[Numpy-discussion] design issues - octave 'incompatibilities'

Robert Kern rkern at ucsd.edu
Sat Jul 23 12:07:11 CDT 2005

Soeren Sonnenburg wrote:
> Dear all,
> I am new to numarray and as I am trying to use it day-by-day
> I am now wondering about certain numeric/numarray design issues. Please
> forgive me / correct me as I probably misunderstood certain issues.
> -- Why did you choose row-major instead of column major format as
> practiced by R/octave/matlab... Doesn't that mean performance problems
> as fortran/blas is optimized if you work with the transposed version ?

Not everyone is interfacing with optimized FORTRAN code. Those who are 
are usually using ATLAS as their BLAS, and ATLAS has row-major versions 
of the BLAS subroutines. Row-major is C's convention and 
numarray/Numeric largely follow that. There are of course some 
performance issues when interfacing with FORTRAN code that expects 
column-major, but there would be other performance problems if 
numarray/Numeric were column-major and interfacing with row-major code.

> -- why do vectors have no 'orientation', i.e. there are only row but no
> column vectors (or why do you treat matrices/vectors differently, i.e.
> have vectors at all as a separate type)

You can certainly make column vectors.

In [1]: a = arange(5)

In [2]: a
Out[2]: NumPy array, format: long
[0 1 2 3 4]

In [3]: a.shape = (5,1)

In [4]: a
Out[4]: NumPy array, format: long

Often, though, a "row" vector can also be used in place of a "column" 
vector. Although sometimes not:

> -- How can one obtain submatrices from full matrices:

In [6]: import numarray

In [7]: a = numarray.arange(1, 10)

In [8]: a.shape = (3,3)

In [9]: a
array([[1, 2, 3],
        [4, 5, 6],
        [7, 8, 9]])

In [10]: i = [0,1]

In [11]: j = [[0],[2]]

In [12]: a[i,j]
array([[1, 4],
        [3, 6]])

> -- why don't you allow iterating over the whole matrix via a single
> index ?


> Are there more elegant ways to do this ? Which issues are likely to be
> fixed in the future ?

None. They're not broken, just different from what you are used to.

Robert Kern
rkern at ucsd.edu

"In the fields of hell where the grass grows high
  Are the graves of dreams allowed to die."
   -- Richard Harter

More information about the Numpy-discussion mailing list