tests/perf_bench: Add some benchmarks from python-performance.
From https://github.com/python/pyperformance commit 6690642ddeda46fc5ee6e97c3ef4b2f292348ab8
This commit is contained in:
Damien George
parent
e92c9aa9c9
commit
127714c3af
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# Source: https://github.com/python/pyperformance
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# License: MIT
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# create chaosgame-like fractals
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# Copyright (C) 2005 Carl Friedrich Bolz
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import math
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import random
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class GVector(object):
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def __init__(self, x=0, y=0, z=0):
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self.x = x
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self.y = y
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self.z = z
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def Mag(self):
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return math.sqrt(self.x ** 2 + self.y ** 2 + self.z ** 2)
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def dist(self, other):
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return math.sqrt((self.x - other.x) ** 2
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+ (self.y - other.y) ** 2
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+ (self.z - other.z) ** 2)
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def __add__(self, other):
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if not isinstance(other, GVector):
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raise ValueError("Can't add GVector to " + str(type(other)))
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v = GVector(self.x + other.x, self.y + other.y, self.z + other.z)
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return v
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def __sub__(self, other):
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return self + other * -1
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def __mul__(self, other):
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v = GVector(self.x * other, self.y * other, self.z * other)
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return v
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__rmul__ = __mul__
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def linear_combination(self, other, l1, l2=None):
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if l2 is None:
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l2 = 1 - l1
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v = GVector(self.x * l1 + other.x * l2,
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self.y * l1 + other.y * l2,
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self.z * l1 + other.z * l2)
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return v
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def __str__(self):
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return "<%f, %f, %f>" % (self.x, self.y, self.z)
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def __repr__(self):
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return "GVector(%f, %f, %f)" % (self.x, self.y, self.z)
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class Spline(object):
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"""Class for representing B-Splines and NURBS of arbitrary degree"""
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def __init__(self, points, degree, knots):
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"""Creates a Spline.
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points is a list of GVector, degree is the degree of the Spline.
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"""
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if len(points) > len(knots) - degree + 1:
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raise ValueError("too many control points")
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elif len(points) < len(knots) - degree + 1:
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raise ValueError("not enough control points")
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last = knots[0]
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for cur in knots[1:]:
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if cur < last:
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raise ValueError("knots not strictly increasing")
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last = cur
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self.knots = knots
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self.points = points
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self.degree = degree
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def GetDomain(self):
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"""Returns the domain of the B-Spline"""
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return (self.knots[self.degree - 1],
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self.knots[len(self.knots) - self.degree])
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def __call__(self, u):
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"""Calculates a point of the B-Spline using de Boors Algorithm"""
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dom = self.GetDomain()
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if u < dom[0] or u > dom[1]:
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raise ValueError("Function value not in domain")
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if u == dom[0]:
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return self.points[0]
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if u == dom[1]:
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return self.points[-1]
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I = self.GetIndex(u)
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d = [self.points[I - self.degree + 1 + ii]
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for ii in range(self.degree + 1)]
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U = self.knots
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for ik in range(1, self.degree + 1):
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for ii in range(I - self.degree + ik + 1, I + 2):
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ua = U[ii + self.degree - ik]
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ub = U[ii - 1]
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co1 = (ua - u) / (ua - ub)
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co2 = (u - ub) / (ua - ub)
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index = ii - I + self.degree - ik - 1
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d[index] = d[index].linear_combination(d[index + 1], co1, co2)
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return d[0]
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def GetIndex(self, u):
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dom = self.GetDomain()
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for ii in range(self.degree - 1, len(self.knots) - self.degree):
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if u >= self.knots[ii] and u < self.knots[ii + 1]:
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I = ii
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break
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else:
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I = dom[1] - 1
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return I
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def __len__(self):
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return len(self.points)
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def __repr__(self):
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return "Spline(%r, %r, %r)" % (self.points, self.degree, self.knots)
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def write_ppm(im, w, h, filename):
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with open(filename, "wb") as f:
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f.write(b'P6\n%i %i\n255\n' % (w, h))
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for j in range(h):
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for i in range(w):
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val = im[j * w + i]
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c = val * 255
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f.write(b'%c%c%c' % (c, c, c))
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class Chaosgame(object):
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def __init__(self, splines, thickness, subdivs):
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self.splines = splines
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self.thickness = thickness
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self.minx = min([p.x for spl in splines for p in spl.points])
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self.miny = min([p.y for spl in splines for p in spl.points])
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self.maxx = max([p.x for spl in splines for p in spl.points])
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self.maxy = max([p.y for spl in splines for p in spl.points])
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self.height = self.maxy - self.miny
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self.width = self.maxx - self.minx
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self.num_trafos = []
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maxlength = thickness * self.width / self.height
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for spl in splines:
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length = 0
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curr = spl(0)
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for i in range(1, subdivs + 1):
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last = curr
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t = 1 / subdivs * i
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curr = spl(t)
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length += curr.dist(last)
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self.num_trafos.append(max(1, int(length / maxlength * 1.5)))
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self.num_total = sum(self.num_trafos)
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def get_random_trafo(self):
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r = random.randrange(int(self.num_total) + 1)
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l = 0
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for i in range(len(self.num_trafos)):
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if r >= l and r < l + self.num_trafos[i]:
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return i, random.randrange(self.num_trafos[i])
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l += self.num_trafos[i]
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return len(self.num_trafos) - 1, random.randrange(self.num_trafos[-1])
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def transform_point(self, point, trafo=None):
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x = (point.x - self.minx) / self.width
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y = (point.y - self.miny) / self.height
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if trafo is None:
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trafo = self.get_random_trafo()
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start, end = self.splines[trafo[0]].GetDomain()
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length = end - start
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seg_length = length / self.num_trafos[trafo[0]]
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t = start + seg_length * trafo[1] + seg_length * x
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basepoint = self.splines[trafo[0]](t)
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if t + 1 / 50000 > end:
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neighbour = self.splines[trafo[0]](t - 1 / 50000)
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derivative = neighbour - basepoint
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else:
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neighbour = self.splines[trafo[0]](t + 1 / 50000)
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derivative = basepoint - neighbour
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if derivative.Mag() != 0:
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basepoint.x += derivative.y / derivative.Mag() * (y - 0.5) * \
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self.thickness
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basepoint.y += -derivative.x / derivative.Mag() * (y - 0.5) * \
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self.thickness
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else:
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# can happen, especially with single precision float
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pass
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self.truncate(basepoint)
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return basepoint
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def truncate(self, point):
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if point.x >= self.maxx:
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point.x = self.maxx
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if point.y >= self.maxy:
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point.y = self.maxy
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if point.x < self.minx:
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point.x = self.minx
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if point.y < self.miny:
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point.y = self.miny
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def create_image_chaos(self, w, h, iterations, rng_seed):
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# Always use the same sequence of random numbers
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# to get reproductible benchmark
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random.seed(rng_seed)
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im = bytearray(w * h)
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point = GVector((self.maxx + self.minx) / 2,
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(self.maxy + self.miny) / 2, 0)
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for _ in range(iterations):
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point = self.transform_point(point)
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x = (point.x - self.minx) / self.width * w
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y = (point.y - self.miny) / self.height * h
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x = int(x)
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y = int(y)
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if x == w:
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x -= 1
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if y == h:
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y -= 1
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im[(h - y - 1) * w + x] = 1
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return im
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###########################################################################
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# Benchmark interface
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bm_params = {
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(100, 50): (0.25, 100, 50, 50, 50, 1234),
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(1000, 1000): (0.25, 200, 400, 400, 1000, 1234),
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(5000, 1000): (0.25, 400, 500, 500, 7000, 1234),
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}
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def bm_setup(params):
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splines = [
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Spline([
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GVector(1.597, 3.304, 0.0),
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GVector(1.576, 4.123, 0.0),
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GVector(1.313, 5.288, 0.0),
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GVector(1.619, 5.330, 0.0),
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GVector(2.890, 5.503, 0.0),
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GVector(2.373, 4.382, 0.0),
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GVector(1.662, 4.360, 0.0)],
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3, [0, 0, 0, 1, 1, 1, 2, 2, 2]),
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Spline([
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GVector(2.805, 4.017, 0.0),
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GVector(2.551, 3.525, 0.0),
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GVector(1.979, 2.620, 0.0),
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GVector(1.979, 2.620, 0.0)],
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3, [0, 0, 0, 1, 1, 1]),
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Spline([
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GVector(2.002, 4.011, 0.0),
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GVector(2.335, 3.313, 0.0),
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GVector(2.367, 3.233, 0.0),
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GVector(2.367, 3.233, 0.0)],
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3, [0, 0, 0, 1, 1, 1])
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]
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chaos = Chaosgame(splines, params[0], params[1])
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image = None
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def run():
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nonlocal image
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_, _, width, height, iter, rng_seed = params
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image = chaos.create_image_chaos(width, height, iter, rng_seed)
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def result():
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norm = params[4]
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# Images are not the same when floating point behaviour is different,
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# so return percentage of pixels that are set (rounded to int).
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#write_ppm(image, params[2], params[3], 'out-.ppm')
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pix = int(100 * sum(image) / len(image))
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return norm, pix
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return run, result
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@ -0,0 +1,67 @@
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# Source: https://github.com/python/pyperformance
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# License: MIT
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# The Computer Language Benchmarks Game
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# http://benchmarksgame.alioth.debian.org/
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# Contributed by Sokolov Yura, modified by Tupteq.
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def fannkuch(n):
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count = list(range(1, n + 1))
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max_flips = 0
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m = n - 1
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r = n
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check = 0
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perm1 = list(range(n))
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perm = list(range(n))
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perm1_ins = perm1.insert
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perm1_pop = perm1.pop
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while 1:
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if check < 30:
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check += 1
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while r != 1:
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count[r - 1] = r
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r -= 1
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if perm1[0] != 0 and perm1[m] != m:
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perm = perm1[:]
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flips_count = 0
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k = perm[0]
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while k:
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perm[:k + 1] = perm[k::-1]
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flips_count += 1
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k = perm[0]
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if flips_count > max_flips:
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max_flips = flips_count
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while r != n:
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perm1_ins(r, perm1_pop(0))
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count[r] -= 1
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if count[r] > 0:
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break
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r += 1
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else:
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return max_flips
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###########################################################################
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# Benchmark interface
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bm_params = {
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(50, 10): (5,),
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(100, 10): (6,),
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(500, 10): (7,),
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(1000, 10): (8,),
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(5000, 10): (9,),
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}
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def bm_setup(params):
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state = None
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def run():
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nonlocal state
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state = fannkuch(params[0])
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def result():
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return params[0], state
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return run, result
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@ -0,0 +1,70 @@
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# Source: https://github.com/python/pyperformance
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# License: MIT
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# Artificial, floating point-heavy benchmark originally used by Factor.
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from math import sin, cos, sqrt
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class Point(object):
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__slots__ = ('x', 'y', 'z')
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def __init__(self, i):
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self.x = x = sin(i)
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self.y = cos(i) * 3
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self.z = (x * x) / 2
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def __repr__(self):
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return "<Point: x=%s, y=%s, z=%s>" % (self.x, self.y, self.z)
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def normalize(self):
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x = self.x
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y = self.y
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z = self.z
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norm = sqrt(x * x + y * y + z * z)
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self.x /= norm
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self.y /= norm
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self.z /= norm
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def maximize(self, other):
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self.x = self.x if self.x > other.x else other.x
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self.y = self.y if self.y > other.y else other.y
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self.z = self.z if self.z > other.z else other.z
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return self
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def maximize(points):
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next = points[0]
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for p in points[1:]:
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next = next.maximize(p)
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return next
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def benchmark(n):
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points = [None] * n
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for i in range(n):
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points[i] = Point(i)
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for p in points:
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p.normalize()
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return maximize(points)
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###########################################################################
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# Benchmark interface
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bm_params = {
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(50, 25): (1, 150),
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(100, 100): (1, 250),
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(1000, 1000): (10, 1500),
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(5000, 1000): (20, 3000),
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}
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def bm_setup(params):
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state = None
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def run():
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nonlocal state
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for _ in range(params[0]):
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state = benchmark(params[1])
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def result():
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return params[0] * params[1], 'Point(%.4f, %.4f, %.4f)' % (state.x, state.y, state.z)
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return run, result
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@ -0,0 +1,647 @@
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# Source: https://github.com/python/pyperformance
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# License: MIT
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# Solver of Hexiom board game.
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# Benchmark from Laurent Vaucher.
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# Source: https://github.com/slowfrog/hexiom : hexiom2.py, level36.txt
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# (Main function tweaked by Armin Rigo.)
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##################################
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class Dir(object):
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def __init__(self, x, y):
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self.x = x
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self.y = y
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DIRS = [Dir(1, 0),
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Dir(-1, 0),
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Dir(0, 1),
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Dir(0, -1),
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Dir(1, 1),
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Dir(-1, -1)]
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EMPTY = 7
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##################################
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class Done(object):
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MIN_CHOICE_STRATEGY = 0
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MAX_CHOICE_STRATEGY = 1
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HIGHEST_VALUE_STRATEGY = 2
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FIRST_STRATEGY = 3
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MAX_NEIGHBORS_STRATEGY = 4
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MIN_NEIGHBORS_STRATEGY = 5
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def __init__(self, count, empty=False):
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self.count = count
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self.cells = None if empty else [
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[0, 1, 2, 3, 4, 5, 6, EMPTY] for i in range(count)]
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def clone(self):
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ret = Done(self.count, True)
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ret.cells = [self.cells[i][:] for i in range(self.count)]
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return ret
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def __getitem__(self, i):
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return self.cells[i]
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def set_done(self, i, v):
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self.cells[i] = [v]
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def already_done(self, i):
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return len(self.cells[i]) == 1
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def remove(self, i, v):
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if v in self.cells[i]:
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self.cells[i].remove(v)
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return True
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else:
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return False
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def remove_all(self, v):
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for i in range(self.count):
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self.remove(i, v)
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|
||||
def remove_unfixed(self, v):
|
||||
changed = False
|
||||
for i in range(self.count):
|
||||
if not self.already_done(i):
|
||||
if self.remove(i, v):
|
||||
changed = True
|
||||
return changed
|
||||
|
||||
def filter_tiles(self, tiles):
|
||||
for v in range(8):
|
||||
if tiles[v] == 0:
|
||||
self.remove_all(v)
|
||||
|
||||
def next_cell_min_choice(self):
|
||||
minlen = 10
|
||||
mini = -1
|
||||
for i in range(self.count):
|
||||
if 1 < len(self.cells[i]) < minlen:
|
||||
minlen = len(self.cells[i])
|
||||
mini = i
|
||||
return mini
|
||||
|
||||
def next_cell_max_choice(self):
|
||||
maxlen = 1
|
||||
maxi = -1
|
||||
for i in range(self.count):
|
||||
if maxlen < len(self.cells[i]):
|
||||
maxlen = len(self.cells[i])
|
||||
maxi = i
|
||||
return maxi
|
||||
|
||||
def next_cell_highest_value(self):
|
||||
maxval = -1
|
||||
maxi = -1
|
||||
for i in range(self.count):
|
||||
if (not self.already_done(i)):
|
||||
maxvali = max(k for k in self.cells[i] if k != EMPTY)
|
||||
if maxval < maxvali:
|
||||
maxval = maxvali
|
||||
maxi = i
|
||||
return maxi
|
||||
|
||||
def next_cell_first(self):
|
||||
for i in range(self.count):
|
||||
if (not self.already_done(i)):
|
||||
return i
|
||||
return -1
|
||||
|
||||
def next_cell_max_neighbors(self, pos):
|
||||
maxn = -1
|
||||
maxi = -1
|
||||
for i in range(self.count):
|
||||
if not self.already_done(i):
|
||||
cells_around = pos.hex.get_by_id(i).links
|
||||
n = sum(1 if (self.already_done(nid) and (self[nid][0] != EMPTY)) else 0
|
||||
for nid in cells_around)
|
||||
if n > maxn:
|
||||
maxn = n
|
||||
maxi = i
|
||||
return maxi
|
||||
|
||||
def next_cell_min_neighbors(self, pos):
|
||||
minn = 7
|
||||
mini = -1
|
||||
for i in range(self.count):
|
||||
if not self.already_done(i):
|
||||
cells_around = pos.hex.get_by_id(i).links
|
||||
n = sum(1 if (self.already_done(nid) and (self[nid][0] != EMPTY)) else 0
|
||||
for nid in cells_around)
|
||||
if n < minn:
|
||||
minn = n
|
||||
mini = i
|
||||
return mini
|
||||
|
||||
def next_cell(self, pos, strategy=HIGHEST_VALUE_STRATEGY):
|
||||
if strategy == Done.HIGHEST_VALUE_STRATEGY:
|
||||
return self.next_cell_highest_value()
|
||||
elif strategy == Done.MIN_CHOICE_STRATEGY:
|
||||
return self.next_cell_min_choice()
|
||||
elif strategy == Done.MAX_CHOICE_STRATEGY:
|
||||
return self.next_cell_max_choice()
|
||||
elif strategy == Done.FIRST_STRATEGY:
|
||||
return self.next_cell_first()
|
||||
elif strategy == Done.MAX_NEIGHBORS_STRATEGY:
|
||||
return self.next_cell_max_neighbors(pos)
|
||||
elif strategy == Done.MIN_NEIGHBORS_STRATEGY:
|
||||
return self.next_cell_min_neighbors(pos)
|
||||
else:
|
||||
raise Exception("Wrong strategy: %d" % strategy)
|
||||
|
||||
##################################
|
||||
|
||||
|
||||
class Node(object):
|
||||
|
||||
def __init__(self, pos, id, links):
|
||||
self.pos = pos
|
||||
self.id = id
|
||||
self.links = links
|
||||
|
||||
##################################
|
||||
|
||||
|
||||
class Hex(object):
|
||||
|
||||
def __init__(self, size):
|
||||
self.size = size
|
||||
self.count = 3 * size * (size - 1) + 1
|
||||
self.nodes_by_id = self.count * [None]
|
||||
self.nodes_by_pos = {}
|
||||
id = 0
|
||||
for y in range(size):
|
||||
for x in range(size + y):
|
||||
pos = (x, y)
|
||||
node = Node(pos, id, [])
|
||||
self.nodes_by_pos[pos] = node
|
||||
self.nodes_by_id[node.id] = node
|
||||
id += 1
|
||||
for y in range(1, size):
|
||||
for x in range(y, size * 2 - 1):
|
||||
ry = size + y - 1
|
||||
pos = (x, ry)
|
||||
node = Node(pos, id, [])
|
||||
self.nodes_by_pos[pos] = node
|
||||
self.nodes_by_id[node.id] = node
|
||||
id += 1
|
||||
|
||||
def link_nodes(self):
|
||||
for node in self.nodes_by_id:
|
||||
(x, y) = node.pos
|
||||
for dir in DIRS:
|
||||
nx = x + dir.x
|
||||
ny = y + dir.y
|
||||
if self.contains_pos((nx, ny)):
|
||||
node.links.append(self.nodes_by_pos[(nx, ny)].id)
|
||||
|
||||
def contains_pos(self, pos):
|
||||
return pos in self.nodes_by_pos
|
||||
|
||||
def get_by_pos(self, pos):
|
||||
return self.nodes_by_pos[pos]
|
||||
|
||||
def get_by_id(self, id):
|
||||
return self.nodes_by_id[id]
|
||||
|
||||
|
||||
##################################
|
||||
class Pos(object):
|
||||
|
||||
def __init__(self, hex, tiles, done=None):
|
||||
self.hex = hex
|
||||
self.tiles = tiles
|
||||
self.done = Done(hex.count) if done is None else done
|
||||
|
||||
def clone(self):
|
||||
return Pos(self.hex, self.tiles, self.done.clone())
|
||||
|
||||
##################################
|
||||
|
||||
|
||||
def constraint_pass(pos, last_move=None):
|
||||
changed = False
|
||||
left = pos.tiles[:]
|
||||
done = pos.done
|
||||
|
||||
# Remove impossible values from free cells
|
||||
free_cells = (range(done.count) if last_move is None
|
||||
else pos.hex.get_by_id(last_move).links)
|
||||
for i in free_cells:
|
||||
if not done.already_done(i):
|
||||
vmax = 0
|
||||
vmin = 0
|
||||
cells_around = pos.hex.get_by_id(i).links
|
||||
for nid in cells_around:
|
||||
if done.already_done(nid):
|
||||
if done[nid][0] != EMPTY:
|
||||
vmin += 1
|
||||
vmax += 1
|
||||
else:
|
||||
vmax += 1
|
||||
|
||||
for num in range(7):
|
||||
if (num < vmin) or (num > vmax):
|
||||
if done.remove(i, num):
|
||||
changed = True
|
||||
|
||||
# Computes how many of each value is still free
|
||||
for cell in done.cells:
|
||||
if len(cell) == 1:
|
||||
left[cell[0]] -= 1
|
||||
|
||||
for v in range(8):
|
||||
# If there is none, remove the possibility from all tiles
|
||||
if (pos.tiles[v] > 0) and (left[v] == 0):
|
||||
if done.remove_unfixed(v):
|
||||
changed = True
|
||||
else:
|
||||
possible = sum((1 if v in cell else 0) for cell in done.cells)
|
||||
# If the number of possible cells for a value is exactly the number of available tiles
|
||||
# put a tile in each cell
|
||||
if pos.tiles[v] == possible:
|
||||
for i in range(done.count):
|
||||
cell = done.cells[i]
|
||||
if (not done.already_done(i)) and (v in cell):
|
||||
done.set_done(i, v)
|
||||
changed = True
|
||||
|
||||
# Force empty or non-empty around filled cells
|
||||
filled_cells = (range(done.count) if last_move is None
|
||||
else [last_move])
|
||||
for i in filled_cells:
|
||||
if done.already_done(i):
|
||||
num = done[i][0]
|
||||
empties = 0
|
||||
filled = 0
|
||||
unknown = []
|
||||
cells_around = pos.hex.get_by_id(i).links
|
||||
for nid in cells_around:
|
||||
if done.already_done(nid):
|
||||
if done[nid][0] == EMPTY:
|
||||
empties += 1
|
||||
else:
|
||||
filled += 1
|
||||
else:
|
||||
unknown.append(nid)
|
||||
if len(unknown) > 0:
|
||||
if num == filled:
|
||||
for u in unknown:
|
||||
if EMPTY in done[u]:
|
||||
done.set_done(u, EMPTY)
|
||||
changed = True
|
||||
# else:
|
||||
# raise Exception("Houston, we've got a problem")
|
||||
elif num == filled + len(unknown):
|
||||
for u in unknown:
|
||||
if done.remove(u, EMPTY):
|
||||
changed = True
|
||||
|
||||
return changed
|
||||
|
||||
|
||||
ASCENDING = 1
|
||||
DESCENDING = -1
|
||||
|
||||
|
||||
def find_moves(pos, strategy, order):
|
||||
done = pos.done
|
||||
cell_id = done.next_cell(pos, strategy)
|
||||
if cell_id < 0:
|
||||
return []
|
||||
|
||||
if order == ASCENDING:
|
||||
return [(cell_id, v) for v in done[cell_id]]
|
||||
else:
|
||||
# Try higher values first and EMPTY last
|
||||
moves = list(reversed([(cell_id, v)
|
||||
for v in done[cell_id] if v != EMPTY]))
|
||||
if EMPTY in done[cell_id]:
|
||||
moves.append((cell_id, EMPTY))
|
||||
return moves
|
||||
|
||||
|
||||
def play_move(pos, move):
|
||||
(cell_id, i) = move
|
||||
pos.done.set_done(cell_id, i)
|
||||
|
||||
|
||||
def print_pos(pos, output):
|
||||
hex = pos.hex
|
||||
done = pos.done
|
||||
size = hex.size
|
||||
for y in range(size):
|
||||
print(" " * (size - y - 1), end="", file=output)
|
||||
for x in range(size + y):
|
||||
pos2 = (x, y)
|
||||
id = hex.get_by_pos(pos2).id
|
||||
if done.already_done(id):
|
||||
c = done[id][0] if done[id][0] != EMPTY else "."
|
||||
else:
|
||||
c = "?"
|
||||
print("%s " % c, end="", file=output)
|
||||
print(end="\n", file=output)
|
||||
for y in range(1, size):
|
||||
print(" " * y, end="", file=output)
|
||||
for x in range(y, size * 2 - 1):
|
||||
ry = size + y - 1
|
||||
pos2 = (x, ry)
|
||||
id = hex.get_by_pos(pos2).id
|
||||
if done.already_done(id):
|
||||
c = done[id][0] if done[id][0] != EMPTY else "."
|
||||
else:
|
||||
c = "?"
|
||||
print("%s " % c, end="", file=output)
|
||||
print(end="\n", file=output)
|
||||
|
||||
|
||||
OPEN = 0
|
||||
SOLVED = 1
|
||||
IMPOSSIBLE = -1
|
||||
|
||||
|
||||
def solved(pos, output, verbose=False):
|
||||
hex = pos.hex
|
||||
tiles = pos.tiles[:]
|
||||
done = pos.done
|
||||
exact = True
|
||||
all_done = True
|
||||
for i in range(hex.count):
|
||||
if len(done[i]) == 0:
|
||||
return IMPOSSIBLE
|
||||
elif done.already_done(i):
|
||||
num = done[i][0]
|
||||
tiles[num] -= 1
|
||||
if (tiles[num] < 0):
|
||||
return IMPOSSIBLE
|
||||
vmax = 0
|
||||
vmin = 0
|
||||
if num != EMPTY:
|
||||
cells_around = hex.get_by_id(i).links
|
||||
for nid in cells_around:
|
||||
if done.already_done(nid):
|
||||
if done[nid][0] != EMPTY:
|
||||
vmin += 1
|
||||
vmax += 1
|
||||
else:
|
||||
vmax += 1
|
||||
|
||||
if (num < vmin) or (num > vmax):
|
||||
return IMPOSSIBLE
|
||||
if num != vmin:
|
||||
exact = False
|
||||
else:
|
||||
all_done = False
|
||||
|
||||
if (not all_done) or (not exact):
|
||||
return OPEN
|
||||
|
||||
print_pos(pos, output)
|
||||
return SOLVED
|
||||
|
||||
|
||||
def solve_step(prev, strategy, order, output, first=False):
|
||||
if first:
|
||||
pos = prev.clone()
|
||||
while constraint_pass(pos):
|
||||
pass
|
||||
else:
|
||||
pos = prev
|
||||
|
||||
moves = find_moves(pos, strategy, order)
|
||||
if len(moves) == 0:
|
||||
return solved(pos, output)
|
||||
else:
|
||||
for move in moves:
|
||||
# print("Trying (%d, %d)" % (move[0], move[1]))
|
||||
ret = OPEN
|
||||
new_pos = pos.clone()
|
||||
play_move(new_pos, move)
|
||||
# print_pos(new_pos)
|
||||
while constraint_pass(new_pos, move[0]):
|
||||
pass
|
||||
cur_status = solved(new_pos, output)
|
||||
if cur_status != OPEN:
|
||||
ret = cur_status
|
||||
else:
|
||||
ret = solve_step(new_pos, strategy, order, output)
|
||||
if ret == SOLVED:
|
||||
return SOLVED
|
||||
return IMPOSSIBLE
|
||||
|
||||
|
||||
def check_valid(pos):
|
||||
hex = pos.hex
|
||||
tiles = pos.tiles
|
||||
# fill missing entries in tiles
|
||||
tot = 0
|
||||
for i in range(8):
|
||||
if tiles[i] > 0:
|
||||
tot += tiles[i]
|
||||
else:
|
||||
tiles[i] = 0
|
||||
# check total
|
||||
if tot != hex.count:
|
||||
raise Exception(
|
||||
"Invalid input. Expected %d tiles, got %d." % (hex.count, tot))
|
||||
|
||||
|
||||
def solve(pos, strategy, order, output):
|
||||
check_valid(pos)
|
||||
return solve_step(pos, strategy, order, output, first=True)
|
||||
|
||||
|
||||
# TODO Write an 'iterator' to go over all x,y positions
|
||||
|
||||
def read_file(file):
|
||||
lines = [line.strip("\r\n") for line in file.splitlines()]
|
||||
size = int(lines[0])
|
||||
hex = Hex(size)
|
||||
linei = 1
|
||||
tiles = 8 * [0]
|
||||
done = Done(hex.count)
|
||||
for y in range(size):
|
||||
line = lines[linei][size - y - 1:]
|
||||
p = 0
|
||||
for x in range(size + y):
|
||||
tile = line[p:p + 2]
|
||||
p += 2
|
||||
if tile[1] == ".":
|
||||
inctile = EMPTY
|
||||
else:
|
||||
inctile = int(tile)
|
||||
tiles[inctile] += 1
|
||||
# Look for locked tiles
|
||||
if tile[0] == "+":
|
||||
# print("Adding locked tile: %d at pos %d, %d, id=%d" %
|
||||
# (inctile, x, y, hex.get_by_pos((x, y)).id))
|
||||
done.set_done(hex.get_by_pos((x, y)).id, inctile)
|
||||
|
||||
linei += 1
|
||||
for y in range(1, size):
|
||||
ry = size - 1 + y
|
||||
line = lines[linei][y:]
|
||||
p = 0
|
||||
for x in range(y, size * 2 - 1):
|
||||
tile = line[p:p + 2]
|
||||
p += 2
|
||||
if tile[1] == ".":
|
||||
inctile = EMPTY
|
||||
else:
|
||||
inctile = int(tile)
|
||||
tiles[inctile] += 1
|
||||
# Look for locked tiles
|
||||
if tile[0] == "+":
|
||||
# print("Adding locked tile: %d at pos %d, %d, id=%d" %
|
||||
# (inctile, x, ry, hex.get_by_pos((x, ry)).id))
|
||||
done.set_done(hex.get_by_pos((x, ry)).id, inctile)
|
||||
linei += 1
|
||||
hex.link_nodes()
|
||||
done.filter_tiles(tiles)
|
||||
return Pos(hex, tiles, done)
|
||||
|
||||
|
||||
def solve_file(file, strategy, order, output):
|
||||
pos = read_file(file)
|
||||
solve(pos, strategy, order, output)
|
||||
|
||||
|
||||
LEVELS = {}
|
||||
|
||||
LEVELS[2] = ("""
|
||||
2
|
||||
. 1
|
||||
. 1 1
|
||||
1 .
|
||||
""", """\
|
||||
1 1
|
||||
. . .
|
||||
1 1
|
||||
""")
|
||||
|
||||
LEVELS[10] = ("""
|
||||
3
|
||||
+.+. .
|
||||
+. 0 . 2
|
||||
. 1+2 1 .
|
||||
2 . 0+.
|
||||
.+.+.
|
||||
""", """\
|
||||
. . 1
|
||||
. 1 . 2
|
||||
0 . 2 2 .
|
||||
. . . .
|
||||
0 . .
|
||||
""")
|
||||
|
||||
LEVELS[20] = ("""
|
||||
3
|
||||
. 5 4
|
||||
. 2+.+1
|
||||
. 3+2 3 .
|
||||
+2+. 5 .
|
||||
. 3 .
|
||||
""", """\
|
||||
3 3 2
|
||||
4 5 . 1
|
||||
3 5 2 . .
|
||||
2 . . .
|
||||
. . .
|
||||
""")
|
||||
|
||||
LEVELS[25] = ("""
|
||||
3
|
||||
4 . .
|
||||
. . 2 .
|
||||
4 3 2 . 4
|
||||
2 2 3 .
|
||||
4 2 4
|
||||
""", """\
|
||||
3 4 2
|
||||
2 4 4 .
|
||||
. . . 4 2
|
||||
. 2 4 3
|
||||
. 2 .
|
||||
""")
|
||||
|
||||
LEVELS[30] = ("""
|
||||
4
|
||||
5 5 . .
|
||||
3 . 2+2 6
|
||||
3 . 2 . 5 .
|
||||
. 3 3+4 4 . 3
|
||||
4 5 4 . 5 4
|
||||
5+2 . . 3
|
||||
4 . . .
|
||||
""", """\
|
||||
3 4 3 .
|
||||
4 6 5 2 .
|
||||
2 5 5 . . 2
|
||||
. . 5 4 . 4 3
|
||||
. 3 5 4 5 4
|
||||
. 2 . 3 3
|
||||
. . . .
|
||||
""")
|
||||
|
||||
LEVELS[36] = ("""
|
||||
4
|
||||
2 1 1 2
|
||||
3 3 3 . .
|
||||
2 3 3 . 4 .
|
||||
. 2 . 2 4 3 2
|
||||
2 2 . . . 2
|
||||
4 3 4 . .
|
||||
3 2 3 3
|
||||
""", """\
|
||||
3 4 3 2
|
||||
3 4 4 . 3
|
||||
2 . . 3 4 3
|
||||
2 . 1 . 3 . 2
|
||||
3 3 . 2 . 2
|
||||
3 . 2 . 2
|
||||
2 2 . 1
|
||||
""")
|
||||
|
||||
|
||||
###########################################################################
|
||||
# Benchmark interface
|
||||
|
||||
bm_params = {
|
||||
(100, 100): (1, 10, DESCENDING, Done.FIRST_STRATEGY),
|
||||
(1000, 1000): (1, 25, DESCENDING, Done.FIRST_STRATEGY),
|
||||
(5000, 1000): (10, 25, DESCENDING, Done.FIRST_STRATEGY),
|
||||
}
|
||||
|
||||
def bm_setup(params):
|
||||
try:
|
||||
import uio as io
|
||||
except ImportError:
|
||||
import io
|
||||
|
||||
loops, level, order, strategy = params
|
||||
|
||||
board, solution = LEVELS[level]
|
||||
board = board.strip()
|
||||
expected = solution.rstrip()
|
||||
output = None
|
||||
|
||||
def run():
|
||||
nonlocal output
|
||||
for _ in range(loops):
|
||||
stream = io.StringIO()
|
||||
solve_file(board, strategy, order, stream)
|
||||
output = stream.getvalue()
|
||||
stream = None
|
||||
|
||||
def result():
|
||||
norm = params[0] * params[1]
|
||||
out = '\n'.join(line.rstrip() for line in output.splitlines())
|
||||
return norm, ((out == expected), out)
|
||||
|
||||
return run, result
|
||||
|
|
@ -0,0 +1,62 @@
|
|||
# Source: https://github.com/python/pyperformance
|
||||
# License: MIT
|
||||
|
||||
# Simple, brute-force N-Queens solver.
|
||||
# author: collinwinter@google.com (Collin Winter)
|
||||
# n_queens function: Copyright 2009 Raymond Hettinger
|
||||
|
||||
# Pure-Python implementation of itertools.permutations().
|
||||
def permutations(iterable, r=None):
|
||||
"""permutations(range(3), 2) --> (0,1) (0,2) (1,0) (1,2) (2,0) (2,1)"""
|
||||
pool = tuple(iterable)
|
||||
n = len(pool)
|
||||
if r is None:
|
||||
r = n
|
||||
indices = list(range(n))
|
||||
cycles = list(range(n - r + 1, n + 1))[::-1]
|
||||
yield tuple(pool[i] for i in indices[:r])
|
||||
while n:
|
||||
for i in reversed(range(r)):
|
||||
cycles[i] -= 1
|
||||
if cycles[i] == 0:
|
||||
indices[i:] = indices[i + 1:] + indices[i:i + 1]
|
||||
cycles[i] = n - i
|
||||
else:
|
||||
j = cycles[i]
|
||||
indices[i], indices[-j] = indices[-j], indices[i]
|
||||
yield tuple(pool[i] for i in indices[:r])
|
||||
break
|
||||
else:
|
||||
return
|
||||
|
||||
# From http://code.activestate.com/recipes/576647/
|
||||
def n_queens(queen_count):
|
||||
"""N-Queens solver.
|
||||
Args: queen_count: the number of queens to solve for, same as board size.
|
||||
Yields: Solutions to the problem, each yielded value is a N-tuple.
|
||||
"""
|
||||
cols = range(queen_count)
|
||||
for vec in permutations(cols):
|
||||
if (queen_count == len(set(vec[i] + i for i in cols))
|
||||
== len(set(vec[i] - i for i in cols))):
|
||||
yield vec
|
||||
|
||||
###########################################################################
|
||||
# Benchmark interface
|
||||
|
||||
bm_params = {
|
||||
(50, 25): (1, 5),
|
||||
(100, 25): (1, 6),
|
||||
(1000, 100): (1, 7),
|
||||
(5000, 100): (1, 8),
|
||||
}
|
||||
|
||||
def bm_setup(params):
|
||||
res = None
|
||||
def run():
|
||||
nonlocal res
|
||||
for _ in range(params[0]):
|
||||
res = len(list(n_queens(params[1])))
|
||||
def result():
|
||||
return params[0] * 10 ** (params[1] - 3), res
|
||||
return run, result
|
||||
|
|
@ -0,0 +1,62 @@
|
|||
# Source: https://github.com/python/pyperformance
|
||||
# License: MIT
|
||||
|
||||
# Calculating some of the digits of π.
|
||||
# This benchmark stresses big integer arithmetic.
|
||||
# Adapted from code on: http://benchmarksgame.alioth.debian.org/
|
||||
|
||||
|
||||
def compose(a, b):
|
||||
aq, ar, as_, at = a
|
||||
bq, br, bs, bt = b
|
||||
return (aq * bq,
|
||||
aq * br + ar * bt,
|
||||
as_ * bq + at * bs,
|
||||
as_ * br + at * bt)
|
||||
|
||||
|
||||
def extract(z, j):
|
||||
q, r, s, t = z
|
||||
return (q * j + r) // (s * j + t)
|
||||
|
||||
|
||||
def gen_pi_digits(n):
|
||||
z = (1, 0, 0, 1)
|
||||
k = 1
|
||||
digs = []
|
||||
for _ in range(n):
|
||||
y = extract(z, 3)
|
||||
while y != extract(z, 4):
|
||||
z = compose(z, (k, 4 * k + 2, 0, 2 * k + 1))
|
||||
k += 1
|
||||
y = extract(z, 3)
|
||||
z = compose((10, -10 * y, 0, 1), z)
|
||||
digs.append(y)
|
||||
return digs
|
||||
|
||||
|
||||
###########################################################################
|
||||
# Benchmark interface
|
||||
|
||||
bm_params = {
|
||||
(50, 25): (1, 35),
|
||||
(100, 100): (1, 65),
|
||||
(1000, 1000): (2, 250),
|
||||
(5000, 1000): (3, 350),
|
||||
}
|
||||
|
||||
def bm_setup(params):
|
||||
state = None
|
||||
|
||||
def run():
|
||||
nonlocal state
|
||||
nloop, ndig = params
|
||||
ndig = params[1]
|
||||
for _ in range(nloop):
|
||||
state = None # free previous result
|
||||
state = gen_pi_digits(ndig)
|
||||
|
||||
def result():
|
||||
return params[0] * params[1], ''.join(str(d) for d in state)
|
||||
|
||||
return run, result
|
||||
Loading…
Reference in New Issue