--- jupytext: formats: md:myst text_representation: extension: .md format_name: myst format_version: 0.13 jupytext_version: 1.11.5 kernelspec: display_name: Python 3 language: python name: python3 --- # The tutorial 8th Describes how PyXplore processes X-ray photoelectron spectroscopy (XPS) data. ## coding > **1. Save your XPS data to the root directory and rename the file to `int.csv`.** ```{code-cell} # import PyXplore package from PyXplore import WPEM import pandas as pd ``` > **2. Parse your diffraction data (`bing energy`, intensity) and perform background processing.** ```{code-cell} intensity_csv = pd.read_csv(r'int.csv',header=None ) var = WPEM.BackgroundFit(intensity_csv,segement=[[910,931],[948,952],[958,959],[966,970]],bac_num=120,Model='XPS',noise = 0.05,bac_var_type='multivariate gaussian') ``` > **3. After running the code, a new folder named `ConvertedDocuments` will be created in the root directory. This folder contains the background information.** > **Copy the two important files — `bac.csv` and `no_bac_intensity.csv` — from `ConvertedDocuments` into the root directory, as they are required for the next steps.** ```{seealso} A key difference with XPS is that the initial binding energy needs to be queried and input using two parameters: `AtomIdentifier` and `satellitePeaks`.** ``` ```{code-cell} AtomIdentifier = [['CuII','2p3/2',933.7,],['CuII','2p1/2',954,],] satellitePeaks = [['CuII', '2p3/2',941.6,],['CuII','2p3/2',943.4],['CuII','2p1/2',962.5,],] # The file name of non-background data no_bac_intensity_file = "no_bac_intensity.csv" # The file name of raw/original data original_file = "int.csv" # The file name of background data bacground_file = "bac.csv" # Execute the model WPEM.XPSfit( var, AtomIdentifier, satellitePeaks,no_bac_intensity_file, original_file, bacground_file, bta = 0.80,iter_max = 50, ) ``` > **The results are saved in the `XPSFittingProfile` folder.**