curve_fitting.c 6.0 KB

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  1. /* Ceres Solver - A fast non-linear least squares minimizer
  2. * Copyright 2015 Google Inc. All rights reserved.
  3. * http://ceres-solver.org/
  4. *
  5. * Redistribution and use in source and binary forms, with or without
  6. * modification, are permitted provided that the following conditions are met:
  7. *
  8. * - Redistributions of source code must retain the above copyright notice,
  9. * this list of conditions and the following disclaimer.
  10. * - Redistributions in binary form must reproduce the above copyright notice,
  11. * this list of conditions and the following disclaimer in the documentation
  12. * and/or other materials provided with the distribution.
  13. * - Neither the name of Google Inc. nor the names of its contributors may be
  14. * used to endorse or promote products derived from this software without
  15. * specific prior written permission.
  16. *
  17. * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
  18. * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
  19. * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
  20. * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
  21. * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
  22. * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
  23. * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
  24. * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
  25. * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
  26. * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
  27. * POSSIBILITY OF SUCH DAMAGE.
  28. *
  29. * Author: mierle@gmail.com (Keir Mierle)
  30. *
  31. * This is a port of curve_fitting.cc to the minimal C API for Ceres.
  32. */
  33. #include <math.h>
  34. #include <stdio.h>
  35. #include <string.h> // For NULL
  36. #include "ceres/c_api.h"
  37. /* Data generated using the following octave code.
  38. *
  39. * randn('seed', 23497);
  40. * m = 0.3;
  41. * c = 0.1;
  42. * x=[0:0.075:5];
  43. * y = exp(m * x + c);
  44. * noise = randn(size(x)) * 0.2;
  45. * y_observed = y + noise;
  46. * data = [x', y_observed'];
  47. *
  48. */
  49. int num_observations = 67;
  50. double data[] = {
  51. 0.000000e+00, 1.133898e+00,
  52. 7.500000e-02, 1.334902e+00,
  53. 1.500000e-01, 1.213546e+00,
  54. 2.250000e-01, 1.252016e+00,
  55. 3.000000e-01, 1.392265e+00,
  56. 3.750000e-01, 1.314458e+00,
  57. 4.500000e-01, 1.472541e+00,
  58. 5.250000e-01, 1.536218e+00,
  59. 6.000000e-01, 1.355679e+00,
  60. 6.750000e-01, 1.463566e+00,
  61. 7.500000e-01, 1.490201e+00,
  62. 8.250000e-01, 1.658699e+00,
  63. 9.000000e-01, 1.067574e+00,
  64. 9.750000e-01, 1.464629e+00,
  65. 1.050000e+00, 1.402653e+00,
  66. 1.125000e+00, 1.713141e+00,
  67. 1.200000e+00, 1.527021e+00,
  68. 1.275000e+00, 1.702632e+00,
  69. 1.350000e+00, 1.423899e+00,
  70. 1.425000e+00, 1.543078e+00,
  71. 1.500000e+00, 1.664015e+00,
  72. 1.575000e+00, 1.732484e+00,
  73. 1.650000e+00, 1.543296e+00,
  74. 1.725000e+00, 1.959523e+00,
  75. 1.800000e+00, 1.685132e+00,
  76. 1.875000e+00, 1.951791e+00,
  77. 1.950000e+00, 2.095346e+00,
  78. 2.025000e+00, 2.361460e+00,
  79. 2.100000e+00, 2.169119e+00,
  80. 2.175000e+00, 2.061745e+00,
  81. 2.250000e+00, 2.178641e+00,
  82. 2.325000e+00, 2.104346e+00,
  83. 2.400000e+00, 2.584470e+00,
  84. 2.475000e+00, 1.914158e+00,
  85. 2.550000e+00, 2.368375e+00,
  86. 2.625000e+00, 2.686125e+00,
  87. 2.700000e+00, 2.712395e+00,
  88. 2.775000e+00, 2.499511e+00,
  89. 2.850000e+00, 2.558897e+00,
  90. 2.925000e+00, 2.309154e+00,
  91. 3.000000e+00, 2.869503e+00,
  92. 3.075000e+00, 3.116645e+00,
  93. 3.150000e+00, 3.094907e+00,
  94. 3.225000e+00, 2.471759e+00,
  95. 3.300000e+00, 3.017131e+00,
  96. 3.375000e+00, 3.232381e+00,
  97. 3.450000e+00, 2.944596e+00,
  98. 3.525000e+00, 3.385343e+00,
  99. 3.600000e+00, 3.199826e+00,
  100. 3.675000e+00, 3.423039e+00,
  101. 3.750000e+00, 3.621552e+00,
  102. 3.825000e+00, 3.559255e+00,
  103. 3.900000e+00, 3.530713e+00,
  104. 3.975000e+00, 3.561766e+00,
  105. 4.050000e+00, 3.544574e+00,
  106. 4.125000e+00, 3.867945e+00,
  107. 4.200000e+00, 4.049776e+00,
  108. 4.275000e+00, 3.885601e+00,
  109. 4.350000e+00, 4.110505e+00,
  110. 4.425000e+00, 4.345320e+00,
  111. 4.500000e+00, 4.161241e+00,
  112. 4.575000e+00, 4.363407e+00,
  113. 4.650000e+00, 4.161576e+00,
  114. 4.725000e+00, 4.619728e+00,
  115. 4.800000e+00, 4.737410e+00,
  116. 4.875000e+00, 4.727863e+00,
  117. 4.950000e+00, 4.669206e+00,
  118. };
  119. /* This is the equivalent of a use-defined CostFunction in the C++ Ceres API.
  120. * This is passed as a callback to the Ceres C API, which internally converts
  121. * the callback into a CostFunction. */
  122. static int exponential_residual(void* user_data,
  123. double** parameters,
  124. double* residuals,
  125. double** jacobians) {
  126. double* measurement = (double*) user_data;
  127. double x = measurement[0];
  128. double y = measurement[1];
  129. double m = parameters[0][0];
  130. double c = parameters[1][0];
  131. residuals[0] = y - exp(m * x + c);
  132. if (jacobians == NULL) {
  133. return 1;
  134. }
  135. if (jacobians[0] != NULL) {
  136. jacobians[0][0] = - x * exp(m * x + c); /* dr/dm */
  137. }
  138. if (jacobians[1] != NULL) {
  139. jacobians[1][0] = - exp(m * x + c); /* dr/dc */
  140. }
  141. return 1;
  142. }
  143. int main(int argc, char** argv) {
  144. /* Note: Typically it is better to compact m and c into one block,
  145. * but in this case use separate blocks to illustrate the use of
  146. * multiple parameter blocks. */
  147. double m = 0.0;
  148. double c = 0.0;
  149. double *parameter_pointers[] = { &m, &c };
  150. int parameter_sizes[] = { 1, 1 };
  151. int i;
  152. ceres_problem_t* problem;
  153. /* Ceres has some internal stuff that needs to get initialized. */
  154. ceres_init();
  155. problem = ceres_create_problem();
  156. /* Add all the residuals. */
  157. for (i = 0; i < num_observations; ++i) {
  158. ceres_problem_add_residual_block(
  159. problem,
  160. exponential_residual, /* Cost function */
  161. &data[2 * i], /* Points to the (x,y) measurement */
  162. NULL, /* No loss function */
  163. NULL, /* No loss function user data */
  164. 1, /* Number of residuals */
  165. 2, /* Number of parameter blocks */
  166. parameter_sizes,
  167. parameter_pointers);
  168. }
  169. ceres_solve(problem);
  170. ceres_free_problem(problem);
  171. printf("Initial m: 0.0, c: 0.0\n");
  172. printf("Final m: %g, c: %g\n", m, c);
  173. return 0;
  174. }