def generate_guided_search_figure(G, positions, src, target):
"""Generate Guided Search solution .. ultimately omitted from book."""
if plt_error:
return None
import matplotlib.pyplot as plt
(G, positions, _) = tmg_load(highway_map())
plt.clf()
plot_gps(positions)
plot_highways(positions, G.edges())
def distance_gps(from_cell, to_cell):
"""These ids are indexed into positions to get GPS coordinates."""
return abs(positions[from_cell][0] -
positions[to_cell][0]) + abs(positions[from_cell][1] -
positions[to_cell][1])
node_from = guided_search(G, src, target, distance=distance_gps)
total = compute_distance(positions, node_from, src, target)
plot_node_from(positions, src, target, node_from, color='purple')
print(
'{0} total steps for Guided Search with distance={1:.1f} miles'.format(
len(path_to(node_from, src, target)) - 1, total))
plt.axis('off')
output_file = image_file('figure-mass-highway-guided.svg')
plt.savefig(output_file, format="svg")
print(output_file)
plt.clf()
return output_file
def generate_bfs_and_dijkstra_figure(src, target):
"""Generate BFS solution overlaying Massachusetts highway."""
if plt_error:
return None
import matplotlib.pyplot as plt
(G, positions, _) = tmg_load(highway_map())
(dist_to, edge_to) = dijkstra_sp(G, src)
print('Dijkstra shortest distance is {} total steps with distance={:.1f}'.
format(
len(edges_path_to(edge_to, src, target)) - 1, dist_to[target]))
path = edges_path_to(edge_to, src, target)
plt.clf()
plot_gps(positions)
plot_highways(positions, G.edges())
plot_path(positions, path)
node_from = bfs_search(G, src)
total = compute_distance(positions, node_from, src, target)
plot_node_from(positions, src, target, node_from, color='purple')
print(
'{0} total steps for Breadth First Search with distance={1:.1f} miles'.
format(len(path_to(node_from, src, target)) - 1, total))
plt.axis('off')
output_file = image_file('figure-mass-highway-bfs.svg')
plt.savefig(output_file, format="svg")
print(output_file)
plt.clf()
return output_file
def test_small_example(self):
from ch07.search import dfs_search, path_to
from ch07.challenge import path_to_recursive
G = nx.Graph()
self.small_example(G)
node_from = dfs_search(G, 'A2')
self.assertEqual(['A2', 'A3', 'A4', 'A5'],
path_to(node_from, 'A2', 'A5'))
self.assertEqual(['A2', 'A3', 'A4', 'A5'],
list(path_to_recursive(node_from, 'A2', 'A5')))
with self.assertRaises(ValueError):
path_to(node_from, 'A2', 'B2') # No path exists
with self.assertRaises(ValueError):
# No path exists: force issue by list(...)
list(path_to_recursive(node_from, 'A2', 'B2'))
def test_guided_search(self):
from ch07.maze import Maze, to_networkx, solution_graph, distance_to
from ch07.search import guided_search, path_to, node_from_field
import random
random.seed(15)
m = Maze(3, 5)
G = to_networkx(m)
# BFS search solution
node_from = guided_search(G, m.start(), m.end(), distance_to)
self.assertEqual((1, 2), node_from[(2, 2)])
# Create graph resulting from the BFS search results
F = node_from_field(G, node_from)
self.assertEqual(14, len(list(F.edges())))
# The actual solution is a two-edge, three node straight path
H = solution_graph(G, path_to(node_from, m.start(), m.end()))
self.assertEqual(2, len(list(H.edges())))
def generate_dfs_figure(src, target):
"""Generate DFS solution overlaying Massachusetts highway."""
if plt_error:
return None
import matplotlib.pyplot as plt
(G, positions, _) = tmg_load(highway_map())
plt.clf()
plot_gps(positions)
plot_highways(positions, G.edges())
node_from = dfs_search_recursive(G, src)
total = compute_distance(positions, node_from, src, target)
plot_node_from(positions, src, target, node_from, color='purple')
print('{0} total steps for Depth First Search with distance={1:.1f} miles'.
format(len(path_to(node_from, src, target)) - 1, total))
plt.axis('off')
output_file = image_file('figure-mass-highway-dfs.svg')
plt.savefig(output_file, format="svg")
print(output_file)
plt.clf()
return output_file