class TSPth(unittest.TestCase):
"""
(a) test case: to check the result of the shortest distance of the shortest path using Tarjan modification with heap.
(b) test data: graphs generated from main.py/ graph_generator.py
(c) expected result: results from built-in networkx_dijkstra_path_length function
(d) actual result: program output
"""
s_txt_file = "../data/heap/dense_stream_arcs.txt"
a_txt_file = "../data/array/dense_weighted_matrix.txt"
to_test_graph = convert_to_adj_list(s_txt_file)
nx_graph = nx.from_numpy_matrix(np.loadtxt(a_txt_file, skiprows=2))
source = 30
target = 56
def setUp(self):
source = self.source
target = self.target
self.to_test_result = tarjanstpath(self.to_test_graph, str(source), str(target))[0]
self.nx_result = nx.dijkstra_path_length(self.nx_graph, source, target)
def testDistance(self):
self.assertEqual(float(self.to_test_result), float(self.nx_result))
def heap_sparse(root):
txt = "../data/heap/sparse_stream_arcs.txt"
graph = convert_to_adj_list(txt)
start_time = time.time()
tarjanspathtree(graph, root)
end_time = time.time()
run_time = end_time - start_time
return run_time
def main():
print("Shortest path program")
print("1. Implementation of algorithms for large graph \n2. Solve Ballyskate problem \n"
"3. Solve Padgett Marriage Alliances \n4. Quit")
user_choice = int(input("Please select your choice: 1, 2 or 3 \n"))
while user_choice != 4:
if user_choice == 1:
print("You need to create a graph first.")
graph_generator()
print("Based on time complexity, we use an array data structure for the dense graph,"
"and a min heap for the sparse graph.")
while True:
structure_choice = input("Input type of data structure (array, heap) you want to use: ")
if structure_choice.lower() == "array":
DjikstraSthTree()
break
elif structure_choice.lower() == "heap":
TarjanSPathTree()
break
else:
print("Please choose 'array' or 'heap'.")
structure_choice = input("Input type of data structure (array, heap) you want to use: ")
elif user_choice == 2:
print("Solution for Ballyskate problem: ")
file = "data/heap/ballyskate_layout.txt"
graph = convert_to_adj_list(file)
print("Distance and the shortest path from node 1 to node p is: ", tarjanstpath(graph, '1', 'p'))
elif user_choice == 3:
print("Solution for Padgett Marriage Alliances problem:")
FloretineMarriage()
else:
print("Please choose 1, 2, or 3.")
print("Shortest path program")
print("1. Implementation of algorithms for large graph \n2. Solve Ballyskate problem \n"
"3. Solve Padgett Marriage Alliances \n4. Quit")
user_choice = int(input("Please select your choice: 1, 2, or 3.\n"))
print("Thank you!")
def TarjanSPathTree():
"""Implementation of Shortest path tree using Tarjain method for a sparse graph."""
file = "data/heap/sparse_stream_arcs.txt"
graph = convert_to_adj_list(file)
print("Our nodes in the graph is ", graph.keys())
initial_node = input("Input node which you want to start with: ")
while initial_node:
if initial_node in graph.keys():
spanning_tree = tarjanspathtree(graph, initial_node)
print("----------Solution----------")
for node, value in spanning_tree.items():
print("Distance and path from node", initial_node, "to node", node, "is: ", value)
choice = input("Do you want to choose another starting node? (y/n): ")
while choice.lower() != 'n':
if choice == "y":
TarjanSPathTree()
else:
print("Please choose y or n")
choice = input("Do you want to choose another starting node? (y/n): ")
break
else:
print("Please input a proper starting node.")
initial_node = input("Input node which you want to start with: ")
def FloretineMarriage():
"""Calculate the centrality measures of each nodes in Padgett data of Floretine Marriage Alliances."""
txt_input_file = "data/padgett.txt"
adj_list = convert_to_adj_list(txt_input_file)
graph = convert_to_graph(txt_input_file)
print(
"Centrality measures available: (1) degree, (2) eigenvector, (3) closeness, (4) and betweeness."
)
measure_choice = int(
input("Please choose measures you want to calculate (from 1 to 4) \n"))
while measure_choice:
if measure_choice == 1:
deg_dict = degree(graph)
for node in deg_dict.keys():
print("Degree centrality of node ", node, " is: ",
"{:.3f}".format(deg_dict[node]))
choice = input("Do you want to calculate other measures?? (y/n): ")
while choice.lower() != 'n':
if choice == "y":
FloretineMarriage()
else:
print("Please choose y or n")
choice = input(
"Do you want to calculate other measures?? (y/n): ")
break
if measure_choice == 2:
eig_dict = eigen_vector(graph)
for node in eig_dict.keys():
print("Eigenvector centrality of node ", node, " is: ",
"{:.3f}".format(eig_dict[node]))
choice = input("Do you want to calculate other measures?? (y/n): ")
while choice.lower() != 'n':
if choice == "y":
FloretineMarriage()
else:
print("Please choose y or n")
choice = input(
"Do you want to calculate other measures?? (y/n): ")
break
if measure_choice == 3:
closeness_dict = closeness(adj_list)
for node in closeness_dict.keys():
print("Closeness centrality of node ", node, " is: ",
"{:.3f}".format(closeness_dict[node]))
choice = input("Do you want to calculate other measures?? (y/n): ")
while choice.lower() != 'n':
if choice == "y":
FloretineMarriage()
else:
print("Please choose y or n")
choice = input(
"Do you want to calculate other measures?? (y/n): ")
break
if measure_choice == 4:
bw_dict = betweeness(graph)
for node in bw_dict.keys():
print("Betweeness centrality of node ", node, " is: ",
"{:.3f}".format(bw_dict[node]))
choice = input("Do you want to calculate other measures?? (y/n): ")
while choice.lower() != 'n':
if choice == "y":
FloretineMarriage()
else:
print("Please choose y or n")
choice = input(
"Do you want to calculate other measures?? (y/n): ")
break
else:
print("Please choose from 1 to 4")
measure_choice = int(
input(
"Please choose measures you want to calculate (from 1 to 4) \n"
))