import numpy as np
import matplotlib.pyplot as plt
import readligo as rl

start = 842656000
stop  = 842670000

# -------------------------------
# Basic Use Case
# Load data based on segment list
# -------------------------------
segs = rl.getsegs(start, stop, 'H1')
for (begin, end) in segs:
    strain, meta, dq = rl.getstrain(begin, end, 'H1')
    # -- Your analysis code goes here

#----------------------------------------------------------------
# Load all LIGO data from a single file 
#----------------------------------------------------------------
strain, time, dq = rl.loaddata('ligo_data/H-H1_LOSC_4_V1-842653696-4096.hdf5', 'H1')

# ---------------------
# Constructing Segments
# ---------------------

# -- Construct segment list for a given flag
segs = rl.getsegs(start, stop, 'H1', flag='BURST_CAT2')

# -- Segment lists may be downloaded from the Timeline app
# For example, download https://losc.ligo.org/timeline/segments/S5/H1_DATA/842656000/14000/
# as H1_segs.txt
segs = rl.SegmentList('H1_segs.txt')

# -- Construct segment list based on multiple DQ channels
strain, time, dq = rl.loaddata('ligo_data/H-H1_LOSC_4_V1-842653696-4096.hdf5', 'H1')
bcat3 = dq['BURST_CAT3']
cbccat3 = dq['CBCLOW_CAT3']
clean = bcat3 & cbccat3
segs = rl.dq2segs(clean, time[0])

# -- Construct segment list based on files in another directory
filelist = rl.FileList(directory='./ligo_data')
segs = rl.getsegs(start, stop, 'H1', flag='BURST_CAT3', filelist=filelist)

# ------------------
# Making File Lists
# ------------------

# Make a file list using directory option
filelist = rl.FileList(directory='./ligo_data')

# Write the filelist to a cache file
filelist.writecache('H1.cache')

# Make a file list based on an existing cache file
filelist = rl.FileList(cache='H1.cache')

# Identify file containing a given GPS time
gps = 842656000
filename = filelist.findfile(gps, 'H1')
print("The file {0} contains time {1} for IFO H1".format(filename, gps))