/*
* This file is part of the GROMACS molecular simulation package.
*
- * Copyright (c) 2010,2011,2012,2013, by the GROMACS development team, led by
- * David van der Spoel, Berk Hess, Erik Lindahl, and including many
- * others, as listed in the AUTHORS file in the top-level source
- * directory and at http://www.gromacs.org.
+ * Copyright (c) 2010,2011,2012,2013,2014, by the GROMACS development team, led by
+ * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
+ * and including many others, as listed in the AUTHORS file in the
+ * top-level source directory and at http://www.gromacs.org.
*
* GROMACS is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public License
#include <vector>
-#include "../abstractdata.h"
-#include "../arraydata.h"
-#include "../datamodule.h"
-#include "../../utility/common.h"
+#include "gromacs/analysisdata/abstractdata.h"
+#include "gromacs/analysisdata/arraydata.h"
+#include "gromacs/analysisdata/datamodule.h"
+#include "gromacs/utility/common.h"
namespace gmx
{
* Data module for independently averaging each column in input data.
*
* Computes the average and standard deviation independently for each column in
- * the input data. Multipoint data and missing data points are both supported.
+ * the input data. Multipoint data, multiple data sets, and missing data
+ * points are all supported.
* The average is always calculated over all frames and data points for a
* column.
- * Multiple input data sets are currently not supported.
*
- * Output data contains a frame for each column in the input data.
- * The first column of each output frame is the average of the corresponding
- * input column. The second output column is the standard deviation of the
- * corresponding input column.
- * average() and stddev() methods are also provided for convenient access to
- * these properties.
+ * Output data contains a column for each data set in the input data, and a
+ * frame for each column in the input data. If different data sets have
+ * different number of columns, the frame count accomodates the largest data
+ * set. Other columns are padded with zero values that are additionally marked
+ * as missing.
+ * Each value in the output data is the average of the corresponding
+ * input column in the corresponding input data set. The error value for each
+ * value provides the standard deviation of the corresponding input column.
+ * average(), standardDeviation(), and sampleCount() methods are also
+ * provided for convenient access to these properties.
*
* The output data becomes available only after the input data has been
* finished.
* \ingroup module_analysisdata
*/
class AnalysisDataAverageModule : public AbstractAnalysisArrayData,
- public AnalysisDataModuleInterface
+ public AnalysisDataModuleSerial
{
public:
AnalysisDataAverageModule();
virtual ~AnalysisDataAverageModule();
using AbstractAnalysisArrayData::setXAxis;
+ using AbstractAnalysisArrayData::setXAxisValue;
+
+ /*! \brief
+ * Sets the averaging to happen over entire data sets.
+ *
+ * If \p bDataSets is false (the default), the module averages each
+ * column separately. The output will have a column for each data set,
+ * and a row for each column.
+ *
+ * If \p bDataSets is true, the module averages all values within
+ * a single data set into a single average/standard deviation.
+ * The output will have only one column, with one row for each data
+ * set.
+ */
+ void setAverageDataSets(bool bDataSets);
virtual int flags() const;
virtual void frameFinished(const AnalysisDataFrameHeader &header);
virtual void dataFinished();
- //! Convenience access to the average of a data column.
- real average(int index) const;
- //! Convenience access to the standard deviation of a data column.
- real stddev(int index) const;
+ /*! \brief
+ * Convenience access to the average of a data column.
+ *
+ * Note that the interpretation of the parameters follows their naming:
+ * with \c setAverageDataSets(false), \p dataSet corresponds to a
+ * column in the output, but with \c setAverageDataSets(false) it
+ * corresponds to an output row. In both cases, it selects the data
+ * set; with \c setAverageDataSets(false), \p column should always be
+ * zero as there is only one value per data set.
+ */
+ real average(int dataSet, int column) const;
+ /*! \brief
+ * Convenience access to the standard deviation of a data column.
+ *
+ * See average() for the interpretation of the parameters.
+ */
+ real standardDeviation(int dataSet, int column) const;
+ /*! \brief
+ * Access the number of samples for a data column.
+ *
+ * See average() for the interpretation of the parameters.
+ */
+ int sampleCount(int dataSet, int column) const;
private:
class Impl;
* \ingroup module_analysisdata
*/
class AnalysisDataFrameAverageModule : public AbstractAnalysisData,
- public AnalysisDataModuleInterface
+ public AnalysisDataModuleSerial
{
public:
AnalysisDataFrameAverageModule();
virtual ~AnalysisDataFrameAverageModule();
+ virtual int frameCount() const;
+
virtual int flags() const;
virtual void dataStarted(AbstractAnalysisData *data);
biod.pnpi.spb.ru / alexxy / gromacs.git / blobdiff