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1 | // This file is part of INSTINCT, the INS Toolkit for Integrated | ||
2 | // Navigation Concepts and Training by the Institute of Navigation of | ||
3 | // the University of Stuttgart, Germany. | ||
4 | // | ||
5 | // This Source Code Form is subject to the terms of the Mozilla Public | ||
6 | // License, v. 2.0. If a copy of the MPL was not distributed with this | ||
7 | // file, You can obtain one at https://mozilla.org/MPL/2.0/. | ||
8 | |||
9 | /// @file CubicSpline.hpp | ||
10 | /// @brief Cubic Spline class | ||
11 | /// @author T. Hobiger (thomas.hobiger@ins.uni-stuttgart.de) | ||
12 | /// @author T. Topp (topp@ins.uni-stuttgart.de) | ||
13 | /// @date 2022-06-06 | ||
14 | |||
15 | #pragma once | ||
16 | |||
17 | #include <cstdint> | ||
18 | #include <cstdio> | ||
19 | #include <cassert> | ||
20 | #include <cmath> | ||
21 | #include <vector> | ||
22 | #include <algorithm> | ||
23 | #include <sstream> | ||
24 | #include <string> | ||
25 | #include <iostream> | ||
26 | |||
27 | #include "util/Assert.h" | ||
28 | |||
29 | namespace NAV | ||
30 | { | ||
31 | |||
32 | /// Cubic Spline class | ||
33 | template<typename Scalar> | ||
34 | class CubicSpline | ||
35 | { | ||
36 | public: | ||
37 | /// @brief Boundary conditions for the spline end-points | ||
38 | struct BoundaryCondition | ||
39 | { | ||
40 | /// @brief Boundary type | ||
41 | enum BoundaryType : uint8_t | ||
42 | { | ||
43 | FirstDerivative = 1, ///< First derivative has to match a certain value | ||
44 | SecondDerivative = 2, ///< Second derivative has to match a certain value | ||
45 | NotAKnot = 3, ///< not-a-knot: At the first and last interior break, even the third derivative is continuous (up to round-off error). | ||
46 | }; | ||
47 | BoundaryType type = SecondDerivative; ///< Type of the boundary condition | ||
48 | Scalar value{ 0.0 }; ///< Value of the boundary condition | ||
49 | }; | ||
50 | |||
51 | /// @brief Default Constructor | ||
52 | 720 | CubicSpline() = default; | |
53 | |||
54 | /// @brief Constructor | ||
55 | /// @param[in] X List of x coordinates for the spline points/knots | ||
56 | /// @param[in] Y List of y coordinates for the spline points/knots | ||
57 | /// @param[in] leftBoundaryCondition Boundary condition for the start knot | ||
58 | /// @param[in] rightBoundaryCondition Boundary condition for the end knot | ||
59 | CubicSpline(const std::vector<Scalar>& X, const std::vector<Scalar>& Y, | ||
60 | BoundaryCondition leftBoundaryCondition = { BoundaryCondition::SecondDerivative, 0.0 }, | ||
61 | BoundaryCondition rightBoundaryCondition = { BoundaryCondition::SecondDerivative, 0.0 }) | ||
62 | : boundaryConditionLeft(leftBoundaryCondition), boundaryConditionRight(rightBoundaryCondition) | ||
63 | { | ||
64 | setPoints(X, Y); | ||
65 | } | ||
66 | |||
67 | /// @brief Set the boundaries conditions. Has to be called before setPoints | ||
68 | /// @param[in] leftBoundaryCondition Boundary condition for the start knot | ||
69 | /// @param[in] rightBoundaryCondition Boundary condition for the end knot | ||
70 | void setBoundaries(BoundaryCondition leftBoundaryCondition, BoundaryCondition rightBoundaryCondition) | ||
71 | { | ||
72 | boundaryConditionLeft = leftBoundaryCondition; | ||
73 | boundaryConditionRight = rightBoundaryCondition; | ||
74 | } | ||
75 | |||
76 | /// @brief Set the points/knots of the spline and calculate the spline coefficients | ||
77 | /// @param[in] x List of x coordinates of the points | ||
78 | /// @param[in] y List of y coordinates of the points | ||
79 | 48 | void setPoints(const std::vector<Scalar>& x, const std::vector<Scalar>& y) | |
80 | { | ||
81 |
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48 | vals_x = x; |
82 |
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48 | vals_y = y; |
83 | 48 | size_t n = x.size(); | |
84 | |||
85 |
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48 | size_t n_upper = (boundaryConditionLeft.type == BoundaryCondition::NotAKnot) ? 2 : 1; |
86 |
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48 | size_t n_lower = (boundaryConditionRight.type == BoundaryCondition::NotAKnot) ? 2 : 1; |
87 |
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48 | BandMatrix A(n, n_upper, n_lower); |
88 |
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48 | std::vector<Scalar> rhs(n); |
89 |
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8064720 | for (size_t i = 1; i < n - 1; i++) |
90 | { | ||
91 |
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8064672 | A(i, i - 1) = 1.0 / 3.0 * (x[i] - x[i - 1]); |
92 |
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8064672 | A(i, i) = 2.0 / 3.0 * (x[i + 1] - x[i - 1]); |
93 |
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8064672 | A(i, i + 1) = 1.0 / 3.0 * (x[i + 1] - x[i]); |
94 | 8064672 | rhs[i] = (y[i + 1] - y[i]) / (x[i + 1] - x[i]) - (y[i] - y[i - 1]) / (x[i] - x[i - 1]); | |
95 | } | ||
96 | // boundary conditions | ||
97 |
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48 | if (boundaryConditionLeft.type == BoundaryCondition::SecondDerivative) |
98 | { | ||
99 | // 2*c[0] = f'' | ||
100 |
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48 | A(0, 0) = 2.0; |
101 |
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48 | A(0, 1) = 0.0; |
102 | 48 | rhs[0] = boundaryConditionLeft.value; | |
103 | } | ||
104 | ✗ | else if (boundaryConditionLeft.type == BoundaryCondition::FirstDerivative) | |
105 | { | ||
106 | // b[0] = f', needs to be re-expressed in terms of c: | ||
107 | // (2c[0]+c[1])(x[1]-x[0]) = 3 ((y[1]-y[0])/(x[1]-x[0]) - f') | ||
108 | ✗ | A(0, 0) = 2.0 * (x[1] - x[0]); | |
109 | ✗ | A(0, 1) = 1.0 * (x[1] - x[0]); | |
110 | ✗ | rhs[0] = 3.0 * ((y[1] - y[0]) / (x[1] - x[0]) - boundaryConditionLeft.value); | |
111 | } | ||
112 | ✗ | else if (boundaryConditionLeft.type == BoundaryCondition::NotAKnot) | |
113 | { | ||
114 | // f'''(x[1]) exists, i.e. d[0]=d[1], or re-expressed in c: | ||
115 | // -h1*c[0] + (h0+h1)*c[1] - h0*c[2] = 0 | ||
116 | ✗ | A(0, 0) = -(x[2] - x[1]); | |
117 | ✗ | A(0, 1) = x[2] - x[0]; | |
118 | ✗ | A(0, 2) = -(x[1] - x[0]); | |
119 | ✗ | rhs[0] = 0.0; | |
120 | } | ||
121 |
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48 | if (boundaryConditionRight.type == BoundaryCondition::SecondDerivative) |
122 | { | ||
123 | // 2*c[n-1] = f'' | ||
124 |
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48 | A(n - 1, n - 1) = 2.0; |
125 |
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48 | A(n - 1, n - 2) = 0.0; |
126 | 48 | rhs[n - 1] = boundaryConditionRight.value; | |
127 | } | ||
128 | ✗ | else if (boundaryConditionRight.type == BoundaryCondition::FirstDerivative) | |
129 | { | ||
130 | // b[n-1] = f', needs to be re-expressed in terms of c: | ||
131 | // (c[n-2]+2c[n-1])(x[n-1]-x[n-2]) | ||
132 | // = 3 (f' - (y[n-1]-y[n-2])/(x[n-1]-x[n-2])) | ||
133 | ✗ | A(n - 1, n - 1) = 2.0 * (x[n - 1] - x[n - 2]); | |
134 | ✗ | A(n - 1, n - 2) = 1.0 * (x[n - 1] - x[n - 2]); | |
135 | ✗ | rhs[n - 1] = 3.0 * (boundaryConditionRight.value - (y[n - 1] - y[n - 2]) / (x[n - 1] - x[n - 2])); | |
136 | } | ||
137 | ✗ | else if (boundaryConditionRight.type == BoundaryCondition::NotAKnot) | |
138 | { | ||
139 | // f'''(x[n-2]) exists, i.e. d[n-3]=d[n-2], or re-expressed in c: | ||
140 | // -h_{n-2}*c[n-3] + (h_{n-3}+h_{n-2})*c[n-2] - h_{n-3}*c[n-1] = 0 | ||
141 | ✗ | A(n - 1, n - 3) = -(x[n - 1] - x[n - 2]); | |
142 | ✗ | A(n - 1, n - 2) = x[n - 1] - x[n - 3]; | |
143 | ✗ | A(n - 1, n - 1) = -(x[n - 2] - x[n - 3]); | |
144 | ✗ | rhs[0] = 0.0; | |
145 | } | ||
146 | |||
147 | // solve the equation system to obtain the parameters c[] | ||
148 |
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48 | coef_c = A.lu_solve(rhs); |
149 | |||
150 | // calculate parameters b[] and d[] based on c[] | ||
151 |
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48 | coef_d.resize(n); |
152 |
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48 | coef_b.resize(n); |
153 |
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8064767 | for (size_t i = 0; i < n - 1; i++) |
154 | { | ||
155 | 8064719 | coef_d[i] = 1.0 / 3.0 * (coef_c[i + 1] - coef_c[i]) / (x[i + 1] - x[i]); | |
156 | 16129438 | coef_b[i] = (y[i + 1] - y[i]) / (x[i + 1] - x[i]) | |
157 | 8064720 | - 1.0 / 3.0 * (2.0 * coef_c[i] + coef_c[i + 1]) * (x[i + 1] - x[i]); | |
158 | } | ||
159 | // for the right extrapolation coefficients (zero cubic term) | ||
160 | // f_{n-1}(x) = y_{n-1} + b*(x-x_{n-1}) + c*(x-x_{n-1})^2 | ||
161 | 48 | auto h = x[n - 1] - x[n - 2]; | |
162 | // coef_c[n-1] is determined by the boundary condition | ||
163 | 48 | coef_d[n - 1] = 0.0; | |
164 | 48 | coef_b[n - 1] = 3.0 * coef_d[n - 2] * h * h + 2.0 * coef_c[n - 2] * h + coef_b[n - 2]; // = f'_{n-2}(x_{n-1}) | |
165 |
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48 | if (boundaryConditionRight.type == BoundaryCondition::FirstDerivative) |
166 | { | ||
167 | ✗ | coef_c[n - 1] = 0.0; // force linear extrapolation | |
168 | } | ||
169 | // for left extrapolation coefficients | ||
170 |
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48 | coef_c0 = (boundaryConditionLeft.type == BoundaryCondition::FirstDerivative) ? 0.0 : coef_c[0]; |
171 | 48 | } | |
172 | |||
173 | /// @brief Returns the size of the spline vector | ||
174 | ✗ | [[nodiscard]] size_t size() const noexcept | |
175 | { | ||
176 | ✗ | return vals_x.size(); | |
177 | } | ||
178 | |||
179 | /// @brief Interpolates or extrapolates a value on the spline | ||
180 | /// @param[in] x X coordinate to inter-/extrapolate the value for | ||
181 | /// @return The y coordinate | ||
182 | 21666422 | [[nodiscard]] Scalar operator()(Scalar x) const | |
183 | { | ||
184 | 21666422 | size_t n = vals_x.size(); | |
185 | 21669295 | size_t idx = findClosestIdx(x); | |
186 | |||
187 | 21660240 | auto h = x - vals_x[idx]; | |
188 | |||
189 |
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21661682 | if (x < vals_x[0]) // extrapolation to the left |
190 | { | ||
191 | ✗ | return (coef_c0 * h + coef_b[0]) * h + vals_y[0]; | |
192 | } | ||
193 |
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21667810 | if (x > vals_x[n - 1]) // extrapolation to the right |
194 | { | ||
195 | ✗ | return (coef_c[n - 1] * h + coef_b[n - 1]) * h + vals_y[n - 1]; | |
196 | } | ||
197 | // interpolation | ||
198 | 21671729 | return ((coef_d[idx] * h + coef_c[idx]) * h + coef_b[idx]) * h + vals_y[idx]; | |
199 | } | ||
200 | |||
201 | /// @brief Calculates the derivative of the spline | ||
202 | /// @param[in] order Order of the derivative to calculate (<= 3) | ||
203 | /// @param[in] x X coordinate to calculate the derivative for | ||
204 | /// @return The derivative of y up to the given order | ||
205 | 29893835 | [[nodiscard]] Scalar derivative(size_t order, Scalar x) const | |
206 | { | ||
207 | 29893835 | size_t n = vals_x.size(); | |
208 | 29892860 | size_t idx = findClosestIdx(x); | |
209 | |||
210 | 29879678 | auto h = x - vals_x[idx]; | |
211 |
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29885599 | if (x < vals_x[0]) // extrapolation to the left |
212 | { | ||
213 | ✗ | switch (order) | |
214 | { | ||
215 | ✗ | case 1: | |
216 | ✗ | return 2.0 * coef_c0 * h + coef_b[0]; | |
217 | ✗ | case 2: | |
218 | ✗ | return 2.0 * coef_c0; | |
219 | ✗ | default: | |
220 | ✗ | return 0.0; | |
221 | } | ||
222 | } | ||
223 |
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29915028 | else if (x > vals_x[n - 1]) // extrapolation to the right |
224 | { | ||
225 | ✗ | switch (order) | |
226 | { | ||
227 | ✗ | case 1: | |
228 | ✗ | return 2.0 * coef_c[n - 1] * h + coef_b[n - 1]; | |
229 | ✗ | case 2: | |
230 | ✗ | return 2.0 * coef_c[n - 1]; | |
231 | ✗ | default: | |
232 | ✗ | return 0.0; | |
233 | } | ||
234 | } | ||
235 | else // interpolation | ||
236 | { | ||
237 |
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29906649 | switch (order) |
238 | { | ||
239 | 21277835 | case 1: | |
240 | 21277835 | return (3.0 * coef_d[idx] * h + 2.0 * coef_c[idx]) * h + coef_b[idx]; | |
241 | 8594923 | case 2: | |
242 | 8594923 | return 6.0 * coef_d[idx] * h + 2.0 * coef_c[idx]; | |
243 | ✗ | case 3: | |
244 | ✗ | return 6.0 * coef_d[idx]; | |
245 | 33891 | default: | |
246 | 33891 | return 0.0; | |
247 | } | ||
248 | } | ||
249 | } | ||
250 | |||
251 | private: | ||
252 | std::vector<Scalar> vals_x; ///< x coordinates of the knots | ||
253 | std::vector<Scalar> vals_y; ///< y coordinates of the knots | ||
254 | std::vector<Scalar> coef_b; ///< Spline coefficients b | ||
255 | std::vector<Scalar> coef_c; ///< Spline coefficients c | ||
256 | std::vector<Scalar> coef_d; ///< Spline coefficients d | ||
257 | Scalar coef_c0{ 0.0 }; ///< Spline coefficient c0 for left extrapolation | ||
258 | |||
259 | BoundaryCondition boundaryConditionLeft; ///< Boundary condition for the left knot | ||
260 | BoundaryCondition boundaryConditionRight; ///< Boundary condition for the right knot | ||
261 | |||
262 | /// @brief Finds the closest index so that vals_x[idx] <= x (return 0 if x < vals_x[0]) | ||
263 | /// @param[in] x X coordinate to search the closest knot to | ||
264 | /// @return Index of a knot closest to the x coordinate given | ||
265 | 51557009 | [[nodiscard]] size_t findClosestIdx(Scalar x) const | |
266 | { | ||
267 |
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51557009 | auto it = std::upper_bound(vals_x.begin(), vals_x.end(), x); |
268 | 51563334 | return static_cast<size_t>(std::max(static_cast<int>(it - vals_x.begin()) - 1, 0)); | |
269 | } | ||
270 | |||
271 | /// Sparse matrix whose non-zero entries are confined to a diagonal band, comprising the main diagonal and zero or more diagonals on either side. | ||
272 | class BandMatrix | ||
273 | { | ||
274 | public: | ||
275 | /// @brief Constructor | ||
276 | /// @param[in] dim Dimension of the matrix | ||
277 | /// @param[in] nUpper Amount of upper diagonals | ||
278 | /// @param[in] nLower Amount of lower diagonals | ||
279 | 48 | BandMatrix(size_t dim, size_t nUpper, size_t nLower) | |
280 |
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144 | : upperBand(nUpper + 1, std::vector<Scalar>(dim)), |
281 |
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144 | lowerBand(nLower + 1, std::vector<Scalar>(dim)) {} |
282 | |||
283 | /// @brief Access operator i ∈ [i=0,...,dim()-1] | ||
284 | 129035680 | Scalar& operator()(size_t i, size_t j) | |
285 | { | ||
286 | 129035680 | return const_cast<Scalar&>(static_cast<const CubicSpline::BandMatrix&>(*this)(i, j)); // NOLINT(cppcoreguidelines-pro-type-const-cast) | |
287 | } | ||
288 | /// @brief Access operator i ∈ [i=0,...,dim()-1] | ||
289 | 153229815 | [[nodiscard]] const Scalar& operator()(size_t i, size_t j) const | |
290 | { | ||
291 | // j - i = 0 -> diagonal, > 0 upper right part, < 0 lower left part | ||
292 |
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153229815 | return j >= i ? upperBand[j - i][i] : lowerBand[i - j][i]; |
293 | } | ||
294 | |||
295 | /// Solves the linear equations Ax = b for x by obtaining the LU decomposition A = LU and solving | ||
296 | /// - Ly = b for y | ||
297 | /// - Ux = y for x | ||
298 | 48 | [[nodiscard]] std::vector<Scalar> lu_solve(const std::vector<Scalar>& b, bool is_lu_decomposed = false) | |
299 | { | ||
300 |
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48 | INS_ASSERT_USER_ERROR(dim() == b.size(), "The BandMatrix dimension must be the same as the vector b in the equation Ax = b."); |
301 | |||
302 |
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48 | if (!is_lu_decomposed) |
303 | { | ||
304 |
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48 | lu_decompose(); |
305 | } | ||
306 |
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48 | auto y = l_solve(b); |
307 |
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48 | auto x = u_solve(y); |
308 | 96 | return x; | |
309 | 48 | } | |
310 | |||
311 | private: | ||
312 | /// Returns the matrix dimension | ||
313 | 56453732 | [[nodiscard]] size_t dim() const | |
314 | { | ||
315 |
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56453732 | return !upperBand.empty() ? upperBand[0].size() : 0; |
316 | } | ||
317 | /// Returns the dimension of the upper band | ||
318 | 24194252 | [[nodiscard]] size_t dimUpperBand() const | |
319 | { | ||
320 | 24194252 | return upperBand.size() - 1; | |
321 | } | ||
322 | /// Returns the dimension of the lower band | ||
323 | 40323644 | [[nodiscard]] size_t dimLowerBand() const | |
324 | { | ||
325 | 40323644 | return lowerBand.size() - 1; | |
326 | } | ||
327 | |||
328 | /// @brief Calculate the LU decomposition | ||
329 | 48 | void lu_decompose() | |
330 | { | ||
331 | // preconditioning | ||
332 | // normalize column i so that a_ii=1 | ||
333 |
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8064816 | for (size_t i = 0; i < dim(); i++) |
334 | { | ||
335 |
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8064768 | assert(this->operator()(i, i) != 0.0); |
336 | 8064768 | lowerBand[0][i] = 1.0 / this->operator()(i, i); | |
337 |
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8064768 | size_t j_min = i > dimLowerBand() ? i - dimLowerBand() : 0; |
338 | 8064768 | size_t j_max = std::min(dim() - 1, i + dimUpperBand()); | |
339 |
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32258976 | for (size_t j = j_min; j <= j_max; j++) |
340 | { | ||
341 | 24194208 | this->operator()(i, j) *= lowerBand[0][i]; | |
342 | } | ||
343 | 8064768 | this->operator()(i, i) = 1.0; // prevents rounding errors | |
344 | } | ||
345 | |||
346 | // Gauss LR-Decomposition | ||
347 |
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8064816 | for (size_t k = 0; k < dim(); k++) |
348 | { | ||
349 | 8064768 | size_t i_max = std::min(dim() - 1, k + dimLowerBand()); | |
350 |
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16129488 | for (size_t i = k + 1; i <= i_max; i++) |
351 | { | ||
352 |
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8064720 | assert(this->operator()(k, k) != 0.0); |
353 | |||
354 | 8064720 | auto x = -this->operator()(i, k) / this->operator()(k, k); | |
355 | 8064720 | this->operator()(i, k) = -x; // assembly part of L | |
356 | 8064720 | size_t j_max = std::min(dim() - 1, k + dimUpperBand()); | |
357 |
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16129440 | for (size_t j = k + 1; j <= j_max; j++) |
358 | { | ||
359 | // assembly part of R | ||
360 | 8064720 | this->operator()(i, j) = this->operator()(i, j) + x * this->operator()(k, j); | |
361 | } | ||
362 | } | ||
363 | } | ||
364 | 48 | } | |
365 | |||
366 | /// Solves the equation Lx = b for x | ||
367 | 48 | [[nodiscard]] std::vector<Scalar> l_solve(const std::vector<Scalar>& b) const | |
368 | { | ||
369 |
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48 | INS_ASSERT_USER_ERROR(dim() == b.size(), "The BandMatrix dimension must be the same as the vector b in the equation Ax = b."); |
370 | |||
371 |
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48 | std::vector<Scalar> x(dim()); |
372 |
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8064816 | for (size_t i = 0; i < dim(); i++) |
373 | { | ||
374 | 8064768 | Scalar sum = 0; | |
375 |
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8064768 | size_t j_start = i > dimLowerBand() ? i - dimLowerBand() : 0; |
376 |
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16129488 | for (size_t j = j_start; j < i; j++) |
377 | { | ||
378 | 8064720 | sum += this->operator()(i, j) * x[j]; | |
379 | } | ||
380 | 8064768 | x[i] = (b[i] * lowerBand[0][i]) - sum; | |
381 | } | ||
382 | 48 | return x; | |
383 | } | ||
384 | /// Solves the equation Ux = b for x | ||
385 | 48 | [[nodiscard]] std::vector<Scalar> u_solve(const std::vector<Scalar>& b) const | |
386 | { | ||
387 |
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48 | INS_ASSERT_USER_ERROR(dim() == b.size(), "The BandMatrix dimension must be the same as the vector b in the equation Ax = b."); |
388 | |||
389 |
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48 | std::vector<Scalar> x(dim()); |
390 |
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8064816 | for (size_t i = dim(); i-- > 0;) |
391 | { | ||
392 | 8064767 | Scalar sum = 0; | |
393 | 8064767 | size_t j_stop = std::min(dim() - 1, i + dimUpperBand()); | |
394 |
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16129487 | for (size_t j = i + 1; j <= j_stop; j++) |
395 | { | ||
396 | 8064720 | sum += this->operator()(i, j) * x[j]; | |
397 | } | ||
398 | 8064767 | x[i] = (b[i] - sum) / this->operator()(i, i); | |
399 | } | ||
400 | 48 | return x; | |
401 | } | ||
402 | |||
403 | std::vector<std::vector<Scalar>> upperBand; ///< upper diagonal band | ||
404 | std::vector<std::vector<Scalar>> lowerBand; ///< lower diagonal band | ||
405 | }; | ||
406 | }; | ||
407 | |||
408 | } // namespace NAV | ||
409 |