def a_star_shortest_path(start_node, dest_node):
"""
Test AStar's shortest path in comparison to networkx's shortest_path.
Parameters:
-----------
start_node: networkx Node
The starting node.
dest_node: networkx Node
The ending node.
Passing Criteria:
--------
Both path lengths must be the same.
"""
context = Context(strategies.StrategyAStar(graph, 0, 'vanilla'))
path = context.run_strategy_route(start_node, dest_node)
print("A star shortest path", path)
regular_path_length = graph_utils.get_path_length(graph, path)
nx_shortest_path = shortest_path(start_node, dest_node)
nx_shortest_path_length = graph_utils.get_path_length(
graph, nx_shortest_path)
if nx_shortest_path_length == regular_path_length:
print("Test Passed")
else:
print("Test Failed")
print("\n")
def a_star_max_elevation_grade(start_node, dest_node):
"""
Test AStar's min elevation path using grade as the weight.
Parameters:
-----------
start_node: networkx Node
The starting node.
dest_node: networkx Node
The ending node.
Passing Criteria:
--------
max_elevation path must have the smaller path length than the limit
and grade is less than regular grade.
"""
print("A star max elevation using grade as weight")
context = Context(strategies.StrategyAStar(graph, limit, 'max grade'))
path = context.run_strategy_route(start_node, dest_node)
print("Elevation path", path)
grade = graph_utils.get_average_grade(graph, path)
max_path_length = graph_utils.get_path_length(graph, path)
context = Context(strategies.StrategyAStar(graph, 0, 'vanilla'))
path = context.run_strategy_route(start_node, dest_node)
print("Vanilla path", path)
regular_grade = graph_utils.get_average_grade(graph, path)
regular_path_length = graph_utils.get_path_length(graph, path)
max_length = regular_path_length * (1 + limit)
print("Vanilla path length:", regular_path_length,
"\nMax Possible Path length:", max_length,
"\nLength of elevation path:", max_path_length)
print("Vanilla path Grade:", round(regular_grade, 2), "\nNew Grade:",
round(grade, 2))
if max_path_length <= max_length:
if grade >= regular_grade:
print("Test Passed")
else:
print("Test Passed: Path length. A* wasn't able to maximize grade")
else:
print("Test Failed")
print("\n")
def a_star_max_elevation(start_node, dest_node):
"""
Test AStar's max elevation path using elevation as the weight.
Parameters:
-----------
start_node: networkx Node
The starting node.
dest_node: networkx Node
The ending node.
Passing Criteria:
--------
max_elevation path must have the smaller path length than the limit
and max_elevation is greater than regular elevation.
"""
print("A star max elevation using elevation change as weight")
context = Context(
strategies.StrategyAStar(graph, limit, 'max elevation_change'))
path = context.run_strategy_route(start_node, dest_node)
print("Elevation path", path)
elevation = graph_utils.get_path_elevation(graph, path)
max_path_length = graph_utils.get_path_length(graph, path)
context = Context(strategies.StrategyAStar(graph, 0, 'vanilla'))
path = context.run_strategy_route(start_node, dest_node)
print("Vanilla path", path)
regular_elevation = graph_utils.get_path_elevation(graph, path)
regular_path_length = graph_utils.get_path_length(graph, path)
max_length = regular_path_length * (1 + limit)
print("Vanilla path length:", regular_path_length,
"\nMax Possible Path length:", max_length,
"\nLength of elevation path:", max_path_length)
print("Vanilla path Elevation:", regular_elevation, "\nNew Elevation:",
elevation)
if max_path_length <= max_length and elevation >= regular_elevation:
print("Test Passed")
else:
print("Test Failed")
print("\n")
def all_shortest_path(start, dest):
"""
Run all the shortest path algorithms: BFS, Dijkstra, A*
Parameters:
-----------
start: String
The starting address.
dest: String
The ending address.
Returns:
--------
times: An array of the time (as float values) it took each algorithm to run.
"""
try:
start_node = get_node_from_address(graph, start)
dest_node = get_node_from_address(graph, dest)
except Exception as e:
print(e)
print("Could not map address to node")
times = []
print("Running Dijkstra")
context = Context(strategies.StrategyDijkstra(graph, 0, 'vanilla'))
start_time = time()
path = context.run_strategy_route(start_node, dest_node)
end_time = time()
times.append(end_time - start_time)
print("Running BFS")
context = Context(strategies.StrategyBFS(graph, 0, 'vanilla'))
start_time = time()
path = context.run_strategy_route(start_node, dest_node)
end_time = time()
times.append(end_time - start_time)
print("Running A*")
context = Context(strategies.StrategyAStar(graph, 0, 'vanilla'))
start_time = time()
path = context.run_strategy_route(start_node, dest_node)
end_time = time()
times.append(end_time - start_time)
return times
def max_elevation_path_performance(start, dest, method):
"""
Run a performance test on the maximum elevation path of Dijkstra and A*.
Parameters:
-----------
start: String
The starting address.
dest: String
The ending address.
method: String
The method to use: Maximize Elevation Gain or Maximize Steepness.
Returns:
--------
times: An array of the time (as float values) it took each algorithm to run.
"""
try:
start_node = get_node_from_address(graph, start)
dest_node = get_node_from_address(graph, dest)
except Exception as e:
print(e)
print("Could not map address to node")
times = []
print("Running Dijkstra")
context = Context(strategies.StrategyDijkstra(graph, 0, method))
start_time = time()
path = context.run_strategy_route(start_node, dest_node)
end_time = time()
times.append(end_time - start_time)
print("Running A*")
context = Context(strategies.StrategyAStar(graph, 0, method))
start_time = time()
path = context.run_strategy_route(start_node, dest_node)
end_time = time()
times.append(end_time - start_time)
return times