def _progress(iterable, progress, n_to_run):
"""Add a progress bar to an iterable to be processed.
Parameters
----------
iterable : list or iterable
Iterable object to potentially apply progress tracking to.
progress : {None, 'tqdm', 'tqdm.notebook'}
Which kind of progress bar to use. If None, no progress bar is used.
n_to_run : int
Number of jobs to complete.
Returns
-------
pbar : iterable or tqdm object
Iterable object, with tqdm progress functionality, if requested.
Raises
------
ValueError
If the input for `progress` is not understood.
Notes
-----
The explicit `n_to_run` input is required as tqdm requires this in the parallel case.
The `tqdm` object that is potentially returned acts the same as the underlying iterable,
with the addition of printing out progress every time items are requested.
"""
# Check progress specifier is okay
tqdm_options = ['tqdm', 'tqdm.notebook']
if progress is not None and progress not in tqdm_options:
raise ValueError("Progress bar option not understood.")
# Set the display text for the progress bar
pbar_desc = 'Running FOOOFGroup'
# Use a tqdm, progress bar, if requested
if progress:
# Try loading the tqdm module
tqdm = safe_import(progress)
if not tqdm:
# If tqdm isn't available, proceed without a progress bar
print(("A progress bar requiring the 'tqdm' module was requested, "
"but 'tqdm' is not installed. \nProceeding without using a progress bar."))
pbar = iterable
else:
# If tqdm loaded, apply the progress bar to the iterable
pbar = tqdm.tqdm(iterable, desc=pbar_desc, total=n_to_run, dynamic_ncols=True)
# If progress is None, return the original iterable without a progress bar applied
else:
pbar = iterable
return pbar
def _progress(iterable, verbose, n_to_run):
"""Add a progress bar to an iterable to be processed.
Parameters
----------
iterable : list or iterable
Iterable object to potentially apply progress tracking to.
verbose : 'tqdm', 'tqdm_notebook' or boolean
Which type of verbosity to do.
n_to_run : int
Number of jobs to complete.
Returns
-------
pbar : iterable or tqdm object
Iterable object, with TQDM progress functionality, if requested.
Notes
-----
The explicit n_to_run input is required as tqdm requires this in the parallel case.
The `tqdm` object that is potentially returned acts the same as the underlying iterable,
with the addition of printing out progress everytime items are requested.
"""
# Check verbose specifier is okay
tqdm_options = ['tqdm', 'tqdm_notebook']
if not isinstance(verbose, bool) and not verbose in tqdm_options:
#print('Verbose option not understood. Proceeding without any.')
raise ValueError('Verbose option not understood.')
if verbose:
# Progress bar options, using tqdm
if verbose in tqdm_options:
# Get tqdm, and set which approach to use from tqdm
# Approch to use from tqdm should be what's specified in 'verbose'
tqdm_mod = safe_import('tqdm')
tqdm_type = verbose
# Pulls out the specific tqdm approach to be used from the tqdm module, if available
tqdm = getattr(tqdm_mod, tqdm_type) if tqdm_mod else None
if not tqdm:
print('tqdm requested but is not installed. Proceeding without progress bar.')
pbar = iterable
else:
pbar = tqdm(iterable, desc='Running FOOOFGroup:', total=n_to_run,
dynamic_ncols=True)
# If 'verbose' was just 'True', print out a marker of what is being run (no progress bar)
else:
print('Running FOOOFGroup across {} power spectra.'.format(n_to_run))
pbar = iterable
else:
pbar = iterable
return pbar
def test_style_spectrum_plot(skip_if_no_mpl):
# Create a dummy plot and style it
from fooof.core.modutils import safe_import
plt = safe_import('.pyplot', 'matplotlib')
_, ax = plt.subplots()
style_spectrum_plot(ax, False, False)
# Check that axis labels are added - use as proxy that it ran correctly
assert ax.xaxis.get_label().get_text()
assert ax.yaxis.get_label().get_text()
"""Plots for FOOOF object."""
import os
import numpy as np
from fooof.plts.templates import plot_spectrum
from fooof.core.funcs import gaussian_function
from fooof.core.modutils import safe_import, check_dependency
plt = safe_import('.pyplot', 'matplotlib')
###################################################################################################
###################################################################################################
@check_dependency(plt, 'matplotlib')
def plot_fm(fm,
plt_log=False,
save_fig=False,
file_name='FOOOF_fit',
file_path='',
ax=None):
"""Plot the original power spectrum, and full model fit from FOOOF object.
Parameters
----------
fm : FOOOF() object
FOOOF object, containing a power spectrum and (optionally) results from fitting.
plt_log : boolean, optional
Whether or not to plot the frequency axis in log space. default: False
save_fig : boolean, optional
def skip_if_no_mpl():
if not safe_import('matplotlib'):
pytest.skip('Matplotlib not availabe: skipping test.')
"""Plots for FOOOFGroup object.
Notes
-----
This file contains plotting functions that take as input a FOOOFGroup() object.
"""
import os
from fooof.core.io import fname, fpath
from fooof.core.modutils import safe_import, check_dependency
from fooof.plts.templates import plot_scatter_1, plot_scatter_2, plot_hist
plt = safe_import('.pyplot', 'matplotlib')
gridspec = safe_import('.gridspec', 'matplotlib')
###################################################################################################
###################################################################################################
@check_dependency(plt, 'matplotlib')
def plot_fg(fg, save_fig=False, file_name='FOOOF_group_fit', file_path=None):
"""Plots a figure with subplots covering the group results from a FOOOFGroup object.
Parameters
----------
fg : FOOOFGroup() object
FOOOFGroup object, containing results from fitting a group of power spectra.
save_fig : boolean, optional, default: False
Whether to save out a copy of the plot.
file_name : str, optional
Name to give the saved out file.
import numpy as np
from fooof.core.utils import nearest_ind
from fooof.core.errors import NoModelError
from fooof.core.funcs import gaussian_function
from fooof.core.modutils import safe_import, check_dependency
from fooof.sim.gen import gen_aperiodic
from fooof.plts.utils import check_ax
from fooof.plts.spectra import plot_spectrum
from fooof.plts.settings import PLT_FIGSIZES, PLT_COLORS
from fooof.plts.style import check_n_style, style_spectrum_plot
from fooof.analysis.periodic import get_band_peak_fm
from fooof.utils.params import compute_knee_frequency, compute_fwhm
plt = safe_import('.pyplot', 'matplotlib')
mpatches = safe_import('.patches', 'matplotlib')
###################################################################################################
###################################################################################################
@check_dependency(plt, 'matplotlib')
def plot_annotated_peak_search(fm, plot_style=style_spectrum_plot):
"""Plot a series of plots illustrating the peak search from a flattened spectrum.
Parameters
----------
fm : FOOOF
FOOOF object, with model fit, data and settings available.
plot_style : callable, optional, default: style_spectrum_plot
"""Tests for fooof.plts.utils."""
import os
from fooof.core.modutils import safe_import
from fooof.tests.tutils import plot_test
from fooof.tests.settings import TEST_PLOTS_PATH
from fooof.plts.utils import *
mpl = safe_import('matplotlib')
###################################################################################################
###################################################################################################
def test_check_ax(skip_if_no_mpl):
figsize = [5., 5.]
ax = check_ax(None, figsize=figsize)
assert isinstance(ax, mpl.axes.Axes)
assert figsize == [ax.get_figure().get_figwidth(),
ax.get_figure().get_figheight()]
def test_set_alpha(skip_if_no_mpl):
alpha = set_alpha(100)
assert isinstance(alpha, float)
@plot_test
