+1

Numpy also behaves the way Mike is suggesting here.

imran

On Fri, Jul 28, 2017 at 5:21 PM, Nakul Jindal <nakul02@gmail.com> wrote:

> +1 to Mike & Deron.
>
> Two other languages/packages that behave like this:
> R : http://www.r-tutor.com/r-introduction/matrix
> Octave :
> https://www.gnu.org/software/octave/doc/interpreter/Index-Expressions.html
>
>
> -Nakul
>
>
>
>
> On Fri, Jul 28, 2017 at 4:03 PM, Deron Eriksson <deroneriksson@gmail.com>
> wrote:
>
> > Thank you Mike for bringing this up. To me, this definitely makes sense
> at
> > the user (DML) level.
> >
> > For a Java-style pseudocode example, currently we require the user to do
> > the following:
> >   int[][] m = int[][]{1,2,3,4};
> >   int[][] n = m[0][0];
> >   int x = (int) n;
> >
> > I feel the following would be more 'natural':
> >   int[][] m = int[][]{1,2,3,4};
> >   int x = m[0][0];
> >
> > If a user asks for a specific cell (and not a range) in DML code, I think
> > the user clearly wants a value and not a matrix that the user needs to
> cast
> > via as.scalar.
> >
> > Deron
> >
> >
> >
> > On Fri, Jul 28, 2017 at 3:41 PM, <dusenberrymw@gmail.com> wrote:
> >
> > > Currently, non-range matrix indexing, such as `X[1,2]`, returns a 1x1
> > > matrix in SystemML rather than a single scalar value.  This is
> > inconsistent
> > > with mathematical semantics, and with array indexing semantics of any
> > major
> > > language, thus leading to confusion for users.
> > >
> > > I would like to propose that non-range indexing at the language level,
> > > such as `X[1,2]`, should return a single scalar value, and range
> indexing
> > > of any kind at the language level, including the trivial example
> > > `X[1:1,2:2]`, should return a matrix.  This would lead to clear
> semantics
> > > that are consistent with mathematics and language array indexing, thus
> > > preventing user confusion.  Additionally, these are the semantics that
> > the
> > > NumPy project uses.
> > >
> > > Interested to hear thoughts from the rest of the community!
> > >
> > > -Mike
> > >
> > > --
> > >
> > > Mike Dusenberry
> > > GitHub: github.com/dusenberrymw
> > > LinkedIn: linkedin.com/in/mikedusenberry
> > >
> > > Sent from my iPhone.
> > >
> > >
> >
>