def combine_fooofs(fooofs):
"""Combine a group of FOOOF and/or FOOOFGroup objects into a single FOOOFGroup object.
Parameters
----------
fooofs : list of FOOOF objects
FOOOF objects to be concatenated into a FOOOFGroup.
Returns
-------
fg : FOOOFGroup object
Resultant FOOOFGroup object created from input FOOOFs.
"""
# Compare settings
if not compare_settings(fooofs) or not compare_data_info(fooofs):
raise ValueError("These objects have incompatible settings or data," \
"and so cannot be combined.")
# Initialize FOOOFGroup object, with settings derived from input objects
# Note: FOOOFGroup imported here to avoid an import circularity if imported at the top
from fooof import FOOOFGroup
fg = FOOOFGroup(**get_settings(fooofs[0]), verbose=fooofs[0].verbose)
fg.power_spectra = np.empty([0, len(fooofs[0].freqs)])
# Add FOOOF results from each FOOOF object to group
for f_obj in fooofs:
# Add FOOOFGroup object
if isinstance(f_obj, FOOOFGroup):
fg.group_results.extend(f_obj.group_results)
fg.power_spectra = np.vstack(
[fg.power_spectra, f_obj.power_spectra])
# Add FOOOF object
else:
fg.group_results.append(f_obj.get_results())
fg.power_spectra = np.vstack(
[fg.power_spectra, f_obj.power_spectrum])
# Add data information information
for data_info in get_obj_desc()['freq_info']:
setattr(fg, data_info, getattr(fooofs[0], data_info))
fg.freqs = gen_freqs(fg.freq_range, fg.freq_res)
return fg
def combine_fooofs(fooofs):
"""Combine a group of FOOOF and/or FOOOFGroup objects into a single FOOOFGroup object.
Parameters
----------
fooofs : list of FOOOF objects
FOOOF objects to be concatenated into a FOOOFGroup.
Returns
-------
fg : FOOOFGroup object
Resultant FOOOFGroup object created from input FOOOFs.
"""
# Compare settings
if not compare_info(fooofs, 'settings') or not compare_info(
fooofs, 'data_info'):
raise ValueError("These objects have incompatible settings or data," \
"and so cannot be combined.")
# Initialize FOOOFGroup object, with settings derived from input objects
fg = FOOOFGroup(*fooofs[0].get_settings(), verbose=fooofs[0].verbose)
# Use a temporary store to collect spectra, because we only add them if consistently present
temp_power_spectra = np.empty([0, len(fooofs[0].freqs)])
# Add FOOOF results from each FOOOF object to group
for f_obj in fooofs:
# Add FOOOFGroup object
if isinstance(f_obj, FOOOFGroup):
fg.group_results.extend(f_obj.group_results)
if f_obj.power_spectra is not None:
temp_power_spectra = np.vstack(
[temp_power_spectra, f_obj.power_spectra])
# Add FOOOF object
else:
fg.group_results.append(f_obj.get_results())
if f_obj.power_spectrum is not None:
temp_power_spectra = np.vstack(
[temp_power_spectra, f_obj.power_spectrum])
# If the number of collected power spectra is consistent, then add them to object
if len(fg) == temp_power_spectra.shape[0]:
fg.power_spectra = temp_power_spectra
# Add data information information
fg.add_data_info(fooofs[0].get_data_info())
return fg
