from yt.mods import *

from matplotlib import rc
rc('text', usetex=True)
rc('font', family='serif')

import pylab as pl
#from scipy import *
#import scipy.signal
from h5py import File
#import pyfits
import os
import string
from matplotlib import pyplot 
from matplotlib import pyplot as plt
from matplotlib import pylab
from matplotlib import colors
#from pyreadcol import *
import numpy as np
from matplotlib.ticker import NullFormatter
import pickle

n=28

f=open('../../Ionization/FOF/RedshiftOutput%04i-halos.dat'%n,'r')
lines=f.readlines()
f.close()

f=open('Luminosity_M1600.out','r')
lines1=f.readlines()
f.close()

Mass = []
#Lum = []
Mag = []
for line in lines1:
    line1=lines[int(line.split()[0])+1]
    if float(line1.split()[0])==-1.0: continue
    Mass.append(float(line1.split()[4]))
    Mag.append(float(line.split()[2]))

Mass=np.array(Mass)
#Lum=np.array(Lum)
Mag=np.array(Mag)
x_max = 0 # int(Mass.max()+1)
x_min = -20

y_max = 10
y_min = 6.5

x_bins = 60    #60
y_bins = 70  #200

filename = 'M1600_virialM'
fields = ["HaloNumber"]

fields_label = ['Count']
fields_min = [0]

#prof2d = BinnedProfile2D(sphere, d_bins, "Density", d_min, d_max, True,beta_bins, "beta", beta_min, beta_max, True)
data,xvals,yvals = pylab.histogram2d(Mag,np.log10(Mass),bins=[x_bins,y_bins],range=[[x_min,x_max],[y_min,y_max]])

for field, cbarlabel,field_min in zip(fields,fields_label,fields_min):
    ylabel = r'log$_{10}$ (M$_{virial}$ $[M_\odot]$)'
    xlabel = r'$M_V$'

    dy = yvals[1]-yvals[0]
    dx = xvals[1]-xvals[0]
    xvals1 = xvals[0:-1]+dx/2.0
    yvals1 = yvals[0:-1]+dy/2.0

    #data /= dlogx*dlogy

    intmin = 0
    intmax = data[0:,0:].max()

    fig = pl.figure(figsize=[8,6])
    ax = fig.add_subplot(111)

    mynorm = colors.Normalize([intmin, intmax])

    fontsize=24
    extent = [xvals[0], xvals[-1], yvals[0], yvals[-1]]

    # put in ,norm=colors.LogNorm() if you want colorbar to log
    im = ax.imshow(data.T, cmap=pl.cm.binary,extent=extent, interpolation='nearest',\
               origin='lower',aspect='auto')
    
    #X, Y = np.meshgrid(xvals,yvals)
    #im = ax.imshow(data,cmap=pl.cm.binary, norm=mynorm)
    #ax.set_xscale('log')
    #ax.set_yscale('log')
    cbar = fig.colorbar(im, fraction=0.05, format = '%i', ticks=np.linspace(intmin,intmax, (intmax-intmin)+1), pad=0.01, shrink=0.9)
    cbar.set_label('%s' % cbarlabel)

    pl.xlim(xvals.max(), xvals.min())
    #pl.ylim(yvals.min(), yvals.max())
    pl.ylim(yvals.min(), yvals.max())

    pl.xlabel('%s' % xlabel)
    pl.ylabel('%s'% ylabel)
    pl.savefig('RD%04i_%s.eps'% (n,filename),format='eps',dpi=160)
    fig.clf()