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from itertools import combinations
from pygame import Vector2
def detectTopCollision(particle, box):
if particle.top <= box.top:
return True
return False
def detectBottomCollision(particle, box):
if particle.bottom >= box.bottom:
return True
return False
def detectLeftCollision(particle, box):
if particle.left <= box.left:
return True
return False
def detectRightCollision(particle, box):
if particle.right >= box.right:
return True
return False
def handleTopCollision(particle, box):
particle.velocity.y *= -1
particle.position.y = box.top + particle.radius
return True
def handleBottomCollision(particle, box):
particle.velocity.y *= -1
particle.position.y = box.bottom - particle.radius
return True
def handleLeftCollision(particle, box):
particle.velocity.x *= -1
particle.position.x = box.left + particle.radius
return True
def handleRightCollision(particle, box):
particle.velocity.x *= -1
particle.position.x = box.right - particle.radius
return True
def handleBoxCollision(particle, box):
if detectTopCollision(particle, box) or detectBottomCollision(particle, box):
particle.velocity.y *= -1
return True
elif detectLeftCollision(particle, box) or detectRightCollision(particle, box):
particle.velocity.x *= -1
return True
return False
def detectParticleCollision(particle1, particle2):
if particle1.position.distance_to(particle2.position) <= particle1.radius + particle2.radius and \
particle1 != particle2:
return True
return False
def handleParticleCollision(particle1, particle2): # https://www.vobarian.com/collisions/2dcollisions2.pdf
if detectParticleCollision(particle1, particle2):
n = particle2.position - particle1.position
un = n / n.magnitude()
ut = Vector2(-un.y, un.x)
v1 = particle1.velocity
v2 = particle2.velocity
v1n = un.dot(v1)
v1t = ut.dot(v1)
v2n = un.dot(v2)
v2t = ut.dot(v2)
v1t_prime = v1t
v2t_prime = v2t
v1n_prime = (v1n * (particle1.mass - particle2.mass) + 2 * particle2.mass * v2n) / (
particle1.mass + particle2.mass)
v2n_prime = (v2n * (particle2.mass - particle1.mass) + 2 * particle1.mass * v1n) / (
particle1.mass + particle2.mass)
v1_prime = v1n_prime * un + v1t_prime * ut
v2_prime = v2n_prime * un + v2t_prime * ut
particle1.velocity = v1_prime
particle2.velocity = v2_prime
return True
return False
def sweepAndPrune(particle_list): # broad phase collision detection
particles = particle_list.copy()
particles.sort(key=lambda x: x.position.x)
x_checks = []
active = [particles[0]]
for particle in particles:
if particle == active[0]:
continue
start_x = active[-1].position.x - active[-1].radius
end_x = active[-1].position.x + active[-1].radius
if (start_x <= particle.position.x - particle.radius <= end_x or
start_x <= particle.position.x <= end_x or
start_x <= particle.position.x + particle.radius <= end_x):
active.append(particle)
if len(active) > 1:
x_checks.extend(tuple(combinations(active, 2)))
active = [particle]
particles.sort(key=lambda x: x.position.y)
y_checks = []
active = [particles[0]]
for particle in particles:
if particle == active[0]:
continue
start_y = active[-1].position.y - active[-1].radius
end_y = active[-1].position.y + active[-1].radius
if (start_y <= particle.position.y - particle.radius <= end_y or
start_y <= particle.position.y <= end_y or
start_y <= particle.position.y + particle.radius <= end_y):
active.append(particle)
if len(active) > 1:
y_checks.extend(tuple(combinations(active, 2)))
active = [particle]
return remove_duplicates(x_checks, y_checks)
def intersection(arr1, arr2):
return [value for value in arr1 if value in set(arr2)]
def remove_duplicates(arr1, arr2):
return list(set(arr1 + arr2))
def spacePartitioning(particle_list, width, height): # broad phase collision detection
n = 25
grid = [[[] for _ in range(n)] for _ in range(n)]
for particle in particle_list:
x1 = int(particle.left // (width / n))
x2 = int(particle.right // (width / n))
y1 = int(particle.top // (height / n))
y2 = int(particle.bottom // (height / n))
if x1 < 0:
x1 = 0
if x2 < 0:
x2 = 0
if y1 < 0:
y1 = 0
if y2 < 0:
y2 = 0
if x1 >= n:
x1 = n - 1
if x2 >= n:
x2 = n - 1
if y1 >= n:
y1 = n - 1
if y2 >= n:
y2 = n - 1
grid[y1][x1].append(particle)
grid[y1][x2].append(particle)
grid[y2][x1].append(particle)
grid[y2][x2].append(particle)
checks = []
for i in range(n):
for j in range(n):
checks.extend(tuple(combinations(grid[i][j], 2)))
return list(set(checks))
def smarterSpacePartitioning(particle_list): # broad phase collision detection
particles = particle_list.copy()
collisions = KDTree(particles)
# print(collisions.get_collision(), collisions.n1, collisions.n2)
# quit()
return list(set(collisions.get_collision()))
def median(arr):
return arr[len(arr) // 2]
class KDTree:
default_axis = 0
max_depth = 2
def __init__(self, particles, axis=default_axis, depth=0):
self.depth = depth
self.particles = particles
self.axis = axis
if self.axis == 0:
particles.sort(key=lambda x: x.position.y)
else:
particles.sort(key=lambda x: x.position.x)
self.median = median(particles)
self.left, self.right = [], []
if self.axis == 0:
for particle in particles:
if particle.position.x < self.median.position.x:
self.left.append(particle)
else:
self.right.append(particle)
if particle.left < self.median.position.x:
self.left.append(particle)
if particle.right >= self.median.position.x:
self.right.append(particle)
else:
for particle in particles:
if particle.position.y < self.median.position.y:
self.left.append(particle)
else:
self.right.append(particle)
if particle.top < self.median.position.y:
self.left.append(particle)
if particle.bottom >= self.median.position.y:
self.right.append(particle)
self.n1, self.n2 = None, None
self.build()
def getAxis(self):
return not self.axis
def getParticlesLeft(self):
return self.left
def getParticlesRight(self):
return self.right
def build(self):
if self.depth == self.max_depth:
return
if len(self.particles) > 1:
self.n1 = KDTree(self.getParticlesLeft(), axis=self.getAxis(), depth=self.depth + 1)
self.n2 = KDTree(self.getParticlesRight(), axis=self.getAxis(), depth=self.depth + 1)
def get_collision(self):
if len(self.particles) == 1:
return []
if self.n1 is None or self.n2 is None:
return []
return list(combinations(self.particles, 2)) + self.n1.get_collision() + self.n2.get_collision()
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