def main():
"""Use this program to compare and contrast four graph searching algorithms."""
map_40 = load_map_40()
map_10 = load_map_10()
map_simple = load_map_simple()
algorithms = [a_star, uniform_cost, breath_first, depth_first]
# The loop below will execute the same search using each of the four algorithms.
# Experiment with different maps and searches to understand the attributes,
# performance characteristics, and code of each algorithm.
graph = map_40
start_node = 5
goal_node = 34
print(f"Nodes in Map: {len(graph.intersections)} \n")
for algo in algorithms:
method = algo.SearchAlgo(graph, start_node, goal_node)
method.search()
print(f"Algorithm: {method.algorithm_name}")
print(f"Path: {method.path}")
print(f"Path length: {method.path_length}")
print(f"Number of nodes visited: {len(method.visited)} ({len(method.visited) / len(method.map.intersections) * 100}%)")
print(f"Nodes visited:", ', '.join(map(str, method.visited)))
print("")
def test(shortest_path_function):
map_40 = load_map_40()
correct = 0
for start, goal, answer_path in MAP_40_ANSWERS:
path = shortest_path_function(map_40, start, goal).path
if path == answer_path:
correct += 1
else:
print("For start:", start, "Goal: ", goal, "Your path:", path,
"Correct: ", answer_path)
if correct == len(MAP_40_ANSWERS):
print("All tests pass! Congratulations!")
else:
print("You passed", correct, "/", len(MAP_40_ANSWERS), "test cases")
def main():
# interactive test
map_10 = load_map_10()
map_40 = load_map_40()
print(f"Testing path planner...")
start_node = 5
goal_node = 34
planner = PathPlanner(map_40, start_node, goal_node)
path = planner.path
print(f"Start Node: {start_node}")
print(f"Goal Node: {goal_node}")
print(f"Resulting path: {path}")
if path == [5, 16, 37, 12, 34]:
print(f"Great! Your code works for these inputs!\n")
else:
print("Something is off, your code produced the following:")
print(path, "\n")
# course test for validation of project
from test import test
print(f"Running project validation tests from Udacity...")
test(PathPlanner)
from helpers import load_map_40
from student_code import shortest_path
from test import test
map_40 = load_map_40()
path = shortest_path(map_40, 8, 24)
if path == [8, 14, 16, 37, 12, 17, 10, 24]:
print("great! Your code works for these inputs!")
else:
print("something is off, your code produced the following:")
print(path)
test(shortest_path)
y2 = intersections[node_2][1]
return math.sqrt((x1 - x2)**2 + (y1 - y2)**2)
def get_tentative_gScore(self, current, neighbor):
"""Returns the tentative g Score of a node"""
return self.get_gScore(current) + self.distance(current, neighbor)
def heuristic_cost_estimate(self, node):
""" Returns the heuristic cost estimate of a node """
return self.distance(node, self.goal)
def calculate_fscore(self, node):
"""Calculate the f score of a node. """
return self.get_gScore(node) + self.heuristic_cost_estimate(node)
def record_best_path_to(self, current, neighbor):
"""Record the best path to a node """
self.cameFrom[neighbor] = current
self.gScore[neighbor] = self.get_tentative_gScore(current, neighbor)
self.fScore[neighbor] = self.calculate_fscore(neighbor)
## Calculates shortest route from start to goal
# Modifiy start and goal to see different results!
start = 1
goal = 8
show_map(load_map_40(),
start=start,
goal=goal,
path=PathPlanner(load_map_40(), start, goal).path)
