67 lines
2.1 KiB
C
67 lines
2.1 KiB
C
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// Authors: Unknown. Please, if you are the author of this file, or if you
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// know who are the authors of this file, let us know, so we can give the
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// adequate credits and/or get the adequate authorizations.
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#ifndef NUMERICS_H
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#define NUMERICS_H
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#include "matrix.h"
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#include <vector>
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namespace libNumerics {
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class NumericsException {};
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class SvdConvergenceError : public NumericsException {};
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typedef double flnum;
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/// Solve system AX = B.
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bool solveLU(const matrix<flnum>& A, const vector<flnum>& B,
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vector<flnum>& X);
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bool solveLU(matrix<flnum> A, vector<flnum>& B);
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/// Singular Value Decomposition
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class SVD {
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public:
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SVD(const matrix<flnum>& A);
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matrix<flnum>& U() { return m_U; }
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vector<flnum>& W() { return m_W; }
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matrix<flnum>& V() { return m_V; }
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matrix<flnum> compose() const;
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private:
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matrix<flnum> m_U, m_V;
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vector<flnum> m_W;
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static flnum withSignOf(flnum a, flnum b);
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static flnum hypot(flnum a, flnum b);
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static void rotate(flnum& a, flnum& b, flnum c, flnum s);
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void compute();
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void sort();
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};
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/// Levenberg-Marquardt minimization.
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class MinLM {
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static const flnum DEFAULT_RELATIVE_TOL;
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static const flnum DEFAULT_LAMBDA_INIT;
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static const flnum DEFAULT_LAMBDA_FACT;
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static const flnum EPSILON_KERNEL;
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public:
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MinLM();
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flnum minimize(vector<flnum>& P, const vector<flnum>& ydata,
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flnum targetRMSE=0.1, int maxIters=300);
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virtual void modelData(const vector<flnum>& P,
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vector<flnum>& ymodel) const = 0;
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virtual void modelJacobian(const vector<flnum>& P,
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matrix<flnum>& J) const = 0;
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int iterations;
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flnum relativeTol;
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flnum lambdaInit;
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flnum lambdaFact;
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private:
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std::vector<int> m_nullCols;
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void compress(matrix<flnum>& JtJ, vector<flnum>& B);
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void uncompress(vector<flnum>& B);
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};
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} // namespace libNumerics
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#endif
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