CODEWITHSUNDEEP
pythonarraysnumpyenumerate
Sam Billington
Sam Billington

Reputation: 319

Values being altered in numpy array

So I have a 2D numpy array (256,256), containing values between 0 and 10, which is essentially an image. I need to remove the 0 values and set them to NaN so that I can plot the array using a specific library (APLpy). However whenever I try and change all of the 0 values, some of the other values get altered, in some cases to 100 times their original value (no idea why).

The code I'm using is: 

for index, value in np.ndenumerate(tex_data):
    if value == 0:
        tex_data[index] = 'NaN'

where tex_data is the data array from which I need to remove the zeros. Unfortunately I can't just use a mask for the values I don't need, as APLpy wont except masked arrays as far as I can tell.

Is there anyway I can set the 0 values to NaN without changing the other values in the array?

Upvotes: 4

Views: 1987

Answers (2)

B. M.
B. M.

Reputation: 18628

Using float rules,

tex_data/tex_data*tex_data

make the job here also.

Upvotes: 0

wim
wim

Reputation: 362557

Use fancy-indexing. Like this:

tex_data[tex_data==0] = np.nan

I don't know why your original code was failing. It looks correct to me, although terribly inefficient.

Upvotes: 5

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