Alan G Isaac wrote: >>> On 3/26/07, Alan G Isaac <[EMAIL PROTECTED]> wrote: >>>> finds itself in basic conflict with the idea that >>>> I ought to be able to iterate over the objects in an >>>> iterable container. I mean really, does this not "feel" >>>> wrong? :: > >>> for item in x: print item.__repr__() > >>> ... > >>> matrix([[1, 2]]) > >>> matrix([[3, 4]]) > > > On Mon, 26 Mar 2007, Bill Baxter apparently wrote: >> So you're saying this is what you'd find more pythonic? >>>>> X[1] >> matrix([2,3]) >>>>> X[:,1] >> matrix([[3, >> 4]]) >> Just trying to make it clear what you're proposing. > > > No; that is not possible, since a matrix is inherently 2d. > I just want to get the constituent arrays when I iterate > over the matrix object or use regular Python indexing, but > a matrix when I use matrix/array indexing. That is :: > > >>> X[1] > array([2,3]) > >>> X[1,:] > matrix([[3, 4]]) > > That behavior seems completely natural and unsurprising.
Perhaps things would be clearer if we thought of the constituent groups of data in a matrix as being themselves matrices. X[1] could represent the second row of a matrix. A row of a matrix is a row vector, a special case of a matrix. To get an array, I suggest that an explicit conversion X[1].A is a clearer way to handle things. Similarly, X[2, 3] is best returned as a value which is of a Python type. Colin W. > > >> Probably about half the bugs I get from mixing and matching matrix and >> array are things like >> row = A[i] >> ... >> z = row[2] >> Which works for an array but not for a matrix. > > > Exactly! > That is the evidence of a "bad surprise" in the current > behavior. Iterating over a Python iterable should provide > access to the contained objects. > > Cheers, > Alan Isaac _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
