Charles R Harris wrote: > > > On 3/26/07, *Travis Oliphant* <[EMAIL PROTECTED] > <mailto:[EMAIL PROTECTED]>> wrote: > > > > I think that might be the simplest thing, dot overrides subtypes. > BTW, > > here is another ambiguity > > > > In [6]: dot(array([[1]]),ones(2)) > > > > --------------------------------------------------------------------------- > > > exceptions.ValueError Traceback (most > > recent call last) > > > > /home/charris/<ipython console> > > > > ValueError: matrices are not aligned > > > > Note that in this case dot acts like the rhs is always a column > vector > > although it returns a 1-d vector. I don't know that this is a bad > > thing, but perhaps we should extend this behaviour to matrices, > which > > would be different from the now current 1-d is always a *row* > vector, i.e. > > > The rule 1-d is always a *row* vector only applies when converting to a > matrix. > > In this case, the dot operator does not "convert to a matrix" but uses > rules for operating with mixed 2-d and 1-d arrays inherited from > Numeric. > > I'm very hesitant to change those rules. > > > I wasn't suggesting that, just noticing that the rule was 1-d vector on > right is treated as a column vector by dot, which is why an exception > was raised in the posted case. If it is traditional for matrix routines > always treat is as a row vector, so be it.
My recollection is that text books treat the column vector, represented by a lower case letter, bold or underlined, as the default. If b (dressed as described before) is a column vector, then b' represents a row vector. For numpy, it makes sense to consider b as a row vector, since the underlying array uses the C convention where each row is stored contiguously. Colin W. > > Chuck > > > > ------------------------------------------------------------------------ > > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://projects.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
