新的 Scipy v0.11 提供了一个用于光谱分析的包。不幸的是,文档很少,而且没有很多可用的示例。
作为一个小例子,我正在尝试发现正弦波的周期。不幸的是,它预测的周期为 1
而不是预期的 2pi
。有什么想法吗?
# imports the numerical array and scientific computing packages
import numpy as np
import scipy as sp
from scipy.signal import spectral
# generates 100 evenly spaced points between 1 and 1000
time = np.linspace(1, 1000, 100)
# computes the sine value of each of those points
mags = np.sin(time)
# scales the sine values so that the mean is 0 and the variance is 1 (the documentation specifies that this must be done)
scaled_mags = (mags-mags.mean())/mags.std()
# generates 1000 frequencies between 0.01 and 1
freqs = np.linspace(0.01, 1, 1000)
# computes the Lomb Scargle Periodogram of the time and scaled magnitudes using each frequency as a guess
periodogram = spectral.lombscargle(time, scaled_mags, freqs)
# returns the inverse of the frequence (i.e. the period) of the largest periodogram value
1/freqs[np.argmax(periodogram)]
这将返回 1
而不是 2pi ~= 1/0.6366
的预期周期。有什么想法吗?
最佳答案
请注意 spectral.lombscargle
的最后一个参数是根据 docstring 的角频率:
Parameters
----------
x : array_like
Sample times.
y : array_like
Measurement values.
freqs : array_like
Angular frequencies for output periodogram.
关于python - 使用 scipy.signal.spectral.lombscargle 进行周期发现,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/13349181/