# [Numpy-discussion] OWNDATA flag and reshape() -- views vs. copies

Guillaume Desjardins guillaume.desjardins@gmail....
Fri Apr 11 12:06:48 CDT 2008

```I'm pretty new to Python and numpy (longtime c / matlab programmer),
but after a read through some of the past threads and Travis' "Guide
to Numpy", I think I have a fairly good understanding of how the
reshape() function / methods work, with regards to views and copies.
For what its worth (and to make things clearer), my understanding is
that:

* Function reshape: create a view, or if it can't (i.e. resulting
array cannot be expressed with constant stride parameters), a copy
* Method obj.reshape(): creates a view, or throws an exception if it can't

Now assuming that is the case, I do not understand the behaviour of
the following code.

a = array([[1,2,3,4],[5,6,7,8],[9,10,11,12]]);
a.flags
C_CONTIGUOUS : True
F_CONTIGUOUS : False
OWNDATA : True
WRITEABLE : True
ALIGNED : True
UPDATEIFCOPY : False

b = a[1:,1:3] # creates view of a
>> array([[ 6,  7],
[10, 11]])
b.flags
C_CONTIGUOUS : False
F_CONTIGUOUS : False
OWNDATA : False
WRITEABLE : True
ALIGNED : True
UPDATEIFCOPY : False

c = reshape(b,(4,1))  # RESHAPE FUNCTION: should copy, as view of this
is impossible (? isn't it ?)
c
>> array([[ 6],
[ 7],
[10],
[11]])
c.flags
C_CONTIGUOUS : True
F_CONTIGUOUS : False
OWNDATA : False
WRITEABLE : True
ALIGNED : True
UPDATEIFCOPY : False

First question: if c is a copy of b, then why isn't the OWNDATA set to true ?
To prove that it is indeed a copy,
>> c[0] = 600
modifies the values of c but not of b and a (while modifying b - which
is clearly a view - also modifies a)

d = b.reshape((4,1))   # RESHAPE METHOD: same thing but with method...
shouldn't this give an error ?
d.flags
C_CONTIGUOUS : True
F_CONTIGUOUS : False
OWNDATA : False
WRITEABLE : True
ALIGNED : True
UPDATEIFCOPY : False

Second question: shouldn't b.reshape((4,1)) raise a ValueError since
it can't (as far as I see it) create a view ?
Once again, modifying d does not affect b or a (hence it is a copy).

Thanks for clearing up this issue. It is imperative that I know
exactly when numpy creates views vs. copies (and that I understand all
the intricacies), as I'm planning on doing A LOT of reshape() with
inplace modifications.

Hope I'm not polluting the mailing list with a newbie question.