Eigen: Added simpler nonlinear functions

git-svn-id: svn://ultimatepp.org/upp/trunk@14465 f0d560ea-af0d-0410-9eb7-867de7ffcac7

uppsrc/plugin/Eigen/Eigen.cpp

@@ -1 +1,34 @@
-// Dummy file
+#include <Core/Core.h>
+#include <Eigen.h>
+
+
+namespace Upp {
+
+using namespace Eigen;
+
+bool NonLinearOptimization(VectorXd &y, int numData, Function <int(const VectorXd &b, VectorXd &residual)> Residual) {
+	Basic_functor functor(Residual);
+	functor.unknowns = y.size();
+	functor.datasetLen = numData;
+	Eigen::NumericalDiff<Basic_functor> numDiff(functor);
+	Eigen::LevenbergMarquardt<Eigen::NumericalDiff<Basic_functor> > lm(numDiff);
+	int ret = lm.minimize(y);
+	if (ret == Eigen::LevenbergMarquardtSpace::ImproperInputParameters || 
+		ret == Eigen::LevenbergMarquardtSpace::TooManyFunctionEvaluation)
+		return false;
+	return true;
+}
+
+bool NonLinearSolver(VectorXd &y, Function <int(const VectorXd &b, VectorXd &residual)> Residual) {
+	Basic_functor functor(Residual);
+	HybridNonLinearSolver<Basic_functor> solver(functor);
+	int ret = solver.solveNumericalDiff(y);
+	if (ret == HybridNonLinearSolverSpace::ImproperInputParameters ||
+	    ret == HybridNonLinearSolverSpace::TooManyFunctionEvaluation ||
+	    ret == HybridNonLinearSolverSpace::NotMakingProgressJacobian ||
+	    ret == HybridNonLinearSolverSpace::NotMakingProgressIterations)
+		return false;
+	return true;
+}
+
+}

uppsrc/plugin/Eigen/Eigen.h

@@ -51,20 +51,8 @@ struct Basic_functor : NonLinearOptimizationFunctor<double> {
 	Function <int(const Eigen::VectorXd &b, Eigen::VectorXd &err)> function;
 };
 
-template <class T>
-bool NonLinearOptimization(T &coeff, int numData, Function <int(const T &b, T &err)>function) {
-	Basic_functor functor(function);
-	functor.unknowns = coeff.size();
-	functor.datasetLen = numData;
-	Eigen::NumericalDiff<Basic_functor> numDiff(functor);
-	Eigen::LevenbergMarquardt<Eigen::NumericalDiff<Basic_functor> > lm(numDiff);
-	int ret = lm.minimize(coeff);
-	if (ret == Eigen::LevenbergMarquardtSpace::ImproperInputParameters || 
-		ret == Eigen::LevenbergMarquardtSpace::TooManyFunctionEvaluation)
-		return false;
-	return true;
-}
-
+bool NonLinearOptimization(Eigen::VectorXd &y, int numData, Function <int(const Eigen::VectorXd &y, Eigen::VectorXd &residual)>residual);
+bool NonLinearSolver(Eigen::VectorXd &y, Function <int(const Eigen::VectorXd &b, Eigen::VectorXd &residual)> Residual);
 
 template <class T>
 void Xmlize(XmlIO &xml, Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> &mat) {

uppsrc/plugin/Eigen/Eigen.upp

@@ -13,6 +13,7 @@ file
 	Eigen.cpp,
 	Eigen.h,
 	ToStringPlugin.h,
+	src.tpp,
 	srcdoc.tpp,
 	Copying,
 	Eigen readonly separator,

uppsrc/plugin/Eigen/src.tpp/NonLinear_en-us.tpp

@@ -0,0 +1,41 @@
+topic "";
+[H6;0 $$1,0#05600065144404261032431302351956:begin]
+[i448;a25;kKO9;2 $$2,0#37138531426314131252341829483370:codeitem]
+[l288;2 $$3,0#27521748481378242620020725143825:desc]
+[0 $$4,0#96390100711032703541132217272105:end]
+[ $$0,0#00000000000000000000000000000000:Default]
+[{_}%EN-US 
+[ {{10000@(113.42.0) [s0; [*@2;4 Nonlinear functions]]}}&]
+[s0;*@3;4 &]
+[s0; [2 Some functions have been include to ease nonlinear optimization 
+and equation system solving.]&]
+[s0;2 &]
+[s1;%- &]
+[s2;:Upp`:`:NonLinearOptimization`(Eigen`:`:VectorXd`&`,int`,Upp`:`:Function`<int`(const Eigen`:`:VectorXd`&`,Eigen`:`:VectorXd`&`)`>`):%- [@(0.0.255) b
+ool]_[* NonLinearOptimization]([_^Eigen`:`:VectorXd^ Eigen`::VectorXd]_`&[*@3 y], 
+[@(0.0.255) int]_[*@3 numData], [_^Upp`:`:Function^ Function]_<[@(0.0.255) int]([@(0.0.255) c
+onst]_[_^Eigen`:`:VectorXd^ Eigen`::VectorXd]_`&[*@3 y], [_^Eigen`:`:VectorXd^ Eigen`::Ve
+ctorXd]_`&[*@3 residual])>[*@3 Residual])&]
+[s3; Given a number of [%-*@3 numData] records, the objective is to 
+obtain in an iterative way the [%-*@3 y] unknown coefficients that 
+minimizes, ideally to zero, the [%-*@3 residual] error of the [%-*@3 Residual] 
+Function.&]
+[s3; To improve the success of this calculation, [%-*@3 y] has to be 
+initially filled with adequate initial guess of the unknowns.&]
+[s3; [%-*@3 Residual ]Function has to fill in every call [%-*@3 residual]`[[%-*@3 numData]`]
+ Vector by applying the unknowns provisionally guessed values 
+in [%-*@3 y] to the model to be solved.&]
+[s4; &]
+[s1;%- &]
+[s2;:Upp`:`:NonLinearSolver`(Eigen`:`:VectorXd`&`,Upp`:`:Function`<int`(const Eigen`:`:VectorXd`&b`,Eigen`:`:VectorXd`&residual`)`>`):%- [@(0.0.255) b
+ool]_[* NonLinearSolver]([_^Eigen`:`:VectorXd^ VectorXd]_`&[*@3 y], 
+[_^Upp`:`:Function^ Function]_<[@(0.0.255) int]([@(0.0.255) const]_[_^Eigen`:`:VectorXd^ E
+igen`::VectorXd]_`&[*@3 y], [_^Eigen`:`:VectorXd^ Eigen`::VectorXd]_`&[*@3 residual])>_[*@3 R
+esidual])&]
+[s3; Given a system of equations defined by Function [%-*@3 Residual], 
+and a set of initial values of the unknowns set in [%-*@3 y], this 
+function tries to obtain the set of [%-*@3 y] that best comply 
+with [%-*@3 Residual].&]
+[s3; The dimension of [%-*@3 y] ([%-*@3 y.size()]) has to be equal to 
+the number of equations ([%-*@3 residual.size()]).&]
+[s4; ]]

uppsrc/plugin/Eigen/src.tpp/all.i

@@ -0,0 +1,4 @@
+TOPIC("NonLinear_en-us")
+#include "NonLinear_en-us.tppi"
+END_TOPIC
+

uppsrc/plugin/Eigen/srcdoc.tpp/Eigen_en-us.tpp

@@ -31,7 +31,9 @@ to ease its use for U`+`+ users. It has many samples from Eigen
 library and nonlinear equation solving and optimization like 
 ][^http`:`/`/www`.itl`.nist`.gov`/div898`/strd`/nls`/data`/eckerle4`.shtml^2 Eckerl
 e4][2  and ][^http`:`/`/www`.itl`.nist`.gov`/div898`/strd`/nls`/data`/thurber`.shtml^2 T
-hurber][2  (see the graphs).]&]
+hurber][2  (see the graphs). To simplify access to these features, 
+][^topic`:`/`/plugin`/Eigen`/src`/NonLinear`_en`-us^2 simple functions][2  
+have been added.]&]
 [s0;#2 &]
 [s0;= [2 
 @@image:1272&1104

uppsrc/plugin/Eigen/srcdoc.tpp/NonLinear_en-us.tpp

@@ -1,4 +0,0 @@
-topic "";
-[ $$0,0#00000000000000000000000000000000:Default]
-[{_}%EN-US 
-[s0; ]