from numpy import shape, histogram2d, arange, newaxis, array, nditer, zeros, histogram
from numpy import sqrt, pi, exp, log, log10, sin, cos, where

from matplotlib.pyplot import figure, matshow, savefig, show

from matplotlib.colors import LogNorm

#from scipy.signal import convolve2d

from Read import  resultDirectory, ReadRadial, ReadAngleVsEnergy
from Analytic import Analytic_theta

from Constants import degre

thetalim = 180

philim = 180
step = 0.25 #deg

bining = array([int(2*philim/step)+1,int(2*thetalim/step)+1])

philim=float(philim)
thetalim=float(thetalim)
limits = [[-thetalim,thetalim],[-philim,philim]]

def computeMap(theta,phi,weight,energy,saveId,nbBins=50,borne=[180,180]):

   '''
      Plot 2D histogram of arrival direction of the photons with energy upper than Elim
      Input: list of directories
      Input (optional): lower energy limit (in GeV (default = 100MeV)
      Input (optional): nature of the source (default isotrop) 
      Input (optional): limits on theta, phi 
      Output: 2D histogram of theta cos(phi), theta sin(phi)
   '''

   fig = figure()

   #===============================================================================================#
   #  IMAGE
   #===============================================================================================#

   ax = fig.add_subplot(111)

   #H,xedges,yedges = histogram2d(theta*cos(phi),theta*sin(phi),bining,weights=weight,range=limits)
   #conv=convolve2d(H,source[0],boundary="wrap",mode="same")

   H,xedges,yedges,im = ax.hist2d(theta*cos(phi),theta*sin(phi),bining,weights=weight,
         norm=LogNorm(),range=limits)

   cbar=fig.colorbar(im, ax=ax)
   cbar.ax.set_ylabel("counts")
   ax.set_xlim((-borne[0],borne[0]))
   ax.set_ylim((-borne[1],borne[1]))
   ax.set_xlabel("$\\theta$ $\\cos(\\phi)$ [deg]")
   ax.set_ylabel("$\\theta$ $\\sin(\\phi)$ [deg]")
   ax.grid(b=True,which='major')

   ax.set_title(saveId+" - isotrop")
   savefig(resultDirectory+saveId+"/map_isotrop.png")

#def isotrop():
#   return array([[1]]), "isotropic"
#
#def Gaussian2D(center=[0,0],fwhm=0.01):
#   x = arange(-thetalim,thetalim+step,step)
#   y = arange(-philim,philim+step,step)
#   y = y[:,newaxis]
#   return exp(-4*log(2) * ((x-center[0])**2 + (y+center[1])**2) / fwhm**2), "jet_"+str(fwhm)