"""Plots for the FOOOFGroup object.
Notes
-----
This file contains plotting functions that take as input a FOOOFGroup object.
"""
from fooof.core.errors import NoModelError
from fooof.core.modutils import safe_import, check_dependency
from fooof.plts.settings import PLT_FIGSIZES
from fooof.plts.templates import plot_scatter_1, plot_scatter_2, plot_hist
from fooof.plts.utils import savefig
from fooof.plts.style import style_plot
plt = safe_import('.pyplot', 'matplotlib')
gridspec = safe_import('.gridspec', 'matplotlib')
###################################################################################################
###################################################################################################
[docs]@savefig
@check_dependency(plt, 'matplotlib')
def plot_fg(fg, save_fig=False, file_name=None, file_path=None, **plot_kwargs):
"""Plot a figure with subplots visualizing the parameters from a FOOOFGroup object.
Parameters
----------
fg : FOOOFGroup
Object containing results from fitting a group of power spectra.
save_fig : bool, optional, default: False
Whether to save out a copy of the plot.
file_name : str, optional
Name to give the saved out file.
file_path : Path or str, optional
Path to directory to save to. If None, saves to current directory.
**plot_kwargs
Additional plot related keyword arguments, with styling options managed by ``style_plot``.
Raises
------
NoModelError
If the FOOOF object does not have model fit data available to plot.
"""
if not fg.has_model:
raise NoModelError("No model fit results are available, can not proceed.")
fig = plt.figure(figsize=plot_kwargs.pop('figsize', PLT_FIGSIZES['group']))
gs = gridspec.GridSpec(2, 2, wspace=0.35, hspace=0.35, height_ratios=[1, 1.2])
# Apply scatter kwargs to all subplots
scatter_kwargs = plot_kwargs
scatter_kwargs['all_axes'] = True
# Aperiodic parameters plot
ax0 = plt.subplot(gs[0, 0])
plot_fg_ap(fg, ax0, **scatter_kwargs, custom_styler=None)
# Goodness of fit plot
ax1 = plt.subplot(gs[0, 1])
plot_fg_gf(fg, ax1, **scatter_kwargs, custom_styler=None)
# Center frequencies plot
ax2 = plt.subplot(gs[1, :])
plot_fg_peak_cens(fg, ax2, **plot_kwargs, custom_styler=None)
@savefig
@style_plot
@check_dependency(plt, 'matplotlib')
def plot_fg_ap(fg, ax=None, **plot_kwargs):
"""Plot aperiodic fit parameters, in a scatter plot.
Parameters
----------
fg : FOOOFGroup
Object to plot data from.
ax : matplotlib.Axes, optional
Figure axes upon which to plot.
**plot_kwargs
Additional plot related keyword arguments, with styling options managed by ``style_plot``.
"""
if fg.aperiodic_mode == 'knee':
plot_scatter_2(fg.get_params('aperiodic_params', 'exponent'), 'Exponent',
fg.get_params('aperiodic_params', 'knee'), 'Knee',
'Aperiodic Fit', ax=ax)
else:
plot_scatter_1(fg.get_params('aperiodic_params', 'exponent'), 'Exponent',
'Aperiodic Fit', ax=ax)
@savefig
@style_plot
@check_dependency(plt, 'matplotlib')
def plot_fg_gf(fg, ax=None, **plot_kwargs):
"""Plot goodness of fit results, in a scatter plot.
Parameters
----------
fg : FOOOFGroup
Object to plot data from.
ax : matplotlib.Axes, optional
Figure axes upon which to plot.
**plot_kwargs
Additional plot related keyword arguments, with styling options managed by ``style_plot``.
"""
plot_scatter_2(fg.get_params('error'), 'Error',
fg.get_params('r_squared'), 'R^2', 'Goodness of Fit', ax=ax)
@savefig
@style_plot
@check_dependency(plt, 'matplotlib')
def plot_fg_peak_cens(fg, ax=None, **plot_kwargs):
"""Plot peak center frequencies, in a histogram.
Parameters
----------
fg : FOOOFGroup
Object to plot data from.
ax : matplotlib.Axes, optional
Figure axes upon which to plot.
**plot_kwargs
Additional plot related keyword arguments, with styling options managed by ``style_plot``.
"""
plot_hist(fg.get_params('peak_params', 0)[:, 0], 'Center Frequency',
'Peaks - Center Frequencies', x_lims=fg.freq_range, ax=ax)