SampleDrivers/Matrix_Compression_and_Recovery/CSR_input/01_Column_compression_and_recovery_for_Jacobian_CSR_input_return_Row_Compressed_Format.cpp

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// An example of Column compression and recovery for Jacobian
/* 
This example simulates the situation where the matrix input for BipartiteGraphPartialColoringInterface() constructor in Step 2 is in CSR format 
(in ColPack, we also call this format SSF, Sparse Solvers Format).
Step 1 in this example is used to build the sparse matrix in CSR format. In reality, the data structure in CSR format is the output of some AD tools.

How to compile this driver manually:
        Please make sure that "baseDir" point to the directory (folder) containing the input matrix file, and
                s_InputFile should point to the input file that you want to use
        To compile the code, replace the Main.cpp file in Main directory with this file
                and run "make" in ColPack installation directory. Make will generate "ColPack.exe" executable
        Run "ColPack.exe"

Note: If you got "symbol lookup error ... undefined symbol "
  Please make sure that your LD_LIBRARY_PATH contains libColPack.so

Return by recovery routine: a matrix
double*** dp3_NewValue;
//*/

#include "ColPackHeaders.h"

using namespace ColPack;
using namespace std;

#ifndef TOP_DIR
#define TOP_DIR "."
#endif

// baseDir should point to the directory (folder) containing the input file
string baseDir=TOP_DIR;

#include "extra.h" //This .h file contains functions that are used in the below examples:
                                        //ReadMM(), MatrixMultiplication...(), Times2Plus1point5(), displayMatrix() and displayCompressedRowMatrix()

int main()
{
        // s_InputFile = baseDir + <name of the input file>
        string s_InputFile; //path of the input file
        s_InputFile = baseDir;
        s_InputFile += DIR_SEPARATOR; s_InputFile += "Graphs"; s_InputFile += DIR_SEPARATOR; s_InputFile += "column-compress.mtx";

        // Step 1: Determine sparsity structure of the Jacobian.
        // This step is done by an AD tool. For the purpose of illustration here, we read the structure from a file,
        // and store the structure in a Compressed Row Format and then CSR format.
        unsigned int *** uip3_SparsityPattern = new unsigned int **;    //uip3_ means triple pointers of type unsigned int
        double*** dp3_Value = new double**;     //dp3_ means double pointers of type double. Other prefixes follow the same notation
        int rowCount, columnCount;
        ConvertMatrixMarketFormat2RowCompressedFormat(s_InputFile, uip3_SparsityPattern, dp3_Value,rowCount, columnCount);

        cout<<"just for debugging purpose, display the 2 matrices: the matrix with SparsityPattern only and the matrix with Value"<<endl;
        cout<<fixed<<showpoint<<setprecision(2); //formatting output
        cout<<"(*uip3_SparsityPattern)"<<endl;
        displayCompressedRowMatrix((*uip3_SparsityPattern),rowCount);
        cout<<"(*dp3_Value)"<<endl;
        displayCompressedRowMatrix((*dp3_Value),rowCount);
        cout<<"Finish ConvertMatrixMarketFormat2RowCompressedFormat()"<<endl;
        Pause();

        int** ip_RowIndex = new int*;
        int** ip_ColumnIndex = new int*;
        ConvertRowCompressedFormat2CSR( (*uip3_SparsityPattern) , rowCount, ip_RowIndex, ip_ColumnIndex);

        cout<<"just for debugging purpose, display the matrix in CSR format rowCount = "<<rowCount<<endl;
        cout<<"Display *ip_RowIndex"<<endl;
        displayVector(*ip_RowIndex,rowCount+1);
        cout<<"Display *ip_ColumnIndex"<<endl;
        displayVector(*ip_ColumnIndex, (*ip_RowIndex)[rowCount]);
        cout<<"Finish ConvertRowCompressedFormat2CSR()"<<endl;
        Pause();
        
        //Step 2: Obtain the seed matrix via coloring.
        double*** dp3_Seed = new double**;
        int *ip1_SeedRowCount = new int;
        int *ip1_SeedColumnCount = new int;
        int *ip1_ColorCount = new int; //The number of distinct colors used to color the graph

        //Step 2.1: Read the sparsity pattern of the given Jacobian matrix (compressed sparse rows format)
        //and create the corresponding bipartite graph
        BipartiteGraphPartialColoringInterface *g = new BipartiteGraphPartialColoringInterface(SRC_MEM_CSR, *ip_RowIndex, rowCount, columnCount, *ip_ColumnIndex);

        //Step 2.2: Do Partial-Distance-Two-Coloring the bipartite graph with the specified ordering
        g->PartialDistanceTwoColoring("SMALLEST_LAST", "COLUMN_PARTIAL_DISTANCE_TWO");

        //Step 2.3 (Option 1): From the coloring information, create and return the seed matrix
        (*dp3_Seed) = g->GetSeedMatrix(ip1_SeedRowCount, ip1_SeedColumnCount);
        /* Notes:
        Step 2.3 (Option 2): From the coloring information, you can also get the vector of colorIDs of left or right vertices  (depend on the s_ColoringVariant that you choose)
                vector<int> vi_VertexPartialColors;
                g->GetVertexPartialColors(vi_VertexPartialColors);
        */
        cout<<"Finish GenerateSeed()"<<endl;
        *ip1_ColorCount = *ip1_SeedColumnCount;

        //Display results of step 2
        printf(" dp3_Seed %d x %d \n", *ip1_SeedRowCount, *ip1_SeedColumnCount);
        displayMatrix(*dp3_Seed, *ip1_SeedRowCount, *ip1_SeedColumnCount);
        Pause();

        // Step 3: Obtain the Jacobian-seed matrix product.
        // This step will also be done by an AD tool. For the purpose of illustration here, the orginial matrix V
        // (for Values) is multiplied with the seed matrix S. The resulting matrix is stored in dp3_CompressedMatrix.
        double*** dp3_CompressedMatrix = new double**;
        cout<<"Start MatrixMultiplication()"<<endl;
        MatrixMultiplication_VxS(*uip3_SparsityPattern, *dp3_Value, rowCount, columnCount, *dp3_Seed, *ip1_ColorCount, dp3_CompressedMatrix);
        cout<<"Finish MatrixMultiplication()"<<endl;

        displayMatrix(*dp3_CompressedMatrix,rowCount,*ip1_ColorCount);
        Pause();

        //Step 4: Recover the numerical values of the original matrix from the compressed representation.
        // The new values are store in "dp3_NewValue"
        double*** dp3_NewValue = new double**;
        JacobianRecovery1D* jr1d = new JacobianRecovery1D;
        jr1d->RecoverD2Cln_RowCompressedFormat(g, *dp3_CompressedMatrix, *uip3_SparsityPattern, dp3_NewValue);
        cout<<"Finish Recover()"<<endl;

        displayCompressedRowMatrix(*dp3_NewValue,rowCount);
        Pause();

        //Check for consistency, make sure the values in the 2 matrices are the same.
        if (CompressedRowMatricesAreEqual(*dp3_Value, *dp3_NewValue, rowCount,0)) cout<< "*dp3_Value == dp3_NewValue"<<endl;
        else cout<< "*dp3_Value != dp3_NewValue"<<endl;

        Pause();

        //Deallocate memory using functions in Utilities/MatrixDeallocation.h

        free_2DMatrix(uip3_SparsityPattern, rowCount);
        uip3_SparsityPattern=NULL;

        free_2DMatrix(dp3_Value, rowCount);
        dp3_Value=NULL;

        delete dp3_Seed;
        dp3_Seed = NULL;

        delete ip1_SeedRowCount;
        ip1_SeedRowCount=NULL;

        delete ip1_SeedColumnCount;
        ip1_SeedColumnCount = NULL;

        free_2DMatrix(dp3_CompressedMatrix, rowCount);
        dp3_CompressedMatrix = NULL;

        delete ip1_ColorCount;
        ip1_ColorCount = NULL;

        delete jr1d;
        jr1d = NULL;

        delete dp3_NewValue;
        dp3_NewValue=NULL;

        delete g;
        g=NULL;
        
        delete[] (*ip_RowIndex);
        delete ip_RowIndex;
        delete[] (*ip_ColumnIndex);
        delete ip_ColumnIndex;
        
        return 0;
}