# script Distribution-fromImage.py
''' generate 2d random numbers 
distributed according to brightness of an image
.. author:: Guenter Quast <g.quast@kit.edu>
'''

import numpy as np
import matplotlib.pyplot as plt
from PIL import Image

#open an image
img=Image.open('image.jpg')
#img.show()
print("image size loaded:", img.size[0], img.size[1])
pix=img.load()

def rand_fromImage(size=1):
  # generate <size> pairs of random numbers from an image
  def r_fromImage(maxtrials=10000):
  # helper function: generate 2 random numbers from an image
  #   probability to select (r1,r2)depends on brightness of a pixel
    cnt=0
    while cnt<maxtrials:
      cnt+=1
      rx=np.random.uniform()
      ry=np.random.uniform()
      i=int(img.size[0]*rx-0.5)
      j=img.size[1]-1-int(img.size[1]*ry-0.5)
      r,g,b = pix[i,j]     # brightness of pixel
      if(3*255*np.random.uniform()>r+b+g):
        return rx,ry
# end helper function
  cnt=0
  x=[]
  y=[]
  while cnt<size:
    cnt+=1
    rx,ry=r_fromImage()
    x.append(rx)
    y.append(ry)
  return x,y

# -----------------------------------------------------------------------
if __name__ == "__main__":
  x, y = rand_fromImage(20000)
  
# plot distributions
  fig=plt.figure(figsize=(10,10))
  ax1=fig.add_subplot(2,2,1)
  plt.hist(y,50) # histogram data
  ax1.set_title('y projection ')

  ax4 =fig.add_subplot(2,2,4) # x histogram and statistics
  plt.hist(x,50) # histogram data
  ax4.set_title('x projection')

  ax2 =fig.add_subplot(2,2,2) # 2d historgram and statistics
  plt.hist2d(x,y,50,cmap='Greys')
  ax2.set_title('2d distribution from image')

  plt.show()