How to catch FloatingPointError Exception in Python?

Catching FloatingPointError Exception in Python

FloatingPointError in Python is an exception that occurs when there is an error in floating-point calculations.

By default, Python does not raise this error for basic operations like dividing by zero; instead, it returns inf or nan. To catch this error, you need to enable it explicitly using the numpy module.

In this article, you will learn how to catch a FloatingPointError by enabling it through NumPy settings and handling it using a try-except block.

When Does FloatingPointError Occur?

FloatingPointError can occur in cases like -

• Divide by zero in floating-point calculations (if enabled)
• Overflow in a floating-point operation
• Invalid operations resulting in nan values

Enabling FloatingPointError in NumPy

To raise FloatingPointError, first of all, we need to enable it in the NumPy seterr() method.

Example: Enabling FloatingPointError

In the following example, using NumPy, we are enabling the FloatingPointError, and performing a division operation with 0.0 as the denominator. Here, we are using the try-except blocks to catch the raised exception.

import numpy as np

# Enable FloatingPointError for division and invalid operations
np.seterr(all='raise')

try:
   a = np.array([1.0])
   b = np.array([0.0])
   result = a / b
except FloatingPointError as e:
   print("Floating point error caught:", e)

Following is the output obtained -

Floating point error caught: divide by zero encountered in divide

Example: Catching Overflow Error

If we try to calculate the exponential value (e^x) of a number greater than 709.78, a FloatingPointError is raised, as float in numpy can store values up to 1.7928227943945155e+308. 

In this example, we raise an overflow error and catch it using the FloatingPointError-

import numpy as np

np.seterr(over='raise')

try:
   result = np.exp(1000)
except FloatingPointError as e:
   print("Overflow error caught:", e)

We get the output as shown below -

Overflow error caught: overflow encountered in exp

Example: Handling Invalid Floating Operation

Here, we are trying to calculate the square root of a negative number, which is an invalid operation.

import numpy as np

np.seterr(invalid='raise')

try:
   result = np.sqrt(-1)
except FloatingPointError as e:
   print("Invalid floating operation caught:", e)

The error obtained is as shown below -

Invalid floating operation caught: invalid value encountered in sqrt