looping in array vs looping in a dic

[giuseppe.amatulli at gmail.com]

Hi,  
I have this script in python that i need to apply for very large arrays (arrays coming from satellite images). 
The script works grate but i would like to speed up the process. 
The larger computational time is in the for loop process.
Is there is a way to improve that part?
Should be better to use dic() instead of np.ndarray for saving the results?
and if yes how i can make the sum in dic()(like in the correspondent matrix[row_c,1] = matrix[row_c,1] + valuesRaster[row,col] )?
If the dic() is the solution way is faster?

Thanks
Giuseppe

import numpy  as  np
import sys
from time import clock, time

# create the arrays

start = time()
valuesRaster = np.random.random_integers(0, 100, 100).reshape(10, 10)
valuesCategory = np.random.random_integers(1, 10, 100).reshape(10, 10)

elapsed = (time() - start)
print(elapsed , "create the data")

start = time()

categories = np.unique(valuesCategory)
matrix = np.c_[ categories , np.zeros(len(categories))]

elapsed = (time() - start)
print(elapsed , "create the matrix and append a colum zero ")

rows = 10
cols = 10

start = time()

for col in range(0,cols):
    for row in range(0,rows):
        for row_c in range(0,len(matrix)) :
            if valuesCategory[row,col] == matrix[row_c,0] :
                matrix[row_c,1] = matrix[row_c,1] + valuesRaster[row,col]
                break
elapsed = (time() - start)
print(elapsed , "loop in the  data ")

print (matrix)