On 8/2/2012 8:27 AM, Brian Holt wrote:
> Thanks Jim,
>
> Could you try it again with
>
> X = np.array([[0]])
>
> Note the double "[" bracket - this is what causes the problem for me.
>
> Cheers
> Brian

Sorry about that.

 >>> x = numpy.array([[0]])
 >>> a = numpy.asfortranarray(x)
 >>> a.flags
   C_CONTIGUOUS : False
   F_CONTIGUOUS : True
   OWNDATA : True
   WRITEABLE : True
   ALIGNED : True
   UPDATEIFCOPY : False
 >>>


>
> On 2 August 2012 15:23, Jim Vickroy<[email protected]>  wrote:
>> On 8/2/2012 6:05 AM, Brian Holt wrote:
>>> Hi list,
>>>
>>> I'm refactoring the tree module to introduce lazy argsorting and my
>>> unit tests are failing with:
>>>
>>>       Exception ValueError: ValueError(u'ndarray is not Fortran
>>> contiguous',) in 'sklearn.tree._tree.Tree.recursive_partition' ignored
>>>
>>> I think I've pinned down the problem to this minimal sample:
>>>
>>>>>> import numpy as np
>>>>>> X = np.array([[0]])
>>>>>> a = np.asfortranarray(X)
>>>>>> a.flags
>>>     C_CONTIGUOUS : True
>>>     F_CONTIGUOUS : False
>>>     OWNDATA : True
>>>     WRITEABLE : True
>>>     ALIGNED : True
>>>     UPDATEIFCOPY : False
>>>
>>> Is this a bug in numpy? And if so, is there any workaround?
>>>
>>> Regards
>>> Brian
>> Hi Brian,
>>
>> Here are the results for my setup:
>>
>>   >>>  sys.version
>> '2.7.3 (default, Apr 10 2012, 23:31:26) [MSC v.1500 32 bit (Intel)]'
>>   >>>  import numpy
>>   >>>  numpy.__version__
>> '1.6.2'
>>   >>>  x = numpy.array([0])
>>   >>>  a = numpy.asfortranarray(x)
>>   >>>  a.flags
>>     C_CONTIGUOUS : True
>>     F_CONTIGUOUS : True
>>     OWNDATA : True
>>     WRITEABLE : True
>>     ALIGNED : True
>>     UPDATEIFCOPY : False
>>
>>
>>
>>
>>
>>
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