trimesh issue with minimum sphere

cloud_data.npy

not_quite_minimum_sphere.py

import numpy as np
import trimesh

points = np.load('cloud_data.npy')
center, radius = trimesh.nsphere.minimum_nsphere(points)
print('data has already been centered/rescaled on minimum_nsphere')
print('center=%s, radius=%s' % (center, radius))
print('Largest point norm: %.3f' % np.max(np.linalg.norm(points, axis=-1)))

naive_center = (np.min(points, axis=0) + np.max(points, axis=0)) / 2
points = points - naive_center
r = np.max(np.linalg.norm(points, axis=-1))
print('Largest point norm after naive recentering: %.3f' % r)

# trimesh.points.PointCloud(points).show()