-
sdr.plot.filter(filter: FIR | IIR | ArrayLike | tuple[ArrayLike, ArrayLike], sample_rate: float | None =
None
, N_time: int | None =None
, N_freq: int =1024
, x_axis: 'one-sided' | 'two-sided' | 'log' ='two-sided'
, decades: int =4
) Plots the magnitude response \(|H(\omega)|^2\), impulse response \(h[n]\), step response \(s[n]\), and zeros and poles of the filter.
- Parameters:¶
- filter: FIR | IIR | ArrayLike | tuple[ArrayLike, ArrayLike]¶
The filter definition.
- sample_rate: float | None =
None
¶ The sample rate \(f_s\) of the signal in samples/s. If
None
, the x-axis will be labeled as “Normalized Frequency”.- N_time: int | None =
None
¶ The number of samples \(N_t\) in the time domain. If
None
, the length ofb
is used for FIR filters and 100 for IIR filters.- N_freq: int =
1024
¶ The number of samples \(N_f\) in the frequency response.
- x_axis: 'one-sided' | 'two-sided' | 'log' =
'two-sided'
¶ The x-axis scaling. Options are to display a one-sided spectrum, a two-sided spectrum, or one-sided spectrum with a logarithmic frequency axis.
- decades: int =
4
¶ The number of decades to plot when
x_axis="log"
.
Examples¶
See the FIR filters example.
In [1]: h_srrc = sdr.root_raised_cosine(0.5, 10, 10) In [2]: plt.figure(figsize=(8, 6)); \ ...: sdr.plot.filter(h_srrc) ...:
See the IIR filters example.
In [3]: zero = 0.6; \ ...: pole = 0.8 * np.exp(1j * np.pi / 8); \ ...: iir = sdr.IIR.ZerosPoles([zero], [pole, pole.conj()]) ...: In [4]: plt.figure(figsize=(8, 6)); \ ...: sdr.plot.filter(iir, N_time=30) ...: