Quantization needs to take max of real and imag independently

[MattCarrickPL]

The quantize() function computes the maximum quantization based on the magnitude of a complex number but quantizes against real and imaginary independently.

max_value = max(np.abs(tensor)) + 1e-9
bins = np.linspace(-max_value, max_value, num_levels + 1)

# Digitize to bins
quantized_real = np.digitize(tensor.real, bins)
quantized_imag = np.digitize(tensor.imag, bins)

https://github.com/TorchDSP/torchsig/blob/v0.4.2/torchsig/transforms/functional.py#L1029

The solution is to compute the max of real and imaginary independently, then take the max of their max, ex:

max_value = max( np.abs(np.real(tensor)), np.abs(np.imag(tensor)) )

[MattCarrickPL]

Old issue, closing.