def __init__(self):
self.ants = []
self.food = Circle(19, 18, 0.2)
self.home = Circle(10, 10, 0.2)
self.home_trail = QuadTree(AREA, capacity=QUADTREE_CAPACITY)
self.food_trail = QuadTree(AREA, capacity=QUADTREE_CAPACITY)
self.iteration = -1
def _build_dynamic_location_index(self):
"""
Initialize a quadtree index and insert
all the stored locations
"""
sys.stdout.write("Generating QuadTree location index...\n ")
sys.stdout.flush()
location_index = QuadTree(self.bounding_box)
# iterate through all trips
for trip in self.all_trips:
#Iterate through all locations
current_cell = None
#Loop for adding trajectory information
for location in trip.locations:
current_cell = location_index.insert(location)
location_index.traverse() #Populate leaves[]
_node_id = 0
#Store a reference to all the quadtree LEAF cells
for cell in location_index.leaves:
location = cell._center_of_mass()
cell.id = (location.latitude, location.longitude)
self.all_nodes[(location.latitude, location.longitude)] = cell
sys.stdout.write("Done...\n ")
sys.stdout.flush()
return location_index
def extend(self, item_list):
""" Add the given items to the world.
@param item_list: [ ... polygon ... ]
"""
assert isinstance(item_list, (type(()), type([])))
# Identify the bounds of the new list
l = min(item.left for item in item_list)
t = max(item.top for item in item_list)
r = max(item.right for item in item_list)
b = min(item.bottom for item in item_list)
bounding_box = BBox(l, t, r, b)
if self.item_list:
self.item_list.extend(item_list)
else:
self.item_list = item_list
# Compare with index
if self.index is None:
self.index = QuadTree(self.item_list)
else:
# Check that new items are inside the existing index
i_l, i_t, i_r, i_b = self.index.box_as_tuple
if l >= i_l and t <= i_t and r <= i_r and b >= i_b:
self.index.extend(item_list)
else:
# Rebuild to allow for extra space
self.index = QuadTree(self.item_list)
class World:
def __init__(self, rect):
self.objects = []
self.objects.append(Player())
for i in range(100):
self.objects.append(Hunter())
self.qtree = QuadTree(rect, maxDepth=8)
self.qtree.insert(self.objects)
def update(self, delta_time):
for obj in self.objects:
obj.update(delta_time)
update_collisions(self.qtree, self.objects)
def draw(self, canvas):
canvas.set_source_rgb(1, 1, 1)
canvas.paint()
draw_qtree(canvas, self.qtree)
for obj in self.objects:
mtx = canvas.get_matrix()
obj.draw(canvas)
canvas.set_matrix(mtx)
class World:
def __init__(self, rect):
self.objects = []
self.objects.append(Player())
for i in range(100):
self.objects.append(Hunter())
self.qtree = QuadTree(rect, maxDepth=8)
self.qtree.insert(self.objects)
def update(self, delta_time):
for obj in self.objects:
obj.update(delta_time)
update_collisions(self.qtree, self.objects)
def draw(self, canvas):
canvas.set_source_rgb(1, 1, 1)
canvas.paint()
draw_qtree(canvas, self.qtree)
for obj in self.objects:
mtx = canvas.get_matrix()
obj.draw(canvas)
canvas.set_matrix(mtx)
class Level:
def __init__(self, x=0, y=0, w=960, h=540):
self.x = x
self.y = y
self.w = w
self.h = h
self.plans = set()
self.blocks = set()
self.planTree = QuadTree(boundingRect=(x, y, x+w, y+h))
self.quadTree = QuadTree(boundingRect=(x, y, x+w, y+h))
def save(self):
pass
def load(self):
self.startingBalls = 12
self.blocks |= set(Block(Circle(480 - 192 + 384/16*i, 250 + i%2*24, 16.0)) for i in range(16))
n = 9
r0 = 48.
r1 = 48. + 16.
self.blocks |= set(Block(Arc(300., 128., r0, r1, i*pi/n, pi/n*(i+.9))) for i in range(n))
self.blocks |= set(Block(Arc(480., 80., r0, r1, i*pi/n, pi/n*(i+.9))) for i in range(n))
self.blocks |= set(Block(Arc(660., 128., r0, r1, i*pi/n, pi/n*(i+.9))) for i in range(n))
self.blocks |= set(Block(Capsule(32.+48.*i, 360., 48.+48.*i, 360., 8.)) for i in range(12))
self.blocks |= set(Block(Rectangle(32.+48.*i, 400., 24., 16.)) for i in range(13))
for block in self.blocks:
self.quadTree.insert(block)
def _clear_all(self):
self.find_points = []
self.find_frm = None
self.find_to = None
self.kd_find_result = None
self.kd_find_steps = []
self.find_step_no = 0
self.find_stage = NO_FIND
self.q_find_steps = []
self.q_find_result = []
self._q_found_points = []
self._q_graph = nx.DiGraph()
self._kd_graph = nx.DiGraph()
self._qt = QuadTree((0, 0), (X_SIZE, Y_SIZE),
lambda x: self.add_q_node(x),
lambda x, y: self.connect_q_node(x, y))
self._kdt = KDTree(
(0, 0), (X_SIZE, Y_SIZE),
lambda x: self.add_kd_node(x),
lambda x, y: self.connect_kd_node(x, y),
lambda x, y, z=(False, True): self.highlight_kd_nodes(x, y, z))
self._refresh_graphs()
def __check_collisions(self):
"""Update proximity sensors and detect collisions between objects"""
collisions = []
checked_robots = []
if self.__qtree is None:
self.__qtree = QuadTree(self.__obstacles)
if len(self.__robots) > 1:
rqtree = QuadTree(self.__robots)
else:
rqtree = None
# check each robot
for robot in self.__robots:
# update proximity sensors
for sensor in robot.get_external_sensors():
sensor.get_world_envelope(True)
rect = Rect(sensor.get_bounding_rect())
sensor.update_distance()
# distance to obstacles
for obstacle in self.__qtree.find_items(rect):
sensor.update_distance(obstacle)
# distance to other robots
if rqtree is None:
continue
for other in rqtree.find_items(rect):
if other is not robot:
sensor.update_distance(other)
rect = Rect(robot.get_bounding_rect())
# against nearest obstacles
for obstacle in self.__qtree.find_items(rect):
if robot.has_collision(obstacle):
collisions.append((robot, obstacle))
# against other robots
if rqtree is not None:
for other in rqtree.find_items(rect):
if other is robot:
continue
if other in checked_robots:
continue
if robot.has_collision(other):
collisions.append((robot, other))
checked_robots.append(robot)
if len(collisions) > 0:
# Test code - print out collisions
for (robot, obstacle) in collisions:
self.log("Collision with {}".format(
obstacle), obj=robot, color=robot.get_color())
# end of test code
return True
return False
def _build_location_index(self):
sys.stdout.write("Generating QuadTree location index... ")
sys.stdout.flush()
location_index = QuadTree(MAX_DEPTH, self.bounding_box)
# iterate through all trips
for trip in self.all_trips:
#Iterate through all locations
current_node = None
#Loop for adding trajectory information
for previous, location, next in self.previous_and_next(trip.locations):
current_node = location_index.insert(location)
# First location
if previous is not None and next is not None:
#get the node where the next location would fall
self.update_trajectory(previous, location, next, current_node)
location_index.traverse() #Populate leaves[]
_node_id = 0
#Hash with all leaves
for leave in location_index.leaves:
location = leave._center_of_mass()
leave.id = (location.latitude, location.longitude)
self.all_nodes[(location.latitude, location.longitude)] = leave
return location_index
def __init__(self, rect):
self.objects = []
self.objects.append(Player())
for i in range(100):
self.objects.append(Hunter())
self.qtree = QuadTree(rect, maxDepth=8)
self.qtree.insert(self.objects)
def remove(self, item):
""" Remove a single item from the world
@param item: PolyGon or similar
"""
self.item_list.remove(item)
# Oops. Rebuilding quadtrees is not that easy...
self.index = QuadTree(self.item_list)
def main():
#Load all files and initilize Simple Tracks
os.chdir("/home/moyano/Projects/CreateTracks/trips/")
all_points = []
for trip in os.listdir("."):
trip_data = load_file(trip)
all_points += trip_data
#tracks.append(Track(trip_data))
boundries = max_bounding_rect(all_points)
# depth = depth(boundries, 0.00035)
#print "Nesting Level: %i" % depth
qtree = QuadTree(10, boundries)
#Make the QTree
for coord in all_points:
qtree.add_point(coord)
qtree.traverse()
nodes = qtree.leaves
#Load Trips
trips = []
for trip in os.listdir("."):
if not trip.startswith('.'):
gps_data = load_file(trip)
trips.append(Trip(gps_data,trip))
routes(trips, qtree)
#Weighted Points
os.chdir("/home/moyano/Projects/CreateTracks/edges")
test_file = open("edges.txt", "w")
test_file.write("latitude, longitude, ocurrences, color")
# print children
for node in nodes:
p = node._center_of_mass()
count = len(node.items)
if count > 2:
test_file.write("\n")
test_file.write(str(p.latitude) + "," + str(p.longitude) + "," + str(count) + "," + get_color(count))
#All points
os.chdir("/home/moyano/Projects/CreateTracks/edges")
test_file = open("edges2.csv", "w")
test_file.write("latitude, longitude")
test_file.write("#")
# print children
xpoints = []
for node in nodes:
p = node._center_of_mass()
count = len(node.items)
if count > 100:
for _ in xrange(count):
xpoints.append((p.latitude, p.longitude))
test_file.write(str(p.latitude) + ", " + str(p.longitude))
test_file.write("#")
class QuadTreeFunctionTest(unittest.TestCase):
def setUp(self) -> None:
self.quadtree = QuadTree(Bounds(0, 0, 400, 400),
max_objects=4,
max_level=5)
def test_points_insert(self):
with open('./tests/example_data.json', 'r') as f:
json_data = json.loads(f.read())
points = json_data['data']
for point in points:
self.quadtree.insert(Point(point['x'], point['y'], point['value']))
def test_retrieve(self):
objects = self.quadtree.retrieve(Bounds(200, 200, 50, 50))
def test_retrieve_intersections(self):
objects = self.quadtree.retrieve_intersections(Bounds(
200, 200, 50, 50))
def test_nearest_neighbors(self):
points = self.quadtree.nearest_neighbors(Point(225, 225), radius=25)
def test_visualization(self):
self.quadtree.visualize()
def tearDown(self) -> None:
self.quadtree.clear()
def __init__(self):
super(GUI, self).__init__('Simple example 1')
self.find_stage = False
self.find_points = []
self.find_frm = None
self.find_to = None
self.kd_find_steps = []
self.kd_find_result = None
self.find_step_no = 0
self.q_find_steps = []
self.q_find_result = []
self._q_found_points = []
self._q_structure = ControlMatplotlib('Quad tree structure')
self._q_plain = ControlMatplotlib('Quad tree plain')
self._kd_structure = ControlMatplotlib('KD tree structure')
self._kd_plain = ControlMatplotlib('KD tree plain')
self._find_button = ControlButton('Find')
self._step_button = ControlButton('Step')
self._clear_button = ControlButton('Clear')
self._find_button.value = self._on_find
self._step_button.value = self._on_step
self._clear_button.value = self._clear_all
self._formset = [
'_find_button', '||', '_step_button', '||', "_clear_button", '=', {
'Quad tree': ['_q_structure', '||', '_q_plain'],
'KD tree': ['_kd_structure', '||', '_kd_plain']
}
]
self._q_graph = nx.DiGraph()
self._kd_graph = nx.DiGraph()
self._q_graph_fig = self._q_structure.fig
self._q_plain_fig = self._q_plain.fig
self._kd_graph_fig = self._kd_structure.fig
self._kd_plain_fig = self._kd_plain.fig
self._kd_plain_fig.canvas.mpl_connect(
'button_press_event', lambda x: self._add_point_action(x))
self._q_plain_fig.canvas.mpl_connect(
'button_press_event', lambda x: self._add_point_action(x))
self._qt = QuadTree((0, 0), (X_SIZE, Y_SIZE),
lambda x: self.add_q_node(x),
lambda x, y: self.connect_q_node(x, y))
self._kdt = KDTree(
(0, 0), (X_SIZE, Y_SIZE),
lambda x: self.add_kd_node(x),
lambda x, y: self.connect_kd_node(x, y),
lambda x, y, z=(False, True): self.highlight_kd_nodes(x, y, z))
self._refresh_graphs()
def __init__(self, item_list=None):
""" Set up the solid world
@param item_list: [ ... polygon ... ]
"""
self.item_list = None
if item_list:
self.item_list = item_list
self.index = None
if item_list:
self.index = QuadTree(self.item_list)
def __init__(self, qt: QuadTree, scale=100):
self.w, self.h = qt.get_boundary().w, qt.get_boundary().h
self.qt = qt
scaled = False
if self.w < 100:
self.w *= scale
scaled = True
if self.h < 100:
self.h *= scale
scaled = True
def main():
capacite = input(
"Veuillez entrer la capacitée maximale que QuadTree peut contenir ")
pygame.init()
pygame.mixer.init()
pygame.display.set_caption('QuadTree Project')
ecran = pygame.display.set_mode((WINDOWWIDTH, WINDOWHEIGHT))
refresh(ecran)
e = ensemble_points(0, 512, 512) # création de 8 points aléatoires
# dans un univers de taille
# 512x512
region = Rectangle((0, 0), (512, 512))
quadTree = QuadTree(region, e, int(capacite))
while True: # boucle principale
try:
handleEvents(quadTree)
drawApp(ecran, quadTree)
pygame.display.update()
except Quitte:
break
pygame.quit()
sys.exit(0)
def updateQuads(self, v=None):
isValid = True
try:
c = map(float, [self.lineEdit_xmin.text(), self.lineEdit_ymin.text(), self.lineEdit_xmax.text(), self.lineEdit_ymax.text()])
except:
isValid = False
if isValid:
# create quad rubber bands
rect = QgsRectangle(c[0], c[1], c[2], c[3])
quadtree = QuadTree(self.dialog.iface.mapCanvas().extent())
quadtree.buildTreeByRect(rect, self.spinBox_Height.value())
self.dialog.createRubberBands(quadtree.quads(), rect.center())
self.dialog.setWindowState(self.windowState() & ~Qt.WindowMinimized | Qt.WindowActive)
else:
self.dialog.clearRubberBands()
def rebuild_quad_tree(self):
self.quad_tree = QuadTree( geometry.BoundingBox( 0, self.SCREEN_SIZE[0], 0, self.SCREEN_SIZE[1] ), max_elems=4 )
for wall in self.walls:
for wall_segment in pairwise( wall ):
self.quad_tree.add( geometry.LineSegment( wall_segment[0], wall_segment[1] ) )
self.quad_tree_rects = []
def get_quadrants_rects( quadrant ):
if quadrant.subquadrants is not None:
for subquadrant in quadrant.subquadrants:
get_quadrants_rects( subquadrant )
else:
self.quad_tree_rects.append( pygame.Rect( quadrant.bounding_box.x_lower, quadrant.bounding_box.y_lower,
quadrant.bounding_box.x_upper - quadrant.bounding_box.x_lower + 1,
quadrant.bounding_box.y_upper - quadrant.bounding_box.y_lower + 1 ) )
get_quadrants_rects( self.quad_tree.main_quadrant )
def __init__(self, rect):
self.objects = []
self.objects.append(Player())
for i in range(100):
self.objects.append(Hunter())
self.qtree = QuadTree(rect, maxDepth=8)
self.qtree.insert(self.objects)
def test_constructor_complex():
from quadtree import QuadTree
q = QuadTree(complex(100, 100))
assert abs(q.dimension.real - 100) < 0.0001
assert abs(q.dimension.imag - 100) < 0.0001
assert q.branches == [None, None, None, None]
assert q.children == {}
def test_constructor_distinct():
from quadtree import QuadTree
q = QuadTree(width=100, height=100)
assert abs(q.dimension.real - 100) < 0.0001
assert abs(q.dimension.imag - 100) < 0.0001
assert q.branches == [None, None, None, None]
assert q.children == {}
def __init__(self):
self.root = QuadTree()
self.radius = 0.125
self.searching = None
self.found = []
self.app = QtWidgets.QApplication(sys.argv)
super().__init__()
self.app.setStyle("Fusion")
palette = QtGui.QPalette()
palette.setColor(QtGui.QPalette.Window, self.background)
self.app.setPalette(palette)
self.setWindowTitle('QuadTree')
self.resize(600, 600)
self.show()
# main event loop
sys.exit(self.app.exec_())
def __init__(self, x=0, y=0, w=960, h=540):
self.x = x
self.y = y
self.w = w
self.h = h
self.plans = set()
self.blocks = set()
self.planTree = QuadTree(boundingRect=(x, y, x+w, y+h))
self.quadTree = QuadTree(boundingRect=(x, y, x+w, y+h))
def createQuadTree(extent, p):
"""
args:
p -- demProperties
"""
try:
cx, cy, w, h = map(float, [p["lineEdit_centerX"], p["lineEdit_centerY"], p["lineEdit_rectWidth"], p["lineEdit_rectHeight"]])
except ValueError:
return None
# normalize
c = extent.normalizePoint(cx, cy)
hw = 0.5 * w / extent.width()
hh = 0.5 * h / extent.height()
quadtree = QuadTree()
if not quadtree.buildTreeByRect(QgsRectangle(c.x() - hw, c.y() - hh, c.x() + hw, c.y() + hh), p["spinBox_Height"]):
return None
return quadtree
def build_tree(text):
query = query_broadcast.value
root = None
geometric_centroid_ra = geometric_centroid_dec = None
centroid = None
cent_min_dist = float("inf")
voxel = None
for lines in text:
for line in lines[1].split("\n"):
split = line.split(",")
if len(split) == 4:
min_ra, max_ra, min_dec, max_dec = split
voxel = Voxel(float(min_ra), float(max_ra), float(min_dec),
float(max_dec))
geometric_centroid_ra, geometric_centroid_dec = voxel.getVoxelCentroid(
)
root = Node(voxel)
elif line:
border = False if split[13].lower() == "false" else True
'''star = Element(int(split[0]), float(split[1]), float(split[2]), float(split[3]), float(split[4]),
float(split[5]), float(split[6]), float(split[7]), float(split[8]),
float(split[9]), float(split[10]), float(split[11]), float(split[12]), 0, border)'''
star = Element(int(split[0]), float(split[1]), float(split[2]),
float(split[3]), 0, border)
root.addElement(star)
if star.border is False:
dist = EucDist(star.getRa(), geometric_centroid_ra,
star.getDec(), geometric_centroid_dec)
if dist < cent_min_dist:
centroid = star
cent_min_dist = dist
root.setSize(len(root.getElements()))
root.addCentroid(centroid)
level = compute_level(voxel.getSideSize(), voxel.getHeightSize(),
query.getMaxDistance())
tree = QuadTree(root, level)
print("\n**** Data Descriptions *****")
print("Sky Voxel: %s,%s,%s,%s" %
(voxel.x_left, voxel.x_right, voxel.y_left, voxel.y_right))
print("Sky Diagonal: %s" % voxel.getDiagonal())
print("Tree Level: %s" % level)
print("Tree Elements: %s" % root.size)
print("Tree Leaf nodes: %s" % len(tree.nodes))
print("**** End Data Descriptions *****\n")
return [tree]
def setup(self):
self.quadtree = QuadTree(8, self.width, self.height)
self.buffer = 15
self.numRectangles = 100
self.numPoints = 100
self.rectangles = []
self.points = []
self.rectColor = "#354F00"
self.pointColor = "#567714"
self.backColor = "#97A084"
self.collRectColor = "#441154"
self.maxRectSize = 100
self.minRectSize = 20
self.pointSize = 5
self.collRectWidth = 150
self.collRectHeight = 150
self.collRect = RectData(0,0,self.collRectWidth,self.collRectHeight,"#F00")
for i in range(self.numRectangles):
vals = self.genRandomVals("rectangle")
rect = RectData(vals.x, vals.y, vals.w, vals.h, self.rectColor)
self.rectangles.append(rect)
self.quadtree.add(rect)
for i in range(self.numPoints):
vals = self.genRandomVals("point")
point = RectData(vals.x, vals.y, vals.w, vals.h, self.pointColor)
self.points.append(point)
self.quadtree.add(point)
self.draw_rect(0, 0, self.width, self.height, "#000")
self.draw_rect(self.collRect.x,self.collRect.y,self.collRect.w,self.collRect.h,self.collRect.data)
def __check_collisions(self):
"""Update proximity sensors and detect collisions between objects"""
collisions = []
checked_robots = []
if self.__qtree is None:
self.__qtree = QuadTree(self.__obstacles)
if len(self.__robots) > 1:
rqtree = QuadTree(self.__robots)
else:
rqtree = None
# check each robot
for robot in self.__robots:
# update proximity sensors
for sensor in robot.get_external_sensors():
sensor.get_world_envelope(True)
rect = Rect(sensor.get_bounding_rect())
sensor.update_distance()
# distance to obstacles
for obstacle in self.__qtree.find_items(rect):
sensor.update_distance(obstacle)
# distance to other robots
if rqtree is None: continue
for other in rqtree.find_items(rect):
if other is not robot:
sensor.update_distance(other)
rect = Rect(robot.get_bounding_rect())
# against nearest obstacles
for obstacle in self.__qtree.find_items(rect):
if robot.has_collision(obstacle):
collisions.append((robot, obstacle))
# against other robots
if rqtree is not None:
for other in rqtree.find_items(rect):
if other is robot: continue
if other in checked_robots: continue
if robot.has_collision(other):
collisions.append((robot, other))
checked_robots.append(robot)
if len(collisions) > 0:
# Test code - print out collisions
for (robot, obstacle) in collisions:
self.log("Collision with {}".format(obstacle),
obj=robot,
color=robot.get_color())
# end of test code
return True
return False
def build_tree(filename, query):
start_time = time.time()
root = None
geometric_centroid_ra = geometric_centroid_dec = None
centroid = None
cent_min_dist = float("inf")
voxel = None
with open(filename) as f:
for line in f:
split = line.replace("\n", "").split(",")
if len(split) == 4:
min_ra, max_ra, min_dec, max_dec = split
voxel = Voxel(float(min_ra), float(max_ra), float(min_dec), float(max_dec))
geometric_centroid_ra, geometric_centroid_dec = voxel.getVoxelCentroid()
root = Node(voxel)
elif line:
border = False # if split[13].lower() == "false" else True
star = Element(int(split[0]), float(split[1]), float(split[2]), float(split[3]), float(split[4]),
float(split[5]), float(split[6]), float(split[7]), float(split[8]),
float(split[9]), float(split[10]), float(split[11]), float(split[12]), 0, border)
root.addElement(star)
if star.border is False:
dist = EucDist(star.getRa(), geometric_centroid_ra, star.getDec(), geometric_centroid_dec)
if dist < cent_min_dist:
centroid = star
cent_min_dist = dist
root.setSize(len(root.getElements()))
root.addCentroid(centroid)
level = compute_level(voxel.getSideSize(), voxel.getHeightSize(), query.getMaxDistance())
tree = QuadTree(root, level)
end_time = time.time() - start_time
print("BT - %s - %0.25f" % (filename, end_time))
return tree
def load(filename, zoom):
with open(filename) as file:
data = json.load(file)
FILENAME = data['filename']
startIter = data['iter']
tree = QuadTree( (data['treeMin'][0]*zoom, data['treeMin'][1]*zoom), (data['treeMax'][0]*zoom, data['treeMax'][1]*zoom))
Node.tree = tree
Road.tree = tree
for node in data['nodes']:
Node((node['coord'][0]*zoom, node['coord'][1]*zoom), id=node['id'])
Node.nodeId = max(Node.nodeSet.keys())+1
for road in data['roads']:
newRoad = Road.getClass(road['type'])(Node.nodeSet[road['start']], Node.nodeSet[road['end']], level=road['level'])
if type(newRoad) is SpecialRoad:
newRoad.create(**road['data'])
newRoad.add(road['id'])
newRoad.reset()
Road.roadId = max(Road.roadSet.keys())+1
return FILENAME, startIter
def build_tree(text):
#query = query_broadcast.value
root = None
geometric_centroid_ra = geometric_centroid_dec = None
centroid = None
cent_min_dist = float("inf")
voxel = None
for i in range(1, len(text)): # skip first line
#for line in lines[1].split("\n"):
split = text[i].split(",")
if len(split) == 4:
min_ra, max_ra, min_dec, max_dec = split
voxel = Voxel(float(min_ra), float(max_ra), float(min_dec),
float(max_dec))
geometric_centroid_ra, geometric_centroid_dec = voxel.getVoxelCentroid(
)
root = Node(voxel)
elif text[i]:
star = Element(int(split[0]), float(split[1]), float(split[2]),
float(split[3]), 0, split[4])
root.addElement(star)
dist = EucDist(star.getRa(), geometric_centroid_ra, star.getDec(),
geometric_centroid_dec)
if dist < cent_min_dist:
centroid = star
cent_min_dist = dist
root.setSize(len(root.getElements()))
root.addCentroid(centroid)
level = compute_level(voxel.getSideSize(), voxel.getHeightSize(),
0.00416667)
tree = QuadTree(root, level)
return tree
def test_constructor_wrong():
from quadtree import QuadTree
with pytest.raises(ValueError):
QuadTree()
with pytest.raises(ValueError):
QuadTree(width=100)
with pytest.raises(ValueError):
QuadTree(height=100)
with pytest.raises(ValueError):
QuadTree(complex(100, 100), width=100)
with pytest.raises(ValueError):
QuadTree(complex(100, 100), height=100)
with pytest.raises(ValueError):
QuadTree(complex(100, 100), width=100, height=100)
for d in node.data: pygame.draw.rect(surface, d.data, pygame.Rect(d.x, d.y, d.w, d.h)) if __name__ == "__main__": display = pygame.display.set_mode((640, 640)) clock = pygame.time.Clock() mdown = False mx1 = 0 my1 = 0 mx2 = 0 my2 = 0 selected = [] quadtree = QuadTree(8, 640, 640) keep_going = True while keep_going: for event in pygame.event.get(): if event.type == pygame.QUIT: keep_going = False if event.type == pygame.KEYDOWN: if event.key == pygame.K_RETURN: x = random.randint(0,600) y = random.randint(0,600) w = random.randint(3,40) h = random.randint(3,40) color = (random.randint(64,250), random.randint(64,250), random.randint(64,250)) quadtree.add(RectData(x, y, w, h, color))
class Simulator(threading.Thread):
"""The simulator manages simobjects and their collisions, commands supervisors
and draws the world using the supplied *renderer*.
The simulator runs in a separate thread. None of its functions are thread-safe,
and should never be called directly from other objects (except for the functions
inherited from `threading.Thread`). The communication with the simulator
should be done through its *in_queue* and *out_queue*. See :ref:`ui-sim-queue`.
:param renderer: The renderer that will be used to draw the world.
The simulator will assume control of the renderer.
The renderer functions also have to be considered thread-unsafe.
:type renderer: :class:`~renderer.Renderer`
:param in_queue: The queue that is used to send events to the simulator.
:type in_queue: :class:`Queue.Queue`
"""
__nice_colors = (0x55AAEE, 0x66BB22, 0xFFBB22, 0xCC66AA,
0x77CCAA, 0xFF7711, 0xFF5555, 0x55CC88)
def __init__(self, renderer, in_queue):
"""Create a simulator with *renderer* and *in_queue*
"""
super(Simulator, self).__init__()
#Attributes
self.__stop = False
self.__state = PAUSE
self.__renderer = renderer
self.__center_on_robot = False
self.__orient_on_robot = False
self.__show_sensors = True
self.__draw_supervisors = False
self.__show_tracks = True
self.__in_queue = in_queue
self._out_queue = queue.Queue()
# Zoom on scene - Move to read_config later
self.__time_multiplier = 1.0
self.__time = 0.0
# Plots
self.plot_expressions = []
# World objects
self.__robots = []
self.__trackers = []
self.__obstacles = []
self.__supervisors = []
self.__background = []
self.__zoom_default = 1
self.__world = None
self.__log_queue = deque()
# Internal objects
self.__qtree = None
def read_config(self, filename):
'''Load in the objects from the world XML file '''
self.log('reading initial configuration')
try:
self.__world = XMLReader(filename, 'simulation').read()
except Exception as e:
raise Exception('[Simulator.read_config] Failed to parse ' + filename \
+ ': ' + str(e))
else:
self.__supervisor_param_cache = None
self.__center_on_robot = False
self.__construct_world()
def __construct_world(self):
"""Creates objects previously loaded from the world xml file.
This function uses the world in ``self.__world``.
All the objects will be created anew, including robots and supervisors.
All of the user's code is reloaded.
"""
if self.__world is None:
return
helpers.unload_user_modules()
self.__state = DRAW_ONCE
self.__robots = []
self.__obstacles = []
self.__supervisors = []
self.__background = []
self.__trackers = []
self.__qtree = None
for thing in self.__world:
thing_type = thing[0]
if thing_type == 'robot':
robot_type, supervisor_type, robot_pose, robot_color = thing[1:5]
try:
# Create robot
robot_class = helpers.load_by_name(robot_type,'robots')
robot = robot_class(pose.Pose(robot_pose))
if robot_color is not None:
robot.set_color(robot_color)
elif len(self.__robots) < 8:
robot.set_color(self.__nice_colors[len(self.__robots)])
# Create supervisor
sup_class = helpers.load_by_name(supervisor_type,'supervisors')
info = robot.get_info()
info.color = robot.get_color()
supervisor = sup_class(robot.get_pose(), info)
supervisor.set_logqueue(self.__log_queue)
name = "Robot {}: {}".format(len(self.__robots)+1, sup_class.__name__)
if self.__supervisor_param_cache is not None and \
len(self.__supervisor_param_cache) > len(self.__supervisors):
supervisor.set_parameters(self.__supervisor_param_cache[len(self.__supervisors)])
self._out_queue.put(("make_param_window",
(robot, name,
supervisor.get_ui_description())))
self.__supervisors.append(supervisor)
# append robot after supervisor for the case of exceptions
self.__robots.append(robot)
# Create trackers
self.__trackers.append(simobject.Path(robot.get_pose(),robot))
self.__trackers[-1].set_color(robot.get_color())
except:
self.log("[Simulator.construct_world] Robot creation failed!")
raise
#raise Exception('[Simulator.construct_world] Unknown robot type!')
elif thing_type == 'obstacle':
obstacle_pose, obstacle_coords, obstacle_color = thing[1:4]
if obstacle_color is None:
obstacle_color = 0xFF0000
self.__obstacles.append(
simobject.Polygon(pose.Pose(obstacle_pose),
obstacle_coords,
obstacle_color))
elif thing_type == 'marker':
obj_pose, obj_coords, obj_color = thing[1:4]
if obj_color is None:
obj_color = 0x00FF00
self.__background.append(
simobject.Polygon(pose.Pose(obj_pose),
obj_coords,
obj_color))
else:
raise Exception('[Simulator.construct_world] Unknown object: '
+ str(thing_type))
self.__time = 0.0
if not self.__robots:
raise Exception('[Simulator.construct_world] No robot specified!')
else:
self.__recalculate_default_zoom()
if not self.__center_on_robot:
self.focus_on_world()
self.__supervisor_param_cache = None
self.step_simulation()
self._out_queue.put(('reset',()))
def __recalculate_default_zoom(self):
"""Calculate the zoom level that will show the robot at about 10% its size
"""
maxsize = 0
for robot in self.__robots:
xmin, ymin, xmax, ymax = robot.get_bounds()
maxsize = max(maxsize,math.sqrt(float(xmax-xmin)**2 + float(ymax-ymin)**2))
if maxsize == 0:
self.__zoom_default = 1
else:
self.__zoom_default = max(self.__renderer.size)/maxsize/10
def __reset_world(self):
"""Resets the world and objects to starting position.
All the user's code will be reloaded.
"""
if self.__world is None:
return
self.__supervisor_param_cache = [sv.get_parameters() for sv in self.__supervisors ]
self.__construct_world()
def run(self):
"""Start the thread. In the beginning there's no world, no obstacles
and no robots.
The simulator will try to draw the world undependently of the
simulation status, so that the commands from the UI get processed.
"""
self.log('starting simulator thread')
time_constant = 0.02 # 20 milliseconds
self.__renderer.clear_screen() #create a white screen
self.__update_view()
while not self.__stop:
try:
sleep(time_constant/self.__time_multiplier)
self.__process_queue()
if self.__state == RUN or \
self.__state == RUN_ONCE:
self.__time += time_constant
# First, move robots
for i, robot in enumerate(self.__robots):
robot.move(time_constant)
self.__trackers[i].add_point(robot.get_pose())
self.fwd_logqueue()
# Second, check for collisions and update sensors
if self.__check_collisions():
#print("Collision detected!")
self.__state = DRAW_ONCE
self.fwd_logqueue()
# Now calculate supervisor outputs for the new position
for i, supervisor in enumerate(self.__supervisors):
info = self.__robots[i].get_info()
inputs = supervisor.execute( info, time_constant)
self.__robots[i].set_inputs(inputs)
self.fwd_logqueue()
if self.plot_expressions:
self.announce_plotables()
# Draw to buffer-bitmap
# Note that if the robot moves immediately after calculation,
# the supervisor would draw the previous state.
if self.__state != PAUSE:
self.__draw()
if self.__state == DRAW_ONCE or \
self.__state == RUN_ONCE:
self.pause_simulation()
self.fwd_logqueue()
except Exception as e:
self._out_queue.put(("exception",sys.exc_info()))
self.pause_simulation()
self.fwd_logqueue()
def __draw(self):
"""Draws the world and items in it.
This will draw the markers, the obstacles,
the robots, their tracks and their sensors
"""
if self.__robots and self.__center_on_robot:
# Temporary fix - center onto first robot
robot = self.__robots[0]
if self.__orient_on_robot:
self.__renderer.set_screen_center_pose(robot.get_pose())
else:
self.__renderer.set_screen_center_pose(pose.Pose(robot.get_pose().x, robot.get_pose().y, 0.0))
self.__renderer.clear_screen()
if self.__draw_supervisors:
for supervisor in self.__supervisors:
supervisor.draw_background(self.__renderer)
for bg_object in self.__background:
bg_object.draw(self.__renderer)
for obstacle in self.__obstacles:
obstacle.draw(self.__renderer)
# Draw the robots, trackers and sensors after obstacles
if self.__show_tracks:
for tracker in self.__trackers:
tracker.draw(self.__renderer)
for robot in self.__robots:
robot.draw(self.__renderer)
if self.__show_sensors:
robot.draw_sensors(self.__renderer)
if self.__draw_supervisors:
for supervisor in self.__supervisors:
supervisor.draw_foreground(self.__renderer)
# update view
self.__update_view()
def __update_view(self):
"""Signal the UI that the drawing process is finished,
and it is safe to access the renderer.
"""
self._out_queue.put(('update_view',()))
self._out_queue.join() # wait until drawn
def __draw_once(self):
if self.__state == PAUSE:
self.__state = DRAW_ONCE
def refresh(self):
self.__draw_once()
def focus_on_world(self):
"""Scale the view to include all of the world (including robots)"""
def include_bounds(bounds, o_bounds):
xl, yb, xr, yt = bounds
xlo, ybo, xro, yto = o_bounds
if xlo < xl: xl = xlo
if xro > xr: xr = xro
if ybo < yb: yb = ybo
if yto > yt: yt = yto
return xl, yb, xr, yt
def bloat_bounds(bounds, factor):
xl, yb, xr, yt = bounds
w = xr-xl
h = yt-yb
factor = (factor-1)/2.0
return xl - w*factor, yb - h*factor, xr + w*factor, yt + h*factor
self.__center_on_robot = False
bounds = self.__robots[0].get_bounds()
for robot in self.__robots:
bounds = include_bounds(bounds, bloat_bounds(robot.get_bounds(),4))
for obstacle in self.__obstacles:
bounds = include_bounds(bounds, obstacle.get_bounds())
xl, yb, xr, yt = bounds
self.__renderer.set_view_rect(xl,yb,xr-xl,yt-yb)
self.__draw_once()
def focus_on_robot(self, rotate = True):
"""Center the view on the (first) robot and follow it.
If *rotate* is true, also follow the robot's orientation.
"""
self.__center_on_robot = True
self.__orient_on_robot = rotate
self.__draw_once()
def show_sensors(self, show = True):
"""Show or hide the robots' sensors on the simulation view
"""
self.__show_sensors = show
self.__draw_once()
def show_tracks(self, show = True):
"""Show/hide tracks for every robot on simulator view"""
self.__show_tracks = show
self.__draw_once()
def show_supervisors(self, show = True):
"""Show/hide the information from the supervisors"""
self.__draw_supervisors = show
self.__draw_once()
def show_grid(self, show=True):
"""Show/hide gridlines on simulator view"""
self.__renderer.show_grid(show)
self.__draw_once()
def adjust_zoom(self,factor):
"""Zoom the view by *factor*"""
self.__renderer.set_zoom_level(self.__zoom_default*factor)
self.__draw_once()
def apply_parameters(self,robot,parameters):
"""Apply *parameters* to the supervisor of *robot*.
The parameters have to correspond to the requirements of the supervisor,
as specified in :meth:`supervisor.Supervisor.get_ui_description`
"""
index = self.__robots.index(robot)
if index < 0:
self.log("Robot not found")
else:
self.__supervisors[index].set_parameters(parameters)
self.__draw_once()
def add_plotable(self,expression):
"""A plotable is an expression that yields a numerical
value. It is evaluated every cycle and the values are announced by the
simulator in the ``plot_update`` signal.
The expression has access to the following variables:
``robot`` - the first robot in the scene
``supervisor`` - the supervisor of this robot
``math`` - the math module
"""
if expression is not None and expression not in self.plot_expressions:
self.plot_expressions.append(expression)
def announce_plotables(self):
plots = {'time':self.__time}
for expr in self.plot_expressions:
try:
plots[expr] = \
eval(expr,{},
{'robot':self.__robots[0],
'supervisor':self.__supervisors[0],
'math':math})
except Exception as e:
self.log(str(e))
plots[expr] = 0
self._out_queue.put(('plot_update',(plots,)))
def plotables(self):
""" Returns a list with some examples of plotables"""
return {
"Robot's X coordinate":"robot.get_pose().x",
"Robot's Y coordinate":"robot.get_pose().y",
"Robot's orientation":"robot.get_pose().theta",
"Robot's orientation (degrees)":"robot.get_pose().theta*57.29578",
"Estimated X coordinate":"supervisor.pose_est.x",
"Estimated Y coordinate":"supervisor.pose_est.y",
"Estimated orientation":"supervisor.pose_est.theta",
"Estimated orientation (degrees)":"supervisor.pose_est.theta*57.29578",
"Left wheel speed":"robot.ang_velocity[0]",
"Right wheel speed":"robot.ang_velocity[1]",
"Linear velocity":"robot.diff2uni(robot.ang_velocity)[0]",
"Angular velocity":"robot.diff2uni(robot.ang_velocity)[1]"
# The possibilities are infinite
#"":"",
}
# Stops the thread
def stop(self):
"""Stop the simulator thread when the entire program is closed"""
self.log('stopping simulator thread')
self.__stop = True
self._out_queue.put(('stopped',()))
def start_simulation(self):
"""Start/continue the simulation"""
if self.__robots:
self.__state = RUN
self._out_queue.put(('running',()))
def pause_simulation(self):
"""Pause the simulation"""
self.__state = PAUSE
self._out_queue.put(('paused',()))
def step_simulation(self):
"""Do one step"""
if self.__state != RUN:
self.__state = RUN_ONCE
#self._out_queue.put(('paused',()))
def reset_simulation(self):
"""Reset the simulation to the start position"""
self.__state = DRAW_ONCE
self.__reset_world()
def set_time_multiplier(self,multiplier):
"""Shorten the interval between evaluation cycles by *multiplier*,
speeding up the simulation"""
self.__time_multiplier = multiplier
### FIXME Those two functions are not thread-safe
def get_time(self):
"""Get the internal simulator time."""
return self.__time
def is_running(self):
"""Get the simulation state as a `bool`"""
return self.__state == RUN
###------------------
def __check_collisions(self):
"""Update proximity sensors and detect collisions between objects"""
collisions = []
checked_robots = []
if self.__qtree is None:
self.__qtree = QuadTree(self.__obstacles)
if len(self.__robots) > 1:
rqtree = QuadTree(self.__robots)
else: rqtree = None
# check each robot
for robot in self.__robots:
# update proximity sensors
for sensor in robot.get_external_sensors():
sensor.get_world_envelope(True)
rect = Rect(sensor.get_bounding_rect())
sensor.update_distance()
# distance to obstacles
for obstacle in self.__qtree.find_items(rect):
sensor.update_distance(obstacle)
# distance to other robots
if rqtree is None: continue
for other in rqtree.find_items(rect):
if other is not robot:
sensor.update_distance(other)
rect = Rect(robot.get_bounding_rect())
# against nearest obstacles
for obstacle in self.__qtree.find_items(rect):
if robot.has_collision(obstacle):
collisions.append((robot, obstacle))
# against other robots
if rqtree is not None:
for other in rqtree.find_items(rect):
if other is robot: continue
if other in checked_robots: continue
if robot.has_collision(other):
collisions.append((robot, other))
checked_robots.append(robot)
if len(collisions) > 0:
# Test code - print out collisions
for (robot, obstacle) in collisions:
self.log("Collision with {}".format(obstacle), obj = robot)
# end of test code
return True
return False
def __process_queue(self):
"""Process external calls
"""
while not self.__in_queue.empty():
tpl = self.__in_queue.get()
if isinstance(tpl,tuple) and len(tpl) == 2:
name, args = tpl
if name in self.__class__.__dict__:
try:
self.__class__.__dict__[name](self,*args)
except TypeError:
self.log("Wrong simulator event parameters {}{}".format(name,args))
self._out_queue.put(("exception",sys.exc_info()))
except Exception as e:
self._out_queue.put(("exception",sys.exc_info()))
else:
self.log("Unknown simulator event '{}'".format(name))
else:
self.log("Wrong simulator event format '{}'".format(tpl))
self.__in_queue.task_done()
def log(self, message, obj=None):
if obj is None:
obj = self
print("{}: {}".format(obj.__class__.__name__,message))
self._out_queue.put(("log",(message,obj.__class__.__name__,None)))
def fwd_logqueue(self):
while self.__log_queue:
obj, message = self.__log_queue.popleft()
color = None
# Get the color
if isinstance(obj,simobject.SimObject):
color = obj.get_color()
elif isinstance(obj,supervisor.Supervisor):
color = obj.robot_color
self._out_queue.put(("log",(message,obj.__class__.__name__,color)))
import numpy as np
import matplotlib.pyplot as plt
from quadtree import Point, Rect, QuadTree
from matplotlib import gridspec
DPI = 72
np.random.seed(13)
width, height = 600, 400
N = 5000
coords = np.random.randn(N, 2) * height / 3 + (width / 2, height / 2)
points = [Point(*coord) for coord in coords]
domain = Rect(width / 2, height / 2, width, height)
qtree = QuadTree(domain, 3)
for point in points:
qtree.insert(point)
print('Number of points in the domain =', len(qtree))
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([])
class Simulator(threading.Thread):
"""The simulator manages simobjects and their collisions, commands supervisors
and draws the world using the supplied *renderer*.
The simulator runs in a separate thread. None of its functions are thread-safe,
and should never be called directly from other objects (except for the functions
inherited from `threading.Thread`). The communication with the simulator
should be done through its *in_queue* and *out_queue*. See :ref:`ui-sim-queue`.
:param renderer: The renderer that will be used to draw the world.
The simulator will assume control of the renderer.
The renderer functions also have to be considered thread-unsafe.
:type renderer: :class:`~renderer.Renderer`
:param in_queue: The queue that is used to send events to the simulator.
:type in_queue: :class:`Queue.Queue`
"""
__nice_colors = (0x55AAEE, 0x66BB22, 0xFFBB22, 0xCC66AA, 0x77CCAA,
0xFF7711, 0xFF5555, 0x55CC88)
def __init__(self, renderer, in_queue):
"""Create a simulator with *renderer* and *in_queue*
"""
super(Simulator, self).__init__()
#Attributes
self.__stop = False
self.__state = PAUSE
self.__renderer = renderer
self.__center_on_robot = False
self.__orient_on_robot = False
self.__show_sensors = True
self.__draw_supervisors = False
self.__show_tracks = True
self.__in_queue = in_queue
self._out_queue = queue.Queue()
# Zoom on scene - Move to read_config later
self.__time_multiplier = 1.0
self.__time = 0.0
# World objects
self.__robots = []
self.__trackers = []
self.__obstacles = []
self.__supervisors = []
self.__background = []
self.__zoom_default = 1
self.__world = None
self.__log_queue = deque()
# Internal objects
self.__qtree = None
def read_config(self, filename):
'''Load in the objects from the world XML file '''
self.log('reading initial configuration')
try:
self.__world = XMLReader(filename, 'simulation').read()
except Exception as e:
raise Exception('[Simulator.read_config] Failed to parse ' + filename \
+ ': ' + str(e))
else:
self.__supervisor_param_cache = None
self.__center_on_robot = False
self.__construct_world()
def __construct_world(self):
"""Creates objects previously loaded from the world xml file.
This function uses the world in ``self.__world``.
All the objects will be created anew, including robots and supervisors.
All of the user's code is reloaded.
"""
if self.__world is None:
return
helpers.unload_user_modules()
self.__state = DRAW_ONCE
self.__robots = []
self.__obstacles = []
self.__supervisors = []
self.__background = []
self.__trackers = []
self.__qtree = None
for thing in self.__world:
thing_type = thing[0]
if thing_type == 'robot':
robot_type, supervisor_type, robot_pose, robot_color = thing[
1:5]
try:
# Create robot
robot_class = helpers.load_by_name(robot_type, 'robots')
robot = robot_class(pose.Pose(robot_pose))
if robot_color is not None:
robot.set_color(robot_color)
elif len(self.__robots) < 8:
robot.set_color(self.__nice_colors[len(self.__robots)])
# Create supervisor
sup_class = helpers.load_by_name(supervisor_type,
'supervisors')
info = robot.get_info()
info.color = robot.get_color()
supervisor = sup_class(robot.get_pose(), info)
supervisor.set_logqueue(self.__log_queue)
name = "Robot {}: {}".format(
len(self.__robots) + 1, sup_class.__name__)
if self.__supervisor_param_cache is not None and \
len(self.__supervisor_param_cache) > len(self.__supervisors):
supervisor.set_parameters(
self.__supervisor_param_cache[len(
self.__supervisors)])
self._out_queue.put(
("make_param_window",
(robot, name, supervisor.get_ui_description())))
self.__supervisors.append(supervisor)
# append robot after supervisor for the case of exceptions
self.__robots.append(robot)
# Create trackers
self.__trackers.append(
simobject.Path(robot.get_pose(), robot))
self.__trackers[-1].set_color(robot.get_color())
except:
self.log(
"[Simulator.construct_world] Robot creation failed!")
raise
#raise Exception('[Simulator.construct_world] Unknown robot type!')
elif thing_type == 'obstacle':
obstacle_pose, obstacle_coords, obstacle_color = thing[1:4]
if obstacle_color is None:
obstacle_color = 0xFF0000
self.__obstacles.append(
simobject.Polygon(pose.Pose(obstacle_pose),
obstacle_coords, obstacle_color))
elif thing_type == 'marker':
obj_pose, obj_coords, obj_color = thing[1:4]
if obj_color is None:
obj_color = 0x00FF00
self.__background.append(
simobject.Polygon(pose.Pose(obj_pose), obj_coords,
obj_color))
else:
raise Exception(
'[Simulator.construct_world] Unknown object: ' +
str(thing_type))
self.__time = 0.0
if not self.__robots:
raise Exception('[Simulator.construct_world] No robot specified!')
else:
self.__recalculate_default_zoom()
if not self.__center_on_robot:
self.focus_on_world()
self.__supervisor_param_cache = None
self.step_simulation()
self._out_queue.put(('reset', ()))
def __recalculate_default_zoom(self):
"""Calculate the zoom level that will show the robot at about 10% its size
"""
maxsize = 0
for robot in self.__robots:
xmin, ymin, xmax, ymax = robot.get_bounds()
maxsize = max(maxsize,
sqrt(float(xmax - xmin)**2 + float(ymax - ymin)**2))
if maxsize == 0:
self.__zoom_default = 1
else:
self.__zoom_default = max(self.__renderer.size) / maxsize / 10
def __reset_world(self):
"""Resets the world and objects to starting position.
All the user's code will be reloaded.
"""
if self.__world is None:
return
self.__supervisor_param_cache = [
sv.get_parameters() for sv in self.__supervisors
]
self.__construct_world()
def run(self):
"""Start the thread. In the beginning there's no world, no obstacles
and no robots.
The simulator will try to draw the world undependently of the
simulation status, so that the commands from the UI get processed.
"""
self.log('starting simulator thread')
time_constant = 0.02 # 20 milliseconds
self.__renderer.clear_screen() #create a white screen
self.__update_view()
while not self.__stop:
try:
sleep(time_constant / self.__time_multiplier)
self.__process_queue()
if self.__state == RUN or \
self.__state == RUN_ONCE:
self.__time += time_constant
# First, move robots
for i, robot in enumerate(self.__robots):
robot.move(time_constant)
self.__trackers[i].add_point(robot.get_pose())
self.fwd_logqueue()
# Second, check for collisions and update sensors
if self.__check_collisions():
#print("Collision detected!")
self.__state = DRAW_ONCE
self.fwd_logqueue()
# Now calculate supervisor outputs for the new position
for i, supervisor in enumerate(self.__supervisors):
info = self.__robots[i].get_info()
inputs = supervisor.execute(info, time_constant)
self.__robots[i].set_inputs(inputs)
self.fwd_logqueue()
# Draw to buffer-bitmap
# Note that if the robot moves immediately after calculation,
# the supervisor would draw the previous state.
if self.__state != PAUSE:
self.__draw()
if self.__state == DRAW_ONCE or \
self.__state == RUN_ONCE:
self.pause_simulation()
self.fwd_logqueue()
except Exception as e:
self._out_queue.put(("exception", sys.exc_info()))
self.pause_simulation()
self.fwd_logqueue()
def __draw(self):
"""Draws the world and items in it.
This will draw the markers, the obstacles,
the robots, their tracks and their sensors
"""
if self.__robots and self.__center_on_robot:
# Temporary fix - center onto first robot
robot = self.__robots[0]
if self.__orient_on_robot:
self.__renderer.set_screen_center_pose(robot.get_pose())
else:
self.__renderer.set_screen_center_pose(
pose.Pose(robot.get_pose().x,
robot.get_pose().y, 0.0))
self.__renderer.clear_screen()
for bg_object in self.__background:
bg_object.draw(self.__renderer)
for obstacle in self.__obstacles:
obstacle.draw(self.__renderer)
# Draw the robots, trackers and sensors after obstacles
if self.__show_tracks:
for tracker in self.__trackers:
tracker.draw(self.__renderer)
for robot in self.__robots:
robot.draw(self.__renderer)
if self.__show_sensors:
robot.draw_sensors(self.__renderer)
if self.__draw_supervisors:
for supervisor in self.__supervisors:
supervisor.draw(self.__renderer)
# update view
self.__update_view()
def __update_view(self):
"""Signal the UI that the drawing process is finished,
and it is safe to access the renderer.
"""
self._out_queue.put(('update_view', ()))
self._out_queue.join() # wait until drawn
def __draw_once(self):
if self.__state == PAUSE:
self.__state = DRAW_ONCE
def refresh(self):
self.__draw_once()
def focus_on_world(self):
"""Scale the view to include all of the world (including robots)"""
def include_bounds(bounds, o_bounds):
xl, yb, xr, yt = bounds
xlo, ybo, xro, yto = o_bounds
if xlo < xl: xl = xlo
if xro > xr: xr = xro
if ybo < yb: yb = ybo
if yto > yt: yt = yto
return xl, yb, xr, yt
def bloat_bounds(bounds, factor):
xl, yb, xr, yt = bounds
w = xr - xl
h = yt - yb
factor = (factor - 1) / 2.0
return xl - w * factor, yb - h * factor, xr + w * factor, yt + h * factor
self.__center_on_robot = False
bounds = self.__robots[0].get_bounds()
for robot in self.__robots:
bounds = include_bounds(bounds,
bloat_bounds(robot.get_bounds(), 4))
for obstacle in self.__obstacles:
bounds = include_bounds(bounds, obstacle.get_bounds())
xl, yb, xr, yt = bounds
self.__renderer.set_view_rect(xl, yb, xr - xl, yt - yb)
self.__draw_once()
def focus_on_robot(self, rotate=True):
"""Center the view on the (first) robot and follow it.
If *rotate* is true, also follow the robot's orientation.
"""
self.__center_on_robot = True
self.__orient_on_robot = rotate
self.__draw_once()
def show_sensors(self, show=True):
"""Show or hide the robots' sensors on the simulation view
"""
self.__show_sensors = show
self.__draw_once()
def show_tracks(self, show=True):
"""Show/hide tracks for every robot on simulator view"""
self.__show_tracks = show
self.__draw_once()
def show_supervisors(self, show=True):
"""Show/hide the information from the supervisors"""
self.__draw_supervisors = show
self.__draw_once()
def show_grid(self, show=True):
"""Show/hide gridlines on simulator view"""
self.__renderer.show_grid(show)
self.__draw_once()
def adjust_zoom(self, factor):
"""Zoom the view by *factor*"""
self.__renderer.set_zoom_level(self.__zoom_default * factor)
self.__draw_once()
def apply_parameters(self, robot, parameters):
"""Apply *parameters* to the supervisor of *robot*.
The parameters have to correspond to the requirements of the supervisor,
as specified in :meth:`supervisor.Supervisor.get_ui_description`
"""
index = self.__robots.index(robot)
if index < 0:
self.log("Robot not found")
else:
self.__supervisors[index].set_parameters(parameters)
self.__draw_once()
# Stops the thread
def stop(self):
"""Stop the simulator thread when the entire program is closed"""
self.log('stopping simulator thread')
self.__stop = True
self._out_queue.put(('stopped', ()))
def start_simulation(self):
"""Start/continue the simulation"""
if self.__robots:
self.__state = RUN
self._out_queue.put(('running', ()))
def pause_simulation(self):
"""Pause the simulation"""
self.__state = PAUSE
self._out_queue.put(('paused', ()))
def step_simulation(self):
"""Do one step"""
if self.__state != RUN:
self.__state = RUN_ONCE
#self._out_queue.put(('paused',()))
def reset_simulation(self):
"""Reset the simulation to the start position"""
self.__state = DRAW_ONCE
self.__reset_world()
def set_time_multiplier(self, multiplier):
"""Shorten the interval between evaluation cycles by *multiplier*,
speeding up the simulation"""
self.__time_multiplier = multiplier
### FIXME Those two functions are not thread-safe
def get_time(self):
"""Get the internal simulator time."""
return self.__time
def is_running(self):
"""Get the simulation state as a `bool`"""
return self.__state == RUN
###------------------
def __check_collisions(self):
"""Update proximity sensors and detect collisions between objects"""
collisions = []
checked_robots = []
if self.__qtree is None:
self.__qtree = QuadTree(self.__obstacles)
if len(self.__robots) > 1:
rqtree = QuadTree(self.__robots)
else:
rqtree = None
# check each robot
for robot in self.__robots:
# update proximity sensors
for sensor in robot.get_external_sensors():
sensor.get_world_envelope(True)
rect = Rect(sensor.get_bounding_rect())
sensor.update_distance()
# distance to obstacles
for obstacle in self.__qtree.find_items(rect):
sensor.update_distance(obstacle)
# distance to other robots
if rqtree is None: continue
for other in rqtree.find_items(rect):
if other is not robot:
sensor.update_distance(other)
rect = Rect(robot.get_bounding_rect())
# against nearest obstacles
for obstacle in self.__qtree.find_items(rect):
if robot.has_collision(obstacle):
collisions.append((robot, obstacle))
# against other robots
if rqtree is not None:
for other in rqtree.find_items(rect):
if other is robot: continue
if other in checked_robots: continue
if robot.has_collision(other):
collisions.append((robot, other))
checked_robots.append(robot)
if len(collisions) > 0:
# Test code - print out collisions
for (robot, obstacle) in collisions:
self.log("Collision with {}".format(obstacle), obj=robot)
# end of test code
return True
return False
def __process_queue(self):
"""Process external calls
"""
while not self.__in_queue.empty():
tpl = self.__in_queue.get()
if isinstance(tpl, tuple) and len(tpl) == 2:
name, args = tpl
if name in self.__class__.__dict__:
try:
self.__class__.__dict__[name](self, *args)
except TypeError:
self.log(
"Wrong simulator event parameters {}{}".format(
name, args))
self._out_queue.put(("exception", sys.exc_info()))
except Exception as e:
self._out_queue.put(("exception", sys.exc_info()))
else:
self.log("Unknown simulator event '{}'".format(name))
else:
self.log("Wrong simulator event format '{}'".format(tpl))
self.__in_queue.task_done()
def log(self, message, obj=None):
if obj is None:
obj = self
print("{}: {}".format(obj.__class__.__name__, message))
self._out_queue.put(("log", (message, obj.__class__.__name__, None)))
def fwd_logqueue(self):
while self.__log_queue:
obj, message = self.__log_queue.popleft()
color = None
# Get the color
if isinstance(obj, simobject.SimObject):
color = obj.get_color()
elif isinstance(obj, supervisor.Supervisor):
color = obj.robot_color
self._out_queue.put(
("log", (message, obj.__class__.__name__, color)))
def main():
QuadTree.maxSize = 1
qt = QuadTree( (-160,-160), (160,160))
Node.tree = qt
assert qt.root.isLeaf
assert qt.root.pointCount == 0
print('Test 1 passed')
pts = [[Node(i+10*random.random(),j+10*random.random()) for j in range(-170,180,20)] for i in range(-170,180,20)]
for row in pts:
for p in row:
p.add()
qt.addPoint(pts[1][1])
assert qt.root.isLeaf
assert qt.root.pointCount == 1
print('Test 2 passed')
qt.addPoint(pts[6][2])
assert not qt.root.isLeaf
assert qt.root.pointCount == 2
print('Test 3 passed')
qt.addPoint(pts[0][0])
assert qt.root.minX < -16
assert qt.root.pointCount == 3
print('Test 4 passed')
draw(qt, 'tree1.png')
print('Tree1 complete')
qt = QuadTree( (-155, -155), (155,155))
Node.tree = qt
points = [Node(x,y) for x,y in [(30,50),(30,70),(50,90),(70,90),(90,70),(90,50),(70,30),(50,30)]]
p1 = Node(50,50)
p1.add()
p2 = Node(50,70)
p2.add()
[p.add() for p in points]
pairs = [(a,b) for a in points for b in points if (a.coord-b.coord).sum() > 0]
roads = [TransportRoad(a,b) for a,b in pairs]
[r.add() for r in roads]
for i in range(len(roads)):
qt = QuadTree( (-155,-155), (155,155))
Node.tree = qt
QuadTree.roadNodes = {}
qt.addPoint(p1)
qt.addPoint(p2)
[qt.addPoint(p) for p in points]
qt.addRoad(roads[i])
draw(qt, 'treeroad%d.png' % i)
print('Treeroad%d complete' % i)
QuadTree.roadNodes = {}
qt = QuadTree( (-160,-160), (160,160))
Node.tree = qt
added = []
for i in range(100):
#(row,col) in random.sample(list(itertools.product(range(1,len(pts)-1), range(1,len(pts)-1))), 100):
x = (random.random()-.5) * 320
y = (random.random()-.5) * 320
p = Node(x,y)
p.add()
assert qt.root.parent is None
qt.addPoint(p)
added.append(p)
draw(qt, 'tree2-%d.png' % i)
toCheck = [qt]
while len(toCheck) > 0:
t = toCheck.pop()
for c in t.children:
toCheck.append(c)
assert t.isLeaf or t.pointCount > 0, str(t)
print('Tree2 complete')
for i in range(20):
QuadTree.roadNodes = {}
qt = QuadTree( (-160,-160), (160,160))
Node.tree = qt
added = []
for _ in range(100):
x = (random.random()-.5) * 320
y = (random.random()-.5) * 320
p = Node(x,y)
p.add()
assert qt.root.parent is None
qt.addPoint(p)
added.append(p)
a,b = random.sample(added,2)
road = TransportRoad(a,b)
road.add()
qt.addRoad(road)
draw(qt, 'treeroadr%d.png' % i)
print('Treeroadr%d complete' % i)
def __init__(self, nrof_creatures, world):
super().__init__()
self.nrof_creatures = nrof_creatures
self.world = world
self.creatures = QuadTree(600, 600)
def setUp(self) -> None:
self.quadtree = QuadTree(Bounds(0, 0, 400, 400),
max_objects=4,
max_level=5)
def __init__(self, rootnode, minrect, circles):
CQuadTree.circles = circles
QuadTree.__init__(self, rootnode, minrect)
# Test playground for functions
if __name__ == "__main__":
import p5_vis
import random
import datetime
from p5 import *
from aabb import AABB
from point2d import Point2D
from quadtree import QuadTree
# 1000 x 1000 QuadTree
q = QuadTree(AABB(0, 0, 1000, 1000))
random.seed(datetime.datetime.now().utcoffset())
vis_qt = p5_vis.VisQuadTree(q)
# Insert 100000 points into QuadTree with gaussian distribution
for x in range(0, 100000):
p = Point2D(random.gauss(500, 100), random.gauss(500, 100))
q.insert(p)
# p5py setup function
def setup():
vis_qt.setup()
# p5py run function
run(sketch_draw=vis_qt.draw())
pts = q.get_all()
xtotal = 0
def __init__(self, rootnode, minrect, circles):
CQuadTree.circles = circles
QuadTree.__init__(self, rootnode, minrect)
class CreatureManager(Observable):
def __init__(self, nrof_creatures, world):
super().__init__()
self.nrof_creatures = nrof_creatures
self.world = world
self.creatures = QuadTree(600, 600)
def create_creatures(self, nrof_creatures):
"""create nrof_creatures creatures"""
for i in range(nrof_creatures):
self.create_creature()
def create_creature(self,
position=None,
creature_information=CreatureInformation(0, None)):
"""create a creature with default parameters"""
if (position is None):
position = (int(random.uniform(0,
400)), int(random.uniform(0, 400)))
information = creature_information
dna = DNA(100, 100, 1, 5)
#print(f"x:{position[0]} y:{position[1]}")
creature = Creature(position, dna, information, self.world)
self.register(creature, position)
return creature
def register(self, creature, position):
self.creatures.insert(creature, position[0], position[1])
creature.reproduce.register(self.create_offspring)
creature.death.register(self.handle_death)
self.notify()
def unregister(self, creature):
creature.reproduce.unregister(self.create_offspring)
creature.death.unregister(self.handle_death)
self.creatures.remove(creature)
def handle_death(self, creature):
"""handle the death of a creature by unregistering it"""
try:
self.unregister(creature)
self.notify()
except ValueError as e:
print("Tried removing unregistered creature from creature_manager")
def get_creatures(self):
"""get all currently registered creatures"""
return self.creatures.all()
def update_creatures(self, delta_time):
if (len(self.get_creatures()) < self.nrof_creatures):
self.create_creatures(1)
for creature in self.get_creatures():
self.get_close_creatures(creature)
creature.update(delta_time)
def get_close_creatures(self, creature):
creature.close_creatures = len(
self.creatures.get_neighbors(creature.position[0],
creature.position[1],
creature.dna.sense_distance))
def get_creature_highest_generation(self):
return sorted(self.get_creatures(),
key=lambda creature: creature.information.generation)[-1]
def create_offspring(self, creature):
creature_information = CreatureInformation(
creature.information.generation + 1, creature)
new_position = (creature.position[0] + 5, creature.position[1] + 5)
offspring = self.create_creature(
position=creature.position,
creature_information=creature_information)
offspring.brain = Brain.from_existing_brain(creature.brain)
offspring.brain.mutate()