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/*
File : FitTest.h
Project : LabPlot
Description : Tests for data fitting
--------------------------------------------------------------------
SPDX-FileCopyrightText: 2017 Alexander Semke <alexander.semke@web.de>
SPDX-FileCopyrightText: 2018-2025 Stefan Gerlach <stefan.gerlach@uni.kn>
SPDX-License-Identifier: GPL-2.0-or-later
*/
#ifndef FITTEST_H
#define FITTEST_H
#include <../AnalysisTest.h>
class FitTest : public AnalysisTest {
Q_OBJECT
private:
void printAndCheck(double value, double exact, double tol);
private Q_SLOTS:
void addCurve();
// linear regression (see NIST/linear data)
void testLinearNorris();
void testLinearPontius();
void testLinearNoInt1(); // using custom model
void testLinearNoInt1_2(); // using polynomial model with fixed parameter
void testLinearNoInt2(); // using custom model
void testLinearNoInt2_2(); // using polynomial model with fixed parameter
void testLinearFilip();
void testLinearWampler1();
void testLinearWampler1_custom(); // using custom model
void testLinearWampler2();
void testLinearWampler2_custom(); // using custom model
void testLinearWampler3();
void testLinearWampler3_custom(); // using custom model
void testLinearWampler4();
void testLinearWampler4_custom(); // using custom model
void testLinearWampler5();
void testLinearWampler5_custom(); // using custom model
void testLinearWP_OLS();
void testLinearR_lm2();
// non-linear regression
void testNonLinearMisra1a(); // first set of start values
void testNonLinearMisra1a_2(); // second set of start values
void testNonLinearMisra1a_3(); // third set of start values
void testNonLinearMisra1b(); // first set of start values
void testNonLinearMisra1b_2(); // second set of start values
void testNonLinearMisra1b_3(); // third set of start values
void testNonLinearMisra1c(); // first set of start values
void testNonLinearMisra1c_2(); // second set of start values
void testNonLinearMisra1c_3(); // third set of start values
void testNonLinearMisra1d(); // first set of start values
void testNonLinearMisra1d_2(); // second set of start values
void testNonLinearMisra1d_3(); // third set of start values
void testNonLinearMGH09(); // first set of start values
void testNonLinearMGH09_2(); // second set of start values
void testNonLinearMGH09_3(); // exact start values
void testNonLinearMGH10(); // first set of start values
void testNonLinearMGH10_2(); // second set of start values
void testNonLinearMGH10_3(); // third set of start values
void testNonLinearRat43(); // first set of start values
void testNonLinearRat43_2(); // second set of start values
void testNonLinearRat43_3(); // third set of start values
// more non-linear fits
void testNonLinearHahn1(); // first set of start values
void testNonLinearHahn1_2(); // second set of start values
void testNonLinearHahn1_3(); // exact start values
void testNonLinearBennett5(); // first set of start values
void testNonLinearBennett5_2(); // second set of start values
void testNonLinearBennett5_3(); // exact start values
void testNonLinearMichaelis_Menten();
// fits with weights
void testNonLinearGP_lcdemo();
void testLinearGP_PY_noerror();
void testLinearGP_PY_yerror_polynomial();
void testLinearGP_PY_yerror_custom();
void testLinearGP_PY_xyerror_polynomial();
void testLinearGP_PY_xyerror_custom();
void testLinearGP_PY_xyerror_custom_instrumental_weight();
void testLinearGP_PY_xyerror_custom_inverse_weight();
void testNonLinear_yerror_zero_bug408535();
// histogram fit
void testHistogramFit();
void testHistogramGaussianML();
void testHistogramExponentialML();
void testHistogramLaplaceML();
void testHistogramCauchyML();
void testHistogramLognormalML();
void testHistogramPoissonML();
void testHistogramBinomialML();
};
#endif
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