[SciPy-User] 3D array problem in Python
Thøger Rivera-Thorsen
thoger.emil@gmail....
Sun Dec 30 09:47:07 CST 2012
Use np.where() or logical indexing (same thing, really) to mask your
array, then perform the operations. Let's say your array is called A:
A[float(A) == 0.0] = 0.0
A[float(A) != 0.0] = [...etc.]
This, of course, only works if the operation for an entry doesn't depend
on other entries in the array; but it should give you a great speed gain.
Cheers;
Emil
On 12/30/2012 04:32 AM, Happyman wrote:
> Hello
>
> I have 3 dimensional array which I want to calculate in a huge
> process. Everything is working well if I use ordinary way which is
> unsuitable in Python like the following:
>
> nums=32
> rows=120
> cols=150
>
> for k in range(0,nums):
> for i in range(0,rows):
> for j in range(0,cols):
> if float ( R[ k ] [ i ] [ j ] ) == 0.0:
> val11 [ i ] =0.0
> else:
> val11[ i ] [ j ], val22[ i ][ j ] = integrate.quad(
> lambda x : F1(x)*F2(x) , 0 , pi)
>
> But, this calculation takes so long time, let's say about 1 hour
> (theoretically)... Is there any better way to easily and fast
> calculate the process such as [ F( i ) for i in xlist ] or something
> like that rather than using for loop?
>
>
>
>
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