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Value-based spatial distribution modeling of time-varing scientific data

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Value-based Spatial Distribution

A header-only MPI-based C++ implementation of the paper "Statistical Visualization and Analysis of Large Data Using a Value-based Spatial Distribution"

Current support data type: float32

API Reference

build SGMMs

template<typename T>
Representation<T> DataModeling(std::array<int, 3> dims, int blockSize, std::string filename, Endian endian);

export data

template<typename T>
void ExportReconstructedVolume(std::string outputFilename, Representation<T>& dataBlocks, std::array<int, 3> dims, int blockSize);

template<typename T>
void SaveParameters(std::string filename, Representation<T>& data);

Binary Format of SGMM Parameters

  • blockId[0], blockId[1], blockId[2]

  • blockDims[0], blockDims[1], blockDims[2]

  • numOfBins

  • minValue

  • maxValue

  • histogram

    • binId

    • probability

    • numOfGaussians

    • GaussiansList

      • weight: std::vector<T>
      • means: std::vector<std::array<T, 3>>
      • covariance(upper triangular): std::vector<T>

Paper Reference

Wang, Ko-Chih & Lu, Kewei & Wei, Tzu-Hsuan & Shareef, Naeem & Shen, Han-Wei. (2017). Statistical visualization and analysis of large data using a value-based spatial distribution. 161-170. 10.1109/PACIFICVIS.2017.8031590.

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