[Numpy-discussion] untenable matrix behavior in SVN

[Anne Archibald]

On 29/04/2008, Travis E. Oliphant <oliphant@enthought.com> wrote:

>  I'm quite persuaded now that a[i] should return a 1-d object for
>  arrays.    In addition to the places Chuck identified,  there are at
>  least 2 other places where special code was written to work-around the
>  expectation that item selection returns an object with reduced
>  dimensionality (a special-cased .tolist for matrices and a special-cased
>  getitem in the fancy indexing code).
>
>  As the number of special-case work-arounds grows the more I'm convinced
>  the conceptualization is wrong.   So, I now believe we should change the
>  a[i] for matrices to return a 1-d array.
>
>  The only down-side I see is that a[i] != a[i,:] for matrices.
>  However,  matrix(a[i]) == a[i,:], and so I'm not sure there is really a
>  problem, there.  I also don't think that whatever problem may actually
>  be buried in the fact that type(a[i]) != type(a[i,:]) is worse than the
>  problem that several pieces of NumPy code actually expect hierarchical
>  container behavior of multi-dimensional sequences.

I am puzzled by this. What is the rationale for x[i,:] not being a 1-d
object? Does this not require many special-case bits of code as well?
What about a[i,...]? That is what I would use to make a hierarchical
bit of code, and I would be startled to find myself in an infinite
loop waiting for the dimension to become one.

>  I don't think making the small change to have a[i] return 1-d arrays
>  precludes us from that 1-d array being a bit more formalized in 1.2 as a
>  RowVector should we choose that direction.   It does, however, fix
>  several real bugs right now.

+1

What's more, I think we need to have a matrix-cleanliness test suite
that verifies that all basic numpy tools behave identically on
matrices and preserve matrixiness. But that's a big job, and for 1.2.

Anne