97 lines
3.8 KiB
Python
97 lines
3.8 KiB
Python
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# Copyright 2023 XMOS LIMITED.
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# This Software is subject to the terms of the XMOS Public Licence: Version 1.
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import matplotlib.pyplot as plt
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import numpy as np
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import soundfile
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from scipy.io import wavfile # soundfile has some issues writing high Fs files
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class audio_modulator:
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"""
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This test helper generates a wav file with a fixed sample rate and tone frequency
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of a certain length.
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A method then allows sections of it to be frequency modulated by a value in Hz.
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The modulated signal (which uses cumultaive phase to avoid discontinuites)
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may then be plotted as an FFT to understand the SNR/THD and may also be saved
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as a wav file.
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"""
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def __init__(self, duration_s, sample_rate=48000, test_tone_hz=1000):
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self.sample_rate = sample_rate
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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):
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start_idx = int(start_s * self.sample_rate)
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end_idx = int(end_s * self.sample_rate)
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self.modulator[start_idx:end_idx] += delta_freq
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def modulate_waveform(self):
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# Now create the frequency modulated waveform
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# this is designed to accumulate the phase so doesn't see discontinuities
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# https://dsp.stackexchange.com/questions/80768/fsk-modulation-with-python
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delta_phi = self.modulator * np.pi / (self.sample_rate / 2.0)
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phi = np.cumsum(delta_phi)
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self.waveform = np.sin(phi)
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def save_modulated_wav(self, filename):
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integer_output = np.int16(self.waveform * 32767)
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# soundfile.write(filename, integer_output, int(self.sample_rate)) # This struggles with >768ksps
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wavfile.write(filename, int(self.sample_rate), integer_output)
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def plot_modulated_fft(self, filename, skip_s=None):
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start_x = 0 if skip_s is None else int(skip_s * self.sample_rate) // 2 * 2
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waveform = self.waveform[start_x:]
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xf = np.linspace(0.0, 1.0/(2.0/self.sample_rate), waveform.size // 2)
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N = xf.size
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window = np.kaiser(N*2, 14)
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waveform = waveform * window
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yf = np.fft.fft(waveform)
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fig, ax = plt.subplots()
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# Plot a zoom in on the test
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tone_idx = int(self.test_tone_hz / (self.sample_rate / 2) * N)
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num_side_bins = 50
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yf = 20 * np.log10(np.abs(yf) / N)
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# 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
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ax.plot(xf[:N], yf[:N], marker='.')
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ax.set_xscale("log")
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plt.xlim((10**1, 10**5))
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plt.ylim((-200, 0))
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plt.savefig(filename, dpi=150)
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def load_wav(self, filename):
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"""
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Used for testing only - load a wav into self.waveform
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"""
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self.waveform, self.sample_rate = soundfile.read(filename)
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if __name__ == '__main__':
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"""
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This module is not intended to be run directly. This is here for internal testing only.
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"""
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if 0:
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test_len = 10
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audio = audio_modulator(test_len)
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for time_s in range(test_len):
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modulation_hz = 10 * (time_s - (test_len) / 2)
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audio.apply_frequency_deviation(time_s, time_s + 1, modulation_hz)
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audio.modulate_waveform()
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audio.save_modulated_wav("modulated.wav")
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audio.plot_modulated_fft("modulated_fft.png")
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else:
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audio = audio_modulator(1)
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audio.load_wav("modulated_tone_1000Hz_sd_ds.wav")
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# audio = audio_modulator(1, sample_rate=3072000)
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# audio.modulate_waveform()
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audio.plot_modulated_fft("modulated_tone_1000Hz_sd_ds.png")
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# audio.save_modulated_wav("modulated.wav")
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