Thanks Ben.
cheers,
Chao
2012/1/2 Benjamin Root <ben.r...@ou.edu>
> On Mon, Jan 2, 2012 at 11:10 AM, Chao YUE <chaoyue...@gmail.com> wrote:
>
>> Dear all matplotlib users,
>>
>> Happy New Year.
>> I try to check the distribution of a 2D array and I find that the
>> histogram plot function doesn't respect the numpy masked array?
>>
>>
>> In [188]: a=range(1,6); b=np.array(a+a[::-1])
>>
>> In [189]: b=np.ma.masked_equal(b,2); b=np.ma.masked_equal(b,5)
>>
>> In [190]: b
>> Out[190]:
>> masked_array(data = [1 -- 3 4 -- -- 4 3 -- 1],
>> mask = [False True False False True True False False
>> True False],
>> fill_value = 5)
>>
>>
>> In [191]: n,bins,patches=plt.hist(b)
>>
>> In [192]: n
>> Out[192]: array([2, 0, 2, 0, 0, 2, 0, 2, 0, 2])
>>
>> In [193]: n.sum()
>> Out[193]: 10
>>
>> it seems that all the elements (masked or not) are counted in the history
>> plotting?
>> and the original value is used but not the fill_value?
>>
>> I attach a figure below.
>>
>> In [194]: plt.show()
>>
>>
> Yes, this is a known issue (at least, from the comments within the
> function). Looks like hist() uses np.asarray() instead of np.asanyarray(),
> which would result in the array being stripped of its mask. However, I
> don't think the fix is as straight-forward as changing that to
> np.asanyarray(). I will take a peek and see what can be done.
>
> Ben Root
>
>
--
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Chao YUE
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