spec_analysis.app

The app module defines the objects and logic that drive the graphical interface. It includes dedicated classes for each application window, and a run function for launching the GUI application. For usage examples, see the GettingStarted_ guide.

API Documentation

spec_analysis.app.run(spectra_iter, out_path, config)

Run the graphical interface

Parameters:

• spectra_iter (SpectraIterator) – Iterator over the data to measure
• out_path (str) – Name of CSV file where results are saved
• config (dict) – Application config settings

GUI Classes

class spec_analysis.app.MainWindow(spectra_iter, out_path, config)

The run_sako18spec window for visualizing and measuring spectra

__init__(spectra_iter, out_path, config)

Visualization tool for measuring spectroscopic features

Parameters:

• spectra_iter (SpectraIterator) – Iterator over the data to measure
• out_path (str) – Name of CSV file where results are saved
• config (dict) – Application config settings

calculate()

Logic for the calculate button

Measure the current spectral feature and store to the feature_measurements attribute.

clear_feature_fits()

Clear any plotted feature fits from the plot

clear_plotted_pew(clear_single=False)

Clear any plotted feature boundaries from the plot

Parameters:clear_single (bool) – Clear only the current feature (False)

current_feat_def

The definition of the current feature as a dict

current_feat_name

The name of the current feature

finished()

Logic for the finished button

Skip inspection for all features in the current spectrum

last_feat()

Logic for the last feature button

Skip inspection for the current feature

next_feat()

Logic for the next feature button

Skip inspection for the current feature

plot_saved_feature()

Clear any plotted feature boundaries from the plot

reset_plot()

Reset the plot to display the current spectrum with default settings

Auto zooms the plot and repositions plot widgets to their default locations.

save()

Logic for the save button

Save current feature measurements to internal DataFrame.