#!/usr/bin/env python
""" Plot the log likelihood percentiles for a DQ bin
"""
import logging
import sys
import argparse
import numpy
import pycbc
import h5py
from matplotlib import use; use('Agg')
from matplotlib import pyplot
from pycbc.version import git_verbose_msg as version
import pycbc.results

parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('--version', action='version', version=version)
parser.add_argument('--verbose', action="store_true")
parser.add_argument("--ifo", type=str,required=True)
parser.add_argument("--dq-file", required=True)
parser.add_argument('--background-bin', default='all_bin')
parser.add_argument("--x-max",default=100)
parser.add_argument("--x-min",default=0)
parser.add_argument('--log-x', action="store_true")
parser.add_argument("--output-file", required=True)
args = parser.parse_args()

pycbc.init_logging(args.verbose)

ifo = args.ifo

f = h5py.File(args.dq_file, 'r')

bin_name = args.background_bin

if bin_name not in f['%s/dq_percentiles'%ifo].keys():
    raise ValueError("Background bin name not found in DQ file")
else:
    yvals = f['%s/dq_percentiles/%s'%(ifo,bin_name)][:]

xvals = numpy.linspace(0,100,len(yvals)+1)
centers = (xvals[1:] + xvals[:-1]) / 2
dq_name = f.attrs['stat'].split('-')[0] 

xmax = float(args.x_max)
xmin = float(args.x_min)

if args.log_x and xmin==0:
    raise ValueError("Cannot set the x axis to log scale when xmin=0")

ymax = 1.2 * max(yvals)

color = pycbc.results.ifo_color(ifo)

# create a figure to add a histogram
fig = pyplot.figure(0)
ax = fig.add_subplot(111)

counts_, bins_, _ = ax.hist(centers, bins=len(yvals),
                             weights=yvals, color=color,
                             label=' '.join([ifo,dq_name,bin_name]), 
                             range=(min(xvals), max(xvals)))
ax.legend(loc='upper left', markerscale=5)

# format plot
ax.set_ylabel('Data quality log likelihood')
ax.set_xlabel('Percentile')
ax.set_ylim(ymin=0,ymax=ymax)
ax.set_xlim(xmin=xmin,xmax=xmax)
if args.log_x:
    ax.set_xscale('log')

# add a grid to the plot
ax.grid()

yticks = ax.get_yticks()

# add second axis
ax2=ax.twinx()
ax2_ymax = numpy.exp(ymax)
ax2.set_ylim(1,ax2_ymax)
ax2.plot(xmax+1e9,100)
new_ticks = range(0,int(numpy.ceil(numpy.log10(ax2_ymax))))
ax2.set_yticks([10**t for t in new_ticks])
ax2.set_ylabel('Relative Trigger Rate')
ax2.set_xlim(xmin, xmax)
ax2.set_yscale('log')

# add meta data and save figure
plot_title = '%s: %s log likelihood versus percentile' % (ifo, dq_name)
plot_caption = 'The log likelihood verus percentile of a DQ product.'
pycbc.results.save_fig_with_metadata(fig, args.output_file,
                title = plot_title,
                caption = plot_caption,
                cmd = ' '.join(sys.argv))