RuntimeWarning: overflow encountered in np.exp(x**2)

Question

I need to calculate exp(x**2) where x = numpy.arange(30,90). This raises the warning:

RuntimeWarning: overflow encountered in exp
inf

I cannot safely ignore this warning, but neither SymPy nor mpmath is a solution and I need to perform array operations so a Numpy solution would be my dream.

Does anyone know how to handle this problem?

Answer 1

You could use a data type that has the necessary range, for example decimal.Decimal:

>>> import numpy as np
>>> from decimal import Decimal
>>> x = np.arange(Decimal(30), Decimal(90))
>>> y = np.exp(x ** 2)
>>> y[-1]
Decimal('1.113246031563799750400684712E+3440')

But what are you using these numbers for? Could you avoid the exponentiation and work with logarithms? More detail about your problem would be helpful.

Answer 2

I think you can use this method to solve this problem:

Normalized

I overcome the problem in this method. Before using this method, my classify accuracy is :86%. After using this method, my classify accuracy is :96%!!! It's great!
first:
Min-Max scaling
second:
Z-score standardization

These are common methods to implement normalization.
I use the first method. And I alter it. The maximum number is divided by 10. So the maximum number of the result is 10. Then exp(-10) will be not overflow!
I hope my answer will help you !(^_^)