slmsuite.holography.toolbox.smallest_distance unexpected behavior

[tpr0p]

smallest_distance returns different value depending on ordering of vectors argument.

MWE:

import numpy as np
import matplotlib.pyplot as plt
import slmsuite.holography.toolbox as toolbox

# generate points
shape = (2, 2)
p0 = (0, 0)
p1 = (10, 0)
p2 = (0, 10)
p3 = (10, 10)
points_top_right = np.around(toolbox.fit_3pt(
    p3,
    p1,
    p2,
    N=shape,
    x0=(1, 1),
    x1=(1, 0),
    x2=(0, 1)
)).astype(np.uint64)
points_bottom_left = np.around(toolbox.fit_3pt(
    p3,
    p1,
    p2,
    N=shape,
    x0=(0, 0),
    x1=(1, 0),
    x2=(0, 1)
)).astype(np.uint64)
# plot
plt.scatter(points_bottom_left[0, :], points_bottom_left[1, :], alpha=0.5, color="red", s=100)
plt.scatter(points_top_right[0, :], points_top_right[1, :], alpha=0.5, color="blue", s=10)
xoff, yoff = 0.5, 0.5
for idx in range(np.prod(shape)):
    name_str = "{}".format(idx)
    xtr, ytr = points_top_right[:, idx]
    plt.text(xtr + xoff, ytr + yoff, name_str, color="blue")
    xbl, ybl = points_bottom_left[:, idx]
    plt.text(xbl - xoff, ybl - yoff, name_str, color="red")
ll = -1
lh = 11
plt.xlim(ll, lh)
plt.ylim(ll, lh)
plt.show()
# smallest distance
dtr = toolbox.smallest_distance(points_top_right)
dbl = toolbox.smallest_distance(points_bottom_left)
print("distance_top_right: {}, distance_bottom_left: {}".format(dtr, dbl))

[tpr0p]

The problem is that the points are np.uint64 so the subtraction in the chebyshev metric causes overflow, or similar issue. Not sure if we want to do anything about this.