Closed
Description
When you refer to the documentation of np.array here
http://docs.scipy.org/doc/numpy-1.10.0/reference/generated/numpy.array.html
The page says that order='A' is default, while the function prototype indicates order=None is default. Initially I assumed that both of them give the same results, but that is not the case. See the following snippet.
>>> import numpy as np
>>> from numpy.lib.stride_tricks import as_strided
>>> a = np.array((100000,), dtype=np.float64)
>>> b = as_strided(a, strides=[8, 512], shape=[10, 64])
>>> b.flags
C_CONTIGUOUS : False
F_CONTIGUOUS : False
OWNDATA : False
WRITEABLE : True
ALIGNED : True
UPDATEIFCOPY : False
>>> c = np.array(b, order=None, copy=True)
>>> c.flags # see that C_CONTIGUOUS is False
C_CONTIGUOUS : False
F_CONTIGUOUS : True
OWNDATA : True
WRITEABLE : True
ALIGNED : True
UPDATEIFCOPY : False
>>> d = np.array(b, order='A', copy=True)
>>> d.flags # see that C_CONTIGUOUS is True
C_CONTIGUOUS : True
F_CONTIGUOUS : False
OWNDATA : True
WRITEABLE : True
ALIGNED : True
UPDATEIFCOPY : FalseI expected that when order=None and copy=True the output would be C-Contiguous, since order=None is the default in the function prototype. I believe that either None should behave exactly like 'A' or the documentation of the function prototype should be changed to mention that 'A' is the default order.
Numpy Version = '1.10.2'
Python 2.7.6