Finalized Grid visiualization

Implemented A* Algorithm separatly to reduce clutering in traverse function
This commit is contained in:
2025-05-06 00:10:13 +02:00
parent 229fb4e4e2
commit 565d08290c
8 changed files with 501 additions and 150 deletions

88
P1/graph.py Normal file
View File

@@ -0,0 +1,88 @@
from prettytable import PrettyTable
from pygame.event import set_keyboard_grab
from utils import *
class Node:
def __init__(self, name, x=None, y=None, state="free"):
self.parent = None
self.name = name
self.edges = []
self.value = float('inf') # cost reaching this node
class Edge:
def __init__(self, edge):
self.start = edge[0]
self.end = edge[1]
self.value = edge[2]
class Graph:
def __init__(self, node_list, edges):
self.nodes = []
for name in node_list:
self.nodes.append(Node(name))
for e in edges:
e = (getNode(e[0], self.nodes), getNode(e[1], self.nodes), e[2])
self.nodes[next((i for i, v in enumerate(self.nodes) if v.name == e[0].name), -1)].edges.append(Edge(e))
self.nodes[next((i for i, v in enumerate(self.nodes) if v.name == e[1].name), -1)].edges.append(
Edge((e[1], e[0], e[2])))
def print(self):
node_list = self.nodes
t = PrettyTable([' '] + [i.name for i in node_list])
for node in node_list:
edge_values = ['X'] * len(node_list)
for edge in node.edges:
edge_values[next((i for i, e in enumerate(node_list) if e.name == edge.end.name), -1)] = edge.g
t.add_row([node.name] + edge_values)
print(t)
class Queue:
def __init__(self, type, sort_by = ''):
self.type = type
self.items = []
self.sort_by = sort_by
def empty(self):
return len(self.items) == 0
def pop(self):
if not self.empty():
if self.type == 'LIFO':
''' LIFO
queue = [node_0, node_1, ... , node_n]
-> pop node_n
'''
return self.items.pop()
else:
''' FIFO & PRIO
queue = [node_0, node_1, ... , node_n]
-> pop node_0
'''
return self.items.pop(0)
return None
def push(self, node):
self.items.append(node)
'''
queue = [node_0, node_1, ... , node_n] <- node_n+1
'''
if self.type == 'PRIO':
'''
Sorting so lowest cost/ value is at [0]
queue = [node_0 < node_1 < ... < node_n < node_n+1]
'''
if self.sort_by == '':
self.items.sort(key=lambda item: item.value)
elif self.sort_by == 'f':
self.items.sort(key=lambda item: item.f)

258
P1/grid.py Normal file
View File

@@ -0,0 +1,258 @@
import pygame
import math
from graph import Queue
# Define some colors
BLACK = (0, 0, 0)
WHITE = (255, 255, 255)
BLUE = (0, 0, 255)
GREEN = (0, 255, 0)
RED = (255, 0, 0)
ORANGE = (255, 165, 0)
GREY = (128, 128, 128)
WIDTH = 25
HEIGHT = 25
MARGIN = 3
grid_size = 20
class Field:
def __init__(self, x, y):
self.x = x
self.y = y
self.state = "free" # states: free, obstacale, start, target
self.g = float('inf')
self.h = 0
self.f = float('inf')
self.parent = None
def draw(self, screen):
# state based coloring
color = WHITE
if self.state == "obstacale":
color = BLACK
elif self.state == "start":
color = BLUE
elif self.state == "target":
color = GREEN
elif self.state == "path":
color = ORANGE
elif self.state == "visited":
color = WHITE
x_calc = (MARGIN + WIDTH) * self.x + MARGIN
y_calc = (MARGIN + HEIGHT) * (grid_size - 1 - self.y) + MARGIN # flipping
pygame.draw.rect(
screen,
color,
[x_calc, y_calc, WIDTH, HEIGHT]
)
# Render the heuristic value as text
if self.state != "obstacale": # Don't display on obstacles
# Create a font object
font = pygame.font.Font(None, 16) # None means default font, 14 is the size
# Round the heuristic value to 1 decimal place for better display
f_text = f"{self.f:.1f}"
# Render the text
text = font.render(f_text, True, BLACK) # True for anti-aliasing, BLACK for text color
# Calculate text position (centered in the rectangle)
text_rect = text.get_rect(center=(x_calc + WIDTH / 2, y_calc + HEIGHT / 2))
# Draw the text on the screen
screen.blit(text, text_rect)
class Grid:
def __init__(self, cols, rows):
self.cols = cols # x
self.rows = rows # y
self.grid = []
i = 0
while i < cols: # col = x
col = []
j = 0
while j < rows: # row = y
col.append(Field(i, j)) # (x,y)
j += 1
self.grid.append(col)
i += 1
self.start = None
self.target = None
def draw(self, screen):
for col in self.grid:
for field in col:
field.draw(screen)
def heuristic(self, field):
return math.sqrt((field.x - self.target[0]) ** 2 + (field.y - self.target[1]) ** 2)
def get_state(self, x, y):
return self.grid[x][y].state
def set_state(self, state, x, y):
if state == "free" or state == "obstacale" or state == "start" or state == "target" or state == "path" or state == "visited":
self.grid[x][y].state = state
def set_free(self, x, y):
self.set_state("free", x, y)
def set_obstacle(self, x, y):
self.set_state("obstacale", x, y)
def set_path(self, x, y):
if not (x == self.start[0] and y == self.start[1]) and not (x == self.target[0] and y == self.target[1]):
self.set_state("path", x, y)
def set_visited(self, x, y):
if not (x == self.start[0] and y == self.start[1]) and not (x == self.target[0] and y == self.target[1]):
self.set_state("visited", x, y)
def set_start(self, x, y):
# reset old start if it exits
if self.start:
self.set_free(self.start[0], self.start[1])
self.set_state("start", x, y)
self.grid[x][y].parent = self.grid[x][y]
self.grid[x][y].g = 0
self.grid[x][y].h = self.heuristic(self.grid[x][y])
self.start = (x, y)
def set_target(self, x, y):
# reset old target if it exits
if self.target:
self.set_free(self.target[0], self.target[1])
self.set_state("target", x, y)
self.target = (x, y)
'''
Initializing the Grid
'''
start = (0, 0)
target = (19, 19)
grid = Grid(grid_size, grid_size)
# check if start an target are valid
if 0 <= start[0] < grid.cols and 0 <= target[0] < grid.cols and 0 <= start[1] < grid.cols and 0 <= target[
1] < grid.cols:
grid.set_target(target[0], target[1])
grid.set_start(start[0], start[1])
for i in range(0, 10):
grid.set_obstacle(9, i)
for j in range(4, 10):
grid.set_obstacle(j, 9)
for i in range(9, 20):
grid.set_obstacle(16, i)
'''
Initializing A* Comps
'''
open = Queue('PRIO', 'f')
open.push(grid.grid[0][0])
closed = Queue('PRIO', 'f')
neighbors = []
path = []
pygame.init()
# window
window_width = grid_size * (WIDTH + MARGIN) + MARGIN
window_height = grid_size * (HEIGHT + MARGIN) + MARGIN
size = (window_width, window_height) # made size variable
screen = pygame.display.set_mode(size)
pygame.display.set_caption("A* Algorithm")
done = False
clock = pygame.time.Clock()
def a_star():
neighbor = None
while not open.empty():
current_field = open.pop()
if current_field.x == grid.target[0] and current_field.y == grid.target[1]:
path.append(current_field)
grid.set_path(current_field.x, current_field.y)
while not (current_field.x == grid.start[0] and current_field.y == grid.start[1]):
current_field = current_field.parent
path.insert(0, current_field)
grid.set_path(current_field.x, current_field.y)
break
closed.push(current_field)
grid.set_visited(current_field.x, current_field.y)
# Nachbarn finden
for dx, dy in [(0, -1), (-1, 0), (0, 1), (1, 0)]:
nx = current_field.x + dx
ny = current_field.y + dy
# Prüfen, ob der Nachbar gültig ist
if 0 <= nx < grid.cols and 0 <= ny < grid.rows:
neighbor = grid.grid[nx][ny]
# Hindernis oder bereits in geschlossener Liste -> überspringen
if neighbor.state == "obstacale" or neighbor in [item for item in closed.items]:
continue
# Neuen g-Wert berechnen
tentative_g = current_field.g + 1 # Kosten für einen Schritt = 1
# Wenn Nachbar nicht in offener Liste oder neuer Pfad besser
if neighbor not in [item for item in open.items] or tentative_g < neighbor.g:
neighbor.parent = current_field
neighbor.g = tentative_g
neighbor.h = grid.heuristic(neighbor)
neighbor.f = neighbor.g + neighbor.h
# Knoten zur offenen Liste hinzufügen oder aktualisieren
if neighbor not in [item for item in open.items]:
open.push(neighbor)
else:
# Queue aktualisieren
open.items.sort(key=lambda item: item.f)
def a_star_main():
global done
while not done:
for event in pygame.event.get():
if event.type == pygame.QUIT:
done = True
a_star()
screen.fill(BLACK)
grid.draw(screen)
# refresh display
pygame.display.flip()
# refreshrate
clock.tick(120)
a_star_main()
pygame.quit()

41
P1/main.py Normal file
View File

@@ -0,0 +1,41 @@
from grid import a_star_main
from search import ucs, bfs, dfs
from graph import Graph
# directed and weighted digraph
romania = Graph(['Or', 'Ne', 'Ze', 'Ia', 'Ar', 'Si', 'Fa',
'Va', 'Ri', 'Ti', 'Lu', 'Pi', 'Ur', 'Hi',
'Me', 'Bu', 'Dr', 'Ef', 'Cr', 'Gi'],
[
('Or', 'Ze', 71), ('Or', 'Si', 151),
('Ne', 'Ia', 87), ('Ze', 'Ar', 75),
('Ia', 'Va', 92), ('Ar', 'Si', 140),
('Ar', 'Ti', 118), ('Si', 'Fa', 99),
('Si', 'Ri', 80), ('Fa', 'Bu', 211),
('Va', 'Ur', 142), ('Ri', 'Pi', 97),
('Ri', 'Cr', 146), ('Ti', 'Lu', 111),
('Lu', 'Me', 70), ('Me', 'Dr', 75),
('Dr', 'Cr', 120), ('Cr', 'Pi', 138),
('Pi', 'Bu', 101), ('Bu', 'Gi', 90),
('Bu', 'Ur', 85), ('Ur', 'Hi', 98),
('Hi', 'Ef', 86)
])
def main():
# Task 1
graph = romania
ucs(graph, 'Si', 'Bu')
graph = romania
bfs(graph, 'Si', 'Bu')
graph = romania
dfs(graph, 'Si', 'Bu')
# Task 3 A*
a_star_main()
if __name__ == "__main__":
main()

67
P1/search.py Normal file
View File

@@ -0,0 +1,67 @@
from graph import *
from utils import getNode
def traverse(graph, frontier, start_node_name, target_node_name):
explored = []
path = []
# node
start_node = getNode(start_node_name, graph.nodes)
start_node.value = 0
target_node = getNode(target_node_name, graph.nodes)
frontier.push(start_node)
while not frontier.empty():
current_node = frontier.pop()
if not current_node == target_node:
explored.append(current_node.name)
for edge in current_node.edges:
child = edge.end
new_cost = current_node.value + edge.value
if not explored.__contains__(child.name):
child.parent = current_node
child.value = new_cost
frontier.push(child)
# UCS-only, updating the value and parent of node in the queue
elif frontier.type == 'PRIO' and new_cost < child.value:
for node in frontier.items:
if node.name == child.name:
node.value = new_cost
node.parent = current_node
frontier.items.sort(key=lambda item: item.value)
break
else:
path.append(current_node.name)
while not current_node == start_node:
current_node = current_node.parent
path.insert(0, current_node.name)
break
if len(path) == 0:
print('zwischen ' + start_node_name + ' und ' + target_node_name + ' konnte kein Pfad gefunden werden')
else:
print('From ' + start_node_name + ' to ' + target_node_name + ': ')
print('Path: ' + path.__str__().format())
print('Cost: ' + target_node.value.__str__())
def bfs(graph, start_node_name, target_node_name):
traverse(graph, Queue('FIFO'), start_node_name, target_node_name)
def dfs(graph, start_node_name, target_node_name):
traverse(graph, Queue('LIFO'), start_node_name, target_node_name)
def ucs(graph, start_node_name, target_node_name):
traverse(graph, Queue('PRIO'), start_node_name, target_node_name)

47
P1/utils.py Normal file
View File

@@ -0,0 +1,47 @@
def getNode(name, l):
return next((i for i in l if i.name == name), -1)
def print_grid_direct(self, path=None):
"""
Gibt das Grid in der Konsole aus, direkt wie es im Array gespeichert ist.
Die y-Achse nimmt nach unten zu (0 ist oben), entsprechend der Array-Struktur.
Optionaler Parameter 'path' ist eine Liste von (x,y)-Koordinaten, die den Pfad darstellen.
"""
# Symbole für verschiedene Zustände
symbols = {
"free": ".",
"obstacale": "#", # Tippfehler aus Original-Code beibehalten
"start": "S",
"target": "G",
"path": "o"
}
# Ausgabe des Grids mit Koordinatenachsen
print("\n ", end="")
# Obere x-Achsen-Beschriftung
for x in range(self.cols):
print(f"{x:2d}", end=" ")
print("\n " + "-" * (self.cols * 3))
# Grid mit y-Achsen-Beschriftung
for y in range(self.rows):
print(f"{y:2d} |", end=" ")
for x in range(self.cols):
field = self.grid[x][y]
if path and (x, y) in path and field.state != "start" and field.state != "target":
print(f"{symbols['path']:2s}", end=" ")
else:
print(f"{symbols[field.state]:2s}", end=" ")
print() # Zeilenumbruch
print("\nLegende:")
print(" . = frei")
print(" # = Hindernis")
print(" S = Start")
print(" G = Ziel")
print(" o = Pfad")
# Zusätzliche Statistiken, falls ein Pfad vorhanden ist
if path:
print(f"Pfadlänge: {len(path)} Felder")

View File

@@ -1,65 +0,0 @@
from prettytable import PrettyTable
from utils import *
class Node:
def __init__(self, name):
self.parent = None
self.name = name
self.edges = []
self.value = 0 # cost reaching this node
class Edge:
def __init__(self, edge):
self.start = edge[0]
self.end = edge[1]
self.value = edge[2]
class Graph:
def __init__(self, node_list, edges):
self.nodes = []
for name in node_list:
self.nodes.append(Node(name))
for e in edges:
e = (getNode(e[0],self.nodes), getNode(e[1], self.nodes), e[2])
self.nodes[next((i for i,v in enumerate(self.nodes) if v.name == e[0].name), -1)].edges.append(Edge(e))
self.nodes[next((i for i,v in enumerate(self.nodes) if v.name == e[1].name), -1)].edges.append(Edge((e[1], e[0], e[2])))
def print(self):
node_list = self.nodes
t = PrettyTable([' '] +[i.name for i in node_list])
for node in node_list:
edge_values = ['X'] * len(node_list)
for edge in node.edges:
edge_values[ next((i for i,e in enumerate(node_list) if e.name == edge.end.name) , -1)] = edge.value
t.add_row([node.name] + edge_values)
print(t)
class Queue:
def __init__(self, type):
self.type = type
self.items = []
def empty(self):
return len(self.items) == 0
def pop(self):
if not self.empty():
if self.type=='FIFO':
return self.items.pop(0)
else:
return self.items.pop()
return None
def push(self, node):
self.items.append(node)
if self.type=='PRIO':
# Sorting reverse, because nodes with lowest cost/ value should be prioritized
self.items.sort(key = lambda item: item.value, reverse=True)

83
main.py
View File

@@ -1,83 +0,0 @@
from graph import Graph, Node, Queue
from utils import getNode
# directed and weighted digraph
romania = Graph( ['Or', 'Ne', 'Ze', 'Ia', 'Ar', 'Si', 'Fa',
'Va', 'Ri', 'Ti', 'Lu', 'Pi', 'Ur', 'Hi',
'Me', 'Bu', 'Dr', 'Ef', 'Cr', 'Gi'],
[
('Or', 'Ze', 71), ('Or', 'Si', 151),
('Ne', 'Ia', 87), ('Ze', 'Ar', 75),
('Ia', 'Va', 92), ('Ar', 'Si', 140),
('Ar', 'Ti', 118), ('Si', 'Fa', 99),
('Si', 'Ri', 80), ('Fa', 'Bu', 211),
('Va', 'Ur', 142), ('Ri', 'Pi', 97),
('Ri', 'Cr', 146), ('Ti', 'Lu', 111),
('Lu', 'Me', 70), ('Me', 'Dr', 75),
('Dr', 'Cr', 120), ('Cr', 'Pi', 138),
('Pi', 'Bu', 101), ('Bu', 'Gi', 90),
('Bu', 'Ur', 85), ('Ur', 'Hi', 98),
('Hi', 'Ef', 86)
] )
def search(graph, queue, start_node_name, target_node_name):
visited_nodes = [] # Nodes which have been visited
path = []
start_node = getNode(start_node_name, graph.nodes)
target_node = getNode(target_node_name, graph.nodes)
start_node.value = 0
queue.push(start_node)
while not queue.empty():
current_node = queue.pop()
visited_nodes.append(current_node.name)
if not current_node == target_node:
for edge in current_node.edges:
neighbor = edge.end
condition = not visited_nodes.__contains__(neighbor.name)
new_cost = current_node.value + edge.value
# UCS
if queue.type == 'PRIO':
condition = not visited_nodes.__contains__(neighbor.name) and new_cost < neighbor.value
# works with digraph, because current_node is marked at this point, a cycle is not possible
if condition:
neighbor.parent = current_node
neighbor.value = new_cost
queue.push(neighbor)
else:
path.append(current_node.name)
while not current_node == start_node:
current_node = current_node.parent
path.insert(0, current_node.name)
if path.__len__() == 0:
print('zwischen ' + start_node_name + ' und ' + target_node_name + ' konnte kein Pfad gefunden werden')
else:
print('From ' + start_node_name + ' to ' + target_node_name + ': ')
print('Path: ' + path.__str__().format())
print('Cost: ' + target_node.value.__str__())
def bfs(graph, start_node_name, target_node_name):
search(graph,Queue('FIFO'),start_node_name, target_node_name)
def dfs(graph, start_node_name, target_node_name):
search(graph,Queue('LIFO'),start_node_name, target_node_name)
def utc(graph, start_node_name, target_node_name):
search(graph,Queue('PRIO'),start_node_name, target_node_name)
def main():
bfs(romania, 'Ti', 'Bu')
dfs(romania, 'Ti', 'Bu')
utc(romania, 'Or', 'Si')
if __name__ == "__main__":
main()

View File

@@ -1,2 +0,0 @@
def getNode(name, l):
return next(( i for i in l if i.name == name), -1 )