This file is indexed.

/usr/include/gromacs/analysisdata/modules/average.h is in libgromacs-dev 2016.1-2.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
/*
 * This file is part of the GROMACS molecular simulation package.
 *
 * Copyright (c) 2010,2011,2012,2013,2014,2015, 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
 * as published by the Free Software Foundation; either version 2.1
 * of the License, or (at your option) any later version.
 *
 * GROMACS is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 * Lesser General Public License for more details.
 *
 * You should have received a copy of the GNU Lesser General Public
 * License along with GROMACS; if not, see
 * http://www.gnu.org/licenses, or write to the Free Software Foundation,
 * Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA.
 *
 * If you want to redistribute modifications to GROMACS, please
 * consider that scientific software is very special. Version
 * control is crucial - bugs must be traceable. We will be happy to
 * consider code for inclusion in the official distribution, but
 * derived work must not be called official GROMACS. Details are found
 * in the README & COPYING files - if they are missing, get the
 * official version at http://www.gromacs.org.
 *
 * To help us fund GROMACS development, we humbly ask that you cite
 * the research papers on the package. Check out http://www.gromacs.org.
 */
/*! \file
 * \brief
 * Declares gmx::AnalysisDataAverageModule.
 *
 * \author Teemu Murtola <teemu.murtola@gmail.com>
 * \inpublicapi
 * \ingroup module_analysisdata
 */
#ifndef GMX_ANALYSISDATA_MODULES_AVERAGE_H
#define GMX_ANALYSISDATA_MODULES_AVERAGE_H

#include <vector>

#include "gromacs/analysisdata/abstractdata.h"
#include "gromacs/analysisdata/arraydata.h"
#include "gromacs/analysisdata/datamodule.h"
#include "gromacs/utility/classhelpers.h"

namespace gmx
{

/*! \brief
 * 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, multiple data sets, and missing data
 * points are all supported.
 * The average is always calculated over all frames and data points for a
 * column.
 *
 * 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.
 *
 * \inpublicapi
 * \ingroup module_analysisdata
 */
class AnalysisDataAverageModule : public AbstractAnalysisArrayData,
                                  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 dataStarted(AbstractAnalysisData *data);
        virtual void frameStarted(const AnalysisDataFrameHeader &header);
        virtual void pointsAdded(const AnalysisDataPointSetRef &points);
        virtual void frameFinished(const AnalysisDataFrameHeader &header);
        virtual void dataFinished();

        /*! \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;

        PrivateImplPointer<Impl> impl_;
};

//! Smart pointer to manage an AnalysisDataAverageModule object.
typedef std::shared_ptr<AnalysisDataAverageModule>
    AnalysisDataAverageModulePointer;

/*! \brief
 * Data module for averaging of columns for each frame.
 *
 * Output data has the same number of frames as the input data.
 * The number of columns in the output data is the same as the number of data
 * sets in the input data.
 * Each frame in the output contains the average of the column values for each
 * data set in the corresponding frame of the input data.
 *
 * Multipoint data and missing data points are both supported.  The average
 * is always calculated over all data points present in a column for a data
 * set.
 *
 * \inpublicapi
 * \ingroup module_analysisdata
 */
class AnalysisDataFrameAverageModule : public AbstractAnalysisData,
                                       public AnalysisDataModuleSerial
{
    public:
        AnalysisDataFrameAverageModule();
        virtual ~AnalysisDataFrameAverageModule();

        virtual int frameCount() const;

        virtual int flags() const;

        virtual void dataStarted(AbstractAnalysisData *data);
        virtual void frameStarted(const AnalysisDataFrameHeader &header);
        virtual void pointsAdded(const AnalysisDataPointSetRef &points);
        virtual void frameFinished(const AnalysisDataFrameHeader &header);
        virtual void dataFinished();

    private:
        virtual AnalysisDataFrameRef tryGetDataFrameInternal(int index) const;
        virtual bool requestStorageInternal(int nframes);

        class Impl;

        PrivateImplPointer<Impl> impl_;
};

//! Smart pointer to manage an AnalysisDataFrameAverageModule object.
typedef std::shared_ptr<AnalysisDataFrameAverageModule>
    AnalysisDataFrameAverageModulePointer;

} // namespace gmx

#endif