On 12/22/10 9:16 AM, Ian Stokes-Rees wrote:
> What is the most efficient way to do the Matlab equivalent of nnz(M)
> (nnz = number-of-non-zeros function)?
Thanks to all the various responses. I should have mentioned that I'm
using scipy.sparse, and lil_matrix objects have a method "getnnz()"
wh
To answer the part about the most efficient way to do that,
In [1]: a = array([0,1,4,76,3,0,4,67,9,5,3,9,0,5,23,3,0,5,3,3,0,5,0])
In [8]: %timeit len(where(a!=0)[0])
10 loops, best of 3: 6.54 us per loop
In [9]: %timeit (a!=0).sum()
10 loops, best of 3: 9.81 us per loop
Seems like the w
On Wednesday, December 22, 2010 07:16:17 am Ian Stokes-Rees wrote:
> What is the most efficient way to do the Matlab equivalent of nnz(M)
> (nnz = number-of-non-zeros function)?
>
> I've tried Google, but no luck.
>
> My assumption is that something like
>
> a != 0
>
> will be used, but I'm not
On 12/22/2010 9:16 AM, Ian Stokes-Rees wrote:
> a != 0
>
> will be used, but I'm not sure then how to "count" the number of "True"
> entries.
(a != 0).sum()
hth,
Alan Isaac
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What is the most efficient way to do the Matlab equivalent of nnz(M)
(nnz = number-of-non-zeros function)?
I've tried Google, but no luck.
My assumption is that something like
a != 0
will be used, but I'm not sure then how to "count" the number of "True"
entries.
TIA.
Ian
<>__
