mirror of
https://github.com/gnss-sdr/gnss-sdr
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81 lines
2.5 KiB
C++
81 lines
2.5 KiB
C++
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/*!
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* \file bayesian_estimation_positivity_test.cc
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* \brief This file implements timing tests for the Bayesian covariance estimator
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* \author Gerald LaMountain, 20168. gerald(at)ece.neu.edu
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*
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*
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* -------------------------------------------------------------------------
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*
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* Copyright (C) 2010-2018 (see AUTHORS file for a list of contributors)
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*
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* GNSS-SDR is a software defined Global Navigation
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* Satellite Systems receiver
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*
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* This file is part of GNSS-SDR.
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*
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* GNSS-SDR is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* GNSS-SDR is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with GNSS-SDR. If not, see <https://www.gnu.org/licenses/>.
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*
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* -------------------------------------------------------------------------
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*/
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#include <chrono>
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#include <complex>
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#include <random>
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#include <thread>
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#include <armadillo>
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#include <gtest/gtest.h>
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#include <gflags/gflags.h>
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#include <gnuradio/gr_complex.h>
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#include <volk_gnsssdr/volk_gnsssdr.h>
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#include "bayesian_estimation.h"
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#define BAYESIAN_TEST_N_TRIALS 100
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#define BAYESIAN_TEST_ITER 10000
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TEST(BayesianEstimationPositivityTest, BayesianPositivityTest)
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{
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Bayesian_estimator bayes;
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std::chrono::time_point<std::chrono::system_clock> start, end;
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std::chrono::duration<double> elapsed_seconds(0);
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arma::vec bayes_mu = arma::zeros(1, 1);
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int bayes_nu = 0;
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int bayes_kappa = 0;
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arma::mat bayes_Psi = arma::ones(1, 1);
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arma::vec input = arma::zeros(1, 1);
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arma::mat output = arma::ones(1, 1);
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//--- Perform initializations ------------------------------
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std::random_device r;
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std::default_random_engine e1(r());
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std::normal_distribution<float> normal_dist(0, 5);
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for (int k = 0; k < BAYESIAN_TEST_N_TRIALS; k++)
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{
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bayes.init(bayes_mu, bayes_kappa, bayes_nu, bayes_Psi);
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for (int n = 0; n < BAYESIAN_TEST_ITER; n++)
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{
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input(0) = (double)(normal_dist(e1));
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bayes.update_sequential(input);
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output = bayes.get_Psi_est();
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ASSERT_EQ(output(0) > 0, true);
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}
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}
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}
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