Matlab-style mask in Python??

[Chris Barker]

Ozone Hole near South Pole <ozonehole2k at yahoo.com> wrote:
| I am a long time Matlab user.  I just picked up Python for a short
| while.
| I wonder what should be the best way to do sth like:

| Matlab:
| a=[3,4,6,7,2,54,2,1,2]
| idx=a>4      ans: [0,0,1,1,0,1,0,0,0]
| a(idx)         ans: [6,7,54]

| Python:
| a=[3,4,6,7,2,54,2,1,2]
| idx=map(lambda x: x>4,a) #assume this calculation is lengthy
|                          #and we don't want to repeat
| last cmd???

have a look at Numerical Python http://www.numpy.org. I think it
will help you.

It absolutely will:
>>> from Numeric import *
>>> a=array([3,4,6,7,2,54,2,1,2])
>>> a
array([ 3,  4,  6,  7,  2, 54,  2,  1,  2])
>>> idx = a > 4
>>> idx
array([0, 0, 1, 1, 0, 1, 0, 0, 0])
>>> take(a,nonzero(idx))
array([ 6,  7, 54])


Numeric has most of the basic functionality that MATLAB does, but a much
smaller library of extras. The SciPy (www.scipy.org) project is working
to addess this.

Numeric also lacks MATLAB'S nifty array indexing and mask indexing. Note
how I used take and nonzero above. This does make code littel more
verbose, but Numeric has a number of advantages as well. Consider "array
broadcasting":

>>> x = arange(5)
>>> x.shape = (1,-1) # make it a row vector, the -1 means use whatever fits.
>>> x
array([       [0, 1, 2, 3, 4]])
>>> y = arange(3)
>>> y.shape = (-1,1) # make it a column vector
>>> y
array([[0],
       [1],
       [2]])
>>> z = x*y
>>> z
array([[0, 0, 0, 0, 0],
       [0, 1, 2, 3, 4],
       [0, 2, 4, 6, 8]])

In Matlab, you would have had to create an entire array of X and Y with

[X,Y] = meshgrid(x,y)

Which is a whole lot clunkier, and wastes a lot of memory.

All in all, I like NumPy better. (and I like MATLAB a lot)

-Chris


-- 
Christopher Barker,
Ph.D.                                                           
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