On 11/8/06, Keith Goodman <[EMAIL PROTECTED]> wrote:
Same with the operator *, it takes two arguments but is in infix order, i.e., left side and right side.
And if they are arrays:
A = dot(B,dot(C,D))
Python has a dearth of recognized operators which makes this necessary once '*' is used for elementwise multiplication, it's a long standing complaint. You can use matrices in numpy, in which case '*' is used for matrix multiplication like in matlab, but I think it would be better to get used to using arrays as they are the numpy core.
Chuck
On 11/8/06, izak marais <[EMAIL PROTECTED]> wrote:
> Sorry if this is an obvious question, but what is the easiest way to
> multiply matrices in numpy? Suppose I want to do A=B*C*D. The ' * ' operator
> apparently does element wise multiplication, as does the 'multiply' ufunc.
> All I could find was the numeric function 'matrix_multiply, but this only
> takes two arguments.
Same with the operator *, it takes two arguments but is in infix order, i.e., left side and right side.
If B and C and D are matrices, then '*' is matrix multiplication.
And if they are arrays:
A = dot(B,dot(C,D))
Python has a dearth of recognized operators which makes this necessary once '*' is used for elementwise multiplication, it's a long standing complaint. You can use matrices in numpy, in which case '*' is used for matrix multiplication like in matlab, but I think it would be better to get used to using arrays as they are the numpy core.
Chuck
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