[Compute Distances] Compute the element-wise distances between two arrays of points in 3D space. This rather simple but a snippet I find myself using all the time. #numpy

distances.py

import numpy as np
# The function for computing distances
compute = lambda a, b: np.sqrt(np.sum((b - a)**2, axis=1))

example-distances.py

import numpy as np
# The function for computing distances
compute = lambda a, b: np.sqrt(np.sum((b - a)**2, axis=1))

# Sanity check
check = compute(np.array([[0,0,0],]), np.array([[1,1,1],]))
assert np.allclose(check, np.sqrt(3))

# Example usage
import pyvista as pv
from pyvista import examples

mesh = examples.download_st_helens().warp_by_scalar()

distances = compute(mesh.points, mesh.points[mesh.n_points//2])
mesh['distances'] = distances

mesh.plot(scalars='distances')

sophisticated.py

"""Another implementation that is a bit more robust
"""
import numpy as np

def compute(a, b):
    """Comute distances between points in arrays"""
    if not isinstance(a, np.ndarray):
        a = np.array(a)
    if not isinstance(b, np.ndarray):
        b = np.array(b)
    if a.ndim != 2:
        a = a.reshape((1, -1))
    if b.ndim != 2:
        b = b.reshape((1, -1))
    return np.sqrt(np.sum((b - a)**2, axis=1))

# Sanity check
assert np.allclose(compute([0,0,0], [1,1,0]), np.sqrt(2))