[Numpy-discussion] Problem with concatenate and object arrays
Charles R Harris
charlesr.harris at gmail.com
Wed Sep 6 20:52:42 CDT 2006
On 9/6/06, Charles R Harris <charlesr.harris at gmail.com> wrote:
> On 9/6/06, Travis Oliphant <oliphant.travis at ieee.org> wrote:
> > Charles R Harris wrote:
> > >
> > > Where is array at this point?
> > Basically it supports the old Numeric behavior wherein object array's
> > are treated as before *except* for when an error would have occurred
> > previously when the "new behavior" kicks in. Anything that violates
> > that is a bug needing to be fixed.
> > This leaves the new object-array constructor used less often. It could
> > be exported explicitly into an oarray constructor, but I'm not sure
> > about the advantages of that approach. There are benefits to having
> > object arrays constructed in the same way as other arrays. It turns out
> > many people actually like that feature of Numeric, which is the reason I
> > didn't go the route of numarray which pulled object arrays out.
> > At this point, however, object arrays can even be part of records and so
> > need to be an integral part of the data-type description. Pulling that
> > out is not going to happen. A more intelligent object-array
> > constructor, however, may be a useful tool.
> OK. I do have a couple of questions. Let me insert the docs for array and
> asarray :
> """array(object, dtype=None, copy=1,order=None, subok=0,ndmin=0)
> Return an array from object with the specified date-type.
> object - an array, any object exposing the array interface, any
> object whose __array__ method returns an array, or any
> (nested) sequence.
> dtype - The desired data-type for the array. If not given, then
> the type will be determined as the minimum type required
> to hold the objects in the sequence. This argument can
> be used to 'upcast' the array. For downcasting, use the
> .astype(t) method.
> copy - If true, then force a copy. Otherwise a copy will only
> if __array__ returns a copy, obj is a nested sequence, or
> a copy is needed to satisfy any of the other requirements
> order - Specify the order of the array. If order is 'C', then the
> array will be in C-contiguous order (last-index varies the
> fastest). If order is 'FORTRAN', then the returned array
> will be in Fortran-contiguous order (first-index varies
> fastest). If order is None, then the returned array may
> be in either C-, or Fortran-contiguous order or even
> subok - If True, then sub-classes will be passed-through, otherwise
> the returned array will be forced to be a base-class array
> ndmin - Specifies the minimum number of dimensions that the
> array should have. 1's will be pre-pended to the shape as
> needed to meet this requirement.
> asarray(a, dtype=None, order=None)
> Returns a as an array.
> Unlike array(), no copy is performed if a is already an array.
> are converted to base class ndarray.
> 1) Is it true that array doesn't always return a copy except by default?
> asarray says it contrasts with array in this regard. Maybe copy=0 should be
> 2) Is asarray is basically array with copy=0?
> 3) Is asanyarray basically array with copy=0 and subok=1?
> 4) Is there some sort of precedence table for conversions? To me it looks
> like the most deeply nested lists are converted to arrays first, numeric if
> they contain all numeric types, object otherwise. I assume the algorithm
> then ascends up through the hierarchy like traversing a binary tree in
> 5) All nesting must be to the same depth and the deepest nested items must
> have the same length.
> 6) How is the difference between lists and "lists" determined, i.e.,
> In : array([list([1,2,3]),list([1,2])], dtype = object)
> Out: array([[1, 2, 3], [1, 2]], dtype=object)
> In : array([array([1,2,3]),array([1,2])], dtype = object)
> Out: array([[1 2 3], [1 2]], dtype=object)
> In : array([1,2,3],[1,2]], dtype = object)
> File "<ipython console>", line 1
> array([1,2,3],[1,2]], dtype = object)
> SyntaxError: invalid syntax
> Is the difference that list(...) and array(...) are passed as functions
> (lazy evaluation), but a list is just a list?
> Sorry to be asking all these questions, but I would like to try making the
> documentation be a bit of a reference. I am sure I will have more questions
And, voila, ragged arrays:
In : a = array([array([1,2,3]),array([1,2])], dtype = object)
In : a*2
Out: array([[2 4 6], [2 4]], dtype=object)
In : a + a
Out: array([[2 4 6], [2 4]], dtype=object)
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