NumPy: apply some function to all elements in an array. смотреть онлайн

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2023 09 16 11 17 38


1.7 Applying Functions over Each Element
Problem
You want to apply some function to all elements in an array.

Solution
Use the NumPy vectorize method:
# Load library
import numpy as np
# Create matrix
matrix = np.array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
# Create function that adds 100 to something
add_100 = lambda i: i + 100
# Create vectorized function
vectorized_add_100 = np.vectorize(add_100)
# Apply function to all elements in matrix
vectorized_add_100(matrix)
array([[101, 102, 103],
[104, 105, 106],
[107, 108, 109]])
Discussion
The NumPy vectorize method converts a function into a function that
can apply to all elements in an array or slice of an array. It’s worth noting
that vectorize is essentially a for loop over the elements and does not
increase performance. Furthermore, NumPy arrays allow us to perform
operations between arrays even if their dimensions are not the same (a
process called broadcasting). For example, we can create a much simpler
version of our solution using broadcasting:
# Add 100 to all elements
matrix + 100
array([[101, 102, 103],
[104, 105, 106]
[107, 108, 109]])
Broadcasting does not work for all shapes and situations, but it is a common
way of applying simple operations over all elements of a NumPy array