Python scipy.signal 模块,tukey() 实例源码
我们从Python开源项目中,提取了以下6个代码示例,用于说明如何使用scipy.signal.tukey()。
def tukey_z_scale(z, center, length, alpha=0.25, points=101):
"""
:param z: z-coordinate
:param center: center of Tukey window
:param length: length of Tukey window
:param alpha: rolloff (percentage of window)
:param points: number of points in Tukey window
:return: z_scale (scale,relative to 1.0)
"""
import numpy as np
from scipy.signal import tukey
z = np.abs(z)
zmin = np.abs(center) - length / 2
zmax = np.abs(center) + length / 2
z_tukey_win = np.linspace(zmin, zmax, points)
z_tukey_amp = tukey(points, alpha)
if z < zmin or z > zmax:
z_scale = 0.0
else:
z_scale = z_tukey_amp[np.min(np.where(z_tukey_win >= z))]
return z_scale
def plot_spectrogram(data, rate, name, dir_label):
window_size = 2 ** 10
overlap = window_size // 8
window = sig.tukey(M=window_size, alpha=0.25)
freq, time, spectrogram = sig.spectrogram(data, fs=rate, window=window, nperseg=window_size, scaling='density', noverlap=overlap)
spectrogram = np.log10(np.flipud(spectrogram))
try:
if spectrogram.shape[1] > 512:
spec_padded = spectrogram[:512,:512]
elif spectrogram.shape[1] < 512:
spec_padded = np.pad(spectrogram, ((0, 0), (0, 512 - spectrogram.shape[1])), mode='median')[:512, :]
else:
spec_padded = spectrogram
except Exception as e:
print('ERROR!')
print('Fault in: {}'.format(name))
raise
spec_padded = transform.downscale_local_mean(spec_padded, (2, 2))
final_path = os.path.join(output_dir, dir_label, name + '.png')
plt.imsave(final_path, spec_padded, cmap=plt.get_cmap('gray'))
def Taper(self, Alpha):
"""
Tukey window tapering
"""
Win = _sig.tukey(self.HDR['NSMP'], alpha=Alpha)
for I,S in enumerate(self.CHN):
self.CHN[I] *= Win
#---------------------------------------------------------------------------------------
def test_sweep(self):
self.assertArrayEqual(signal.sweep(5000, 10000, sp.chirp(np.arange(5000, dtype=np.float)/50000, 5000, 'linear'))
self.assertArrayEqual(signal.sweep(5000, 'hyperbolic'), 'hyperbolic'))
self.assertArrayEqual(signal.sweep(5000, window=('tukey', 0.1)*sp.chirp(np.arange(5000, 10000), precision=2)
def shift_waveform(tr, dtshift):
"""
tr_shift = shift_waveform(tr,dtshift):
Shift data in trace tr by dtshift seconds backwards.
Parameters
----------
tr : obspy.Trace
Trace that contains the data to shift
dtshift : float
Time shift in seconds
Returns
-------
tr_shift : obspy.Trace
copy of tr,but with data shifted dtshift seconds backwards.
"""
data_pad = np.r_[tr.data, np.zeros_like(tr.data)]
freq = fft.fftfreq(len(data_pad), tr.stats.delta)
shiftvec = np.exp(- 2 * np.pi * complex(0., 1.) * freq * dtshift)
data_fd = shiftvec * fft.fft(data_pad *
signal.tukey(len(data_pad),
alpha=0.2))
tr.data = np.real(fft.ifft(data_fd))[0:tr.stats.npts]