output operand requires a reduction, but reduction is not enabled

http://stackoverflow.com/questions/11625412/add-a-vector-to-array

 

A really stupid question, but I could not figure the right way..

1. A is a 2 by 2 matrix, and B is a 2 by 1 matrix.
2. In a 10 iterations loop, B_new=A*B. B_new is 2 by 1.
3. Save B_new to an output matrix B_final after each iteration. So in the end, B_final is 2 by 10.

However, I have problem of adding B to B_new in a loop. Below is my code, can anyone give me some suggestions?

import numpy as np a=np.ones(shape=(2,2)) b=np.ones(shape=(2,1)) c_final=np.zeros(shape=(2,10))for i in range(0,10): c=np.dot(a,b) b=c c_final[:,i]=c

Here is the error message:

 c_final[:,i]=c ValueError: output operand requires a reduction, but reduction isnot enabled

The error you're seeing is because when numpy broadcasts c_final[:,i] and np.dot(a,b)together it produces an array with shape (2,2), which then can't be assigned to c_final[:,i]since it has a shape of (2,1). I think it's much clearer if you just play around with it in the interpreter:

>>>import numpy as np >>> a = np.ones((2,2))>>> b = np.ones((2,1))>>> c_final = np.zeros((2,10))>>> np.dot(a,b) array([[2.],[2.]])>>> np.dot(a,b).shape (2,1)>>> c_final[:,0] array([0.,0.])>>> c_final[:,0].shape (2,)>>> np.broadcast(c_final[:,0],np.dot(a,b)).shape (2,2)

The way around this is to flatten np.dot(a,b) by using np.squeeze or something similar so that when they are broadcast together they produce a 2 element array. For example:

>>> c_final[:,0]= np.dot(a,b).squeeze()

You're not alone in finding the error message unhelpful. Someone filed a ticket about this about a year ago.