1 files changed, 50 insertions, 0 deletions
diff --git a/tools/pdm2pcm.py b/tools/pdm2pcm.py
new file mode 100644
index 0000000..6d2c284
--- /dev/null
+++ b/tools/pdm2pcm.py
@@ -0,0 +1,50 @@
+
+import numpy
+import numpy as np
+from scipy.signal import firwin, lfilter, decimate
+import soundfile
+
+def load_pdm_file(filename):
+    with open(filename, 'rb') as f:
+        byte_data = np.frombuffer(f.read(), dtype=np.uint8)
+    bit_data = np.unpackbits(byte_data)
+    # Convert to +1 (for 1s) and -1 (for 0s)
+    pdm_signal = 2 * bit_data - 1
+    return pdm_signal
+
+def pdm_to_pcm(pdm_signal, decimation_factor=64):
+    # Design a low-pass filter
+    fir_filter = firwin(numtaps=101, cutoff=0.5/decimation_factor)
+    # Filter the PDM signal
+    filtered = lfilter(fir_filter, [1.0], pdm_signal)
+    # Decimate (downsample)
+    pcm_signal = filtered[::decimation_factor]
+    return pcm_signal
+
+def main():
+
+    pdm_path = 'test_tone.pdm'
+    out_path = 'output.wav'
+    pdm_data = load_pdm_file(pdm_path)
+
+    # Convert to PCM
+    oversample = 64
+    samplerate = 16000
+    pcm_data = pdm_to_pcm(pdm_data, decimation_factor=oversample)
+
+    # Normalize and save to WAV
+    pcm_data = np.expand_dims(pcm_data, axis=1)
+    #print(pcm_data.shape)
+
+    print(numpy.min(pcm_data), numpy.max(pcm_data), numpy.mean(pcm_data))
+
+    # Normalize
+    pcm_data -= 128.0
+    pcm_data = 2**15 * (pcm_data / np.max(np.abs(pcm_data)))
+
+    print(numpy.min(pcm_data), numpy.max(pcm_data), numpy.mean(pcm_data))
+
+    soundfile.write(out_path, pcm_data, samplerate)
+
+if __name__ == '__main__':
+    main()