ml4gw.transforms.iirfilter

Classes

IIRFilter(N, Wn[, rs, rp, btype, analog, ...])

IIR digital and analog filter design given order and critical points.

class ml4gw.transforms.iirfilter.IIRFilter(N, Wn, rs=None, rp=None, btype='band', analog=False, ftype='butter', fs=None)

Bases: Module

IIR digital and analog filter design given order and critical points. Design an Nth-order digital or analog filter and apply it to a signal. Uses SciPy's iirfilter function to create the filter coefficients. https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.iirfilter.html

The forward call of this module accepts a batch tensor of shape (n_waveforms, n_samples) and returns the filtered waveforms.

Parameters:

N (int) -- The order of the filter.
Wn (Union[float, Tensor]) -- A scalar or length-2 sequence giving the critical frequencies. For digital filters, Wn are in the same units as fs. By default, fs is 2 half-cycles/sample, so these are normalized from 0 to 1, where 1 is the Nyquist frequency. (Wn is thus in half-cycles / sample). For analog filters, Wn is an angular frequency (e.g., rad/s). When Wn is a length-2 sequence,``Wn[0]`` must be less than Wn[1].
rp (Union[None, float, Tensor]) -- For Chebyshev and elliptic filters, provides the maximum ripple in the passband. (dB)
rs (Union[None, float, Tensor]) -- For Chebyshev and elliptic filters, provides the minimum attenuation in the stop band. (dB)
btype -- The type of filter. Default is 'bandpass'.
analog -- When True, return an analog filter, otherwise a digital filter is returned.
ftype --
The type of IIR filter to design:
- Butterworth : 'butter'
- Chebyshev I : 'cheby1'
- Chebyshev II : 'cheby2'
- Cauer/elliptic: 'ellip'
- Bessel/Thomson: 'bessel's
fs -- The sampling frequency of the digital system.

Returns:

Filtered signal on the forward pass.

forward(x)

Apply the filter to the input signal.