Charles R Harris wrote: > > > On Tue, Apr 29, 2008 at 7:24 AM, Stéfan van der Walt <[EMAIL PROTECTED] > <mailto:[EMAIL PROTECTED]>> wrote: > > Hi Charles > > 2008/4/29 Charles R Harris <[EMAIL PROTECTED] > <mailto:[EMAIL PROTECTED]>>: > > May I add that if I edit defmatrix.py to act like an array for > scalar > > indexing, then the following works. > > > > In [1]: a = matrix(eye(2)) > > > > In [2]: array([a,a]) > > Out[2]: > > array([[[ 1., 0.], > > [ 0., 1.]], > > > > [[ 1., 0.], > > [ 0., 1.]]]) > > > > This generates an error with the current version of matrix and, > frankly, I > > am not going to be bothered going all through the numpy c > sources to special > > case matrices to fix that. Someone else can do it if they wish. > There are > > recursive routines that expect the dimensions to decrease on > each call. > > I'd also like to see matrices become proper hierarchical containers -- > the question is just how to do that. Thus far, I'm most convinced by > the arguments for RowVectors/Columns, which leaves us with a sane > model for doing linear algebra, while providing the enhancements you > mentioned here and in comments to another ticket. > > We were thinking of raising a warning on scalar indexing for 1.1, but > given the above, would that be sensical? > > > Hi Stefan, > > The numpy c routines call PySequence_GetItem(s,i) as well as ask for > the length (first index), so I think these should be left as they are > for arrays in order to guarantee that matrices are compatible with all > the normal array operations. This means either returning special row > objects that index as expected > or returning 1D arrays. I don't think the '*' operator has these > problems, but in any case that is a well documented feature of matrices.
Thanks for looking in to this Chuck, 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 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. So, I'm +1 on making the following change: def __getitem__(self, index): + if isscalar(index): + return self.__array__()[index] -Travis _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
