NumPy Tutorial · NumPy ufunc

ufunc Intro

Learn all about ufunc Intro in this comprehensive tutorial.

5 min read advanced

•ufuncs stands for "Universal Functions" and they are NumPy functions that operate on the ndarray object.
•ufuncs are used to implement vectorization in NumPy which is way faster than iterating over elements.
•Converting iterative statements into a vector based operation is called vectorization.

What are ufuncs?

ufuncs stands for "Universal Functions" and they are NumPy functions that operate on the ndarray object.

ufuncs are used to implement vectorization in NumPy which is way faster than iterating over elements.

They also provide broadcasting and additional methods like reduce, accumulate etc. that are very helpful for computation.

ufuncs also take additional arguments, like:

where boolean array or condition defining where the operations should take place.

dtype defining the return type of elements.

out output array where the return value should be copied.

Converting iterative statements into a vector based operation is called vectorization.

It is faster as modern CPUs are optimized for such operations.

list 1: [1, 2, 3, 4]

list 2: [4, 5, 6, 7]

One way of doing it is to iterate over both of the lists and then sum each elements.

python

val_1 = [1, 2, 3, 4]val_2 = [4, 5, 6, 7]z = []for i, j in zip(val_1, val_2):  
  z.append(i + j)print(z)

NumPy has a ufunc for this, called add(x, y) that will produce the same result.

python

import numpy as npx = [1, 2, 3, 4]val_2 = [4, 5, 6, 7]z = np.add(val_1, val_2)print(z)

2 questions

Which of the following is true about ufunc Intro?

It is strictly typedIt is evaluated at runtimeIt requires explicit memory managementIt is deprecated

What is the most common pitfall when working with ufunc Intro?

SyntaxErrorIndentationErrorNameErrorTypeError

Answer all questions to submit.