Method testHistogramCauchyML

tests/analysis/fit/FitTest.cpp:3979–4020

}

void FitTest::testHistogramCauchyML() {
	Spreadsheet spreadsheet(QStringLiteral("test"), false);
	AsciiFilter filter;

	const QString& fileName = QFINDTESTDATA(QLatin1String("data/Cauchy.dat"));

	auto properties = filter.properties();
	properties.headerEnabled = false;
	filter.setProperties(properties);
	filter.readDataFromFile(fileName, &spreadsheet, AbstractFileFilter::ImportMode::Replace);

	QCOMPARE(spreadsheet.rowCount(), 1000);
	QCOMPARE(spreadsheet.columnCount(), 1);

	Worksheet worksheet(QStringLiteral("test"), false);
	auto* plot = new CartesianPlot(QStringLiteral("plot"));
	worksheet.addChild(plot);

	auto* hist = new Histogram(QStringLiteral("Histogram"));
	plot->addChild(hist);
	hist->setDataColumn(spreadsheet.column(0));

	// Do the fit
	plot->addHistogramFit(hist, nsl_sf_stats_cauchy_lorentz);

	auto fit = dynamic_cast<XYFitCurve*>(plot->child<XYFitCurve>(0));
	QVERIFY(fit != nullptr);

	QCOMPARE(fit->name(), i18n("Distribution Fit to '%1'", hist->name()));
	// get results
	const XYFitCurve::FitResult& fitResult = fit->fitResult();

	QCOMPARE(fitResult.available, true);
	QCOMPARE(fitResult.valid, true);

	WARN(std::setprecision(15) << fitResult.paramValues.at(0));
	QCOMPARE(fitResult.paramValues.at(0), 34973.659700564);
	WARN(std::setprecision(15) << fitResult.paramValues.at(1));
	QCOMPARE(fitResult.paramValues.at(1), 1.87876026823743);
	WARN(std::setprecision(15) << fitResult.paramValues.at(2));
	QCOMPARE(fitResult.paramValues.at(2), 5.09155507540282);
}

void FitTest::testHistogramLognormalML() {
	Spreadsheet spreadsheet(QStringLiteral("test"), false);