I would like to know a simple way to know the size of a given dimension of a
numpy array.
Example
A = numpy.zeros((10,20,30),float)
The size of the second dimension of the array A is 20.
Thanks.
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How can i take out the diagonal values of a matrix and fix them to zero?
Example:
input: [[2,3,4],[3,4,5],[4,5,6]]
output: [[0,3,4],[3,0,5],[4,5,0]]
Thanks.
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Sent from th
Suppose i have an array A of length n
I want a variable b to be an array consisting of the first k elements of A
and variable c to be an array with the last n-k elements of A.
How do you do this?
Example A = np.array([1,2,3,4,5,6]), k = 2
b = [1,2]
c=[3,4,5,6]
Thanks.
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I have another matrix operations which seems a little more complicated.
Let A be an n x n matrix and let S be a subset of {0,...,n-1}. Assume
S is represented by a binary vector s, with a 1 at the index i if i is
in S. (e.g. if S={0,3} then s = [1,0,0,1])
I re-post the question because the examp
Hello,
I want to "divide" an n x n (2-dimension) numpy array matrix A by a n
(1-dimension) array d as follows:
Take n = 2.
Let A= 2 3
1 10
and let d = [ 3 2 ]
Then i would like to have "A/d" = 2/3 3/3
1/2 10/2
This is to avoid loops to i
Hello,
I want to "divide" an n x n (2-dimension) numpy array matrix A by a n
(1-dimension) array d as follows:
Take n = 2.
Let A= 2 3
1 10
and let d = [ 3 2 ]
Then i would like to have "A/d" = 2/3 3/3
1/2 10/2
This is to avoid loops t