[SciPy-user] Newbie issues in moving to SciPy

[Travis E. Oliphant]

Gary Pajer wrote:
> Andy,
> 
> I'm probably about two steps ahead of you.  I think you had better learn at
> least a bit about "python properly". A fair bit of Numeric and scipy is
> structured into namespaces and objects, and while python itself works just
> fine with a basic set of commands, using scipy needs a little more.  But not
> too terribly much more.  Learn what you need as you go.
> 
> There are a lot of differences w.r.t. Matlab.  The one I find most irksome
> is the awkward way one adds an additional row or column to an array.  Unless
> I'm missing something.  The plotting facilities are still under
> construction:  a few bugs and missing features, but quite servicable unless
> you want publication quality. (But there are solutions to that problem.)
> All things considered, scipy seems richer and *possibly* more featured than
> Matlab, but with a steeper learning curve.
> 

I disagree with lack of publication quality.  You can get publication 
quality now with xplt.  Others use add on tools to get quality output. 
For example I've heard that grace has a nice interface with Python.


Regarding r_ and c_

These are tools for constructing arrays quickly.  They essentially wrap 
the concatentator.

Their primary use is to simplify construction of 1-d and 2-d arrays.  r_ 
  stands for row concatenation and c_ stands for column concatenation. 
Of course in 1-d it doesn't matter which you use.

Examples:

 >>> a = r_[1:10]; print a
[1 2 3 4 5 6 7 8 9]

 >>> a = r_[0:10:0.5];  print a  # sample spacing of 0.5
[ 0.   0.5  1.   1.5  2.   2.5  3.   3.5  4.   4.5  5.   5.5  6.   6.5  7.
        7.5  8.   8.5  9.   9.5]

 >>> a = r_[0:10:20j]; print a   # 20j => generate 20 samples
[  0.       0.5263   1.0526   1.5789   2.1053   2.6316   3.1579   3.6842
         4.2105   4.7368   5.2632   5.7895   6.3158   6.8421   7.3684 
7.8947
         8.4211   8.9474   9.4737  10.    ]


You can also combine lists

 >>> a = r_[0:10, 1.0, 3.0, 5:10:10j]; print a
[  0.       1.       2.       3.       4.       5.       6.       7.
         8.       9.       1.       3.       5.       5.5556   6.1111 
6.6667
         7.2222   7.7778   8.3333   8.8889   9.4444  10.    ]


When called with multiple "indexes"  r_ concatentates the rows of the 
arguments.  For 1-d arrays as in this example it just creates a 1-d array.

For 2-d arrays you get the effect of stacking the arguments on top of 
each other.

 >>> C = r_[A,B]

produces the equivalent of MATLAB's C = [A; B]  (note that A and B must 
be 2-d for this to work as you want)


The column equivalent is c_[]

So,

 >>> C = c_[A,B]

produces the equivalent of C = [A, B]  in MATLAB

To construct a matrix from blocks

F = [  A   B  ]
     [  C   D  ]

use

 >>> F = c_[r_[A,C],r_[A,D]]
or
 >>> F = r_[c_[A,B],c_[C,D]]

A = [[1,2]]
B = [[3,4,5]]
C = [[6,7],[8,9],[10,11]]
D = [[12,13,14],[15,16,17],[18,19,20]]

F = r_[c_[A,B],c_[C,D]]
print F

results in

[[ 1  2  3  4  5]
  [ 6  7 12 13 14]
  [ 8  9 15 16 17]
  [10 11 18 19 20]]

I would not be opposed to adding a version that interprets a string 
using MATLAB syntax so that

r_['A B; C D']

did the same thing.


-Travis O.