generate-router

back_end/a_star.py

@@ -68,5 +68,9 @@ def reconstruct_path():
                 distance.update({node_data[0]:g})
                 boundary_nodes.update({tuple(node_data):(g+h)})
     return []
-
-print(a_star([21.0347047,105.8143796],[21.0346086,105.8147965]))
+#3,6,14,16,9
+print(a_star([21.0347047,105.8143796],[21.0346086,105.8147965])) 
+print(a_star([21.0370748,105.8151156],[21.0335594,105.8170105])) 
+print(a_star([21.0372027,105.8149064],[21.034173,105.8172348])) 
+print(a_star([21.0379433,105.8133858],[21.0348241,105.8175344])) 
+print(a_star([21.0343185,105.8160597],[21.0419711,105.8163784])) 

back_end/nearest_point.py

@@ -28,5 +28,4 @@ def find_nearest_node(point):
     print("Execution time:",execution_time)
 
     return nearest_node_id
-
-print(find_nearest_node([21.0347047,105.8143797]))
+ #print(find_nearest_node([21.0347047,105.8143797]))

back_end/testRandoms.py

@@ -0,0 +1,61 @@
+import random
+import pandas as pd
+from a_star import a_star 
+# Read the CSV file into a DataFrame
+node_df = pd.read_csv("./data/nodes.csv")
+
+# Define a function to get a random node from the DataFrame
+def get_random_node():
+    # Get a random row index
+    random_index = random.randint(0, len(node_df) - 1)
+
+    # Get the row at the random index
+    random_node = node_df.loc[random_index, ['y', 'x']].tolist()
+
+    return random_node
+
+# Define a function to compare results
+def compare_results(a_star_result, other_program_result):
+    return a_star_result == other_program_result
+
+# Generate 1000 random test cases
+test_cases = []
+for _ in range(1000):
+    start_node = get_random_node()
+    end_node = get_random_node()
+    test_cases.append((start_node, end_node))
+
+# Compare results for each test case
+same_results = 0
+different_results = []
+for start_node, end_node in test_cases:
+    print(start_node, end_node)
+    # Run a_star.py and get the result
+    a_star_result = a_star(start_node, end_node)
+
+    # Run the other program and get the result
+
+    # TODO ORTHER PROGRAM
+    other_program_result = a_star(start_node, end_node)
+
+    # Compare the results
+    if compare_results(a_star_result, other_program_result):
+        same_results += 1
+    else:
+        different_results.append((start_node, end_node, a_star_result, other_program_result))
+
+# Calculate accuracy
+accuracy = same_results / 1000
+
+# Print accuracy
+print("Accuracy:", accuracy)
+
+# Print wrong cases
+if accuracy < 1:
+    print("Wrong cases:")
+    for case in different_results:
+        start_node, end_node, a_star_result, other_program_result = case
+        print("Case's input:", start_node, end_node)
+        print("Case's output of a_star.py:", a_star_result)
+        print("Case's output of the other program:", other_program_result)
+        print()