-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathheatmap.py
185 lines (158 loc) · 6.78 KB
/
heatmap.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
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
from matplotlib import pyplot as plt
import numpy as np
import sympy as sym
from itertools import product
import dbcontroller
from certification_data import *
import sys
import mpld3
# 各RPIの座標
rpi_a_coor = [0, 0]
rpi_b_coor = [0, 5]
rpi_c_coor = [3.5, 5 / 2]
# ヒートマップ表示範囲[m]
map_range = 5
# 各RPIのmacaddr
rpi_a_mac = "3476c58b5506", "b827ebe98ea9"
rpi_b_mac = "b827ebf277a4", "3476c58b5522"
rpi_c_mac = "b827ebb63034", "106f3f59c177"
# # ダミーデータ
# data_a = {"id": 6, "macaddr": "AA:BB:CC:DD:EE", "pwr": -42, "distance": 2, "rpimac": "rpi_a"}
def trilateration(a_dist, b_dist, c_dist):
"""各RPIを中心、デバイスまでの距離を半径とした3つの円を考え、それら3円に接する最も半径の小さい円の中心座標と半径を返す"""
x, y, R = sym.symbols('x,y,R', real=True)
sign = [-1, 1]
minans = (0, 0, 1000)
for o, p, q in product(sign, sign, sign):
result = sym.solve([(x - rpi_a_coor[0]) ** 2 + (y - rpi_a_coor[1]) ** 2 - (R + o * a_dist) ** 2,
(x - rpi_b_coor[0]) ** 2 + (y - rpi_b_coor[1]) ** 2 - (R + p * b_dist) ** 2,
(x - rpi_c_coor[0]) ** 2 + (y - rpi_c_coor[1]) ** 2 - (R + q * c_dist) ** 2], [x, y, R])
for ans in result:
if 0 < ans[2] < minans[2]:
minans = ans
print("R:{}".format(minans[2]))
return minans[0], minans[1], minans[2]
class Device:
PI_DATA_SIZE = 5
CIRCLE_DATA_SIZE = 5
def __init__(self, macaddr):
self.macaddr = macaddr
self.data_a_list = []
self.data_b_list = []
self.data_c_list = []
self.range_circle_list = []
def put_data_a(self, devdata):
if len(self.data_a_list) == self.PI_DATA_SIZE:
temp = self.data_a_list[1:]
temp.append(devdata)
self.data_a_list = temp
else:
self.data_a_list.append(devdata)
def put_data_b(self, devdata):
if len(self.data_b_list) == self.PI_DATA_SIZE:
temp = self.data_b_list[1:]
temp.append(devdata)
self.data_b_list = temp
else:
self.data_b_list.append(devdata)
def put_data_c(self, devdata):
if len(self.data_c_list) == self.PI_DATA_SIZE:
temp = self.data_c_list[1:]
temp.append(devdata)
self.data_c_list = temp
else:
self.data_c_list.append(devdata)
def put_range_circle(self, circle_data):
if len(self.range_circle_list) == self.CIRCLE_DATA_SIZE:
temp = self.range_circle_list[1:]
temp.append(circle_data)
self.range_circle_list = temp
else:
self.range_circle_list.append(circle_data)
def get_moving_average_of_dist(self, data_list):
sum = 0
for item in data_list:
sum += item["distance"]
return sum / self.PI_DATA_SIZE
def get_moving_average_of_circle(self, data_list):
sum_x = 0
sum_y = 0
sum_r = 0
for item in data_list:
sum_x += item[0]
sum_y += item[1]
sum_r += item[2]
return sum_x / self.CIRCLE_DATA_SIZE, sum_y / self.CIRCLE_DATA_SIZE, sum_r / self.CIRCLE_DATA_SIZE
def make_heatmap(self, circle_list):
squares = 40
weight = 10
dot_per_meter = int(squares / map_range)
map_ary = [[0]*squares for s in range(squares)]
for i, circle in enumerate(circle_list):
circle_squ = [int(p * dot_per_meter) for p in circle]
y_min = circle_squ[1] - circle_squ[2]
y_max = circle_squ[1] + circle_squ[2]
for y in range(squares):
if y_min < y < y_max:
for x in range(squares):
if (x-circle_squ[0])**2 + (y-circle_squ[1])**2 < circle_squ[2]**2:
map_ary[x][y] += weight
return map_ary
def make_histogram(self, circle_list):
# ドットの数
squares = 5
dot_per_meter = int(squares / map_range)
x_ary = []
y_ary = []
for i, circle in enumerate(circle_list):
circle_squ = [p*dot_per_meter for p in circle]
for x_squ, y_squ in product(range(squares), range(squares)):
if (x_squ-circle_squ[0])**2 + (y_squ-circle_squ[1])**2 <= circle_squ[2]**2:
x_ary.append(x_squ / dot_per_meter)
y_ary.append(y_squ / dot_per_meter)
return x_ary, y_ary
def main(argv):
debug = True
map_margin = 1
devlist = []
for macaddr in argv[1:]:
dev = Device(macaddr)
devlist.append(dev)
if debug:
dev.macaddr = "84:89:AD:8D:85:F6"
dev.hostname = "iPhone"
conn, cur = dbcontroller.mysql_connect(host, user, passwd, db)
try:
while True:
for dev in devlist:
dev.put_data_a(dbcontroller.select_latest(conn, cur, dev.macaddr, rpi_a_mac))
dev.put_data_b(dbcontroller.select_latest(conn, cur, dev.macaddr, rpi_b_mac))
dev.put_data_c(dbcontroller.select_latest(conn, cur, dev.macaddr, rpi_c_mac))
print("#a:{} #b{} #c{}".format(dev.get_moving_average_of_dist(dev.data_a_list), dev.get_moving_average_of_dist(dev.data_b_list), dev.get_moving_average_of_dist(dev.data_c_list), ))
# n点で移動平均をとった距離データを元に3辺測位をする
dev.coordinate = trilateration(
dev.get_moving_average_of_dist(dev.data_a_list),
dev.get_moving_average_of_dist(dev.data_b_list),
dev.get_moving_average_of_dist(dev.data_c_list),
)
dev.put_range_circle(dev.coordinate)
x, y = dev.make_histogram(dev.range_circle_list)
plt.clf()
plt.ion()
plt.hist2d(x, y, bins=map_range+map_margin*2, range=[[0-map_margin, map_range+map_margin], [0-map_margin, map_range+map_margin]])
xcoord = float(dev.get_moving_average_of_circle(dev.range_circle_list)[0])
ycoord = float(dev.get_moving_average_of_circle(dev.range_circle_list)[1])
plt.text(xcoord, ycoord, dev.hostname, fontsize=15, color="white")
plt.colorbar()
plt.scatter([rpi_a_coor[0], rpi_b_coor[0], rpi_c_coor[0]], [rpi_a_coor[1], rpi_b_coor[1], rpi_c_coor[1]], s=50, c='red')
plt.axes().set_aspect('equal', 'datalim')
plt.savefig("position.png")
with open('heatmap.html', 'w') as fout:
fout.write(mpld3.fig_to_html(plt.gcf()))
# TODO DBに送信
plt.pause(5)
except KeyboardInterrupt:
plt.close()
conn.close()
if __name__ == "__main__":
main(sys.argv)