looping and searching in numpy array

[Heli]

On Thursday, March 10, 2016 at 2:02:57 PM UTC+1, Peter Otten wrote:
> Heli wrote:
> 
> > Dear all,
> > 
> > I need to loop over a numpy array and then do the following search. The
> > following is taking almost 60(s) for an array (npArray1 and npArray2 in
> > the example below) with around 300K values.
> > 
> > 
> > for id in np.nditer(npArray1):
> >                   
> >        newId=(np.where(npArray2==id))[0][0]
> > 
> > 
> > Is there anyway I can make the above faster? I need to run the script
> > above on much bigger arrays (50M). Please note that my two numpy arrays in
> > the lines above, npArray1 and npArray2  are not necessarily the same size,
> > but they are both 1d.
> 
> You mean you are looking for the index of the first occurence in npArray2 
> for every value of npArray1?
> 
> I don't know how to do this in numpy (I'm not an expert), but even basic 
> Python might be acceptable:
> 
> lookup = {}
> for i, v in enumerate(npArray2):
>     if v not in lookup:
>         lookup[v] = i
> 
> for v in npArray1:
>     print(lookup.get(v, "<not found>"))
> 
> That way you iterate once (in Python) instead of 2*len(npArray1) times (in 
> C) over npArray2.

Dear Peter, 

Thanks for your reply. This really helped. It reduces the script time from 61(s) to 2(s). 

I am still very interested in knowing the correct numpy way to do this, but till then your fix works great. 

Thanks a lot,