[Numpy-discussion] argmin and argmax without nan

[Dmitrey]

          On Thu, Mar 24, 2011 at 6:19 AM, Ralf Gommers
     <

     ralf.gommers@googlemail.com     > wrote:
     > 2011/3/24 Dmitrey <     tmp50@ukr.net     >:
     >> hi,
     >> is there any way to get argmin and argmax of an array w/o nans?
     >> Currently I have
     >>>>> from numpy import *
     >>>>> argmax([10,nan,100])
     >> 1
     >>>>> argmin([10,nan,100])
     >> 1
     >> But it's not the values I would like to get.
     >>
     >> The walkaround I use: get all indeces of nans, replace them by -inf, get
     >> argmax, replace them by inf, get argmin.
     >> Is there any better way? (BTW, I invoke argmin/argmax along of a chosen
     >> axis)
     >> D.
     >
     > In [3]: np.nanargmax([10, np.nan, 100])
     > Out[3]: 2
     >
     > In [4]: np.nanargmin([10, np.nan, 100])
     > Out[4]: 0
     
     And if speed is an issue (it usually isn't) you can use the nanargmax
     from Bottleneck:
     
     >> a = np.random.rand(10000)
     >> a[a > 0.5] = np.nan
     >> timeit np.nanargmax(a)
     10000 loops, best of 3: 127 us per loop
     >> import bottleneck as bn
     >> timeit bn.nanargmax(a)
     100000 loops, best of 3: 12.4 us per loop
        

   For some problems some % speedup could be yielded.
   Are there any plans for merging bottleneck into numpy?
   Also, are those benchmarks valid for ordinary numpy only or numpy with
   MKL/ACML or it doesn't matter?
   If I have huge arrays and multicore CPU, will numpy with MKL/ACML or
   something else involve parallel computations with numpy funcs like
   amin, amax, argmin, nanargmin etc?
   D.

     
        
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