[ot][spam][random][crazy][random][crazy]

[Undescribed Horrific Abuse, One Victim & Survivor of Many]

here's what i have now. my plan is to pdb through it and see how the
two reconstructed things compare.

i feel like they won't compare well. part of this feeling is backed by
a personal experience regarding frequency domain mutations and
sample-to-sample comparisons. another part is my personal experience
of how densely and thoroughly i make mistakes.

to really ensure this passes, i should simplify the data so much that
it is obvious that it will, verify that it does, make it pass if it
doesn't, and then make it more complex and see what stimulates
inaccuracy.

import pdb; pdb.set_trace()
period_fft_idx = recording_bufsize / period_length
fft_subregion = np.concatenate(([0],recording_fft[int(period_fft_idx):]))
# then reconstruct using irfft [curious: is this complex output? what
do the angles look like?]
# then downsample original_signal to the bandwidth using averaging
# then compare real values
# NOTE: failure is expected AT FIRST. then, identify the mistake, and
improve it.

reconstructed_fft = fft_subregion
original_fft = np.ftt.rfft(original_signal)

reconstructed_rfftsize = min(len(reconstructed_fft), len(original_fft)) // 2
reconstructed_from_reconstructed =
np.fft.irfft(reconstructed_fft[:reconstructed_rfftsize].abs())
reconstructed_from_original = np.fft.irfft(original_fft[:original_fft].abs())