From 127714c3af73633ba723dad2cf7267131e7ac6c2 Mon Sep 17 00:00:00 2001 From: Damien George Date: Wed, 26 Jun 2019 14:24:13 +1000 Subject: [PATCH] tests/perf_bench: Add some benchmarks from python-performance. From https://github.com/python/pyperformance commit 6690642ddeda46fc5ee6e97c3ef4b2f292348ab8 --- tests/perf_bench/bm_chaos.py | 274 ++++++++++++++ tests/perf_bench/bm_fannkuch.py | 67 ++++ tests/perf_bench/bm_float.py | 70 ++++ tests/perf_bench/bm_hexiom.py | 647 ++++++++++++++++++++++++++++++++ tests/perf_bench/bm_nqueens.py | 62 +++ tests/perf_bench/bm_pidigits.py | 62 +++ 6 files changed, 1182 insertions(+) create mode 100644 tests/perf_bench/bm_chaos.py create mode 100644 tests/perf_bench/bm_fannkuch.py create mode 100644 tests/perf_bench/bm_float.py create mode 100644 tests/perf_bench/bm_hexiom.py create mode 100644 tests/perf_bench/bm_nqueens.py create mode 100644 tests/perf_bench/bm_pidigits.py diff --git a/tests/perf_bench/bm_chaos.py b/tests/perf_bench/bm_chaos.py new file mode 100644 index 0000000000..04e04531ca --- /dev/null +++ b/tests/perf_bench/bm_chaos.py @@ -0,0 +1,274 @@ +# Source: https://github.com/python/pyperformance +# License: MIT + +# create chaosgame-like fractals +# Copyright (C) 2005 Carl Friedrich Bolz + +import math +import random + + +class GVector(object): + + def __init__(self, x=0, y=0, z=0): + self.x = x + self.y = y + self.z = z + + def Mag(self): + return math.sqrt(self.x ** 2 + self.y ** 2 + self.z ** 2) + + def dist(self, other): + return math.sqrt((self.x - other.x) ** 2 + + (self.y - other.y) ** 2 + + (self.z - other.z) ** 2) + + def __add__(self, other): + if not isinstance(other, GVector): + raise ValueError("Can't add GVector to " + str(type(other))) + v = GVector(self.x + other.x, self.y + other.y, self.z + other.z) + return v + + def __sub__(self, other): + return self + other * -1 + + def __mul__(self, other): + v = GVector(self.x * other, self.y * other, self.z * other) + return v + __rmul__ = __mul__ + + def linear_combination(self, other, l1, l2=None): + if l2 is None: + l2 = 1 - l1 + v = GVector(self.x * l1 + other.x * l2, + self.y * l1 + other.y * l2, + self.z * l1 + other.z * l2) + return v + + def __str__(self): + return "<%f, %f, %f>" % (self.x, self.y, self.z) + + def __repr__(self): + return "GVector(%f, %f, %f)" % (self.x, self.y, self.z) + + +class Spline(object): + """Class for representing B-Splines and NURBS of arbitrary degree""" + + def __init__(self, points, degree, knots): + """Creates a Spline. + + points is a list of GVector, degree is the degree of the Spline. + """ + if len(points) > len(knots) - degree + 1: + raise ValueError("too many control points") + elif len(points) < len(knots) - degree + 1: + raise ValueError("not enough control points") + last = knots[0] + for cur in knots[1:]: + if cur < last: + raise ValueError("knots not strictly increasing") + last = cur + self.knots = knots + self.points = points + self.degree = degree + + def GetDomain(self): + """Returns the domain of the B-Spline""" + return (self.knots[self.degree - 1], + self.knots[len(self.knots) - self.degree]) + + def __call__(self, u): + """Calculates a point of the B-Spline using de Boors Algorithm""" + dom = self.GetDomain() + if u < dom[0] or u > dom[1]: + raise ValueError("Function value not in domain") + if u == dom[0]: + return self.points[0] + if u == dom[1]: + return self.points[-1] + I = self.GetIndex(u) + d = [self.points[I - self.degree + 1 + ii] + for ii in range(self.degree + 1)] + U = self.knots + for ik in range(1, self.degree + 1): + for ii in range(I - self.degree + ik + 1, I + 2): + ua = U[ii + self.degree - ik] + ub = U[ii - 1] + co1 = (ua - u) / (ua - ub) + co2 = (u - ub) / (ua - ub) + index = ii - I + self.degree - ik - 1 + d[index] = d[index].linear_combination(d[index + 1], co1, co2) + return d[0] + + def GetIndex(self, u): + dom = self.GetDomain() + for ii in range(self.degree - 1, len(self.knots) - self.degree): + if u >= self.knots[ii] and u < self.knots[ii + 1]: + I = ii + break + else: + I = dom[1] - 1 + return I + + def __len__(self): + return len(self.points) + + def __repr__(self): + return "Spline(%r, %r, %r)" % (self.points, self.degree, self.knots) + + +def write_ppm(im, w, h, filename): + with open(filename, "wb") as f: + f.write(b'P6\n%i %i\n255\n' % (w, h)) + for j in range(h): + for i in range(w): + val = im[j * w + i] + c = val * 255 + f.write(b'%c%c%c' % (c, c, c)) + + +class Chaosgame(object): + + def __init__(self, splines, thickness, subdivs): + self.splines = splines + self.thickness = thickness + self.minx = min([p.x for spl in splines for p in spl.points]) + self.miny = min([p.y for spl in splines for p in spl.points]) + self.maxx = max([p.x for spl in splines for p in spl.points]) + self.maxy = max([p.y for spl in splines for p in spl.points]) + self.height = self.maxy - self.miny + self.width = self.maxx - self.minx + self.num_trafos = [] + maxlength = thickness * self.width / self.height + for spl in splines: + length = 0 + curr = spl(0) + for i in range(1, subdivs + 1): + last = curr + t = 1 / subdivs * i + curr = spl(t) + length += curr.dist(last) + self.num_trafos.append(max(1, int(length / maxlength * 1.5))) + self.num_total = sum(self.num_trafos) + + def get_random_trafo(self): + r = random.randrange(int(self.num_total) + 1) + l = 0 + for i in range(len(self.num_trafos)): + if r >= l and r < l + self.num_trafos[i]: + return i, random.randrange(self.num_trafos[i]) + l += self.num_trafos[i] + return len(self.num_trafos) - 1, random.randrange(self.num_trafos[-1]) + + def transform_point(self, point, trafo=None): + x = (point.x - self.minx) / self.width + y = (point.y - self.miny) / self.height + if trafo is None: + trafo = self.get_random_trafo() + start, end = self.splines[trafo[0]].GetDomain() + length = end - start + seg_length = length / self.num_trafos[trafo[0]] + t = start + seg_length * trafo[1] + seg_length * x + basepoint = self.splines[trafo[0]](t) + if t + 1 / 50000 > end: + neighbour = self.splines[trafo[0]](t - 1 / 50000) + derivative = neighbour - basepoint + else: + neighbour = self.splines[trafo[0]](t + 1 / 50000) + derivative = basepoint - neighbour + if derivative.Mag() != 0: + basepoint.x += derivative.y / derivative.Mag() * (y - 0.5) * \ + self.thickness + basepoint.y += -derivative.x / derivative.Mag() * (y - 0.5) * \ + self.thickness + else: + # can happen, especially with single precision float + pass + self.truncate(basepoint) + return basepoint + + def truncate(self, point): + if point.x >= self.maxx: + point.x = self.maxx + if point.y >= self.maxy: + point.y = self.maxy + if point.x < self.minx: + point.x = self.minx + if point.y < self.miny: + point.y = self.miny + + def create_image_chaos(self, w, h, iterations, rng_seed): + # Always use the same sequence of random numbers + # to get reproductible benchmark + random.seed(rng_seed) + + im = bytearray(w * h) + point = GVector((self.maxx + self.minx) / 2, + (self.maxy + self.miny) / 2, 0) + for _ in range(iterations): + point = self.transform_point(point) + x = (point.x - self.minx) / self.width * w + y = (point.y - self.miny) / self.height * h + x = int(x) + y = int(y) + if x == w: + x -= 1 + if y == h: + y -= 1 + im[(h - y - 1) * w + x] = 1 + + return im + + +########################################################################### +# Benchmark interface + +bm_params = { + (100, 50): (0.25, 100, 50, 50, 50, 1234), + (1000, 1000): (0.25, 200, 400, 400, 1000, 1234), + (5000, 1000): (0.25, 400, 500, 500, 7000, 1234), +} + +def bm_setup(params): + splines = [ + Spline([ + GVector(1.597, 3.304, 0.0), + GVector(1.576, 4.123, 0.0), + GVector(1.313, 5.288, 0.0), + GVector(1.619, 5.330, 0.0), + GVector(2.890, 5.503, 0.0), + GVector(2.373, 4.382, 0.0), + GVector(1.662, 4.360, 0.0)], + 3, [0, 0, 0, 1, 1, 1, 2, 2, 2]), + Spline([ + GVector(2.805, 4.017, 0.0), + GVector(2.551, 3.525, 0.0), + GVector(1.979, 2.620, 0.0), + GVector(1.979, 2.620, 0.0)], + 3, [0, 0, 0, 1, 1, 1]), + Spline([ + GVector(2.002, 4.011, 0.0), + GVector(2.335, 3.313, 0.0), + GVector(2.367, 3.233, 0.0), + GVector(2.367, 3.233, 0.0)], + 3, [0, 0, 0, 1, 1, 1]) + ] + + chaos = Chaosgame(splines, params[0], params[1]) + image = None + + def run(): + nonlocal image + _, _, width, height, iter, rng_seed = params + image = chaos.create_image_chaos(width, height, iter, rng_seed) + + def result(): + norm = params[4] + # Images are not the same when floating point behaviour is different, + # so return percentage of pixels that are set (rounded to int). + #write_ppm(image, params[2], params[3], 'out-.ppm') + pix = int(100 * sum(image) / len(image)) + return norm, pix + + return run, result diff --git a/tests/perf_bench/bm_fannkuch.py b/tests/perf_bench/bm_fannkuch.py new file mode 100644 index 0000000000..c9782e3e9a --- /dev/null +++ b/tests/perf_bench/bm_fannkuch.py @@ -0,0 +1,67 @@ +# Source: https://github.com/python/pyperformance +# License: MIT + +# The Computer Language Benchmarks Game +# http://benchmarksgame.alioth.debian.org/ +# Contributed by Sokolov Yura, modified by Tupteq. + +def fannkuch(n): + count = list(range(1, n + 1)) + max_flips = 0 + m = n - 1 + r = n + check = 0 + perm1 = list(range(n)) + perm = list(range(n)) + perm1_ins = perm1.insert + perm1_pop = perm1.pop + + while 1: + if check < 30: + check += 1 + + while r != 1: + count[r - 1] = r + r -= 1 + + if perm1[0] != 0 and perm1[m] != m: + perm = perm1[:] + flips_count = 0 + k = perm[0] + while k: + perm[:k + 1] = perm[k::-1] + flips_count += 1 + k = perm[0] + + if flips_count > max_flips: + max_flips = flips_count + + while r != n: + perm1_ins(r, perm1_pop(0)) + count[r] -= 1 + if count[r] > 0: + break + r += 1 + else: + return max_flips + + +########################################################################### +# Benchmark interface + +bm_params = { + (50, 10): (5,), + (100, 10): (6,), + (500, 10): (7,), + (1000, 10): (8,), + (5000, 10): (9,), +} + +def bm_setup(params): + state = None + def run(): + nonlocal state + state = fannkuch(params[0]) + def result(): + return params[0], state + return run, result diff --git a/tests/perf_bench/bm_float.py b/tests/perf_bench/bm_float.py new file mode 100644 index 0000000000..5a66b9bb3e --- /dev/null +++ b/tests/perf_bench/bm_float.py @@ -0,0 +1,70 @@ +# Source: https://github.com/python/pyperformance +# License: MIT + +# Artificial, floating point-heavy benchmark originally used by Factor. + +from math import sin, cos, sqrt + + +class Point(object): + __slots__ = ('x', 'y', 'z') + + def __init__(self, i): + self.x = x = sin(i) + self.y = cos(i) * 3 + self.z = (x * x) / 2 + + def __repr__(self): + return "" % (self.x, self.y, self.z) + + def normalize(self): + x = self.x + y = self.y + z = self.z + norm = sqrt(x * x + y * y + z * z) + self.x /= norm + self.y /= norm + self.z /= norm + + def maximize(self, other): + self.x = self.x if self.x > other.x else other.x + self.y = self.y if self.y > other.y else other.y + self.z = self.z if self.z > other.z else other.z + return self + + +def maximize(points): + next = points[0] + for p in points[1:]: + next = next.maximize(p) + return next + + +def benchmark(n): + points = [None] * n + for i in range(n): + points[i] = Point(i) + for p in points: + p.normalize() + return maximize(points) + + +########################################################################### +# Benchmark interface + +bm_params = { + (50, 25): (1, 150), + (100, 100): (1, 250), + (1000, 1000): (10, 1500), + (5000, 1000): (20, 3000), +} + +def bm_setup(params): + state = None + def run(): + nonlocal state + for _ in range(params[0]): + state = benchmark(params[1]) + def result(): + return params[0] * params[1], 'Point(%.4f, %.4f, %.4f)' % (state.x, state.y, state.z) + return run, result diff --git a/tests/perf_bench/bm_hexiom.py b/tests/perf_bench/bm_hexiom.py new file mode 100644 index 0000000000..3a6f1f6c4b --- /dev/null +++ b/tests/perf_bench/bm_hexiom.py @@ -0,0 +1,647 @@ +# Source: https://github.com/python/pyperformance +# License: MIT + +# Solver of Hexiom board game. +# Benchmark from Laurent Vaucher. +# Source: https://github.com/slowfrog/hexiom : hexiom2.py, level36.txt +# (Main function tweaked by Armin Rigo.) + + +################################## +class Dir(object): + + def __init__(self, x, y): + self.x = x + self.y = y + + +DIRS = [Dir(1, 0), + Dir(-1, 0), + Dir(0, 1), + Dir(0, -1), + Dir(1, 1), + Dir(-1, -1)] + +EMPTY = 7 + +################################## + + +class Done(object): + MIN_CHOICE_STRATEGY = 0 + MAX_CHOICE_STRATEGY = 1 + HIGHEST_VALUE_STRATEGY = 2 + FIRST_STRATEGY = 3 + MAX_NEIGHBORS_STRATEGY = 4 + MIN_NEIGHBORS_STRATEGY = 5 + + def __init__(self, count, empty=False): + self.count = count + self.cells = None if empty else [ + [0, 1, 2, 3, 4, 5, 6, EMPTY] for i in range(count)] + + def clone(self): + ret = Done(self.count, True) + ret.cells = [self.cells[i][:] for i in range(self.count)] + return ret + + def __getitem__(self, i): + return self.cells[i] + + def set_done(self, i, v): + self.cells[i] = [v] + + def already_done(self, i): + return len(self.cells[i]) == 1 + + def remove(self, i, v): + if v in self.cells[i]: + self.cells[i].remove(v) + return True + else: + return False + + def remove_all(self, v): + for i in range(self.count): + self.remove(i, v) + + 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 diff --git a/tests/perf_bench/bm_nqueens.py b/tests/perf_bench/bm_nqueens.py new file mode 100644 index 0000000000..87e7245c04 --- /dev/null +++ b/tests/perf_bench/bm_nqueens.py @@ -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 diff --git a/tests/perf_bench/bm_pidigits.py b/tests/perf_bench/bm_pidigits.py new file mode 100644 index 0000000000..ca2e5297d0 --- /dev/null +++ b/tests/perf_bench/bm_pidigits.py @@ -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