问题
Here's the matrix
>> x = [2 7 5 9 2; 8 3 1 6 10; 4 7 3 10 1; 6 7 10 1 8;2 8 2 5 9]
Matlab gives me
>> mtimes(x',x)
ans =
124 124 94 122 154
124 220 145 198 179
94 145 139 101 121
122 198 101 243 141
154 179 121 141 250
However, the same operation(on same data) in python(numpy) produces different result. I'm unable to understand why?
import numpy as np
a = [[2, 7, 5, 9, 2],[8,3,1,6,10],[4,7,3,10,1],[6,7,10,1,8],[2,8,2,5,9]]
x = np.array(a)
print 'A : ',type(x),'\n',x,'\n\n'
# print np.transpose(A)
X = np.multiply(np.transpose(x),x)
print "A'*A",type(X),'\n',X
produces
A : <type 'numpy.ndarray'>
[[ 2 7 5 9 2]
[ 8 3 1 6 10]
[ 4 7 3 10 1]
[ 6 7 10 1 8]
[ 2 8 2 5 9]]
A'*A <type 'numpy.ndarray'>
[[ 4 56 20 54 4]
[ 56 9 7 42 80]
[ 20 7 9 100 2]
[ 54 42 100 1 40]
[ 4 80 2 40 81]]
回答1:
Numpy documentation states that the operator you apply performs element-wise multiplication.
However, mtimes in MATLAB does matrix multiplication.
To verify, MATLAB syntax for element-wise multiplication produces the same result you see in numpy:
disp(x.'.*x)
4 56 20 54 4
56 9 7 42 80
20 7 9 100 2
54 42 100 1 40
4 80 2 40 81
来源：https://stackoverflow.com/questions/34028059/matrix-multiplication-resulting-in-different-values-in-matlab-and-numpy