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int64 0
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| repo
stringlengths 32
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| hash
stringlengths 40
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| diff
stringlengths 113
1.17k
| old_path
stringlengths 5
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| rewrite
stringlengths 34
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| initial_state
stringlengths 75
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| final_state
stringlengths 76
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|---|---|---|---|---|---|---|---|
400 |
https://:@github.com/dmlc/keras.git
|
e2e281e14f619d9ade61c46567e2c599db070f16
|
@@ -23,7 +23,7 @@ def test_unitnorm_constraint():
lookup.compile(loss='binary_crossentropy', optimizer='sgd',
class_mode='binary')
lookup.train_on_batch(X1, np.array([[1], [0]], dtype='int32'))
- norm = np.linalg.norm(K.get_value(lookup.params[0]), axis=1)
+ norm = np.linalg.norm(K.get_value(lookup.params[0]), axis=0)
assert_allclose(norm, np.ones_like(norm).astype('float32'), rtol=1e-05)
|
tests/keras/layers/test_embeddings.py
|
ReplaceText(target='0' @(26,62)->(26,63))
|
def test_unitnorm_constraint():
lookup.compile(loss='binary_crossentropy', optimizer='sgd',
class_mode='binary')
lookup.train_on_batch(X1, np.array([[1], [0]], dtype='int32'))
norm = np.linalg.norm(K.get_value(lookup.params[0]), axis=1)
assert_allclose(norm, np.ones_like(norm).astype('float32'), rtol=1e-05)
|
def test_unitnorm_constraint():
lookup.compile(loss='binary_crossentropy', optimizer='sgd',
class_mode='binary')
lookup.train_on_batch(X1, np.array([[1], [0]], dtype='int32'))
norm = np.linalg.norm(K.get_value(lookup.params[0]), axis=0)
assert_allclose(norm, np.ones_like(norm).astype('float32'), rtol=1e-05)
|
401 |
https://:@github.com/dmlc/keras.git
|
e2e281e14f619d9ade61c46567e2c599db070f16
|
@@ -54,7 +54,7 @@ def test_identity_oddballs():
def test_unitnorm():
unitnorm_instance = constraints.unitnorm()
normalized = unitnorm_instance(K.variable(example_array))
- norm_of_normalized = np.sqrt(np.sum(K.eval(normalized)**2, axis=1))
+ norm_of_normalized = np.sqrt(np.sum(K.eval(normalized)**2, axis=0))
# in the unit norm constraint, it should be equal to 1.
difference = norm_of_normalized - 1.
largest_difference = np.max(np.abs(difference))
|
tests/keras/test_constraints.py
|
ReplaceText(target='0' @(57,68)->(57,69))
|
def test_identity_oddballs():
def test_unitnorm():
unitnorm_instance = constraints.unitnorm()
normalized = unitnorm_instance(K.variable(example_array))
norm_of_normalized = np.sqrt(np.sum(K.eval(normalized)**2, axis=1))
# in the unit norm constraint, it should be equal to 1.
difference = norm_of_normalized - 1.
largest_difference = np.max(np.abs(difference))
|
def test_identity_oddballs():
def test_unitnorm():
unitnorm_instance = constraints.unitnorm()
normalized = unitnorm_instance(K.variable(example_array))
norm_of_normalized = np.sqrt(np.sum(K.eval(normalized)**2, axis=0))
# in the unit norm constraint, it should be equal to 1.
difference = norm_of_normalized - 1.
largest_difference = np.max(np.abs(difference))
|
402 |
https://:@github.com/dmlc/keras.git
|
f4af11c7300816ca28b6b707fdf7d64b00430074
|
@@ -52,7 +52,7 @@ def pad_sequences(sequences, maxlen=None, dtype='int32', padding='pre', truncati
elif truncating == 'post':
trunc = s[:maxlen]
else:
- raise ValueError("Truncating type '%s' not understood" % padding)
+ raise ValueError("Truncating type '%s' not understood" % truncating)
# check `trunc` has expected shape
trunc = np.asarray(trunc, dtype=dtype)
|
keras/preprocessing/sequence.py
|
ReplaceText(target='truncating' @(55,69)->(55,76))
|
def pad_sequences(sequences, maxlen=None, dtype='int32', padding='pre', truncati
elif truncating == 'post':
trunc = s[:maxlen]
else:
raise ValueError("Truncating type '%s' not understood" % padding)
# check `trunc` has expected shape
trunc = np.asarray(trunc, dtype=dtype)
|
def pad_sequences(sequences, maxlen=None, dtype='int32', padding='pre', truncati
elif truncating == 'post':
trunc = s[:maxlen]
else:
raise ValueError("Truncating type '%s' not understood" % truncating)
# check `trunc` has expected shape
trunc = np.asarray(trunc, dtype=dtype)
|
403 |
https://:@github.com/dmlc/keras.git
|
b61235b77f87288d62ddd8ce4aae88b76babf887
|
@@ -153,7 +153,7 @@ def check_array_lengths(X, Y, W):
raise Exception('All input arrays (x) should have '
'the same number of samples.')
set_y = set(y_lengths)
- if len(set_x) != 1:
+ if len(set_y) != 1:
raise Exception('All target arrays (y) should have '
'the same number of samples.')
set_w = set(w_lengths)
|
keras/engine/training.py
|
ReplaceText(target='set_y' @(156,11)->(156,16))
|
def check_array_lengths(X, Y, W):
raise Exception('All input arrays (x) should have '
'the same number of samples.')
set_y = set(y_lengths)
if len(set_x) != 1:
raise Exception('All target arrays (y) should have '
'the same number of samples.')
set_w = set(w_lengths)
|
def check_array_lengths(X, Y, W):
raise Exception('All input arrays (x) should have '
'the same number of samples.')
set_y = set(y_lengths)
if len(set_y) != 1:
raise Exception('All target arrays (y) should have '
'the same number of samples.')
set_w = set(w_lengths)
|
404 |
https://:@github.com/dmlc/keras.git
|
98974efa5f51d6f55afbf2bc125d6fd090bcf782
|
@@ -510,7 +510,7 @@ class Model(Container):
'it should have one entry per model outputs. '
'The model has ' + str(len(self.outputs)) +
' outputs, but you passed loss_weights=' +
- str(loss))
+ str(loss_weights))
loss_weights_list = loss_weights
else:
raise Exception('Could not interpret loss_weights argument: ' +
|
keras/engine/training.py
|
ReplaceText(target='loss_weights' @(513,36)->(513,40))
|
class Model(Container):
'it should have one entry per model outputs. '
'The model has ' + str(len(self.outputs)) +
' outputs, but you passed loss_weights=' +
str(loss))
loss_weights_list = loss_weights
else:
raise Exception('Could not interpret loss_weights argument: ' +
|
class Model(Container):
'it should have one entry per model outputs. '
'The model has ' + str(len(self.outputs)) +
' outputs, but you passed loss_weights=' +
str(loss_weights))
loss_weights_list = loss_weights
else:
raise Exception('Could not interpret loss_weights argument: ' +
|
405 |
https://:@github.com/dmlc/keras.git
|
48ae7217e482a1a3624d6e5380c972a653cacfaf
|
@@ -1136,7 +1136,7 @@ def rnn(step_function, inputs, initial_states,
if mask is not None:
if go_backwards:
- mask = tf.reverse(mask, [True] + [False] * (ndim - 1))
+ mask = tf.reverse(mask, [True] + [False] * (ndim - 2))
# Transpose not supported by bool tensor types, hence round-trip to uint8.
mask = tf.cast(mask, tf.uint8)
|
keras/backend/tensorflow_backend.py
|
ReplaceText(target='2' @(1139,67)->(1139,68))
|
def rnn(step_function, inputs, initial_states,
if mask is not None:
if go_backwards:
mask = tf.reverse(mask, [True] + [False] * (ndim - 1))
# Transpose not supported by bool tensor types, hence round-trip to uint8.
mask = tf.cast(mask, tf.uint8)
|
def rnn(step_function, inputs, initial_states,
if mask is not None:
if go_backwards:
mask = tf.reverse(mask, [True] + [False] * (ndim - 2))
# Transpose not supported by bool tensor types, hence round-trip to uint8.
mask = tf.cast(mask, tf.uint8)
|
406 |
https://:@github.com/dmlc/keras.git
|
41741c38e5f29ebf69fe9bd82a604eba3c0b97e5
|
@@ -1261,7 +1261,7 @@ def rnn(step_function, inputs, initial_states,
new_state = new_states[0]
else:
# return dummy state, otherwise _dynamic_rnn_loop breaks
- new_state = output
+ new_state = state
return output, new_state
_step.state_size = state_size * nb_states
|
keras/backend/tensorflow_backend.py
|
ReplaceText(target='state' @(1264,32)->(1264,38))
|
def rnn(step_function, inputs, initial_states,
new_state = new_states[0]
else:
# return dummy state, otherwise _dynamic_rnn_loop breaks
new_state = output
return output, new_state
_step.state_size = state_size * nb_states
|
def rnn(step_function, inputs, initial_states,
new_state = new_states[0]
else:
# return dummy state, otherwise _dynamic_rnn_loop breaks
new_state = state
return output, new_state
_step.state_size = state_size * nb_states
|
407 |
https://:@github.com/dmlc/keras.git
|
80fbbc3a6a2a30f391bad2aa85e7558c50ca0709
|
@@ -411,7 +411,7 @@ class ImageDataGenerator(object):
if self.zca_whitening:
flatX = np.reshape(X, (X.shape[0], X.shape[1] * X.shape[2] * X.shape[3]))
- sigma = np.dot(flatX.T, flatX) / flatX.shape[1]
+ sigma = np.dot(flatX.T, flatX) / flatX.shape[0]
U, S, V = linalg.svd(sigma)
self.principal_components = np.dot(np.dot(U, np.diag(1. / np.sqrt(S + 10e-7))), U.T)
|
keras/preprocessing/image.py
|
ReplaceText(target='0' @(414,57)->(414,58))
|
class ImageDataGenerator(object):
if self.zca_whitening:
flatX = np.reshape(X, (X.shape[0], X.shape[1] * X.shape[2] * X.shape[3]))
sigma = np.dot(flatX.T, flatX) / flatX.shape[1]
U, S, V = linalg.svd(sigma)
self.principal_components = np.dot(np.dot(U, np.diag(1. / np.sqrt(S + 10e-7))), U.T)
|
class ImageDataGenerator(object):
if self.zca_whitening:
flatX = np.reshape(X, (X.shape[0], X.shape[1] * X.shape[2] * X.shape[3]))
sigma = np.dot(flatX.T, flatX) / flatX.shape[0]
U, S, V = linalg.svd(sigma)
self.principal_components = np.dot(np.dot(U, np.diag(1. / np.sqrt(S + 10e-7))), U.T)
|
408 |
https://:@github.com/dmlc/keras.git
|
7bd5c862a271f125a76fa1ada7f0d9ae27159549
|
@@ -209,7 +209,7 @@ def check_loss_and_target_compatibility(targets, losses, output_shapes):
'which does expect integer targets.')
if loss.__name__ in key_losses:
for target_dim, out_dim in zip(y.shape[1:], shape[1:]):
- if target_dim is not None and target_dim != out_dim:
+ if out_dim is not None and target_dim != out_dim:
raise Exception('A target array with shape ' + str(y.shape) +
' was passed for an output of shape ' + str(shape) +
' while using as loss `' + loss.__name__ + '`. '
|
keras/engine/training.py
|
ReplaceText(target='out_dim' @(212,19)->(212,29))
|
def check_loss_and_target_compatibility(targets, losses, output_shapes):
'which does expect integer targets.')
if loss.__name__ in key_losses:
for target_dim, out_dim in zip(y.shape[1:], shape[1:]):
if target_dim is not None and target_dim != out_dim:
raise Exception('A target array with shape ' + str(y.shape) +
' was passed for an output of shape ' + str(shape) +
' while using as loss `' + loss.__name__ + '`. '
|
def check_loss_and_target_compatibility(targets, losses, output_shapes):
'which does expect integer targets.')
if loss.__name__ in key_losses:
for target_dim, out_dim in zip(y.shape[1:], shape[1:]):
if out_dim is not None and target_dim != out_dim:
raise Exception('A target array with shape ' + str(y.shape) +
' was passed for an output of shape ' + str(shape) +
' while using as loss `' + loss.__name__ + '`. '
|
409 |
https://:@github.com/dmlc/keras.git
|
cb4f93913eb871a5e234db0c31f885daff87ecdf
|
@@ -67,7 +67,7 @@ def _obtain_input_shape(input_shape, default_size, min_size, dim_ordering, inclu
if input_shape is not None:
if len(input_shape) != 3:
raise ValueError('`input_shape` must be a tuple of three integers.')
- if input_shape[1] != 3:
+ if input_shape[0] != 3:
raise ValueError('The input must have 3 channels; got '
'`input_shape=' + str(input_shape) + '`')
if ((input_shape[1] is not None and input_shape[1] < min_size) or
|
keras/applications/imagenet_utils.py
|
ReplaceText(target='0' @(70,31)->(70,32))
|
def _obtain_input_shape(input_shape, default_size, min_size, dim_ordering, inclu
if input_shape is not None:
if len(input_shape) != 3:
raise ValueError('`input_shape` must be a tuple of three integers.')
if input_shape[1] != 3:
raise ValueError('The input must have 3 channels; got '
'`input_shape=' + str(input_shape) + '`')
if ((input_shape[1] is not None and input_shape[1] < min_size) or
|
def _obtain_input_shape(input_shape, default_size, min_size, dim_ordering, inclu
if input_shape is not None:
if len(input_shape) != 3:
raise ValueError('`input_shape` must be a tuple of three integers.')
if input_shape[0] != 3:
raise ValueError('The input must have 3 channels; got '
'`input_shape=' + str(input_shape) + '`')
if ((input_shape[1] is not None and input_shape[1] < min_size) or
|
410 |
https://:@github.com/dmlc/keras.git
|
82ca6d418588ccd61d663ec8029937290b62d583
|
@@ -120,7 +120,7 @@ X = X[indices]
y = y[indices]
# Explicitly set apart 10% for validation data that we never train over
-split_at = len(X) - len(X) / 10
+split_at = len(X) - len(X) // 10
(X_train, X_val) = (slice_X(X, 0, split_at), slice_X(X, split_at))
(y_train, y_val) = (y[:split_at], y[split_at:])
|
examples/addition_rnn.py
|
ReplaceText(target='//' @(123,27)->(123,28))
|
X = X[indices]
y = y[indices]
# Explicitly set apart 10% for validation data that we never train over
split_at = len(X) - len(X) / 10
(X_train, X_val) = (slice_X(X, 0, split_at), slice_X(X, split_at))
(y_train, y_val) = (y[:split_at], y[split_at:])
|
X = X[indices]
y = y[indices]
# Explicitly set apart 10% for validation data that we never train over
split_at = len(X) - len(X) // 10
(X_train, X_val) = (slice_X(X, 0, split_at), slice_X(X, split_at))
(y_train, y_val) = (y[:split_at], y[split_at:])
|
411 |
https://:@github.com/dmlc/keras.git
|
7c34add25d0f6a773f1c74d1d8bb50f4482afc76
|
@@ -1875,7 +1875,7 @@ def set_value(x, value):
"""Sets the value of a variable,
from a Numpy array. It returns `None`.
"""
- if isinstance(x, Number):
+ if isinstance(value, Number):
value = [value]
x.bind(mx.nd.array(value))
|
keras/backend/mxnet_backend.py
|
ReplaceText(target='value' @(1878,18)->(1878,19))
|
def set_value(x, value):
"""Sets the value of a variable,
from a Numpy array. It returns `None`.
"""
if isinstance(x, Number):
value = [value]
x.bind(mx.nd.array(value))
|
def set_value(x, value):
"""Sets the value of a variable,
from a Numpy array. It returns `None`.
"""
if isinstance(value, Number):
value = [value]
x.bind(mx.nd.array(value))
|
412 |
https://:@github.com/incountry/sdk-python.git
|
e98e4243dae300a5ae9cab87347fa61bb87b51a9
|
@@ -28,6 +28,6 @@ storage = Storage(
while not migration_complete:
migration_res = storage.migrate(country=COUNTRY, limit=50)
- if migration_res["total_left"] <= 0:
+ if migration_res["total_left"] == 0:
migration_complete = True
time.sleep(1)
|
examples/full_migration.py
|
ReplaceText(target='==' @(31,35)->(31,37))
|
storage = Storage(
while not migration_complete:
migration_res = storage.migrate(country=COUNTRY, limit=50)
if migration_res["total_left"] <= 0:
migration_complete = True
time.sleep(1)
|
storage = Storage(
while not migration_complete:
migration_res = storage.migrate(country=COUNTRY, limit=50)
if migration_res["total_left"] == 0:
migration_complete = True
time.sleep(1)
|
413 |
https://:@github.com/knockrentals/scrapy-elasticsearch.git
|
1c5c20459e68544eeb8a0490b9f7b14895861b24
|
@@ -96,7 +96,7 @@ class ElasticSearchPipeline(object):
self.items_buffer.append(index_action)
- if len(self.items_buffer) == self.settings.get('ELASTICSEARCH_BUFFER_LENGTH', 500):
+ if len(self.items_buffer) >= self.settings.get('ELASTICSEARCH_BUFFER_LENGTH', 500):
self.send_items()
self.items_buffer = []
|
scrapyelasticsearch/scrapyelasticsearch.py
|
ReplaceText(target='>=' @(99,34)->(99,36))
|
class ElasticSearchPipeline(object):
self.items_buffer.append(index_action)
if len(self.items_buffer) == self.settings.get('ELASTICSEARCH_BUFFER_LENGTH', 500):
self.send_items()
self.items_buffer = []
|
class ElasticSearchPipeline(object):
self.items_buffer.append(index_action)
if len(self.items_buffer) >= self.settings.get('ELASTICSEARCH_BUFFER_LENGTH', 500):
self.send_items()
self.items_buffer = []
|
414 |
https://:@github.com/smithlabcode/ribotricer.git
|
805255ef81f4c94dcaf9f0c63ba39f0de7f14eea
|
@@ -149,7 +149,7 @@ def detect_orfs_cmd(bam, ribocop_index, prefix, stranded, read_lengths,
sys.exit('Error: cannot convert psite_offsets into integers')
if len(read_lengths) != len(psite_offsets):
sys.exit('Error: psite_offsets must match read_lengths')
- if not all(x > 0 for x in psite_offsets):
+ if not all(x >= 0 for x in psite_offsets):
sys.exit('Error: P-site offset must be >= 0')
if not all(x > y for (x, y) in zip(read_lengths, psite_offsets)):
sys.exit('Error: P-site offset must be smaller than read length')
|
RiboCop/cli.py
|
ReplaceText(target='>=' @(152,21)->(152,22))
|
def detect_orfs_cmd(bam, ribocop_index, prefix, stranded, read_lengths,
sys.exit('Error: cannot convert psite_offsets into integers')
if len(read_lengths) != len(psite_offsets):
sys.exit('Error: psite_offsets must match read_lengths')
if not all(x > 0 for x in psite_offsets):
sys.exit('Error: P-site offset must be >= 0')
if not all(x > y for (x, y) in zip(read_lengths, psite_offsets)):
sys.exit('Error: P-site offset must be smaller than read length')
|
def detect_orfs_cmd(bam, ribocop_index, prefix, stranded, read_lengths,
sys.exit('Error: cannot convert psite_offsets into integers')
if len(read_lengths) != len(psite_offsets):
sys.exit('Error: psite_offsets must match read_lengths')
if not all(x >= 0 for x in psite_offsets):
sys.exit('Error: P-site offset must be >= 0')
if not all(x > y for (x, y) in zip(read_lengths, psite_offsets)):
sys.exit('Error: P-site offset must be smaller than read length')
|
415 |
https://:@github.com/smithlabcode/ribotricer.git
|
9e9c9497eb5c2669bd272729e19f47e2cbf2b3db
|
@@ -321,7 +321,7 @@ def prepare_orfs(gtf, fasta, prefix, min_orf_length, start_codons,
for orf in tqdm(candidate_orfs):
coordinate = ','.join(
['{}-{}'.format(iv.start, iv.end) for iv in orf.intervals])
- to_write = formatter.format(orf.oid, orf.category, orf.tid, orf.ttype,
+ to_write += formatter.format(orf.oid, orf.category, orf.tid, orf.ttype,
orf.gid, orf.gname, orf.gtype, orf.chrom,
orf.strand, coordinate)
|
RiboCop/prepare_orfs.py
|
ReplaceText(target='+=' @(324,17)->(324,18))
|
def prepare_orfs(gtf, fasta, prefix, min_orf_length, start_codons,
for orf in tqdm(candidate_orfs):
coordinate = ','.join(
['{}-{}'.format(iv.start, iv.end) for iv in orf.intervals])
to_write = formatter.format(orf.oid, orf.category, orf.tid, orf.ttype,
orf.gid, orf.gname, orf.gtype, orf.chrom,
orf.strand, coordinate)
|
def prepare_orfs(gtf, fasta, prefix, min_orf_length, start_codons,
for orf in tqdm(candidate_orfs):
coordinate = ','.join(
['{}-{}'.format(iv.start, iv.end) for iv in orf.intervals])
to_write += formatter.format(orf.oid, orf.category, orf.tid, orf.ttype,
orf.gid, orf.gname, orf.gtype, orf.chrom,
orf.strand, coordinate)
|
416 |
https://:@github.com/pughlab/ConsensusCruncher.git
|
3622410b893b07afb4e423a4537eab33da26a55d
|
@@ -147,7 +147,7 @@ def main():
sscs_bam = pysam.AlignmentFile(args.infile, "rb")
dcs_bam = pysam.AlignmentFile(args.outfile, "wb", template=sscs_bam)
- if re.search('dcs.sc', args.outfile) is None:
+ if re.search('dcs.sc', args.outfile) is not None:
sscs_singleton_bam = pysam.AlignmentFile('{}.sscs.sc.singleton.bam'.format(args.outfile.split('.dcs.sc')[0]),
"wb", template=sscs_bam)
dcs_header = "DCS - Singleton Correction"
|
ConsensusCruncher/DCS_maker.py
|
ReplaceText(target=' is not ' @(150,40)->(150,44))
|
def main():
sscs_bam = pysam.AlignmentFile(args.infile, "rb")
dcs_bam = pysam.AlignmentFile(args.outfile, "wb", template=sscs_bam)
if re.search('dcs.sc', args.outfile) is None:
sscs_singleton_bam = pysam.AlignmentFile('{}.sscs.sc.singleton.bam'.format(args.outfile.split('.dcs.sc')[0]),
"wb", template=sscs_bam)
dcs_header = "DCS - Singleton Correction"
|
def main():
sscs_bam = pysam.AlignmentFile(args.infile, "rb")
dcs_bam = pysam.AlignmentFile(args.outfile, "wb", template=sscs_bam)
if re.search('dcs.sc', args.outfile) is not None:
sscs_singleton_bam = pysam.AlignmentFile('{}.sscs.sc.singleton.bam'.format(args.outfile.split('.dcs.sc')[0]),
"wb", template=sscs_bam)
dcs_header = "DCS - Singleton Correction"
|
417 |
https://:@github.com/django-guardian/django-guardian.git
|
f60306eb93fd276879806d6e78557bdb5d1ce34f
|
@@ -172,7 +172,7 @@ def get_obj_perms_model(obj, base_cls, generic_cls):
for attr in fields:
model = getattr(attr, 'related_model', None)
if (model and issubclass(model, base_cls) and
- model is not generic_cls and getattr(attr, 'enabled', True)):
+ model is not generic_cls and getattr(model, 'enabled', True)):
# if model is generic one it would be returned anyway
if not model.objects.is_generic():
# make sure that content_object's content_type is same as
|
guardian/utils.py
|
ReplaceText(target='model' @(175,53)->(175,57))
|
def get_obj_perms_model(obj, base_cls, generic_cls):
for attr in fields:
model = getattr(attr, 'related_model', None)
if (model and issubclass(model, base_cls) and
model is not generic_cls and getattr(attr, 'enabled', True)):
# if model is generic one it would be returned anyway
if not model.objects.is_generic():
# make sure that content_object's content_type is same as
|
def get_obj_perms_model(obj, base_cls, generic_cls):
for attr in fields:
model = getattr(attr, 'related_model', None)
if (model and issubclass(model, base_cls) and
model is not generic_cls and getattr(model, 'enabled', True)):
# if model is generic one it would be returned anyway
if not model.objects.is_generic():
# make sure that content_object's content_type is same as
|
418 |
https://:@github.com/podhmo/magicalimport.git
|
293f619fee3f401ebe0daf55f001354ecf2a2124
|
@@ -69,7 +69,7 @@ def import_symbol(sym, here=None, sep=":", ns=None):
sym = "{}:{}".format(ns, sym)
module_path, fn_name = sym.rsplit(sep, 2)
try:
- module = import_module(sym, here=here, sep=sep)
+ module = import_module(module_path, here=here, sep=sep)
return getattr(module, fn_name)
except (ImportError, AttributeError) as e:
sys.stderr.write("could not import {!r}\n{}\n".format(sym, e))
|
magicalimport/__init__.py
|
ReplaceText(target='module_path' @(72,31)->(72,34))
|
def import_symbol(sym, here=None, sep=":", ns=None):
sym = "{}:{}".format(ns, sym)
module_path, fn_name = sym.rsplit(sep, 2)
try:
module = import_module(sym, here=here, sep=sep)
return getattr(module, fn_name)
except (ImportError, AttributeError) as e:
sys.stderr.write("could not import {!r}\n{}\n".format(sym, e))
|
def import_symbol(sym, here=None, sep=":", ns=None):
sym = "{}:{}".format(ns, sym)
module_path, fn_name = sym.rsplit(sep, 2)
try:
module = import_module(module_path, here=here, sep=sep)
return getattr(module, fn_name)
except (ImportError, AttributeError) as e:
sys.stderr.write("could not import {!r}\n{}\n".format(sym, e))
|
419 |
https://:@github.com/sigmavirus24/betamax.git
|
9d84fcffbdf41133dbdd686490c993d63e0243fc
|
@@ -112,7 +112,7 @@ def deserialize_response(serialized):
for header_name, header_list in serialized['headers'].items():
if isinstance(header_list, list):
for header_value in header_list:
- header_dict.add(header_name, header_list)
+ header_dict.add(header_name, header_value)
else:
header_dict.add(header_name, header_list)
r.headers = CaseInsensitiveDict(header_dict)
|
betamax/cassette/util.py
|
ReplaceText(target='header_value' @(115,45)->(115,56))
|
def deserialize_response(serialized):
for header_name, header_list in serialized['headers'].items():
if isinstance(header_list, list):
for header_value in header_list:
header_dict.add(header_name, header_list)
else:
header_dict.add(header_name, header_list)
r.headers = CaseInsensitiveDict(header_dict)
|
def deserialize_response(serialized):
for header_name, header_list in serialized['headers'].items():
if isinstance(header_list, list):
for header_value in header_list:
header_dict.add(header_name, header_value)
else:
header_dict.add(header_name, header_list)
r.headers = CaseInsensitiveDict(header_dict)
|
420 |
https://:@github.com/CodyKochmann/generators.git
|
0c99248a9a96a675d6995855c4a9ae0efebef329
|
@@ -17,7 +17,7 @@ def itemgetter(iterable, indexes):
for i,x in enumerate(iterable):
if i in positive_indexes:
out[i]=x
- negative_index_buffer.append(i)
+ negative_index_buffer.append(x)
out.update({ni:negative_index_buffer[ni] for ni in negative_indexes})
else:
# if just positive results
|
generators/itemgetter.py
|
ReplaceText(target='x' @(20,41)->(20,42))
|
def itemgetter(iterable, indexes):
for i,x in enumerate(iterable):
if i in positive_indexes:
out[i]=x
negative_index_buffer.append(i)
out.update({ni:negative_index_buffer[ni] for ni in negative_indexes})
else:
# if just positive results
|
def itemgetter(iterable, indexes):
for i,x in enumerate(iterable):
if i in positive_indexes:
out[i]=x
negative_index_buffer.append(x)
out.update({ni:negative_index_buffer[ni] for ni in negative_indexes})
else:
# if just positive results
|
421 |
https://:@github.com/reiinakano/xcessiv.git
|
b197e370a6f8a46f6ba3e9b77fb76f150f28edd5
|
@@ -146,7 +146,7 @@ def evaluate_stacked_ensemble(path, ensemble_id):
)
preds = []
trues_list = []
- for train_index, test_index in cv.split(X, y):
+ for train_index, test_index in cv.split(secondary_features, y):
X_train, X_test = secondary_features[train_index], secondary_features[test_index]
y_train, y_test = y[train_index], y[test_index]
est = est.fit(X_train, y_train)
|
xcessiv/rqtasks.py
|
ReplaceText(target='secondary_features' @(149,52)->(149,53))
|
def evaluate_stacked_ensemble(path, ensemble_id):
)
preds = []
trues_list = []
for train_index, test_index in cv.split(X, y):
X_train, X_test = secondary_features[train_index], secondary_features[test_index]
y_train, y_test = y[train_index], y[test_index]
est = est.fit(X_train, y_train)
|
def evaluate_stacked_ensemble(path, ensemble_id):
)
preds = []
trues_list = []
for train_index, test_index in cv.split(secondary_features, y):
X_train, X_test = secondary_features[train_index], secondary_features[test_index]
y_train, y_test = y[train_index], y[test_index]
est = est.fit(X_train, y_train)
|
422 |
https://:@github.com/MosesofEgypt/mozzarilla.git
|
5c0f1e29111be71edbb67ef13094a0cdc83d760c
|
@@ -684,7 +684,7 @@ def _compile_model_animations(self):
print(error)
self.update()
- if messagebox.askyesno(
+ if not messagebox.askyesno(
"Model_animations compilation failed",
"Errors occurred while compiling animations(check console). "
"Do you want to save the model_animations tag anyway?",
|
mozzarilla/tools/animations_compiler_window.py
|
ReplaceText(target='not ' @(687,15)->(687,15))
|
def _compile_model_animations(self):
print(error)
self.update()
if messagebox.askyesno(
"Model_animations compilation failed",
"Errors occurred while compiling animations(check console). "
"Do you want to save the model_animations tag anyway?",
|
def _compile_model_animations(self):
print(error)
self.update()
if not messagebox.askyesno(
"Model_animations compilation failed",
"Errors occurred while compiling animations(check console). "
"Do you want to save the model_animations tag anyway?",
|
423 |
https://:@github.com/HeeroYui/lutin.git
|
9fc593fb59a192ddf5f50a96e2a6cba76dab73b6
|
@@ -23,7 +23,7 @@ class System(system.System):
# no check needed ==> just add this:
self.add_module_depend(['c'])
self.add_export_flag('link-lib', 'X11')
- if env.get_isolate_system() == False:
+ if env.get_isolate_system() == True:
self.add_header_file([
"/usr/include/X11/*"
],
|
lutin/z_system/lutinSystem_Linux_X11.py
|
ReplaceText(target='True' @(26,33)->(26,38))
|
class System(system.System):
# no check needed ==> just add this:
self.add_module_depend(['c'])
self.add_export_flag('link-lib', 'X11')
if env.get_isolate_system() == False:
self.add_header_file([
"/usr/include/X11/*"
],
|
class System(system.System):
# no check needed ==> just add this:
self.add_module_depend(['c'])
self.add_export_flag('link-lib', 'X11')
if env.get_isolate_system() == True:
self.add_header_file([
"/usr/include/X11/*"
],
|
424 |
https://:@github.com/sanger-pathogens/ariba.git
|
8625628cf307e533bb6e778d9b8e936e48cef727
|
@@ -294,7 +294,7 @@ class ReferenceData:
def sanity_check(self, outprefix):
variants_only_removed = self._remove_bad_genes(self.seq_dicts['variants_only'], outprefix + '.00.check_fasta_variants_only.log')
presence_absence_removed = self._remove_bad_genes(self.seq_dicts['presence_absence'], outprefix + '.00.check_fasta_presence_absence.log')
- self._filter_bad_variant_data(outprefix + '.01.check_variants', variants_only_removed, presence_absence_removed)
+ self._filter_bad_variant_data(outprefix + '.01.check_variants', presence_absence_removed, variants_only_removed)
@classmethod
|
ariba/reference_data.py
|
ArgSwap(idxs=1<->2 @(297,8)->(297,37))
|
class ReferenceData:
def sanity_check(self, outprefix):
variants_only_removed = self._remove_bad_genes(self.seq_dicts['variants_only'], outprefix + '.00.check_fasta_variants_only.log')
presence_absence_removed = self._remove_bad_genes(self.seq_dicts['presence_absence'], outprefix + '.00.check_fasta_presence_absence.log')
self._filter_bad_variant_data(outprefix + '.01.check_variants', variants_only_removed, presence_absence_removed)
@classmethod
|
class ReferenceData:
def sanity_check(self, outprefix):
variants_only_removed = self._remove_bad_genes(self.seq_dicts['variants_only'], outprefix + '.00.check_fasta_variants_only.log')
presence_absence_removed = self._remove_bad_genes(self.seq_dicts['presence_absence'], outprefix + '.00.check_fasta_presence_absence.log')
self._filter_bad_variant_data(outprefix + '.01.check_variants', presence_absence_removed, variants_only_removed)
@classmethod
|
425 |
https://:@github.com/sanger-pathogens/ariba.git
|
c70bc90299a1c5a85f20127ac8c750925219316b
|
@@ -192,7 +192,7 @@ class Summary:
if self.show_known_het and (cluster, variant) in all_het_snps:
rows[filename][cluster][key + '.%'] = 'NA'
- if self.show_known_het and (ref_name, variant) in all_het_snps and key + '.%' not in rows[filename][cluster]:
+ if self.show_known_het and (cluster, variant) in all_het_snps and key + '.%' not in rows[filename][cluster]:
rows[filename][cluster][key + '.%'] = 'NA'
for key, wanted in self.cluster_columns.items():
|
ariba/summary.py
|
ReplaceText(target='cluster' @(195,52)->(195,60))
|
class Summary:
if self.show_known_het and (cluster, variant) in all_het_snps:
rows[filename][cluster][key + '.%'] = 'NA'
if self.show_known_het and (ref_name, variant) in all_het_snps and key + '.%' not in rows[filename][cluster]:
rows[filename][cluster][key + '.%'] = 'NA'
for key, wanted in self.cluster_columns.items():
|
class Summary:
if self.show_known_het and (cluster, variant) in all_het_snps:
rows[filename][cluster][key + '.%'] = 'NA'
if self.show_known_het and (cluster, variant) in all_het_snps and key + '.%' not in rows[filename][cluster]:
rows[filename][cluster][key + '.%'] = 'NA'
for key, wanted in self.cluster_columns.items():
|
426 |
https://:@github.com/sanger-pathogens/ariba.git
|
1fd2c639e7b24a69252390744ae4e1a9e49db5dd
|
@@ -47,7 +47,7 @@ class MlstReporter:
depths = [int(x) for x in d['smtls_nts_depth'].split(',')]
depths.sort()
het_pc = round(100.0 * depths[-1] / sum(depths), 2)
- if results['hetmin'] == '.' or results['hetmin'] < het_pc:
+ if results['hetmin'] == '.' or results['hetmin'] > het_pc:
results['hetmin'] = het_pc
if len(het_data):
results['hets'] = '.'.join(het_data)
|
ariba/mlst_reporter.py
|
ReplaceText(target='>' @(50,69)->(50,70))
|
class MlstReporter:
depths = [int(x) for x in d['smtls_nts_depth'].split(',')]
depths.sort()
het_pc = round(100.0 * depths[-1] / sum(depths), 2)
if results['hetmin'] == '.' or results['hetmin'] < het_pc:
results['hetmin'] = het_pc
if len(het_data):
results['hets'] = '.'.join(het_data)
|
class MlstReporter:
depths = [int(x) for x in d['smtls_nts_depth'].split(',')]
depths.sort()
het_pc = round(100.0 * depths[-1] / sum(depths), 2)
if results['hetmin'] == '.' or results['hetmin'] > het_pc:
results['hetmin'] = het_pc
if len(het_data):
results['hets'] = '.'.join(het_data)
|
427 |
https://:@github.com/urschrei/pyzotero.git
|
cdfd191116363c947fc0a0d0b4f37849d709f9f2
|
@@ -40,7 +40,7 @@ def check():
return library_version == git_version
if __name__ == '__main__':
- if check():
+ if not check():
sys.exit(1)
else:
sys.exit(0)
|
pre-deploy.py
|
ReplaceText(target='not ' @(43,7)->(43,7))
|
def check():
return library_version == git_version
if __name__ == '__main__':
if check():
sys.exit(1)
else:
sys.exit(0)
|
def check():
return library_version == git_version
if __name__ == '__main__':
if not check():
sys.exit(1)
else:
sys.exit(0)
|
428 |
https://:@github.com/lyft/confidant.git
|
5de06bb144ad392dba5ef9c75603eb9587dfcfe3
|
@@ -410,7 +410,7 @@ def update_credential(id):
include_credential_pairs=True,
)
credential_response.permissions = permissions
- return credential_response_schema.dumps(permissions)
+ return credential_response_schema.dumps(credential_response)
@blueprint.route('/v1/credentials/<id>/<to_revision>', methods=['PUT'])
|
confidant/routes/credentials.py
|
ReplaceText(target='credential_response' @(413,44)->(413,55))
|
def update_credential(id):
include_credential_pairs=True,
)
credential_response.permissions = permissions
return credential_response_schema.dumps(permissions)
@blueprint.route('/v1/credentials/<id>/<to_revision>', methods=['PUT'])
|
def update_credential(id):
include_credential_pairs=True,
)
credential_response.permissions = permissions
return credential_response_schema.dumps(credential_response)
@blueprint.route('/v1/credentials/<id>/<to_revision>', methods=['PUT'])
|
429 |
https://:@github.com/cloudenvy/cloudenvy.git
|
a19f6f84832b1dfddbf5ad7b1e84790842b22712
|
@@ -35,7 +35,7 @@ class Files(cloudenvy.envy.Command):
logging.info("Copying file from '%s' to '%s'",
local_path, remote_path)
- if os.path.exists(local_path):
+ if not os.path.exists(local_path):
logging.error("Local file '%s' not found.", local_path)
dest_dir = _parse_directory(remote_path)
|
cloudenvy/commands/files.py
|
ReplaceText(target='not ' @(38,23)->(38,23))
|
class Files(cloudenvy.envy.Command):
logging.info("Copying file from '%s' to '%s'",
local_path, remote_path)
if os.path.exists(local_path):
logging.error("Local file '%s' not found.", local_path)
dest_dir = _parse_directory(remote_path)
|
class Files(cloudenvy.envy.Command):
logging.info("Copying file from '%s' to '%s'",
local_path, remote_path)
if not os.path.exists(local_path):
logging.error("Local file '%s' not found.", local_path)
dest_dir = _parse_directory(remote_path)
|
430 |
https://:@github.com/WeiXuanChan/autoD.git
|
e163474f70ed6a02f39cd6edaa298271e5f23327
|
@@ -520,7 +520,7 @@ class Imaginary(AD):
class Absolute(AD):
def __init__(self,func):
self.func=func
- self.abs=(Real(func)**2.-Imaginary(func)**2.)**0.5
+ self.abs=(Real(func)**2.+Imaginary(func)**2.)**0.5
try:
self.dependent=func.dependent[:]
except AttributeError:
|
autoD.py
|
ReplaceText(target='+' @(523,32)->(523,33))
|
class Imaginary(AD):
class Absolute(AD):
def __init__(self,func):
self.func=func
self.abs=(Real(func)**2.-Imaginary(func)**2.)**0.5
try:
self.dependent=func.dependent[:]
except AttributeError:
|
class Imaginary(AD):
class Absolute(AD):
def __init__(self,func):
self.func=func
self.abs=(Real(func)**2.+Imaginary(func)**2.)**0.5
try:
self.dependent=func.dependent[:]
except AttributeError:
|
431 |
https://:@github.com/dwavesystems/dimod.git
|
79979454139757bd49c1e31c67d890c1d5efeee2
|
@@ -279,7 +279,7 @@ class PolyScaleComposite(ComposedPolySampler):
# we need to know how much we scaled by, which we can do by looking
# at the biases
try:
- v = next((v for v, bias in poly.items() if bias))
+ v = next((v for v, bias in original.items() if bias))
except StopIteration:
# nothing to scale
scalar = 1
|
dimod/reference/composites/higherordercomposites.py
|
ReplaceText(target='original' @(282,43)->(282,47))
|
class PolyScaleComposite(ComposedPolySampler):
# we need to know how much we scaled by, which we can do by looking
# at the biases
try:
v = next((v for v, bias in poly.items() if bias))
except StopIteration:
# nothing to scale
scalar = 1
|
class PolyScaleComposite(ComposedPolySampler):
# we need to know how much we scaled by, which we can do by looking
# at the biases
try:
v = next((v for v, bias in original.items() if bias))
except StopIteration:
# nothing to scale
scalar = 1
|
432 |
https://:@github.com/dwavesystems/dimod.git
|
c21ee99ab65a519b822689361fcfcc66ffb890f2
|
@@ -2146,7 +2146,7 @@ class TestSerialization(unittest.TestCase):
new = dimod.BinaryQuadraticModel.from_serializable(bqm.to_serializable(use_bytes=True))
self.assertEqual(bqm, new)
- self.assertEqual(bqm.info, {"tag": 5})
+ self.assertEqual(new.info, {"tag": 5})
class TestZeroField(unittest.TestCase):
|
tests/test_binary_quadratic_model.py
|
ReplaceText(target='new' @(2149,25)->(2149,28))
|
class TestSerialization(unittest.TestCase):
new = dimod.BinaryQuadraticModel.from_serializable(bqm.to_serializable(use_bytes=True))
self.assertEqual(bqm, new)
self.assertEqual(bqm.info, {"tag": 5})
class TestZeroField(unittest.TestCase):
|
class TestSerialization(unittest.TestCase):
new = dimod.BinaryQuadraticModel.from_serializable(bqm.to_serializable(use_bytes=True))
self.assertEqual(bqm, new)
self.assertEqual(new.info, {"tag": 5})
class TestZeroField(unittest.TestCase):
|
433 |
https://:@github.com/dwavesystems/dimod.git
|
ceee47e049c2c3305d459c6ae865a430dbd113e9
|
@@ -197,7 +197,7 @@ def ran_r(r, graph, cls=BinaryQuadraticModel, seed=None):
rvals = np.empty(2*r)
rvals[0:r] = range(-r, 0)
rvals[r:] = range(1, r+1)
- qdata = rnd.choice(rvals, size=len(variables))
+ qdata = rnd.choice(rvals, size=len(irow))
offset = 0
|
dimod/generators/random.py
|
ReplaceText(target='irow' @(200,39)->(200,48))
|
def ran_r(r, graph, cls=BinaryQuadraticModel, seed=None):
rvals = np.empty(2*r)
rvals[0:r] = range(-r, 0)
rvals[r:] = range(1, r+1)
qdata = rnd.choice(rvals, size=len(variables))
offset = 0
|
def ran_r(r, graph, cls=BinaryQuadraticModel, seed=None):
rvals = np.empty(2*r)
rvals[0:r] = range(-r, 0)
rvals[r:] = range(1, r+1)
qdata = rnd.choice(rvals, size=len(irow))
offset = 0
|
434 |
https://:@github.com/dvdotsenko/jsonrpc.py.git
|
92ad90db194c878cb2023e97758671d72c976797
|
@@ -75,7 +75,7 @@ class JSONPRCWSGIApplicationTestSuite(TestCase):
response_json = responses_data[0]
assert 'error' not in response_json
- assert response_json['id'] == request2['id']
+ assert response_json['id'] == request1['id']
assert response_json['result'] == 5
response_json = responses_data[1]
|
tests/test_wsgi_application.py
|
ReplaceText(target='request1' @(78,38)->(78,46))
|
class JSONPRCWSGIApplicationTestSuite(TestCase):
response_json = responses_data[0]
assert 'error' not in response_json
assert response_json['id'] == request2['id']
assert response_json['result'] == 5
response_json = responses_data[1]
|
class JSONPRCWSGIApplicationTestSuite(TestCase):
response_json = responses_data[0]
assert 'error' not in response_json
assert response_json['id'] == request1['id']
assert response_json['result'] == 5
response_json = responses_data[1]
|
435 |
https://:@github.com/MarSoft/ses-mailer-2.git
|
8c1b6aafc09412a6b6b2b1a69337ccbd99fc43f2
|
@@ -264,7 +264,7 @@ class Mail(object):
for ob in optional_blocks:
if ob in blocks:
if ob == "format" and \
- mail_params[ob].lower() not in ["html", "text"]:
+ blocks[ob].lower() not in ["html", "text"]:
continue
mail_params[ob] = blocks[ob]
return mail_params
|
ses_mailer.py
|
ReplaceText(target='blocks' @(267,24)->(267,35))
|
class Mail(object):
for ob in optional_blocks:
if ob in blocks:
if ob == "format" and \
mail_params[ob].lower() not in ["html", "text"]:
continue
mail_params[ob] = blocks[ob]
return mail_params
|
class Mail(object):
for ob in optional_blocks:
if ob in blocks:
if ob == "format" and \
blocks[ob].lower() not in ["html", "text"]:
continue
mail_params[ob] = blocks[ob]
return mail_params
|
436 |
https://:@github.com/interpretml/interpret.git
|
dfae1d47394d50472e25717c53c245cbe9f8a5ad
|
@@ -1067,7 +1067,7 @@ class BaseEBM(BaseEstimator):
"scores_range": bounds,
}
feature_list.append(feature_dict)
- density_dict.append({})
+ density_list.append({})
data_dict = {
"type": "pairwise",
|
python/interpret/glassbox/ebm/ebm.py
|
ReplaceText(target='density_list' @(1070,16)->(1070,28))
|
class BaseEBM(BaseEstimator):
"scores_range": bounds,
}
feature_list.append(feature_dict)
density_dict.append({})
data_dict = {
"type": "pairwise",
|
class BaseEBM(BaseEstimator):
"scores_range": bounds,
}
feature_list.append(feature_dict)
density_list.append({})
data_dict = {
"type": "pairwise",
|
437 |
https://:@gitlab.com/serial-lab/random-flavorpack.git
|
e69ba47e04a84e1746363a93d33bfe2ca9581cd5
|
@@ -76,7 +76,7 @@ class RandomGenerator(Generator):
if maximum <= minimum:
raise ValueError(
_("The maximum can not be less than the minimum."))
- if start < minimum or start >= maximum:
+ if start < minimum or start > maximum:
raise ValueError(
_("The start must be between the minimum and maximum!"))
rnrange = maximum - minimum
|
random_flavorpack/generators/random.py
|
ReplaceText(target='>' @(79,36)->(79,38))
|
class RandomGenerator(Generator):
if maximum <= minimum:
raise ValueError(
_("The maximum can not be less than the minimum."))
if start < minimum or start >= maximum:
raise ValueError(
_("The start must be between the minimum and maximum!"))
rnrange = maximum - minimum
|
class RandomGenerator(Generator):
if maximum <= minimum:
raise ValueError(
_("The maximum can not be less than the minimum."))
if start < minimum or start > maximum:
raise ValueError(
_("The start must be between the minimum and maximum!"))
rnrange = maximum - minimum
|
438 |
https://:@github.com/Ezibenroc/PyRoaringBitMap.git
|
7081ceba18ccaf2ee80d3c142e6e612cf77d17d2
|
@@ -779,7 +779,7 @@ class OptimizationTest(unittest.TestCase):
self.assertGreater(bm2.shrink_to_fit(), 0)
self.assertEqual(bm2.shrink_to_fit(), 0)
bm3 = cls(bm1, optimize=True)
- self.assertEqual(bm2.shrink_to_fit(), 0)
+ self.assertEqual(bm3.shrink_to_fit(), 0)
class VersionTest(unittest.TestCase):
|
test.py
|
ReplaceText(target='bm3' @(782,25)->(782,28))
|
class OptimizationTest(unittest.TestCase):
self.assertGreater(bm2.shrink_to_fit(), 0)
self.assertEqual(bm2.shrink_to_fit(), 0)
bm3 = cls(bm1, optimize=True)
self.assertEqual(bm2.shrink_to_fit(), 0)
class VersionTest(unittest.TestCase):
|
class OptimizationTest(unittest.TestCase):
self.assertGreater(bm2.shrink_to_fit(), 0)
self.assertEqual(bm2.shrink_to_fit(), 0)
bm3 = cls(bm1, optimize=True)
self.assertEqual(bm3.shrink_to_fit(), 0)
class VersionTest(unittest.TestCase):
|
439 |
https://:@github.com/Cavenfish/autogamess.git
|
09def521ebf6c9686479439d71aee114d554a5de
|
@@ -136,8 +136,8 @@ def new_project(maindir, csvfile, ebasis_dir, initial_coords_dict=None,
#Run Input Builder function
save_dir = maindir + 'inputs/'
- input_builder(csvfile, initial_coords_dict, ebasis_dir,
- save_dir, title.replace('/', '\n'))
+ input_builder(csvfile, save_dir, ebasis_dir,
+ initial_coords_dict, title.replace('/', '\n'))
return
|
autogamess/new_project.py
|
ArgSwap(idxs=1<->3 @(139,4)->(139,17))
|
def new_project(maindir, csvfile, ebasis_dir, initial_coords_dict=None,
#Run Input Builder function
save_dir = maindir + 'inputs/'
input_builder(csvfile, initial_coords_dict, ebasis_dir,
save_dir, title.replace('/', '\n'))
return
|
def new_project(maindir, csvfile, ebasis_dir, initial_coords_dict=None,
#Run Input Builder function
save_dir = maindir + 'inputs/'
input_builder(csvfile, save_dir, ebasis_dir,
initial_coords_dict, title.replace('/', '\n'))
return
|
440 |
https://:@github.com/Cavenfish/autogamess.git
|
4dcbf5d1a0f9059f8bdbc1a346c8f9cced70f62d
|
@@ -136,7 +136,7 @@ def new_project(maindir, csvfile, ebasis_dir, initial_coords_dict=None,
#Run Input Builder function
save_dir = maindir + 'inputs/'
- input_builder(csvfile, save_dir, ebasis_dir,
+ input_builder(csvfile, ebasis_dir, save_dir,
initial_coords_dict, title.replace('/', '\n'))
|
autogamess/new_project.py
|
ArgSwap(idxs=1<->2 @(139,4)->(139,17))
|
def new_project(maindir, csvfile, ebasis_dir, initial_coords_dict=None,
#Run Input Builder function
save_dir = maindir + 'inputs/'
input_builder(csvfile, save_dir, ebasis_dir,
initial_coords_dict, title.replace('/', '\n'))
|
def new_project(maindir, csvfile, ebasis_dir, initial_coords_dict=None,
#Run Input Builder function
save_dir = maindir + 'inputs/'
input_builder(csvfile, ebasis_dir, save_dir,
initial_coords_dict, title.replace('/', '\n'))
|
441 |
https://:@github.com/Cavenfish/autogamess.git
|
3890ccfd3dc7e723a37b8b5308d59a8de0b6f807
|
@@ -306,6 +306,6 @@ def fill_spreadsheets(projdir=False, sorteddir=False, sheetsdir=False):
if vsc in df:
df[vsc].to_excel(writer, sheet_name=vsc, startrow=6)
if cmp in df:
- df[cmp].to_excel(writer, sheet_name=vsc, startrow=6)
+ df[cmp].to_excel(writer, sheet_name=cmp, startrow=6)
return
|
autogamess/fill_spreadsheets.py
|
ReplaceText(target='cmp' @(309,52)->(309,55))
|
def fill_spreadsheets(projdir=False, sorteddir=False, sheetsdir=False):
if vsc in df:
df[vsc].to_excel(writer, sheet_name=vsc, startrow=6)
if cmp in df:
df[cmp].to_excel(writer, sheet_name=vsc, startrow=6)
return
|
def fill_spreadsheets(projdir=False, sorteddir=False, sheetsdir=False):
if vsc in df:
df[vsc].to_excel(writer, sheet_name=vsc, startrow=6)
if cmp in df:
df[cmp].to_excel(writer, sheet_name=cmp, startrow=6)
return
|
442 |
https://:@github.com/EntilZha/ScalaFunctional.git
|
8426ff978b84cb4125052ad842ae5db64eaf42f3
|
@@ -185,6 +185,6 @@ class TestStreams(unittest.TestCase):
# test insert into a connection
with sqlite3.connect(tmp_path) as conn:
- seq(elements).to_sqlite3(tmp_path, insert_sql)
+ seq(elements).to_sqlite3(conn, insert_sql)
result = seq.sqlite3(conn, "SELECT id, name FROM user;").to_list()
self.assertListEqual(elements, result)
|
functional/test/test_streams.py
|
ReplaceText(target='conn' @(188,37)->(188,45))
|
class TestStreams(unittest.TestCase):
# test insert into a connection
with sqlite3.connect(tmp_path) as conn:
seq(elements).to_sqlite3(tmp_path, insert_sql)
result = seq.sqlite3(conn, "SELECT id, name FROM user;").to_list()
self.assertListEqual(elements, result)
|
class TestStreams(unittest.TestCase):
# test insert into a connection
with sqlite3.connect(tmp_path) as conn:
seq(elements).to_sqlite3(conn, insert_sql)
result = seq.sqlite3(conn, "SELECT id, name FROM user;").to_list()
self.assertListEqual(elements, result)
|
443 |
https://:@github.com/wesselb/stheno.git
|
32d55bf855f88067e689684eaa5d6f9e8c7604d6
|
@@ -80,7 +80,7 @@ class Kernel(Referentiable):
def feat_map(x):
scale = 2 * B.pi / B.cast(period, x.dtype)
return B.concatenate((B.sin(x * scale),
- B.cos(x * scale)), axis=0)
+ B.cos(x * scale)), axis=1)
return Kernel(lambda x, y: self.f(feat_map(x), feat_map(y)))
|
stheno/kernel.py
|
ReplaceText(target='1' @(83,59)->(83,60))
|
class Kernel(Referentiable):
def feat_map(x):
scale = 2 * B.pi / B.cast(period, x.dtype)
return B.concatenate((B.sin(x * scale),
B.cos(x * scale)), axis=0)
return Kernel(lambda x, y: self.f(feat_map(x), feat_map(y)))
|
class Kernel(Referentiable):
def feat_map(x):
scale = 2 * B.pi / B.cast(period, x.dtype)
return B.concatenate((B.sin(x * scale),
B.cos(x * scale)), axis=1)
return Kernel(lambda x, y: self.f(feat_map(x), feat_map(y)))
|
444 |
https://:@github.com/djgagne/hagelslag.git
|
7ef4f68645a7b7146f21813f2b39a0a7208b0fdb
|
@@ -19,7 +19,7 @@ class Watershed(object):
self.max_intensity = max_intensity
def label(self, data):
- core_labels, n_labels = label(data <= self.max_intensity)
+ core_labels, n_labels = label(data >= self.max_intensity)
ws_labels = watershed(data.max() - data, markers=core_labels, mask=data >= self.min_intensity)
return ws_labels
|
hagelslag/processing/Watershed.py
|
ReplaceText(target='>=' @(22,43)->(22,45))
|
class Watershed(object):
self.max_intensity = max_intensity
def label(self, data):
core_labels, n_labels = label(data <= self.max_intensity)
ws_labels = watershed(data.max() - data, markers=core_labels, mask=data >= self.min_intensity)
return ws_labels
|
class Watershed(object):
self.max_intensity = max_intensity
def label(self, data):
core_labels, n_labels = label(data >= self.max_intensity)
ws_labels = watershed(data.max() - data, markers=core_labels, mask=data >= self.min_intensity)
return ws_labels
|
445 |
https://:@github.com/djgagne/hagelslag.git
|
28dbda86b4244802a1651a808dfcfe0dbdeb62e3
|
@@ -19,7 +19,7 @@ class Watershed(object):
self.max_intensity = max_intensity
def label(self, data):
- core_labels, n_labels = label(data >= self.max_intensity)
+ core_labels, n_labels = label(data <= self.max_intensity)
ws_labels = watershed(data.max() - data, markers=core_labels, mask=data >= self.min_intensity)
return ws_labels
|
hagelslag/processing/Watershed.py
|
ReplaceText(target='<=' @(22,43)->(22,45))
|
class Watershed(object):
self.max_intensity = max_intensity
def label(self, data):
core_labels, n_labels = label(data >= self.max_intensity)
ws_labels = watershed(data.max() - data, markers=core_labels, mask=data >= self.min_intensity)
return ws_labels
|
class Watershed(object):
self.max_intensity = max_intensity
def label(self, data):
core_labels, n_labels = label(data <= self.max_intensity)
ws_labels = watershed(data.max() - data, markers=core_labels, mask=data >= self.min_intensity)
return ws_labels
|
446 |
https://:@github.com/djgagne/hagelslag.git
|
be189c11c1135f782bb30529f58dff78e99f4c8e
|
@@ -19,7 +19,7 @@ class Watershed(object):
self.max_intensity = max_intensity
def label(self, data):
- core_labels, n_labels = label(data <= self.max_intensity)
+ core_labels, n_labels = label(data >= self.max_intensity)
ws_labels = watershed(data.max() - data, markers=core_labels, mask=data >= self.min_intensity)
return ws_labels
|
hagelslag/processing/Watershed.py
|
ReplaceText(target='>=' @(22,43)->(22,45))
|
class Watershed(object):
self.max_intensity = max_intensity
def label(self, data):
core_labels, n_labels = label(data <= self.max_intensity)
ws_labels = watershed(data.max() - data, markers=core_labels, mask=data >= self.min_intensity)
return ws_labels
|
class Watershed(object):
self.max_intensity = max_intensity
def label(self, data):
core_labels, n_labels = label(data >= self.max_intensity)
ws_labels = watershed(data.max() - data, markers=core_labels, mask=data >= self.min_intensity)
return ws_labels
|
447 |
https://:@github.com/ICRAR/daliuge.git
|
72b08c308f61bc4e9006976fc9e63f3638fad9e8
|
@@ -604,7 +604,7 @@ def chiles_pg():
total_bandwidth = 480
num_obs = 8 # the same as num of data island
subband_width = 60 # MHz
- num_subb = total_bandwidth / subband_width
+ num_subb = total_bandwidth // subband_width
subband_dict = collections.defaultdict(list) # for corner turning
img_list = []
start_freq = 940
|
test/graphsRepository.py
|
ReplaceText(target='//' @(607,31)->(607,32))
|
def chiles_pg():
total_bandwidth = 480
num_obs = 8 # the same as num of data island
subband_width = 60 # MHz
num_subb = total_bandwidth / subband_width
subband_dict = collections.defaultdict(list) # for corner turning
img_list = []
start_freq = 940
|
def chiles_pg():
total_bandwidth = 480
num_obs = 8 # the same as num of data island
subband_width = 60 # MHz
num_subb = total_bandwidth // subband_width
subband_dict = collections.defaultdict(list) # for corner turning
img_list = []
start_freq = 940
|
448 |
https://:@github.com/ICRAR/daliuge.git
|
00eb7a92f6679df09650e2e8054e9163f0089785
|
@@ -115,7 +115,7 @@ class TestDM(unittest.TestCase):
a.setCompleted()
for dm, drop in (dm1,a), (dm2,b), (dm2,c):
- self.assertEqual(DROPStates.COMPLETED, dm.get_drop_property(sessionId, 'status', drop.uid))
+ self.assertEqual(DROPStates.COMPLETED, dm.get_drop_property(sessionId, drop.uid, 'status'))
self.assertEqual(a.checksum, int(droputils.allDropContents(c)))
for dropProxy in a,b,c:
|
test/manager/test_dm.py
|
ArgSwap(idxs=1<->2 @(118,51)->(118,71))
|
class TestDM(unittest.TestCase):
a.setCompleted()
for dm, drop in (dm1,a), (dm2,b), (dm2,c):
self.assertEqual(DROPStates.COMPLETED, dm.get_drop_property(sessionId, 'status', drop.uid))
self.assertEqual(a.checksum, int(droputils.allDropContents(c)))
for dropProxy in a,b,c:
|
class TestDM(unittest.TestCase):
a.setCompleted()
for dm, drop in (dm1,a), (dm2,b), (dm2,c):
self.assertEqual(DROPStates.COMPLETED, dm.get_drop_property(sessionId, drop.uid, 'status'))
self.assertEqual(a.checksum, int(droputils.allDropContents(c)))
for dropProxy in a,b,c:
|
449 |
https://:@github.com/ICRAR/daliuge.git
|
a45bf6f0b7e2fa2627b7e4faa18324aa1087d8f5
|
@@ -167,7 +167,7 @@ class DockerTests(unittest.TestCase):
c = FileDROP('c', 'c')
b.addInput(a)
b.addOutput(c)
- with DROPWaiterCtx(self, b, 100):
+ with DROPWaiterCtx(self, c, 100):
a.setCompleted()
self.assertEqual(six.b(a.dataURL), droputils.allDropContents(c))
|
test/apps/test_docker.py
|
ReplaceText(target='c' @(170,33)->(170,34))
|
class DockerTests(unittest.TestCase):
c = FileDROP('c', 'c')
b.addInput(a)
b.addOutput(c)
with DROPWaiterCtx(self, b, 100):
a.setCompleted()
self.assertEqual(six.b(a.dataURL), droputils.allDropContents(c))
|
class DockerTests(unittest.TestCase):
c = FileDROP('c', 'c')
b.addInput(a)
b.addOutput(c)
with DROPWaiterCtx(self, c, 100):
a.setCompleted()
self.assertEqual(six.b(a.dataURL), droputils.allDropContents(c))
|
450 |
https://:@github.com/ICRAR/daliuge.git
|
882b2feb9672662c5347bf0b11ce06b0e7529be8
|
@@ -512,7 +512,7 @@ class LogParser(object):
for dim_log_f in possible_logs:
if (os.path.exists(dim_log_f)):
self._dim_log_f = [dim_log_f]
- if (dim_log_f == possible_logs[1]):
+ if (dim_log_f == possible_logs[0]):
cluster_log = os.path.join(log_dir, '0', 'start_dlg_cluster.log')
if (os.path.exists(cluster_log)):
self._dim_log_f.append(cluster_log)
|
dlg/deploy/pawsey/scale_test.py
|
ReplaceText(target='0' @(515,47)->(515,48))
|
class LogParser(object):
for dim_log_f in possible_logs:
if (os.path.exists(dim_log_f)):
self._dim_log_f = [dim_log_f]
if (dim_log_f == possible_logs[1]):
cluster_log = os.path.join(log_dir, '0', 'start_dlg_cluster.log')
if (os.path.exists(cluster_log)):
self._dim_log_f.append(cluster_log)
|
class LogParser(object):
for dim_log_f in possible_logs:
if (os.path.exists(dim_log_f)):
self._dim_log_f = [dim_log_f]
if (dim_log_f == possible_logs[0]):
cluster_log = os.path.join(log_dir, '0', 'start_dlg_cluster.log')
if (os.path.exists(cluster_log)):
self._dim_log_f.append(cluster_log)
|
451 |
https://:@github.com/ICRAR/daliuge.git
|
f1204971537d6fa5e972cd96c963f907166dd291
|
@@ -952,7 +952,7 @@ class KFamilyPartition(Partition):
kwargs['weight'] = self_global_dag.node[u].get('weight', 5)
self._dag.add_node(u, **kwargs)
for k in self._w_attr:
- self._tmp_max_dop[_w_attr] = get_max_weighted_antichain(self._dag, w_attr=k)[0]
+ self._tmp_max_dop[k] = get_max_weighted_antichain(self._dag, w_attr=k)[0]
self._max_dop = self._tmp_max_dop
def can_merge(self, that, u, v):
|
dlg/dropmake/scheduler.py
|
ReplaceText(target='k' @(955,30)->(955,37))
|
class KFamilyPartition(Partition):
kwargs['weight'] = self_global_dag.node[u].get('weight', 5)
self._dag.add_node(u, **kwargs)
for k in self._w_attr:
self._tmp_max_dop[_w_attr] = get_max_weighted_antichain(self._dag, w_attr=k)[0]
self._max_dop = self._tmp_max_dop
def can_merge(self, that, u, v):
|
class KFamilyPartition(Partition):
kwargs['weight'] = self_global_dag.node[u].get('weight', 5)
self._dag.add_node(u, **kwargs)
for k in self._w_attr:
self._tmp_max_dop[k] = get_max_weighted_antichain(self._dag, w_attr=k)[0]
self._max_dop = self._tmp_max_dop
def can_merge(self, that, u, v):
|
452 |
https://:@github.com/ICRAR/daliuge.git
|
6a91d4338a9a90bc2413e4e78c9ed8ca02264ae4
|
@@ -2225,7 +2225,7 @@ def partition(pgt, algo, num_partitions=1, num_islands=1,
elif algo == ALGO_MIN_NUM_PARTS:
time_greedy = 1 - time_greedy / 100.0 # assuming between 1 to 100
- pgt = MinNumPartsPGTP(pgt, deadline, num_partitions, partition_label, max_dop, merge_parts=could_merge, optimistic_factor=time_greedy)
+ pgt = MinNumPartsPGTP(pgt, deadline, num_partitions, partition_label, max_cpu, merge_parts=could_merge, optimistic_factor=time_greedy)
elif algo == ALGO_PSO:
pgt = PSOPGTP(pgt, partition_label, max_dop, deadline=deadline, topk=topk, swarm_size=swarm_size, merge_parts=could_merge)
|
dlg/dropmake/pg_generator.py
|
ReplaceText(target='max_cpu' @(2228,79)->(2228,86))
|
def partition(pgt, algo, num_partitions=1, num_islands=1,
elif algo == ALGO_MIN_NUM_PARTS:
time_greedy = 1 - time_greedy / 100.0 # assuming between 1 to 100
pgt = MinNumPartsPGTP(pgt, deadline, num_partitions, partition_label, max_dop, merge_parts=could_merge, optimistic_factor=time_greedy)
elif algo == ALGO_PSO:
pgt = PSOPGTP(pgt, partition_label, max_dop, deadline=deadline, topk=topk, swarm_size=swarm_size, merge_parts=could_merge)
|
def partition(pgt, algo, num_partitions=1, num_islands=1,
elif algo == ALGO_MIN_NUM_PARTS:
time_greedy = 1 - time_greedy / 100.0 # assuming between 1 to 100
pgt = MinNumPartsPGTP(pgt, deadline, num_partitions, partition_label, max_cpu, merge_parts=could_merge, optimistic_factor=time_greedy)
elif algo == ALGO_PSO:
pgt = PSOPGTP(pgt, partition_label, max_dop, deadline=deadline, topk=topk, swarm_size=swarm_size, merge_parts=could_merge)
|
453 |
https://:@github.com/ICRAR/daliuge.git
|
885ea31e59129d694329161da7acf7e8f2654348
|
@@ -96,7 +96,7 @@ def check_hosts(ips, port, timeout=None, check_with_session=False, retry=1):
logger.info("Host %s:%d is running", ip, port)
return ip
logger.warning("Failed to contact host %s:%d", ip, port)
- ntries -= 0
+ ntries -= 1
return None
# Don't return None values
|
dlg/deploy/pawsey/start_dfms_cluster.py
|
ReplaceText(target='1' @(99,22)->(99,23))
|
def check_hosts(ips, port, timeout=None, check_with_session=False, retry=1):
logger.info("Host %s:%d is running", ip, port)
return ip
logger.warning("Failed to contact host %s:%d", ip, port)
ntries -= 0
return None
# Don't return None values
|
def check_hosts(ips, port, timeout=None, check_with_session=False, retry=1):
logger.info("Host %s:%d is running", ip, port)
return ip
logger.warning("Failed to contact host %s:%d", ip, port)
ntries -= 1
return None
# Don't return None values
|
454 |
https://:@github.com/ICRAR/daliuge.git
|
ca615527deef8c147aaad3c64755b5f3d89b65b8
|
@@ -56,7 +56,7 @@ def timed_import(module_name):
"""Imports `module_name` and log how long it took to import it"""
start = time.time()
module = importlib.import_module(module_name)
- logger.info('Imported %s in %.3f seconds', module, time.time() - start)
+ logger.info('Imported %s in %.3f seconds', module_name, time.time() - start)
return module
|
dlg/utils.py
|
ReplaceText(target='module_name' @(59,47)->(59,53))
|
def timed_import(module_name):
"""Imports `module_name` and log how long it took to import it"""
start = time.time()
module = importlib.import_module(module_name)
logger.info('Imported %s in %.3f seconds', module, time.time() - start)
return module
|
def timed_import(module_name):
"""Imports `module_name` and log how long it took to import it"""
start = time.time()
module = importlib.import_module(module_name)
logger.info('Imported %s in %.3f seconds', module_name, time.time() - start)
return module
|
455 |
https://:@github.com/JRCSTU/co2mpas-ta.git
|
8e8557c3590acc6942bcabc7167de3767681e48b
|
@@ -419,7 +419,7 @@ def define_alternator_status_model(
if soc < dn_soc or (prev_status == 1 and soc < up_soc):
status = 1
- elif has_energy_recuperation and gear_box_power_in >= 0:
+ elif has_energy_recuperation and gear_box_power_in < 0:
status = 2
return status
|
co2mpas/functions/physical/electrics/__init__.py
|
ReplaceText(target='<' @(422,63)->(422,65))
|
def define_alternator_status_model(
if soc < dn_soc or (prev_status == 1 and soc < up_soc):
status = 1
elif has_energy_recuperation and gear_box_power_in >= 0:
status = 2
return status
|
def define_alternator_status_model(
if soc < dn_soc or (prev_status == 1 and soc < up_soc):
status = 1
elif has_energy_recuperation and gear_box_power_in < 0:
status = 2
return status
|
456 |
https://:@github.com/JRCSTU/co2mpas-ta.git
|
b155780da4cd2489da6c06da12e0c4df41534ab5
|
@@ -2766,8 +2766,8 @@ class Dispatcher(object):
elif node_id in dists: # The node w already estimated.
if dist < dists[node_id]: # Error for negative paths.
- raise DispatcherError('Contradictory paths found: '
- 'negative weights?', self)
+ raise DispatcherError(self, 'Contradictory paths found: '
+ 'negative weights?')
elif node_id not in seen or dist < seen[node_id]: # Check min dist.
seen[node_id] = dist # Update dist.
|
co2mpas/dispatcher/__init__.py
|
ArgSwap(idxs=0<->1 @(2769,22)->(2769,37))
|
class Dispatcher(object):
elif node_id in dists: # The node w already estimated.
if dist < dists[node_id]: # Error for negative paths.
raise DispatcherError('Contradictory paths found: '
'negative weights?', self)
elif node_id not in seen or dist < seen[node_id]: # Check min dist.
seen[node_id] = dist # Update dist.
|
class Dispatcher(object):
elif node_id in dists: # The node w already estimated.
if dist < dists[node_id]: # Error for negative paths.
raise DispatcherError(self, 'Contradictory paths found: '
'negative weights?')
elif node_id not in seen or dist < seen[node_id]: # Check min dist.
seen[node_id] = dist # Update dist.
|
457 |
https://:@github.com/JRCSTU/co2mpas-ta.git
|
46830a3edd1490d499b8f0e788ce87efe873d264
|
@@ -225,7 +225,7 @@ def _predict_electrics(
alternator_current = calculate_alternator_current(
alternator_status, on_engine, gear_box_power_in,
alternator_current_model, engine_start_current,
- prev_battery_current, acceleration)
+ battery_state_of_charge, acceleration)
battery_current = calculate_battery_current(
electric_load, alternator_current, alternator_nominal_voltage,
|
co2mpas/functions/co2mpas_model/physical/electrics/electrics_prediction.py
|
ReplaceText(target='battery_state_of_charge' @(228,8)->(228,28))
|
def _predict_electrics(
alternator_current = calculate_alternator_current(
alternator_status, on_engine, gear_box_power_in,
alternator_current_model, engine_start_current,
prev_battery_current, acceleration)
battery_current = calculate_battery_current(
electric_load, alternator_current, alternator_nominal_voltage,
|
def _predict_electrics(
alternator_current = calculate_alternator_current(
alternator_status, on_engine, gear_box_power_in,
alternator_current_model, engine_start_current,
battery_state_of_charge, acceleration)
battery_current = calculate_battery_current(
electric_load, alternator_current, alternator_nominal_voltage,
|
458 |
https://:@github.com/JRCSTU/co2mpas-ta.git
|
45e4f0782888c84b9c99842db88457353b45efb3
|
@@ -240,7 +240,7 @@ def define_data_schema(read=True):
'f0_uncorrected': positive,
'f2': positive,
'f0': positive,
- 'correct_f0': positive,
+ 'correct_f0': _bool,
'co2_emission_low': positive,
'co2_emission_medium': positive,
|
co2mpas/functions/io/schema.py
|
ReplaceText(target='_bool' @(243,22)->(243,30))
|
def define_data_schema(read=True):
'f0_uncorrected': positive,
'f2': positive,
'f0': positive,
'correct_f0': positive,
'co2_emission_low': positive,
'co2_emission_medium': positive,
|
def define_data_schema(read=True):
'f0_uncorrected': positive,
'f2': positive,
'f0': positive,
'correct_f0': _bool,
'co2_emission_low': positive,
'co2_emission_medium': positive,
|
459 |
https://:@github.com/JRCSTU/co2mpas-ta.git
|
3fcd6ce4395980ea879bde8f1270e390e750a8ee
|
@@ -3020,7 +3020,7 @@ class Dispatcher(object):
self._meet[dsp_id] = initial_dist # Set view distance.
# Check if inputs are satisfied.
- if self.check_wait_in(node['wait_inputs'], node_id):
+ if self.check_wait_in(node['wait_inputs'], dsp_id):
return False # Pass the node
if dsp_id not in distances:
|
co2mpas/dispatcher/__init__.py
|
ReplaceText(target='dsp_id' @(3023,51)->(3023,58))
|
class Dispatcher(object):
self._meet[dsp_id] = initial_dist # Set view distance.
# Check if inputs are satisfied.
if self.check_wait_in(node['wait_inputs'], node_id):
return False # Pass the node
if dsp_id not in distances:
|
class Dispatcher(object):
self._meet[dsp_id] = initial_dist # Set view distance.
# Check if inputs are satisfied.
if self.check_wait_in(node['wait_inputs'], dsp_id):
return False # Pass the node
if dsp_id not in distances:
|
460 |
https://:@github.com/JRCSTU/co2mpas-ta.git
|
e3346285e51b0bba0d909746146e0be70c3090eb
|
@@ -87,7 +87,7 @@ def calculate_full_load(full_load_speeds, full_load_powers, idle_engine_speed):
"""
pn = np.array((full_load_speeds, full_load_powers))
- max_speed_at_max_power, max_power = pn[:, np.argmax(pn[0])]
+ max_speed_at_max_power, max_power = pn[:, np.argmax(pn[1])]
pn[1] /= max_power
idle = idle_engine_speed[0]
pn[0] = (pn[0] - idle) / (max_speed_at_max_power - idle)
|
co2mpas/model/physical/engine/__init__.py
|
ReplaceText(target='1' @(90,59)->(90,60))
|
def calculate_full_load(full_load_speeds, full_load_powers, idle_engine_speed):
"""
pn = np.array((full_load_speeds, full_load_powers))
max_speed_at_max_power, max_power = pn[:, np.argmax(pn[0])]
pn[1] /= max_power
idle = idle_engine_speed[0]
pn[0] = (pn[0] - idle) / (max_speed_at_max_power - idle)
|
def calculate_full_load(full_load_speeds, full_load_powers, idle_engine_speed):
"""
pn = np.array((full_load_speeds, full_load_powers))
max_speed_at_max_power, max_power = pn[:, np.argmax(pn[1])]
pn[1] /= max_power
idle = idle_engine_speed[0]
pn[0] = (pn[0] - idle) / (max_speed_at_max_power - idle)
|
461 |
https://:@github.com/JRCSTU/co2mpas-ta.git
|
4154efcd8980a1790f2675afa14803991b4da76e
|
@@ -1223,7 +1223,7 @@ def calibrate_co2_params(
p = restrict_bounds(p)
- p, s = calibrate_model_params(co2_error_function_on_phases, p)
+ p, s = calibrate_model_params(co2_error_function_on_emissions, p)
success.append((s, copy.deepcopy(p)))
_set_attr(p, vary)
|
co2mpas/model/physical/engine/co2_emission.py
|
ReplaceText(target='co2_error_function_on_emissions' @(1226,34)->(1226,62))
|
def calibrate_co2_params(
p = restrict_bounds(p)
p, s = calibrate_model_params(co2_error_function_on_phases, p)
success.append((s, copy.deepcopy(p)))
_set_attr(p, vary)
|
def calibrate_co2_params(
p = restrict_bounds(p)
p, s = calibrate_model_params(co2_error_function_on_emissions, p)
success.append((s, copy.deepcopy(p)))
_set_attr(p, vary)
|
462 |
https://:@github.com/JRCSTU/co2mpas-ta.git
|
4c077512de9127f377b3802d2c82fe8ebd56f5c2
|
@@ -703,7 +703,7 @@ def define_data_schema(read=True):
'alternator_powers_demand': np_array,
'alternator_statuses': np_array_int,
'auxiliaries_power_losses': np_array,
- 'auxiliaries_torque_loss': positive,
+ 'auxiliaries_torque_loss': tuplefloat,
'auxiliaries_torque_losses': np_array,
'battery_currents': np_array,
'clutch_tc_powers': np_array,
|
co2mpas/io/schema.py
|
ReplaceText(target='tuplefloat' @(706,35)->(706,43))
|
def define_data_schema(read=True):
'alternator_powers_demand': np_array,
'alternator_statuses': np_array_int,
'auxiliaries_power_losses': np_array,
'auxiliaries_torque_loss': positive,
'auxiliaries_torque_losses': np_array,
'battery_currents': np_array,
'clutch_tc_powers': np_array,
|
def define_data_schema(read=True):
'alternator_powers_demand': np_array,
'alternator_statuses': np_array_int,
'auxiliaries_power_losses': np_array,
'auxiliaries_torque_loss': tuplefloat,
'auxiliaries_torque_losses': np_array,
'battery_currents': np_array,
'clutch_tc_powers': np_array,
|
463 |
https://:@github.com/JRCSTU/co2mpas-ta.git
|
274f898a173aa42185fa5ef138035b4cb5994d28
|
@@ -74,7 +74,7 @@ class TestGearBox(unittest.TestCase):
def test_calculate_torque_out(self):
wp, es, gbs = self.wp, self.es, self.ws
self.assertEquals(
- list(calculate_gear_box_torques(wp, es, gbs, 10)), list(self.tgb)
+ list(calculate_gear_box_torques(wp, gbs, es, 10)), list(self.tgb)
)
@unittest.skip("to be reviewed")
|
tests/functions/test_gear_box.py
|
ArgSwap(idxs=1<->2 @(77,17)->(77,43))
|
class TestGearBox(unittest.TestCase):
def test_calculate_torque_out(self):
wp, es, gbs = self.wp, self.es, self.ws
self.assertEquals(
list(calculate_gear_box_torques(wp, es, gbs, 10)), list(self.tgb)
)
@unittest.skip("to be reviewed")
|
class TestGearBox(unittest.TestCase):
def test_calculate_torque_out(self):
wp, es, gbs = self.wp, self.es, self.ws
self.assertEquals(
list(calculate_gear_box_torques(wp, gbs, es, 10)), list(self.tgb)
)
@unittest.skip("to be reviewed")
|
464 |
https://:@github.com/JRCSTU/co2mpas-ta.git
|
739964622f68661a4dc35b8a60a30db5cb8475b2
|
@@ -2608,7 +2608,7 @@ class Co2guiCmd(cmdlets.Cmd):
progr_bar.grid(column=1, row=1, sticky='nswe')
if step is not None:
- if step < 0:
+ if step <= 0:
progr_var.set(-step)
else:
progr_var.set(progr_var.get() + step)
|
co2mpas/co2gui/__init__.py
|
ReplaceText(target='<=' @(2611,20)->(2611,21))
|
class Co2guiCmd(cmdlets.Cmd):
progr_bar.grid(column=1, row=1, sticky='nswe')
if step is not None:
if step < 0:
progr_var.set(-step)
else:
progr_var.set(progr_var.get() + step)
|
class Co2guiCmd(cmdlets.Cmd):
progr_bar.grid(column=1, row=1, sticky='nswe')
if step is not None:
if step <= 0:
progr_var.set(-step)
else:
progr_var.set(progr_var.get() + step)
|
465 |
https://:@github.com/JRCSTU/co2mpas-ta.git
|
18af1fede3536121930c99ea0a2c94e8ffeb3bf7
|
@@ -450,6 +450,6 @@ def calculate_drive_battery_currents_v2(
n_p, n_s = drive_battery_n_parallel_cells, drive_battery_n_series_cells
p = drive_battery_electric_powers
r0, ocv = drive_battery_r0, drive_battery_ocv
- x = ocv + np.nan_to_num(np.sqrt(ocv ** 2 - (4e3 * r0 / (n_s * n_p)) * p))
+ x = ocv - np.nan_to_num(np.sqrt(ocv ** 2 - (4e3 * r0 / (n_s * n_p)) * p))
x *= n_p / (2 * r0)
return x
|
co2mpas/core/model/physical/electrics/batteries/drive.py
|
ReplaceText(target='-' @(453,12)->(453,13))
|
def calculate_drive_battery_currents_v2(
n_p, n_s = drive_battery_n_parallel_cells, drive_battery_n_series_cells
p = drive_battery_electric_powers
r0, ocv = drive_battery_r0, drive_battery_ocv
x = ocv + np.nan_to_num(np.sqrt(ocv ** 2 - (4e3 * r0 / (n_s * n_p)) * p))
x *= n_p / (2 * r0)
return x
|
def calculate_drive_battery_currents_v2(
n_p, n_s = drive_battery_n_parallel_cells, drive_battery_n_series_cells
p = drive_battery_electric_powers
r0, ocv = drive_battery_r0, drive_battery_ocv
x = ocv - np.nan_to_num(np.sqrt(ocv ** 2 - (4e3 * r0 / (n_s * n_p)) * p))
x *= n_p / (2 * r0)
return x
|
466 |
https://:@github.com/JRCSTU/co2mpas-ta.git
|
8f4cfb4afa97fc43a95b62b497f182fd72b0e379
|
@@ -263,7 +263,7 @@ def calculate_service_battery_loads(
Service battery load vector [kW].
:rtype: numpy.array
"""
- p = service_battery_electric_powers - service_battery_electric_powers_supply
+ p = service_battery_electric_powers + service_battery_electric_powers_supply
return p
|
co2mpas/core/model/physical/electrics/batteries/service/__init__.py
|
ReplaceText(target='+' @(266,40)->(266,41))
|
def calculate_service_battery_loads(
Service battery load vector [kW].
:rtype: numpy.array
"""
p = service_battery_electric_powers - service_battery_electric_powers_supply
return p
|
def calculate_service_battery_loads(
Service battery load vector [kW].
:rtype: numpy.array
"""
p = service_battery_electric_powers + service_battery_electric_powers_supply
return p
|
467 |
https://:@github.com/JRCSTU/co2mpas-ta.git
|
52695d79acea053f5ff38a8a5d223f1907d33fb8
|
@@ -46,7 +46,7 @@ def calculate_final_drive_ratios(final_drive_ratio, n_gears=1):
# noinspection PyUnusedLocal,PyMissingOrEmptyDocstring
def is_not_manual_or_automatic(gear_box_type, *args):
- return gear_box_type in ('manual', 'automatic')
+ return gear_box_type not in ('manual', 'automatic')
dsp.add_function(
|
co2mpas/core/model/physical/final_drive.py
|
ReplaceText(target=' not in ' @(49,24)->(49,28))
|
def calculate_final_drive_ratios(final_drive_ratio, n_gears=1):
# noinspection PyUnusedLocal,PyMissingOrEmptyDocstring
def is_not_manual_or_automatic(gear_box_type, *args):
return gear_box_type in ('manual', 'automatic')
dsp.add_function(
|
def calculate_final_drive_ratios(final_drive_ratio, n_gears=1):
# noinspection PyUnusedLocal,PyMissingOrEmptyDocstring
def is_not_manual_or_automatic(gear_box_type, *args):
return gear_box_type not in ('manual', 'automatic')
dsp.add_function(
|
468 |
https://:@github.com/JRCSTU/co2mpas-ta.git
|
401ec07523c5b34dacab9e73cf9a417dada880cb
|
@@ -429,7 +429,7 @@ class CorrectGear:
# 3.2
j = i + np.searchsorted(times[i:], times[i] + 1)
- if not gear and up_clip(velocities, j + 1) >= up_clip(velocities, j):
+ if not gear and up_clip(velocities, j + 1) > up_clip(velocities, j):
gear = self.min_gear
return gear
|
co2mpas/core/model/physical/gear_box/at_gear/__init__.py
|
ReplaceText(target='>' @(432,51)->(432,53))
|
class CorrectGear:
# 3.2
j = i + np.searchsorted(times[i:], times[i] + 1)
if not gear and up_clip(velocities, j + 1) >= up_clip(velocities, j):
gear = self.min_gear
return gear
|
class CorrectGear:
# 3.2
j = i + np.searchsorted(times[i:], times[i] + 1)
if not gear and up_clip(velocities, j + 1) > up_clip(velocities, j):
gear = self.min_gear
return gear
|
469 |
https://:@github.com/JRCSTU/co2mpas-ta.git
|
745c3623fffca5cf7f84358f8fff87287a35525c
|
@@ -125,7 +125,7 @@ def define_tau_function(after_treatment_temperature_threshold):
f = sci_sta.lognorm(max(s, dfl.EPS), 0, temp_mean).cdf
def _tau_function(t0, t1, temp):
- return t0 - (t1 - t0) * f(temp + 273)
+ return t0 + (t1 - t0) * f(temp + 273)
return _tau_function
|
co2mpas/core/model/physical/engine/fc.py
|
ReplaceText(target='+' @(128,18)->(128,19))
|
def define_tau_function(after_treatment_temperature_threshold):
f = sci_sta.lognorm(max(s, dfl.EPS), 0, temp_mean).cdf
def _tau_function(t0, t1, temp):
return t0 - (t1 - t0) * f(temp + 273)
return _tau_function
|
def define_tau_function(after_treatment_temperature_threshold):
f = sci_sta.lognorm(max(s, dfl.EPS), 0, temp_mean).cdf
def _tau_function(t0, t1, temp):
return t0 + (t1 - t0) * f(temp + 273)
return _tau_function
|
470 |
https://:@github.com/RasaHQ/rasa.git
|
57d15923475ec8b5361cd6f84f327d864253746a
|
@@ -33,7 +33,7 @@ def run_train(_config):
def load_interpreter_for_model(nlp, config, persisted_path):
metadata = DataRouter.read_model_metadata(persisted_path, config)
- return DataRouter.create_interpreter(nlp, metadata)
+ return DataRouter.create_interpreter(metadata, nlp)
class ResponseTest(object):
|
_pytest/utilities.py
|
ArgSwap(idxs=0<->1 @(36,11)->(36,40))
|
def run_train(_config):
def load_interpreter_for_model(nlp, config, persisted_path):
metadata = DataRouter.read_model_metadata(persisted_path, config)
return DataRouter.create_interpreter(nlp, metadata)
class ResponseTest(object):
|
def run_train(_config):
def load_interpreter_for_model(nlp, config, persisted_path):
metadata = DataRouter.read_model_metadata(persisted_path, config)
return DataRouter.create_interpreter(metadata, nlp)
class ResponseTest(object):
|
471 |
https://:@github.com/RasaHQ/rasa.git
|
bb0b24e56a97affbfa3db91be71782f293e9e5c2
|
@@ -29,7 +29,7 @@ def test_luis_data_without_tokenizer():
def test_wit_data():
td = load_data('data/examples/wit/demo-flights.json', "en")
assert td.entity_examples != []
- assert td.intent_examples != []
+ assert td.intent_examples == []
assert td.entity_synonyms == {}
|
_pytest/test_training_data.py
|
ReplaceText(target='==' @(32,30)->(32,32))
|
def test_luis_data_without_tokenizer():
def test_wit_data():
td = load_data('data/examples/wit/demo-flights.json', "en")
assert td.entity_examples != []
assert td.intent_examples != []
assert td.entity_synonyms == {}
|
def test_luis_data_without_tokenizer():
def test_wit_data():
td = load_data('data/examples/wit/demo-flights.json', "en")
assert td.entity_examples != []
assert td.intent_examples == []
assert td.entity_synonyms == {}
|
472 |
https://:@github.com/RasaHQ/rasa.git
|
12484270fb8c3c271d74c5b3269f287eaf2d7cfb
|
@@ -84,7 +84,7 @@ class SklearnIntentClassifier(Component):
# dirty str fix because sklearn is expecting str not instance of basestr...
tuned_parameters = [{'C': [1, 2, 5, 10, 20, 100], 'kernel': [str('linear')]}]
- cv_splits = max(2, min(MAX_CV_FOLDS, np.min(np.bincount(y)) / 5)) # aim for at least 5 examples in each fold
+ cv_splits = max(2, min(MAX_CV_FOLDS, np.min(np.bincount(y)) // 5)) # aim for at least 5 examples in each fold
self.clf = GridSearchCV(SVC(C=1, probability=True),
param_grid=tuned_parameters, n_jobs=num_threads,
|
rasa_nlu/classifiers/sklearn_intent_classifier.py
|
ReplaceText(target='//' @(87,68)->(87,69))
|
class SklearnIntentClassifier(Component):
# dirty str fix because sklearn is expecting str not instance of basestr...
tuned_parameters = [{'C': [1, 2, 5, 10, 20, 100], 'kernel': [str('linear')]}]
cv_splits = max(2, min(MAX_CV_FOLDS, np.min(np.bincount(y)) / 5)) # aim for at least 5 examples in each fold
self.clf = GridSearchCV(SVC(C=1, probability=True),
param_grid=tuned_parameters, n_jobs=num_threads,
|
class SklearnIntentClassifier(Component):
# dirty str fix because sklearn is expecting str not instance of basestr...
tuned_parameters = [{'C': [1, 2, 5, 10, 20, 100], 'kernel': [str('linear')]}]
cv_splits = max(2, min(MAX_CV_FOLDS, np.min(np.bincount(y)) // 5)) # aim for at least 5 examples in each fold
self.clf = GridSearchCV(SVC(C=1, probability=True),
param_grid=tuned_parameters, n_jobs=num_threads,
|
473 |
https://:@github.com/RasaHQ/rasa.git
|
b5f9b6ad06ff52d75522b49c745f3e83c32ee7cd
|
@@ -135,7 +135,7 @@ class TrainingData(object):
logger.info("Training data stats: \n" +
"\t- intent examples: {} ({} distinct intents)\n".format(
self.num_intent_examples, len(different_intents)) +
- "\t- found intents: {}\n".format(list_to_str(different_entities)) +
+ "\t- found intents: {}\n".format(list_to_str(different_intents)) +
"\t- entity examples: {} ({} distinct entities)\n".format(
self.num_entity_examples, len(different_entities)) +
"\t- found entities: {}\n".format(list_to_str(different_entities)))
|
rasa_nlu/training_data.py
|
ReplaceText(target='different_intents' @(138,65)->(138,83))
|
class TrainingData(object):
logger.info("Training data stats: \n" +
"\t- intent examples: {} ({} distinct intents)\n".format(
self.num_intent_examples, len(different_intents)) +
"\t- found intents: {}\n".format(list_to_str(different_entities)) +
"\t- entity examples: {} ({} distinct entities)\n".format(
self.num_entity_examples, len(different_entities)) +
"\t- found entities: {}\n".format(list_to_str(different_entities)))
|
class TrainingData(object):
logger.info("Training data stats: \n" +
"\t- intent examples: {} ({} distinct intents)\n".format(
self.num_intent_examples, len(different_intents)) +
"\t- found intents: {}\n".format(list_to_str(different_intents)) +
"\t- entity examples: {} ({} distinct entities)\n".format(
self.num_entity_examples, len(different_entities)) +
"\t- found entities: {}\n".format(list_to_str(different_entities)))
|
474 |
https://:@github.com/RasaHQ/rasa.git
|
c5e10bd1c504146064183b6b87cfdf80d8617a4d
|
@@ -28,7 +28,7 @@ class MarkdownToRasa:
entities = []
utter = example_in_md
for regex in [ent_regex, ent_regex_with_value]:
- utter = re.sub(regex, r"\1", example_in_md) # [text](entity) -> text
+ utter = re.sub(regex, r"\1", utter) # [text](entity) -> text
ent_matches = re.finditer(regex, example_in_md)
for matchNum, match in enumerate(ent_matches):
if 'synonym' in match.groupdict():
|
rasa_nlu/utils/md_to_rasa.py
|
ReplaceText(target='utter' @(31,41)->(31,54))
|
class MarkdownToRasa:
entities = []
utter = example_in_md
for regex in [ent_regex, ent_regex_with_value]:
utter = re.sub(regex, r"\1", example_in_md) # [text](entity) -> text
ent_matches = re.finditer(regex, example_in_md)
for matchNum, match in enumerate(ent_matches):
if 'synonym' in match.groupdict():
|
class MarkdownToRasa:
entities = []
utter = example_in_md
for regex in [ent_regex, ent_regex_with_value]:
utter = re.sub(regex, r"\1", utter) # [text](entity) -> text
ent_matches = re.finditer(regex, example_in_md)
for matchNum, match in enumerate(ent_matches):
if 'synonym' in match.groupdict():
|
475 |
https://:@github.com/RasaHQ/rasa.git
|
571c59bc9fccca87aa1c29b56ddf874fce9b111a
|
@@ -87,9 +87,9 @@ class Metadata(object):
return []
def for_component(self, name, defaults=None):
- return config.component_config_from_pipeline(self.get('pipeline', []),
- name,
- defaults)
+ return config.component_config_from_pipeline(name,
+ self.get('pipeline', []),
+ defaults)
@property
def language(self):
|
rasa_nlu/model.py
|
ArgSwap(idxs=0<->1 @(90,15)->(90,52))
|
class Metadata(object):
return []
def for_component(self, name, defaults=None):
return config.component_config_from_pipeline(self.get('pipeline', []),
name,
defaults)
@property
def language(self):
|
class Metadata(object):
return []
def for_component(self, name, defaults=None):
return config.component_config_from_pipeline(name,
self.get('pipeline', []),
defaults)
@property
def language(self):
|
476 |
https://:@github.com/RasaHQ/rasa.git
|
9a06d81201ca84812540bc4128111c55e22ffca7
|
@@ -156,7 +156,7 @@ class RasaNLUModelConfig(object):
return json_to_string(self.__dict__, indent=4)
def for_component(self, name, defaults=None):
- return component_config_from_pipeline(self.pipeline, name, defaults)
+ return component_config_from_pipeline(name, self.pipeline, defaults)
@property
def component_names(self):
|
rasa_nlu/config.py
|
ArgSwap(idxs=0<->1 @(159,15)->(159,45))
|
class RasaNLUModelConfig(object):
return json_to_string(self.__dict__, indent=4)
def for_component(self, name, defaults=None):
return component_config_from_pipeline(self.pipeline, name, defaults)
@property
def component_names(self):
|
class RasaNLUModelConfig(object):
return json_to_string(self.__dict__, indent=4)
def for_component(self, name, defaults=None):
return component_config_from_pipeline(name, self.pipeline, defaults)
@property
def component_names(self):
|
477 |
https://:@github.com/RasaHQ/rasa.git
|
2d92ef4002144ec4b3d66bd911c26642e5ab698f
|
@@ -42,7 +42,7 @@ def create_argument_parser():
description='evaluates a dialogue model')
parent_parser = argparse.ArgumentParser(add_help=False)
add_args_to_parser(parent_parser)
- cli.arguments.add_model_and_story_group(parser,
+ cli.arguments.add_model_and_story_group(parent_parser,
allow_pretrained_model=False)
utils.add_logging_option_arguments(parent_parser)
subparsers = parser.add_subparsers(help='mode', dest='mode')
|
rasa_core/evaluate.py
|
ReplaceText(target='parent_parser' @(45,44)->(45,50))
|
def create_argument_parser():
description='evaluates a dialogue model')
parent_parser = argparse.ArgumentParser(add_help=False)
add_args_to_parser(parent_parser)
cli.arguments.add_model_and_story_group(parser,
allow_pretrained_model=False)
utils.add_logging_option_arguments(parent_parser)
subparsers = parser.add_subparsers(help='mode', dest='mode')
|
def create_argument_parser():
description='evaluates a dialogue model')
parent_parser = argparse.ArgumentParser(add_help=False)
add_args_to_parser(parent_parser)
cli.arguments.add_model_and_story_group(parent_parser,
allow_pretrained_model=False)
utils.add_logging_option_arguments(parent_parser)
subparsers = parser.add_subparsers(help='mode', dest='mode')
|
478 |
https://:@github.com/RasaHQ/rasa.git
|
665cf94ee30f44aac85e8ac3c5ed8b2b0694354a
|
@@ -49,7 +49,7 @@ def create_argument_parser():
description='evaluates a dialogue model')
parent_parser = argparse.ArgumentParser(add_help=False)
add_args_to_parser(parent_parser)
- cli.arguments.add_model_and_story_group(parser,
+ cli.arguments.add_model_and_story_group(parent_parser,
allow_pretrained_model=False)
utils.add_logging_option_arguments(parent_parser)
subparsers = parser.add_subparsers(help='mode', dest='mode')
|
rasa_core/evaluate.py
|
ReplaceText(target='parent_parser' @(52,44)->(52,50))
|
def create_argument_parser():
description='evaluates a dialogue model')
parent_parser = argparse.ArgumentParser(add_help=False)
add_args_to_parser(parent_parser)
cli.arguments.add_model_and_story_group(parser,
allow_pretrained_model=False)
utils.add_logging_option_arguments(parent_parser)
subparsers = parser.add_subparsers(help='mode', dest='mode')
|
def create_argument_parser():
description='evaluates a dialogue model')
parent_parser = argparse.ArgumentParser(add_help=False)
add_args_to_parser(parent_parser)
cli.arguments.add_model_and_story_group(parent_parser,
allow_pretrained_model=False)
utils.add_logging_option_arguments(parent_parser)
subparsers = parser.add_subparsers(help='mode', dest='mode')
|
479 |
https://:@github.com/RasaHQ/rasa.git
|
37f446c8246c78339727f7b09bd2021906ec8d60
|
@@ -174,7 +174,7 @@ def test_generate_training_data_original_and_augmented_trackers(
hasattr(t, 'is_augmented') or not t.is_augmented
]
assert len(original_trackers) == 3
- assert len(original_trackers) <= 33
+ assert len(training_trackers) <= 33
def test_visualize_training_data_graph(tmpdir, default_domain):
|
tests/test_dsl.py
|
ReplaceText(target='training_trackers' @(177,15)->(177,32))
|
def test_generate_training_data_original_and_augmented_trackers(
hasattr(t, 'is_augmented') or not t.is_augmented
]
assert len(original_trackers) == 3
assert len(original_trackers) <= 33
def test_visualize_training_data_graph(tmpdir, default_domain):
|
def test_generate_training_data_original_and_augmented_trackers(
hasattr(t, 'is_augmented') or not t.is_augmented
]
assert len(original_trackers) == 3
assert len(training_trackers) <= 33
def test_visualize_training_data_graph(tmpdir, default_domain):
|
480 |
https://:@github.com/RasaHQ/rasa.git
|
31ab3bb5d10a09f8957455909311257b257f44dc
|
@@ -218,7 +218,7 @@ class TestMemoizationPolicy(PolicyTestCollection):
assert recalled == default_domain.index_for_action(actions[0])
for tracker, states, actions \
- in zip(trackers, all_states_augmented, all_actions_augmented):
+ in zip(augmented_trackers, all_states_augmented, all_actions_augmented):
recalled = trained_policy.recall(states, tracker, default_domain)
assert recalled == 0
|
tests/test_policies.py
|
ReplaceText(target='augmented_trackers' @(221,23)->(221,31))
|
class TestMemoizationPolicy(PolicyTestCollection):
assert recalled == default_domain.index_for_action(actions[0])
for tracker, states, actions \
in zip(trackers, all_states_augmented, all_actions_augmented):
recalled = trained_policy.recall(states, tracker, default_domain)
assert recalled == 0
|
class TestMemoizationPolicy(PolicyTestCollection):
assert recalled == default_domain.index_for_action(actions[0])
for tracker, states, actions \
in zip(augmented_trackers, all_states_augmented, all_actions_augmented):
recalled = trained_policy.recall(states, tracker, default_domain)
assert recalled == 0
|
481 |
https://:@github.com/RasaHQ/rasa.git
|
90a98e954b209a05a168e86e78d4ad90e12d8869
|
@@ -31,7 +31,7 @@ def run(model: Text, endpoints: Text, connector: Text = None,
from rasa_core.utils import AvailableEndpoints
model_path = get_model(model)
- core_path, nlu_path = get_model_subdirectories(model)
+ core_path, nlu_path = get_model_subdirectories(model_path)
_endpoints = AvailableEndpoints.read_endpoints(endpoints)
if not connector and not credentials:
|
rasa/run.py
|
ReplaceText(target='model_path' @(34,51)->(34,56))
|
def run(model: Text, endpoints: Text, connector: Text = None,
from rasa_core.utils import AvailableEndpoints
model_path = get_model(model)
core_path, nlu_path = get_model_subdirectories(model)
_endpoints = AvailableEndpoints.read_endpoints(endpoints)
if not connector and not credentials:
|
def run(model: Text, endpoints: Text, connector: Text = None,
from rasa_core.utils import AvailableEndpoints
model_path = get_model(model)
core_path, nlu_path = get_model_subdirectories(model_path)
_endpoints = AvailableEndpoints.read_endpoints(endpoints)
if not connector and not credentials:
|
482 |
https://:@github.com/RasaHQ/rasa.git
|
e43636652c80d0e9d81dc01f6a83ebfc5444ee12
|
@@ -69,8 +69,8 @@ def test_core(
if os.path.exists(core_path) and os.path.exists(nlu_path):
_interpreter = NaturalLanguageInterpreter.create(nlu_path, _endpoints.nlu)
- _agent = Agent.load(core_path, interpreter=_interpreter)
-
+ _agent = Agent.load(model_path, interpreter=_interpreter)
+
kwargs = minimal_kwargs(kwargs, rasa.core.test, ["stories", "agent"])
loop.run_until_complete(
|
rasa/test.py
|
ReplaceText(target='model_path' @(72,28)->(72,37))
|
def test_core(
if os.path.exists(core_path) and os.path.exists(nlu_path):
_interpreter = NaturalLanguageInterpreter.create(nlu_path, _endpoints.nlu)
_agent = Agent.load(core_path, interpreter=_interpreter)
kwargs = minimal_kwargs(kwargs, rasa.core.test, ["stories", "agent"])
loop.run_until_complete(
|
def test_core(
if os.path.exists(core_path) and os.path.exists(nlu_path):
_interpreter = NaturalLanguageInterpreter.create(nlu_path, _endpoints.nlu)
_agent = Agent.load(model_path, interpreter=_interpreter)
kwargs = minimal_kwargs(kwargs, rasa.core.test, ["stories", "agent"])
loop.run_until_complete(
|
483 |
https://:@github.com/RasaHQ/rasa.git
|
2d74a8355b63f587c6e1a7d69027a84982fe237d
|
@@ -118,7 +118,7 @@ async def train_comparison_models(
file_importer,
train_path,
policy_config=policy_config,
- exclusion_percentage=current_run,
+ exclusion_percentage=percentage,
kwargs=kwargs,
dump_stories=dump_stories,
)
|
rasa/core/train.py
|
ReplaceText(target='percentage' @(121,45)->(121,56))
|
async def train_comparison_models(
file_importer,
train_path,
policy_config=policy_config,
exclusion_percentage=current_run,
kwargs=kwargs,
dump_stories=dump_stories,
)
|
async def train_comparison_models(
file_importer,
train_path,
policy_config=policy_config,
exclusion_percentage=percentage,
kwargs=kwargs,
dump_stories=dump_stories,
)
|
484 |
https://:@github.com/RasaHQ/rasa.git
|
3b51563dc49830f4e5f9a09ebd823c5f7eb563ef
|
@@ -29,7 +29,7 @@ class Tokenizer(Component):
if "use_cls_token" in self.component_config:
self.use_cls_token = self.component_config["use_cls_token"]
else:
- self.use_cls_token = False
+ self.use_cls_token = True
def add_cls_token(
self, tokens: List[Token], attribute: Text = MESSAGE_TEXT_ATTRIBUTE
|
rasa/nlu/tokenizers/tokenizer.py
|
ReplaceText(target='True' @(32,33)->(32,38))
|
class Tokenizer(Component):
if "use_cls_token" in self.component_config:
self.use_cls_token = self.component_config["use_cls_token"]
else:
self.use_cls_token = False
def add_cls_token(
self, tokens: List[Token], attribute: Text = MESSAGE_TEXT_ATTRIBUTE
|
class Tokenizer(Component):
if "use_cls_token" in self.component_config:
self.use_cls_token = self.component_config["use_cls_token"]
else:
self.use_cls_token = True
def add_cls_token(
self, tokens: List[Token], attribute: Text = MESSAGE_TEXT_ATTRIBUTE
|
485 |
https://:@github.com/RasaHQ/rasa.git
|
f96eb791fb2236695a98fd5a4f935c3c5d316fe3
|
@@ -376,7 +376,7 @@ def test_intent_evaluation_report_large(tmpdir_factory):
assert len(report.keys()) == 8
assert report["A"] == a_results
- assert result["E"] == e_results
+ assert report["E"] == e_results
def test_response_evaluation_report(tmpdir_factory):
|
tests/nlu/base/test_evaluation.py
|
ReplaceText(target='report' @(379,11)->(379,17))
|
def test_intent_evaluation_report_large(tmpdir_factory):
assert len(report.keys()) == 8
assert report["A"] == a_results
assert result["E"] == e_results
def test_response_evaluation_report(tmpdir_factory):
|
def test_intent_evaluation_report_large(tmpdir_factory):
assert len(report.keys()) == 8
assert report["A"] == a_results
assert report["E"] == e_results
def test_response_evaluation_report(tmpdir_factory):
|
486 |
https://:@github.com/RasaHQ/rasa.git
|
ff9bb32d79e484cd2cfd7cde0acfa9d0006e14f8
|
@@ -527,7 +527,7 @@ class DotProductLoss(tf.keras.layers.Layer):
tiled = tf.tile(tf.expand_dims(x, 0), (batch_size, 1, 1))
- return tf.gather(tiled, idxs, batch_dims=-1)
+ return tf.gather(tiled, idxs, batch_dims=1)
def _get_bad_mask(
self, labels: "tf.Tensor", target_labels: "tf.Tensor", idxs: "tf.Tensor"
|
rasa/utils/tf_layers.py
|
ReplaceText(target='1' @(530,49)->(530,51))
|
class DotProductLoss(tf.keras.layers.Layer):
tiled = tf.tile(tf.expand_dims(x, 0), (batch_size, 1, 1))
return tf.gather(tiled, idxs, batch_dims=-1)
def _get_bad_mask(
self, labels: "tf.Tensor", target_labels: "tf.Tensor", idxs: "tf.Tensor"
|
class DotProductLoss(tf.keras.layers.Layer):
tiled = tf.tile(tf.expand_dims(x, 0), (batch_size, 1, 1))
return tf.gather(tiled, idxs, batch_dims=1)
def _get_bad_mask(
self, labels: "tf.Tensor", target_labels: "tf.Tensor", idxs: "tf.Tensor"
|
487 |
https://:@github.com/RasaHQ/rasa.git
|
75e04b5ec3cb1ac6925152f491db074a391a9378
|
@@ -67,7 +67,7 @@ class SpacyFeaturizer(Featurizer):
non_zero_features = np.array([f for f in features if f.any()])
if self.pooling_operation == "mean":
- return np.mean(features, axis=0, keepdims=True)
+ return np.mean(non_zero_features, axis=0, keepdims=True)
elif self.pooling_operation == "max":
return np.max(features, axis=0, keepdims=True)
else:
|
rasa/nlu/featurizers/dense_featurizer/spacy_featurizer.py
|
ReplaceText(target='non_zero_features' @(70,27)->(70,35))
|
class SpacyFeaturizer(Featurizer):
non_zero_features = np.array([f for f in features if f.any()])
if self.pooling_operation == "mean":
return np.mean(features, axis=0, keepdims=True)
elif self.pooling_operation == "max":
return np.max(features, axis=0, keepdims=True)
else:
|
class SpacyFeaturizer(Featurizer):
non_zero_features = np.array([f for f in features if f.any()])
if self.pooling_operation == "mean":
return np.mean(non_zero_features, axis=0, keepdims=True)
elif self.pooling_operation == "max":
return np.max(features, axis=0, keepdims=True)
else:
|
488 |
https://:@github.com/RasaHQ/rasa.git
|
ba4b8f70ffbb7bb4d3429c3b6aaa1f9fbcc3f632
|
@@ -69,7 +69,7 @@ class SpacyFeaturizer(Featurizer):
if self.pooling_operation == "mean":
return np.mean(non_zero_features, axis=0, keepdims=True)
elif self.pooling_operation == "max":
- return np.max(features, axis=0, keepdims=True)
+ return np.max(non_zero_features, axis=0, keepdims=True)
else:
raise ValueError(
f"Invalid pooling operation specified. Available operations are "
|
rasa/nlu/featurizers/dense_featurizer/spacy_featurizer.py
|
ReplaceText(target='non_zero_features' @(72,26)->(72,34))
|
class SpacyFeaturizer(Featurizer):
if self.pooling_operation == "mean":
return np.mean(non_zero_features, axis=0, keepdims=True)
elif self.pooling_operation == "max":
return np.max(features, axis=0, keepdims=True)
else:
raise ValueError(
f"Invalid pooling operation specified. Available operations are "
|
class SpacyFeaturizer(Featurizer):
if self.pooling_operation == "mean":
return np.mean(non_zero_features, axis=0, keepdims=True)
elif self.pooling_operation == "max":
return np.max(non_zero_features, axis=0, keepdims=True)
else:
raise ValueError(
f"Invalid pooling operation specified. Available operations are "
|
489 |
https://:@github.com/RasaHQ/rasa.git
|
a2552e73fc8e4a656f43796101121ff8963bc0da
|
@@ -50,7 +50,7 @@ class EntityExtractor(Component):
# get indices of entity labels that belong to one word
for idx in range(1, len(entities)):
if entities[idx]["start"] == entities[idx - 1]["end"]:
- if entity_indices and entity_indices[-1][1] == idx - 1:
+ if entity_indices and entity_indices[-1][-1] == idx - 1:
entity_indices[-1].append(idx)
else:
entity_indices.append([idx - 1, idx])
|
rasa/nlu/extractors/extractor.py
|
ReplaceText(target='-1' @(53,57)->(53,58))
|
class EntityExtractor(Component):
# get indices of entity labels that belong to one word
for idx in range(1, len(entities)):
if entities[idx]["start"] == entities[idx - 1]["end"]:
if entity_indices and entity_indices[-1][1] == idx - 1:
entity_indices[-1].append(idx)
else:
entity_indices.append([idx - 1, idx])
|
class EntityExtractor(Component):
# get indices of entity labels that belong to one word
for idx in range(1, len(entities)):
if entities[idx]["start"] == entities[idx - 1]["end"]:
if entity_indices and entity_indices[-1][-1] == idx - 1:
entity_indices[-1].append(idx)
else:
entity_indices.append([idx - 1, idx])
|
490 |
https://:@github.com/RasaHQ/rasa.git
|
16ac7259b842e188c5c012bcaf6303e4bf4a4602
|
@@ -223,7 +223,7 @@ class RasaModel(tf.keras.models.Model):
self.save(self.best_model_file, overwrite=True)
if best_model_epoch >= 0:
- logger.info(f'The model of epoch {epoch} (out of {epochs} in total) will be stored!')
+ logger.info(f'The model of epoch {best_model_epoch} (out of {epochs} in total) will be stored!')
if self.model_summary_file is not None:
self._write_model_summary()
|
rasa/utils/tensorflow/models.py
|
ReplaceText(target='best_model_epoch' @(226,46)->(226,51))
|
class RasaModel(tf.keras.models.Model):
self.save(self.best_model_file, overwrite=True)
if best_model_epoch >= 0:
logger.info(f'The model of epoch {epoch} (out of {epochs} in total) will be stored!')
if self.model_summary_file is not None:
self._write_model_summary()
|
class RasaModel(tf.keras.models.Model):
self.save(self.best_model_file, overwrite=True)
if best_model_epoch >= 0:
logger.info(f'The model of epoch {best_model_epoch} (out of {epochs} in total) will be stored!')
if self.model_summary_file is not None:
self._write_model_summary()
|
491 |
https://:@github.com/RasaHQ/rasa.git
|
194820a60d61607fc480a95d981cb570e9ec3d4f
|
@@ -254,7 +254,7 @@ class RasaModel(tf.keras.models.Model):
val_results = self._get_metric_results(prefix="val_")
if self._does_model_improve(val_results):
logger.debug(f"Creating model checkpoint after training...")
- best_model_epoch = epoch
+ best_model_epoch = epochs
self.save(self.best_model_file, overwrite=True)
if best_model_epoch >= 0:
|
rasa/utils/tensorflow/models.py
|
ReplaceText(target='epochs' @(257,35)->(257,40))
|
class RasaModel(tf.keras.models.Model):
val_results = self._get_metric_results(prefix="val_")
if self._does_model_improve(val_results):
logger.debug(f"Creating model checkpoint after training...")
best_model_epoch = epoch
self.save(self.best_model_file, overwrite=True)
if best_model_epoch >= 0:
|
class RasaModel(tf.keras.models.Model):
val_results = self._get_metric_results(prefix="val_")
if self._does_model_improve(val_results):
logger.debug(f"Creating model checkpoint after training...")
best_model_epoch = epochs
self.save(self.best_model_file, overwrite=True)
if best_model_epoch >= 0:
|
492 |
https://:@github.com/gbrammer/grizli.git
|
a14c6aef2fb7790a5418ac882e332cbddf3771d9
|
@@ -87,7 +87,7 @@ def run_all(id, t0=None, t1=None, fwhm=1200, zr=[0.65, 1.6], dz=[0.004, 0.0002],
if scale_photometry:
scl = mb.scale_to_photometry(z=fit.meta['z_map'][0], method='lm', templates=t0, order=scale_photometry*1)
- if scl.status == 0:
+ if scl.status > 0:
mb.pscale = scl.x
st.pscale = scl.x
|
grizli/fitting.py
|
ReplaceText(target='>' @(90,22)->(90,24))
|
def run_all(id, t0=None, t1=None, fwhm=1200, zr=[0.65, 1.6], dz=[0.004, 0.0002],
if scale_photometry:
scl = mb.scale_to_photometry(z=fit.meta['z_map'][0], method='lm', templates=t0, order=scale_photometry*1)
if scl.status == 0:
mb.pscale = scl.x
st.pscale = scl.x
|
def run_all(id, t0=None, t1=None, fwhm=1200, zr=[0.65, 1.6], dz=[0.004, 0.0002],
if scale_photometry:
scl = mb.scale_to_photometry(z=fit.meta['z_map'][0], method='lm', templates=t0, order=scale_photometry*1)
if scl.status > 0:
mb.pscale = scl.x
st.pscale = scl.x
|
493 |
https://:@github.com/gbrammer/grizli.git
|
06b2bb1a51cc4090eb57f37798a4b6cb6b24b2c2
|
@@ -2291,7 +2291,7 @@ For example,
# Pixel area map
pam = os.path.join(os.getenv('iref'), 'ir_wfc3_map.fits')
print('Pixel area map: {0}'.format(pam))
- if not os.path.exists(badpix):
+ if not os.path.exists(pam):
os.system('curl -o {0} http://www.stsci.edu/hst/wfc3/pam/ir_wfc3_map.fits'.format(pam))
def fetch_config_files(ACS=False):
|
grizli/utils.py
|
ReplaceText(target='pam' @(2294,26)->(2294,32))
|
For example,
# Pixel area map
pam = os.path.join(os.getenv('iref'), 'ir_wfc3_map.fits')
print('Pixel area map: {0}'.format(pam))
if not os.path.exists(badpix):
os.system('curl -o {0} http://www.stsci.edu/hst/wfc3/pam/ir_wfc3_map.fits'.format(pam))
def fetch_config_files(ACS=False):
|
For example,
# Pixel area map
pam = os.path.join(os.getenv('iref'), 'ir_wfc3_map.fits')
print('Pixel area map: {0}'.format(pam))
if not os.path.exists(pam):
os.system('curl -o {0} http://www.stsci.edu/hst/wfc3/pam/ir_wfc3_map.fits'.format(pam))
def fetch_config_files(ACS=False):
|
494 |
https://:@github.com/gbrammer/grizli.git
|
60c15addafcb4ac4a0e55bc697b4bb18d6463736
|
@@ -229,7 +229,7 @@ def go(root='j010311+131615', maglim=[17,26], HOME_PATH='/Volumes/Pegasus/Grizli
ir_ref = None
auto_script.drizzle_overlaps(root, filters=optical_filters,
- make_combined=(ir_ref is not None), ref_image=ir_ref)
+ make_combined=(ir_ref is None), ref_image=ir_ref)
if ir_ref is None:
# Need
|
grizli/pipeline/auto_script.py
|
ReplaceText(target=' is ' @(232,33)->(232,41))
|
def go(root='j010311+131615', maglim=[17,26], HOME_PATH='/Volumes/Pegasus/Grizli
ir_ref = None
auto_script.drizzle_overlaps(root, filters=optical_filters,
make_combined=(ir_ref is not None), ref_image=ir_ref)
if ir_ref is None:
# Need
|
def go(root='j010311+131615', maglim=[17,26], HOME_PATH='/Volumes/Pegasus/Grizli
ir_ref = None
auto_script.drizzle_overlaps(root, filters=optical_filters,
make_combined=(ir_ref is None), ref_image=ir_ref)
if ir_ref is None:
# Need
|
495 |
https://:@github.com/gbrammer/grizli.git
|
e32899e470d02fa98365ca1ab1bfc70d6b64077b
|
@@ -3420,7 +3420,7 @@ def field_rgb(root='j010514+021532', xsize=6, output_dpi=None, HOME_PATH='./', s
PATH_TO = '{0}/{1}/Prep'.format(HOME_PATH, root)
else:
PATH_TO = './'
- sci_files = glob.glob('./{1}-f*sci.fits'.format(HOME_PATH, root))
+ sci_files = glob.glob('./{1}-f*sci.fits'.format(PATH_TO, root))
if filters is None:
filters = [file.split('_')[-3].split('-')[-1] for file in sci_files]
|
grizli/pipeline/auto_script.py
|
ReplaceText(target='PATH_TO' @(3423,56)->(3423,65))
|
def field_rgb(root='j010514+021532', xsize=6, output_dpi=None, HOME_PATH='./', s
PATH_TO = '{0}/{1}/Prep'.format(HOME_PATH, root)
else:
PATH_TO = './'
sci_files = glob.glob('./{1}-f*sci.fits'.format(HOME_PATH, root))
if filters is None:
filters = [file.split('_')[-3].split('-')[-1] for file in sci_files]
|
def field_rgb(root='j010514+021532', xsize=6, output_dpi=None, HOME_PATH='./', s
PATH_TO = '{0}/{1}/Prep'.format(HOME_PATH, root)
else:
PATH_TO = './'
sci_files = glob.glob('./{1}-f*sci.fits'.format(PATH_TO, root))
if filters is None:
filters = [file.split('_')[-3].split('-')[-1] for file in sci_files]
|
496 |
https://:@github.com/gbrammer/grizli.git
|
27974fdbe2c948dee6777f6c6d333b46e1456a80
|
@@ -575,7 +575,7 @@ class GroupFLT():
is_cgs=False):
"""TBD
"""
- if cpu_count == 0:
+ if cpu_count <= 0:
cpu_count = mp.cpu_count()
if fit_info is None:
|
grizli/multifit.py
|
ReplaceText(target='<=' @(578,21)->(578,23))
|
class GroupFLT():
is_cgs=False):
"""TBD
"""
if cpu_count == 0:
cpu_count = mp.cpu_count()
if fit_info is None:
|
class GroupFLT():
is_cgs=False):
"""TBD
"""
if cpu_count <= 0:
cpu_count = mp.cpu_count()
if fit_info is None:
|
497 |
https://:@github.com/gbrammer/grizli.git
|
73b7211978b46ce1f7bcc1de111237c047fbe00e
|
@@ -959,7 +959,7 @@ def parse_visits(field_root='', HOME_PATH='./', use_visit=True, combine_same_pa=
elif (combine_minexp > 0) & (not has_grism):
combined = []
for visit in visits:
- if len(visit['files']) > combine_minexp*1:
+ if len(visit['files']) >= combine_minexp*1:
combined.append(copy.deepcopy(visit))
else:
filter_pa = '-'.join(visit['product'].split('-')[-2:])
|
grizli/pipeline/auto_script.py
|
ReplaceText(target='>=' @(962,35)->(962,36))
|
def parse_visits(field_root='', HOME_PATH='./', use_visit=True, combine_same_pa=
elif (combine_minexp > 0) & (not has_grism):
combined = []
for visit in visits:
if len(visit['files']) > combine_minexp*1:
combined.append(copy.deepcopy(visit))
else:
filter_pa = '-'.join(visit['product'].split('-')[-2:])
|
def parse_visits(field_root='', HOME_PATH='./', use_visit=True, combine_same_pa=
elif (combine_minexp > 0) & (not has_grism):
combined = []
for visit in visits:
if len(visit['files']) >= combine_minexp*1:
combined.append(copy.deepcopy(visit))
else:
filter_pa = '-'.join(visit['product'].split('-')[-2:])
|
498 |
https://:@github.com/gbrammer/grizli.git
|
54178395a55d79f53bf11d651b53bb6bc3448eb6
|
@@ -3386,7 +3386,7 @@ def make_filter_combinations(root, weight_fnu=True, filter_combinations=FILTER_C
# UVIS
if filt_i.startswith('f') & filt_i.endswith('u'):
- filt_i = filt_i[:1]
+ filt_i = filt_i[:-1]
band = None
for f in filter_combinations:
|
grizli/pipeline/auto_script.py
|
ReplaceText(target='-1' @(3389,29)->(3389,30))
|
def make_filter_combinations(root, weight_fnu=True, filter_combinations=FILTER_C
# UVIS
if filt_i.startswith('f') & filt_i.endswith('u'):
filt_i = filt_i[:1]
band = None
for f in filter_combinations:
|
def make_filter_combinations(root, weight_fnu=True, filter_combinations=FILTER_C
# UVIS
if filt_i.startswith('f') & filt_i.endswith('u'):
filt_i = filt_i[:-1]
band = None
for f in filter_combinations:
|
499 |
https://:@github.com/PmagPy/PmagPy.git
|
153e127b39023f35ad6724b0e89609849ec48689
|
@@ -33,7 +33,7 @@ def main():
try:
fh_last = open(last_path, 'r+')
last_checked = pickle.load(fh_last)
- if last_checked > time.time() - 24*60*60:
+ if last_checked < time.time() - 24*60*60:
return # stop here because it's been less than 24 hours
else:
pickle.dump(time.time(), fh_last)
|
check_updates.py
|
ReplaceText(target='<' @(36,24)->(36,25))
|
def main():
try:
fh_last = open(last_path, 'r+')
last_checked = pickle.load(fh_last)
if last_checked > time.time() - 24*60*60:
return # stop here because it's been less than 24 hours
else:
pickle.dump(time.time(), fh_last)
|
def main():
try:
fh_last = open(last_path, 'r+')
last_checked = pickle.load(fh_last)
if last_checked < time.time() - 24*60*60:
return # stop here because it's been less than 24 hours
else:
pickle.dump(time.time(), fh_last)
|
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