Re-hi,
thanks for all the comments. I have re-tried with
X = nm.random.rand( 1, 3 ) and the times (in seconds) were:
428.588043213 # scipy.dot, array
445.045716047 # numpy.dot, array
519.489458799 # scipy.dot, matrix
513.328601122 # numpy.dot, matrix
The scipy.dot and numpy.dot performs the
On 5/21/07, Charles R Harris <[EMAIL PROTECTED]> wrote:
On 5/21/07, David Cournapeau <[EMAIL PROTECTED]> wrote:
>
> Nils Wagner wrote:
> > Robert Cimrman wrote:
> >> I have come to a case where using a matrix would be easier than an
> >> array. The code uses lots of dot products, so I tested s
On 5/21/07, David Cournapeau <[EMAIL PROTECTED]> wrote:
Nils Wagner wrote:
> Robert Cimrman wrote:
>> I have come to a case where using a matrix would be easier than an
>> array. The code uses lots of dot products, so I tested scipy.dot()
>> performance with the code below and found that the arr
Nils Wagner wrote:
> Robert Cimrman wrote:
>> I have come to a case where using a matrix would be easier than an
>> array. The code uses lots of dot products, so I tested scipy.dot()
>> performance with the code below and found that the array version is much
>> faster (about 3 times for the given s
Robert Cimrman wrote:
> I have come to a case where using a matrix would be easier than an
> array. The code uses lots of dot products, so I tested scipy.dot()
> performance with the code below and found that the array version is much
> faster (about 3 times for the given shape). What is the reason
I have come to a case where using a matrix would be easier than an
array. The code uses lots of dot products, so I tested scipy.dot()
performance with the code below and found that the array version is much
faster (about 3 times for the given shape). What is the reason for this?
Or is something wro
