How to pretty print a quadtree in python? - python

I have some code that can make a quad tree from data points. I know how to print out binary tree with slashes, but I don't even know where to start to print/draw out a tree with 4 children instead of 2 each to be able to visualize my tree.
I've been testing it by using my search_pqtreee function. For example, to list all the points in the northeast quadrant, I can test it by making a list like: [search_pqtree(q.ne,p) for p in points]
#The point import is a class for points in Cartesian coordinate systems
from point import *
class PQuadTreeNode():
def __init__(self,point,nw=None,ne=None,se=None,sw=None):
self.point = point
self.nw = nw
self.ne = ne
self.se = se
self.sw = sw
def __repr__(self):
return str(self.point)
def is_leaf(self):
return self.nw==None and self.ne==None and \
self.se==None and self.sw==None
def search_pqtree(q, p, is_find_only=True):
if q is None:
return
if q.point == p:
if is_find_only:
return q
else:
return
dx,dy = 0,0
if p.x >= q.point.x:
dx = 1
if p.y >= q.point.y:
dy = 1
qnum = dx+dy*2
child = [q.sw, q.se, q.nw, q.ne][qnum]
if child is None and not is_find_only:
return q
return search_pqtree(child, p, is_find_only)
def insert_pqtree(q, p):
n = search_pqtree(q, p, False)
node = PQuadTreeNode(point=p)
if p.x < n.point.x and p.y < n.point.y:
n.sw = node
elif p.x < n.point.x and p.y >= n.point.y:
n.nw = node
elif p.x >= n.point.x and p.y < n.point.y:
n.se = node
else:
n.ne = node
def pointquadtree(data):
root = PQuadTreeNode(point = data[0])
for p in data[1:]:
insert_pqtree(root, p)
return root
#Test
data1 = [ (2,2), (0,5), (8,0), (9,8), (7,14), (13,12), (14,13) ]
points = [Point(d[0], d[1]) for d in data1]
q = pointquadtree(points)
print([search_pqtree(q.ne, p) for p in points])
What I'm trying to say is if I was pretty printing a binary tree, it might look like this:
(2, 2)
/ \
(0, 5) (8, 0)
/ \ / \
Is there a way to write a function that print out 4 lines each? Or maybe print it out sideways?


As you classified your question with GIS and spatial, this problem made me think of a map with north-east, north-west, south-east and south-west in each corner.
A single node quadtree would simply be :
(0,0)
A two node quadtree would be :
.|( 1, 1)
----( 0, 0)----
.|.
With 3 nodes in depth that would go to :
| .|( 2, 2)
|----( 1, 1)----
.| .|.
------------( 0, 0)------------
.|.
|
|
I've implemented this idea, with some changes to your code to make it easier:
I've added a trivial point class, with the __repr__ method I needed for number formatting
I made quadrants into a dictionary to be able to loop on them
I thought I would need the get_depth method, but it's not used...
I also think that search and insert functions should be methods of the class PQuadTreeNode, but I leave it to you as an exercise :)
The implementation works with the following steps:
If the quadtree is a leaf, its map is the central point
Get the maps of the 4 quadrants (if empty, it's a dot)
Normalize them using the size of the largest, and puts them near the center of the parent
Combine the 4 quadrants with the quadtree point at the center.
This is of course higly recursive, and I didn't made any attempt at optimization.
If numbers have a length greater than 2 (like 100 or -10), you can adjust the num_length variable.
num_length = 2
num_fmt = '%' + str(num_length) + 'd'
class Point():
def __init__(self,x=None,y=None):
self.x = x
self.y = y
def __repr__(self):
return '(' + (num_fmt % self.x) + ',' + (num_fmt % self.y) + ')'
def normalize(corner, quadmap, width, height):
old_height = len(quadmap)
old_width = len(quadmap[0])
if old_height == height and old_width == width:
return quadmap
else:
blank_width = width - old_width
if corner == 'nw':
new = [' '*width for i in range(height - old_height)]
for line in quadmap:
new.append(' '*blank_width + line)
elif corner == 'ne':
new = [' '*width for i in range(height - old_height)]
for line in quadmap:
new.append(line + ' '*blank_width)
elif corner == 'sw':
new = []
for line in quadmap:
new.append(' '*blank_width + line)
for i in range(height - old_height):
new.append(' '*width)
elif corner == 'se':
new = []
for line in quadmap:
new.append(line + ' '*blank_width)
for i in range(height - old_height):
new.append(' '*width)
return new
class PQuadTreeNode():
def __init__(self,point,nw=None,ne=None,se=None,sw=None):
self.point = point
self.quadrants = {'nw':nw, 'ne':ne, 'se':se, 'sw':sw}
def __repr__(self):
return '\n'.join(self.get_map())
def is_leaf(self):
return all(q == None for q in self.quadrants.values())
def get_depth(self):
if self.is_leaf():
return 1
else:
return 1 + max(q.get_depth() if q else 0 for q in self.quadrants.values())
def get_map(self):
if self.is_leaf():
return [str(self.point)]
else:
subquadmaps = {
sqn:sq.get_map() if sq else ['.']
for sqn, sq
in self.quadrants.items()
}
subheight = max(len(map) for map in subquadmaps.values())
subwidth = max(len(mapline) for map in subquadmaps.values() for mapline in map)
subquadmapsnorm = {
sqn:normalize(sqn, sq, subwidth, subheight)
for sqn, sq
in subquadmaps.items()
}
map = []
for n in range(subheight):
map.append(subquadmapsnorm['nw'][n] + '|' + subquadmapsnorm['ne'][n])
map.append('-' * (subwidth-num_length-1) + str(self.point) + '-' * (subwidth-num_length-1))
for n in range(subheight):
map.append(subquadmapsnorm['sw'][n] + '|' + subquadmapsnorm['se'][n])
return map
def search_pqtree(q, p, is_find_only=True):
if q is None:
return
if q.point == p:
if is_find_only:
return q
else:
return
dx,dy = 0,0
if p.x >= q.point.x:
dx = 1
if p.y >= q.point.y:
dy = 1
qnum = dx+dy*2
child = [q.quadrants['sw'], q.quadrants['se'], q.quadrants['nw'], q.quadrants['ne']][qnum]
if child is None and not is_find_only:
return q
return search_pqtree(child, p, is_find_only)
def insert_pqtree(q, p):
n = search_pqtree(q, p, False)
node = PQuadTreeNode(point=p)
if p.x < n.point.x and p.y < n.point.y:
n.quadrants['sw'] = node
elif p.x < n.point.x and p.y >= n.point.y:
n.quadrants['nw'] = node
elif p.x >= n.point.x and p.y < n.point.y:
n.quadrants['se'] = node
else:
n.quadrants['ne'] = node
def pointquadtree(data):
root = PQuadTreeNode(point = data[0])
for p in data[1:]:
insert_pqtree(root, p)
return root
#Test
data1 = [ (2,2), (0,5), (8,0), (9,8), (7,14), (13,12), (14,13) ]
points = [Point(d[0], d[1]) for d in data1]
q = pointquadtree(points)
print(q)
With your example data:
| | .|(14,13)
| |----(13,12)----
| ( 7,14)| .|.
|------------( 9, 8)------------
| .|.
| |
( 0, 5)| |
----------------------------( 2, 2)----------------------------
.|( 8, 0)
|
|
|
|
|
|
Tell me if you find it useful !

Related

How to change 'cost' of path here?

I'm reading this python code about A star algorithm. For me, I understand how this algorithm work, but when I come to the code I got some confusing things until to understand. I want to be able to change the cost of paths here. I mean I need to be able to set a cost to each pixel here while calculating the best path but I couldn't figure out where to do it. I have 2 paths and I want the algorithm to choose the bottom path because of the cost of the top path. How do I do that?
Image of the paths. I want algorithm to choose bottom one.
Entire code of the algorithm:
"""
A* grid planning
author: Atsushi Sakai(#Atsushi_twi)
Nikos Kanargias (nkana#tee.gr)
See Wikipedia article (https://en.wikipedia.org/wiki/A*_search_algorithm)
"""
import math
import matplotlib.pyplot as plt
show_animation = True
class AStarPlanner:
def __init__(self, ox, oy, reso, rr):
"""
Initialize grid map for a star planning
ox: x position list of Obstacles [m]
oy: y position list of Obstacles [m]
reso: grid resolution [m]
rr: robot radius[m]
"""
self.reso = reso
self.rr = rr
self.calc_obstacle_map(ox, oy)
self.motion = self.get_motion_model()
class Node:
def __init__(self, x, y, cost, pind):
self.x = x # index of grid
self.y = y # index of grid
self.cost = cost
self.pind = pind
def __str__(self):
return str(self.x) + "," + str(self.y) + "," + str(
self.cost) + "," + str(self.pind)
def planning(self, sx, sy, gx, gy):
"""
A star path search
input:
sx: start x position [m]
sy: start y position [m]
gx: goal x position [m]
gy: goal y position [m]
output:
rx: x position list of the final path
ry: y position list of the final path
"""
nstart = self.Node(self.calc_xyindex(sx, self.minx),
self.calc_xyindex(sy, self.miny), 0.0, -1)
ngoal = self.Node(self.calc_xyindex(gx, self.minx),
self.calc_xyindex(gy, self.miny), 0.0, -1)
open_set, closed_set = dict(), dict()
open_set[self.calc_grid_index(nstart)] = nstart
while 1:
if len(open_set) == 0:
print("Open set is empty..")
break
c_id = min(
open_set,
key=lambda o: open_set[o].cost + self.calc_heuristic(ngoal,
open_set[
o]))
current = open_set[c_id]
# show graph
if show_animation: # pragma: no cover
plt.plot(self.calc_grid_position(current.x, self.minx),
self.calc_grid_position(current.y, self.miny), "xc")
# for stopping simulation with the esc key.
plt.gcf().canvas.mpl_connect('key_release_event',
lambda event: [exit(
0) if event.key == 'escape' else None])
if len(closed_set.keys()) % 10 == 0:
plt.pause(0.001)
if current.x == ngoal.x and current.y == ngoal.y:
print("Find goal")
ngoal.pind = current.pind
ngoal.cost = current.cost
break
# Remove the item from the open set
del open_set[c_id]
# Add it to the closed set
closed_set[c_id] = current
# expand_grid search grid based on motion model
for i, _ in enumerate(self.motion):
node = self.Node(current.x + self.motion[i][0],
current.y + self.motion[i][1],
current.cost + self.motion[i][2], c_id)
n_id = self.calc_grid_index(node)
# If the node is not safe, do nothing
if not self.verify_node(node):
continue
if n_id in closed_set:
continue
if n_id not in open_set:
open_set[n_id] = node # discovered a new node
else:
if open_set[n_id].cost > node.cost:
# This path is the best until now. record it
open_set[n_id] = node
rx, ry = self.calc_final_path(ngoal, closed_set)
return rx, ry
def calc_final_path(self, ngoal, closedset):
# generate final course
rx, ry = [self.calc_grid_position(ngoal.x, self.minx)], [
self.calc_grid_position(ngoal.y, self.miny)]
pind = ngoal.pind
while pind != -1:
n = closedset[pind]
rx.append(self.calc_grid_position(n.x, self.minx))
ry.append(self.calc_grid_position(n.y, self.miny))
pind = n.pind
return rx, ry
#staticmethod
def calc_heuristic(n1, n2):
w = 1.0 # weight of heuristic
d = w * math.hypot(n1.x - n2.x, n1.y - n2.y)
return d
def calc_grid_position(self, index, minp):
"""
calc grid position
:param index:
:param minp:
:return:
"""
pos = index * self.reso + minp
return pos
def calc_xyindex(self, position, min_pos):
return round((position - min_pos) / self.reso)
def calc_grid_index(self, node):
return (node.y - self.miny) * self.xwidth + (node.x - self.minx)
def verify_node(self, node):
px = self.calc_grid_position(node.x, self.minx)
py = self.calc_grid_position(node.y, self.miny)
if px < self.minx:
return False
elif py < self.miny:
return False
elif px >= self.maxx:
return False
elif py >= self.maxy:
return False
# collision check
if self.obmap[node.x][node.y]:
return False
return True
def calc_obstacle_map(self, ox, oy):
self.minx = round(min(ox))
self.miny = round(min(oy))
self.maxx = round(max(ox))
self.maxy = round(max(oy))
print("minx:", self.minx)
print("miny:", self.miny)
print("maxx:", self.maxx)
print("maxy:", self.maxy)
self.xwidth = round((self.maxx - self.minx) / self.reso)
self.ywidth = round((self.maxy - self.miny) / self.reso)
print("xwidth:", self.xwidth)
print("ywidth:", self.ywidth)
# obstacle map generation
self.obmap = [[False for i in range(self.ywidth)]
for i in range(self.xwidth)]
for ix in range(self.xwidth):
x = self.calc_grid_position(ix, self.minx)
for iy in range(self.ywidth):
y = self.calc_grid_position(iy, self.miny)
for iox, ioy in zip(ox, oy):
d = math.hypot(iox - x, ioy - y)
if d <= self.rr:
self.obmap[ix][iy] = True
break
#staticmethod
def get_motion_model():
# dx, dy, cost
motion = [[1, 0, 1],
[0, 1, 1],
[-1, 0, 1],
[0, -1, 1],
[-1, -1, math.sqrt(2)],
[-1, 1, math.sqrt(2)],
[1, -1, math.sqrt(2)],
[1, 1, math.sqrt(2)]]
return motion
def main():
print(__file__ + " start!!")
# start and goal position
sx = 1.0 # [m]
sy = 1.0 # [m]
gx = 50.0 # [m]
gy = 50.0 # [m]
grid_size = 10.0 # [m]
robot_radius = 1.0 # [m]
# set obstacle positions
ox, oy = [], []
for i in range(-10, 60):
ox.append(i)
oy.append(-10.0)
for i in range(-10, 60):
ox.append(60.0)
oy.append(i)
for i in range(-10, 61):
ox.append(i)
oy.append(60.0)
for i in range(-10, 61):
ox.append(-10.0)
oy.append(i)
for i in range(-10, 40):
ox.append(20.0)
oy.append(i)
for i in range(0, 10):
ox.append(40.0)
oy.append(i)
for i in range(0, 40):
ox.append(40.0)
oy.append(60.0 - i)
if show_animation: # pragma: no cover
plt.plot(ox, oy, ".k")
plt.plot(sx, sy, "og")
plt.plot(gx, gy, "xb")
plt.grid(True)
plt.axis("equal")
a_star = AStarPlanner(ox, oy, grid_size, robot_radius)
rx, ry = a_star.planning(sx, sy, gx, gy)
if show_animation: # pragma: no cover
plt.plot(rx, ry, "-r")
plt.show()
plt.pause(0.001)
if __name__ == '__main__':
main()

I did it with adding a part of code like that
# expand_grid search grid based on motion model
for i, _ in enumerate(self.motion):
cost = 0
if(current.x + self.motion[i][0] >= 45 and (current.x + self.motion[i][0]) <= 55 and current.y + self.motion[i][1] >= 20 and current.y + self.motion[i][1] <= 31):
cost = 15
node = self.Node(current.x + self.motion[i][0],
current.y + self.motion[i][1],
current.cost + self.motion[i][2] + cost, c_id)
n_id = self.calc_grid_index(node)

Dijkstra's shortest path

I'm VERY new to Python (self learning) and am writing some code, and have read as much as possible (both on this website and youtube) to figure it out, and I'm perplexed as to why it's not working for me
I've generated this dictionary of dictionaries (may not be most efficient, please let me know how to improve, been doing this a couple weeks only):
graphx = []
all_locs = []
def graph(width, height):
for r in range(height):
row = []
for c in range(width):
t = (r, c)
row.append(t)
all_locs.append(t)
graphx.append(row)
graph(width, height)
# # Builds a dictionary of all nodes, and their weight
weighted_grid = {}
for node in graphx:
for c in node:
n = {}
s = {}
e = {}
w = {}
if (c[0] < height) and (c[0] > 0):
n[c[0] + 1, c[1]] = 1
s[c[0] - 1, c[1]] = 1
elif c[0] == 0:
n[c[0] + 1, c[1]] = 1
elif c[0] == height:
s[c[0] - 1, c[1]] = 1
if c[1] < width and c[1] > 0:
e[c[0], c[1] + 1] = 1
w[c[0], c[1] - 1] = 1
elif c[1] == 0:
e[c[0], c[1] + 1] = 1
elif c[1] == height:
w[c[0], c[1] - 1] = 1
temp = {}
blank = {}
if n != blank:
temp[c[0] + 1, c[1]] = 1
if e != blank:
temp[c[0], c[1] + 1] = 1
if s != blank:
temp[c[0] - 1, c[1]] = 1
if w != blank:
temp[c[0], c[1] - 1] = 1
weighted_grid[c[0],c[1]] = temp
When I run dijikstras, using the the tuples as start and destination, I get an error. Here's the version of dijkstras I'm running:
def dijkstra(graph, start, goal):
shortest_distance = {} # records the current cost to reach that node.
track_predecessor = {} # keeps track of the path that led to this node.
unseen_nodes = graph # Iterate through the graph to check all nodes.
infinity = 99999 # Make it any large number,greater than possible path weights.
track_path = [] # gives us the trace-back path of the optimal route
for node in unseen_nodes:
shortest_distance[node] = infinity
shortest_distance[start] = 0
while unseen_nodes:
min_distance_node = None
for node in unseen_nodes:
if min_distance_node is None:
min_distance_node = node
elif shortest_distance[node] < shortest_distance[min_distance_node]:
min_distance_node = node
path_options = graph[min_distance_node].items()
for child_node, weight in path_options:
if weight + shortest_distance[min_distance_node] < shortest_distance[child_node]:
shortest_distance[child_node] = weight + shortest_distance[min_distance_node]
track_predecessor[child_node] = min_distance_node
unseen_nodes.pop(min_distance_node)
current_node = goal
while current_node != start:
try:
track_path.insert(0, current_node)
current_node = track_predecessor[current_node]
except KeyError:
break
track_path.insert(0, start)
if shortest_distance[goal] != infinity:
pass
The error I get is:
Traceback (most recent call last):
File "C:/Users/Dave/Desktop/Important/PycharmProjects/DMT2/dungeonmasterstome/Main.py", line 318, in <module>
dijkstra(weighted_grid, (0, 0), (0,1))
File "C:/Users/Dave/Desktop/Important/PycharmProjects/DMT2/dungeonmasterstome/Main.py", line 300, in dijkstra
if weight + shortest_distance[min_distance_node] < shortest_distance[child_node]:
KeyError: (0, 30)
Thoughts and thanks for any help and constructive criticism.

Why doesn't update repaint a scene?

I am making a marching cubes project in python using PyQt5 and PyOpenGL. I am trying to hide the wireframe cube which marches across the screen, referenced as mainWindow.marchingCube to disappear after cycling through. I managed to get the disappearing cycle to occur, but the cube does not actually disappear. I called the QOpenGLWidget's update function, but the cube still did not disappear.
import sys
from PyQt5.QtWidgets import (
QApplication, QMainWindow, QSlider,
QOpenGLWidget, QLabel, QPushButton
)
from PyQt5.QtCore import Qt
from OpenGL.GL import (
glLoadIdentity, glTranslatef, glRotatef,
glClear, glBegin, glEnd,
glColor3fv, glVertex3fv,
GL_COLOR_BUFFER_BIT, GL_DEPTH_BUFFER_BIT,
GL_QUADS, GL_LINES
)
from OpenGL.GLU import gluPerspective
from numerics import sin, cos, tan, avg, rnd #Numerics is my custom math library.
import random, time
class mainWindow(QMainWindow): #Main class.
shapes = [] #this will hold instances of the following classes: cube
dataPoints = []
zoomLevel = -10
rotateDegreeV = -90
rotateDegreeH = 0
marchActive = False
limit = -1
meshPoints = []
class cube():
render = True
solid = False
color = (1, 1, 1)
def config(self, x, y, z, size = 0.1, solid = False, color = (1, 1, 1)):
self.solid = solid
self.color = color
self.size = size / 2
s = self.size
self.vertices = [
(-s + x, s + y, -s + z),
(s + x, s + y, -s + z),
(s + x, -s + y, -s + z),
(-s + x, -s + y, -s + z),
(-s + x, s + y, s + z),
(s + x, s + y, s + z),
(s + x, -s + y, s + z),
(-s + x, -s + y, s + z)
]
self.edges = [
(0,1), (0,3), (0,4), (2,1),
(2,3), (2,6), (7,3), (7,4),
(7,6), (5,1), (5,4), (5,6)
]
self.facets = [
(0, 1, 2, 3), (0, 1, 6, 5),
(0, 3, 7, 4), (6, 5, 1, 2),
(6, 7, 4, 5), (6, 7, 3, 2)
]
def show(self):
self.render = True
def hide(self):
self.render = False
class dataPoint():
location = (0, 0, 0)
value = 0
shape = None
def place(self, x, y, z):
self.location = (x, y, z)
def set(self, val):
self.value = val
def setShape(self, shape):
self.shape = shape
class meshPoint():
location = (0, 0, 0)
shape = None
def place(self, x, y, z):
self.location = (x, y, z)
def setShape(self, shape):
self.shape = shape
def keyPressEvent(self, event): #This is the keypress detector. I use this to determine input to edit grids.
try:
key = event.key()
#print(key)
if key == 87:
self.rotateV(5)
elif key == 65:
self.rotateH(5)
elif key == 83:
self.rotateV(-5)
elif key == 68:
self.rotateH(-5)
elif key == 67:
self.zoom(1)
elif key == 88:
self.zoom(-1)
elif key == 77:
self.marchStep()
except:
pass
def __init__(self):
super(mainWindow, self).__init__()
self.currentStep = 0
self.width = 700 #Variables used for the setting of the size of everything
self.height = 600
self.setGeometry(0, 0, self.width + 50, self.height) #Set the window size
self.initData(3, 3, 3)
def setupUI(self):
self.openGLWidget = QOpenGLWidget(self) #Create the GLWidget
self.openGLWidget.setGeometry(0, 0, self.width, self.height)
self.openGLWidget.initializeGL()
self.openGLWidget.resizeGL(self.width, self.height) #Resize GL's knowledge of the window to match the physical size?
self.openGLWidget.paintGL = self.paintGL #override the default function with my own?
self.filterSlider = QSlider(Qt.Vertical, self)
self.filterSlider.setGeometry(self.width + 10, int(self.height / 2) - 100, 30, 200)
self.filterSlider.valueChanged[int].connect(self.filter)
self.limitDisplay = QLabel(self)
self.limitDisplay.setGeometry(self.width, int(self.height / 2) - 130, 50, 30)
self.limitDisplay.setAlignment(Qt.AlignCenter)
self.limitDisplay.setText('-1')
self.marchButton = QPushButton(self)
self.marchButton.setGeometry(self.width, int(self.height / 2) - 160, 50, 30)
self.marchButton.setText('March!')
self.marchButton.clicked.connect(self.marchStep)
def marchStep(self):
if not self.marchActive:
marchAddr = len(self.shapes)
self.shapes.append(self.cube())
self.marchingCube = self.shapes[marchAddr]
self.marchActive = True
self.currentStep = 0
if self.currentStep == len(self.marchPoints):
self.currentStep = 0
#print('meshPoints: {}'.format(self.meshPoints))
for mp in self.meshPoints:
#print(mp.shape)
self.shapes.remove(mp.shape)
self.meshPoints.clear()
self.marchingCube.hide()
return
if self.currentStep == 0:
self.marchingCube.show()
p = self.marchPoints[self.currentStep]
x, y, z = p
self.marchingCube.config(x, y, z, size = 1)
points = []
for i in range(8):
point = self.getDataPointByLocation(self.marchingCube.vertices[i])
points.append(point)
self.openGLWidget.update()
#print('step: {} x: {} y: {} z: {}'.format(self.currentStep, x, y, z))
#for point in points:
# print(point.location, end = ' ')
#print()
for pair in self.marchingCube.edges:
pointA = points[pair[0]]
pointB = points[pair[1]]
#print('pointA.value: {} pointB.value: {} limit: {}'.formatpointA.value, pointB.value, self.limit)
if (pointA.value < self.limit and pointB.value > self.limit) or (pointA.value > self.limit and pointB.value < self.limit):
xA, yA, zA = pointA.location
xB, yB, zB = pointB.location
valA = (pointA.value + 1) / 2
valB = (pointB.value + 1) / 2
xC = float(avg([xA, xB]))
yC = float(avg([yA, yB]))
zC = float(avg([zA, zB]))
mp = self.meshPoint()
mp.place(xC, yC, zC)
mp.setShape(self.cube())
mp.shape.config(xC, yC, zC, size = 0.05, solid = True, color = (1, 0, 0))
self.shapes.append(mp.shape)
self.meshPoints.append(mp)
self.currentStep += 1
self.openGLWidget.update()
def zoom(self, value):
self.zoomLevel += value
self.openGLWidget.update()
def rotateV(self, value):
self.rotateDegreeV += value
self.openGLWidget.update()
def rotateH(self, value):
self.rotateDegreeH += value
self.openGLWidget.update()
def filter(self, value):
self.limit = rnd((value / 49.5) -1, -2)
for d in self.dataPoints:
if d.value < self.limit:
d.shape.hide()
else:
d.shape.show()
self.limitDisplay.setText(str(self.limit))
self.openGLWidget.update()
def getDataPointByLocation(self, coord):
x, y, z = coord
for dp in self.dataPoints:
if dp.location == (x, y, z):
return dp
return False
def paintGL(self):
glLoadIdentity()
gluPerspective(45, self.width / self.height, 0.1, 110.0) #set perspective?
glTranslatef(0, 0, self.zoomLevel) #I used -10 instead of -2 in the PyGame version.
glRotatef(self.rotateDegreeV, 1, 0, 0) #I used 2 instead of 1 in the PyGame version.
glRotatef(self.rotateDegreeH, 0, 0, 1)
glClear(GL_COLOR_BUFFER_BIT|GL_DEPTH_BUFFER_BIT)
if len(self.shapes) != 0:
glBegin(GL_LINES)
for s in self.shapes:
glColor3fv(s.color)
if s.render and not s.solid:
for e in s.edges:
for v in e:
glVertex3fv(s.vertices[v])
glEnd()
glBegin(GL_QUADS)
for s in self.shapes:
glColor3fv(s.color)
if s.render and s.solid:
for f in s.facets:
for v in f:
glVertex3fv(s.vertices[v])
glEnd()
def initData(self, sizeX, sizeY, sizeZ):
marchSizeX = sizeX - 1
marchSizeY = sizeY - 1
marchSizeZ = sizeZ - 1
xOff = -(sizeX / 2) + 0.5
yOff = -(sizeY / 2) + 0.5
zOff = -(sizeZ / 2) + 0.5
xMarchOff = -(marchSizeX / 2) + 0.5
yMarchOff = -(marchSizeY / 2) + 0.5
zMarchOff = -(marchSizeZ / 2) + 0.5
vals = []
self.marchPoints = []
for z in range(marchSizeZ):
for y in range(marchSizeY):
for x in range(marchSizeX):
self.marchPoints.append((x + xMarchOff, y + yMarchOff ,z + zMarchOff))
for z in range(sizeZ):
for y in range(sizeY):
for x in range(sizeX):
loc = len(self.dataPoints)
val = self.generate(x + xOff, y + yOff, z + zOff)
self.dataPoints.append(self.dataPoint())
self.dataPoints[loc].place(x + xOff, y + yOff, z + zOff)
self.dataPoints[loc].set(val)
loc2 = len(self.shapes)
self.shapes.append(self.cube())
self.shapes[loc2].config(x + xOff, y + yOff, z + zOff, solid = True, color = (0, (val + 1) / 2, (val + 1) / -2 + 1))
self.dataPoints[loc].setShape(self.shapes[loc2])
vals.append(val)
print(avg(vals))
def generate(self, xIn, yIn, zIn): #Function which produces semi-random values based on the supplied coordinates.
i = -(xIn * yIn * (10 + zIn))
j = xIn * yIn * (10 + zIn)
if i < j:
mixer = random.randint(i, j)
else:
mixer = random.randint(j, i + 1)
a = avg([sin(cos(xIn)), tan(tan(yIn)), cos(tan(zIn))])
out = mixer * a
while out > 10:
out -= 5
while out < -10:
out += 5
return float(out / 10)
app = QApplication([])
window = mainWindow()
window.setupUI()
window.show()
sys.exit(app.exec_())
Why doesn't the cube disappear? I have caught wind during my web searches on the subject that update does not always work as expected. Directly calling self.openGLWidget.paintGL() does not work either. What must I do to make the cube disappear?
EDIT:
If I make a call to rotate, rotate, or zoom, the screen refreshes and the meshpoints as well as the marching cube all disappear. I think I may end up making a workaround by calling one of those with a zero value.
To test, save the following code in a file named numerics.py in the same directory as the rest of the code.
from decimal import Decimal as dec
degrad = 'deg'
pi = 3.14159265358979323846
terms = dec(9) #number of terms used for the trig calculations
def version():
print('numerics.py version 1.0.0')
print('Packaged with the cubes project')
def mode(modeinput = ''): #switch between degrees and radians or check the current mode
global degrad
if modeinput == 'deg':
degrad = 'deg'
return 'deg'
if modeinput == 'rad':
degrad = 'rad'
return 'rad'
if modeinput == '':
return degrad
else:
return False
def accuracy(accinput = ''):
global terms
global pi
if accinput == '':
return terms
terms = dec(accinput)
PI = calculatePi(accinput)
print('Pi is: {}'.format(PI))
return terms
def calculatePi(placeIn = terms):
if placeIn > 15:
if input("Warning: You have chosen to calculate more than 20 digits of pi. This may take a LONG TIME and may be inacurate. Enter 'yes' if you wish to proceed. If you enter anything else, this function will revert to 10 digits.") == 'yes':
place = placeIn
else:
place = 10
else:
place = placeIn
print('Calculating Pi...\nPlease wait, as this may take a while.')
PI = dec(3)
addSub = True
for i in range(2, 2 * (int(place) ** 6) + 1, 2):
if addSub:
PI += dec(4) / (dec(i) * dec(i + 1) * dec(i + 2))
elif not addSub:
PI -= dec(4) / (dec(i) * dec(i + 1) * dec(i + 2))
addSub = not addSub
return rnd(PI, -(place), mode = 'cutoff')
def radToDeg(radin):
return (dec(radin) * dec(180 / pi))
def degToRad(degin):
return (dec(degin) * dec(pi / 180))
def avg(numsIn): #return the average of two numbers, specified as an integer or float
num1 = dec(0)
for i in numsIn:
num1 += dec(i)
return rnd(dec(num1 / dec(len(numsIn))))
def sin(anglein, dr = degrad): #return sine of the supplied angle using the predetermined mode or the supplied mode
if dr == 'deg':
while anglein > 180:
anglein -= 360
while anglein < -180:
anglein += 360
angle = degToRad(anglein)
if dr == 'rad':
while anglein > pi:
anglein -= (2 * pi)
while anglein < -pi:
anglein += (2 * pi)
angle = anglein
return rnd(rawsin(dec(angle)), -terms)
def arcsin(ratioin, dr = degrad): #return arcsine of the supplied ratio using the predetermined mode or the supplied mode
if ratioin > 1 or ratioin < -1: #if the input is illegal
return False
attempt = dec(0) #start at 0
target = rnd(dec(ratioin), -terms) #identify the target value
#print('target is: {}'.format(target))
for i in range(-1, int(terms) + 1): #for each place from 10s to terms decimal place (use -i, not i)
#print('Editing place {0}'.format(10 ** -i)) #debugging
for j in range(10): #for 10 steps
#print('current attempt: {}'.format(attempt), end = ' ')
if rnd(sin(attempt, dr), -terms) == target:
if attempt < 0:
final = (attempt * dec(-1))
else:
final = attempt
#print('attempt: {0} final: {1}'.format(attempt, final))
return final
if rnd(sin(attempt, dr), -terms) < target:
#add some
attempt += (dec(10) ** -i)
#print('attempt: {}'.format(attempt), end = ' ')
if rnd(sin(attempt, dr), -terms) > target:
#subtract some
attempt -= (dec(10) ** -i)
#print('attempt: {}'.format(attempt), end = ' ')
#print('')
if attempt < 0:
final = (attempt * dec(-1))
else:
final = attempt
#print('attempt: {0} final: {1}'.format(attempt, final))
return (final)
def cos(anglein, dr = degrad): #return cosine of the supplied angle
if dr == 'deg':
return rawsin(degToRad(90 - anglein))
else:
angle = anglein
return rnd(rawsin(90 - angle), -terms)
def arccos(ratioin, dr = degrad): #return arccosine of the supplied ratio
if ratioin > 1 or ratioin < -1:
return False
attempt = dec(0) #start at 0
target = rnd(dec(ratioin), -terms) #identify the target value
#print('target is: {}'.format(target))
for i in range(-1, int(terms) + 1): #for each place from 10s to terms decimal place (use -i, not i)
#print('Editing place {0}'.format(10 ** -i)) #debugging
for j in range(10): #for 10 steps
#print('current attempt: {}'.format(attempt), end = ' ')
if rnd(cos(attempt, dr), -terms) == target:
if attempt < 0:
final = (attempt * dec(-1))
else:
final = attempt
#print('attempt: {0} final: {1}'.format(attempt, final))
return final
if rnd(cos(attempt, dr), -terms) < target:
#add some
attempt += (dec(10) ** -i)
#print('attempt: {}'.format(attempt), end = ' ')
if rnd(cos(attempt, dr), -terms) > target:
#subtract some
attempt -= (dec(10) ** -i)
#print('attempt: {}'.format(attempt), end = ' ')
#print('')
if attempt < 0:
final = (attempt * dec(-1))
else:
final = attempt
#print('attempt: {0} final: {1}'.format(attempt, final))
return (final)
def tan(anglein, dr = degrad): #return tangent of the supplied angle
a = sin(anglein, dr)
b = cos(anglein, dr)
if (not a == 0) and (not b == 0):
return rnd((a / b), -terms)
else:
return False
def arctan(ratioin, dr = degrad): #return arctangent of the supplied ratio
if ratioin > 1 or ratioin < -1:
return False
attempt = dec(0) #start at 0
target = rnd(dec(ratioin), -terms) #identify the target value
#print('target is: {}'.format(target))
for i in range(-1, int(terms) + 1): #for each place from 10s to terms decimal place (use -i, not i)
#print('Editing place {0}'.format(10 ** -i)) #debugging
for j in range(10): #for 10 steps
#print('current attempt: {}'.format(attempt), end = ' ')
if rnd(tan(attempt, dr), -terms) == target:
if attempt < 0:
final = (attempt * dec(-1))
else:
final = attempt
#print('attempt: {0} final: {1}'.format(attempt, final))
return final
if rnd(tan(attempt, dr), -terms) < target:
#add some
attempt += (dec(10) ** -i)
#print('attempt: {}'.format(attempt), end = ' ')
if rnd(tan(attempt, dr), -terms) > target:
#subtract some
attempt -= (dec(10) ** -i)
#print('attempt: {}'.format(attempt), end = ' ')
#print('')
if attempt < 0:
final = (attempt * dec(-1))
else:
final = attempt
#print('attempt: {0} final: {1}'.format(attempt, final))
return (final)
def rawsin(anglein): #return the result of sine of the supplied angle, using radians
#This is the taylor series used.
#final = x - (x^3 / 3!) + (x^5 / 5!) - (x^7 / 7!) + (x^9 / 9!) - (x^11 / 11!)...
angle = dec(anglein)
final = angle
add = False
for i in range(3, int(terms) * 3, 2):
if add:
final += dec(angle ** i) / fact(i)
elif not add:
final -= dec(angle ** i) / fact(i)
add = not add
return final
def fact(intin): #return the factorial of the given integer, return False if not given an int
if intin == int(intin):
intout = 1
for i in range(1, intin + 1):
intout *= i
return intout
else:
return False
def rnd(numIn, decPlcIn = -terms, mode = 'fiveHigher'): #return the given number, rounded to the given decimal place.
#use 1 to indicate 10s, 0 to indicate 1s, -2 to indicate 100ths, etc.
num1 = dec(numIn)
decPlc = dec(decPlcIn)
if mode == 'fiveHigher':
return dec(str(dec(round(num1 * (dec(10) ** -decPlc))) * (dec(10) ** decPlc)).rstrip('0'))
elif mode == 'cutoff':
return dec(str(dec(int(num1 * (dec(10) ** -decPlc))) * (dec(10) ** decPlc)).rstrip('0'))
def root(numIn, rootVal):
num = dec(numIn)
rt = dec(dec(1) / rootVal)
num1 = num ** rt
return rnd(num1, -terms)
def quad(aIn, bIn, cIn): #Plugin for the quadratic formula. Provide a, b, and c.
a = dec(aIn)
b = dec(bIn)
c = dec(cIn)
try:
posResult = (-b + root((b ** dec(2)) - (dec(4) * a * c), 2)) / (dec(2) * a)
except:
posResult = False
try:
negResult = (-b - root((b ** dec(2)) - (dec(4) * a * c), 2)) / (dec(2) * a)
except:
negResult = False
return (posResult, negResult)

You are missing 1 call to self.openGLWidget.update(). There is a return statement in the instruction block of the if. The function is terminated at this point and the self.openGLWidget.update() instruction at the end of the code is never executed.
Add self.openGLWidget.update() right before return, to solve the issue:
class mainWindow(QMainWindow):
# [...]
def marchStep(self):
if not self.marchActive:
# [...]
self.currentStep = 0
if self.currentStep == len(self.marchPoints):
# [...]
self.meshPoints.clear()
self.marchingCube.hide()
self.openGLWidget.update() # <--------- ADD
return
if self.currentStep == 0:
self.marchingCube.show()
# [...]

Python: Point in polygon, boundary and vertex check (ray casting)

So I have written some code to check whether a point [(x,y)] lies within a polygon [(x,y), (x,y), (x,y), (x,y)] but the code fails if the point lies on a boundary or a vertex, I need this to be classed as lying within the polygon. This is the code:
def areasign(poly):
sumarea = 0
for i in range(0, len(poly)-1):
xi = poly[i][0]
yi = poly[i][1]
xj = poly[i+1][0]
yj = poly[i+1][1]
sumarea = sumarea + ((xi*yj)-(yi*xj))
if sumarea == 0: return 0
if sumarea < 0: return -1
if sumarea > 0: return 1
def lineintersection(xy, ij):
xyi = []
xyj = []
ijx = []
ijy = []
xyi.extend(xy)
xyj.extend(xy)
xyi.append(ij[0])
xyj.append(ij[1])
xyi.append(xy[0])
xyj.append(xy[0])
ijx.extend(ij)
ijy.extend(ij)
ijx.append(xy[0])
ijy.append(xy[1])
ijx.append(ij[0])
ijy.append(ij[0])
a = areasign(xyi)
b = areasign(xyj)
c = areasign(ijx)
d = areasign(ijy)
if (a!= b) and (c!=d):
return True
else:
return False
def openpointfile(fname):
p = []
f = open(fname)
for line in f:
line = line.replace('POINT(', '')
line = line.replace(')', '')
vals = line.split(' ')
res = map(float, vals)
ctuple = tuple(res)
p.append(ctuple)
print ctuple
f.close()
return p
points = openpointfile('C:/Users/Dan/Documents/Informatics/Data/Point_On_Line.txt')
def openpolygonfile(fname):
p = []
f = open(fname)
for line in f:
line = line.replace('POLYGON((', '')
line = line.replace('))', '')
s = line.split(',')
poly = []
for coord in s:
vals = coord.split(' ')
res = map(float, vals)
ctuple = tuple(res)
poly.append(ctuple)
p.append(poly)
f.close()
return p
polys = openpolygonfile('C:/Users/Dan/Documents/Informatics/Data/Polygon_On_Line.txt')
def pointinpoly(points, polys):
infinity = tuple([100000000.0, 100000010.0])
sum = 0
testline = (points, infinity)
for i in range(0, len(poly)-1):
start = poly[i]
end = poly[i+1]
line = (start, end)
l = lineintersection(line, testline)
if l == True:
sum = sum + 1
if sum % 2 == 0:
return False
else:
return True
pointcount = 0
for point in points:
pointcount = pointcount + 1
polycount = 0
for poly in polys:
polycount = polycount + 1
l = pointinpoly(point, poly)
res = 'Point ' + str(pointcount) + ' lies within Polygon ' + str(polycount) + ' = ' + str(l)
print l
print (res)
Like i said before this doesnt work if the point lies on a boundary or a vertex, i have this function that i found on here that seems to work but i can't find a way to get it my files into the correct format for the function and to get it to iterate oer a list of polygons.
def point_in_poly(x,y,poly):
# check if point is a vertex
if (x,y) in poly: return "IN"
# check if point is on a boundary
for i in range(len(poly)):
p1 = None
p2 = None
if i==0:
p1 = poly[0]
p2 = poly[1]
else:
p1 = poly[i-1]
p2 = poly[i]
if p1[1] == p2[1] and p1[1] == y and x > min(p1[0], p2[0]) and x < max(p1[0], p2[0]):
return "IN"
n = len(poly)
inside = False
p1x,p1y = poly[0]
for i in range(n+1):
p2x,p2y = poly[i % n]
if y > min(p1y,p2y):
if y <= max(p1y,p2y):
if x <= max(p1x,p2x):
if p1y != p2y:
xints = (y-p1y)*(p2x-p1x)/(p2y-p1y)+p1x
if p1x == p2x or x <= xints:
inside = not inside
p1x,p1y = p2x,p2y
if inside: return "IN"
else: return "OUT"
Any help on how to build that function into my existing code or any help on a new function that could be used to check if the point lies on the boundary of a polygon or on a vertex

A* Algorithm does not find shortest path

I am trying to implement the A* algorithm in python but have hit a problem when trying to find the path of this map:
X X X X X X X S = Start
0 0 0 X 0 0 0 E = End
0 S 0 X 0 E 0 X = Wall
0 0 0 X 0 0 0
0 0 0 0 0 0 0
I am using the Manhattan method. My implementation does find a path, but not the shortest one. The error starts on it's second move -- after moving right. At this point it can move up and the heuristic cost would be four (three right, one down) or down (three right, one up). Is there a way so it chooses down to get the shortest path?
Code:
class Node:
def __init__(self, (x, y), g, h, parent):
self.x = x
self.y = y
self.g = g
self.h = h
self.f = g+h
self.parent = parent
def __eq__(self, other):
if other != None:
return self.x == other.x and self.y == other.y
return False
def __lt__(self, other):
if other != None:
return self.f < other.f
return False
def __gt__(self, other):
if other != None:
return self.f > other.f
return True
def __str__(self):
return "(" + str(self.x) + "," + str(self.y) + ") " + str(self.f)
def find_path(start, end, open_list, closed_list, map, no_diag=True, i=1):
closed_list.append(start)
if start == end or start == None:
return closed_list
new_open_list = []
for x, y in [(-1,1),(-1,-1),(1,-1),(1,1),(0,-1),(0,1),(-1,0),(1,0)]:
full_x = start.x + x
full_y = start.y + y
g = 0
if x != 0 and y != 0:
if no_diag:
continue
g = 14
else:
g = 10
h = 10 * (abs(full_x - end.x) + abs(full_y - end.y))
n = Node((full_x,full_y),g,h,start)
if 0 <= full_y < len(map) and 0 <= full_x < len(map[0]) and map[full_y][full_x] != 1 and n not in closed_list:
if n in open_list:
if open_list[open_list.index(n)].g > n.g:
new_open_list.append(n)
else:
new_open_list.append(open_list[open_list.index(n)])
else:
new_open_list.append(n)
if new_open_list == None or len(new_open_list) == 0:
return find_path(start.parent, end, open_list, closed_list, map, no_diag, i-1)
new_open_list.sort()
return find_path(new_open_list[0], end, new_open_list, closed_list, map, no_diag)

You seem to be constructing a new open list for each node, which contains only that node's neighbors. This essentially makes your search a form of a depth-first search, while A* should be a best-first search.
You need to use one open list which will be updated with each node's neighbors as you visit that node. The old nodes in the open list must remain there until they are traversed and moved to the closed list.
Regarding what you said in your question, It's OK for the search to try moving up before down (since according to the heuristic, they are the same distance from the goal). What matters is that in the end, the path chosen will be the shortest.

Categories