norm

ssapy.utils.norm(arr)[source][source]

Compute the Euclidean norm of an array over the last axis while preserving leading axes.

Parameters:

arrarray-like: Input array where the Euclidean norm is computed along the last axis. The array can have any shape, with the last axis representing the vector components.

Returns:

normarray-like: The Euclidean norm of the input array computed along the last axis. The output shape matches the input shape, excluding the last axis.

Notes:

This implementation directly computes the norm using np.sqrt and np.einsum, avoiding the intermediate step of calling normSq. This improves performance.
The computation uses np.einsum(”…i,…i”, arr, arr) to efficiently sum the squared components along the last axis, followed by taking the square root.
Faster than using np.linalg.norm() for this specific use case and generalizes well to arrays of arbitrary shape.

Example:

>>> import numpy as np
>>> arr = np.array([[1, 2, 3], [4, 5, 6]])
>>> norm(arr)
array([3.74165739, 8.77496439])