b_asic.sfg_generators¶
B-ASIC signal flow graph generators.
This module contains a number of functions generating SFGs for specific functions.
- b_asic.sfg_generators.direct_form_1_iir(b: Sequence[complex], a: Sequence[complex], name: str | None = None, mult_properties: dict[str, int] | dict[str, dict[str, int]] | None = None, add_properties: dict[str, int] | dict[str, dict[str, int]] | None = None) SFG¶
Generate a direct-form IIR filter of type I with coefficients a and b.
- b_asic.sfg_generators.direct_form_2_iir(b: Sequence[complex], a: Sequence[complex], name: str | None = None, mult_properties: dict[str, int] | dict[str, dict[str, int]] | None = None, add_properties: dict[str, int] | dict[str, dict[str, int]] | None = None) SFG¶
Generate a direct-form IIR filter of type II with coefficients a and b.
- b_asic.sfg_generators.direct_form_fir(coefficients: Sequence[complex], name: str | None = None, mult_properties: dict[str, int] | dict[str, dict[str, int]] | None = None, add_properties: dict[str, int] | dict[str, dict[str, int]] | None = None) SFG¶
Generate a signal flow graph of a direct form FIR filter.
The coefficients parameter is a sequence of impulse response values:
coefficients = [h0, h1, h2, ..., hN]
Leading to the transfer function:
\[\sum_{i=0}^N h_iz^{-i}\]- Parameters:
- coefficients1D-array
Coefficients to use for the FIR filter section.
- nameName, optional
The name of the SFG. If None, “Direct-form FIR filter”.
- mult_propertiesdictionary, optional
Properties passed to
ConstantMultiplication.- add_propertiesdictionary, optional
Properties passed to
Addition.
- Returns:
- Signal flow graph
See also
- b_asic.sfg_generators.ldlt_matrix_inverse(N: int, name: str | None = None, mads_properties: dict[str, int] | dict[str, dict[str, int]] | None = None, reciprocal_properties: dict[str, int] | dict[str, dict[str, int]] | None = None) SFG¶
Generate an SFG for the LDLT matrix inverse algorithm.
- Parameters:
- Nint
Dimension of the square input matrix.
- nameName, optional
The name of the SFG. If None, “Direct-form FIR filter”.
- mads_propertiesdictionary, optional
Properties passed to
MADS.- reciprocal_propertiesdictionary, optional
Properties passed to
Reciprocal.
- Returns:
- SFG
Signal Flow Graph
- b_asic.sfg_generators.radix_2_dif_fft(points: int) SFG¶
Generate a radix-2 decimation-in-frequency FFT structure.
- Parameters:
- pointsint
Number of points for the FFT, needs to be a positive power of 2.
- Returns:
- SFG
Signal Flow Graph
- b_asic.sfg_generators.symmetric_fir(coefficients: Sequence[complex], name: str | None = None, mult_properties: dict[str, int] | dict[str, dict[str, int]] | None = None, add_properties: dict[str, int] | dict[str, dict[str, int]] | None = None) SFG¶
Generate a signal flow graph of a symmetric FIR filter.
The coefficients parameter is a sequence of impulse response values of even length:
coefficients = [h0, h1, h2, ..., hN]
Leading to the transfer function:
\[\sum_{i=0}^N h_iz^{-i}\]- Parameters:
- coefficients1D-array
Coefficients to use for the FIR filter section.
- nameName, optional
The name of the SFG. If None, “Transposed direct-form FIR filter”.
- mult_propertiesdictionary, optional
Properties passed to
ConstantMultiplication.- add_propertiesdictionary, optional
Properties passed to
Addition.
- Returns:
- Signal flow graph
See also
- b_asic.sfg_generators.transposed_direct_form_fir(coefficients: Sequence[complex], name: str | None = None, mult_properties: dict[str, int] | dict[str, dict[str, int]] | None = None, add_properties: dict[str, int] | dict[str, dict[str, int]] | None = None) SFG¶
Generate a signal flow graph of a transposed direct form FIR filter.
The coefficients parameter is a sequence of impulse response values:
coefficients = [h0, h1, h2, ..., hN]
Leading to the transfer function:
\[\sum_{i=0}^N h_iz^{-i}\]- Parameters:
- coefficients1D-array
Coefficients to use for the FIR filter section.
- nameName, optional
The name of the SFG. If None, “Transposed direct-form FIR filter”.
- mult_propertiesdictionary, optional
Properties passed to
ConstantMultiplication.- add_propertiesdictionary, optional
Properties passed to
Addition.
- Returns:
- Signal flow graph
See also
- b_asic.sfg_generators.wdf_allpass(coefficients: Sequence[float], name: str | None = None, latency: int | None = None, latency_offsets: dict[str, int] | None = None, execution_time: int | None = None) SFG¶
Generate a signal flow graph of a WDF allpass section based on symmetric two-port adaptors.
Simplifies the SFG in case an adaptor operation is 0.
- Parameters:
- coefficients1D-array
Coefficients to use for the allpass section.
- nameName, optional
The name of the SFG. If None, “WDF allpass section”.
- latencyint, optional
Latency of the symmetric two-port adaptors.
- latency_offsetsoptional
Latency offsets of the symmetric two-port adaptors.
- execution_timeint, optional
Execution time of the symmetric two-port adaptors.
- Returns:
- Signal flow graph