Filters

class tiliqua.dsp.SVF(*args, src_loc_at=0, **kwargs)

Oversampled Chamberlin State Variable Filter.

Filter cutoff and resonance are tunable at the system sample rate.

Highpass, lowpass, bandpass routed out on stream payloads hp, lp, bp.

Reference: Fig.3 in https://arxiv.org/pdf/2111.05592

class tiliqua.dsp.FIR(*args, src_loc_at=0, **kwargs)

Fixed-point FIR filter that uses a single multiplier.

This filter contains some optional optimizations to act as an efficient interpolator/decimator. For details, see stride_i, stride_o below.

Members:

• i (In(stream.Signature(ASQ))) – Input stream for sending samples to the filter.

• o (In(stream.Signature(ASQ))) – Output stream for getting samples from the filter. There is 1 output sample per input sample, presented filter_order+1 cycles after the input sample. For stride_o > 1, there is only 1 output sample per stride_o input samples.

__init__(fs, filter_cutoff_hz, filter_order, filter_type='lowpass', prescale=1, stride_i=1, stride_o=1)

fsint

Sample rate of the filter, used for calculating FIR coefficients.

filter_cutoff_hzint

Cutoff frequency of the filter, used for calculating FIR coefficients.

filter_orderint

Size of the filter (number of coefficients).

filter_typestr

Type of the filter passed to signal.firwin - "lowpass", "highpass" or so on.

prescalefloat

All taps are scaled by prescale. This is used in cases where you are upsampling and need to preserve energy. Be careful with this, it can overflow the tap coefficients (you’ll get a warning).

stride_iint

When an FIR filter is used as an interpolator, a common pattern is to provide 1 ‘actual’ sample and pad S-1 zeroes for every S output samples needed. For any stride > 1, the stride must evenly divide filter_order (i.e. no remainder). For stride > 1, this core applies some optimizations, assuming every S’th sample is nonzero, and the rest are zero. This results in a factor S reduction in MAC ops (latency) and a factor S reduction in RAM needed for sample storage. The tap storage remains of size filter_order as all taps are still mathematically required. The nonzero sample must be the first sample to arrive.

stride_oint

When an FIR filter is used as a decimator, it is common to keep only 1 sample and discard M-1 samples (if decimating by factor M). For stride_o == M, only 1 output sample is produced per M input samples. This does not reduce LUT/RAM usage, but avoids performing MACs to produce samples that will be discarded.

class tiliqua.dsp.Boxcar(*args, src_loc_at=0, **kwargs)

Simple Boxcar Average.

Average of previous N samples, implemented with an accumulator. Requires no multiplies, often useful for simple smoothing.

Can be used in low- or high-pass mode.