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import numpy
import soundfile
import numpy as np
import matplotlib.pyplot as plt
from pcm2pdm import convert, convert_file, save_pdm_bin
from pdm2pcm import pdm_to_pcm, load_pdm_file
from testsignal import generate_test_tone
def plot_reconstruct(pcm_in, pdm, pcm_reconstructed, sr,
aspect = 4.0,
height = 3.0,
pcm_marker = None,
):
# --- Plotting using OO API ---
width = height * aspect
figheight = height * 3
fig, axs = plt.subplots(3, 1, figsize=(width, figheight), sharex=True)
duration = pcm_in.shape[0] / sr
print(duration)
t = np.linspace(0, duration, int(sr * duration), endpoint=False)
# Plot original PCM
axs[0].plot(t, pcm_in, label="PCM_in", color='blue', marker=pcm_marker)
axs[0].set_title("Original PCM")
axs[0].set_ylabel("Amplitude")
axs[0].set_ylim(-1.2, 1.2)
axs[0].grid(True)
# Plot PDM bitstream
time_pdm = np.linspace(0, duration, len(pdm), endpoint=False)
axs[1].step(time_pdm, pdm, where='mid', color='black')
axs[1].set_title("PDM Bitstream")
axs[1].set_ylabel("Bit")
axs[1].set_ylim(-0.2, 1.2)
axs[1].grid(True)
# Plot reconstructed PCM
axs[2].plot(t, pcm_reconstructed[:len(t)], label="PCM_rec", color='green', marker=pcm_marker)
axs[2].set_title("Reconstructed PCM")
axs[2].set_ylabel("Amplitude")
axs[2].set_xlabel("Time [s]")
axs[2].set_ylim(-1.2, 1.2)
axs[2].grid(True)
fig.tight_layout()
return fig
def test_sine():
# temp files
pcm_file = 'test.wav'
pdm_file = 'test.pdm'
# Generate test data
oversample = 32
sample_rate = 16000
signal = generate_test_tone(sample_rate=sample_rate,
duration_sec=1.000, freqs=[1000.0], noise_level=0.0)
pcm = signal
soundfile.write(pcm_file, signal, sample_rate)
# Convert to PDM
pdm_data = convert_file(pcm_file, oversample=oversample)
with open(pdm_file, 'wb') as f:
save_pdm_bin(pdm_data, f)
pdm_loaded = load_pdm_file(pdm_file)
numpy.testing.assert_equal(pdm_loaded, pdm_data)
print(pdm_data)
print(pdm_loaded)
# PDM to PCM conversion
pcm_reconstructed = pdm_to_pcm(pdm_loaded, decimation_factor=oversample)
# Remove DC offset
pcm_reconstructed -= numpy.mean(pcm_reconstructed)
fig = plot_reconstruct(pcm, pdm_loaded, pcm_reconstructed, sr=sample_rate)
print(fig.axes)
offset = 0.2
fig.axes[0].set_xlim(offset+0.0010,offset+0.0020)
plot_path = 'test.png'
fig.savefig(plot_path)
print(f'Saved {plot_path}')
if __name__ == '__main__':
test_sine()
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