def create_report(subject, params):
""" Collect parameters from the dialog and creates an FOOOFReport item
"""
report_name = params['name']
spectrum_name = params['spectrum_name']
peak_width_low = params['peak_width_low']
peak_width_high = params['peak_width_high']
peak_threshold = params['peak_threshold']
max_n_peaks = params['max_n_peaks']
aperiodic_mode = params['aperiodic_mode']
minfreq = params['minfreq']
maxfreq = params['maxfreq']
spectrum = subject.spectrum.get(spectrum_name)
peak_width_limits = [peak_width_low, peak_width_high]
peak_threshold = peak_threshold
max_n_peaks = max_n_peaks
aperiodic_mode = aperiodic_mode
freq_range = [minfreq, maxfreq]
# As meggie spectrum items can contain data for multiple conditions,
# reports are also created for all those conditions, and dict is used.
report_content = {}
for key, data in spectrum.content.items():
fg = FOOOFGroup(peak_width_limits=peak_width_limits,
peak_threshold=peak_threshold,
max_n_peaks=max_n_peaks,
aperiodic_mode=aperiodic_mode,
verbose=False)
fg.fit(spectrum.freqs, data, freq_range)
logging.getLogger('ui_logger').info('FOOOF results for ' +
subject.name + ', ' +
'condition: ' + key)
# Log the textual report
logging.getLogger('ui_logger').info(
gen_results_fg_str(fg, concise=True))
report_content[key] = fg
params['conditions'] = list(spectrum.content.keys())
params['ch_names'] = spectrum.ch_names
fooof_directory = subject.fooof_report_directory
# Create a container item that meggie understands,
# and which holds the report data
report = FOOOFReport(report_name, fooof_directory, params, report_content)
# save report data to fs
report.save_content()
# and add the report item to subject
subject.add(report, 'fooof_report')
def print_results(self, concise=False):
"""Print out FOOOFGroup results.
Parameters
----------
concise : bool, optional, default: False
Whether to print the report in a concise mode, or not.
"""
print(gen_results_fg_str(self, concise))
def save_report_fg(fg, file_name, file_path=None):
"""Generate and save out as a PDF a report for a FOOOFGroup object.
Parameters
----------
fg : FOOOFGroup() object
FOOOFGroup object, containing results from fitting a group of power spectra.
file_name : str
Name to give the saved out file.
file_path : str, optional
Path to directory in which to save. If not provided, saves to current directory.
"""
font = _report_settings()
# Initialize figure
fig = plt.figure(figsize=(16, 20))
gs = gridspec.GridSpec(3,
2,
wspace=0.35,
hspace=0.25,
height_ratios=[0.8, 1.0, 1.0])
# First / top: text results
ax0 = plt.subplot(gs[0, :])
results_str = gen_results_fg_str(fg)
ax0.text(0.5, 0.7, results_str, font, ha='center', va='center')
ax0.set_frame_on(False)
ax0.set_xticks([])
ax0.set_yticks([])
# Aperiodic parameters plot
ax1 = plt.subplot(gs[1, 0])
plot_fg_ap(fg, ax1)
# Goodness of fit plot
ax2 = plt.subplot(gs[1, 1])
plot_fg_gf(fg, ax2)
# Peak center frequencies plot
ax3 = plt.subplot(gs[2, :])
plot_fg_peak_cens(fg, ax3)
# Save out the report
plt.savefig(fpath(file_path, fname(file_name, 'pdf')))
plt.close()
def save_report_fg(fg, file_name, file_path=None):
"""Generate and save out a PDF report for a group of power spectrum models.
Parameters
----------
fg : FOOOFGroup
Object with results from fitting a group of power spectra.
file_name : str
Name to give the saved out file.
file_path : str, optional
Path to directory to save to. If None, saves to current directory.
"""
# Initialize figure
_ = plt.figure(figsize=REPORT_FIGSIZE)
grid = gridspec.GridSpec(3,
2,
wspace=0.4,
hspace=0.25,
height_ratios=[0.8, 1.0, 1.0])
# First / top: text results
ax0 = plt.subplot(grid[0, :])
results_str = gen_results_fg_str(fg)
ax0.text(0.5, 0.7, results_str, REPORT_FONT, ha='center', va='center')
ax0.set_frame_on(False)
ax0.set_xticks([])
ax0.set_yticks([])
# Aperiodic parameters plot
ax1 = plt.subplot(grid[1, 0])
plot_fg_ap(fg, ax1)
# Goodness of fit plot
ax2 = plt.subplot(grid[1, 1])
plot_fg_gf(fg, ax2)
# Peak center frequencies plot
ax3 = plt.subplot(grid[2, :])
plot_fg_peak_cens(fg, ax3)
# Save out the report
plt.savefig(fpath(file_path, fname(file_name, SAVE_FORMAT)))
plt.close()
def create_report(self, subject, selected_spectrum):
""" Collect parameters from the dialog and creates an FOOOFReport item
"""
report_name = validate_name(self.ui.lineEditName.text())
spectrum = subject.spectrum.get(selected_spectrum)
peak_width_low = self.ui.doubleSpinBoxPeakWidthLow.value()
peak_width_high = self.ui.doubleSpinBoxPeakWidthHigh.value()
peak_threshold = self.ui.doubleSpinBoxPeakThreshold.value()
max_n_peaks = self.ui.spinBoxMaxNPeaks.value()
aperiodic_mode = self.ui.comboBoxAperiodicMode.currentText()
minfreq = self.ui.doubleSpinBoxFreqMin.value()
maxfreq = self.ui.doubleSpinBoxFreqMax.value()
peak_width_limits = [peak_width_low, peak_width_high]
peak_threshold = peak_threshold
max_n_peaks = max_n_peaks
aperiodic_mode = aperiodic_mode
freq_range = [minfreq, maxfreq]
# As meggie spectrum items can contain data for multiple conditions,
# reports are also created for all those conditions, and dict is used.
report_content = {}
for key, data in spectrum.content.items():
fg = FOOOFGroup(peak_width_limits=peak_width_limits,
peak_threshold=peak_threshold,
max_n_peaks=max_n_peaks,
aperiodic_mode=aperiodic_mode,
verbose=False)
@threaded
def fit(**kwargs):
""" Run fitting in a separate thread so that UI stays responsive
"""
fg.fit(spectrum.freqs, data, freq_range)
fit(do_meanwhile=self.parent.update_ui)
logging.getLogger('ui_logger').info('FOOOF results for ' +
subject.name + ', ' +
'condition: ' + key)
# Log the textual report
logging.getLogger('ui_logger').info(
gen_results_fg_str(fg, concise=True))
report_content[key] = fg
params = {
'conditions': list(spectrum.content.keys()),
'based_on': selected_spectrum,
'ch_names': spectrum.ch_names,
}
fooof_directory = subject.fooof_report_directory
# Create a container item that meggie understands,
# and which holds the report data
report = FOOOFReport(report_name, fooof_directory, params,
report_content)
# save report data to fs
report.save_content()
# and add the report item to subject
subject.add(report, 'fooof_report')