I have numpy array with the shape of (1,5,10).
array([[[ -5, -5, -5, -5, 120, 116, 118, 118, -5, -5],
[ -5, -5, 126, 127, 125, 118, 118, 123, -5, -5],
[ -5, 121, 125, 118, 115, 115, 121, 121, 114, 127],
[112, 118, 108, 111, 110, 112, 104, 102, 103, -5],
[105, 108, 107, -5, -5, -5, -5, -5, -5, -5]]], dtype=int16)
I would like to change all the -5 into np.nan value. In order to do that I have written this code:
out_image[out_image == (-5)] = np.nan
but that gives me an error:
ValueError: cannot convert float NaN to integer
Why do I get this error? and how can I replace the values into nan?
CodePudding user response:
You're doing it as out_image
were a pandas.Dataframe
. Instead you can use numpy.where
method like this:
np.where(out_image == -5, np.NaN, out_image)
CodePudding user response:
You just need to convert it to float
first.
out_image = out_image.astype('float')
out_image[out_image== -5] = np.NAN