Undescribed Horrific Abuse, One Victim & Survivor of Many gmkarl at gmail.com
Thu Nov 10 06:22:03 PST 2022

trigger #3 (#4?): might relate to switching contexts while considering
parts of fft apis and fourier data, don't quite remember. might relate
to amount of time spent coding something while holding a goal, not

import numpy as np

signal_bufsize = 1024 * 1024
recording_bufsize = signal_bufsize
original_signal = np.random.random(signal_bufsize)
recording = np.empty(recording_bufsize)
period_length = len(clear_signal) // recording_bufsize ** 0.5  *

for out_idx in range(recording_bufsize): # using a loop because i am confused
    in_idx = int(out_idx * signal_bufsize / period_length) % signal_bufsize
    recording[out_idx] = original_signal[in_idx]

# now take fft with np.fft.rfft
# then select only upper portion of 1 + bandwidth equal to period_length
# 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.

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