consolidate plotting to spectra funcs in docs

Author: ryanhammonds

doc/api.rst

@@ -247,7 +247,6 @@ Plots for visualizing power spectra.
 .. autosummary::
     :toctree: generated/
 
-    plot_spectrum
     plot_spectra
 
 Plots for plotting power spectra with shaded regions.
@@ -257,7 +256,6 @@ Plots for plotting power spectra with shaded regions.
 .. autosummary::
     :toctree: generated/
 
-    plot_spectrum_shading
     plot_spectra_shading
 
 Plot Model Properties & Parameters

examples/analyses/plot_mne_example.py

@@ -32,7 +32,7 @@
 from fooof import FOOOFGroup
 from fooof.bands import Bands
 from fooof.analysis import get_band_peak_fg
-from fooof.plts.spectra import plot_spectrum
+from fooof.plts.spectra import plot_spectra
 
 ###################################################################################################
 # Load & Check MNE Data
@@ -284,10 +284,10 @@ def check_nans(data, nan_policy='zero'):
 
 # Compare the power spectra between low and high exponent channels
 fig, ax = plt.subplots(figsize=(8, 6))
-plot_spectrum(fg.freqs, fg.get_fooof(np.argmin(exps)).power_spectrum,
-              ax=ax, label='Low Exponent')
-plot_spectrum(fg.freqs, fg.get_fooof(np.argmax(exps)).power_spectrum,
-              ax=ax, label='High Exponent')
+plot_spectra(fg.freqs, fg.get_fooof(np.argmin(exps)).power_spectrum,
+             ax=ax, label='Low Exponent')
+plot_spectra(fg.freqs, fg.get_fooof(np.argmax(exps)).power_spectrum,
+             ax=ax, label='High Exponent')
 
 ###################################################################################################
 # Conclusion

examples/plots/plot_power_spectra.py

@@ -11,8 +11,7 @@
 import matplotlib.pyplot as plt
 
 # Import plotting functions
-from fooof.plts.spectra import plot_spectrum, plot_spectra
-from fooof.plts.spectra import plot_spectrum_shading, plot_spectra_shading
+from fooof.plts.spectra import plot_spectra, plot_spectra_shading
 
 # Import simulation utilities for creating test data
 from fooof.sim.gen import gen_power_spectrum, gen_group_power_spectra
@@ -59,7 +58,7 @@
 #
 # First we will start with the core plotting function that plots an individual power spectrum.
 #
-# The :func:`~.plot_spectrum` function takes in an array of frequency values and a 1d array of
+# The :func:`~.plot_spectra` function takes in an array of frequency values and a 1d array of
 # of power values, and plots the corresponding power spectrum.
 #
 # This function, as all the functions in the plotting module, takes in optional inputs
@@ -70,7 +69,7 @@
 ###################################################################################################
 
 # Create a spectrum plot with a single power spectrum
-plot_spectrum(freqs, powers1, log_powers=True)
+plot_spectra(freqs, powers1, log_powers=True)
 
 ###################################################################################################
 # Plotting Multiple Power Spectra
@@ -97,7 +96,7 @@
 # In some cases it may be useful to highlight or shade in particular frequency regions,
 # for example, when examining power in particular frequency regions.
 #
-# The :func:`~.plot_spectrum_shading` function takes in a power spectrum and one or more
+# The :func:`~.plot_spectra_shading` function takes in a power spectrum and one or more
 # shaded regions, and plot the power spectrum with the indicated region shaded.
 #
 # The same can be done for multiple power spectra with :func:`~.plot_spectra_shading`.
@@ -110,7 +109,7 @@
 ###################################################################################################
 
 # Plot a single power spectrum, with a shaded region covering alpha
-plot_spectrum_shading(freqs, powers1, [8, 12], log_powers=True)
+plot_spectra_shading(freqs, powers1, [8, 12], log_powers=True)
 
 ###################################################################################################
 
@@ -157,6 +156,6 @@
 fig, ax = plt.subplots(figsize=[12, 8])
 plot_spectra_shading(freqs_al, powers_al, [8, 12],
                      log_powers=True, alpha=0.6, ax=ax)
-plot_spectrum(freqs_al10, powers_al10, log_powers=True,
+plot_spectra(freqs_al10, powers_al10, log_powers=True,
               color='black', linewidth=3, label='10 Hz Alpha', ax=ax)
 plt.title('Comparing Alphas', {'fontsize' : 20, 'fontweight' : 'bold'});

motivations/measurements/plot_BandRatios.py

@@ -44,7 +44,7 @@
 from fooof.utils import trim_spectrum
 from fooof.sim.gen import gen_power_spectrum
 from fooof.sim.utils import set_random_seed
-from fooof.plts.spectra import plot_spectrum_shading, plot_spectra_shading
+from fooof.plts.spectra import plot_spectra_shading
 
 ###################################################################################################
 
@@ -124,9 +124,9 @@ def calc_band_ratio(freqs, powers, low_band, high_band):
 ###################################################################################################
 
 # Plot the power spectrum, shading the frequency bands used for the ratio
-plot_spectrum_shading(freqs, powers, [bands.theta, bands.beta],
-                      color='black', shade_colors=shade_color,
-                      log_powers=True, linewidth=3.5)
+plot_spectra_shading(freqs, powers, [bands.theta, bands.beta],
+                     color='black', shade_colors=shade_color,
+                     log_powers=True, linewidth=3.5)
 
 ###################################################################################################
 

tutorials/plot_01-ModelDescription.py

@@ -41,7 +41,7 @@
 from fooof import FOOOF
 from fooof.sim.gen import gen_power_spectrum
 from fooof.sim.utils import set_random_seed
-from fooof.plts.spectra import plot_spectrum
+from fooof.plts.spectra import plot_spectra
 from fooof.plts.annotate import plot_annotated_model
 
 ###################################################################################################
@@ -81,8 +81,8 @@
 ###################################################################################################
 
 # Plot one of the example power spectra
-plot_spectrum(freqs1, powers1, log_powers=True,
-              color='black', label='Original Spectrum')
+plot_spectra(freqs1, powers1, log_powers=True,
+             color='black', label='Original Spectrum')
 
 ###################################################################################################
 # Conceptual Overview

tutorials/plot_03-FOOOFAlgorithm.py

@@ -41,7 +41,7 @@
 #   These are used here to demonstrate the algorithm
 #   You do not need to import these functions for standard usage of the module
 from fooof.sim.gen import gen_aperiodic
-from fooof.plts.spectra import plot_spectrum
+from fooof.plts.spectra import plot_spectra
 from fooof.plts.annotate import plot_annotated_peak_search
 
 # Import a utility to download and load example data
@@ -110,10 +110,10 @@
 
 # Plot the initial aperiodic fit
 _, ax = plt.subplots(figsize=(12, 10))
-plot_spectrum(fm.freqs, fm.power_spectrum, plt_log,
-              label='Original Power Spectrum', color='black', ax=ax)
-plot_spectrum(fm.freqs, init_ap_fit, plt_log, label='Initial Aperiodic Fit',
-              color='blue', alpha=0.5, linestyle='dashed', ax=ax)
+plot_spectra(fm.freqs, fm.power_spectrum, plt_log,
+             label='Original Power Spectrum', color='black', ax=ax)
+plot_spectra(fm.freqs, init_ap_fit, plt_log, label='Initial Aperiodic Fit',
+             color='blue', alpha=0.5, linestyle='dashed', ax=ax)
 
 ###################################################################################################
 # Step 2: Flatten the Spectrum
@@ -131,8 +131,8 @@
 init_flat_spec = fm.power_spectrum - init_ap_fit
 
 # Plot the flattened the power spectrum
-plot_spectrum(fm.freqs, init_flat_spec, plt_log,
-              label='Flattened Spectrum', color='black')
+plot_spectra(fm.freqs, init_flat_spec, plt_log,
+             label='Flattened Spectrum', color='black')
 
 ###################################################################################################
 # Step 3: Detect Peaks
@@ -172,7 +172,7 @@
 ###################################################################################################
 
 # Plot the peak fit: created by re-fitting all of the candidate peaks together
-plot_spectrum(fm.freqs, fm._peak_fit, plt_log, color='green', label='Final Periodic Fit')
+plot_spectra(fm.freqs, fm._peak_fit, plt_log, color='green', label='Final Periodic Fit')
 
 ###################################################################################################
 # Step 5: Create a Peak-Removed Spectrum
@@ -188,8 +188,8 @@
 ###################################################################################################
 
 # Plot the peak removed power spectrum, created by removing peak fit from original spectrum
-plot_spectrum(fm.freqs, fm._spectrum_peak_rm, plt_log,
-              label='Peak Removed Spectrum', color='black')
+plot_spectra(fm.freqs, fm._spectrum_peak_rm, plt_log,
+             label='Peak Removed Spectrum', color='black')
 
 ###################################################################################################
 # Step 6: Re-fit the Aperiodic Component
@@ -206,10 +206,10 @@
 
 # Plot the final aperiodic fit, calculated on the peak removed power spectrum
 _, ax = plt.subplots(figsize=(12, 10))
-plot_spectrum(fm.freqs, fm._spectrum_peak_rm, plt_log,
-              label='Peak Removed Spectrum', color='black', ax=ax)
-plot_spectrum(fm.freqs, fm._ap_fit, plt_log, label='Final Aperiodic Fit',
-              color='blue', alpha=0.5, linestyle='dashed', ax=ax)
+plot_spectra(fm.freqs, fm._spectrum_peak_rm, plt_log,
+             label='Peak Removed Spectrum', color='black', ax=ax)
+plot_spectra(fm.freqs, fm._ap_fit, plt_log, label='Final Aperiodic Fit',
+             color='blue', alpha=0.5, linestyle='dashed', ax=ax)
 
 ###################################################################################################
 # Step 7: Combine the Full Model Fit
@@ -226,8 +226,8 @@
 ###################################################################################################
 
 # Plot full model, created by combining the peak and aperiodic fits
-plot_spectrum(fm.freqs, fm.fooofed_spectrum_, plt_log,
-              label='Full Model', color='red')
+plot_spectra(fm.freqs, fm.fooofed_spectrum_, plt_log,
+             label='Full Model', color='red')
 
 ###################################################################################################
 #