interp_fit.h

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/* +------------------------------------------------------------------------+
   |                     Mobile Robot Programming Toolkit (MRPT)            |
   |                          https://www.mrpt.org/                         |
   |                                                                        |
   | Copyright (c) 2005-2019, Individual contributors, see AUTHORS file     |
   | See: https://www.mrpt.org/Authors - All rights reserved.               |
   | Released under BSD License. See: https://www.mrpt.org/License          |
   +------------------------------------------------------------------------+ */
#pragma once

#include <mrpt/math/CMatrixDynamic.h>
#include <mrpt/math/wrap2pi.h>

namespace mrpt::math
{
/** @addtogroup interpolation_grp Interpolation, least-squares fit, splines
 * \ingroup mrpt_math_grp
 *  @{ */

/** Interpolate a data sequence "ys" ranging from "x0" to "x1" (equally spaced),
 * to obtain the approximation of the sequence at the point "x".
 *  If the point "x" is out of the range [x0,x1], the closest extreme "ys"
 * value is returned.
 * \note Implementation in `#include <mrpt/math/interp_fit.hpp>`
 * \sa spline, interpolate2points
 */
template <class T, class VECTOR>
T interpolate(const T& x, const VECTOR& ys, const T& x0, const T& x1);

/** Linear interpolation/extrapolation: evaluates at "x" the line
 * (x0,y0)-(x1,y1).
 *  If wrap2pi is true, output is wrapped to ]-pi,pi] (It is assumed that input
 * "y" values already are in the correct range).
 * \sa spline, interpolate, leastSquareLinearFit
 */
double interpolate2points(
    const double x, const double x0, const double y0, const double x1,
    const double y1, bool wrap2pi = false);

/** Interpolates the value of a function in a point "t" given 4 SORTED points
 * where "t" is between the two middle points
 *  If wrap2pi is true, output "y" values are wrapped to ]-pi,pi] (It is
 * assumed that input "y" values already are in the correct range).
 * \sa leastSquareLinearFit
 * \note Implementation in `#include <mrpt/math/interp_fit.hpp>`
 */
template <typename NUMTYPE, class VECTORLIKE>
NUMTYPE spline(
    const NUMTYPE t, const VECTORLIKE& x, const VECTORLIKE& y,
    bool wrap2pi = false);

/** Interpolates or extrapolates using a least-square linear fit of the set of
 * values "x" and "y", evaluated at a single point "t".
 *  The vectors x and y must have size >=2, and all values of "x" must be
 * different.
 *  If wrap2pi is true, output "y" values are wrapped to ]-pi,pi] (It is
 * assumed that input "y" values already are in the correct range).
 * \sa spline
 * \sa getRegressionLine, getRegressionPlane
 * \note Implementation in `#include <mrpt/math/interp_fit.hpp>`
 */
template <
    typename NUMTYPE, class VECTORLIKE, int NUM_POINTS = -1 /*Eigen::Dynamic*/>
NUMTYPE leastSquareLinearFit(
    const NUMTYPE t, const VECTORLIKE& x, const VECTORLIKE& y,
    bool wrap2pi = false);

/** Interpolates or extrapolates using a least-square linear fit of the set of
 * values "x" and "y", evaluated at a sequence of points "ts" and returned at
 * "outs".
 *  If wrap2pi is true, output "y" values are wrapped to ]-pi,pi] (It is
 * assumed that input "y" values already are in the correct range).
 * \sa spline, getRegressionLine, getRegressionPlane
 * \note Implementation in `#include <mrpt/math/interp_fit.hpp>`
 * \note Requires `#include <Eigen/Dense>`
 */
template <
    class VECTORLIKE1, class VECTORLIKE2, class VECTORLIKE3,
    int NUM_POINTS = -1 /*Eigen::Dynamic*/>
void leastSquareLinearFit(
    const VECTORLIKE1& ts, VECTORLIKE2& outs, const VECTORLIKE3& x,
    const VECTORLIKE3& y, bool wrap2pi = false);

/** @} */  // end grouping interpolation_grp

}  // namespace mrpt::math