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Viewing changes to source/TEST/LmaGaussModel_test.C

  • Committer: Package Import Robot
  • Author(s): Filippo Rusconi
  • Date: 2012-11-12 15:58:12 UTC
  • Revision ID: package-import@ubuntu.com-20121112155812-vr15wtg9b50cuesg
Tags: upstream-1.9.0
Import upstream version 1.9.0

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source/TEST/LmaGaussModel_test.C
 
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// -*- mode: C++; tab-width: 2; -*-
 
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// vi: set ts=2:
 
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//
 
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// --------------------------------------------------------------------------
 
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//                   OpenMS Mass Spectrometry Framework 
 
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// --------------------------------------------------------------------------
 
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//  Copyright (C) 2003-2011 -- Oliver Kohlbacher, Knut Reinert
 
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//
 
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//  This library is free software; you can redistribute it and/or
 
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//  modify it under the terms of the GNU Lesser General Public
 
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//  License as published by the Free Software Foundation; either
 
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//  version 2.1 of the License, or (at your option) any later version.
 
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//
 
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//  This library 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 GNU
 
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//  Lesser General Public License for more details.
 
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//
 
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//  You should have received a copy of the GNU Lesser General Public
 
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//  License along with this library; if not, write to the Free Software
 
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//  Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
 
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//
 
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// --------------------------------------------------------------------------
 
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// $Maintainer: Clemens Groepl $
 
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// $Authors: $
 
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// --------------------------------------------------------------------------
 
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#include <OpenMS/CONCEPT/ClassTest.h>
 
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///////////////////////////
 
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#include <OpenMS/TRANSFORMATIONS/FEATUREFINDER/LmaGaussModel.h>
 
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///////////////////////////
 
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START_TEST(LmaGaussModel, "$Id: LmaGaussModel_test.C 8210 2011-03-28 13:19:52Z aiche $")
 
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/////////////////////////////////////////////////////////////
 
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/////////////////////////////////////////////////////////////
 
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using namespace OpenMS;
 
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using std::stringstream;
 
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// default ctor
 
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LmaGaussModel* ptr = 0;
 
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LmaGaussModel* nullPointer = 0;
 
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START_SECTION((LmaGaussModel()))
 
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        ptr = new LmaGaussModel();
 
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  TEST_EQUAL(ptr->getName(), "LmaGaussModel")
 
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        TEST_NOT_EQUAL(ptr, nullPointer)
 
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END_SECTION
 
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// destructor
 
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START_SECTION((virtual ~LmaGaussModel()))
 
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        delete ptr;
 
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END_SECTION
 
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START_SECTION((static const String getProductName()))
 
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        TEST_EQUAL(LmaGaussModel::getProductName(),"LmaGaussModel")
 
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        TEST_EQUAL(LmaGaussModel().getName(),"LmaGaussModel")
 
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END_SECTION
 
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START_SECTION((static BaseModel<1>* create()))
 
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        BaseModel<1>* ptr = LmaGaussModel::create();
 
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        TEST_EQUAL(ptr->getName(), "LmaGaussModel")
 
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        TEST_NOT_EQUAL(ptr, nullPointer)
 
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END_SECTION
 
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// assignment operator
 
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START_SECTION((virtual LmaGaussModel& operator=(const LmaGaussModel &source)))
 
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        LmaGaussModel lm1;
 
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        lm1.setInterpolationStep(0.3);
 
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        Param tmp;
 
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        tmp.setValue("bounding_box:min", 678.9);
 
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        tmp.setValue("bounding_box:max", 789.0);
 
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        tmp.setValue("statistics:mean", 680.1 );
 
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        tmp.setValue("statistics:variance",  2.0);
 
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        tmp.setValue("lma:scale_factor", 1000000.0);
 
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        tmp.setValue("lma:standard_deviation", 2.0);
 
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        tmp.setValue("lma:expected_value", 680.0);
 
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        lm1.setParameters(tmp);
 
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        LmaGaussModel lm2;
 
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        lm2 = lm1;
 
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        LmaGaussModel lm3;
 
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        lm3.setInterpolationStep(0.3);
 
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        lm3.setParameters(tmp);
 
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        TEST_EQUAL(lm3.getParameters(), lm2.getParameters())
 
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END_SECTION
 
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// copy ctor
 
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START_SECTION((LmaGaussModel(const LmaGaussModel& source)))
 
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        LmaGaussModel lm1;
 
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        lm1.setInterpolationStep(0.3);
 
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        Param tmp;
 
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        tmp.setValue("bounding_box:min", 678.9);
 
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        tmp.setValue("bounding_box:max", 789.0);
 
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        tmp.setValue("statistics:mean", 680.1 );
 
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        tmp.setValue("statistics:variance",  2.0);
 
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        tmp.setValue("lma:scale_factor", 10.0);
 
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        tmp.setValue("lma:standard_deviation", 2.0);
 
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        tmp.setValue("lma:expected_value", 680.0);
 
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        lm1.setParameters(tmp);
 
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        LmaGaussModel lm2(lm1);
 
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        LmaGaussModel lm3;
 
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        lm3.setInterpolationStep(0.3);
 
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        lm3.setParameters(tmp);
 
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        TEST_EQUAL(lm3.getParameters(), lm2.getParameters())
 
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END_SECTION
 
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START_SECTION([EXTRA] DefaultParamHandler::setParameters(...))
 
118
        TOLERANCE_ABSOLUTE(0.001)
 
119
        LmaGaussModel lm1;
 
120
        
 
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        Param tmp;
 
122
        tmp.setValue("bounding_box:min", 678.9);
 
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        tmp.setValue("bounding_box:max", 680.9);
 
124
        tmp.setValue("statistics:mean", 679.1 );
 
125
        tmp.setValue("statistics:variance",  2.0);
 
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        tmp.setValue("lma:scale_factor", 10.0);
 
127
        tmp.setValue("lma:standard_deviation", 2.0);
 
128
        tmp.setValue("lma:expected_value", 700.0);
 
129
        lm1.setParameters(tmp);
 
130
        lm1.setOffset(680.0);
 
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132
        TEST_REAL_SIMILAR(lm1.getCenter(), 680.2)
 
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134
        LmaGaussModel lm2;
 
135
        lm2.setParameters(lm1.getParameters());
 
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137
        std::vector<Peak1D> dpa1;
 
138
        std::vector<Peak1D> dpa2;
 
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        lm1.getSamples(dpa1);
 
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        lm2.getSamples(dpa2);
 
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142
        TOLERANCE_ABSOLUTE(0.0001)
 
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        TEST_EQUAL(dpa1.size(),dpa2.size())
 
144
        ABORT_IF(dpa1.size()!=dpa2.size());
 
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        for (Size i=0; i<dpa1.size(); ++i)
 
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        {
 
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                TEST_REAL_SIMILAR(dpa1[i].getPosition()[0],dpa2[i].getPosition()[0])
 
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                TEST_REAL_SIMILAR(dpa1[i].getIntensity(),dpa2[i].getIntensity())
 
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        }
 
150
END_SECTION
 
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152
START_SECTION([EXTRA] DefaultParamHandler::setParameters(...))
 
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        LmaGaussModel lm1;
 
154
        
 
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        Param tmp;
 
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        tmp.setValue("bounding_box:min", -1.0);
 
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        tmp.setValue("bounding_box:max", 4.0);
 
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        tmp.setValue("statistics:mean", 0.0 );
 
159
        tmp.setValue("statistics:variance",  0.1);
 
160
        tmp.setValue("lma:scale_factor", 1.0);
 
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        tmp.setValue("lma:standard_deviation", 2.0);
 
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        tmp.setValue("lma:expected_value", 3.0);
 
163
        lm1.setParameters(tmp);
 
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165
        TEST_REAL_SIMILAR(lm1.getCenter(), 0.0)
 
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167
        TOLERANCE_ABSOLUTE(0.001)
 
168
        TEST_REAL_SIMILAR(lm1.getIntensity(-1.0), 0.0269955);
 
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        TEST_REAL_SIMILAR(lm1.getIntensity(0.0), 0.0647588);
 
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        TEST_REAL_SIMILAR(lm1.getIntensity(1.0), 0.120985);
 
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        TEST_REAL_SIMILAR(lm1.getIntensity(2.0), 0.176033);
 
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173
        lm1.setInterpolationStep(0.2);
 
174
        lm1.setSamples();
 
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176
        TEST_REAL_SIMILAR(lm1.getIntensity(-1.0), 0.0269955);
 
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        TEST_REAL_SIMILAR(lm1.getIntensity(0.0), 0.0647588);
 
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        TEST_REAL_SIMILAR(lm1.getIntensity(1.0), 0.120985);
 
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        TEST_REAL_SIMILAR(lm1.getIntensity(2.0), 0.176033);
 
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181
        TOLERANCE_ABSOLUTE(0.1)
 
182
        tmp.setValue("lma:scale_factor", 10.0);
 
183
        lm1.setParameters(tmp);
 
184
        lm1.setSamples();
 
185
        
 
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        TEST_REAL_SIMILAR(lm1.getIntensity(-1.0), 0.269955);
 
187
        TEST_REAL_SIMILAR(lm1.getIntensity(0.0), 0.647588);
 
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        TEST_REAL_SIMILAR(lm1.getIntensity(1.0), 1.20985);
 
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        TEST_REAL_SIMILAR(lm1.getIntensity(2.0), 1.76033);
 
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END_SECTION
 
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192
START_SECTION((void setOffset(CoordinateType offset)))
 
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194
        LmaGaussModel lm1;
 
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196
        Param tmp;
 
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        tmp.setValue("bounding_box:min", 678.9);
 
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        tmp.setValue("bounding_box:max", 789.0);
 
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        tmp.setValue("statistics:mean", 680.1 );
 
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        tmp.setValue("statistics:variance",  2.0);
 
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        tmp.setValue("lma:scale_factor", 10.0);
 
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        tmp.setValue("lma:standard_deviation", 2.0);
 
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        tmp.setValue("lma:expected_value", 700.0);
 
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        lm1.setParameters(tmp);
 
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        lm1.setOffset(680.9);
 
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207
        LmaGaussModel lm2;
 
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        lm2.setParameters(tmp);
 
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        lm2.setOffset(680.9);
 
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211
        TEST_EQUAL(lm1.getParameters(), lm2.getParameters())
 
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        TEST_REAL_SIMILAR(lm1.getCenter(), lm2.getCenter())
 
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        TEST_REAL_SIMILAR(lm1.getCenter(), 682.1)
 
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        std::vector<Peak1D> dpa1;
 
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        std::vector<Peak1D> dpa2;
 
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        lm1.getSamples(dpa1);
 
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        lm2.getSamples(dpa2);
 
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        TOLERANCE_ABSOLUTE(0.01)
 
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        TEST_EQUAL(dpa1.size(),dpa2.size())
 
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        ABORT_IF(dpa1.size()!=dpa2.size());
 
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        for (Size i=0; i<dpa1.size(); ++i)
 
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        {
 
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                TEST_REAL_SIMILAR(dpa1[i].getPosition()[0],dpa2[i].getPosition()[0])
 
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                TEST_REAL_SIMILAR(dpa1[i].getIntensity(),dpa2[i].getIntensity())
 
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        }
 
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229
END_SECTION
 
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START_SECTION((CoordinateType getCenter() const))
 
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        // already test above, but just for the sake of it
 
233
        TOLERANCE_ABSOLUTE(0.001)
 
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        LmaGaussModel lm1;
 
235
        
 
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        Param tmp;
 
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        tmp.setValue("bounding_box:min", 678.9);
 
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        tmp.setValue("bounding_box:max", 789.0);
 
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        tmp.setValue("statistics:mean", 680.1 );
 
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        tmp.setValue("statistics:variance",  2.0);
 
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        tmp.setValue("lma:scale_factor", 10.0);
 
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        tmp.setValue("lma:standard_deviation", 2.0);
 
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        tmp.setValue("lma:expected_value", 700.0);      
 
244
        lm1.setParameters(tmp);
 
245
        lm1.setOffset(680.0);
 
246
 
 
247
        TEST_REAL_SIMILAR(lm1.getCenter(), 681.2)
 
248
 
 
249
END_SECTION
 
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251
START_SECTION((void setSamples()))
 
252
{
 
253
  // dummy subtest
 
254
        TEST_EQUAL(1,1)
 
255
}
 
256
END_SECTION
 
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259
/////////////////////////////////////////////////////////////
 
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/////////////////////////////////////////////////////////////
 
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END_TEST