pyFDN.flamo_process#

pyFDN.flamo_process(model, signal, *, fs=None, tail_seconds=0.0, dtype=None)[source]#

Run a 1-D signal through a FLAMO Shell model offline.

Wraps the boilerplate of turning a NumPy signal into the (batch, time, channel) tensor FLAMO expects, running a no-grad forward pass, and converting the result back to NumPy.

The model convolves in the frequency domain over a block of length nfft (read from the model’s input layer), so the signal is truncated or zero-padded to nfft. Because that is a circular convolution, a long reverb tail can wrap around onto the start of the block; pass tail_seconds to reserve that much trailing silence for the tail to decay into (requires fs).

Parameters:

model – FLAMO Shell whose input layer exposes nfft (e.g. the output of pyFDN.dss_to_flamo()).
signal (np.ndarray) – 1-D input signal.
fs (int, optional) – Sampling rate, required only when tail_seconds > 0.
tail_seconds (float) – Trailing silence to reserve so the reverb tail does not wrap around.
dtype (torch.dtype or None) – Tensor dtype for the forward pass; defaults to float32.

Returns:

Squeezed model output on CPU.

Return type:

np.ndarray