Webb Sprague wrote:
> Does anyone have some vectorized code that pulls out all the row
> indices for any row which has an nan (or a number less than 1 or
> whatever). I want to subsequently be able to perform an operation
> with all the good rows. See the imaginary code below.
>
> a = numpy.array([[1,2],[nan,1], [2,3]])
> is_row_nan(a) == array([1])
> ii = numpy.negative(is_row_nan(a))
>
> a[ii,:] # these are the ones I want. Hopefully this is array([[1,2],[2,3]])
>
> I can imagine doing this with a loop or with (maybe) some fancy set
> union stuff, but I am at a loss for vectorized versions.
(Untested)
def is_row_nan(a):
return numpy.isnan(a).any(axis=-1)
--
Robert Kern
"I have come to believe that the whole world is an enigma, a harmless enigma
that is made terrible by our own mad attempt to interpret it as though it had
an underlying truth."
-- Umberto Eco
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