NumPy Universal Functions (ufuncs)

What are ufuncs?

A ufunc (universal function) is a function that operates element-wise on arrays and is optimized for speed.

Examples:

They are faster and cleaner than Python loops.

sqrt

import numpy as np
 
arr = np.array([1, 4, 9, 16])
print(np.sqrt(arr))

sqrt

import numpy as np
 
arr = np.array([1, 4, 9, 16])
print(np.sqrt(arr))

math

import numpy as np
 
x = np.array([1.0, 2.0, 3.0])
print(np.exp(x))
print(np.log(x))
print(np.log10(x))

math

import numpy as np
 
x = np.array([1.0, 2.0, 3.0])
print(np.exp(x))
print(np.log(x))
print(np.log10(x))

trig

import numpy as np
 
angles = np.array([0, np.pi/2, np.pi])
print(np.sin(angles))
print(np.cos(angles))

trig

import numpy as np
 
angles = np.array([0, np.pi/2, np.pi])
print(np.sin(angles))
print(np.cos(angles))

max-min

import numpy as np
 
a = np.array([1, 10, 3])
b = np.array([2, 5, 4])
 
print(np.maximum(a, b))
print(np.minimum(a, b))

max-min

import numpy as np
 
a = np.array([1, 10, 3])
b = np.array([2, 5, 4])
 
print(np.maximum(a, b))
print(np.minimum(a, b))

Some ufuncs have NaN-safe variants.

nan

import numpy as np
 
arr = np.array([1.0, np.nan, 3.0])
print(np.nanmean(arr))
print(np.nansum(arr))

nan

import numpy as np
 
arr = np.array([1.0, np.nan, 3.0])
print(np.nanmean(arr))
print(np.nansum(arr))

Ufuncs naturally work with broadcasting.

broadcast

import numpy as np
 
mat = np.array([[1, 2, 3], [4, 5, 6]])
print(np.sqrt(mat))

broadcast

import numpy as np
 
mat = np.array([[1, 2, 3], [4, 5, 6]])
print(np.sqrt(mat))

Continue to: Stacking and Splitting Arrays to combine and break arrays along different axes.