Method lowPassButterWorth

tests/analysis/fourier/FourierTest.cpp:94–143

}

void FourierTest::lowPassButterWorth() {
	const QString filename = QStringLiteral("butterworth.csv");
	READ_DATA(filename);

	// data
	const auto xData = data.at(0);
	const auto yData = data.at(1);
	const auto filteredDataRef = data.at(2);

	// data source columns
	Column xDataColumn(QStringLiteral("x"), AbstractColumn::ColumnMode::Double);
	xDataColumn.replaceValues(0, xData);

	Column yDataColumn(QStringLiteral("y"), AbstractColumn::ColumnMode::Double);
	yDataColumn.replaceValues(0, yData);

	XYFourierFilterCurve curve(QStringLiteral("fourierFiltering"));
	curve.setXDataColumn(&xDataColumn);
	curve.setYDataColumn(&yDataColumn);

	// prepare the filtering
	auto filterData = curve.filterData();
	filterData.type = nsl_filter_type_low_pass;
	filterData.form = nsl_filter_form_butterworth;
	filterData.autoRange = true; // use complete data range
	filterData.cutoff = 100; // [Hz]
	// filterData.cutoff2; // Not relevant for lowpass filter
	filterData.order = 1;
	filterData.unit = nsl_filter_cutoff_unit_frequency;
	// filterData.unit2; // Not relevant for lowpass filter
	// filterData.xRange; // Not relevant because autoRange is true
	curve.setFilterData(filterData);

	// perform the differentiation
	curve.recalculate();
	const XYFourierFilterCurve::FilterResult& results = curve.filterResult();

	QVERIFY(results.available);
	QVERIFY(results.valid);

	// This does not work yet, because the implementation uses two side filtering,
	// considering knowing of future values (values after the current processed index)
	// Octave is using an IIR filter
	//	const auto xVec = *(curve.d_func()->xVector);
	//	const auto yVec = *(curve.d_func()->yVector);
	//	WRITE_RESULT_DATA(xData, yData, filteredDataRef, yVec);

	//	COMPARE_DOUBLE_VECTORS(xVec, xData);
	//	COMPARE_DOUBLE_VECTORS(yVec, filteredDataRef);
}

QTEST_MAIN(FourierTest)