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Merge pull request #45 from ed-xmos/feature/sdm
Refactor python model and initial SDM model
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# Copyright 2023 XMOS LIMITED. | ||
# This Software is subject to the terms of the XMOS Public Licence: Version 1. | ||
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import matplotlib.pyplot as plt | ||
import numpy as np | ||
import soundfile | ||
from scipy.io import wavfile # soundfile has some issues writing high Fs files | ||
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class audio_modulator: | ||
def __init__(self, duration_s, sample_rate=48000, test_tone_hz=1000): | ||
self.sample_rate = sample_rate | ||
self.test_tone_hz = test_tone_hz | ||
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self.modulator = np.full(int(duration_s * sample_rate), test_tone_hz, dtype=np.float64) | ||
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def apply_frequency_deviation(self, start_s, end_s, delta_freq): | ||
start_idx = int(start_s * self.sample_rate) | ||
end_idx = int(end_s * self.sample_rate) | ||
self.modulator[start_idx:end_idx] += delta_freq | ||
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def modulate_waveform(self): | ||
# Now create the frequency modulated waveform | ||
# this is designed to accumulate the phase so doesn't see discontinuities | ||
# https://dsp.stackexchange.com/questions/80768/fsk-modulation-with-python | ||
delta_phi = self.modulator * np.pi / (self.sample_rate / 2.0) | ||
phi = np.cumsum(delta_phi) | ||
self.waveform = np.sin(phi) | ||
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def save_modulated_wav(self, filename): | ||
integer_output = np.int16(self.waveform * 32767) | ||
# soundfile.write(filename, integer_output, int(self.sample_rate)) # This struggles with >768ksps | ||
wavfile.write(filename, int(self.sample_rate), integer_output) | ||
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def plot_modulated_fft(self, filename, skip_s=None): | ||
start_x = 0 if skip_s is None else int(skip_s * self.sample_rate) // 2 * 2 | ||
waveform = self.waveform[start_x:] | ||
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xf = np.linspace(0.0, 1.0/(2.0/self.sample_rate), waveform.size // 2) | ||
N = xf.size | ||
window = np.kaiser(N*2, 14) | ||
waveform = waveform * window | ||
yf = np.fft.fft(waveform) | ||
fig, ax = plt.subplots() | ||
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# Plot a zoom in on the test | ||
tone_idx = int(self.test_tone_hz / (self.sample_rate / 2) * N) | ||
num_side_bins = 50 | ||
yf = 20 * np.log10(np.abs(yf) / N) | ||
# ax.plot(xf[tone_idx - num_side_bins:tone_idx + num_side_bins], yf[tone_idx - num_side_bins:tone_idx + num_side_bins], marker='.') | ||
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# Plot the whole frequncy range from DC to nyquist | ||
ax.plot(xf[:N], yf[:N], marker='.') | ||
ax.set_xscale("log") | ||
plt.xlim((10**1, 10**5)) | ||
plt.ylim((-200, 0)) | ||
plt.savefig(filename, dpi=150) | ||
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def load_wav(self, filename): | ||
""" | ||
Used for testing only - load a wav into self.waveform | ||
""" | ||
self.waveform, self.sample_rate = soundfile.read(filename) | ||
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if __name__ == '__main__': | ||
""" | ||
This module is not intended to be run directly. This is here for internal testing only. | ||
""" | ||
if 0: | ||
test_len = 10 | ||
audio = audio_modulator(test_len) | ||
for time_s in range(test_len): | ||
modulation_hz = 10 * (time_s - (test_len) / 2) | ||
audio.apply_frequency_deviation(time_s, time_s + 1, modulation_hz) | ||
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audio.modulate_waveform() | ||
audio.save_modulated_wav("modulated.wav") | ||
audio.plot_modulated_fft("modulated_fft.png") | ||
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else: | ||
audio = audio_modulator(1) | ||
audio.load_wav("modulated_tone_1000Hz_sd_ds.wav") | ||
# audio = audio_modulator(1, sample_rate=3072000) | ||
# audio.modulate_waveform() | ||
audio.plot_modulated_fft("modulated_tone_1000Hz_sd_ds.png") | ||
# audio.save_modulated_wav("modulated.wav") | ||
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