Dealing with -0 values in a numpy array

Question

For some reason, my data reduction for a fits image has given me -0 values, which I would like to set to 0.

I've attempted to use:

my_array[~numpy.isfinite(my_array)] = 0

All I would like to do is set the -0 values in the corrfact_um2_ext1 array to 0. Just to keep everything in the same format, as I think this may cause a problem in subsequent data reduction steps.

But this just deals with NaN values and sets them to 0. So, I'm halfway there!

Possible duplicate of How to eliminate the extra minus sign when rounding negative numbers towards zero in numpy? — runDOSrun
– runDOSrun, Commented Feb 15, 2016 at 17:02
I don't even know! :) I used scipy.ndimage.filters.uniform_filter() — GCien
– GCien, Commented Feb 15, 2016 at 17:04

meltdown90 · Accepted Answer · 2016-02-15 17:26:09Z

1

Simply adding 0.0 to each floating point number should fix this:

a = np.array([-0.0, 0.0, 1.0, -1.0])
Out[1]: array([-0.,  0.,  1., -1.]

a += 0.0
a
Out[2]: array([ 0.,  0.,  1., -1.])

But note:

np.array(-0.) == np.array(+0.)
Out[3]: True

Does this solve your problem?

answered Feb 15, 2016 at 17:26

meltdown90

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