Fast in-place replacement of some values in a numpy array

Question

There has got to be a faster way to do in place replacement of values, right? I've got a 2D array representing a grid of elevations/bathymetry. I want to replace anything over 0 with NAN and this way is super slow:

for x in range(elevation.shape[0]):
    for y in range(elevation.shape[1]):
        if elevation[x,y] > 0:
            elevation[x,y] = numpy.NAN

It seems like that has so be a much better way!

Glorfindel · Accepted Answer · 2022-12-24 21:00:30Z

21

The following will do it:

elevation[elevation > 0] = numpy.NAN

See Indexing with Boolean Arrays in the NumPy tutorial.

edited Dec 24, 2022 at 21:00

Glorfindel

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answered Nov 3, 2011 at 11:33

NPE

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eumiro · Accepted Answer · 2011-11-03 11:35:52Z

3

np.putmask(elevation, elevation > 0, np.nan)

answered Nov 3, 2011 at 11:35

eumiro

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