master > master: code py - fügte option hinzu, um auch 0-costs anzuzeigen

- Abdunkeln in Summen jetzt nicht bei Werten

code/python/assets/config.yaml

@@ -30,3 +30,5 @@ options:
       - TREE
   rucksack:
     verbose: true
+    show:
+      - ALL-WEIGHTS

code/python/models/config-schema.yaml

@@ -53,7 +53,7 @@ components:
         - tsp
         - tarjan
         - hirschberg
-        - rucksack-branch-and-bound
+        - rucksack
       properties:
         log-level:
           $ref: '#/components/schemas/EnumLogLevel'
@@ -117,12 +117,16 @@ components:
               default: []
         rucksack:
           type: object
-          required:
-            - verbose
+          required: []
           properties:
             verbose:
               type: boolean
               default: false
+            show:
+              type: array
+              items:
+                $ref: '#/components/schemas/EnumRucksackShow'
+              default: []
     # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
     # Enum LogLevel
     # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -148,8 +152,17 @@ components:
     # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
     EnumHirschbergShow:
       description: |-
-        Enumeration of verbosity options for Hirschberg
+        Enumeration of display options for Hirschberg
       type: string
       enum:
         - TREE
         - ATOMS
+    # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+    # Enum Rucksack - display options
+    # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+    EnumRucksackShow:
+      description: |-
+        Enumeration of display options for the Rucksack problem
+      type: string
+      enum:
+        - ALL-WEIGHTS

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

@@ -83,7 +83,7 @@ def rucksack_greedy_algorithm(
 
     # verbose output hier behandeln (irrelevant für Algorithmus):
     if verbose:
-        repr_rucksack = display_rucksack(items=items[rucksack], costs=costs[rucksack], values=values[rucksack], choice=np.asarray(choice)[rucksack]);
+        repr_rucksack = display_rucksack(items=items, costs=costs, values=values, choice=choice);
         print('\x1b[1mEingeschätzte Lösung\x1b[0m');
         print('');
         print(f'Mask: [{", ".join(map(str, soln.choice))}]');
@@ -173,7 +173,7 @@ def rucksack_branch_and_bound_algorithm(
     # verbose output hier behandeln (irrelevant für Algorithmus):
     if verbose:
         repr = display_branch_and_bound(values=values, steps=logged_steps);
-        repr_rucksack = display_rucksack(items=items[rucksack], costs=costs[rucksack], values=values[rucksack], choice=np.asarray(mask.choice)[rucksack]);
+        repr_rucksack = display_rucksack(items=items, costs=costs, values=values, choice=mask.choice);
         print(repr);
         print('');
         print('\x1b[1mLösung\x1b[0m');

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

@@ -9,6 +9,8 @@ from src.thirdparty.code import *;
 from src.thirdparty.maths import *;
 from src.thirdparty.types import *;
 
+from src.setup import config;
+from models.generated.config import *;
 from src.models.stacks import *;
 from src.models.rucksack import *;
 
@@ -62,9 +64,17 @@ def display_rucksack(
     items: np.ndarray,
     costs: np.ndarray,
     values: np.ndarray,
-    choice: np.ndarray,
+    choice: List[Fraction],
 ) -> str:
+    show_options = config.OPTIONS.rucksack.show;
     render = lambda r: f'{r:g}';
+    choice = np.asarray(choice);
+    rucksack = np.where(choice > 0);
+    if not(EnumRucksackShow.all_weights in show_options):
+        items = items[rucksack];
+        costs = costs[rucksack];
+        values = values[rucksack];
+        choice = choice[rucksack];
     table = pd.DataFrame({
         'items':  items.tolist() + ['----', '∑'],
         'nr':  list(map(str, choice))
@@ -132,15 +142,22 @@ def display_sum(
     indexes: List[int] = [],
     as_maximum: bool = True,
 ) -> str:
+    show_options = config.OPTIONS.rucksack.show;
+    show_all_weights = (EnumRucksackShow.all_weights in show_options);
+
     def render(x: Tuple[bool, Fraction, float]):
         b, u, value = x;
-        expr = f'\x1b[91m{value:g}\x1b[0m' if b else f'\x1b[2m{value:g}\x1b[0m';
-        return expr if u == 1 else f'\x1b[4;2m{u}\x1b[0m\x1b[2m·\x1b[0m{expr}';
+        expr = f'\x1b[91m{value:g}\x1b[0m' if b else f'\x1b[0m{value:g}\x1b[0m';
+        if not show_all_weights and u == 1:
+            return expr;
+        return f'\x1b[2m{u}\x1b[0m\x1b[2m·\x1b[0m{expr}';
 
     parts = [ (i in indexes, u, x) for i, (u, x) in enumerate(zip(choice, values)) ];
     if not (order is None):
         parts = [ parts[j] for j in order ];
-    parts = list(filter(lambda x: x[1] > 0, parts));
+    if not show_all_weights:
+        parts = list(filter(lambda x: x[1] > 0, parts));
+
     value = sum([ u*x for _, u, x in parts ]);
     expr = '\x1b[2m+\x1b[0m'.join(map(render, parts));