-
Notifications
You must be signed in to change notification settings - Fork 1
/
build_graphs.py
222 lines (206 loc) · 8.42 KB
/
build_graphs.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
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
import datetime
import os
from math import cos, sin, radians
import matplotlib.pyplot as plt
import pandas as pd
vel_param = [4, 6.5, 8.5, 9.8, 12.2, 16, 19, 20]
vel_param_x = [4, 4.333, 4.666, 5, 6, 7, 8, 8.333]
vel_func = lambda x: 3.06 * x - 5.502
unsolved_x = [5, 6, 7, 8, 9, 10, 11, 11.5]
unsolved_y = [81, 91, 96, 100, 100, 100, 100, 100]
def get_n_targets(name):
"""
Detects number of targets in case
@param name: foldername with path
@return:
"""
foldername = os.path.split(name)[1]
foldername2 = foldername.split(sep="_")
if float(foldername2[1]) == 0 or float(foldername2[2]) == 0:
return 1
else:
return 2
def build_percent_diag(filename, dist_max, dist_min, step, show_graph=True):
"""
Builds percent diagram with codes and errors to velocities graph
@param filename:
@param dist_max:
@param dist_min:
@param step:
@return:
"""
df = pd.read_excel(filename, engine='openpyxl')
names = df['datadir']
codes = df['code']
N = int((dist_max - dist_min) / step)
dists = [dist_min + i * step for i in range(N + 1)]
N_dists = [0 for i in range(N + 1)]
code0 = [0 for i in range(N + 1)]
code1 = [0 for i in range(N + 1)]
code2 = [0 for i in range(N + 1)]
code4 = [0 for i in range(N + 1)]
code5 = [0 for i in range(N + 1)]
code4_fnmes = []
vel2 = []
dist2 = []
f_names2 = []
n_targ = 1
for i, name in enumerate(names):
foldername = os.path.split(name)[1]
n_targ = get_n_targets(foldername)
foldername2 = foldername.split(sep="_")
dist = 0
if n_targ == 1:
dist = max(float(foldername2[1]), float(foldername2[2]))
elif n_targ == 2:
dist = min(float(foldername2[1]), float(foldername2[2]))
if codes[i] == 0:
ind = round((dist - dist_min) / step)
if N_dists[ind] > -1:
code0[ind] += 1
N_dists[ind] += 1
elif codes[i] == 2:
ind = round((dist - dist_min) / step)
if N_dists[ind] > -1:
code2[ind] += 1
N_dists[ind] += 1
vel2.append(float(foldername2[3]))
dist2.append(dist)
if float(foldername2[3]) < vel_func(dist):
f_names2.append(foldername)
elif codes[i] == 4:
ind = round((dist - dist_min) / step)
if N_dists[ind] > -1:
code4[ind] += 1
N_dists[ind] += 1
code4_fnmes.append(foldername)
elif codes[i] == 1:
ind = round((dist - dist_min) / step)
if N_dists[ind] > -1:
code1[ind] += 1
N_dists[ind] += 1
elif codes[i] == 5:
ind = round((dist - dist_min) / step)
if N_dists[ind] > -1:
code5[ind] += 1
N_dists[ind] += 1
fig, ax = plt.subplots()
for i in range(N + 1):
if N_dists[i] == 0:
N_dists[i] = 1
df4 = pd.DataFrame()
df4['names_4'] = code4_fnmes
df4.to_excel("4code_tests.xlsx")
plt.figure(figsize=(10, 6), dpi=200)
ddf = pd.DataFrame()
ddf['critical'] = f_names2
ddf.to_excel("critical.xlsx")
code0_p = [code0[i] / N_dists[i] * 100 for i in range(N + 1)]
code1_p = [code1[i] / N_dists[i] * 100 for i in range(N + 1)]
code2_p = [code2[i] / N_dists[i] * 100 for i in range(N + 1)]
code4_p = [code4[i] / N_dists[i] * 100 for i in range(N + 1)]
code5_p = [code5[i] / N_dists[i] * 100 for i in range(N + 1)]
print(N_dists)
if show_graph:
plt.plot(dists, code0_p, 'b', label="Код 0", linewidth=3)
print(code0_p)
# plt.fill_between(dists, code0_p, 100, color='orange', alpha=0.5)
# plt.fill_between(dists, code0_p, 0, color='green', alpha=0.5)
plt.plot(dists, code1_p, 'r', label="Код 1")
plt.plot(dists, code2_p, 'y--', label="Код 2")
plt.plot(dists, code4_p, 'o--', label="Код 4")
plt.plot(dists, code5_p, 'g', label="Код 5")
plt.grid()
plt.axis([dist_min, dist_max, 0, 100])
plt.xlabel('Дистанция до ближайшей цели, мили', fontsize=20)
plt.ylabel('Маневр построен, %', fontsize=20)
# plt.plot(unsolved_x, unsolved_y, 'o--')
plt.legend(loc='upper left', shadow=True)
plt.title("Дата: " + str(datetime.date.today()) + ", цели: " + str(n_targ))
plt.savefig("./images/" + str(datetime.date.today()) + "_" + str(n_targ) + "_stats.png")
plt.show()
fig, ax = plt.subplots()
plt.scatter(dist2, vel2, alpha=0.5)
plt.plot(vel_param_x, vel_param)
plt.xlabel('Дистанция до цели, мили')
plt.ylabel('Скорость цели, узлы')
plt.grid()
plt.title("Дата: " + str(datetime.date.today()) + ", цели: " + str(n_targ))
plt.savefig("./images/" + str(datetime.date.today()) + "_" + str(n_targ) + "_vels.png")
plt.show()
else:
return [code0_p, code1_p, code2_p, code4_p, code5_p, dists, n_targ]
def build_turn_diagram(filename, dist_max, dist_min, step):
df = pd.read_excel(filename)
names = df['datadir']
turns = df['right']
N = int((dist_max - dist_min) / step)
dists = [dist_min + i * step for i in range(N + 1)]
N_dists = [0 for i in range(N + 1)]
left = [0 for i in range(N + 1)]
right = [0 for i in range(N + 1)]
left_names = []
for i, name in enumerate(names):
foldername = os.path.split(name)[1]
n_targ = get_n_targets(foldername)
foldername2 = foldername.split(sep="_")
dist = 0
if n_targ == 1:
dist = max(float(foldername2[1]), float(foldername2[2]))
elif n_targ == 2:
dist = min(float(foldername2[1]), float(foldername2[2]))
ind = round((dist - dist_min) / step)
if turns[i] == True:
right[ind] += 1
N_dists[ind] += 1
elif turns[i] == False:
left[ind] += 1
N_dists[ind] += 1
left_names.append(foldername)
df = pd.DataFrame()
df['dirnames'] = left_names
df.to_excel('./reports/' + str(n_targ) + '_left_maneuvers.xlsx')
fig, ax = plt.subplots()
for i in range(N + 1):
if N_dists[i] == 0:
N_dists[i] = 1
plt.figure(figsize=(10, 6), dpi=200)
right_p = [right[i] / N_dists[i] * 100 for i in range(N + 1)]
left_p = [left[i] / N_dists[i] * 100 for i in range(N + 1)]
plt.plot(dists, right_p, 'b', label="Поворот вправо", linewidth=3)
plt.plot(dists, left_p, 'r', label="Поворот влево", linewidth=3)
plt.grid()
plt.axis([dist_min, dist_max, 0, 100])
plt.xlabel('Дистанция до ближайшей цели, мили', fontsize=20)
plt.ylabel('Поворот в сторону, %', fontsize=20)
plt.legend(loc='upper left', shadow=True)
plt.title("Дата: " + str(datetime.date.today()) + ", цели: " + str(n_targ))
plt.savefig("./images/" + str(datetime.date.today()) + "_" + str(n_targ) + "_turns.png")
plt.show()
if __name__ == "__main__":
build_percent_diag('./reports/report1_2021-07-20.xlsx', 12, 4, 0.5)
build_turn_diagram('./reports/report1_2021-07-20.xlsx', 12, 4, 0.5)
build_percent_diag('./reports/report2_2021-07-20.xlsx', 12, 4, 0.5)
build_turn_diagram('./reports/report2_2021-07-20.xlsx', 12, 4, 0.5)
df = pd.read_excel('./reports/report_2_4.xlsx')
names = df['datadir']
x1, y1, c1 = [], [], []
x2, y2, c2 = [], [], []
fig, ax = plt.subplots()
# скорость судна скорость цели
# тесты для одной цели
for name in names:
foldername = name.split(sep="\\")[6]
foldername = foldername.split(sep="_")
x1.append(cos(radians(float(foldername[3]))) * float(foldername[1]))
x2.append(cos(radians(float(foldername[4]))) * float(foldername[2]))
y1.append(sin(radians(float(foldername[3]))) * float(foldername[1]))
y2.append(sin(radians(float(foldername[4]))) * float(foldername[2]))
c1.append("#17becf")
c2.append('#d62728')
plt.scatter(x1, y1, c=c1, alpha=0.5, label="Цели №1")
plt.scatter(x2, y2, c=c2, alpha=0.5, label="Цели №2")
plt.plot(0, 0, 'y*', linewidth=2, markersize=12, label="Наше судно")
plt.grid()
legend = ax.legend(loc='upper left', shadow=True, fontsize='x-large')
plt.show()