Numpy transpose multiplication problem

Question

I tried to find the eigenvalues of a matrix multiplied by its transpose but I couldn't do it using numpy.

testmatrix = numpy.array([[1,2],[3,4],[5,6],[7,8]])
prod = testmatrix * testmatrix.T
print eig(prod)

I expected to get the following result for the product:

5    11    17    23
11    25    39    53
17    39    61    83
23    53    83   113

and eigenvalues:

Instead I got ValueError: shape mismatch: objects cannot be broadcast to a single shape when multiplying testmatrix with its transpose.

This works (the multiplication, not the code) in MatLab but I need to use it in a python application.

Can someone tell me what I'm doing wrong?

score 27 · Accepted Answer · edited Dec 09 '22 at 20:00

27

You might find this tutorial useful since you know MATLAB.

Also, try multiplying testmatrix with the dot() function, i.e. numpy.dot(testmatrix,testmatrix.T)

Apparently numpy.dot is used between arrays for matrix multiplication! The * operator is for element-wise multiplication (.* in MATLAB).

edited Dec 09 '22 at 20:00

Glorfindel

answered Jul 09 '10 at 13:42

Jacob

4

PEP 465 allows the use of the infix `@` operator: `mat1 @ mat2` – BallpointBen Dec 09 '16 at 19:15

score 8 · Answer 2 · answered Jul 09 '10 at 13:44

8

You're using element-wise multiplication - the * operator on two Numpy matrices is equivalent to the .* operator in Matlab. Use

prod = numpy.dot(testmatrix, testmatrix.T)

answered Jul 09 '10 at 13:44

ptomato

score 1 · Answer 3 · answered Dec 22 '22 at 13:45

1

You can also write testmatrix@testmatrix.T

answered Dec 22 '22 at 13:45

Sahil Sharma

2

Your answer could be improved with additional supporting information. Please [edit] to add further details, such as citations or documentation, so that others can confirm that your answer is correct. You can find more information on how to write good answers [in the help center](/help/how-to-answer). – Community Dec 23 '22 at 16:18

3 Answers3