--- /dev/null
+/*
+ * This file is part of the GROMACS molecular simulation package.
+ *
+ * Copyright (c) 2015,2016,2017,2018,2019,2020, 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
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+
+/*! \internal \file
+ *
+ * \brief
+ * Declares the CorrelationTensor class for correlation tensor statistics.
+ *
+ * \author Viveca Lindahl
+ * \author Berk Hess <hess@kth.se>
+ * \ingroup module_awh
+ */
+
+#ifndef GMX_AWH_CORRELATIONTENSOR_H
+#define GMX_AWH_CORRELATIONTENSOR_H
+
+#include <cstddef>
+
+#include <vector>
+
+#include "gromacs/utility/arrayref.h"
+#include "gromacs/utility/basedefinitions.h"
+#include "gromacs/utility/gmxassert.h"
+
+namespace gmx
+{
+
+struct CorrelationBlockDataHistory;
+
+/*! \internal \brief Correlation block averaging weight-only data.
+ */
+class CorrelationBlockData
+{
+public:
+ /*! \internal \brief Correlation block averaging data.
+ */
+ struct CoordData
+ {
+ /*! \brief Constructor.
+ */
+ CoordData() : blockSumWeightX(0), sumOverBlocksBlockWeightBlockWeightX(0) {}
+
+ double blockSumWeightX; /**< Weighted sum of x for current block. */
+ double sumOverBlocksBlockWeightBlockWeightX; /**< Sum over all blocks in the simulation of block weight times sum_wx. */
+ };
+
+ /*! \brief Constructor.
+ *
+ * \param[in] numDim The dimensionality.
+ * \param[in] blockLengthInit The initial block length.
+ */
+ CorrelationBlockData(int numDim, double blockLengthInit) :
+ blockSumWeight_(0),
+ blockSumSquareWeight_(0),
+ sumOverBlocksSquareBlockWeight_(0),
+ sumOverBlocksBlockSquareWeight_(0),
+ blockLength_(blockLengthInit),
+ previousBlockIndex_(-1),
+ coordData_(numDim),
+ correlationIntegral_(numDim * (numDim + 1) / 2)
+ {
+ }
+
+ /*! \brief Restore the state from history.
+ *
+ * \param[in] blockHistory The block data history containing the weight sums.
+ * \param[in] coordData The coordinate data.
+ * \param[in] correlationIntegral The correlation integral for all tensor elements.
+ */
+ void restoreFromHistory(const CorrelationBlockDataHistory& blockHistory,
+ const std::vector<CoordData>& coordData,
+ const std::vector<double>& correlationIntegral);
+
+ /*! \brief Adds a weighted data vector to one point in the correlation grid.
+ *
+ * \param[in] weight The weight of the data.
+ * \param[in] data One data point for each grid dimension.
+ */
+ void addData(double weight, gmx::ArrayRef<const double> data)
+ {
+ GMX_ASSERT(data.size() == coordData_.size(),
+ "Size of data should match the size of coordData");
+
+ blockSumWeight_ += weight;
+ blockSumSquareWeight_ += weight * weight;
+
+ for (size_t d = 0; d < coordData_.size(); d++)
+ {
+ coordData_[d].blockSumWeightX += weight * data[d];
+ }
+ }
+
+ /*! \brief Adds a filled data block to correlation time integral.
+ */
+ void addBlockToCorrelationIntegral();
+
+ /*! \brief Returns the sum weights for current block. */
+ double blockSumWeight() const { return blockSumWeight_; }
+
+ /*! \brief Returns the sum weights^2 for current block. */
+ double blockSumSquareWeight() const { return blockSumSquareWeight_; }
+
+ /*! \brief Returns the sum over blocks of block weight^2. */
+ double sumOverBlocksSquareBlockWeight() const { return sumOverBlocksSquareBlockWeight_; }
+
+ /*! \brief Returns the sum over blocks of weight^2. */
+ double sumOverBlocksBlockSquareWeight() const { return sumOverBlocksBlockSquareWeight_; }
+
+ /*! \brief Returns the length of each block used for block averaging. */
+ double blockLength() const { return blockLength_; }
+
+ /*! \brief Double the length of each block used for block averaging. */
+ void doubleBlockLength() { blockLength_ *= 2; }
+
+ /*! \brief Return the last block index data was added to (needed only for block length in terms of time). */
+ int previousBlockIndex() const { return previousBlockIndex_; }
+
+ /*! \brief Set the last block index data was added to.
+ *
+ * \param[in] blockIndex The block index.
+ */
+ void setPreviousBlockIndex(int blockIndex) { previousBlockIndex_ = blockIndex; }
+
+ /*! \brief Return sums for each coordinate dimension. */
+ const std::vector<CoordData>& coordData() const { return coordData_; }
+
+ /*! \brief Return the correlation integral tensor. */
+ const std::vector<double>& correlationIntegral() const { return correlationIntegral_; }
+
+private:
+ /* Weight sum data, indentical for all dimensions */
+ double blockSumWeight_; /**< Sum weights for current block. */
+ double blockSumSquareWeight_; /**< Sum weights^2 for current block. */
+ double sumOverBlocksSquareBlockWeight_; /**< Sum over all blocks in the simulation of block weight^2. */
+ double sumOverBlocksBlockSquareWeight_; /**< Sum over all blocks in the simulation of weight^2. */
+ double blockLength_; /**< The length of each block used for block averaging */
+ int previousBlockIndex_; /**< The last block index data was added to (needed only for block length in terms of time). */
+
+ /* Sums for each coordinate dimension. */
+ std::vector<CoordData> coordData_; /**< Array with sums for each coordinate dimension. */
+
+ /* Correlation tensor. */
+ std::vector<double> correlationIntegral_; /**< Array with the correlation elements corr(x, y) in the tensor, where x, y are vector components. */
+};
+
+/*! \internal
+ * \brief Correlation data for computing the correlation tensor of one grid point.
+ *
+ * The time integrated autocorrelation of the desired quantity is computed using
+ * block averages, which is a computationally efficient and low memory method.
+ * Most of the work here goes into computing the block averages for weights
+ * and the coordinate quantity. This is done for a number of blocks in
+ * the range of \p c_numCorrelationBlocks/2 + 1 to \p c_numCorrelationBlocks,
+ * depending on the current simulation length. As the simulation time
+ * progresses, the blocks get longer. This is implemented in an efficient
+ * way by keeping track of log2(\p c_numCorrelationBlocks) \p BlockData
+ * data blocks with block length increasing progressively by a factor of 2.
+ * Once \p c_numCorrelationBlocks are reached, all block lengths are doubled.
+ */
+class CorrelationTensor
+{
+public:
+ /*! \brief 64 blocks is a good trade-off between signal and noise */
+ static constexpr int c_numCorrelationBlocks = 64;
+
+ /*! \brief Constructor.
+ *
+ * \param[in] numDim The dimensionality.
+ * \param[in] numBlockData The number of data block data structs.
+ * \param[in] blockLengthInit The initial block length.
+ */
+ CorrelationTensor(int numDim, int numBlockData, double blockLengthInit);
+
+ /*! \brief Get a const reference to the list of block data.
+ */
+ const std::vector<CorrelationBlockData>& blockDataList() const { return blockDataList_; }
+
+ /*! \brief
+ * Get the total weight of the data in the correlation matrix.
+ *
+ * \returns the weight of the added data.
+ */
+ double getWeight() const
+ {
+ /* The last blockdata has only 1 block containing all data */
+ return blockDataList().back().blockSumWeight();
+ }
+
+ /*! \brief Restore a correlation element from history.
+ *
+ * \param[in] blockDataBuffer The linear correlation grid data history buffer.
+ * \param[in,out] bufferIndex The index in \p blockDataBuffer to start reading, is increased with the number of blocks read.
+ */
+ void restoreFromHistory(const std::vector<CorrelationBlockDataHistory>& blockDataBuffer,
+ size_t* bufferIndex);
+
+private:
+ /*! \brief Updates the block length by doubling.
+ *
+ * The length of all blocks is doubled. This is achieved by removing
+ * the shortest block, moving all other blocks and duplicating
+ * the data of longest block to a nw block of double length (but
+ * currenly only half filled with data).
+ */
+ void doubleBlockLengths();
+
+ /*! \brief Updates the block length such that data fits.
+ *
+ * \param[in] samplingLength Sampling length of all data, in time or weight.
+ */
+ void updateBlockLengths(double samplingLength);
+
+public:
+ /*! \brief Adds a weighted data vector to one point in the correlation grid.
+ *
+ * \note To avoid rounding noise, data with weight smaller than 1e-6
+ * is ignored.
+ *
+ * \param[in] weight The weight of the data.
+ * \param[in] data One data point for each grid dimension.
+ * \param[in] blockLengthInWeight If true, a block is measured in probability weight, otherwise
+ * in time. \param[in] t The simulation time.
+ */
+ void addData(double weight, gmx::ArrayRef<const double> data, bool blockLengthInWeight, double t);
+
+ /*! \brief Returns an element of the time integrated correlation tensor at a given point in the grid.
+ *
+ * The units of the integral are time*(units of data)^2. This will be friction units time/length^2
+ * if the data unit is 1/length.
+ *
+ * The correlation index lists the elements of the upper-triangular
+ * correlation matrix row-wise, so e.g. in 3D:
+ * 0 (0,0), 1 (1,0), 2 (1,1), 3 (2,0), 4 (2,1), 5 (2,2).
+ * (TODO: this should ideally not have to be known by the caller.)
+ *
+ * \param[in] tensorIndex Index in the tensor.
+ * \param[in] dtSample The sampling interval length.
+ * \returns the integral.
+ */
+ double getTimeIntegral(int tensorIndex, double dtSample) const;
+
+ /*! \brief
+ * Returns the volume element of the correlation metric.
+ *
+ * The matrix of the metric equals the time-integrated correlation matrix. The volume element of
+ * the metric therefore equals the square-root of the absolute value of its determinant
+ * according to the standard formula for a volume element in a metric space.
+ *
+ * Since the units of the metric matrix elements are time*(units of data)^2, the volume element
+ * has units of (sqrt(time)*(units of data))^(ndim of data).
+ *
+ * \param[in] dtSample The sampling interval length.
+ * \returns the volume element.
+ */
+ double getVolumeElement(double dtSample) const;
+
+private:
+ std::vector<CorrelationBlockData> blockDataList_; /**< The block data for different, consecutively doubling block lengths. */
+};
+
+} // namespace gmx
+
+#endif /* GMX_AWH_CORRELATIONTENSOR_H */
biod.pnpi.spb.ru / alexxy / gromacs.git / blobdiff