[Numpy-discussion] Nonzero behaving strangely?

[Matthieu Brucher]

Hi,

Did you try np.where(res[:,4]==2) ?

Matthieu

2011/3/17 santhu kumar <mesanthu at gmail.com>

> Hello all,
>
> I am new to Numpy. I used to program before in matlab and am getting used
> to Numpy.
>
> I have a array like:
> res
> array([[ 33.35053669,  49.4615004 ,  44.27631299,   1.        ,   2.
> ],
>        [ 32.84263059,  50.24752036,  43.92291659,   1.        ,   0.
> ],
>        [ 33.68999668,  48.90554673,  43.51746687,   1.        ,   0.
> ],
>        [ 34.11564931,  49.77487763,  44.83843076,   1.        ,   0.
> ],
>        [ 32.4641859 ,  48.65469145,  45.09300791,   1.        ,   3.
> ],
>        [ 32.15428526,  49.26922262,  45.92959026,   1.        ,   0.
> ],
>        [ 31.23860825,  48.21824628,  44.30816331,   1.        ,   0.
> ],
>        [ 30.71171138,  47.45600573,  44.9282456 ,   1.        ,   0.
> ],
>        [ 30.53843426,  49.07713258,  44.20899822,   1.        ,   0.
> ],
>        [ 31.54722284,  47.61953925,  42.95235178,   1.        ,   0.
> ],
>        [ 32.44334635,  48.10500653,  42.51103537,   1.        ,   0.
> ],
>        [ 31.77269609,  46.53603145,  43.06468455,   1.        ,   0.
> ],
>        [ 30.1820843 ,  47.80819604,  41.77667819,   1.        ,   0.
> ],
>        [ 30.78652668,  46.82907769,  40.38586451,   1.        ,   0.
> ],
>        [ 30.05963091,  46.84268609,  39.54583693,   1.        ,   0.
> ],
>        [ 31.75239177,  47.22768463,  40.00717713,   1.        ,   0.
> ],
>        [ 30.94617127,  45.76986265,  40.68226643,   1.        ,   0.
> ],
>        [ 33.20069679,  47.42127403,  45.66738249,   1.        ,   0.
> ],
>        [ 34.39608116,  47.25481126,  45.4438599 ,   1.        ,   0.
> ]])
>
> The array is 19X5.
> When I do:
> nid = (res[:,4]==2).nonzero()
> nid tuple turns out to be empty. But the very first row satisfies the
> criteria.
>
> nid = (res[:,4]==3).nonzero(), works out and finds the 5th row.
>
> Am i doing something wrong?
> I basically want to find the rows whose fifth coloumn(4th in numpy matrix
> format) is 2.
>
> Any suggestions?
> Thanks
> Santhosh
>
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>


-- 
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