Ignore divide by 0 warning in NumPy

PythonNumpySuppress WarningsDivide by-Zero

Python Problem Overview


I have a function for statistic issues:

import numpy as np
from scipy.special import gamma as Gamma

def Foo(xdata):
    ...
    return x1 * (
                 ( #R is a numpy vector
                  ( ((R - x2)/beta) ** (x3 -1) ) * 
                  ( np.exp( - ((R - x2) / x4) ) ) /
                  ( x4 * Gamma(x3))
                 ).real
                )

Sometimes I get from the shell the following warning:

RuntimeWarning: divide by zero encountered in...

I use the numpy isinf function to correct the results of the function in other files, so I do not need this warning.

Is there a way to ignore the message? In other words, I do not want the shell to print this message.

I do not want to disable all python warnings, just this one.

Python Solutions


Solution 1 - Python

You can disable the warning with numpy.seterr. Put this before the possible division by zero:

np.seterr(divide='ignore')

That'll disable zero division warnings globally. If you just want to disable them for a little bit, you can use numpy.errstate in a with clause:

with np.errstate(divide='ignore'):
    # some code here

For a zero by zero division (undetermined, results in a NaN), the error behaviour has changed with numpy version 1.12.0: this is now considered "invalid", while previously it was "divide".

Thus, if there is a chance you your numerator could be zero as well, use

np.seterr(divide='ignore', invalid='ignore')

or

with np.errstate(divide='ignore', invalid='ignore'):
    # some code here

See the "Compatibility" section in the release notes, last paragraph before the "New Features" section:

> Comparing NaN floating point numbers now raises the invalid runtime warning. If a NaN is expected the warning can be ignored using np.errstate.

Solution 2 - Python

You could also use numpy.divide for division. That way you don't have to explicitly disable warnings.

In [725]: np.divide(2, 0)
Out[725]: 0

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Solution 1 - PythondddsnnView Answer on Stackoverflow
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