Sometimes while working with NumPy, you might face RunTimeWarning. One example is Runtimewarning: invalid value encountered in long_scalars error which occurs when we do mathematical operation on a list of very large numbers or vary the small numbers and then we apply operations like Nan or null as an input. In other words, this error occurs when we perform a mathematical operation that is invalid. In this short article, we will discuss how we can solve the Runtimewarning: invalid value encountered in long_scalars error using various methods. Moreover, we will discuss how to understand errors in Python taking Runtimewarning: invalid value encountered in long_scalars as an example.
Runtimewarning: invalid value encountered in long_scalars – Possible Solutions
We know that the error Runtimewarning: invalid value encountered in long_scalars occurs when we performed an invalid mathematical operation in NumPy. Sometimes, when we are doing mathematical operations and work with very large or small numbers, some modules cannot handle this and through an error.
Here are some of the steps through which we can prevent this error:
- Use a function that can handle the error and can deal with very large or small numbers
- Use built-in complex mathematical functions
- Make necessary changes in the mathematical operation
In this short article, we will go through the following methods to solve the problem:
- Using if statement
- Using numpy.special.logsumexp() method
Let us now jump into the possible solutions:
Soluton-1: Using the if statement
In Python, an if statement is used for a boolean condition. Before going to see how we can use the if statement to prevent Runtimewarning: invalid value encountered in long_scalars error, let us first see when we are getting this error:
import numpy arr1 = [1, 2, 4, 7, 8] # this input array causes error arr2 =  result1 = numpy.mean(arr1) # this line causes the error result2 = numpy.mean(arr2) # printing print(result1) print(result2)
This causes the error because we are trying to find the mean of the array that is empty.
import numpy array1 = [1, 2, 4, 7, 8] # this input array causes error array2 =  # Here we check error if array1 and array2: print( numpy.mean(array1)) print( numpy.mean(array2)) else: print("The Array is not valid")
The Array is not valid
As you can see, we got rid of the error by using the if statement.
Solution-2: Using numpy.special.logsumexp() method
First, let us when we are getting the error taking an example:
import numpy as np from numpy import sinh x = 900 y = 711 # This operation raise error sol1 = np.log(np.sum(np.exp(x)))/np.log(np.sum(np.exp(y))) print(sol1)
nan /tmp/ipykernel_341710/2489633295.py:8: RuntimeWarning: overflow encountered in exp sol1 = np.log(np.sum(np.exp(x)))/np.log(np.sum(np.exp(y))) /tmp/ipykernel_341710/2489633295.py:8: RuntimeWarning: invalid value encountered in double_scalars sol1 = np.log(np.sum(np.exp(x)))/np.log(np.sum(np.exp(y)))
Now let us see, how we can solve the problem using numpy.special.logsumexp() method.
import numpy as np from scipy.special import logsumexp x = 900 y = 711 # Solution of the error with the # help of built-in function sol1 = logsumexp(x) - logsumexp(y) # printing the answer print(sol1)
Notice that this time, we didn’t get the error anymore.
Understanding the Runtimewarning: invalid value encountered in long_scalars
Now let us try to understand the error. The error has two main parts which help us to figure out and understand it. The first part of the error is about the category of the error which in this case is the RuntimeWarning. This is not an error but a warning that occurs during the run time.
The second part of the error gives more specific information about the warning and it clearly says that an invalid value was encountered in long_scalars which means we are performing some invalid operation.
Reasons for getting Runtimewarning: invalid value encountered in long_scalars error
The “RuntimeWarning: invalid value encountered in long_scalars” error typically occurs in Python when trying to perform an arithmetic operation with an invalid input, which results in a NaN (Not a Number) value. Some of the possible reasons for this error message are:
- Division by zero: If you divide a number by zero, you will get a NaN value.
- Overflow or underflow: If a calculation produces a value that is too large or too small to be represented by the computer, it will result in a NaN value.
- Invalid input: If the input to a function or operation is invalid, it can result in a NaN value.
- Using NaN values in calculations: If you use NaN values in subsequent calculations, it can result in an error.
In this short article, we discussed how we can solve Runtimewarning: invalid value encountered in long_scalars using various methods. We mainly discussed two methods along with examples.
- TypeError: ‘module’ object is not callable [Solved]
- Failed to initialize nvml: driver/library version mismatch