[Tutor] index of elements in numpy array

[eryksun]

On Fri, Sep 14, 2012 at 4:36 AM, Bala subramanian
<bala.biophysics at gmail.com> wrote:
>
>  10 # loop over each row
>  11 for i1, d1 in enumerate(b):
>  12     # each x in d1 - value in z corresponding to index of x in d1
>  13     d1=[x-z[d1.index(x)] for x in d1]
>
> If d1 is a simple list, i can fetch the index of its element as
> d1.index(x). So i would like to know how can achieve the same with
> numpy array.

In general you don't want to loop over and enumerate a NumPy array.
That's a lot slower than using vectorized operations (just like in
MATLAB) and broadcasting. See Peter Otten's answer.

For an 'index' operation you have a couple of options. To begin with,
a test returns a bool array:


    >>> d = np.array([1,2,1,2,1])

    >>> d == 1
    array([ True, False,  True, False,  True], dtype=bool)


You can use this bool array to index the source array:


    >>> d[d == 1]
    array([1, 1, 1])

    >>> d[d == 1] = 3
    >>> d
    array([3, 2, 3, 2, 3])


To get the indexes, use "nonzero" or "where":


    >>> np.nonzero(d == 2)
    (array([1, 3]),)

    >>> np.where(d == 2)
    (array([1, 3]),)