Numeric N-dimensional array initialization

[Robert Kern]

TG wrote:
> I tried to use Numeric.fromfunction, but there seems to be a problem :
> 
> the function called must have the right number of args (hint : the
> number of dimensions, which I don't know). So i tried to use a function
> like :
> 
> def myfunc(*args, **kw):
>      return 0
> 
> and then i get :
> 
>>> Numeric.fromfunction(myfunc,(5,5))
> 0
> 
> I'm a bit puzzled here

In [24]: def myfunc(*args):
    ....:     print args
    ....:
    ....:

In [26]: fromfunction(myfunc, (2, 2))
(array([[0, 0],
         [1, 1]]),
  array([[0, 1],
         [0, 1]]))

fromfunction() does not iterate over the possible indices and call the function 
with scalar arguments to get a scalar return value. It generates N arrays with 
index values in them and calls the function once with those arrays. The return 
value should be another array.

If you actually just want 0s:

In [27]: zeros((5, 5))
Out[27]:
array([[0, 0, 0, 0, 0],
        [0, 0, 0, 0, 0],
        [0, 0, 0, 0, 0],
        [0, 0, 0, 0, 0],
        [0, 0, 0, 0, 0]])

If you want 1s:

In [28]: ones((5, 5))
Out[28]:
array([[1, 1, 1, 1, 1],
        [1, 1, 1, 1, 1],
        [1, 1, 1, 1, 1],
        [1, 1, 1, 1, 1],
        [1, 1, 1, 1, 1]])

If you just want an array as fast as possible because you are going to fill in 
values later:

In [29]: empty((5, 5))
Out[29]:
array([[    13691,         0,         0,   2883587,         3],
        [        3,         0, 828189706,         6,         0],
        [        0,         9,        10, 828202281,         0],
        [        7,         0,         0,         0,         0],
        [        0,         0,         0,         0,         0]])


If you have more complicated needs, we can talk about them on numpy-discussion.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco