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NNfunction.cxx
Go to the documentation of this file.
Or view
the newest version in sPHENIX GitHub for file NNfunction.cxx
1
#include "
NNfunction.h
"
2
#include <cmath>
3
4
double
NNfunction::Value
(
int
index,
double
in0,
double
in1,
double
in2,
double
in3,
double
in4,
double
in5) {
5
input0
= (in0 - 0)/1;
6
input1
= (in1 - 0)/1;
7
input2
= (in2 - 0)/1;
8
input3
= (in3 - 0)/1;
9
input4
= (in4 - 0)/1;
10
input5
= (in5 - 0)/1;
11
switch
(index) {
12
case
0:
13
return
neuron0x860e698
();
14
default
:
15
return
0.;
16
}
17
}
18
19
double
NNfunction::Value
(
int
index,
double
* input) {
20
input0
= (input[0] - 0)/1;
21
input1
= (input[1] - 0)/1;
22
input2
= (input[2] - 0)/1;
23
input3
= (input[3] - 0)/1;
24
input4
= (input[4] - 0)/1;
25
input5
= (input[5] - 0)/1;
26
switch
(index) {
27
case
0:
28
return
neuron0x860e698
();
29
default
:
30
return
0.;
31
}
32
}
33
34
double
NNfunction::neuron0x85fe910
() {
35
return
input0
;
36
}
37
38
double
NNfunction::neuron0x85feae8
() {
39
return
input1
;
40
}
41
42
double
NNfunction::neuron0x860cfa8
() {
43
return
input2
;
44
}
45
46
double
NNfunction::neuron0x860d180
() {
47
return
input3
;
48
}
49
50
double
NNfunction::neuron0x860d358
() {
51
return
input4
;
52
}
53
54
double
NNfunction::neuron0x860d530
() {
55
return
input5
;
56
}
57
58
double
NNfunction::input0x860d840
() {
59
double
input = -2.59262;
60
input +=
synapse0x85fe830
();
61
input +=
synapse0x860d9f0
();
62
input +=
synapse0x860da18
();
63
input +=
synapse0x860da40
();
64
input +=
synapse0x860da68
();
65
input +=
synapse0x860da90
();
66
return
input;
67
}
68
69
double
NNfunction::neuron0x860d840
() {
70
double
input =
input0x860d840
();
71
return
((input < -709. ? 0. : (1/(1+exp(-input)))) * 1)+0;
72
}
73
74
double
NNfunction::input0x860dab8
() {
75
double
input = -0.632405;
76
input +=
synapse0x860dcb0
();
77
input +=
synapse0x860dcd8
();
78
input +=
synapse0x860dd00
();
79
input +=
synapse0x860dd28
();
80
input +=
synapse0x860dd50
();
81
input +=
synapse0x860dd78
();
82
return
input;
83
}
84
85
double
NNfunction::neuron0x860dab8
() {
86
double
input =
input0x860dab8
();
87
return
((input < -709. ? 0. : (1/(1+exp(-input)))) * 1)+0;
88
}
89
90
double
NNfunction::input0x860dda0
() {
91
double
input = 2.12136;
92
input +=
synapse0x860df98
();
93
input +=
synapse0x860dfc0
();
94
input +=
synapse0x860dfe8
();
95
input +=
synapse0x860e010
();
96
input +=
synapse0x860e038
();
97
input +=
synapse0x860e0e8
();
98
return
input;
99
}
100
101
double
NNfunction::neuron0x860dda0
() {
102
double
input =
input0x860dda0
();
103
return
((input < -709. ? 0. : (1/(1+exp(-input)))) * 1)+0;
104
}
105
106
double
NNfunction::input0x860e110
() {
107
double
input = -0.392621;
108
input +=
synapse0x860e2c0
();
109
input +=
synapse0x860e2e8
();
110
input +=
synapse0x860e310
();
111
input +=
synapse0x860e338
();
112
input +=
synapse0x860e360
();
113
input +=
synapse0x860e388
();
114
return
input;
115
}
116
117
double
NNfunction::neuron0x860e110
() {
118
double
input =
input0x860e110
();
119
return
((input < -709. ? 0. : (1/(1+exp(-input)))) * 1)+0;
120
}
121
122
double
NNfunction::input0x860e3b0
() {
123
double
input = -0.0330152;
124
input +=
synapse0x860e5a8
();
125
input +=
synapse0x860e5d0
();
126
input +=
synapse0x860e5f8
();
127
input +=
synapse0x860e620
();
128
input +=
synapse0x860e648
();
129
input +=
synapse0x860e670
();
130
return
input;
131
}
132
133
double
NNfunction::neuron0x860e3b0
() {
134
double
input =
input0x860e3b0
();
135
return
((input < -709. ? 0. : (1/(1+exp(-input)))) * 1)+0;
136
}
137
138
double
NNfunction::input0x860e698
() {
139
double
input = 0.353032;
140
input +=
synapse0x860e798
();
141
input +=
synapse0x860e7c0
();
142
input +=
synapse0x860e7e8
();
143
input +=
synapse0x860e060
();
144
input +=
synapse0x860e088
();
145
return
input;
146
}
147
148
double
NNfunction::neuron0x860e698
() {
149
double
input =
input0x860e698
();
150
return
(input * 1)+0;
151
}
152
153
double
NNfunction::synapse0x85fe830
() {
154
return
(
neuron0x85fe910
()*-0.745014);
155
}
156
157
double
NNfunction::synapse0x860d9f0
() {
158
return
(
neuron0x85feae8
()*-0.78933);
159
}
160
161
double
NNfunction::synapse0x860da18
() {
162
return
(
neuron0x860cfa8
()*0.459588);
163
}
164
165
double
NNfunction::synapse0x860da40
() {
166
return
(
neuron0x860d180
()*0.00956551);
167
}
168
169
double
NNfunction::synapse0x860da68
() {
170
return
(
neuron0x860d358
()*2.85689);
171
}
172
173
double
NNfunction::synapse0x860da90
() {
174
return
(
neuron0x860d530
()*6.88496);
175
}
176
177
double
NNfunction::synapse0x860dcb0
() {
178
return
(
neuron0x85fe910
()*2.70722);
179
}
180
181
double
NNfunction::synapse0x860dcd8
() {
182
return
(
neuron0x85feae8
()*-5.22734);
183
}
184
185
double
NNfunction::synapse0x860dd00
() {
186
return
(
neuron0x860cfa8
()*1.95147);
187
}
188
189
double
NNfunction::synapse0x860dd28
() {
190
return
(
neuron0x860d180
()*1.69863);
191
}
192
193
double
NNfunction::synapse0x860dd50
() {
194
return
(
neuron0x860d358
()*-1.4849);
195
}
196
197
double
NNfunction::synapse0x860dd78
() {
198
return
(
neuron0x860d530
()*-0.0587496);
199
}
200
201
double
NNfunction::synapse0x860df98
() {
202
return
(
neuron0x85fe910
()*-0.156646);
203
}
204
205
double
NNfunction::synapse0x860dfc0
() {
206
return
(
neuron0x85feae8
()*0.324913);
207
}
208
209
double
NNfunction::synapse0x860dfe8
() {
210
return
(
neuron0x860cfa8
()*-0.164592);
211
}
212
213
double
NNfunction::synapse0x860e010
() {
214
return
(
neuron0x860d180
()*-0.0524867);
215
}
216
217
double
NNfunction::synapse0x860e038
() {
218
return
(
neuron0x860d358
()*0.415657);
219
}
220
221
double
NNfunction::synapse0x860e0e8
() {
222
return
(
neuron0x860d530
()*20.8707);
223
}
224
225
double
NNfunction::synapse0x860e2c0
() {
226
return
(
neuron0x85fe910
()*0.274578);
227
}
228
229
double
NNfunction::synapse0x860e2e8
() {
230
return
(
neuron0x85feae8
()*-0.0421086);
231
}
232
233
double
NNfunction::synapse0x860e310
() {
234
return
(
neuron0x860cfa8
()*0.465929);
235
}
236
237
double
NNfunction::synapse0x860e338
() {
238
return
(
neuron0x860d180
()*0.536229);
239
}
240
241
double
NNfunction::synapse0x860e360
() {
242
return
(
neuron0x860d358
()*0.365813);
243
}
244
245
double
NNfunction::synapse0x860e388
() {
246
return
(
neuron0x860d530
()*0.126046);
247
}
248
249
double
NNfunction::synapse0x860e5a8
() {
250
return
(
neuron0x85fe910
()*0.400093);
251
}
252
253
double
NNfunction::synapse0x860e5d0
() {
254
return
(
neuron0x85feae8
()*0.44706);
255
}
256
257
double
NNfunction::synapse0x860e5f8
() {
258
return
(
neuron0x860cfa8
()*0.344358);
259
}
260
261
double
NNfunction::synapse0x860e620
() {
262
return
(
neuron0x860d180
()*0.672479);
263
}
264
265
double
NNfunction::synapse0x860e648
() {
266
return
(
neuron0x860d358
()*0.372075);
267
}
268
269
double
NNfunction::synapse0x860e670
() {
270
return
(
neuron0x860d530
()*-0.268089);
271
}
272
273
double
NNfunction::synapse0x860e798
() {
274
return
(
neuron0x860d840
()*1.53795);
275
}
276
277
double
NNfunction::synapse0x860e7c0
() {
278
return
(
neuron0x860dab8
()*-2.55427);
279
}
280
281
double
NNfunction::synapse0x860e7e8
() {
282
return
(
neuron0x860dda0
()*-2.13902);
283
}
284
285
double
NNfunction::synapse0x860e060
() {
286
return
(
neuron0x860e110
()*1.00768);
287
}
288
289
double
NNfunction::synapse0x860e088
() {
290
return
(
neuron0x860e3b0
()*0.838776);
291
}
292
EicRoot
blob
master
rich
standalone
algorithm
NNfunction.cxx
Built by
Jin Huang
. updated:
Mon Jan 22 2024 12:43:37
using
1.8.2 with
EIC GitHub integration