src/gromacs/math/tests/exponentialmovingaverage.cpp

   1 /*
   2  * This file is part of the GROMACS molecular simulation package.
   3  *
   4  * Copyright (c) 2019, by the GROMACS development team, led by
   5  * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
   6  * and including many others, as listed in the AUTHORS file in the
   7  * top-level source directory and at http://www.gromacs.org.
   8  *
   9  * GROMACS is free software; you can redistribute it and/or
  10  * modify it under the terms of the GNU Lesser General Public License
  11  * as published by the Free Software Foundation; either version 2.1
  12  * of the License, or (at your option) any later version.
  13  *
  14  * GROMACS is distributed in the hope that it will be useful,
  15  * but WITHOUT ANY WARRANTY; without even the implied warranty of
  16  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
  17  * Lesser General Public License for more details.
  18  *
  19  * You should have received a copy of the GNU Lesser General Public
  20  * License along with GROMACS; if not, see
  21  * http://www.gnu.org/licenses, or write to the Free Software Foundation,
  22  * Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA.
  23  *
  24  * If you want to redistribute modifications to GROMACS, please
  25  * consider that scientific software is very special. Version
  26  * control is crucial - bugs must be traceable. We will be happy to
  27  * consider code for inclusion in the official distribution, but
  28  * derived work must not be called official GROMACS. Details are found
  29  * in the README & COPYING files - if they are missing, get the
  30  * official version at http://www.gromacs.org.
  31  *
  32  * To help us fund GROMACS development, we humbly ask that you cite
  33  * the research papers on the package. Check out http://www.gromacs.org.
  34  */
  35 /*! \internal \file
  36  * \brief
  37  * Tests for the exponential moving average.
  38  *
  39  * \author Christian Blau <blau@kth.se>
  40  * \ingroup module_math
  41  */
  42 #include "gmxpre.h"
  43
  44 #include "gromacs/math/exponentialmovingaverage.h"
  45
  46 #include <gtest/gtest.h>
  47
  48 #include "testutils/testasserts.h"
  49
  50 namespace gmx
  51 {
  52
  53 namespace test
  54 {
  55
  56 namespace
  57 {
  58
  59 TEST(ExponentialMovingAverage, ThrowsWhenLagTimeIsZero)
  60 {
  61     EXPECT_THROW_GMX(ExponentialMovingAverage(0), InconsistentInputError);
  62 }
  63
  64 TEST(ExponentialMovingAverage, ThrowsWhenLagTimeIsNegative)
  65 {
  66     EXPECT_THROW_GMX(ExponentialMovingAverage(-10), InconsistentInputError);
  67 }
  68
  69 TEST(ExponentialMovingAverage, LagTimeOneYieldsInstantaneousValue)
  70 {
  71     const real               lagTime = 1;
  72     ExponentialMovingAverage exponentialMovingAverage(lagTime);
  73
  74     exponentialMovingAverage.updateWithDataPoint(10);
  75     EXPECT_REAL_EQ(10, exponentialMovingAverage.biasCorrectedAverage());
  76
  77     exponentialMovingAverage.updateWithDataPoint(-10);
  78     EXPECT_REAL_EQ(-10, exponentialMovingAverage.biasCorrectedAverage());
  79 }
  80
  81 TEST(ExponentialMovingAverage, YieldsCorrectValue)
  82 {
  83     const real               lagTime = 100;
  84     ExponentialMovingAverage exponentialMovingAverage(lagTime);
  85
  86     exponentialMovingAverage.updateWithDataPoint(10);
  87     EXPECT_REAL_EQ(10, exponentialMovingAverage.biasCorrectedAverage());
  88
  89     exponentialMovingAverage.updateWithDataPoint(-10);
  90     EXPECT_REAL_EQ(-0.050251256281406857, exponentialMovingAverage.biasCorrectedAverage());
  91
  92     exponentialMovingAverage.updateWithDataPoint(0);
  93     EXPECT_REAL_EQ(-0.03333221103666531, exponentialMovingAverage.biasCorrectedAverage());
  94 }
  95
  96 TEST(ExponentialMovingAverage, SetAverageCorrectly)
  97 {
  98     const real               lagTime = 100;
  99     ExponentialMovingAverage exponentialMovingAverage(lagTime);
 100
 101     exponentialMovingAverage.updateWithDataPoint(10);
 102     EXPECT_REAL_EQ(10, exponentialMovingAverage.biasCorrectedAverage());
 103
 104     ExponentialMovingAverageState thisState = exponentialMovingAverage.state();
 105
 106     ExponentialMovingAverage other(lagTime, thisState);
 107
 108     other.updateWithDataPoint(-10);
 109     EXPECT_REAL_EQ(-0.050251256281406857, other.biasCorrectedAverage());
 110
 111     other.updateWithDataPoint(0);
 112     EXPECT_REAL_EQ(-0.03333221103666531, other.biasCorrectedAverage());
 113 }
 114
 115 TEST(ExponentialMovingAverage, DeterminesCorrectlyIfIncreasing)
 116 {
 117     const real               lagTime = 100;
 118     ExponentialMovingAverage exponentialMovingAverage(lagTime);
 119
 120     exponentialMovingAverage.updateWithDataPoint(10);
 121     exponentialMovingAverage.updateWithDataPoint(10);
 122
 123     EXPECT_FALSE(exponentialMovingAverage.increasing());
 124
 125     exponentialMovingAverage.updateWithDataPoint(-10);
 126
 127     EXPECT_FALSE(exponentialMovingAverage.increasing());
 128
 129     exponentialMovingAverage.updateWithDataPoint(100);
 130     EXPECT_TRUE(exponentialMovingAverage.increasing());
 131 }
 132
 133
 134 TEST(ExponentialMovingAverage, InverseLagTimeCorrect)
 135 {
 136     const real               lagTime = 2.;
 137     ExponentialMovingAverage exponentialMovingAverage(lagTime);
 138     EXPECT_REAL_EQ(0.5, exponentialMovingAverage.inverseTimeConstant());
 139 }
 140
 141 TEST(ExponentialMovingAverage, RoundTripAsKeyValueTree)
 142 {
 143     KeyValueTreeBuilder           builder;
 144     const real                    weightedSum   = 9;
 145     const real                    weightedCount = 1;
 146     const bool                    increasing    = true;
 147     ExponentialMovingAverageState state         = { weightedSum, weightedCount, increasing };
 148     exponentialMovingAverageStateAsKeyValueTree(builder.rootObject(), state);
 149     state                     = {};
 150     KeyValueTreeObject result = builder.build();
 151     state                     = exponentialMovingAverageStateFromKeyValueTree(result);
 152     EXPECT_EQ(weightedSum, state.weightedSum_);
 153     EXPECT_EQ(weightedCount, state.weightedCount_);
 154     EXPECT_EQ(increasing, state.increasing_);
 155 }
 156
 157 } // namespace
 158
 159 } // namespace test
 160
 161 } // namespace gmx