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# Examen 2024
---
_**201.1 Algorithmes et Structures de données**_
![unit tests workflow](https://git.kb28.ch/HEL/AlgoDS-Examen2024/actions/workflows/tests.yaml/badge.svg)
Voici mes réponses pour l'examen 2024 d'_Algorithmes et Structures de données_ ainsi que les tests unitaires fournis.
## Exercice 1
<table>
<tr>
<td><strong>But</strong></td>
<td>Compter le nombre de triangles dans un graphe</td>
</tr>
<tr>
<td><strong>Input</strong></td>
<td>Liste des arêtes du graphe</td>
</tr>
<tr>
<td><strong>Output</strong></td>
<td>Nombre de triangles</td>
</tr>
<tr>
<td><strong>Signature</strong></td>
<td>
```python
def countTriangles(
edges: list[tuple[int, int]]
) -> int:
```
</td>
</tr>
</table>
[Source](https://git.kb28.ch/HEL/AlgoDS-Examen2024/src/branch/main/src/ex1_triangles.py)
/
[Tests](https://git.kb28.ch/HEL/AlgoDS-Examen2024/src/branch/main/tests/test_ex1.py)
## Exercice 2
<table>
<tr>
<td><strong>But</strong></td>
<td>Calculer le plus grand nombre d'émission complète consécutives qui peuvent être enregistrée sur un disque de taille finie</td>
</tr>
<tr>
<td><strong>Input</strong></td>
<td>Liste des durées des émissions, durée d'enregistrement totale maximum</td>
</tr>
<tr>
<td><strong>Output</strong></td>
<td>Nombre d'émission consécutives complètes enregistrables maximum</td>
</tr>
<tr>
<td><strong>Signature</strong></td>
<td>
```python
def startRecordingAt(
tv_show: list[int],
hard_drive_memory: int
) -> int:
```
</td>
</tr>
</table>
[Source](https://git.kb28.ch/HEL/AlgoDS-Examen2024/src/branch/main/src/ex2_tv.py)
/
[Tests](https://git.kb28.ch/HEL/AlgoDS-Examen2024/src/branch/main/tests/test_ex2.py)
## Exercice 3
<table>
<tr>
<td><strong>But</strong></td>
<td>Calculer le score maximum en prenant tour à tour un des côtés d'une série de cartes</td>
</tr>
<tr>
<td><strong>Input</strong></td>
<td>Liste des cartes (valeurs)</td>
</tr>
<tr>
<td><strong>Output</strong></td>
<td>Score maximum face à un adversaire optimal</td>
</tr>
<tr>
<td><strong>Signature</strong></td>
<td>
```python
def tauntScore(
cards: list[int]
) -> int:
```
</td>
</tr>
</table>
[Source](https://git.kb28.ch/HEL/AlgoDS-Examen2024/src/branch/main/src/ex3_cards.py)
/
[Tests](https://git.kb28.ch/HEL/AlgoDS-Examen2024/src/branch/main/tests/test_ex3.py)
## Exercice 4
<table>
<tr>
<td><strong>But</strong></td>
<td>Trouver la meilleure manière de déplacer des meubles d'un agencement donné à un autre</td>
</tr>
<tr>
<td><strong>Input</strong></td>
<td>
Agencement actuel, agencement final\
(grille de valeurs, 0=vide, `i`=meuble n°`i`)
</td>
</tr>
<tr>
<td><strong>Output</strong></td>
<td>Liste des états intermédiaires</td>
</tr>
<tr>
<td><strong>Signature</strong></td>
<td>
```python
def minimumMoves(
current_plan: list[list[int]],
target_plan: list[list[int]]
) -> list[list[list[int]]]:
```
</td>
</tr>
</table>
[Source](https://git.kb28.ch/HEL/AlgoDS-Examen2024/src/branch/main/src/ex4_furniture.py)
/
[Tests](https://git.kb28.ch/HEL/AlgoDS-Examen2024/src/branch/main/tests/test_ex4.py)

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@ -62,17 +62,13 @@ class Furniture:
class State: class State:
def __init__( def __init__(
self, self,
#plan: list[list[int]],
width: int, width: int,
height: int, height: int,
furniture: dict[id, Furniture], furniture: dict[id, Furniture],
parent: Optional[State] = None parent: Optional[State] = None
): ):
#self.plan: list[list[int]] = plan
self.furniture: dict[id, Furniture] = furniture self.furniture: dict[id, Furniture] = furniture
self.parent: Optional[State] = parent self.parent: Optional[State] = parent
#self.width: int = len(plan[0])
#self.height: int = len(plan)
self.width: int = width self.width: int = width
self.height: int = height self.height: int = height
@ -93,7 +89,6 @@ class State:
for i, tiles in furniture.items() for i, tiles in furniture.items()
} }
#return State(plan, furniture2)
return State(width, height, furniture2) return State(width, height, furniture2)
def to_list(self) -> list[list[int]]: def to_list(self) -> list[list[int]]:
@ -113,22 +108,6 @@ class State:
return self.parent.get_depth() + 1 return self.parent.get_depth() + 1
def apply_move(self, id: int, offset: tuple[int, int]) -> Optional[State]: def apply_move(self, id: int, offset: tuple[int, int]) -> Optional[State]:
#new_plan: list[list[int]] = [[0] * self.width for _ in range(self.height)]
"""
for y, row in enumerate(self.plan):
for x, tile in enumerate(row):
if tile == id:
x2, y2 = x + offset[0], y + offset[1]
if x2 < 0 or x2 >= self.width or y2 < 0 or y2 >= self.height:
return None
if new_plan[y2][x2] not in (0, id):
return None
new_plan[y2][x2] = id
new_plan[y][x] = 0
else:
new_plan[y][x] = tile
"""
plan: list[list[int]] = self.to_list() plan: list[list[int]] = self.to_list()
furn2: Furniture = self.furniture[id].move(offset) furn2: Furniture = self.furniture[id].move(offset)
for tx, ty in furn2.get_tiles(): for tx, ty in furn2.get_tiles():
@ -192,7 +171,6 @@ def minimumMoves(current_plan: list[list[int]], target_plan: list[list[int]]) ->
current_state = State.from_list(current_plan) current_state = State.from_list(current_plan)
target_state = State.from_list(target_plan) target_state = State.from_list(target_plan)
states: list[State] = [current_state] states: list[State] = [current_state]
while len(states) != 0: while len(states) != 0:
new_states: list[State] = [] new_states: list[State] = []