# 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
```