From 6a8f55117cd0d3c975f51808e836a958caf08b23 Mon Sep 17 00:00:00 2001
From: MLErik <baerenjesus@gmail.com>
Date: Sat, 17 Aug 2019 11:17:27 -0400
Subject: [PATCH] Fixed typo and formatting
---
flatland/envs/generators.py | 29 ++++++++++---------
flatland/envs/grid4_generators_utils.py | 1 +
...test_flatland_env_sparse_rail_generator.py | 15 ++++------
3 files changed, 21 insertions(+), 24 deletions(-)
diff --git a/flatland/envs/generators.py b/flatland/envs/generators.py
index a0eb7ca7..50759734 100644
--- a/flatland/envs/generators.py
+++ b/flatland/envs/generators.py
@@ -543,7 +543,7 @@ def random_rail_generator(cell_type_relative_proportion=[1.0] * 11):
return generator
-def realistic_rail_generator(nr_start_goal=1, seed=0):
+def realistic_rail_generator(nr_start_goal=1, seed=0):
"""
Parameters
-------
@@ -682,7 +682,7 @@ def realistic_rail_generator(nr_start_goal=1, seed=0):
idx_forward = []
idx_backward = []
- idx_target=0
+ idx_target = 0
for off_set_loop in range(len(x_offsets)):
off_set = x_offsets[off_set_loop]
# second track
@@ -739,14 +739,17 @@ def realistic_rail_generator(nr_start_goal=1, seed=0):
(x_offsets[off_set_loop] - 1, 0),
(x_offsets[off_set_loop] - 2, 0))
- for nbr_track_loop in range(max_n_track_seg-1):
+ for nbr_track_loop in range(max_n_track_seg - 1):
if len(data) < 2 * n_track_seg + 1:
break
x = np.sort(np.random.choice(data, 2 * n_track_seg, False)).astype(int)
data = []
for x_loop in range(int(len(x) / 2)):
- start = (max(0, min(off_set + nbr_track_loop + 1, height - 1)), max(0, min(x[2 * x_loop], width - 1)))
- goal = (max(0, min(off_set + nbr_track_loop + 1, height - 1)), max(0, min(x[2 * x_loop + 1], width - 1)))
+ start = (
+ max(0, min(off_set + nbr_track_loop + 1, height - 1)), max(0, min(x[2 * x_loop], width - 1)))
+ goal = (
+ max(0, min(off_set + nbr_track_loop + 1, height - 1)),
+ max(0, min(x[2 * x_loop + 1], width - 1)))
d = np.arange(x[2 * x_loop] + 1, x[2 * x_loop + 1] - 1, 2)
data.extend(d)
@@ -767,15 +770,15 @@ def realistic_rail_generator(nr_start_goal=1, seed=0):
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)
+ 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
+ idx_target += 1
agents_position = []
agents_target = []
agents_direction = []
- for a in range(min(len(agents_targets),num_agents)):
+ 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)
@@ -789,7 +792,7 @@ def realistic_rail_generator(nr_start_goal=1, seed=0):
agents_positions_backward.pop(sel)
agents_directions_backward.pop(sel)
idx_backward.pop(sel)
- agents_position.append((p[0],p[1]))
+ agents_position.append((p[0], p[1]))
agents_direction.append(d)
else:
if len(idx_forward) > 0:
@@ -801,10 +804,9 @@ def realistic_rail_generator(nr_start_goal=1, seed=0):
agents_positions_forward.pop(sel)
agents_directions_forward.pop(sel)
idx_forward.pop(sel)
- agents_position.append((p[0],p[1]))
+ 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)
return generator
@@ -881,7 +883,7 @@ def sparse_rail_generator(num_cities=100, num_intersections=10, num_trainstation
for neighb in connected_neighb_idx:
if neighb not in node_stack:
node_stack.append(neighb)
- new_path = connect_nodes(rail_trans, rail_array, node_positions[current_node], node_positions[neighb])
+ connect_nodes(rail_trans, rail_array, node_positions[current_node], node_positions[neighb])
node_stack.pop(0)
# Place train stations close to the node
@@ -908,8 +910,7 @@ def sparse_rail_generator(num_cities=100, num_intersections=10, num_trainstation
train_stations[trainstation_node].append((station_x, station_y))
# Connect train station to the correct node
- new_path = connect_from_nodes(rail_trans, rail_array, node_positions[trainstation_node],
- (station_x, station_y))
+ connect_from_nodes(rail_trans, rail_array, node_positions[trainstation_node], (station_x, station_y))
# Fix all nodes with illegal transition maps
for current_node in node_positions:
diff --git a/flatland/envs/grid4_generators_utils.py b/flatland/envs/grid4_generators_utils.py
index 9116adb6..fbb1f03d 100644
--- a/flatland/envs/grid4_generators_utils.py
+++ b/flatland/envs/grid4_generators_utils.py
@@ -194,6 +194,7 @@ def connect_to_nodes(rail_trans, rail_array, start, end):
current_dir = new_dir
return path
+
def get_rnd_agents_pos_tgt_dir_on_rail(rail, num_agents):
"""
Given a `rail' GridTransitionMap, return a random placement of agents (initial position, direction and target).
diff --git a/tests/test_flatland_env_sparse_rail_generator.py b/tests/test_flatland_env_sparse_rail_generator.py
index 34e6c2b4..66b7ca3b 100644
--- a/tests/test_flatland_env_sparse_rail_generator.py
+++ b/tests/test_flatland_env_sparse_rail_generator.py
@@ -1,5 +1,3 @@
-import time
-
import numpy as np
from flatland.envs.generators import sparse_rail_generator, realistic_rail_generator
@@ -10,18 +8,18 @@ from flatland.utils.rendertools import RenderTool
def test_realistic_rail_generator():
for test_loop in range(20):
- num_agents = np.random.randint(10,30)
- env = RailEnv(width=np.random.randint(40,80),
- height=np.random.randint(10,20),
- rail_generator=realistic_rail_generator(nr_start_goal=num_agents+1,seed=test_loop),
+ num_agents = np.random.randint(10, 30)
+ env = RailEnv(width=np.random.randint(40, 80),
+ height=np.random.randint(10, 20),
+ rail_generator=realistic_rail_generator(nr_start_goal=num_agents + 1, seed=test_loop),
number_of_agents=num_agents,
obs_builder_object=GlobalObsForRailEnv())
# reset to initialize agents_static
env_renderer = RenderTool(env, gl="PILSVG", )
env_renderer.render_env(show=True, show_observations=True, show_predictions=False)
- time.sleep(2)
env_renderer.close_window()
+
def test_sparse_rail_generator():
env = RailEnv(width=20,
height=50,
@@ -38,7 +36,4 @@ def test_sparse_rail_generator():
# reset to initialize agents_static
env_renderer = RenderTool(env, gl="PILSVG", )
env_renderer.render_env(show=True, show_observations=True, show_predictions=False)
- time.sleep(20)
- env_renderer.gl.save_image("flatalnd_2_0.png")
- time.sleep(1)
--
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