class TwoPhaseModel:
    def __init__(self, MI, NI, granulometry, matrixLabel):

        self.MI = MI
        self.NI = NI
        self.granulometry = granulometry
        self.matrixLabel = matrixLabel

        xv = np.linspace(0, self.MI - 1, self.MI,
                         endpoint=True).astype(np.int32)
        yv = np.linspace(0, self.NI - 1, self.NI,
                         endpoint=True).astype(np.int32)
        X, Y = np.int32(np.meshgrid(xv, yv))

        self.coords = {(x, y) for x, y in zip(X.ravel(), Y.ravel())}

        depth = 4
        self.qtree = Quadtree(int(depth), Rect(0, 0, int(self.MI),
                                               int(self.NI)))
        (self.XX, self.YY) = np.meshgrid(range(0, self.NI), range(0, self.MI))

    def compute(self):

        Objs = []
        Image = np.ones((self.MI, self.NI), np.int32) * self.matrixLabel
        Image = Image.astype(np.int32)

        start = time.time()

        for ix, value in enumerate(
                zip(self.granulometry.a_reversed,
                    self.granulometry.c_reversed)):
            print(ix, value[0], value[1])
            area_set = 0
            while area_set < value[1]:

                cy, cx = self.coords.pop()
                #if Image[cy,cx] == self.matrixLabel:
                if True:

                    b = self.granulometry.getB(value[0])
                    theta = random.uniform(0, np.pi)

                    c = Ellipse(cy, cx, int(value[0]), int(b), theta)
                    objs = self.qtree.query(c)
                    if len(objs) == 0:
                        self.qtree.insert(c)
                        Objs.append(c)
                        area_set += c.area()

                        #ellipseMatrix(c.y(), c.x(), c.a(), c.b(), c.theta(), Image, int(self.granulometry.Label), self.XX, self.YY)
                        #ellipseDiscard(c.y(), c.x(), c.a(), c.b(), c.theta(), self.XX, self.YY, self.coords, Image, self.granulometry.Label)

                    else:
                        self.coords.add((cy, cx))

        print(time.time() - start)

        return Objs, int(self.granulometry.Label), self.XX, self.YY, Image
Exemple #2
0
def main():
    pygame.init()
    screen = pygame.display.set_mode((width, height))
    map = pygame.Surface((map_width, map_height))
    pygame.display.set_caption("quadtree")
    font = pygame.font.SysFont('arial', 20)

    clock = pygame.time.Clock()

    particles = Group([
        Particle(
            random.gauss(map_width / 2, 150) % map_width,
            random.gauss(map_height / 2, 150) % map_height, 4, map)
        for _ in range(1000)
    ])

    qtree = Quadtree(map.get_rect(), 4, map)
    for p in particles:
        qtree.insert(p)

    while True:
        clock.tick(60)
        fps_text = font.render(f'fps:{int(clock.get_fps())}', True,
                               THECOLORS['white'])
        fps_rect = fps_text.get_rect()

        for event in pygame.event.get():
            if event.type == pygame.QUIT:
                exit()

        qtree = Quadtree(map.get_rect(), 4, map)
        for p in particles:
            qtree.insert(p)

        particles.update()

        for p in particles:
            p.highlight = False
            query_rect = Rect(p.rect.x, p.rect.y, p.radius * 2, p.radius * 2)
            if len(qtree.query(query_rect)) != 1:
                p.highlight = True

        map.fill(THECOLORS['black'])
        particles.draw(map)

        pygame.transform.scale(map, (width, height), screen)

        screen.blit(fps_text, fps_rect)

        pygame.display.update()
Exemple #3
0
def update_boids():

    tree = Quadtree(b[0], 0, 0, WIDTH, HEIGHT)
    for i in range(1, len(b)):
        tree.insert(b[i])

    for boid in b:
        accel = [0, 0]
        possible_close_boids = tree.findInCircle(boid.pos[0], boid.pos[1], NEIGHBORHOOD_THRESHOLD)
        if len(possible_close_boids) > 1:
            accel = boid.compute_acceleration(possible_close_boids, SEPARATION_THRESHOLD, C, A, S)
        if Quadtree.pointInCircle(tree, boid.pos[0], boid.pos[1], mouse[0], mouse[1], NEIGHBORHOOD_THRESHOLD):
            accel = list(map(sum, zip(accel, boid.avoid(mouse))))
        boid.update(WIDTH, HEIGHT, accel)
Exemple #4
0
from quadtree import Quadtree
import numpy as np
import time

np.random.seed(5)

p = Quadtree(0, 0, 100, 100, 5)

N = 5000000
data = 100 * np.random.random(size=(N, 2))
data = data.astype(np.float32)

start = time.time()
p.insert(data)
print(time.time() - start)

start = time.time()
r = .1
d = p.select_from(data, r)
print(time.time() - start)

print(d[0])
print()
Exemple #5
0
from quadtree import Point, Rectangle, Quadtree

DPI = 72
np.random.seed(60)

width, height = 600, 400

N = 500
coords = np.random.randn(N, 2) * height / 3 + (width / 2, height / 2)
points = [Point(*coord) for coord in coords]
print(len(points))
center = Point(width / 2, height / 2)
domain = Rectangle(center, height, width)
qtree = Quadtree(domain, 3)
for point in points:
    qtree.insert(point)

print('Number of points in the domain =',
      len(qtree))  # it might not be adding all the points for some reason

fig = plt.figure(figsize=(700 / DPI, 500 / DPI), dpi=DPI)
ax = plt.subplot()
ax.set_xlim(0, width)
ax.set_ylim(0, height)
qtree.draw(ax)

ax.scatter([p.x for p in points], [p.y for p in points], s=4)
ax.set_xticks([])
ax.set_yticks([])

domain.draw(ax, color='r', linewidth=5)