaxis.set_minor_locator(mticker.AutoMinorLocator(**kwargs))
+ ax.yaxis.set_minor_locator(mticker.AutoMinorLocator(**kwargs))
+ assert_almost_equal(ax.xaxis.get_ticklocs(minor=True), ref)
+ assert_almost_equal(ax.yaxis.get_ticklocs(minor=True), ref)
+
+ @pytest.mark.parametrize('use_rcparam', [False, True])
+ @pytest.mark.parametrize(
+ 'n, lim, ref', [
+ (2, (0, 4), [0.5, 1.5, 2.5, 3.5]),
+ (4, (0, 2), [0.25, 0.5, 0.75, 1.25, 1.5, 1.75]),
+ (10, (0, 1), [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]),
+ ])
+ def test_number_of_minor_ticks_int(self, n, lim, ref, use_rcparam):
+ if use_rcparam:
+ context = {'xtick.minor.ndivs': n, 'ytick.minor.ndivs': n}
+ kwargs = {}
+ else:
+ context = {}
+ kwargs = {'n': n}
+
+ with mpl.rc_context(context):
+ fig, ax = plt.subplots()
+ ax.set_xlim(*lim)
+ ax.set_ylim(*lim)
+ ax.xaxis.set_major_locator(mticker.MultipleLocator(1))
+ ax.xaxis.set_minor_locator(mticker.AutoMinorLocator(**kwargs))
+ ax.yaxis.set_major_locator(mticker.MultipleLocator(1))
+ ax.yaxis.set_minor_locator(mticker.AutoMinorLocator(**kwargs))
+ assert_almost_equal(ax.xaxis.get_ticklocs(minor=True), ref)
+ assert_almost_equal(ax.yaxis.get_ticklocs(minor=True), ref)
+
class TestLogLocator:
def test_basic(self):
|
[
{
"path": "doc/users/next_whats_new/auto_minor_tick.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/auto_minor_tick.rst",
"metadata": "diff --git a/doc/users/next_whats_new/auto_minor_tick.rst b/doc/users/next_whats_new/auto_minor_tick.rst\nnew file mode 100644\nindex 000000000000..02db8f6beb38\n--- /dev/null\n+++ b/doc/users/next_whats_new/auto_minor_tick.rst\n@@ -0,0 +1,5 @@\n+rcParams for ``AutoMinorLocator`` divisions\n+-------------------------------------------\n+The rcParams :rc:`xtick.minor.ndivs` and :rc:`ytick.minor.ndivs` have been\n+added to enable setting the default number of divisions; if set to ``auto``,\n+the number of divisions will be chosen by the distance between major ticks.\n"
}
] |
3.7
|
b61bb0b6392c23d38cd45c658bfcd44df145830d
|
[
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[1000-100-1000]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_offset_value[-0.492-0.492-0]",
"lib/matplotlib/tests/test_ticker.py::TestPercentFormatter::test_basic[autodecimal, x<100%, display_range=8.4 (autodecimal test 2)]",
"lib/matplotlib/tests/test_ticker.py::TestMultipleLocator::test_view_limits_round_numbers",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.001-0.015-0.001]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_cursor_dummy_axis[0.0123-0.012]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_invalid[-0.1]",
"lib/matplotlib/tests/test_ticker.py::TestEngFormatter::test_params[True-1001-expected21]",
"lib/matplotlib/tests/test_ticker.py::TestAsinhLocator::test_linear_values",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_minor[lims6-expected_low_ticks6]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_format_data[0.1-1e-1]",
"lib/matplotlib/tests/test_ticker.py::TestFormatStrFormatter::test_basic",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_format_data_short[253]",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_nonsingular_ok[lims0]",
"lib/matplotlib/tests/test_ticker.py::TestLogLocator::test_tick_values_not_empty",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterMathtext::test_min_exponent[3-1000.0-$\\\\mathdefault{10^{3}}$]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.003141592654-100-0]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_variablelength[0.02005753653785041]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.003141592654-0.001-3.142e-3]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.1-0.001-1e-1]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[1000-0.015-1000]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_basic[0.001]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.01-0.001-1e-2]",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_nonsingular_ok[lims8]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_invalid[-1]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterMathtext::test_min_exponent[0-1-$\\\\mathdefault{10^{0}}$]",
"lib/matplotlib/tests/test_ticker.py::TestEngFormatter::test_params[False--1234.56789-expected0]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterExponent::test_basic[2.718281828459045-False-50-locs2-positions2-expected2]",
"lib/matplotlib/tests/test_ticker.py::TestEngFormatter::test_params[True--999.9999-expected19]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.3141592654-0.015-0.314]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_variablelength[0.9956983447069072]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_minor_vs_major[False-lims3-cases3]",
"lib/matplotlib/tests/test_ticker.py::TestPercentFormatter::test_latex[True-True-50\\\\{t}%]",
"lib/matplotlib/tests/test_ticker.py::TestMaxNLocator::test_basic[0.001-0.0001-expected1]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[1000-0.001-1000]",
"lib/matplotlib/tests/test_ticker.py::test_small_range_loglocator[9]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterExponent::test_basic[5.0-False-50-locs2-positions2-expected2]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterExponent::test_basic[5.0-False-10-locs1-positions1-expected1]",
"lib/matplotlib/tests/test_ticker.py::TestPercentFormatter::test_basic[decimals=0, x>100%]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.3141592654-100-0.3]",
"lib/matplotlib/tests/test_ticker.py::TestPercentFormatter::test_basic[autodecimal, x<-100%, display_range=1e-6 (tiny display range)]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterMathtext::test_min_exponent[3-100.0-$\\\\mathdefault{100}$]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[1-0.015-1]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterSciNotation::test_basic[10-500000-$\\\\mathdefault{5\\\\times10^{5}}$]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_format_data[0.11-1.1e-1]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterExponent::test_basic[3.141592653589793-False-10-locs1-positions1-expected1]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_basic[0.1]",
"lib/matplotlib/tests/test_ticker.py::TestFixedLocator::test_set_params",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_nonsingular_ok[lims3]",
"lib/matplotlib/tests/test_ticker.py::TestPercentFormatter::test_basic[autodecimal, x>100%, display_range=6 (custom xmax test)]",
"lib/matplotlib/tests/test_ticker.py::TestAsinhLocator::test_symmetrizing",
"lib/matplotlib/tests/test_ticker.py::TestSymmetricalLogLocator::test_set_params",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_cursor_dummy_axis[0.0-0.000]",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_nonsingular_ok[lims11]",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_nonsingular_ok[lims26]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[100-100-100]",
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"lib/matplotlib/tests/test_ticker.py::TestLogFormatterExponent::test_basic[3.141592653589793-True-4-locs0-positions0-expected0]",
"lib/matplotlib/tests/test_ticker.py::TestLogLocator::test_switch_to_autolocator",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_basic_major[lims1-expected_low_ticks1]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_logit_deformater[STUFF0.41OTHERSTUFF-0.41]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_basic[1e-07]",
"lib/matplotlib/tests/test_ticker.py::TestEngFormatter::test_params[True--0.00123456789-expected7]",
"lib/matplotlib/tests/test_ticker.py::TestPercentFormatter::test_basic[autodecimal, x<100%, display_range=1]",
"lib/matplotlib/tests/test_ticker.py::TestAutoMinorLocator::test_basic",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.1-0.015-0.1]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_offset_value[3789.12-3783.1-3780]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.03141592654-0.5-0.031]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_basic[0.999999999]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterMathtext::test_min_exponent[0-100.0-$\\\\mathdefault{10^{2}}$]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[3.141592654-1000000.0-3.1]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[100-1000000.0-100]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_sublabel",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.01-5-0.01]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.0003141592654-0.015-0]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.0001-1000000.0-1e-4]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_scilimits[True-scilimits8-lim8-6-False]",
"lib/matplotlib/tests/test_ticker.py::TestLogLocator::test_tick_values_correct",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_scilimits[True-scilimits2-lim2-0-False]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_LogFormatter_call[1000]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.0003141592654-5-0]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterSciNotation::test_basic[10-100000-$\\\\mathdefault{10^{5}}$]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.0001-100-0]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_variablelength[0.0009110511944006454]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_empty_locs",
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"lib/matplotlib/tests/test_ticker.py::TestMultipleLocator::test_set_params",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_scilimits[True-scilimits4-lim4-2-False]",
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"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_variablelength[0.6852009766653157]",
"lib/matplotlib/tests/test_ticker.py::TestPercentFormatter::test_latex[True-False-50\\\\{t}%]",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_maxn_major[lims2]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_basic[0.9999]",
"lib/matplotlib/tests/test_ticker.py::TestEngFormatter::test_params[True-1.23456789-expected15]",
"lib/matplotlib/tests/test_ticker.py::TestAsinhLocator::test_base_rounding",
"lib/matplotlib/tests/test_ticker.py::TestAutoMinorLocator::test_first_and_last_minorticks",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_nbins_major[lims3]",
"lib/matplotlib/tests/test_ticker.py::TestEngFormatter::test_params[True-0.123456789-expected12]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[3.141592654e-05-0.5-0]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterExponent::test_basic[10.0-False-10-locs1-positions1-expected1]",
"lib/matplotlib/tests/test_ticker.py::test_set_offset_string[formatter0]",
"lib/matplotlib/tests/test_ticker.py::test_minorticks_rc",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_use_offset[True]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[10-1000000.0-10]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_offset_value[123-189-0]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.03141592654-5-0.03]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_minor_vs_major[True-lims2-cases2]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_variablelength[0.3147990233346844]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterExponent::test_basic[2.718281828459045-False-10-locs1-positions1-expected1]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.0003141592654-0.001-3.142e-4]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[1e-05-5-0]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_LogFormatter_call_tiny[1e-323]",
"lib/matplotlib/tests/test_ticker.py::TestAsinhLocator::test_near_zero",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[100-0.015-100]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterExponent::test_basic[2.0-False-10-locs1-positions1-expected1]",
"lib/matplotlib/tests/test_ticker.py::TestPercentFormatter::test_latex[False-False-50\\\\{t}%]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_variablelength[0.0043016552930929]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.001-0.001-1e-3]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_basic[0.9]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[10-0.001-10]",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_nonsingular_ok[lims29]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.0001-0.015-0]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterSciNotation::test_basic[10-1e-05-$\\\\mathdefault{10^{-5}}$]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[10000-5-10000]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterExponent::test_blank",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[10000-1000000.0-1e4]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[31.41592654-100-31.4]",
"lib/matplotlib/tests/test_ticker.py::TestEngFormatter::test_params[False--1.23456789-expected2]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_basic[1e-09]",
"lib/matplotlib/tests/test_ticker.py::TestAutoMinorLocator::test_low_number_of_majorticks[0-0]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[314.1592654-0.015-314.159]",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_basic_major[lims4-expected_low_ticks4]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_minor_vs_major[True-lims1-cases1]",
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"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_logit_deformater[STUFF1.41\\\\cdot10^{-2}OTHERSTUFF-0.0141]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_basic[0.999]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.001-5-0]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_offset_value[9.99-10.01-10]",
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"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_offset_value[12331.4-12350.5-12300]",
"lib/matplotlib/tests/test_ticker.py::TestEngFormatter::test_params[False--0.123456789-expected4]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[3141.592654-5-3141.59]",
"lib/matplotlib/tests/test_ticker.py::TestAutoMinorLocator::test_additional[lim3-ref3]",
"lib/matplotlib/tests/test_ticker.py::TestPercentFormatter::test_basic[Empty percent symbol]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.0003141592654-0.5-0]",
"lib/matplotlib/tests/test_ticker.py::test_majlocator_type",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.1-0.5-0.1]",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_minor[lims2-expected_low_ticks2]",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_nbins_major[lims5]",
"lib/matplotlib/tests/test_ticker.py::test_bad_locator_subs[sub0]",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_nbins_major[lims9]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.1-5-0.1]",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_nbins_major[lims2]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.0001-0.001-1e-4]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.3141592654-1000000.0-3.1e-1]",
"lib/matplotlib/tests/test_ticker.py::TestPercentFormatter::test_basic[None as percent symbol]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[1000-0.5-1000]",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_minor[lims1-expected_low_ticks1]",
"lib/matplotlib/tests/test_ticker.py::TestPercentFormatter::test_basic[decimals=1, x>100%]",
"lib/matplotlib/tests/test_ticker.py::test_minlocator_type",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_offset_value[45124.3-45831.75-45000]",
"lib/matplotlib/tests/test_ticker.py::TestLogLocator::test_multiple_shared_axes",
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"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[314.1592654-0.001-3.142e2]",
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"lib/matplotlib/tests/test_ticker.py::TestEngFormatter::test_params[True-0.1-expected13]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_offset_value[-100000.5--99990.5--100000]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_cursor_dummy_axis[12.3-12.300]",
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"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[1e-05-0.001-1e-5]",
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"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_offset_value[99.99-100.01-100]",
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"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_nonsingular_ok[lims7]",
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"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_nonsingular_ok[lims14]",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_nonsingular_ok[lims1]",
"lib/matplotlib/tests/test_ticker.py::TestAutoMinorLocator::test_additional[lim2-ref2]",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_nonsingular_nok[0.39999999999999997]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_cursor_precision[1.23-1.230]",
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"lib/matplotlib/tests/test_ticker.py::TestMaxNLocator::test_basic[-1000000000000000.0-1000000000000000.0-expected2]",
"lib/matplotlib/tests/test_ticker.py::TestAutoMinorLocator::test_additional[lim5-ref5]",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_nonsingular_nok[0.16]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_offset_value[12592.82-12591.43-12590]",
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"lib/matplotlib/tests/test_ticker.py::test_remove_overlap[True-6]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_offset_value[9.0-12.0-0]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_offset_value[1-1-1]",
"lib/matplotlib/tests/test_ticker.py::TestLogLocator::test_polar_axes",
"lib/matplotlib/tests/test_ticker.py::TestLogLocator::test_basic",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[31415.92654-0.001-3.142e4]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[1e-05-1000000.0-1e-5]",
"lib/matplotlib/tests/test_ticker.py::TestLinearLocator::test_set_params",
"lib/matplotlib/tests/test_ticker.py::TestAutoMinorLocator::test_number_of_minor_ticks[2-4]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterSciNotation::test_basic[2-38.4-$\\\\mathdefault{1.2\\\\times2^{5}}$]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[3.141592654e-05-100-0]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_scilimits[True-scilimits3-lim3-2-False]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_offset_value[-12349--12341--12340]",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_nonsingular_ok[lims24]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_offset_value[99999.5-100010.5-100000]",
"lib/matplotlib/tests/test_ticker.py::TestEngFormatter::test_params[True--0.0-expected8]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[3.141592654-0.5-3.142]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.001-0.5-0.001]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatterExponent::test_basic[10.0-True-4-locs0-positions0-expected0]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_LogFormatter_call[1]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.03141592654-100-0]",
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"lib/matplotlib/tests/test_ticker.py::TestMaxNLocator::test_integer[-0.1-0.95-None-expected1]",
"lib/matplotlib/tests/test_ticker.py::TestIndexLocator::test_set_params",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_nbins_major[lims7]",
"lib/matplotlib/tests/test_ticker.py::TestAutoMinorLocator::test_low_number_of_majorticks[1-0]",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_minor_attr",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[100000-1000000.0-1e5]",
"lib/matplotlib/tests/test_ticker.py::TestAutoMinorLocator::test_number_of_minor_ticks[5-5]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[1e-05-100-0]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_variablelength[0.9799424634621495]",
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"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[31415.92654-100-31415.9]",
"lib/matplotlib/tests/test_ticker.py::TestEngFormatter::test_params[True-999.9-expected16]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_LogFormatter_call_tiny[2e-323]",
"lib/matplotlib/tests/test_ticker.py::TestEngFormatter::test_params[True--1.23456789-expected3]",
"lib/matplotlib/tests/test_ticker.py::TestLogitLocator::test_nonsingular_ok[lims9]",
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"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[314.1592654-0.5-314.159]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_LogFormatter_call_tiny[1.1e-322]",
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"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_offset_value[0.000721-0.0007243-0.00072]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_cursor_dummy_axis[0.123-0.123]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_basic[1e-06]",
"lib/matplotlib/tests/test_ticker.py::TestPercentFormatter::test_latex[False-True-50\\\\\\\\\\\\{t\\\\}\\\\%]",
"lib/matplotlib/tests/test_ticker.py::TestStrMethodFormatter::test_basic[{x:03d}-{pos:02d}-input1-002-01]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.003141592654-1000000.0-3.1e-3]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_LogFormatter_call_tiny[1e-322]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[31415.92654-0.015-31415.927]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_invalid[1.1]",
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"lib/matplotlib/tests/test_ticker.py::TestLogFormatterSciNotation::test_basic[2-1-$\\\\mathdefault{2^{0}}$]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[0.01-0.5-0.01]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[100000-5-100000]",
"lib/matplotlib/tests/test_ticker.py::TestLogitFormatter::test_basic[0.0001]",
"lib/matplotlib/tests/test_ticker.py::TestLinearLocator::test_basic",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_offset_value[-1234001--1233999--1234000]",
"lib/matplotlib/tests/test_ticker.py::TestEngFormatter::test_params[True-987654.321-expected23]",
"lib/matplotlib/tests/test_ticker.py::TestScalarFormatter::test_offset_value[5.99-6.01-6]",
"lib/matplotlib/tests/test_ticker.py::TestLogFormatter::test_pprint[100000-0.015-100000]"
] |
[
"lib/matplotlib/tests/test_ticker.py::TestAutoMinorLocator::test_number_of_minor_ticks_int[2-lim0-ref0-True]",
"lib/matplotlib/tests/test_ticker.py::TestAutoMinorLocator::test_number_of_minor_ticks_auto[lim1-ref1-False]",
"lib/matplotlib/tests/test_ticker.py::TestAutoMinorLocator::test_number_of_minor_ticks_auto[lim1-ref1-True]",
"lib/matplotlib/tests/test_ticker.py::TestAutoMinorLocator::test_number_of_minor_ticks_int[4-lim1-ref1-True]",
"lib/matplotlib/tests/test_ticker.py::TestAutoMinorLocator::test_number_of_minor_ticks_auto[lim0-ref0-True]",
"lib/matplotlib/tests/test_ticker.py::TestAutoMinorLocator::test_number_of_minor_ticks_int[10-lim2-ref2-True]",
"lib/matplotlib/tests/test_ticker.py::TestAutoMinorLocator::test_number_of_minor_ticks_auto[lim0-ref0-False]"
] |
{
"header": "If completing this task requires creating new files, classes, fields, or error messages, you may consider using the following suggested entity names:",
"data": []
}
|
[
{
"path": "doc/users/next_whats_new/auto_minor_tick.rst",
"old_path": "/dev/null",
"new_path": "b/doc/users/next_whats_new/auto_minor_tick.rst",
"metadata": "diff --git a/doc/users/next_whats_new/auto_minor_tick.rst b/doc/users/next_whats_new/auto_minor_tick.rst\nnew file mode 100644\nindex 000000000000..02db8f6beb38\n--- /dev/null\n+++ b/doc/users/next_whats_new/auto_minor_tick.rst\n@@ -0,0 +1,5 @@\n+rcParams for ``AutoMinorLocator`` divisions\n+-------------------------------------------\n+The rcParams :rc:`xtick.minor.ndivs` and :rc:`ytick.minor.ndivs` have been\n+added to enable setting the default number of divisions; if set to ``auto``,\n+the number of divisions will be chosen by the distance between major ticks.\n"
}
] |
diff --git a/doc/users/next_whats_new/auto_minor_tick.rst b/doc/users/next_whats_new/auto_minor_tick.rst
new file mode 100644
index 000000000000..02db8f6beb38
--- /dev/null
+++ b/doc/users/next_whats_new/auto_minor_tick.rst
@@ -0,0 +1,5 @@
+rcParams for ``AutoMinorLocator`` divisions
+-------------------------------------------
+The rcParams :rc:`xtick.minor.ndivs` and :rc:`ytick.minor.ndivs` have been
+added to enable setting the default number of divisions; if set to ``auto``,
+the number of divisions will be chosen by the distance between major ticks.
|
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