Reputation: 141
Here is my code. What I want it to return is an array of matrices
[[1,1],[1,1]], [[2,4],[8,16]], [[3,9],[27,81]]
I know I can probably do it using for loop and looping through my vector k, but I was wondering if there is a simple way that I am missing. Thanks!
from numpy import *
import numpy as np
k=np.arange(1,4,1)
print k
def exam(p):
return np.array([[p,p**2],[p**3,p**4]])
print exam(k)
The output:
[1 2 3]
[[[ 1 2 3]
[ 1 4 9]]
[[ 1 8 27]
[ 1 16 81]]]
Upvotes: 1
Views: 46
Reputation: 64368
The key is to play with the shapes and broadcasting.
b = np.arange(1,4) # the base
e = np.arange(1,5) # the exponent
b[:,np.newaxis] ** e
=>
array([[ 1, 1, 1, 1],
[ 2, 4, 8, 16],
[ 3, 9, 27, 81]])
(b[:,None] ** e).reshape(-1,2,2)
=>
array([[[ 1, 1],
[ 1, 1]],
[[ 2, 4],
[ 8, 16]],
[[ 3, 9],
[27, 81]]])
If you must have the output as a list of matrices, do:
m = (b[:,None] ** e).reshape(-1,2,2)
[ np.mat(a) for a in m ]
=>
[matrix([[1, 1],
[1, 1]]),
matrix([[ 2, 4],
[ 8, 16]]),
matrix([[ 3, 9],
[27, 81]])]
Upvotes: 2