Resampling¶
Sample rate conversion using a polyphase sinc resampler with Kaiser-windowed anti-aliasing filter.
- pyminidsp.resample_output_len(input_len, in_rate, out_rate)[source]¶
Compute the number of output samples for a given resampling operation.
Compute the number of output samples for a given resampling operation. Use this to pre-allocate buffers when you need fine control over memory.
- pyminidsp.resample(signal, in_rate, out_rate, num_zero_crossings=13, kaiser_beta=5.0)[source]¶
Resample a signal using a polyphase sinc resampler with Kaiser-windowed anti-aliasing filter.
- Parameters:
- Returns:
numpy array of resampled signal.
- Return type:
Resample a signal using a polyphase sinc resampler. Automatically computes the output buffer size and applies a Kaiser-windowed anti-aliasing filter to prevent aliasing during downsampling.
- Parameters:
- Returns:
Resampled signal array.
- Return type:
# Upsample from 22050 Hz to 44100 Hz signal = md.sine_wave(22050, freq=440.0, sample_rate=22050.0) upsampled = md.resample(signal, in_rate=22050.0, out_rate=44100.0) # len(upsampled) == 44100 # Downsample from 48000 Hz to 16000 Hz signal = md.sine_wave(48000, freq=440.0, sample_rate=48000.0) downsampled = md.resample(signal, in_rate=48000.0, out_rate=16000.0)