Backpack corrections and updates for file validation

Lab3/graph.py

@@ -1,6 +1,8 @@
 import random
 import time
 import matplotlib.pyplot as plt
+import sys
+from typing import List
 
 def generateGraph(n: int, saturation: int):
     edges = (n * (n - 1)) // 2
@@ -49,7 +51,16 @@ def generateGraph(n: int, saturation: int):
 
     return graph
 
-def findEulerianCycle(graph_adj_sets):
+def graphFromMatrix(matrix: List[List[int]]):
+    n = len(matrix)
+    graph = {i: [] for i in range(n)}
+    for i in range(n):
+        for j in range(n):
+            if matrix[i][j] == 1:
+                graph[i].append(j)
+    return graph
+
+def findEulerianCycle(graph_adj_sets) -> List[int] | None:
     current_graph = {v: set(neighbors) for v, neighbors in graph_adj_sets.items()}
 
     if not current_graph:
@@ -113,6 +124,41 @@ def findHamiltonianCycle(graph):
     return None
 
 if __name__ == "__main__":
+    # Check if there was given a second argument, if yes run a test instead of the benchmark
+    if len(sys.argv) > 1:
+        file = sys.argv[1]
+        """
+        Format we are expecting:
+        0 0 1 1 1 1
+        0 0 1 1 0 0
+        1 1 0 0 1 1
+        1 1 0 0 1 1
+        1 0 1 1 0 1
+        1 0 1 1 1 0
+        """
+        with open(file, 'r') as f:
+            lines = f.readlines()
+            matrix = [list(map(int, line.strip().split())) for line in lines]
+            graph = graphFromMatrix(matrix)
+
+            euler = findEulerianCycle(graph)
+            hamilton = findHamiltonianCycle(graph)
+
+            if euler is None:
+                print("Eulerian cycle not found.")
+                exit(1)
+            if hamilton is None:
+                print("Hamiltonian cycle not found.")
+                exit(1)
+
+            # We were asked to print the cycles starting from 1. Add the first node to the end of the list to make it a cycle
+            # Expected: 1 6 5 4 6 3 5 1 4 2 3 1 | Actual: 1 3 2 4 1 5 3 6 4 5 6 1
+            print("Eulerian Cycle:", [v + 1 for v in euler ])
+            # 1 3 2 4 5 6 1 | Real: 1 3 2 4 5 6 1
+            print("Hamiltonian Cycle", [v + 1 for v in hamilton] + [hamilton[0] + 1])
+
+            exit(0)
+
     n_values = range(10, 26)  # Number of nodes to test
     saturations = [30, 70]  # Saturation levels to test
     results = {}

Lab3/hamilton.py

@@ -1,6 +1,8 @@
 import random
 import time
 import matplotlib.pyplot as plt
+import sys
+from typing import List
 
 def generate_hamiltonian_graph(n, saturation_percent):
     max_possible_edges = n * (n - 1) // 2
@@ -34,6 +36,16 @@ def generate_hamiltonian_graph(n, saturation_percent):
 
     return {k: list(v) for k, v in graph.items()}
 
+def graphFromMatrix(matrix: List[List[int]]):
+    n = len(matrix)
+    graph = {i: [] for i in range(n)}
+    for i in range(n):
+        for j in range(n):
+            if matrix[i][j] == 1:
+                graph[i].append(j)
+    return graph
+
+
 def find_all_hamiltonian_cycles(graph):
     n = len(graph)
     cycles = set()
@@ -65,6 +77,28 @@ def find_all_hamiltonian_cycles(graph):
     return list(cycles)
 
 if __name__ == "__main__":
+    if len(sys.argv) > 1:
+        file = sys.argv[1]
+        """
+        Format we are expecting:
+        0 0 1 1 1 1
+        0 0 1 1 0 0
+        1 1 0 0 1 1
+        1 1 0 0 1 1
+        1 0 1 1 0 1
+        1 0 1 1 1 0
+        """
+        with open(file, 'r') as f:
+            lines = f.readlines()
+            matrix = [list(map(int, line.strip().split())) for line in lines]
+            graph = graphFromMatrix(matrix)
+
+            cycles = find_all_hamiltonian_cycles(graph)
+
+            for cycle in cycles:
+                print(cycle)
+            exit(0)
+
     n_values = range(5, 15)
     saturation = 50
 

Lab4/backpack.py

@@ -4,18 +4,16 @@ import matplotlib.pyplot as plt
 import sys
 
 def greedy(n, weight, value, capacity ):
-    ratios = [(value[i] / weight[i], weight[i]) for i in range(n)]
+    pairs = list(zip(value, weight))
-    ratios.sort(reverse=True, key=lambda x: x[0])
+    pairs.sort(reverse=True, key=lambda x: x[0] / x[1])
 
-    current_weight = 0
     current_value = 0
-    items_taken = []
+    currentCapacity = capacity
 
-    for ratio, weight in ratios:
+    for i in range(n):
-        if current_weight + weight <= capacity and current_value + value[ratios.index((ratio, weight))] <= capacity:
+        if pairs[i][1] <= currentCapacity:
-            current_weight += weight
+            current_value += pairs[i][0]
-            current_value += value[ratios.index((ratio, weight))]
+            currentCapacity -= pairs[i][1]
-            items_taken.append(ratios.index((ratio, weight)))
 
     return current_value
 
@@ -61,6 +59,7 @@ def benchmark_containers(container_list, capacity):
         greedy_values.append(gr)
         dynamic_values.append(dyn)
 
+        print(f"greedy: {gr}, dynamic: {dyn}, rel_error: {(dyn - gr) / dyn * 100 if dyn != 0 else 0:.2f}%")
         rel_errors.append((dyn - gr) / dyn * 100 if dyn != 0 else 0)
 
     return greedy_times, dynamic_times, rel_errors
@@ -75,7 +74,7 @@ def benchmark_capacity(capacity_list, containers):
     # For each container number or capacity
     for capacity in capacity_list:
         weights = [random.randint(1, 10) for _ in range(containers)]
-        values = [random.randint(1, 20) for _ in range(containers)]
+        values = [random.randint(2, 20) for _ in range(containers)]
 
         # Dynamic
         start = time.time()
@@ -91,8 +90,9 @@ def benchmark_capacity(capacity_list, containers):
         dynamic_times.append(dyn_time)
         greedy_values.append(gr)
         dynamic_values.append(dyn)
+        print(f"greedy: {gr}, dynamic: {dyn}, rel_error: {(dyn - gr) / dyn * 100 if dyn != 0 else 0:.2f}%")
 
-        rel_errors.append(abs((dyn - gr) / dyn) * 100 if dyn != 0 else 0)
+        rel_errors.append((dyn - gr) / dyn * 100 if dyn != 0 else 0)
 
     return greedy_times, dynamic_times, rel_errors
 
@@ -115,20 +115,22 @@ if __name__ == "__main__":
             capacity = int(lines[3].strip())
 
             dynamic(n, weights, values, capacity, print_table=True)
+            print(greedy(n, weights, values, capacity))
         exit(0)
 
     # First test case - constant capacity, variable number of containers
-    containers_list = list(range(5, 101, 5))
+    containers_list = list(range(1, 51, 2))
 
     # Constant capacity of 20
     greedy_times, dynamic_times, rel_errors = benchmark_containers(containers_list, 20)
 
     plt.figure(figsize=(12,5))
     plt.subplot(1,2,1)
-    plt.plot(containers_list, greedy_times, label='Zachłanny', marker='o')
+    plt.plot(containers_list, greedy_times, label='Zachłanny', )
-    plt.plot(containers_list, dynamic_times, label='Dynamiczny', marker='o')
+    plt.plot(containers_list, dynamic_times, label='Dynamiczny', )
     plt.xlabel('Liczba kontenerów')
     plt.ylabel('Czas [ms]')
+    # plt.yscale('log', base=2)
     plt.title('Czas działania dla zmiennej liczby kontenerów (B=20)')
     plt.legend()
 
@@ -149,8 +151,8 @@ if __name__ == "__main__":
 
     plt.figure(figsize=(12,5))
     plt.subplot(1,2,1)
-    plt.plot(capacity_list, greedy_times, label='Zachłanny', marker='o')
+    plt.plot(capacity_list, greedy_times, label='Zachłanny' )
-    plt.plot(capacity_list, dynamic_times, label='Dynamiczny' , marker='o')
+    plt.plot(capacity_list, dynamic_times, label='Dynamiczny')
     plt.xlabel('Pojemność')
     plt.ylabel('Czas [ms]')
     plt.title('Czas działania dla zmiennej pojemności (n=50)')