8. Plot Functions¶
- pcassie.plot_functions.plot_spectral_square(spectra_array, wave, title=None, x_label=None, y_label=None, cbar_label=None)[source]¶
Plots a 2d “spectra_array” grid against a 1d “wave” array. Valuable to show a grid od spectral observations, 2d CCF arrays, etc.
- pcassie.plot_functions.plot_preprocess(flux, wave)[source]¶
Plots the spectral grid at various stages of normalizing, median subtracting, and standard deviation dividing.
- pcassie.plot_functions.plot_covariance(tdm_covariance, wdm_covariance)[source]¶
Plots the covariance grid of the PCA analysis in the time and wavelegnth domains.
- pcassie.plot_functions.plot_eigenvectors(eigenvectors, title=None)[source]¶
Plots the first five eigenvectors.
- pcassie.plot_functions.plot_explained_variance(eigenvalues, title=None)[source]¶
Plot the explained variance from eigenvalues.
- pcassie.plot_functions.plot_reconstructed_spectra(original, reconstructed, wave, title=None)[source]¶
Plots the original and post-PCA spectra.
- pcassie.plot_functions.plot_pca_subtraction(spectra, wave, start_wav, end_wav, first_comps=0, last_comps=0, preprocess=False)[source]¶
Runs PCA subtraction and plots the results.