1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
|
discard """
output: '''
'''
ccodeCheck: "\\i ! @'deepCopy(' .*"
"""
# parallel convex hull for Nim bigbreak
# nim c --threads:on -d:release pconvex_hull.nim
import algorithm, sequtils, threadpool
type Point = tuple[x, y: float]
proc cmpPoint(a, b: Point): int =
result = cmp(a.x, b.x)
if result == 0:
result = cmp(a.y, b.y)
template cross[T](o, a, b: T): untyped =
(a.x - o.x) * (b.y - o.y) - (a.y - o.y) * (b.x - o.x)
template pro(): untyped =
while lr1 > 0 and cross(result[lr1 - 1], result[lr1], p[i]) <= 0:
discard result.pop
lr1 -= 1
result.add(p[i])
lr1 += 1
proc half[T](p: seq[T]; upper: bool): seq[T] =
var i, lr1: int
result = @[]
lr1 = -1
if upper:
i = 0
while i <= high(p):
pro()
i += 1
else:
i = high(p)
while i >= low(p):
pro()
i -= 1
discard result.pop
proc convex_hull[T](points: var seq[T], cmp: proc(x, y: T): int {.closure.}) : seq[T] =
if len(points) < 2: return points
points.sort(cmp)
var ul: array[2, FlowVar[seq[T]]]
parallel:
for k in 0..ul.high:
ul[k] = spawn half[T](points, k == 0)
result = concat(^ul[0], ^ul[1])
var s = map(toSeq(0..9999), proc(x: int): Point = (float(x div 100), float(x mod 100)))
# On some runs, this pool size reduction will set the "shutdown" attribute on the
# worker thread that executes our spawned task, before we can read the flowvars.
setMaxPoolSize 2
for i in 0..2:
doAssert convex_hull[Point](s, cmpPoint) ==
@[(0.0, 0.0), (99.0, 0.0), (99.0, 99.0), (0.0, 99.0)]
|