combine_fooofs fails when there are "gaps" in frequencies #237
Description
Hi guys,
I found an error when using the above function inside the fooof.objs.utils module, if a FOOOFGroup object is created by non-consecutive frequencies (as can happen when notch-filtering for example).
A minimal code to reproduce the error is the following
import numpy as np
from fooof import FOOOFGroup
from fooof.objs.utils import combine_fooofs
freqs = np.array([1, 2, 3, 5, 6]) # missing 4
PSD = np.random.randn(5, len(freqs)) ** 2
fg = FOOOFGroup()
fg.fit(freqs, PSD)
fgs = combine_fooofs([fg])And the error is:
Exception has occurred: ValueError
all the input array dimensions for the concatenation axis must match exactly, but along dimension 1, the array at index 0 has size 6 and the array at index 1 has size 5
The problem stems in the combine_fooofs function where the frequencies and PSDs are initialized as:
n_freqs = len(gen_freqs(meta_data.freq_range, meta_data.freq_res))
temp_power_spectra = np.empty([0, n_freqs])Hence, ending up with more frequencies than there actually are and causing the error in the np.vstack function. A possible solution could be to get rid of the initial definitions and initialize from the first object in the passed list, as:
meta_data = fooofs[0].get_meta_data()
# Add FOOOF results from each FOOOF object to group
for i, f_obj in enumerate(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:
if i == 0:
temp_power_spectra = f_obj.power_spectra
else:
temp_power_spectra = np.vstack([temp_power_spectra, f_obj.power_spectra])Thanks again for the wonderful tool!