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Graham's scan convex hull algorithm, updated for Python 3.x
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def convex_hull_graham(points): | |
''' | |
Returns points on convex hull in CCW order according to Graham's scan algorithm. | |
By Tom Switzer <thomas.switzer@gmail.com>. | |
''' | |
TURN_LEFT, TURN_RIGHT, TURN_NONE = (1, -1, 0) | |
def cmp(a, b): | |
return (a > b) - (a < b) | |
def turn(p, q, r): | |
return cmp((q[0] - p[0])*(r[1] - p[1]) - (r[0] - p[0])*(q[1] - p[1]), 0) | |
def _keep_left(hull, r): | |
while len(hull) > 1 and turn(hull[-2], hull[-1], r) != TURN_LEFT: | |
hull.pop() | |
if not len(hull) or hull[-1] != r: | |
hull.append(r) | |
return hull | |
points = sorted(points) | |
l = reduce(_keep_left, points, []) | |
u = reduce(_keep_left, reversed(points), []) | |
return l.extend(u[i] for i in range(1, len(u) - 1)) or l |
I too faced this error :
return (a > b) - (a < b)
TypeError: numpy boolean subtract, the `-` operator, is not supported, use the bitwise_xor, the ^ operator, or the logical_xor function instead.
To fix this, I typecasted it to float :
def cmp(a, b):
return float(a > b) - float(a < b)
Nice! Thanks.
Numba version for the graham_hull
import numba
import numpy as np
@numba.njit
def cmp(a, b):
return (a > b) - (a < b)
@numba.njit
def turn(p, q, r):
return cmp((q[..., 0] - p[..., 0])*(r[..., 1] - p[..., 1]) - (r[..., 0] - p[..., 0])*(q[..., 1] - p[..., 1]), 0)
@numba.njit
def reduce_keepleft(points):
left = []
for r in points:
while len(left) > 1 and turn(left[-2], left[-1], r) != 1:
left.pop()
if not len(left) or not np.allclose(left[-1], r, 1e-5, 1e-8, False):
left.append(r)
return left
@numba.njit
def sort(points):
for i in range(points.shape[-1]-1, -1, -1):
idx = np.argsort(points[:, i], kind="mergesort")
points = points[idx]
return points
@numba.njit
def stack(alist):
out = np.empty((len(alist), *alist[0].shape))
for i, r in enumerate(alist):
out[i] = r
return out
@numba.njit
def convex_hull_graham(points):
points = sort(points)
l = reduce_keepleft(points)
u = reduce_keepleft(points[::-1])
hull = l + u[1:-1]
return stack(hull)
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