From 391d7f226a36b7bcab8cdd10e3c4f723fbd8a9b1 Mon Sep 17 00:00:00 2001
From: "Egli Adrian (IT-SCI-API-PFI)" <adrian.egli@sbb.ch>
Date: Fri, 16 Aug 2019 22:15:18 +0200
Subject: [PATCH] feasible solution: OK?
---
flatland/envs/generators.py | 64 ++++++++++++++-----
...test_flatland_env_sparse_rail_generator.py | 1 +
2 files changed, 50 insertions(+), 15 deletions(-)
diff --git a/flatland/envs/generators.py b/flatland/envs/generators.py
index d7173fa3..b17238d5 100644
--- a/flatland/envs/generators.py
+++ b/flatland/envs/generators.py
@@ -673,10 +673,16 @@ def realistic_rail_generator(nr_start_goal=1, seed=0):
max_n_track_seg = np.random.choice([3, 4, 5])
x_offsets = np.arange(0, height, max_n_track_seg).astype(int)
- agents_positions = []
+ agents_positions_forward = []
+ agents_directions_forward = []
+ agents_positions_backward = []
+ agents_directions_backward = []
agents_targets = []
- agents_directions = []
+ idx_forward = []
+ idx_backward = []
+
+ idx_target=0
for off_set_loop in range(len(x_offsets)):
off_set = x_offsets[off_set_loop]
# second track
@@ -752,24 +758,52 @@ def realistic_rail_generator(nr_start_goal=1, seed=0):
make_switch_w_e(width, height, grid_map, c)
add_pos = (int((start[0] + goal[0]) / 2), int((start[1] + goal[1]) / 2))
- agents_positions.append(add_pos)
- agents_directions.append([1,3][nbr_track_loop % 2])
- add_pos = (int((start[0] + goal[0]) / 2), int((2*start[1] + goal[1]) / 3))
+ if nbr_track_loop % 2 == 0:
+ agents_positions_forward.append(add_pos)
+ agents_directions_forward.append(([1, 3][off_set_loop % 2]))
+ idx_forward.append(idx_target)
+ else:
+ agents_positions_backward.append(add_pos)
+ agents_directions_backward.append(([1, 3][off_set_loop % 2]))
+ idx_backward.append(idx_target)
+
+ add_pos = (int((start[0] + goal[0]) / 2), int((2*start[1] + goal[1]) / 3),idx_target)
agents_targets.append(add_pos)
+ idx_target+=1
agents_position = []
agents_target = []
agents_direction = []
- filter_agent = np.random.choice(np.arange(len(agents_positions)),min(len(agents_positions),num_agents),False)
- for f in filter_agent:
- d = agents_positions[f]
- agents_position.append(d)
- d = agents_directions[f]
- agents_direction.append(d)
- filter_target = np.random.choice(np.arange(len(agents_targets)),min(len(agents_targets),num_agents),False)
- for f in filter_target:
- d = agents_targets[f]
- agents_target.append(d)
+
+ for a in range(min(len(agents_targets),num_agents)):
+ t = np.random.choice(range(len(agents_targets)))
+ d = agents_targets[t]
+ agents_targets.pop(t)
+ if d[2] < idx_target / 2:
+ if len(idx_backward) > 0:
+ agents_target.append((d[0], d[1]))
+ sel = np.random.choice(range(len(idx_backward)))
+ # backward
+ p = agents_positions_backward[sel]
+ d = agents_directions_backward[sel]
+ agents_positions_backward.pop(sel)
+ agents_directions_backward.pop(sel)
+ idx_backward.pop(sel)
+ agents_position.append((p[0],p[1]))
+ agents_direction.append(d)
+ else:
+ if len(idx_forward) > 0:
+ agents_target.append((d[0], d[1]))
+ sel = np.random.choice(range(len(idx_forward)))
+ # forward
+ p = agents_positions_forward[sel]
+ d = agents_directions_forward[sel]
+ agents_positions_forward.pop(sel)
+ agents_directions_forward.pop(sel)
+ idx_forward.pop(sel)
+ agents_position.append((p[0],p[1]))
+ agents_direction.append(d)
+
return grid_map, agents_position, agents_direction, agents_target, [1.0] * len(agents_position)
diff --git a/tests/test_flatland_env_sparse_rail_generator.py b/tests/test_flatland_env_sparse_rail_generator.py
index 3c1bc18b..2619dbca 100644
--- a/tests/test_flatland_env_sparse_rail_generator.py
+++ b/tests/test_flatland_env_sparse_rail_generator.py
@@ -33,3 +33,4 @@ def test_sparse_rail_generator():
env_renderer = RenderTool(env, gl="PILSVG", )
env_renderer.render_env(show=True, show_observations=True, show_predictions=False)
time.sleep(2)
+
--
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