def __init__(self, width, height, pure_python=False, should_unroll=False):
self.width = width
self.height = height
self.kernel = IteratedConwayKernel(77)
self.kernel.pure_python = pure_python
self.kernel.should_unroll = should_unroll
# kernel.pure_python = True
# create a stencil grid for t+1
self.current_grid = StencilGrid([height, width])
all_neighbors = [(x, y) for x in range(-1, 2) for y in range(-1, 2)]
all_neighbors.remove((0, 0))
self.current_grid.neighbor_definition.append(all_neighbors)
self.future_grid = copy.deepcopy(
self.current_grid
) # this will be swapped to current after each iteration
# Randomly initialize a quarter of the cells to 1
for x in self.current_grid.interior_points():
if np.random.random() > 0.75:
self.current_grid[x] = 1
self.new_state_map = StencilGrid([18])
for index, new_state in enumerate(
[0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0]):
self.new_state_map[index] = new_state
def gaussian(stdev, length):
result = StencilGrid([length])
scale = 1.0 / (stdev * math.sqrt(2.0 * math.pi))
divisor = -1.0 / (2.0 * stdev * stdev)
for x in range(length):
result[x] = scale * math.exp(float(x) * float(x) * divisor)
return result
class GameRunner(object):
def __init__(self, width, height, pure_python=False, should_unroll=False):
self.width = width
self.height = height
self.kernel = IteratedConwayKernel(77)
self.kernel.pure_python = pure_python
self.kernel.should_unroll = should_unroll
# kernel.pure_python = True
# create a stencil grid for t+1
self.current_grid = StencilGrid([height, width])
all_neighbors = [(x, y) for x in range(-1, 2) for y in range(-1, 2)]
all_neighbors.remove((0, 0))
self.current_grid.neighbor_definition.append(all_neighbors)
self.future_grid = copy.deepcopy(self.current_grid) # this will be swapped to current after each iteration
# Randomly initialize a quarter of the cells to 1
for x in self.current_grid.interior_points():
if np.random.random() > 0.75:
self.current_grid[x] = 1
self.new_state_map = StencilGrid([18])
for index, new_state in enumerate([0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0]):
self.new_state_map[index] = new_state
def set_pure_python(self, new_mode):
self.kernel.pure_python = new_mode
def run_game(self, generations=1):
for generation in range(generations):
self.kernel.kernel(self.current_grid, self.new_state_map, self.future_grid)
self.current_grid, self.future_grid = self.future_grid, self.current_grid
print("gen %s" % generation)
def __call__(self, *args, **kwargs):
self.run_game()
def run(self):
self.run_game()
def render(self):
GameRunner.render_grid(self.current_grid)
@staticmethod
def render_grid(sk, msg="---"):
"""
Simplistic render of a life board
"""
print(msg)
for h in range(sk.shape[0]):
for w in range(sk.shape[1]):
if sk[h][w] > 0:
print('*', end='')
else:
print(' ', end='')
print('')
def __init__(self, width, height, pure_python=False, should_unroll=False):
self.width = width
self.height = height
self.kernel = IteratedConwayKernel(77)
self.kernel.pure_python = pure_python
self.kernel.should_unroll = should_unroll
# kernel.pure_python = True
# create a stencil grid for t+1
self.current_grid = StencilGrid([height, width])
all_neighbors = [(x, y) for x in range(-1, 2) for y in range(-1, 2)]
all_neighbors.remove((0, 0))
self.current_grid.neighbor_definition.append(all_neighbors)
self.future_grid = copy.deepcopy(self.current_grid) # this will be swapped to current after each iteration
# Randomly initialize a quarter of the cells to 1
for x in self.current_grid.interior_points():
if np.random.random() > 0.75:
self.current_grid[x] = 1
self.new_state_map = StencilGrid([18])
for index, new_state in enumerate([0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0]):
self.new_state_map[index] = new_state
time_steps = 500
class Kernel(StencilKernel):
def kernel(self, in_img, out_img):
for x in out_img.interior_points():
out_img[x] = in_img[x]
for y in in_img.neighbors(x, 0):
out_img[x] += 0.125 * in_img[y]
for z in in_img.neighbors(x, 1):
out_img[x] -= 0.125 * 2.0 * in_img[z]
kernel = Kernel()
kernel.should_unroll = False
out_grid = StencilGrid([time_steps, width, height])
out_grid.ghost_depth = 1
in_grid = StencilGrid([time_steps, width, height])
in_grid.ghost_depth = 1
base = 1024
r = random.seed()
for i in range(width):
for j in range(height):
in_grid.data[(0, i, j)] = random.randrange(1024) * 1.0
in_grid.neighbor_definition[0] = [(-1, 1, 0), (-1, -1, 0), (-1, 0, 1),
(-1, 0, -1)]
in_grid.neighbor_definition[1] = [(-1, 0, 0), (-1, 0, 0)]
height = 1600
time_steps = 500
class Kernel(StencilKernel):
def kernel(self, in_img, out_img):
for x in out_img.interior_points():
out_img[x] = in_img[x]
for y in in_img.neighbors(x, 0):
out_img[x] += 0.125 * in_img[y]
for z in in_img.neighbors(x, 1):
out_img[x] -= 0.125 * 2.0 * in_img[z]
kernel = Kernel()
kernel.should_unroll = False
out_grid = StencilGrid([time_steps, width, height])
out_grid.ghost_depth = 1
in_grid = StencilGrid([time_steps, width, height])
in_grid.ghost_depth = 1
base = 1024
r = random.seed()
for i in range(width):
for j in range(height):
in_grid.data[(0, i, j)] = random.randrange(1024) * 1.0
in_grid.neighbor_definition[0] = [(-1, 1, 0), (-1, -1, 0),
(-1, 0, 1), (-1, 0, -1)]
in_grid.neighbor_definition[1] = [(-1, 0, 0), (-1, 0, 0)]
alpha = 0.5
beta = 1.0
class LaplacianKernel(StencilKernel):
def __init__(self, alpha, beta):
super(LaplacianKernel, self).__init__()
self.constants = {'alpha': alpha, 'beta': beta}
def kernel(self, in_grid, out_grid):
for x in in_grid.interior_points():
out_grid[x] = alpha * in_grid[x]
for y in in_grid.neighbors(x, 1):
out_grid[x] += beta * in_grid[y]
nx = int(sys.argv[1])
ny = int(sys.argv[2])
nz = int(sys.argv[3])
input_grid = StencilGrid([nx, ny, nz])
output_grid = StencilGrid([nx, ny, nz])
for x in input_grid.interior_points():
input_grid[x] = random.randint(nx * ny * nz)
laplacian = LaplacianKernel(alpha, beta)
for i in range(50):
for x in input_grid.interior_points():
input_grid[x] = random.randint(nx * ny * nz)
laplacian.kernel(input_grid, output_grid)
result[x] = scale * math.exp(float(x) * float(x) * divisor)
return result
def distance(x, y):
return math.sqrt(sum([(x[i] - y[i])**2 for i in range(0, len(x))]))
pixels = map(ord,
list(image_in.read(width * height))) # Read in grayscale values
# pixels = image_in.read(width * height) # Read in grayscale values
# intensity = float(sum(pixels))/len(pixels)
kernel = Kernel()
kernel.should_unroll = False
out_grid = StencilGrid([width, height])
out_grid.ghost_depth = radius
in_grid = StencilGrid([width, height])
in_grid.ghost_depth = radius
for x in range(-radius, radius + 1):
for y in range(-radius, radius + 1):
in_grid.neighbor_definition[1].append((x, y))
for x in range(0, width):
for y in range(0, height):
in_grid.data[(x, y)] = pixels[y * width + x]
gaussian1 = gaussian(stdev_d, radius * 2)
gaussian2 = gaussian(stdev_s, 256)
class GameRunner(object):
def __init__(self, width, height, pure_python=False, should_unroll=False):
self.width = width
self.height = height
self.kernel = IteratedConwayKernel(77)
self.kernel.pure_python = pure_python
self.kernel.should_unroll = should_unroll
# kernel.pure_python = True
# create a stencil grid for t+1
self.current_grid = StencilGrid([height, width])
all_neighbors = [(x, y) for x in range(-1, 2) for y in range(-1, 2)]
all_neighbors.remove((0, 0))
self.current_grid.neighbor_definition.append(all_neighbors)
self.future_grid = copy.deepcopy(
self.current_grid
) # this will be swapped to current after each iteration
# Randomly initialize a quarter of the cells to 1
for x in self.current_grid.interior_points():
if np.random.random() > 0.75:
self.current_grid[x] = 1
self.new_state_map = StencilGrid([18])
for index, new_state in enumerate(
[0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0]):
self.new_state_map[index] = new_state
def set_pure_python(self, new_mode):
self.kernel.pure_python = new_mode
def run_game(self, generations=1):
for generation in range(generations):
self.kernel.kernel(self.current_grid, self.new_state_map,
self.future_grid)
self.current_grid, self.future_grid = self.future_grid, self.current_grid
print("gen %s" % generation)
def __call__(self, *args, **kwargs):
self.run_game()
def run(self):
self.run_game()
def render(self):
GameRunner.render_grid(self.current_grid)
@staticmethod
def render_grid(sk, msg="---"):
"""
Simplistic render of a life board
"""
print(msg)
for h in range(sk.shape[0]):
for w in range(sk.shape[1]):
if sk[h][w] > 0:
print('*', end='')
else:
print(' ', end='')
print('')
divisor = -1.0 / (2.0 * stdev * stdev)
for x in range(length):
result[x] = scale * math.exp(float(x) * float(x) * divisor)
return result
def distance(x, y):
return math.sqrt(sum([(x[i]-y[i])**2 for i in range(0, len(x))]))
pixels = map(ord, list(image_in.read(width * height))) # Read in grayscale values
# pixels = image_in.read(width * height) # Read in grayscale values
# intensity = float(sum(pixels))/len(pixels)
kernel = Kernel()
kernel.should_unroll = False
out_grid = StencilGrid([width, height])
out_grid.ghost_depth = radius
in_grid = StencilGrid([width, height])
in_grid.ghost_depth = radius
for x in range(-radius, radius+1):
for y in range(-radius, radius+1):
in_grid.neighbor_definition[1].append((x, y))
for x in range(0, width):
for y in range(0, height):
in_grid.data[(x, y)] = pixels[y * width + x]
gaussian1 = gaussian(stdev_d, radius*2)
gaussian2 = gaussian(stdev_s, 256)
