[Numpy-discussion] np.ma.argmax not respecting the mask?

[Chao YUE]

Sorry I didn't the docs very carefully. there is no doc for np.ma.argmax
for indeed there is for np.ma.argmin

so it's an expected behavior rather than a bug. Let some heavy users to say
their ideas.

Practicaly, the returned value of 0 will be always confused with the values
which are not masked
but do have the minimum or maximum values at the 0 position over the
specified axis.

One way to walk around is:


data_mask = np.ma.mean(axis=0).mask

np.ma.masked_array(np.ma.argmax(data,axis=0), mask=data_mask)

Chao


On Tue, Jul 9, 2013 at 4:26 PM, Pierre Gerard-Marchant <pgmdevlist at gmail.com
> wrote:

>
> On Jul 9, 2013, at 16:08 , Sebastian Berg <sebastian at sipsolutions.net>
> wrote:
>
> > On Tue, 2013-07-09 at 15:14 +0200, Stéfan van der Walt wrote:
> >> On Tue, Jul 9, 2013 at 2:55 PM, Chao YUE <chaoyuejoy at gmail.com> wrote:
> >>> I am using 1.7.1 version of numpy and np.ma.argmax is not repecting the
> >>> mask?
> >>>
> >>> In [96]: d3
> >>> Out[96]:
> >>> masked_array(data =
> >>> [[-- -- -- -- 4]
> >>> [5 -- 7 8 9]],
> >>>             mask =
> >>> [[ True  True  True  True False]
> >>> [False  True False False False]],
> >>>       fill_value = 6)
> >>>
> >>>
> >>> In [97]: np.ma.argmax(d3,axis=0)
> >>> Out[97]: array([1, 0, 1, 1, 1])
> >>
> >> This is the result I would expect.  If both values are masked, the
> >> fill value is used, so there is always an argmin value.
> >>
> >
> > To be honest, I would expect the exact opposite. If there is no value,
> > there is no minimum argument -> either its an error, or it signals
> > invalid in some other way. On masked arrays I would expect it to be
> > masked to signal this.
>
> The doc is quite clear: masked values are replaced by `fill_value` when
> determining the argmax/argmin. Attaching a mask a posteriori is always
> doable, but making the output of np.ma.argstuff a MaskedArray may be a
> nuisance at this point (any input from heavy users?).
>
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Chao YUE
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