-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathvisualize.py
130 lines (112 loc) · 4.95 KB
/
visualize.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
#!/usr/bin/env python3
from matplotlib.patches import Circle, Rectangle
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import animation
Colors = ['green', 'blue', 'orange']
class Animation:
def __init__(self, my_map, starts, goals, paths):
self.my_map = np.flip(np.transpose(my_map), 1)
self.starts = []
for start in starts:
self.starts.append((start[1], len(self.my_map[0]) - 1 - start[0]))
self.goals = []
for goal in goals:
self.goals.append((goal[1], len(self.my_map[0]) - 1 - goal[0]))
self.paths = []
if paths:
for path in paths:
print(path)
self.paths.append([])
for loc in path:
self.paths[-1].append((loc[1], len(self.my_map[0]) - 1 - loc[0]))
aspect = len(self.my_map) / len(self.my_map[0])
self.fig = plt.figure(frameon=False, figsize=(4 * aspect, 4))
self.ax = self.fig.add_subplot(111, aspect='equal')
self.fig.subplots_adjust(left=0, right=1, bottom=0, top=1, wspace=None, hspace=None)
# self.ax.set_frame_on(False)
self.patches = []
self.artists = []
self.agents = dict()
self.agent_names = dict()
# create boundary patch
x_min = -0.5
y_min = -0.5
x_max = len(self.my_map) - 0.5
y_max = len(self.my_map[0]) - 0.5
plt.xlim(x_min, x_max)
plt.ylim(y_min, y_max)
self.patches.append(Rectangle((x_min, y_min), x_max - x_min, y_max - y_min, facecolor='none', edgecolor='gray'))
for i in range(len(self.my_map)):
for j in range(len(self.my_map[0])):
if self.my_map[i][j]:
self.patches.append(Rectangle((i - 0.5, j - 0.5), 1, 1, facecolor='gray', edgecolor='gray'))
# create agents:
self.T = 0
# draw goals first
for i, goal in enumerate(self.goals):
self.patches.append(Rectangle((goal[0] - 0.25, goal[1] - 0.25), 0.5, 0.5, facecolor=Colors[i % len(Colors)],
edgecolor='black', alpha=0.5))
for i in range(len(self.paths)):
name = str(i)
self.agents[i] = Circle((starts[i][0], starts[i][1]), 0.3, facecolor=Colors[i % len(Colors)],
edgecolor='black')
self.agents[i].original_face_color = Colors[i % len(Colors)]
self.patches.append(self.agents[i])
self.T = max(self.T, len(paths[i]) - 1)
self.agent_names[i] = self.ax.text(starts[i][0], starts[i][1] + 0.25, name)
self.agent_names[i].set_horizontalalignment('center')
self.agent_names[i].set_verticalalignment('center')
self.artists.append(self.agent_names[i])
self.animation = animation.FuncAnimation(self.fig, self.animate_func,
init_func=self.init_func,
frames=int(self.T + 1) * 10,
interval=100,
blit=True)
def save(self, file_name, speed):
self.animation.save(
file_name,
fps=10 * speed,
dpi=200,
savefig_kwargs={"pad_inches": 0, "bbox_inches": "tight"})
@staticmethod
def show():
plt.show()
def init_func(self):
for p in self.patches:
self.ax.add_patch(p)
for a in self.artists:
self.ax.add_artist(a)
return self.patches + self.artists
def animate_func(self, t):
for k in range(len(self.paths)):
pos = self.get_state(t / 10, self.paths[k])
self.agents[k].center = (pos[0], pos[1])
self.agent_names[k].set_position((pos[0], pos[1] + 0.5))
# reset all colors
for _, agent in self.agents.items():
agent.set_facecolor(agent.original_face_color)
# check drive-drive collisions
agents_array = [agent for _, agent in self.agents.items()]
for i in range(0, len(agents_array)):
for j in range(i + 1, len(agents_array)):
d1 = agents_array[i]
d2 = agents_array[j]
pos1 = np.array(d1.center)
pos2 = np.array(d2.center)
if np.linalg.norm(pos1 - pos2) < 0.7:
d1.set_facecolor('red')
d2.set_facecolor('red')
print("COLLISION! (agent-agent) ({}, {}) at time {}".format(i, j, t/10))
return self.patches + self.artists
@staticmethod
def get_state(t, path):
if int(t) <= 0:
return np.array(path[0])
elif int(t) >= len(path):
return np.array(path[-1])
else:
pos_last = np.array(path[int(t) - 1])
pos_next = np.array(path[int(t)])
pos = (pos_next - pos_last) * (t - int(t)) + pos_last
return pos