-
Notifications
You must be signed in to change notification settings - Fork 5
/
Copy pathfitdiff.h
231 lines (217 loc) · 8.3 KB
/
fitdiff.h
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
223
224
225
226
227
228
229
230
231
#ifndef FITDIFF_H
#define FITDIFF_H
#include "globals.h"
struct CDdiffFitmrq {
int ndata, ma, mfit;
std::vector< double > &x,&y,&sig;
int ndone, itmax;
double tol;
void (*funcs)(const double, std::vector< double > &, double &, std::vector< double > &);
std::vector< bool > ia;
std::vector< double > a;
std::vector< std::vector< double > > covar;
std::vector< std::vector< double > > alpha;
double chisq;
CDdiffFitmrq(std::vector< double > &xx, std::vector< double > &yy, std::vector< double > &ssig, std::vector< double > &aa,
std::vector< bool > &iia, void funks(const double, std::vector< double > &, double &, std::vector< double > &), const double
TOL=1.e-3, const int NDONE=4, const int ITMAX=1000) : ndata(xx.size()), ma(aa.size()), x(xx), y(yy), sig(ssig),
ndone(NDONE), itmax(ITMAX), tol(TOL), funcs(funks), ia(ma),
a(aa), covar(ma,std::vector<double>(ma,0)), alpha(ma,std::vector<double>(ma,0))
{
for (int i=0;i<ma;i++) ia[i] = iia[i];
}
void hold(const int i, const double val) {ia[i]=false; a[i]=val;}
void free(const int i) {ia[i]=true;}
void invertMatrix2(std::vector< std::vector< double > > &temp, std::vector< std::vector< double > > &unitVec)
{
double d1,d2,d3;
int column=0,row=0,n=temp.size(),m=unitVec[0].size();
std::vector< int > Col(n),Row(n),Pivot(n);
for (int i=0; i<n; i++)
Pivot[i]=0;
for (int i=0; i<n; i++)
{
d1=0.0;
for (int j=0; j<n; j++)
if (Pivot[j] != 1)
for (int k=0; k<n; k++)
{
if (Pivot[k] == 0)
{
if (abs(temp[j][k])>= d1)
{
d1=abs(temp[j][k]);
row=j;
column=k;
}
}
}
Pivot[column]+=1;
if (row != column)
{
for (int k=0; k<n; k++)
std::swap(temp[row][k],temp[column][k]);
for (int k=0; k<m; k++)
std::swap(unitVec[row][k],unitVec[column][k]);
}
Row[i]=row;
Col[i]=column;
if (temp[column][column] == 0.0)
{
extern QString matrixError;
matrixError = "Singular matrix, recheck your starting parameters.";
return;
}
d3=1.0/temp[column][column];
temp[column][column]=1.0;
for (int k=0; k<n; k++)
temp[column][k] *= d3;
for (int k=0; k<m; k++)
unitVec[column][k] *= d3;
for (int k=0; k<n; k++)
if (k != column)
{
d2=temp[k][column];
temp[k][column]=0.0;
for (int l=0; l<n; l++)
temp[k][l] -= temp[column][l]*d2;
for (int l=0; l<m; l++)
unitVec[k][l] -= unitVec[column][l]*d2;
}
}
for (int k=n-1; k>=0; k--)
{
if (Row[k] != Col[k])
for (int l=0; l<n; l++)
std::swap(temp[l][Row[k]],temp[l][Col[k]]);
}
}
void fit() {
int j,k,l,iter,done=0;
double alamda=.001,ochisq;
std::vector< double > atry(ma),beta(ma),da(ma);
mfit=0;
for (j=0;j<ma;j++) if (ia[j]) mfit++;
std::vector< std::vector< double > > oneda(mfit,std::vector<double>(1,0)), temp(mfit,std::vector<double>(mfit,0));
mrqcof(a,alpha,beta);
for (j=0;j<ma;j++) atry[j]=a[j];
ochisq=chisq;
for (iter=0;iter<itmax;iter++) {
if (done==ndone) alamda=0.;
for (j=0;j<mfit;j++) {
for (k=0;k<mfit;k++) covar[j][k]=alpha[j][k];
covar[j][j]=alpha[j][j]*(1.0+alamda);
for (k=0;k<mfit;k++) temp[j][k]=covar[j][k];
oneda[j][0]=beta[j];
}
if(mfit>0)
invertMatrix2(temp,oneda);
extern QString matrixError;
if(matrixError!="")
return;
for (j=0;j<mfit;j++) {
for (k=0;k<mfit;k++) covar[j][k]=temp[j][k];
da[j]=oneda[j][0];
}
if (done==ndone) {
covsrt(covar);
covsrt(alpha);
return;
}
for (j=0,l=0;l<ma;l++)
if (ia[l]) atry[l]=a[l]+da[j++];
mrqcof(atry,covar,da);
if (abs(chisq-ochisq) < std::max(tol,tol*chisq)) done++;
if (chisq < ochisq) {
alamda *= 0.1;
ochisq=chisq;
for (j=0;j<mfit;j++) {
for (k=0;k<mfit;k++) alpha[j][k]=covar[j][k];
beta[j]=da[j];
}
for (l=0;l<ma;l++) a[l]=atry[l];
} else {
alamda *= 10.0;
chisq=ochisq;
}
}
extern QString matrixError;
matrixError = "Too many iterations!\nRecheck your start parameters.";
}
void mrqcof(std::vector< double > &a, std::vector< std::vector< double > > &alpha, std::vector< double > &beta) {
int i,j,k,l,m;
double ymod,wt,sig2i,dy;
std::vector< double > dyda(ma);
for (j=0;j<mfit;j++) {
for (k=0;k<=j;k++) alpha[j][k]=0.0;
beta[j]=0.;
}
chisq=0.;
for (i=0;i<ndata;i++) {
funcs(x[i],a,ymod,dyda);
sig2i=1.0/(sig[i]*sig[i]);
dy=y[i]-ymod;
for (j=0,l=0;l<ma;l++) {
if (ia[l]) {
wt=dyda[l]*sig2i;
for (k=0,m=0;m<l+1;m++)
if (ia[m]) alpha[j][k++] += wt*dyda[m];
beta[j++] += dy*wt;
}
}
chisq += dy*dy*sig2i;
}
for (j=1;j<mfit;j++)
for (k=0;k<j;k++) alpha[k][j]=alpha[j][k];
}
void covsrt(std::vector< std::vector< double > > &covar) {
int i,j,k;
for (i=mfit;i<ma;i++)
for (j=0;j<i+1;j++) covar[i][j]=covar[j][i]=0.0;
k=mfit-1;
for (j=ma-1;j>=0;j--) {
if (ia[j]) {
for (i=0;i<ma;i++) std::swap(covar[i][k],covar[i][j]);
for (i=0;i<ma;i++) std::swap(covar[k][i],covar[j][i]);
k--;
}
}
}
// This is the public gridsearch
void gridSearch(std::vector< double > &aLo, std::vector< double > &aHi, std::vector< int > &aSteps, bool fgrid) {
if (fgrid) {
std::vector< double > aAct(aLo);
gridSearch(aLo, aHi, aSteps, aAct, 0);
}
}
// NOTE THIS VERSION SHOULD ONLY BE USED WITHIN THE CLASS
void gridSearch(std::vector< double > &aLo, std::vector< double > &aHi, std::vector< int > &aSteps, std::vector< double > &aAct, int index)
{
static double chisqLo = -1.;
static std::vector< double > dyda(ma);
double chisqGrid, yGrid;
for (int i=0; i<aSteps[index]; i++) {
if ((uint) index == a.size()-1) {
//cout << aAct[0] << " " << aAct[1] << " " << aAct[2] << " " << aAct[3] << " " << aAct[4] << " " << aAct[5] << endl;
chisqGrid = 0.;
for (int j=0; j<ndata; j++) {
funcs(x[j], aAct, yGrid, dyda);
chisqGrid += (yGrid -y[j]/sig[j])*(yGrid -y[j]/sig[j]);
}
if (chisqGrid < chisqLo || chisqLo == -1.) {
chisqLo = chisqGrid;
a = aAct;
}
}
else {
gridSearch(aLo, aHi, aSteps, aAct, index+1);
}
if(index == 2)
aAct[index] += aAct[index]*1.05;
else
aAct[index] += (aHi[index]-aLo[index])/(double)(aSteps[index]-1);
}
aAct[index] = aLo[index];
}
};
#endif // FITDIFF_H