1 #ifndef __JFIT__JGRADIENT__
2 #define __JFIT__JGRADIENT__
21 namespace JPP {
using namespace JFIT; }
40 virtual void apply(
const double step) = 0;
48 public std::shared_ptr<JParameter_t>
91 const int debug = 3) :
120 return numeric_limits<double>::max();
125 const size_t N = this->size();
130 for (
size_t i = 0;
i !=
N; ++
i) {
136 size_t number_of_iterations = 0;
138 for ( ; number_of_iterations !=
Nmax; ++number_of_iterations) {
140 DEBUG(
"chi2[0] " << setw(4) << number_of_iterations <<
' ' <<
FIXED(12,5) <<
chi2[0] << endl);
149 for (
double ds = 1.0; ds > 1.0e-3; ) {
151 this->
move(+1.0 * ds);
155 DEBUG(
"chi2[3] " << setw(4) << m <<
' ' <<
FIXED(12,5) <<
chi2[3] <<
' ' <<
FIXED(12,5) << ds << endl);
181 for ( ; m != 0; --m) {
182 this->
move(-1.0 * ds);
189 this->
move(-1.0 * ds);
199 const double f21 =
chi2[2] -
chi2[1];
200 const double f23 = chi2[2] - chi2[3];
202 const double xs = 0.5 * (f21 - f23) / (f23 + f21);
204 this->
move(+1.0 * xs * ds);
208 if (chi2[3] < chi2[2]) {
214 this->
move(-1.0 * xs * ds);
219 DEBUG(
"chi2[2] " << setw(4) << number_of_iterations <<
' ' <<
FIXED(12,5) << chi2[2] <<
' ' <<
SCIENTIFIC(12,5) << ds << endl);
241 for (
size_t i = 0;
i !=
N; ++
i){
252 for (
size_t i = 0;
i !=
N; ++
i){
254 H[
i] = G[
i] + dgg * H[
i];
259 DEBUG(
"chi2[0] " << setw(4) << number_of_iterations <<
' ' <<
FIXED(12,5) <<
chi2[0] << endl);
280 const size_t N = this->size();
292 for (
size_t i = 0;
i !=
N; ++
i) {
293 if ((*
this)[
i].
name.size() > width) {
294 width = (*this)[
i].name.size();
300 for (
size_t i = 0;
i !=
N; ++
i) {
302 if ((*
this)[
i].value != 0.0) {
304 (*this)[
i]->apply(+0.5 * (*
this)[
i].value);
308 (*this)[
i]->apply(-0.5 * (*
this)[
i].value);
309 (*this)[
i]->apply(-0.5 * (*
this)[
i].value);
315 (*this)[
i]->apply(+0.5 * (*
this)[
i].value);
327 DEBUG(setw(width) << left <<
"|gradient|" << right <<
' ' <<
FIXED(12,5) << sqrt(
V) << endl);
339 for (
size_t i = 0;
i != this->size(); ++
i) {
340 (*this)[
i ]->apply((*
this)[
i ].value *
gradient[
i ] * factor);
342 }
else if (factor < 0.0) {
343 for (
size_t i = this->size();
i != 0; --
i) {
344 (*this)[
i-1]->apply((*
this)[
i-1].value *
gradient[
i-1] * factor);
JModifier_t(const std::string &name, JParameter_t *parameter, const double value)
Constructor.
void move(const double factor)
Move.
virtual ~JParameter_t()
Virtual destructor.
then echo Enter input within $TIMEOUT_S seconds echo n User name
double operator()(const T &getChi2)
Fit.
static const double H
Planck constant [eV s].
void evaluate(const T &getChi2)
Evaluate gradient.
Auxiliary data structure for floating point format specification.
V(JDAQEvent-JTriggerReprocessor)*1.0/(JDAQEvent+1.0e-10)
size_t Nextra
maximum number of extra steps
do set_variable OUTPUT_DIRECTORY $WORKDIR T
JGradient(const size_t Nmax=std::numeric_limits< size_t >::max(), const size_t Nextra=0, const double epsilon=1.0e-4, const int debug=3)
Constructor.
std::vector< double > gradient
virtual void apply(const double step)=0
Apply step.
size_t Nmax
maximum number of iterations
Auxiliary data structure for fit parameter.
General purpose messaging.
Auxiliary data structure for editable parameter.
then usage $script< input file >[option[primary[working directory]]] nWhere option can be N
double getChi2(const double P)
Get chi2 corresponding to given probability.
Auxiliary data structure for floating point format specification.
#define DEBUG(A)
Message macros.