1 /*
2 * Copyright 2017, Max Planck Society.
3 * All rights reserved.
4 *
5 * Redistribution and use in source and binary forms, with or without modification,
6 * are permitted provided that the following conditions are met:
7 *
8 * 1. Redistributions of source code must retain the above copyright notice,
9 * this list of conditions and the following disclaimer.
10 *
11 * 2. Redistributions in binary form must reproduce the above copyright notice,
12 * this list of conditions and the following disclaimer in the documentation
13 * and/or other materials provided with the distribution.
14 *
15 * 3. Neither the name of the copyright holder nor the names of its contributors
16 * may be used to endorse or promote products derived from this software without
17 * specific prior written permission.
18 *
19 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
20 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
21 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
22 * IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT,
23 * INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
24 * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
25 * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
26 * LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE
27 * OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED
28 * OF THE POSSIBILITY OF SUCH DAMAGE.
29 *
30 */
31
32 /* Created by Edgar Klenske <edgar.klenske@tuebingen.mpg.de>
33 */
34
35 #include "gaussian_process_guider.h"
36 #include "guide_performance_tools.h"
37
main(int argc,char ** argv)38 int main(int argc, char** argv)
39 {
40 if (argc < 15)
41 return -1;
42
43 GaussianProcessGuider* GPG;
44
45 GaussianProcessGuider::guide_parameters parameters;
46
47 // use parameters from command line
48 parameters.control_gain_ = std::stod(argv[2]);
49 parameters.min_periods_for_inference_ = std::stod(argv[3]);
50 parameters.min_move_ = std::stod(argv[4]);
51 parameters.SE0KLengthScale_ = std::stod(argv[5]);
52 parameters.SE0KSignalVariance_ = std::stod(argv[6]);
53 parameters.PKLengthScale_ = std::stod(argv[7]);
54 parameters.PKPeriodLength_ = std::stod(argv[8]);
55 parameters.PKSignalVariance_ = std::stod(argv[9]);
56 parameters.SE1KLengthScale_ = std::stod(argv[10]);
57 parameters.SE1KSignalVariance_ = std::stod(argv[11]);
58 parameters.min_periods_for_period_estimation_ = std::stod(argv[12]);
59 parameters.points_for_approximation_ = static_cast<int>(std::floor(std::stod(argv[13])));
60 parameters.prediction_gain_ = std::stod(argv[14]);
61 parameters.compute_period_ = true;
62
63 GPG = new GaussianProcessGuider(parameters);
64
65 GAHysteresis GAH;
66
67 std::string filename;
68
69 filename = argv[1];
70 double improvement = calculate_improvement(filename, GAH, GPG);
71
72 std::cout << improvement << std::endl;
73
74 return 0;
75 }
76