[Numpy-discussion] try to solve issue #2649 and revisit #473
Wed Apr 3 18:11:10 CDT 2013
Agree with the row-vector and column-vector thing. I notice that in
ndarraymultiplication, the 1-d array is treated as a column-vector.
But in matrix
multiplication, 1-d array is converted to a row-vector. So just match the
1-d array to a column-vector, the behavior of ndarray and matrix will be
On Wed, Apr 3, 2013 at 6:59 PM, Chris Barker - NOAA Federal <
> On Wed, Apr 3, 2013 at 1:03 PM, Alan G Isaac <firstname.lastname@example.org> wrote:
> > On 4/3/2013 3:18 PM, email@example.com wrote:
> > In my view, the result should be a 1d array,
> > the same as I.A.dot(x).
> > But the maintainers wanted operations with matrices to
> > return matrices whenever possible. So instead of
> > returning x it returns np.matrix(x).
> the matrix object is a fine idea, but the key problem is that it
> provides a 2-d matrix, but no concept of a 1-d vector. I think it
> would all be a cleaner if there were a row-vector and column-vector
> object to accompany matrix -- they things that naturally return a
> vector could do so, You can't use a regular 1-d array because there is
> no way to distinguish between a row or column version.
> But as Alan sid, this was all hashed out a few years back -- a bunch
> of great ideas, but no one to implement them.
> The truth is that matrix has little value outside of teaching, so no
> one with the skills to push it forward uses it themselves.
> Christopher Barker, Ph.D.
> Emergency Response Division
> NOAA/NOS/OR&R (206) 526-6959 voice
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> NumPy-Discussion mailing list
Department of Applied math & Statistics
Stony Brook University
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