import matplotlib.pyplot as plt
import numpy as np
import sys

"""Totally random"""
# Red gradient
A = np.random.random( (10,10) )
plt.gray()
plt.imshow(A,interpolation='nearest')
plt.show()
"""
# Red gradient
A = np.random.random( (100,100,3) )
# i is the rows, j is the columns
for i in range(100):
  for j in range(100):
    A[i,j,0] = 1-(i)*0.01 #Red
    A[i,j,1] = 0          #Green
    A[i,j,2] = 0          #Blue
print A
plt.gray()
plt.imshow(A,interpolation='nearest')
plt.show()
"""
"""
# Red to black to green
A = np.zeros( (100,100,3) )
# i is the rows, j is the columns
for i in range(100):
  for j in range(100):
    if i < 50:
      A[i,j,0] = 1-(i*0.02)
      A[i,j,1] = 0
      A[i,j,2] = 0
    else:
      A[i,j,0] = 0
      A[i,j,1] = (i-50)*0.02
      A[i,j,2] = 0
      
plt.gray()
plt.imshow(A,interpolation='nearest')
plt.show()
"""
GE = np.zeros((100,7,3))
all_lines = open('geneexpression.txt').readlines()
all_values = sum((line.strip().split('\t')[1:] for line in all_lines), [])
min_value = min(float(v) for v in all_values)
max_value = max(float(v) for v in all_values)

for i in range(100):
  line = all_lines[i]
  line = line.strip().split('\t')
  for j in range(7):
    #GE[i][j] = float(line[1+j])
    value = float(line[1+j])
    if value < 0.:
      # Between red and black
      GE[i,j,0] = value/min_value
      GE[i,j,1] = 0.
      GE[i,j,2] = 0.
    else:
      # Between black and full green
      GE[i,j,0] = 0.
      GE[i,j,1] = value/max_value
      GE[i,j,2] = 0.

plt.figure()
a = plt.imshow(GE,interpolation='nearest', aspect='auto')
plt.show()