# Numpy – Check For Negative Infinity

In this tutorial, we will look at how to check if a value in a Numpy array is negative infinity or not with the help of some examples.

## How to test for negative infinity in a Numpy array?

You can use the `numpy.isneginf()` function to check (element-wise) if values in a Numpy array are negative infinity or not. The following is the syntax –

```# test for negative infinity - pass scaler value or numpy array
np.isneginf(a)```

It returns a boolean value (`True` if the value is negative infinity otherwise `False`) if you pass a scaler value and a boolean array if you pass an array.

## Examples

Let’s now look at some examples of using the above function to test for -ve infinity.

### Example 1 – Check if a number is a negative infinity or not using `numpy.isneginf()`

First, let’s pass scaler values to the `numpy.isneginf()` function.

Let’s create three variables – one containing a finite value and the others set to positive and negative infinity respectively and then apply the `numpy.isneginf()` function on each of these values.

```import numpy as np

# create three variables with scaler values
a = 21
b = np.inf
c = -np.inf

# check for negative infinity
print(np.isneginf(a))
print(np.isneginf(b))
print(np.isneginf(c))```

Output:

```False
False
True```

We get `True` as the output for the negative infinity and `False` as the output for the finite number and the positive infinity.

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### Example 2 – Element-wise check for negative infinity in a Numpy array using `numpy.isneginf()`

If you apply the `numpy.isneginf()` function on an array, it will return a boolean array containing `True` for values that are negative infinity and `False` for other values.

Let’s create a 1-D array and apply the `numpy.isneginf()` function to it.

```# create a numpy array
ar = np.array([1, 2, np.inf, 4, 5, -np.inf, np.inf])
# check for negative infinity in ar
np.isneginf(ar)```

Output:

`array([False, False, False, False, False,  True, False])`

We get a boolean array as an output. You can see that in the boolean array we get `True` for only the values that test as negative infinity in the original array.

## Summary

In this tutorial, we looked at how we can use the `numpy.isneginf()` function to check for negative infinity in a Numpy array. Keep in mind that if you pass a scaler value, it returns a boolean value and if you pass a 1-D array it returns a boolean array.

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## Author

• Piyush is a data professional passionate about using data to understand things better and make informed decisions. He has experience working as a Data Scientist in the consulting domain and holds an engineering degree from IIT Roorkee. His hobbies include watching cricket, reading, and working on side projects.

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