phase_calibration function, an in-depth
-In the PySSPFM application, users can concretely assign the desired phase values for both forward and reverse directions using the pha_fwd and pha_rev parameters. It is essential for the user to identify whether they are dealing with a predominant electrostatic component in the on field mode through the main_electrostatic parameter. The value of this parameter can vary from one file to another and can therefore be read from a file that contains a list of these parameter values, across main_elec_file_path, read with extract_main_elec_tab function of utils/nanoloop_to_hyst/file.py script. dont le chemin est spécifié par le Additionally, they can opt to specify the sign for the electrostatic component's slope with the parameter locked_elec_slope. The user should also provide information about the piezoelectric coefficient sign of the material in the measurement record. With these provided parameters and the calibration protocol, phase values can be attributed to the two peaks in the histogram.
+In the PySSPFM application, users can concretely assign the desired phase values for both forward and reverse directions using the pha_fwd and pha_rev parameters. It is essential for the user to identify whether they are dealing with a predominant electrostatic component in the on field mode through the main_electrostatic parameter. The value of this parameter can vary from one file to another and can therefore be read from a file that contains a list of these parameter values, across main_elec_file_path, read with extract_main_elec_tab function of utils/nanoloop_to_hyst/file.py script. Additionally, they can opt to specify the sign for the electrostatic component's slope with the parameter locked_elec_slope. The user should also provide information about the piezoelectric coefficient sign of the material in the measurement record. With these provided parameters and the calibration protocol, phase values can be attributed to the two peaks in the histogram.
@@ -1503,7 +1503,7 @@ User parameters:
-The operating principle of this reader differs slightly from that of the global map reader (see Section VIII.1.d) - Global map reader in the documentation). In this case, a single mask can be defined by the user, and a list of measures to be mapped is provided by the user. The concept behind this reader is to observe multiple maps of different properties simultaneously (rather than one by one). Therefore, the main_mapping function is not used. In the main function of the script, main_list_map_reader, the mask is constructed, and cross-correlative analysis is performed only between the mapped measures (for cross-correlative analysis, please refer to section VII.5) - 2D cross correlation of the documentation.). Then, the figure containing all the different maps is formatted using the formatting_fig function. For each map, the tratment_plot_map function is used to carry out treatments (masking, interpolation, etc.) and generate the map of the corresponding property, making use of functions from the SSPFM mapping scripts. Finally, all the graphs of the evolution of the different properties as a function of time and the index of the map row are detrmined in the same way with the treatment_plot_graph and formatting_fig_graphs functions.
+The operating principle of this reader differs slightly from that of the global map reader (see Section VIII.1.d) - Global map reader in the documentation). In this case, a single mask can be defined by the user, and a list of measures to be mapped is provided by the user. The concept behind this reader is to observe multiple maps of different properties simultaneously (rather than one by one). Therefore, the main_mapping function is not used. In the main function of the script, main_list_map_reader, the mask is constructed, and cross-correlative analysis is performed only between the mapped measures (for cross-correlative analysis, please refer to section VII.5) - 2D cross correlation of the documentation.). Then, the figure containing all the different maps is formatted using the formatting_fig function. For each map, the tratment_plot_map function is used to carry out treatments (masking, interpolation, etc.) and generate the map of the corresponding property, making use of functions from the SSPFM mapping scripts. Finally, all the graphs of the evolution of the different properties as a function of time and the index of the map row are detrmined in the same way with the treatment_plot_graph and formatting_fig_graphs functions. Histograms are plotted too with the treatment_plot_hist and formatting_fig_graphs functions.
@@ -1521,6 +1521,11 @@ The operating principle of this reader differs slightly from that of the global
Result of list_map_reader (figure generated with main_list_map_reader function of toolbox/list_map_reader.py script)
+The files containing the phase offsets and inversions, phase_offset.txt and phase_inversion.txt generated by
+toolbox/phase_offset_analyzer.py and toolbox/phase_inversion_analyzer.py scripts can be analyzed by the script.
+