本文整理汇总了Python中scipy.signal.cheby1方法的典型用法代码示例。如果您正苦于以下问题：Python signal.cheby1方法的具体用法？Python signal.cheby1怎么用？Python signal.cheby1使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类scipy.signal的用法示例。
在下文中一共展示了signal.cheby1方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: __init__
# 需要导入模块: from scipy import signal [as 别名]
# 或者: from scipy.signal import cheby1 [as 别名]
def __init__(self,M_change = 12,fcutoff=0.9,N_filt_order=8,ftype='butter'):
"""
Object constructor method
"""
self.M = M_change # Rate change factor M or L
self.fc = fcutoff*.5 # must be fs/(2*M), but scale by fcutoff
self.N_forder = N_filt_order
if ftype.lower() == 'butter':
self.b, self.a = signal.butter(self.N_forder,2/self.M*self.fc)
elif ftype.lower() == 'cheby1':
# Set the ripple to 0.05 dB
self.b, self.a = signal.cheby1(self.N_forder,0.05,2/self.M*self.fc)
else:
print('ftype must be "butter" or "cheby1"') 示例2: _test_phaseshift
# 需要导入模块: from scipy import signal [as 别名]
# 或者: from scipy.signal import cheby1 [as 别名]
def _test_phaseshift(self, method, zero_phase):
rate = 120
rates_to = [15, 20, 30, 40] # q = 8, 6, 4, 3
t_tot = int(100) # Need to let antialiasing filters settle
t = np.arange(rate*t_tot+1) / float(rate)
# Sinusoids at 0.8*nyquist, windowed to avoid edge artifacts
freqs = np.array(rates_to) * 0.8 / 2
d = (np.exp(1j * 2 * np.pi * freqs[:, np.newaxis] * t)
* signal.windows.tukey(t.size, 0.1))
for rate_to in rates_to:
q = rate // rate_to
t_to = np.arange(rate_to*t_tot+1) / float(rate_to)
d_tos = (np.exp(1j * 2 * np.pi * freqs[:, np.newaxis] * t_to)
* signal.windows.tukey(t_to.size, 0.1))
# Set up downsampling filters, match v0.17 defaults
if method == 'fir':
n = 30
system = signal.dlti(signal.firwin(n + 1, 1. / q,
window='hamming'), 1.)
elif method == 'iir':
n = 8
wc = 0.8*np.pi/q
system = signal.dlti(*signal.cheby1(n, 0.05, wc/np.pi))
# Calculate expected phase response, as unit complex vector
if zero_phase is False:
_, h_resps = signal.freqz(system.num, system.den,
freqs/rate*2*np.pi)
h_resps /= np.abs(h_resps)
else:
h_resps = np.ones_like(freqs)
y_resamps = signal.decimate(d.real, q, n, ftype=system,
zero_phase=zero_phase)
# Get phase from complex inner product, like CSD
h_resamps = np.sum(d_tos.conj() * y_resamps, axis=-1)
h_resamps /= np.abs(h_resamps)
subnyq = freqs < 0.5*rate_to
# Complex vectors should be aligned, only compare below nyquist
assert_allclose(np.angle(h_resps.conj()*h_resamps)[subnyq], 0,
atol=1e-3, rtol=1e-3) 示例3: am_rx_BPF
# 需要导入模块: from scipy import signal [as 别名]
# 或者: from scipy.signal import cheby1 [as 别名]
def am_rx_BPF(N_order = 7, ripple_dB = 1, B = 10e3, fs = 192e3):
"""
Bandpass filter design for the AM receiver Case Study of Chapter 17.
Design a 7th-order Chebyshev type 1 bandpass filter to remove/reduce
adjacent channel intereference at the envelope detector input.
Parameters
----------
N_order : the filter order (default = 7)
ripple_dB : the passband ripple in dB (default = 1)
B : the RF bandwidth (default = 10e3)
fs : the sampling frequency
Returns
-------
b_bpf : ndarray of the numerator filter coefficients
a_bpf : ndarray of the denominator filter coefficients
Examples
--------
>>> from scipy import signal
>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> import sk_dsp_comm.sigsys as ss
>>> # Use the default values
>>> b_bpf,a_bpf = ss.am_rx_BPF()
Pole-zero plot of the filter.
>>> ss.zplane(b_bpf,a_bpf)
>>> plt.show()
Plot of the frequency response.
>>> f = np.arange(0,192/2.,.1)
>>> w, Hbpf = signal.freqz(b_bpf,a_bpf,2*np.pi*f/192)
>>> plt.plot(f*10,20*np.log10(abs(Hbpf)))
>>> plt.axis([0,1920/2.,-80,10])
>>> plt.ylabel("Power Spectral Density (dB)")
>>> plt.xlabel("Frequency (kHz)")
>>> plt.show()
"""
b_bpf,a_bpf = signal.cheby1(N_order,ripple_dB,2*np.array([75e3-B/2.,75e3+B/2.])/fs,'bandpass')
return b_bpf,a_bpf