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no more tiles no more floor

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Steffen Illium
2023-10-20 14:36:23 +02:00
parent 8709b093b8
commit 7a1d3f84f1
41 changed files with 265 additions and 217 deletions
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4
marl_factory_grid/algorithms/static/TSP_base_agent.py
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@ -21,7 +21,7 @@ class TSPBaseAgent(ABC):
self.local_optimization = True
self._env = state
self.state = self._env.state[c.AGENT][agent_i]
self._floortile_graph = points_to_graph(self._env[c.FLOORS].positions)
self._position_graph = points_to_graph(self._env.entities.floorlist)
self._static_route = None
@abstractmethod
@ -50,7 +50,7 @@ class TSPBaseAgent(ABC):
else:
nodes = [self.state.pos] + positions
route = tsp.traveling_salesman_problem(self._floortile_graph,
route = tsp.traveling_salesman_problem(self._position_graph,
nodes=nodes, cycle=True, method=tsp.greedy_tsp)
return route

12
marl_factory_grid/algorithms/static/utils.py
View File

@ -4,17 +4,17 @@ import networkx as nx
import numpy as np
def points_to_graph(coordiniates_or_tiles, allow_euclidean_connections=True, allow_manhattan_connections=True):
def points_to_graph(coordiniates, allow_euclidean_connections=True, allow_manhattan_connections=True):
"""
Given a set of coordinates, this function contructs a non-directed graph, by conncting adjected points.
There are three combinations of settings:
Allow all neigbors: Distance(a, b) <= sqrt(2)
Allow only manhattan: Distance(a, b) == 1
Allow only euclidean: Distance(a, b) == sqrt(2)
Allow only Euclidean: Distance(a, b) == sqrt(2)
:param coordiniates_or_tiles: A set of coordinates.
:type coordiniates_or_tiles: Tiles
:param coordiniates: A set of coordinates.
:type coordiniates: Tuple[int, int]
:param allow_euclidean_connections: Whether to regard diagonal adjected cells as neighbors
:type: bool
:param allow_manhattan_connections: Whether to regard directly adjected cells as neighbors
@ -24,9 +24,7 @@ def points_to_graph(coordiniates_or_tiles, allow_euclidean_connections=True, all
:rtype: nx.Graph
"""
assert allow_euclidean_connections or allow_manhattan_connections
if hasattr(coordiniates_or_tiles, 'positions'):
coordiniates_or_tiles = coordiniates_or_tiles.positions
possible_connections = itertools.combinations(coordiniates_or_tiles, 2)
possible_connections = itertools.combinations(coordiniates, 2)
graph = nx.Graph()
for a, b in possible_connections:
diff = np.linalg.norm(np.asarray(a)-np.asarray(b))