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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
sure.
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 *
np.random.random()
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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