i noticed mistakes in the calculation of max_freq when freq_count was
odd, and it now looks like this:
else:
min_freq = freq_sample_rate / freq_count
if max_freq is None:
#max_freq = freq_sample_rate / 2
max_freq = freq_count * min_freq / 2
if freq_count % 2 != 0:
#max_freq -= freq_sample_rate / (2 * freq_count)
max_freq -= min_freq / 2
min_freq /= sample_rate
max_freq /= sample_rate
if freq_count % 2 == 0:
if complex:
neg_freqs = np.linspace(-max_freq, -min_freq,
num=freq_count // 2, endpoint=True)
I'm guessing the issue in the overall frequency scaling relates to
min_freq, but I wanted to address the mistakes when I noticed them.
