Simple question about numpy matrix in python

Let's suppose I have a numpy matrix variable called MATRIX with 3 coordinates: (x, y, z).

Is acessing the matrix's value through the following code

myVar = MATRIX[0,0,0]

equal to

myVar = MATRIX[0,0][0]

or

myVar = MATRIX[0][0,0]

?

What about if I have the following code?

myTuple = (0,0)
myScalar = 0
myVar = MATRIX[myTuple, myScalar]

Is the last line equivalent to doing

myVar = MATRIX[myTuple[0], myTuple[1], myScalar]

I have done simple tests and it seems so, but maybe that is not so in all the cases. How do square bracket开发者_高级运维s work in python with numpy matrices? Since day one I felt confused as how they work.

Thanks

I assume you have a array instance rather than a matrix, since the latter only can have two dimensions.

m[0, 0, 0] gets the element at position (0, 0, 0). m[0, 0] gets a whole subarray (a slice), which is itself a array. You can get the first element of this subarray like this: m[0, 0][0], which is why both syntaxes work (even though m[i, j, k] is preferred because it doesn't have the unnecessary intermediate step).

Take a look at this ipython session:

rbonvall@andy:~$ ipython
Python 2.5.4 (r254:67916, Sep 26 2009, 08:19:36) 
[...]

In [1]: import numpy.random

In [2]: m = numpy.random.random(size=(3, 3, 3))

In [3]: m
Out[3]: 
array([[[ 0.68853531,  0.8815277 ,  0.53613676],
        [ 0.9985735 ,  0.56409085,  0.03887982],
        [ 0.12083102,  0.0301229 ,  0.51331851]],

       [[ 0.73868543,  0.24904349,  0.24035031],
        [ 0.15458694,  0.35570177,  0.22097202],
        [ 0.81639051,  0.55742805,  0.5866573 ]],

       [[ 0.90302482,  0.29878548,  0.90705737],
        [ 0.68582033,  0.1988247 ,  0.9308886 ],
        [ 0.88956484,  0.25112987,  0.69732309]]])

In [4]: m[0, 0]
Out[4]: array([ 0.68853531,  0.8815277 ,  0.53613676])

In [5]: m[0, 0][0]
Out[5]: 0.6885353066709865

It only works like this for numpy arrays. Python built-in tuples and lists are not indexable by tuples, just by integers.

It's not possible to index a tuple with another tuple, so none of that code is valid.