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@ -239,8 +239,8 @@ class Basis {
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* i.e., one row of the Kronecker product of weights_ with the
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* MxM identity matrix. See also VectorEvaluationFunctor.
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*/
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void calculateJacobian(size_t N) {
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H_.setZero(1, M_ * N);
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void calculateJacobian() {
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H_.setZero(1, M_ * EvaluationFunctor::weights_.size());
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for (int j = 0; j < EvaluationFunctor::weights_.size(); j++)
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H_(0, rowIndex_ + j * M_) = EvaluationFunctor::weights_(j);
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}
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@ -252,14 +252,14 @@ class Basis {
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/// Construct with row index
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VectorComponentFunctor(size_t M, size_t N, size_t i, double x)
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: EvaluationFunctor(N, x), M_(M), rowIndex_(i) {
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calculateJacobian(N);
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calculateJacobian();
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}
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/// Construct with row index and interval
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VectorComponentFunctor(size_t M, size_t N, size_t i, double x, double a,
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double b)
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: EvaluationFunctor(N, x, a, b), M_(M), rowIndex_(i) {
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calculateJacobian(N);
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calculateJacobian();
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}
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/// Calculate component of component rowIndex_ of P
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@ -460,8 +460,8 @@ class Basis {
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* i.e., one row of the Kronecker product of weights_ with the
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* MxM identity matrix. See also VectorDerivativeFunctor.
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*/
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void calculateJacobian(size_t N) {
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H_.setZero(1, M_ * N);
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void calculateJacobian() {
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H_.setZero(1, M_ * this->weights_.size());
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for (int j = 0; j < this->weights_.size(); j++)
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H_(0, rowIndex_ + j * M_) = this->weights_(j);
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}
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@ -473,14 +473,14 @@ class Basis {
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/// Construct with row index
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ComponentDerivativeFunctor(size_t M, size_t N, size_t i, double x)
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: DerivativeFunctorBase(N, x), M_(M), rowIndex_(i) {
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calculateJacobian(N);
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calculateJacobian();
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}
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/// Construct with row index and interval
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ComponentDerivativeFunctor(size_t M, size_t N, size_t i, double x, double a,
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double b)
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: DerivativeFunctorBase(N, x, a, b), M_(M), rowIndex_(i) {
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calculateJacobian(N);
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calculateJacobian();
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}
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/// Calculate derivative of component rowIndex_ of F
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double apply(const Matrix& P,
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@ -32,7 +32,7 @@ Weights Chebyshev2::CalculateWeights(size_t N, double x, double a, double b) {
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const double dj =
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x - Point(N, j, a, b); // only thing that depends on [a,b]
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if (std::abs(dj) < 1e-10) {
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if (std::abs(dj) < 1e-12) {
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// exceptional case: x coincides with a Chebyshev point
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weights.setZero();
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weights(j) = 1;
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@ -73,7 +73,7 @@ Weights Chebyshev2::DerivativeWeights(size_t N, double x, double a, double b) {
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for (size_t j = 0; j < N; j++) {
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const double dj =
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x - Point(N, j, a, b); // only thing that depends on [a,b]
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if (std::abs(dj) < 1e-10) {
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if (std::abs(dj) < 1e-12) {
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// exceptional case: x coincides with a Chebyshev point
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weightDerivatives.setZero();
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// compute the jth row of the differentiation matrix for this point
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@ -51,27 +51,30 @@ class GTSAM_EXPORT Chebyshev2 : public Basis<Chebyshev2> {
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using Parameters = Eigen::Matrix<double, /*Nx1*/ -1, 1>;
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using DiffMatrix = Eigen::Matrix<double, /*NxN*/ -1, -1>;
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/// Specific Chebyshev point
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static double Point(size_t N, int j) {
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/**
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* @brief Specific Chebyshev point, within [a,b] interval.
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* Default interval is [-1, 1]
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*
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* @param N The degree of the polynomial
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* @param j The index of the Chebyshev point
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* @param a Lower bound of interval (default: -1)
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* @param b Upper bound of interval (default: 1)
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* @return double
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*/
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static double Point(size_t N, int j, double a = -1, double b = 1) {
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assert(j >= 0 && size_t(j) < N);
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const double dtheta = M_PI / (N > 1 ? (N - 1) : 1);
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// We add -PI so that we get values ordered from -1 to +1
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// sin(- M_PI_2 + dtheta*j); also works
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return cos(-M_PI + dtheta * j);
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}
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/// Specific Chebyshev point, within [a,b] interval
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static double Point(size_t N, int j, double a, double b) {
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assert(j >= 0 && size_t(j) < N);
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const double dtheta = M_PI / (N - 1);
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// We add -PI so that we get values ordered from -1 to +1
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// sin(-M_PI_2 + dtheta*j); also works
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return a + (b - a) * (1. + cos(-M_PI + dtheta * j)) / 2;
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}
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/// All Chebyshev points
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static Vector Points(size_t N) {
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Vector points(N);
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for (size_t j = 0; j < N; j++) points(j) = Point(N, j);
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for (size_t j = 0; j < N; j++) {
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points(j) = Point(N, j);
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}
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return points;
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}
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@ -11,10 +11,9 @@ Author: Frank Dellaert & Gerry Chen (Python)
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import unittest
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import numpy as np
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from gtsam.utils.test_case import GtsamTestCase
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import gtsam
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from gtsam.utils.test_case import GtsamTestCase
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from gtsam.symbol_shorthand import B
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class TestBasis(GtsamTestCase):
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@ -26,6 +25,7 @@ class TestBasis(GtsamTestCase):
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Chebyshev bases, the line y=x is used to generate the data while for Fourier, 0.7*cos(x) is
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used.
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"""
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def setUp(self):
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self.N = 2
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self.x = [0., 0.5, 0.75]
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