- 
sdr.plot.phase_delay(b: ArrayLike, a: ArrayLike = 
1, sample_rate: float =1.0, N: int =1024, x_axis: 'one-sided' | 'two-sided' | 'log' ='two-sided', decades: int =4, **kwargs) Plots the phase delay \(\tau_{\phi}(\omega)\) of the filter.
- Parameters:¶
 - b: ArrayLike¶
 The feedforward coefficients \(b_i\).
- a:   ArrayLike   =   
1¶ The feedback coefficients \(a_j\). For FIR filters, this is set to 1.
- sample_rate:   float   =   
1.0¶ The sample rate \(f_s\) of the filter in samples/s.
- N:   int   =   
1024¶ The number of samples \(N\) in the phase delay.
- 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".- **kwargs¶
 Additional keyword arguments to pass to
matplotlib.pyplot.plot().
Examples¶
See the FIR filters example.
In [1]: h_srrc = sdr.root_raised_cosine(0.5, 10, 10) In [2]: plt.figure(figsize=(8, 4)); \ ...: sdr.plot.phase_delay(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, 4)); \ ...: sdr.plot.phase_delay(iir.b_taps, iir.a_taps) ...:
In [5]: plt.figure(figsize=(8, 4)); \ ...: sdr.plot.phase_delay(h_srrc, x_axis="one-sided") ...:
In [6]: plt.figure(figsize=(8, 4)); \ ...: sdr.plot.phase_delay(iir.b_taps, iir.a_taps, x_axis="log", decades=3) ...: