src/gromacs/analysisdata/modules/average.h

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  35 /*! \file
  36  * \brief
  37  * Declares gmx::AnalysisDataAverageModule.
  38  *
  39  * \author Teemu Murtola <teemu.murtola@gmail.com>
  40  * \inpublicapi
  41  * \ingroup module_analysisdata
  42  */
  43 #ifndef GMX_ANALYSISDATA_MODULES_AVERAGE_H
  44 #define GMX_ANALYSISDATA_MODULES_AVERAGE_H
  45
  46 #include <vector>
  47
  48 #include "gromacs/analysisdata/abstractdata.h"
  49 #include "gromacs/analysisdata/arraydata.h"
  50 #include "gromacs/analysisdata/datamodule.h"
  51 #include "gromacs/utility/classhelpers.h"
  52
  53 namespace gmx
  54 {
  55
  56 /*! \brief
  57  * Data module for independently averaging each column in input data.
  58  *
  59  * Computes the average and standard deviation independently for each column in
  60  * the input data.  Multipoint data, multiple data sets, and missing data
  61  * points are all supported.
  62  * The average is always calculated over all frames and data points for a
  63  * column.
  64  *
  65  * Output data contains a column for each data set in the input data, and a
  66  * frame for each column in the input data.  If different data sets have
  67  * different number of columns, the frame count accomodates the largest data
  68  * set.  Other columns are padded with zero values that are additionally marked
  69  * as missing.
  70  * Each value in the output data is the average of the corresponding
  71  * input column in the corresponding input data set.  The error value for each
  72  * value provides the standard deviation of the corresponding input column.
  73  * average(), standardDeviation(), and sampleCount() methods are also
  74  * provided for convenient access to these properties.
  75  *
  76  * The output data becomes available only after the input data has been
  77  * finished.
  78  *
  79  * \inpublicapi
  80  * \ingroup module_analysisdata
  81  */
  82 class AnalysisDataAverageModule : public AbstractAnalysisArrayData,
  83                                   public AnalysisDataModuleSerial
  84 {
  85     public:
  86         AnalysisDataAverageModule();
  87         ~AnalysisDataAverageModule() override;
  88
  89         using AbstractAnalysisArrayData::setXAxis;
  90         using AbstractAnalysisArrayData::setXAxisValue;
  91
  92         /*! \brief
  93          * Sets the averaging to happen over entire data sets.
  94          *
  95          * If \p bDataSets is false (the default), the module averages each
  96          * column separately.  The output will have a column for each data set,
  97          * and a row for each column.
  98          *
  99          * If \p bDataSets is true, the module averages all values within
 100          * a single data set into a single average/standard deviation.
 101          * The output will have only one column, with one row for each data
 102          * set.
 103          */
 104         void setAverageDataSets(bool bDataSets);
 105
 106         int flags() const override;
 107
 108         void dataStarted(AbstractAnalysisData *data) override;
 109         void frameStarted(const AnalysisDataFrameHeader &header) override;
 110         void pointsAdded(const AnalysisDataPointSetRef &points) override;
 111         void frameFinished(const AnalysisDataFrameHeader &header) override;
 112         void dataFinished() override;
 113
 114         /*! \brief
 115          * Convenience access to the average of a data column.
 116          *
 117          * Note that the interpretation of the parameters follows their naming:
 118          * with \c setAverageDataSets(false), \p dataSet corresponds to a
 119          * column in the output, but with \c setAverageDataSets(false) it
 120          * corresponds to an output row.  In both cases, it selects the data
 121          * set; with \c setAverageDataSets(false), \p column should always be
 122          * zero as there is only one value per data set.
 123          */
 124         real average(int dataSet, int column) const;
 125         /*! \brief
 126          * Convenience access to the standard deviation of a data column.
 127          *
 128          * See average() for the interpretation of the parameters.
 129          */
 130         real standardDeviation(int dataSet, int column) const;
 131         /*! \brief
 132          * Access the number of samples for a data column.
 133          *
 134          * See average() for the interpretation of the parameters.
 135          */
 136         int sampleCount(int dataSet, int column) const;
 137
 138     private:
 139         class Impl;
 140
 141         PrivateImplPointer<Impl> impl_;
 142 };
 143
 144 //! Smart pointer to manage an AnalysisDataAverageModule object.
 145 typedef std::shared_ptr<AnalysisDataAverageModule>
 146     AnalysisDataAverageModulePointer;
 147
 148 /*! \brief
 149  * Data module for averaging of columns for each frame.
 150  *
 151  * Output data has the same number of frames as the input data.
 152  * The number of columns in the output data is the same as the number of data
 153  * sets in the input data.
 154  * Each frame in the output contains the average of the column values for each
 155  * data set in the corresponding frame of the input data.
 156  *
 157  * Multipoint data and missing data points are both supported.  The average
 158  * is always calculated over all data points present in a column for a data
 159  * set.
 160  *
 161  * \inpublicapi
 162  * \ingroup module_analysisdata
 163  */
 164 class AnalysisDataFrameAverageModule : public AbstractAnalysisData,
 165                                        public AnalysisDataModuleSerial
 166 {
 167     public:
 168         AnalysisDataFrameAverageModule();
 169         ~AnalysisDataFrameAverageModule() override;
 170
 171         int frameCount() const override;
 172
 173         int flags() const override;
 174
 175         void dataStarted(AbstractAnalysisData *data) override;
 176         void frameStarted(const AnalysisDataFrameHeader &header) override;
 177         void pointsAdded(const AnalysisDataPointSetRef &points) override;
 178         void frameFinished(const AnalysisDataFrameHeader &header) override;
 179         void dataFinished() override;
 180
 181     private:
 182         AnalysisDataFrameRef tryGetDataFrameInternal(int index) const override;
 183         bool requestStorageInternal(int nframes) override;
 184
 185         class Impl;
 186
 187         PrivateImplPointer<Impl> impl_;
 188 };
 189
 190 //! Smart pointer to manage an AnalysisDataFrameAverageModule object.
 191 typedef std::shared_ptr<AnalysisDataFrameAverageModule>
 192     AnalysisDataFrameAverageModulePointer;
 193
 194 } // namespace gmx
 195
 196 #endif