How to calculate a logistic sigmoid function in Python?

Question

This is a logistic sigmoid function:

I know x. How can I calculate F(x

Answer 1

Vectorized method when using pandas DataFrame/Series or numpy array:

The top answers are optimized methods for single point calculation, but when you want to apply these methods to a pandas series or numpy array, it requires apply, which is basically for loop in the background and will iterate over every row and apply the method. This is quite inefficient.

To speed up our code, we can make use of vectorization and numpy broadcasting:

x = np.arange(-5,5)
np.divide(1, 1+np.exp(-x))

0    0.006693
1    0.017986
2    0.047426
3    0.119203
4    0.268941
5    0.500000
6    0.731059
7    0.880797
8    0.952574
9    0.982014
dtype: float64

Or with a pandas Series:

x = pd.Series(np.arange(-5,5))
np.divide(1, 1+np.exp(-x))