GIT_REPOSITORIES/LPP/Users/mperrinel/SCIQLOP-Initialisation Commit - r561:72b3a7366e6c

Shows min x-axis data in Variable widget (1)...

Alexandre Leroux -

r561:72b3a7366e6c

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r561:72b3a7366e6c

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core/include/Data/DataSeries.h +8 0

             #ifndef SCIQLOP_DATASERIES_H
             #define SCIQLOP_DATASERIES_H
             #include "CoreGlobal.h"
             #include <Common/SortUtils.h>
             #include <Data/ArrayData.h>
             #include <Data/IDataSeries.h>
             #include <QLoggingCategory>
             #include <QReadLocker>
             #include <QReadWriteLock>
             #include <memory>
             // We don't use the Qt macro since the log is used in the header file, which causes multiple log
             // definitions with inheritance. Inline method is used instead
             inline const QLoggingCategory &LOG_DataSeries()
             {
                 static const QLoggingCategory category{"DataSeries"};
                 return category;
             }
             template <int Dim>
             class DataSeries;
             namespace dataseries_detail {
             template <int Dim>
             class IteratorValue : public DataSeriesIteratorValue::Impl {
             public:
                 explicit IteratorValue(const DataSeries<Dim> &dataSeries, bool begin)
                         : m_XIt(begin ? dataSeries.xAxisData()->cbegin() : dataSeries.xAxisData()->cend()),
                           m_ValuesIt(begin ? dataSeries.valuesData()->cbegin()
                                            : dataSeries.valuesData()->cend())
                 {
                 }
                 IteratorValue(const IteratorValue &other) = default;
                 std::unique_ptr<DataSeriesIteratorValue::Impl> clone() const override
                 {
                     return std::make_unique<IteratorValue<Dim> >(*this);
                 }
                 bool equals(const DataSeriesIteratorValue::Impl &other) const override try {
                     const auto &otherImpl = dynamic_cast<const IteratorValue &>(other);
                     return std::tie(m_XIt, m_ValuesIt) == std::tie(otherImpl.m_XIt, otherImpl.m_ValuesIt);
                 }
                 catch (const std::bad_cast &) {
                     return false;
                 }
                 void next() override
                 {
                     ++m_XIt;
                     ++m_ValuesIt;
                 }
                 void prev() override
                 {
                     --m_XIt;
                     --m_ValuesIt;
                 }
                 double x() const override { return m_XIt->at(0); }
                 double value() const override { return m_ValuesIt->at(0); }
                 double value(int componentIndex) const override { return m_ValuesIt->at(componentIndex); }
             private:
                 ArrayData<1>::Iterator m_XIt;
                 typename ArrayData<Dim>::Iterator m_ValuesIt;
             };
             } // namespace dataseries_detail
             /**
              * @brief The DataSeries class is the base (abstract) implementation of IDataSeries.
              *
              * It proposes to set a dimension for the values data.
              *
              * A DataSeries is always sorted on its x-axis data.
              *
              * @tparam Dim The dimension of the values data
              *
              */
             template <int Dim>
             class SCIQLOP_CORE_EXPORT DataSeries : public IDataSeries {
             public:
                 /// @sa IDataSeries::xAxisData()
                 std::shared_ptr<ArrayData<1> > xAxisData() override { return m_XAxisData; }
                 const std::shared_ptr<ArrayData<1> > xAxisData() const { return m_XAxisData; }
                 /// @sa IDataSeries::xAxisUnit()
                 Unit xAxisUnit() const override { return m_XAxisUnit; }
                 /// @return the values dataset
                 std::shared_ptr<ArrayData<Dim> > valuesData() { return m_ValuesData; }
                 const std::shared_ptr<ArrayData<Dim> > valuesData() const { return m_ValuesData; }
                 /// @sa IDataSeries::valuesUnit()
                 Unit valuesUnit() const override { return m_ValuesUnit; }
                 SqpRange range() const override
                 {
                     if (!m_XAxisData->cdata().isEmpty()) {
                         return SqpRange{m_XAxisData->cdata().first(), m_XAxisData->cdata().last()};
                     }
                     return SqpRange{};
                 }
                 void clear()
                 {
                     m_XAxisData->clear();
                     m_ValuesData->clear();
                 }
                 /// Merges into the data series an other data series
                 /// @remarks the data series to merge with is cleared after the operation
                 void merge(IDataSeries *dataSeries) override
                 {
                     dataSeries->lockWrite();
                     lockWrite();
                     if (auto other = dynamic_cast<DataSeries<Dim> *>(dataSeries)) {
                         const auto &otherXAxisData = other->xAxisData()->cdata();
                         const auto &xAxisData = m_XAxisData->cdata();
                         // As data series are sorted, we can improve performances of merge, by call the sort
                         // method only if the two data series overlap.
                         if (!otherXAxisData.empty()) {
                             auto firstValue = otherXAxisData.front();
                             auto lastValue = otherXAxisData.back();
                             auto xAxisDataBegin = xAxisData.cbegin();
                             auto xAxisDataEnd = xAxisData.cend();
                             bool prepend;
                             bool sortNeeded;
                             if (std::lower_bound(xAxisDataBegin, xAxisDataEnd, firstValue) == xAxisDataEnd) {
                                 // Other data series if after data series
                                 prepend = false;
                                 sortNeeded = false;
                             }
                             else if (std::upper_bound(xAxisDataBegin, xAxisDataEnd, lastValue)
                                      == xAxisDataBegin) {
                                 // Other data series if before data series
                                 prepend = true;
                                 sortNeeded = false;
                             }
                             else {
                                 // The two data series overlap
                                 prepend = false;
                                 sortNeeded = true;
                             }
                             // Makes the merge
                             m_XAxisData->add(*other->xAxisData(), prepend);
                             m_ValuesData->add(*other->valuesData(), prepend);
                             if (sortNeeded) {
                                 sort();
                             }
                         }
                         // Clears the other data series
                         other->clear();
                     }
                     else {
                         qCWarning(LOG_DataSeries())
                             << QObject::tr("Detection of a type of IDataSeries we cannot merge with !");
                     }
                     unlock();
                     dataSeries->unlock();
                 }
                 // ///////// //
                 // Iterators //
                 // ///////// //
                 DataSeriesIterator cbegin() const override
                 {
                     return DataSeriesIterator{DataSeriesIteratorValue{
                         std::make_unique<dataseries_detail::IteratorValue<Dim> >(*this, true)}};
                 }
                 DataSeriesIterator cend() const override
                 {
                     return DataSeriesIterator{DataSeriesIteratorValue{
                         std::make_unique<dataseries_detail::IteratorValue<Dim> >(*this, false)}};
                 }
+                /// @sa IDataSeries::minData()
+                DataSeriesIterator minData(double minXAxisData) const override
+                {
+                    return std::lower_bound(
+                        cbegin(), cend(), minXAxisData,
+                        [](const auto &itValue, const auto &value) { return itValue.x() < value; });
+                }
                 std::pair<DataSeriesIterator, DataSeriesIterator> subData(double min, double max) const override
                 {
                     if (min > max) {
                         std::swap(min, max);
                     }
                     auto begin = cbegin();
                     auto end = cend();
                     auto lowerIt
                         = std::lower_bound(begin, end, min, [](const auto &itValue, const auto &value) {
                               return itValue.x() < value;
                           });
                     auto upperIt
                         = std::upper_bound(begin, end, max, [](const auto &value, const auto &itValue) {
                               return value < itValue.x();
                           });
                     return std::make_pair(lowerIt, upperIt);
                 }
                 // /////// //
                 // Mutexes //
                 // /////// //
                 virtual void lockRead() { m_Lock.lockForRead(); }
                 virtual void lockWrite() { m_Lock.lockForWrite(); }
                 virtual void unlock() { m_Lock.unlock(); }
             protected:
                 /// Protected ctor (DataSeries is abstract). The vectors must have the same size, otherwise a
                 /// DataSeries with no values will be created.
                 /// @remarks data series is automatically sorted on its x-axis data
                 explicit DataSeries(std::shared_ptr<ArrayData<1> > xAxisData, const Unit &xAxisUnit,
                                     std::shared_ptr<ArrayData<Dim> > valuesData, const Unit &valuesUnit)
                         : m_XAxisData{xAxisData},
                           m_XAxisUnit{xAxisUnit},
                           m_ValuesData{valuesData},
                           m_ValuesUnit{valuesUnit}
                 {
                     if (m_XAxisData->size() != m_ValuesData->size()) {
                         clear();
                     }
                     // Sorts data if it's not the case
                     const auto &xAxisCData = m_XAxisData->cdata();
                     if (!std::is_sorted(xAxisCData.cbegin(), xAxisCData.cend())) {
                         sort();
                     }
                 }
                 /// Copy ctor
                 explicit DataSeries(const DataSeries<Dim> &other)
                         : m_XAxisData{std::make_shared<ArrayData<1> >(*other.m_XAxisData)},
                           m_XAxisUnit{other.m_XAxisUnit},
                           m_ValuesData{std::make_shared<ArrayData<Dim> >(*other.m_ValuesData)},
                           m_ValuesUnit{other.m_ValuesUnit}
                 {
                     // Since a series is ordered from its construction and is always ordered, it is not
                     // necessary to call the sort method here ('other' is sorted)
                 }
                 /// Assignment operator
                 template <int D>
                 DataSeries &operator=(DataSeries<D> other)
                 {
                     std::swap(m_XAxisData, other.m_XAxisData);
                     std::swap(m_XAxisUnit, other.m_XAxisUnit);
                     std::swap(m_ValuesData, other.m_ValuesData);
                     std::swap(m_ValuesUnit, other.m_ValuesUnit);
                     return *this;
                 }
             private:
                 /**
                  * Sorts data series on its x-axis data
                  */
                 void sort() noexcept
                 {
                     auto permutation = SortUtils::sortPermutation(*m_XAxisData, std::less<double>());
                     m_XAxisData = m_XAxisData->sort(permutation);
                     m_ValuesData = m_ValuesData->sort(permutation);
                 }
                 std::shared_ptr<ArrayData<1> > m_XAxisData;
                 Unit m_XAxisUnit;
                 std::shared_ptr<ArrayData<Dim> > m_ValuesData;
                 Unit m_ValuesUnit;
                 QReadWriteLock m_Lock;
             };
             #endif // SCIQLOP_DATASERIES_H

core/include/Data/IDataSeries.h +4 0

             #ifndef SCIQLOP_IDATASERIES_H
             #define SCIQLOP_IDATASERIES_H
             #include <Common/MetaTypes.h>
             #include <Data/DataSeriesIterator.h>
             #include <Data/SqpRange.h>
             #include <memory>
             #include <QString>
             template <int Dim>
             class ArrayData;
             struct Unit {
                 explicit Unit(const QString &name = {}, bool timeUnit = false)
                         : m_Name{name}, m_TimeUnit{timeUnit}
                 {
                 }
                 inline bool operator==(const Unit &other) const
                 {
                     return std::tie(m_Name, m_TimeUnit) == std::tie(other.m_Name, other.m_TimeUnit);
                 }
                 inline bool operator!=(const Unit &other) const { return !(*this == other); }
                 QString m_Name;  ///< Unit name
                 bool m_TimeUnit; ///< The unit is a unit of time (UTC)
             };
             /**
              * @brief The IDataSeries aims to declare a data series.
              *
              * A data series is an entity that contains at least :
              * - one dataset representing the x-axis
              * - one dataset representing the values
              *
              * Each dataset is represented by an ArrayData, and is associated with a unit.
              *
              * An ArrayData can be unidimensional or two-dimensional, depending on the implementation of the
              * IDataSeries. The x-axis dataset is always unidimensional.
              *
              * @sa ArrayData
              */
             class IDataSeries {
             public:
                 virtual ~IDataSeries() noexcept = default;
                 /// Returns the x-axis dataset
                 virtual std::shared_ptr<ArrayData<1> > xAxisData() = 0;
                 /// Returns the x-axis dataset (as const)
                 virtual const std::shared_ptr<ArrayData<1> > xAxisData() const = 0;
                 virtual Unit xAxisUnit() const = 0;
                 virtual Unit valuesUnit() const = 0;
                 virtual void merge(IDataSeries *dataSeries) = 0;
                 /// @todo Review the name and signature of this method
                 virtual std::shared_ptr<IDataSeries> subDataSeries(const SqpRange &range) = 0;
                 virtual std::unique_ptr<IDataSeries> clone() const = 0;
                 virtual SqpRange range() const = 0;
                 // ///////// //
                 // Iterators //
                 // ///////// //
                 virtual DataSeriesIterator cbegin() const = 0;
                 virtual DataSeriesIterator cend() const = 0;
+                /// @return the iterator to the first entry of the data series whose x-axis data is greater than
+                /// or equal to the value passed in parameter, or the end iterator if there is no matching value
+                virtual DataSeriesIterator minData(double minXAxisData) const = 0;
                 virtual std::pair<DataSeriesIterator, DataSeriesIterator> subData(double min,
                                                                                   double max) const = 0;
                 // /////// //
                 // Mutexes //
                 // /////// //
                 virtual void lockRead() = 0;
                 virtual void lockWrite() = 0;
                 virtual void unlock() = 0;
             };
             // Required for using shared_ptr in signals/slots
             SCIQLOP_REGISTER_META_TYPE(IDATASERIES_PTR_REGISTRY, std::shared_ptr<IDataSeries>)
             #endif // SCIQLOP_IDATASERIES_H

core/tests/Data/TestDataSeries.cpp +59 0

             #include "Data/DataSeries.h"
             #include "Data/ScalarSeries.h"
             #include <QObject>
             #include <QtTest>
             Q_DECLARE_METATYPE(std::shared_ptr<ScalarSeries>)
             class TestDataSeries : public QObject {
                 Q_OBJECT
             private slots:
                 /// Input test data
                 /// @sa testCtor()
                 void testCtor_data();
                 /// Tests construction of a data series
                 void testCtor();
                 /// Input test data
                 /// @sa testMerge()
                 void testMerge_data();
                 /// Tests merge of two data series
                 void testMerge();
                 /// Input test data
+                /// @sa testMinData()
+                void testMinData_data();
+                /// Tests get min data of a data series
+                void testMinData();
                 /// @sa testSubdata()
                 void testSubdata_data();
                 /// Tests get subdata of two data series
                 void testSubdata();
             };
             void TestDataSeries::testCtor_data()
             {
                 // ////////////// //
                 // Test structure //
                 // ////////////// //
                 // x-axis data
                 QTest::addColumn<QVector<double> >("xAxisData");
                 // values data
                 QTest::addColumn<QVector<double> >("valuesData");
                 // expected x-axis data
                 QTest::addColumn<QVector<double> >("expectedXAxisData");
                 // expected values data
                 QTest::addColumn<QVector<double> >("expectedValuesData");
                 // ////////// //
                 // Test cases //
                 // ////////// //
                 QTest::newRow("invalidData (different sizes of vectors)")
                     << QVector<double>{1., 2., 3., 4., 5.} << QVector<double>{100., 200., 300.}
                     << QVector<double>{} << QVector<double>{};
                 QTest::newRow("sortedData") << QVector<double>{1., 2., 3., 4., 5.}
                                             << QVector<double>{100., 200., 300., 400., 500.}
                                             << QVector<double>{1., 2., 3., 4., 5.}
                                             << QVector<double>{100., 200., 300., 400., 500.};
                 QTest::newRow("unsortedData") << QVector<double>{5., 4., 3., 2., 1.}
                                               << QVector<double>{100., 200., 300., 400., 500.}
                                               << QVector<double>{1., 2., 3., 4., 5.}
                                               << QVector<double>{500., 400., 300., 200., 100.};
                 QTest::newRow("unsortedData2")
                     << QVector<double>{1., 4., 3., 5., 2.} << QVector<double>{100., 200., 300., 400., 500.}
                     << QVector<double>{1., 2., 3., 4., 5.} << QVector<double>{100., 500., 300., 200., 400.};
             }
             void TestDataSeries::testCtor()
             {
                 // Creates series
                 QFETCH(QVector<double>, xAxisData);
                 QFETCH(QVector<double>, valuesData);
                 auto series = std::make_shared<ScalarSeries>(std::move(xAxisData), std::move(valuesData),
                                                              Unit{}, Unit{});
                 // Validates results : we check that the data series is sorted on its x-axis data
                 QFETCH(QVector<double>, expectedXAxisData);
                 QFETCH(QVector<double>, expectedValuesData);
                 auto seriesXAxisData = series->xAxisData()->data();
                 auto seriesValuesData = series->valuesData()->data();
                 QVERIFY(
                     std::equal(expectedXAxisData.cbegin(), expectedXAxisData.cend(), seriesXAxisData.cbegin()));
                 QVERIFY(std::equal(expectedValuesData.cbegin(), expectedValuesData.cend(),
                                    seriesValuesData.cbegin()));
             }
             namespace {
             std::shared_ptr<ScalarSeries> createSeries(QVector<double> xAxisData, QVector<double> valuesData)
             {
                 return std::make_shared<ScalarSeries>(std::move(xAxisData), std::move(valuesData), Unit{},
                                                       Unit{});
             }
             } // namespace
             void TestDataSeries::testMerge_data()
             {
                 // ////////////// //
                 // Test structure //
                 // ////////////// //
                 // Data series to merge
                 QTest::addColumn<std::shared_ptr<ScalarSeries> >("dataSeries");
                 QTest::addColumn<std::shared_ptr<ScalarSeries> >("dataSeries2");
                 // Expected values in the first data series after merge
                 QTest::addColumn<QVector<double> >("expectedXAxisData");
                 QTest::addColumn<QVector<double> >("expectedValuesData");
                 // ////////// //
                 // Test cases //
                 // ////////// //
                 QTest::newRow("sortedMerge")
                     << createSeries({1., 2., 3., 4., 5.}, {100., 200., 300., 400., 500.})
                     << createSeries({6., 7., 8., 9., 10.}, {600., 700., 800., 900., 1000.})
                     << QVector<double>{1., 2., 3., 4., 5., 6., 7., 8., 9., 10.}
                     << QVector<double>{100., 200., 300., 400., 500., 600., 700., 800., 900., 1000.};
                 QTest::newRow("unsortedMerge")
                     << createSeries({6., 7., 8., 9., 10.}, {600., 700., 800., 900., 1000.})
                     << createSeries({1., 2., 3., 4., 5.}, {100., 200., 300., 400., 500.})
                     << QVector<double>{1., 2., 3., 4., 5., 6., 7., 8., 9., 10.}
                     << QVector<double>{100., 200., 300., 400., 500., 600., 700., 800., 900., 1000.};
                 QTest::newRow("unsortedMerge2")
                     << createSeries({1., 2., 8., 9., 10}, {100., 200., 300., 400., 500.})
                     << createSeries({3., 4., 5., 6., 7.}, {600., 700., 800., 900., 1000.})
                     << QVector<double>{1., 2., 3., 4., 5., 6., 7., 8., 9., 10.}
                     << QVector<double>{100., 200., 600., 700., 800., 900., 1000., 300., 400., 500.};
                 QTest::newRow("unsortedMerge3")
                     << createSeries({3., 5., 8., 7., 2}, {100., 200., 300., 400., 500.})
                     << createSeries({6., 4., 9., 10., 1.}, {600., 700., 800., 900., 1000.})
                     << QVector<double>{1., 2., 3., 4., 5., 6., 7., 8., 9., 10.}
                     << QVector<double>{1000., 500., 100., 700., 200., 600., 400., 300., 800., 900.};
             }
             void TestDataSeries::testMerge()
             {
                 // Merges series
                 QFETCH(std::shared_ptr<ScalarSeries>, dataSeries);
                 QFETCH(std::shared_ptr<ScalarSeries>, dataSeries2);
                 dataSeries->merge(dataSeries2.get());
                 // Validates results : we check that the merge is valid and the data series is sorted on its
                 // x-axis data
                 QFETCH(QVector<double>, expectedXAxisData);
                 QFETCH(QVector<double>, expectedValuesData);
                 auto seriesXAxisData = dataSeries->xAxisData()->data();
                 auto seriesValuesData = dataSeries->valuesData()->data();
                 QVERIFY(
                     std::equal(expectedXAxisData.cbegin(), expectedXAxisData.cend(), seriesXAxisData.cbegin()));
                 QVERIFY(std::equal(expectedValuesData.cbegin(), expectedValuesData.cend(),
                                    seriesValuesData.cbegin()));
             }
+            void TestDataSeries::testMinData_data()
+            {
+                // ////////////// //
+                // Test structure //
+                // ////////////// //
+                // Data series to get min data
+                QTest::addColumn<std::shared_ptr<ScalarSeries> >("dataSeries");
+                // Min data
+                QTest::addColumn<double>("min");
+                // Expected results
+                QTest::addColumn<bool>(
+                    "expectedOK"); // if true, expects to have a result (i.e. the iterator != end iterator)
+                QTest::addColumn<double>(
+                    "expectedMin"); // Expected value when method doesn't return end iterator
+                // ////////// //
+                // Test cases //
+                // ////////// //
+                QTest::newRow("minData1") << createSeries({1., 2., 3., 4., 5.}, {100., 200., 300., 400., 500.})
+                                          << 0. << true << 1.;
+                QTest::newRow("minData2") << createSeries({1., 2., 3., 4., 5.}, {100., 200., 300., 400., 500.})
+                                          << 1. << true << 1.;
+                QTest::newRow("minData3") << createSeries({1., 2., 3., 4., 5.}, {100., 200., 300., 400., 500.})
+                                          << 1.1 << true << 2.;
+                QTest::newRow("minData4") << createSeries({1., 2., 3., 4., 5.}, {100., 200., 300., 400., 500.})
+                                          << 5. << true << 5.;
+                QTest::newRow("minData5") << createSeries({1., 2., 3., 4., 5.}, {100., 200., 300., 400., 500.})
+                                          << 5.1 << false << std::numeric_limits<double>::quiet_NaN();
+                QTest::newRow("minData6") << createSeries({}, {}) << 1.1 << false
+                                          << std::numeric_limits<double>::quiet_NaN();
+            }
+            void TestDataSeries::testMinData()
+            {
+                QFETCH(std::shared_ptr<ScalarSeries>, dataSeries);
+                QFETCH(double, min);
+                QFETCH(bool, expectedOK);
+                QFETCH(double, expectedMin);
+                auto it = dataSeries->minData(min);
+                QCOMPARE(expectedOK, it != dataSeries->cend());
+                // If the method doesn't return a end iterator, checks with expected value
+                if (expectedOK) {
+                    QCOMPARE(expectedMin, it->x());
+                }
+            }
             void TestDataSeries::testSubdata_data()
             {
                 // ////////////// //
                 // Test structure //
                 // ////////////// //
                 // Data series to get subdata
                 QTest::addColumn<std::shared_ptr<ScalarSeries> >("dataSeries");
                 // Min/max values
                 QTest::addColumn<double>("min");
                 QTest::addColumn<double>("max");
                 // Expected values after subdata
                 QTest::addColumn<QVector<double> >("expectedXAxisData");
                 QTest::addColumn<QVector<double> >("expectedValuesData");
                 // ////////// //
                 // Test cases //
                 // ////////// //
                 QTest::newRow("subData1") << createSeries({1., 2., 3., 4., 5.}, {100., 200., 300., 400., 500.})
                                           << -1. << 3.2 << QVector<double>{1., 2., 3.}
                                           << QVector<double>{100., 200., 300.};
                 QTest::newRow("subData2") << createSeries({1., 2., 3., 4., 5.}, {100., 200., 300., 400., 500.})
                                           << 1. << 4. << QVector<double>{1., 2., 3., 4.}
                                           << QVector<double>{100., 200., 300., 400.};
                 QTest::newRow("subData3") << createSeries({1., 2., 3., 4., 5.}, {100., 200., 300., 400., 500.})
                                           << 1. << 3.9 << QVector<double>{1., 2., 3.}
                                           << QVector<double>{100., 200., 300.};
                 QTest::newRow("subData4") << createSeries({1., 2., 3., 4., 5.}, {100., 200., 300., 400., 500.})
                                           << 0. << 0.9 << QVector<double>{} << QVector<double>{};
                 QTest::newRow("subData5") << createSeries({1., 2., 3., 4., 5.}, {100., 200., 300., 400., 500.})
                                           << 0. << 1. << QVector<double>{1.} << QVector<double>{100.};
                 QTest::newRow("subData6") << createSeries({1., 2., 3., 4., 5.}, {100., 200., 300., 400., 500.})
                                           << 2.1 << 6. << QVector<double>{3., 4., 5.}
                                           << QVector<double>{300., 400., 500.};
                 QTest::newRow("subData7") << createSeries({1., 2., 3., 4., 5.}, {100., 200., 300., 400., 500.})
                                           << 6. << 9. << QVector<double>{} << QVector<double>{};
                 QTest::newRow("subData8") << createSeries({1., 2., 3., 4., 5.}, {100., 200., 300., 400., 500.})
                                           << 5. << 9. << QVector<double>{5.} << QVector<double>{500.};
             }
             void TestDataSeries::testSubdata()
             {
                 QFETCH(std::shared_ptr<ScalarSeries>, dataSeries);
                 QFETCH(double, min);
                 QFETCH(double, max);
                 QFETCH(QVector<double>, expectedXAxisData);
                 QFETCH(QVector<double>, expectedValuesData);
                 auto bounds = dataSeries->subData(min, max);
                 QVERIFY(std::equal(bounds.first, bounds.second, expectedXAxisData.cbegin(),
                                    expectedXAxisData.cend(),
                                    [](const auto &it, const auto &expectedX) { return it.x() == expectedX; }));
                 QVERIFY(std::equal(
                     bounds.first, bounds.second, expectedValuesData.cbegin(), expectedValuesData.cend(),
                     [](const auto &it, const auto &expectedVal) { return it.value() == expectedVal; }));
             }
             QTEST_MAIN(TestDataSeries)
             #include "TestDataSeries.moc"

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