master > master: code py - display verbessert

code/python/src/algorithms/rucksack/algorithms.py

@@ -62,23 +62,31 @@ def rucksack_greedy_algorithm(
                 vector[i] = (capacity - weight_total)/weights[i];
             break;
 
-    # verbose output hier behandeln (irrelevant für Algorithmus):
+    # Aspekte der Lösung speichern:
-    if verbose:
+    soln = Solution(
-        repr = display_greedy(vector=vector, values=values);
-        print('');
-        print('\x1b[1mRucksack Problem - Greedy\x1b[0m');
-        print('');
-        print(repr);
-        print('');
-
-    # Lösung ausgeben
-    return Solution(
         vector = vector,
         items = items[rucksack].tolist(),
         weights = weights[rucksack].tolist(),
         values = values[rucksack].tolist(),
     );
 
+    # verbose output hier behandeln (irrelevant für Algorithmus):
+    if verbose:
+        expr_value = display_sum(vector=soln.vector, values=values);
+        expr_weight = display_sum(vector=soln.vector, values=weights);
+        print('');
+        print('\x1b[1mRucksack Problem - Greedy\x1b[0m');
+        print('');
+        print(f'Rucksack: {", ".join(soln.items)}.');
+        if fractional:
+            print(f'Vector: {soln.vector_support}');
+        print(f'max. Value ≈ {expr_value}');
+        print(f'∑ Weights  = {expr_weight}');
+        print('');
+
+    # Lösung ausgeben
+    return soln;
+
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 # METHOD branch and bound algorithm
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -122,23 +130,33 @@ def rucksack_branch_and_bound_algorithm(
                 lb_estimate = lb;
                 vector = A;
 
+    # Aspekte der Lösung speichern
+    rucksack = vector.indexes_one; # Indexes von Items im Rucksack
+    soln = Solution(
+        vector = vector.decision,
+        items = items[rucksack].tolist(),
+        values = values[rucksack].tolist(),
+        weights = weights[rucksack].tolist(),
+    );
+
     # verbose output hier behandeln (irrelevant für Algorithmus):
     if verbose:
+        expr_value = display_sum(vector=soln.vector, values=values);
+        expr_weight = display_sum(vector=soln.vector, values=weights);
         repr = display_branch_and_bound(values=values, steps=logged_steps);
         print('');
         print('\x1b[1mRucksack Problem - Branch & Bound\x1b[0m');
         print('');
         print(repr);
         print('');
+        print(f'Rucksack: {", ".join(soln.items)}.');
+        print(f'max. Value ≈ {expr_value}');
+        print(f'∑ Weights  = {expr_weight}');
+        print('');
+
 
     # Lösung ausgeben
-    rucksack = vector.indexes_one; # Indexes von Items im Rucksack
+    return soln;
-    return Solution(
-        vector = vector.decision,
-        items = items[rucksack].tolist(),
-        values = values[rucksack].tolist(),
-        weights = weights[rucksack].tolist(),
-    );
 
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 # AUXILIARY METHOD resort

code/python/src/algorithms/rucksack/display.py

@@ -15,7 +15,7 @@ from src.models.stacks import *;
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 __all__ = [
-    'display_greedy',
+    'display_sum',
     'display_branch_and_bound',
 ];
 
@@ -23,7 +23,7 @@ __all__ = [
 # METHODS display
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-def display_greedy(
+def display_sum(
     vector: Union[List[int], List[float]],
     values: np.ndarray,
 ) -> str:
@@ -46,7 +46,7 @@ def display_branch_and_bound(
             rows.append((f'{lb_estimate:g}', f'{lb:g}', S));
         else:
             used_vectors.append(u)
-            rows.append((f'{lb_estimate:g}', display_greedy(vector=u, values=values), S));
+            rows.append((f'{lb_estimate:g}', display_sum(vector=u, values=values), S));
 
     table = pd.DataFrame(rows) \
         .rename(columns={0: 'b', 1: 'g(TOP(S))', 2: 'S'}) \

code/python/src/models/rucksack/solution.py

@@ -34,6 +34,10 @@ class Solution(SolutionRaw):
     def support(self) -> List[float]:
         return [ i for i, v in enumerate(self.vector) if v > 0 ];
 
+    @property
+    def vector_support(self) -> List[float]:
+        return [ v for v in self.vector if v > 0 ];
+
     @property
     def total_weight(self) -> float:
         return sum([ self.vector[i]*x for (i, x) in zip(self.support, self.weights) ]);