-
Notifications
You must be signed in to change notification settings - Fork 4
Expand file tree
/
Copy pathsdeNode.cpp
More file actions
104 lines (79 loc) · 4.16 KB
/
sdeNode.cpp
File metadata and controls
104 lines (79 loc) · 4.16 KB
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
/* last modifier: js */
#include "sdeNode.h"
namespace conedy
{
//gslNoise sdeNode::noise;
// -------------------------Node for Stochastic Differential Equations----------------------------- //
// Dieser Ornstein-Uhlenbeck Prozess kann dazu benutzt werden
// Dies ist das EEG-Modell von Fabrice Wendling: (C_i = params[i])
// C_0 = sigma_n, C_1 = mean_n,
// C_2 = a_0, C_3 = e_0,
// C_4 = v_0, C_5 = r
// C_6 = C_1, C_7 = C_2,
// C_8 = C_3, C_9 = C_4,
// C_10 = A, C_11 = a, C_12 = B,
// C_13 = b,
// K Speichert die Kopplungskonstanten zu den anderen Populationen
//
/*void wendling::operator()(valarray<double>& y, valarray<double>& dxdt, valarray<double>&s) {
dxdt[0] = y[3];
dxdt[3] = params[10] * params[11] * sigmoid(y[1] - y[2]) - 2.0 * params[11] * y[3] - params[11] * params[11] * y[0];
dxdt[1] = y[4];
dxdt[4] = params[10]*params[11]*(couplingSum() + params[1] + params[7]*sigmoid(params[6]*y[0])) - 2 * params[11]*y[4] - params[11]*params[11]*y[1];
dxdt[2] = y[5];
dxdt[5] = params[12]*params[13]*(params[9]*sigmoid(params[8]*y[0])) - 2.0*params[13]*y[5] - params[13]*params[13]*y[2];
dxdt[6] = y[7];
dxdt[7] = params[10]*params[2]*sigmoid(y[1] - y[2]) - 2.0*params[2]*y[7] - params[2]*params[2]*y[6];
s[4] = params[10]*params[11]*params[0];
}
void coloredWendling::operator()(valarray<double>& y, valarray<double>& dxdt, valarray<double>&s) {
dxdt[0] = y[3];
dxdt[3] = getParams(10) * getParams(11) * sigmoid(y[1] - y[2]) - 2.0 * getParams(11) * y[3] - getParams(11) * getParams(11) * y[0];
dxdt[1] = y[4];
dxdt[4] = getParams(10)*getParams(11)*(couplingSum() + getParams(1) + getParams(0)*y[8] + getParams(7)*sigmoid(getParams(6)*y[0])) - 2 * getParams(11)*y[4] - getParams(11)*getParams(11)*y[1];
dxdt[2] = y[5];
dxdt[5] = getParams(12)*getParams(13)*(getParams(9)*sigmoid(getParams(8)*y[0])) - 2.0*getParams(13)*y[5] - getParams(13)*getParams(13)*y[2];
dxdt[6] = y[7];
dxdt[7] = getParams(10)*getParams(2)*sigmoid(y[1] - y[2]) - 2.0*getParams(2)*y[7] - getParams(2)*getParams(2)*y[6];
dxdt[8] = -1/getParams(14)*y[8];
s[8] = 1.0;
// cout << getParams(0) << ":" << getParams(3) << ":" << getParams (15) << endl;
// cout << "TMP:" << x[0] << " "<< x[1] << " "<< x[2] << " "<< x[3]<< " " << x[4] << endl;
}
*/
//void ornUhl::operator()(baseType x[], baseType dxdt[], baseType s[]) {
//
// //cout << getParams(0) << ":" << getParams(1) << endl;
//
// dxdt[0]=-1.0/params<baseType>::getParams(0) * x[0] + this->couplingSum();
// s[0]=sqrt(2.0 * params<baseType>::getParams(1))/params<baseType>::getParams(0);
//}
//
/*
void breakspear::operator()(valarray<double>& y, valarray<double>& dxdt, valarray<double>&s) {
double coupling = couplingSum();
Qtmp = S(y[0], params[14], params[15]);
dxdt[0] = -(params[2] + (1 - params[29])*params[27]*params[19]*Qtmp + params[29]*params[27]*params[19]*coupling)*
S(y[0], params[0], params[1])*(y[0] - params[3]) - params[6]*y[2]*(y[0] - params[7]) - params[13]*(y[0] - params[12])
- (params[10]*S(y[0], params[8], params[9]) + (1 - params[29])*params[19]*Qtmp + params[29]*params[19]*coupling)*(y[0] - params[11])
- params[21]*y[1]*S(y[1], params[16], params[17]);
dxdt[1] = params[24]*params[20]*y[0]*Qtmp;
dxdt[2] = params[25]/params[26]*(S(y[0], params[7], params[5]) - y[2]);
s[0] = params[22]*params[18];
s[1] = params[24]*params[23]*params[18];
};
void coloredBreakspear::operator()(valarray<double>& y, valarray<double>& dxdt, valarray<double>&s) {
double coupling = couplingSum();
Qtmp = S(y[0], params[14], params[15]);
dxdt[0] = -(params[2] + (1 - params[29])*params[27]*params[19]*Qtmp + params[29]*params[27]*params[19]*coupling)*
S(y[0], params[0], params[1])*(y[0] - params[3]) - params[6]*y[2]*(y[0] - params[7]) - params[13]*(y[0] - params[12])
- (params[10]*S(y[0], params[8], params[9]) + (1 - params[29])*params[19]*Qtmp + params[29]*params[19]*coupling)*(y[0] - params[11])
- params[21]*y[1]*S(y[1], params[16], params[17]) + params[22]*y[3];
dxdt[1] = params[24]*params[20]*y[0]*Qtmp + params[24]*params[23]*y[3];
dxdt[2] = params[25]/params[26]*(S(y[0], params[7], params[5]) - y[2]);
dxdt[3] = -1.0/params[30]*y[3];
s[3] = 1.0;
};
*/
}
// Node for Stochastic Differential Equations //