On 05/20/2010 01:33 PM, Nathann Cohen wrote:
The
manipulation of matrices in R is just amazing. If you want to strip
all the negative values contained in a matrix M, you but have to write
M * (M> 0). How easier can it et ?
Here is the amazing numpy at work:
sage: a=random_matrix(ZZ,5).numpy();
sage: a<0
array([[ True, False, True, True, False],
[ True, False, False, True, True],
[False, True, True, False, False],
[ True, False, False, True, False],
[ True, False, True, True, True]], dtype=bool)
sage: a[a<0]=0
sage: a
array([[ 0, 1, 0, 0, 3],
[ 0, 2, 1, 0, 0],
[ 2, 0, 0, 25, 1],
[ 0, 1, 2, 0, 9],
[ 0, 1, 0, 0, 0]])
I would like to do something like that in Sage. We have some of the
framework in place, but when we do a comparison with a matrix, we don't
do it element-wise. In fact, I'm not sure what we do:
sage: b
[ 0 1 0 0 3]
[ 0 2 1 0 0]
[ 2 0 0 25 1]
[ 0 1 2 0 9]
[ 0 1 0 0 0]
sage: b>1
False
What in the world does that mean?
There is a thousand tricks like
that available in R that I noticed nowhere else.
Matlab/Octave and numpy both have a huge amount of tricks like the above
as well.
And the same goes for
plottings using R. I mean that on these two points, the R language is
much more expressive than any other I know.
I really like the plotting in R. Kudos to Karl-Dieter and others for
working on getting the R plotting to work nicely in the Sage notebook!
Another reason I like R in teaching is that it comes with a huge number
of real-life datasets.
Jason
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