Python: What is the difference between math.exp and numpy.exp and why do numpy creators choose to introduce exp again

Question

exp means exponential function

exp in math module: https://docs.python.org/2/library/math.html

exp in numpy module: http://docs.scipy.org/doc/numpy/reference/generated/numpy.exp.html

Why do numpy creators introduce this function again?

Answer 1

The math.exp works only for scalars as EdChum mentions. Whereas numpy.exp will work for arrays.

Example:

>>> import math >>> import numpy as np >>> x = [1.,2.,3.,4.,5.] >>> math.exp(x)  Traceback (most recent call last):   File "<pyshell#10>", line 1, in <module>     math.exp(x) TypeError: a float is required >>> np.exp(x) array([   2.71828183,    7.3890561 ,   20.08553692,   54.59815003,         148.4131591 ]) >>>  

It is the same case for other math functions.

>>> math.sin(x)  Traceback (most recent call last):   File "<pyshell#12>", line 1, in <module>     math.sin(x) TypeError: a float is required >>> np.sin(x) array([ 0.84147098,  0.90929743,  0.14112001, -0.7568025 , -0.95892427]) >>>  

Also refer to THIS ANSWER to check out how numpy is faster than math.