Use of scipy.signal.lombscargle

For class, we are trying to prove a simple example of the Lomb-Scargle Periodogram using the embedded package in scipy. There is little documentation on how to use this function, and I have not been able to find any help online. When I run the code, I get a value of ~6.3 for the main peak of the periodogram, as opposed to the expected ~23.3. The data that we are pulling from is a simple .dat file with lists of numbers. Here is the code, any ideas on what's happening?

import scipy as sp
import math as m
import numpy as np
from scipy.signal import lombscargle
import pylab as plt
from numpy import shape


x=[]
y=[]
nout = 10000
file=open("hv878_1945.dat", 'r')

for pair in file:
    xandy=pair.split()
    x.append(float(xandy[0]))
    y.append(float(xandy[2]))


x=np.asarray(x)
y=np.asarray(y)
f = np.linspace(0.1, 50, nout)

periodogram=sp.signal.spectral.lombscargle(x,y,f)
normval = x.shape[0]
plt.plot(f, np.sqrt(4*(periodogram/normval)))
plt.show()

Here is the file, if anybody wants to run it: http://www.mediafire.com/download/9a0aw9nc40r4c73/hv878_1945.dat

Any help would be appreciated!

It would appear you have the same problem described here. Basically you are not testing the frequency of interest and did not take into account that the frequencies passed to lombscargle are angular frequencies.

If you change your list of tested frequencies, you'll see there's a peak near the angular frequency of ~138, which corresponds to a frequency of 22.28 (=angular frequency /2/pi):

import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import lombscargle

plt.ion()
data = np.loadtxt('hv878_1945.dat')

ang_freq = np.linspace(.1, 25*6, 10000)
periodogram = lombscargle(data[:,0], data[:,2], ang_freq)
print(ang_freq[np.argmax(periodogram)]/2/np.pi)
plt.plot(ang_freq, periodogram)