logs

networkz/algorithms/approximation/firefighter_problem/Firefighter_Problem.py

@@ -318,12 +318,14 @@ def heuristic_maxsave(Graph:nx.DiGraph, budget:int, source:int, targets:list, sp
     logger.info(f"Starting the heuristic_maxsave function with source node {source}, budget {budget}, targets: {targets}, and spreading: {spreading}")
 
     clean_graph(Graph)
+    display_graph(Graph)
     infected_nodes = []
     vaccinated_nodes = []
     vaccination_strategy = []
     can_spread = True
     Graph.nodes[source]['status'] = Status.INFECTED.value
     infected_nodes.append(source)
+    display_graph(Graph)
     time_step = 1
 
     while can_spread:

networkz/algorithms/approximation/firefighter_problem/Utils.py

@@ -341,6 +341,7 @@ def spread_virus(graph:nx.DiGraph, infected_nodes:list)->bool:
                 graph.nodes[neighbor]['status'] = Status.INFECTED.value
                 new_infected_nodes.append(neighbor)
                 logger.debug("SPREAD VIRUS: Node " + f'{neighbor}' + " has been infected from node " + f'{node}')
+                display_graph(graph)
     infected_nodes.clear()
     for node in new_infected_nodes:
         infected_nodes.append(node)  
@@ -375,6 +376,7 @@ def spread_vaccination(graph:nx.DiGraph, vaccinated_nodes:list)->None:
                 graph.nodes[neighbor]['status'] = Status.VACCINATED.value
                 new_vaccinated_nodes.append(neighbor)
                 logger.debug("SPREAD VACCINATION: Node " + f'{neighbor}' + " has been vaccinated from node " + f'{node}')
+                display_graph(graph)
     vaccinated_nodes.clear()
     for node in new_vaccinated_nodes:
         vaccinated_nodes.append(node)
@@ -401,6 +403,7 @@ def vaccinate_node(graph:nx.DiGraph, node:int)->None:
     """
     graph.nodes[node]['status'] = Status.DIRECTLY_VACCINATED.value
     logger.info("Node " + f'{node}' + " has been directly vaccinated")
+    display_graph(graph)
     return
 
 def clean_graph(graph:nx.DiGraph)->None:
@@ -577,7 +580,7 @@ def calculate_vaccine_matrix(layers:list, min_cut_nodes_grouped:dict)->np.matrix
                 value = N_j / (j + 1) 
                 matrix[i][j] = value
 
-    logger.info(f"Vaccination Matrix Before Conversion: {matrix}")
+    logger.info(f"Vaccination Matrix Before Conversion:\n{matrix}")
     return matrix
 
 def matrix_to_integers_values(matrix: np.matrix) -> np.matrix:
@@ -649,7 +652,7 @@ def matrix_to_integers_values(matrix: np.matrix) -> np.matrix:
             else:
                 integral_matrix[i, j] = np.floor(matrix[i, j])
 
-    logger.info(f"Integral and final Matrix: {integral_matrix}")
+    logger.info(f"Integral and final Matrix:\n{integral_matrix}")
     return np.matrix(integral_matrix)
 
 

networkz/algorithms/approximation/firefighter_problem/main.py

@@ -20,6 +20,9 @@
 """
 
 import logging
+import json
+logger = logging.getLogger(__name__)
+
 
 # This is a fix for an issue where the top one has to be exclusive for pytest to work
 # and the bottom one needs to be exclusive for running this from terminal to work
@@ -38,22 +41,28 @@ def setup_global_logger(level: int = logging.DEBUG):
     root_logger.setLevel(level)
     root_logger.addHandler(handler)
 
-setup_global_logger()
-
-logger = logging.getLogger(__name__)
-
 
 if __name__ == "__main__":
     import doctest
-    result = doctest.testmod(firefighter_problem, verbose=True)
-    logger.info(f"Doctest results: {result}")
-
-    #G3 = nx.DiGraph() 
-    #G3.add_nodes_from([0,1,2,3,4,5,6,7,8], status="vulnerable")
-    #G3.add_edges_from([(0,2),(0,4),(0,5),(2,1),(2,3),(4,1),(4,6),(5,3),(5,6),(5,7),(6,7),(6,8),(7,8)])
-    #logger.info("=" * 150)
-    #logger.info(spreading_minbudget(G3,0,[2,6,1,8]))
-    #print(spreading_maxsave(G3,1, 0,[2,6,1,8])[1])
+    setup_global_logger(level=logging.DEBUG)
+
+    # result = doctest.testmod(firefighter_problem, verbose=True)
+    # logger.info(f"Doctest results: {result}")
+
+    G3 = nx.DiGraph() 
+    G3.add_nodes_from([0,1,2,3,4,5,6,7,8])
+    G3.add_edges_from([(0,2),(0,4),(0,5),(2,1),(2,3),(4,1),(4,6),(5,3),(5,6),(5,7),(6,7),(6,8),(7,8)])
+    logger.info("=" * 150)
+    #print(spreading_maxsave(G3,source=0,targets=[2,6,1,8],budget=1))
+    #print(spreading_minbudget(G3,source=0,targets=[2,6,1,8]))
+
+    # with open("networkz/algorithms/tests/test_firefighter_problem/graphs.json", "r") as file:
+    #     json_data = json.load(file)
+    # graphs = parse_json_to_networkx(json_data)
+
+    # G2 = graphs["Dirlay_Graph-2"]
+    # print(non_spreading_dirlaynet_minbudget(G2,src=0,targets=[2,4]))
+    print(spreading_maxsave(G3,1, 0,[2,6,1,8])[1])
     # logger.info("=" * 150)
-    # logger.info(heuristic_minbudget(G3,0,[2,6,1,8], True))
+    #logger.info(heuristic_minbudget(G3,0,[2,6,1,8], True))