Iterating over Numpy matrix rows to apply a function each?

I want to be able to iterate over the matrix to apply a function to each row. How can I do it for a Numpy matrix ?

3 Answers

You can use numpy.apply_along_axis(). Assuming that your array is 2D, you can use it like:

import numpy as np mymatrix = np.matrix([[11,12,13], [21,22,23], [31,32,33]]) def myfunction(x): return sum(x) print(np.apply_along_axis(myfunction, axis=1, arr=mymatrix)) #[36 66 96] 

While you should certainly provide more information, if you are trying to go through each row, you can just iterate with a for loop:

import numpy m = numpy.ones((3,5),dtype='int') for row in m: print str(row) 

Here's my take if you want to try using multiprocesses to process each row of numpy array,

from multiprocessing import Pool import numpy as np def my_function(x): pass # do something and return something if __name__ == '__main__': X = np.arange(6).reshape((3,2)) pool = Pool(processes = 4) results = pool.map(my_function, map(lambda x: x, X)) pool.close() pool.join() 

pool.map take in a function and an iterable.
I used 'map' function to create an iterator over each rows of the array.
Maybe there's a better to create the iterable though.