Pierre GM wrote:
> Ryan,
> Thanks for reporting. An idea would be to force the dtype of the
> masked column to the largest dtype of the other columns (in your
> example, that would be int). I'll try to see how easily it can be done
> early next week. Meanwhile, you can always give an explicit dtype at
> creation.
Ok, thanks. I've dug a little further, and it seems like the problem is that a
column of all missing values ends up as a column of all None's. When you create
a (masked) array from a list of None's, you end up with an object array. On one
hand I'd love for things to behave differently in this case, but on the other I
understand why things work this way.
Ryan
>
> On Jan 24, 2009, at 5:58 PM, Ryan May wrote:
>
>> Pierre,
>>
>> I've found what I consider to be a bug in the new mafromtxt (though
>> apparently it
>> existed in earlier versions as well). If you have an entire column
>> of data in a
>> file that contains only masked data, and try to get mafromtxt to
>> automatically
>> choose the dtype, the dtype gets selected to be object type. In
>> this case, I'd
>> think the better behavior would be float, but I'm not sure how hard
>> it would be
>> to make this the case. Here's a test case:
>>
>> import numpy as np
>> from StringIO import StringIO
>> s = StringIO('1 2 3\n4 5 6\n')
>> a = np.mafromtxt(s, missing='2,5', dtype=None)
>> print a.dtype
>>
>> Ryan
>>
>> --
>> Ryan May
>> Graduate Research Assistant
>> School of Meteorology
>> University of Oklahoma
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>
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--
Ryan May
Graduate Research Assistant
School of Meteorology
University of Oklahoma
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