[Numpy-discussion] checking element types in array
Zoho Vignochi
zoho.vignochi@gmail....
Sun May 18 08:59:10 CDT 2008
On Sat, 17 May 2008 14:58:20 -0400, Anne Archibald wrote:
> numpy arrays are efficient, among other reasons, because they have
> homogeneous types. So all the elements in an array are the same type.
> (Yes, this means if you have an array of numbers only one of which
> happens to be complex, you have to represent them all as complex numbers
> whose imaginary part happens to be zero.) So if A is an array A.dtype is
> the type of its elements.
>
> numpy provides two convenience functions for checking whether an array
> is complex, depending on what you want:
>
> iscomplex checks whether each element has a nonzero imaginary part and
> returns an array representing the element-by-element answer; so
> any(iscomplex(A)) will be true if any element of A has a nonzero
> imaginary part.
>
> iscomplexobj checks whether the array has a complex data type. This is
> much much faster, but of course it may happen that all the imaginary
> parts happen to be zero; if you want to treat this array as real, you
> must use iscomplex.
>
> Anne
>
>
> Anne
Thank you for the explanation. I knew there would be a speed penalty but
the current numpy dot doesn't work as expected with mpf or mpc just yet
and so I had to write my own. Your explanation helped as I decided to
treat all numbers as complex and just implemented the complex version.
Thanks, Zoho
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