使用scipy.signal.spectral.lombscargle发现周期

Question

新的Scipy v0.11提供了一个用于频谱分析的软件包。不幸的是，文档很少，并没有很多可用的例子。

作为一个婴儿的例子，我试图做一个正弦波的时期发现。不幸的是，它预测的时间段为1，而不是预期的2pi。有任何想法吗？

# 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代替2pi ~= 1/0.6366预产期。有任何想法吗？

Answer 1

请注意的spectral.lombscargle的最后一个参数是根据docstring角频率：

Parameters 
---------- 
x : array_like 
Sample times. 
y : array_like 
Measurement values. 
freqs : array_like 
Angular frequencies for output periodogram.