From c9207ec0e93f3371e8c45c838a87f1862f5b8aba Mon Sep 17 00:00:00 2001
From: MLErik <baerenjesus@gmail.com>
Date: Sat, 28 Sep 2019 10:18:49 -0400
Subject: [PATCH] updated how closest neighbours are found. Now always looking
at directions similar to initial try
---
examples/flatland_2_0_example.py | 2 +-
flatland/envs/rail_generators.py | 58 ++++++++++++++------------------
2 files changed, 26 insertions(+), 34 deletions(-)
diff --git a/examples/flatland_2_0_example.py b/examples/flatland_2_0_example.py
index 0099b1cd..7ed5d27c 100644
--- a/examples/flatland_2_0_example.py
+++ b/examples/flatland_2_0_example.py
@@ -33,7 +33,7 @@ env = RailEnv(width=50,
rail_generator=sparse_rail_generator(num_cities=9, # Number of cities in map (where train stations are)
min_node_dist=12, # Minimal distance of nodes
node_radius=4, # Proximity of stations to city center
- seed=0, # Random seed
+ seed=12, # Random seed
grid_mode=False,
max_inter_city_rails=2,
tracks_in_city=5,
diff --git a/flatland/envs/rail_generators.py b/flatland/envs/rail_generators.py
index 226b7f89..d1911d4b 100644
--- a/flatland/envs/rail_generators.py
+++ b/flatland/envs/rail_generators.py
@@ -728,23 +728,19 @@ def sparse_rail_generator(num_cities=5, min_node_dist=20, node_radius=2,
for current_node in np.arange(len(node_positions)):
direction = 0
connected_to_city = []
+ neighbours = _closest_neigh_in_direction(current_node, node_positions)
for nbr_connection_points in connection_info[current_node]:
if nbr_connection_points > 0:
- neighb_idx = _closest_neigh_in_direction(current_node, direction, node_positions)
+ neighb_idx = neighbours[direction]
else:
direction += 1
continue
- if neighb_idx is None or neighb_idx in connected_to_city:
- node_dist = []
- for av_node in node_positions:
- node_dist.append(distance_on_rail(node_positions[current_node], av_node))
- i = 1
- neighbours = np.argsort(node_dist)
- neighb_idx = neighbours[i]
- while neighb_idx in connected_to_city:
- i += 1
- neighb_idx = neighbours[i]
+ # If no closest neighbour was found look for the next one clock wise to avoid connecting to previous node
+ tmp_direction = (direction + 1) % 4
+ while neighb_idx is None:
+ neighb_idx = neighbours[tmp_direction]
+ tmp_direction = (tmp_direction - 1) % 4
connected_to_city.append(neighb_idx)
for tmp_out_connection_point in connection_points[current_node][direction]:
@@ -882,33 +878,29 @@ def sparse_rail_generator(num_cities=5, min_node_dist=20, node_radius=2,
for cell in rails_to_fix:
grid_map.fix_transitions(cell)
- def _closest_neigh_in_direction(current_node, direction, node_positions):
- # Sort available neighbors according to their distance.
-
+ def _closest_neigh_in_direction(current_node, node_positions):
+ """
+ Returns indices of closest neighbours in every direction NESW
+ :param current_node: Index of node in node_positions list
+ :param node_positions: list of all points being considered
+ :return: list of index of closest neighbours in all directions
+ """
node_dist = []
+ closest_neighb = [None for i in range(4)]
for av_node in range(len(node_positions)):
node_dist.append(distance_on_rail(node_positions[current_node], node_positions[av_node]))
sorted_neighbours = np.argsort(node_dist)
-
+ direction_set = 0
for neighb in sorted_neighbours[1:]:
- distance_0 = np.abs(node_positions[current_node][0] - node_positions[neighb][0])
- distance_1 = np.abs(node_positions[current_node][1] - node_positions[neighb][1])
- if direction == 0:
- if node_positions[neighb][0] < node_positions[current_node][0] and distance_1 <= distance_0:
- return neighb
-
- if direction == 1:
- if node_positions[neighb][1] > node_positions[current_node][1] and distance_0 <= distance_1:
- return neighb
-
- if direction == 2:
- if node_positions[neighb][0] > node_positions[current_node][0] and distance_1 <= distance_0:
- return neighb
-
- if direction == 3:
- if node_positions[neighb][1] < node_positions[current_node][1] and distance_0 <= distance_1:
- return neighb
- return None
+ direction_to_neighb = direction_to_point(node_positions[current_node], node_positions[neighb])
+ if closest_neighb[direction_to_neighb] == None:
+ closest_neighb[direction_to_neighb] = neighb
+ direction_set += 1
+
+ if direction_set == 4:
+ return closest_neighb
+
+ return closest_neighb
def argsort(seq):
# http://stackoverflow.com/questions/3071415/efficient-method-to-calculate-the-rank-vector-of-a-list-in-python
--
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