Simulate at clock speed and downsample output
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waveform.py
22
waveform.py
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@ -1,5 +1,6 @@
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import math
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import random
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import librosa
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import numpy
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import soundfile as sf
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@ -20,9 +21,9 @@ def params(freq, damping, dt):
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return c1, c2, b1, b2
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def wave(count: int):
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def wave(count: int, sample_rate):
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freq = 3875
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dt = 1 / 44100.
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dt = 1 / sample_rate
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damping = -1210 # -0.015167
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c1, c2, b1, b2 = params(freq, damping, dt)
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@ -41,14 +42,15 @@ def wave(count: int):
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# scale = 500 * math.sqrt(d * d+ w * w) * math.exp(-d * tm) / (dt * 2000)
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x1 = 1.0
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th = 44100
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th = 23 # sample_rate // 10
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switch = th
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scale = 3 # TODO: analytic expression
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scale = 650 # TODO: analytic expression
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maxy = 0
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for i in range(count):
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# y = (c1 * y1 - c2 * y2 + b1 * x1 + b2 * x2) + mult2 * (
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# 1 - cc1 * y1 + cc2 * y2 - bb1 * x1 - bb2 * x2)
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y = (c1 * y1 - c2 * y2 + b1 * x1 + b2 * x2)
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# print(i, y / scale, x1)
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x2 = x1
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if i >= switch:
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x1 = -x1
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@ -63,8 +65,14 @@ def wave(count: int):
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def main():
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# print(list(wave(1020400)))
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with sf.SoundFile("out.wav", "w", samplerate=44100, channels=1) as f:
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f.write(list(wave(441000)))
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sample_rate = 1015657
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output = numpy.array(list(wave(1015657, sample_rate)), dtype=numpy.float32)
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output_rate = 96000 # int(sample_rate / 4)
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output = librosa.resample(output, orig_sr=sample_rate,
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target_sr=output_rate)
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with sf.SoundFile("out.wav", "w", samplerate=96000, channels=1) as f:
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f.write(output)
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if __name__ == "__main__":
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