data2list.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-


import numpy as np
from scipy import signal
from scipy.interpolate import interp1d
from scipy.signal import butter, filtfilt, iirdesign, zpk2tf, freqz
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
import h5py
# LIGO-specific readligo.py 
import readligo as rl


# Load LIGO data from a single file
#----------------------------------------------------------------
# First from H1
fn_H1 = 'H-H1_LOSC_4_V1-1126259446-32.hdf5'
strain_H1, time_H1, chan_dict_H1 = rl.loaddata(fn_H1, 'H1')
# and then from L1
fn_L1 = 'L-L1_LOSC_4_V1-1126259446-32.hdf5'
strain_L1, time_L1, chan_dict_L1 = rl.loaddata(fn_L1, 'L1')

# sampling rate:
fs = 4096
# both H1 and L1 will have the same time vector, so:
time = time_H1
# the time sample interval (uniformly sampled!)
dt = time[1] - time[0]

# number of sample for the fast fourier transform:
NFFT = 1*fs
fmin = 10
fmax = 2000
Pxx_H1, freqs = mlab.psd(strain_H1, Fs = fs, NFFT = NFFT)
Pxx_L1, freqs = mlab.psd(strain_L1, Fs = fs, NFFT = NFFT)

with open('test.txt', 'w') as f:
	for H1 in Pxx_H1:
f.write("%s\n" %(np.sqrt(H1)))