Ejemplo n.º 1
0
/** load a matrix market file into a matrix */
void load_matrix_market_matrix(const std::string & filename, int offset, int D){
  MM_typecode matcode;                        
  uint i,I,J;
  double val;
  uint rows, cols;
  size_t nnz;
  FILE * f = open_file(filename.c_str() ,"r");
  int rc = mm_read_banner(f, &matcode); 
  if (rc != 0)
    logstream(LOG_FATAL)<<"Failed to load matrix market banner in file: " << filename << std::endl;

  if (mm_is_sparse(matcode)){
    int rc = mm_read_mtx_crd_size(f, &rows, &cols, &nnz);
    if (rc != 0)
      logstream(LOG_FATAL)<<"Failed to load matrix market banner in file: " << filename << std::endl;
  }
  else { //dense matrix
    rc = mm_read_mtx_array_size(f, &rows, &cols);
    if (rc != 0)
      logstream(LOG_FATAL)<<"Failed to load matrix market banner in file: " << filename << std::endl;
    nnz = rows * cols;
  }

  if (D != (int)cols)
    logstream(LOG_FATAL)<<"Wrong matrix size detected, command line argument should be --D=" << D << " instead of : " << cols << std::endl;

  for (i=0; i<nnz; i++){
    if (mm_is_sparse(matcode)){
      rc = fscanf(f, "%u %u %lg\n", &I, &J, &val);
      if (rc != 3)
        logstream(LOG_FATAL)<<"Error reading input line " << i << std::endl;
      I--; J--;
      assert(I >= 0 && I < rows);
      assert(J >= 0 && J < cols);
      //set_val(a, I, J, val);
      latent_factors_inmem[I+offset].set_val(J,val);
    }
    else {
      rc = fscanf(f, "%lg", &val);
      if (rc != 1)
        logstream(LOG_FATAL)<<"Error reading nnz " << i << std::endl;
      I = i / cols;
      J = i % cols;
      latent_factors_inmem[I+offset].set_val(J, val);
    }
  }
  logstream(LOG_INFO) << "Factors from file: loaded matrix of size " << rows << " x " << cols << " from file: " << filename << " total of " << nnz << " entries. "<< i << std::endl;
  fclose(f);
}
Ejemplo n.º 2
0
/* READ_MTX - read symmetric sparse matrix in MatrixMarket format
 */
void read_MTX_SSS(char *fname, int *n,
                  double **va, double **da, int **ja, int **ia) {
  int m, nz, ret_code, i;
  double *v_coo;
  int *i_coo, *j_coo;
  MM_typecode matcode;
  FILE *f;

  f = fopen(fname, "r");
  assert(f != NULL);
  ret_code = mm_read_banner(f, &matcode);
  assert(ret_code == 0);
  assert(mm_is_real(matcode) && mm_is_matrix(matcode) &&
         mm_is_sparse(matcode) && mm_is_symmetric(matcode));
  ret_code = mm_read_mtx_crd_size(f, &m, n, &nz);
  assert(ret_code == 0);
  assert(m == *n);
  /* read COO format */
  i_coo = (int *)malloc(nz * sizeof(int));
  j_coo = (int *)malloc(nz * sizeof(int));
  v_coo = (double *)malloc(nz * sizeof(double));
  assert(i_coo && j_coo && v_coo);
  for (i = 0; i < nz; i ++) {
    fscanf(f, "%d %d %lg\n", &i_coo[i], &j_coo[i], &v_coo[i]);
    i_coo[i]--;  /* adjust from 1-based to 0-based */
    j_coo[i]--;
  }
  fclose(f);
  /* convert to SSS format */
  convert_COO_SSS(*n, nz, i_coo, j_coo, v_coo, ia, ja, va, da);
  free(i_coo); free(j_coo); free(v_coo);
}
Ejemplo n.º 3
0
/**
  compute validation rmse
  */
void validation_rmse3(float (*prediction_func)(const vertex_data & user, const vertex_data & movie, const vertex_data & time, float rating, double & prediction)
    ,graphchi_context & gcontext,int tokens_per_row = 4) {
  int ret_code;
  MM_typecode matcode;
  FILE *f;
  size_t nz;   

  if ((f = fopen(validation.c_str(), "r")) == NULL) {
    std::cout<<std::endl;
    return; //missing validaiton data, nothing to compute
  }

  if (mm_read_banner(f, &matcode) != 0)
    logstream(LOG_FATAL) << "Could not process Matrix Market banner. File: " << validation << std::endl;

  if (mm_is_complex(matcode) || !mm_is_sparse(matcode))
    logstream(LOG_FATAL) << "Sorry, this application does not support complex values and requires a sparse matrix." << std::endl;

  /* find out size of sparse matrix .... */
  if ((ret_code = mm_read_mtx_crd_size(f, &Me, &Ne, &nz)) !=0) {
    logstream(LOG_FATAL) << "Failed reading matrix size: error=" << ret_code << std::endl;
  }
  if ((M > 0 && N > 0) && (Me != M || Ne != N))
    logstream(LOG_FATAL)<<"Input size of validation matrix must be identical to training matrix, namely " << M << "x" << N << std::endl;

  Le = nz;

  last_validation_rmse = dvalidation_rmse;
  dvalidation_rmse = 0;   
  int I, J;
  double val, time = 1.0;
 
  for (size_t i=0; i<nz; i++)
  {
   int rc;
    rc = fscanf(f, "%d %d %lg %lg\n", &I, &J, &time, &val);

    if (rc != tokens_per_row)
      logstream(LOG_FATAL)<<"Error when reading input file on line: " << i << " . should have" << tokens_per_row << std::endl;
    if (val < minval || val > maxval)
      logstream(LOG_FATAL)<<"Value is out of range: " << val << " should be: " << minval << " to " << maxval << std::endl;
    if ((uint)time > K)
      logstream(LOG_FATAL)<<"Third column value time should be smaller than " << K << " while observed " << time << " in line : " << i << std::endl;

    I--;  /* adjust from 1-based to 0-based */
    J--;
    double prediction;
    (*prediction_func)(latent_factors_inmem[I], latent_factors_inmem[J+M], latent_factors_inmem[M+N+(uint)time], val, prediction);
    dvalidation_rmse += pow(prediction - val, 2);
  }
  fclose(f);

  assert(Le > 0);
  dvalidation_rmse = sqrt(dvalidation_rmse / (double)Le);
  std::cout<<"  Validation RMSE: " << std::setw(10) << dvalidation_rmse << std::endl;
  if (halt_on_rmse_increase && dvalidation_rmse > last_validation_rmse && gcontext.iteration > 0){
       logstream(LOG_WARNING)<<"Stopping engine because of validation RMSE increase" << std::endl;
       gcontext.set_last_iteration(gcontext.iteration);
    }
}
Ejemplo n.º 4
0
void convert_2_vec(const char * filename, shotgun_data * prob )
{
    int ret_code;
    MM_typecode matcode;
    FILE *f;
    int M, N, nz;   
    int i;

    if ((f = fopen(filename, "r")) == NULL) {
           printf("Could not file vector input file : %s.\n", filename);
            exit(1);
    }

    if (mm_read_banner(f, &matcode) != 0)
    {
        printf("Could not process Matrix Market banner in input file %s.\n", filename);
        exit(1);
    }

    /*  This is how one can screen matrix types if their application */
    /*  only supports a subset of the Matrix Market data types.      */

    if (mm_is_complex(matcode) && mm_is_matrix(matcode) && 
            mm_is_sparse(matcode) )
    {
        printf("Sorry, this application does not support ");
        printf("Market Market type: [%s]\n", mm_typecode_to_str(matcode));
        exit(1);
    }

    /* find out size of sparse matrix .... */

    if ((ret_code = mm_read_mtx_crd_size(f, &M, &N, &nz)) !=0){
        printf("Could not process Matrix Market size in input file: %s.\n", filename);
        exit(1);
    }


    /* NOTE: when reading in doubles, ANSI C requires the use of the "l"  */
    /*   specifier as in "%lg", "%lf", "%le", otherwise errors will occur */
    /*  (ANSI C X3.159-1989, Sec. 4.9.6.2, p. 136 lines 13-15)            */

    prob->y.reserve(nz);
    int I,J; 
    double val;

    for (i=0; i<nz; i++)
    {
        fscanf(f, "%d %d %lg\n", &I, &J, &val);
        I--;  /* adjust from 1-based to 0-based */
        J--;
        assert(J==0);
        prob->y.push_back(val);
    }

    if (f !=stdin) fclose(f);

}
Ejemplo n.º 5
0
int mm_read_mtx_crd(char *fname, int *M, int *N, int *nz, int **I, int **J,
        double **val, MM_typecode *matcode)
{
    int ret_code;
    FILE *f;

    if (strcmp(fname, "stdin") == 0) f=stdin;
    else
    if ((f = fopen(fname, "r")) == NULL)
        return MM_COULD_NOT_READ_FILE;


    if ((ret_code = mm_read_banner(f, matcode)) != 0)
        return ret_code;

    if (!(mm_is_valid(*matcode) && mm_is_sparse(*matcode) &&
            mm_is_matrix(*matcode)))
        return MM_UNSUPPORTED_TYPE;

    if ((ret_code = mm_read_mtx_crd_size(f, M, N, nz)) != 0)
        return ret_code;


    //*I = (int *)  malloc(*nz * sizeof(int));
    //*J = (int *)  malloc(*nz * sizeof(int));
    //*val = NULL;

    *I = new int[*nz];
    *J = new int[*nz];
    *val = 0;

    if (mm_is_complex(*matcode))
    {
        //*val = (double *) malloc(*nz * 2 * sizeof(double));
        *val = new double[2*(*nz)];
        ret_code = mm_read_mtx_crd_data(f, *M, *N, *nz, *I, *J, *val,
                *matcode);
        if (ret_code != 0) return ret_code;
    }
    else if (mm_is_real(*matcode))
    {
        //*val = (double *) malloc(*nz * sizeof(double));
        *val = new double[*nz];
        ret_code = mm_read_mtx_crd_data(f, *M, *N, *nz, *I, *J, *val,
                *matcode);
        if (ret_code != 0) return ret_code;
    }

    else if (mm_is_pattern(*matcode))
    {
        ret_code = mm_read_mtx_crd_data(f, *M, *N, *nz, *I, *J, *val,
                *matcode);
        if (ret_code != 0) return ret_code;
    }

    if (f != stdin) fclose(f);
    return 0;
}
Ejemplo n.º 6
0
char  *mm_typecode_to_str(MM_typecode matcode)
{
    char buffer[MM_MAX_LINE_LENGTH];
    char *types[4];
	char *mm_strdup(const char *);
    int error =0;

    /* check for MTX type */
    if (mm_is_matrix(matcode)) 
        types[0] = MM_MTX_STR;
    else
        error=1;

    /* check for CRD or ARR matrix */
    if (mm_is_sparse(matcode))
        types[1] = MM_SPARSE_STR;
    else
    if (mm_is_dense(matcode))
        types[1] = MM_DENSE_STR;
    else
        return NULL;

    /* check for element data type */
    if (mm_is_real(matcode))
        types[2] = MM_REAL_STR;
    else
    if (mm_is_complex(matcode))
        types[2] = MM_COMPLEX_STR;
    else
    if (mm_is_pattern(matcode))
        types[2] = MM_PATTERN_STR;
    else
    if (mm_is_integer(matcode))
        types[2] = MM_INT_STR;
    else
        return NULL;


    /* check for symmetry type */
    if (mm_is_general(matcode))
        types[3] = MM_GENERAL_STR;
    else
    if (mm_is_symmetric(matcode))
        types[3] = MM_SYMM_STR;
    else 
    if (mm_is_hermitian(matcode))
        types[3] = MM_HERM_STR;
    else 
    if (mm_is_skew(matcode))
        types[3] = MM_SKEW_STR;
    else
        return NULL;

    sprintf(buffer,"%s %s %s %s", types[0], types[1], types[2], types[3]);
    return mm_strdup(buffer);

}
Ejemplo n.º 7
0
 void mm_typecode_to_str(MM_typecode matcode, char * buffer)
{
    char type0[20];
    char type1[20];
    char type2[20];
    char type3[20];
    int error =0;

    /* check for MTX type */
    if (mm_is_matrix(matcode))
        strcpy(type0, MM_MTX_STR);
    else
        error=1;

    /* check for CRD or ARR matrix */
    if (mm_is_sparse(matcode))
        strcpy(type1, MM_SPARSE_STR);
    else
    if (mm_is_dense(matcode))
        strcpy(type1, MM_DENSE_STR);
    else
        return;

    /* check for element data type */
    if (mm_is_real(matcode))
        strcpy(type2, MM_REAL_STR);
    else
    if (mm_is_complex(matcode))
        strcpy(type2, MM_COMPLEX_STR);
    else
    if (mm_is_pattern(matcode))
        strcpy(type2, MM_PATTERN_STR);
    else
    if (mm_is_integer(matcode))
        strcpy(type2, MM_INT_STR);
    else
        return;

    /* check for symmetry type */
    if (mm_is_general(matcode))
        strcpy(type3, MM_GENERAL_STR);
    else
    if (mm_is_symmetric(matcode))
        strcpy(type3, MM_SYMM_STR);
    else
    if (mm_is_hermitian(matcode))
        strcpy(type3, MM_HERM_STR);
    else
    if (mm_is_skew(matcode))
        strcpy(type3, MM_SKEW_STR);
    else
        return;

    sprintf(buffer,"%s %s %s %s", type0, type1, type2, type3);
    return;
}
Ejemplo n.º 8
0
/** Reads a matrix market file for a symmetric real valued sparse
    matrix and returns the matrix in 1-indexed CSR form. */
void read_mm_sym_matrix(FILE* f, MM_typecode mcode,
                        int n, int nnzs,
                        double *values, int* col_ind, int *row_ptr
                        ) {

  if (!(mm_is_real(mcode) && mm_is_matrix(mcode) &&
        mm_is_sparse(mcode) && mm_is_symmetric(mcode)) ) {
    printf("First argument must be a symmetric, real-valued, sparse matrix\n");
    printf("Market Market type: [%s]\n", mm_typecode_to_str(mcode));
    exit(1);
  }

  // read Matrix Market matrix in COO format
  int* I = (int *) malloc(nnzs * sizeof(int));
  int *J = (int *) malloc(nnzs * sizeof(int));
  double *val = (double *) malloc(nnzs * sizeof(double));

  int i;
  for (i=0; i<nnzs; i++) {
    fscanf(f, "%d %d %lg\n", &I[i], &J[i], &val[i]);
    I[i]--;
    J[i]--;
  }

  MKL_INT job[] = {
    1, // convert COO to CSR
    1, // use 1 based indexing for CSR matrix (required by mkl_dcsrsymv)
    0,
    0, // Is this used?
    nnzs,
    0
  };

  MKL_INT info;

  // convert COO matrix to CSR
  mkl_dcsrcoo(job,
              &n,
              values,
              col_ind,
              row_ptr,
              &nnzs,
              val,
              I,
              J,
              &info);

  if (info != 0) {
    printf("CSR to COO conversion failed: not enough memory!\n");
    exit(1);
  }
}
Ejemplo n.º 9
0
void test_predictions3(float (*prediction_func)(const vertex_data & user, const vertex_data & movie, const vertex_data & time, float rating, double & prediction)) {
  int ret_code;
  MM_typecode matcode;
  FILE *f;
  uint Me, Ne;
  size_t nz;   

  if ((f = fopen(test.c_str(), "r")) == NULL) {
    return; //missing validaiton data, nothing to compute
  }
  FILE * fout = fopen((test + ".predict").c_str(),"w");
  if (fout == NULL)
    logstream(LOG_FATAL)<<"Failed to open test prediction file for writing"<<std::endl;

  if (mm_read_banner(f, &matcode) != 0)
    logstream(LOG_FATAL) << "Could not process Matrix Market banner. File: " << test << std::endl;

  /*  This is how one can screen matrix types if their application */
  /*  only supports a subset of the Matrix Market data types.      */
  if (mm_is_complex(matcode) || !mm_is_sparse(matcode))
    logstream(LOG_FATAL) << "Sorry, this application does not support complex values and requires a sparse matrix." << std::endl;

  /* find out size of sparse matrix .... */
  if ((ret_code = mm_read_mtx_crd_size(f, &Me, &Ne, &nz)) !=0) {
    logstream(LOG_FATAL) << "Failed reading matrix size: error=" << ret_code << std::endl;
  }

  if ((M > 0 && N > 0 ) && (Me != M || Ne != N))
    logstream(LOG_FATAL)<<"Input size of test matrix must be identical to training matrix, namely " << M << "x" << N << std::endl;

  mm_write_banner(fout, matcode);
  mm_write_mtx_crd_size(fout ,M,N,nz); 

  for (uint i=0; i<nz; i++)
  {
    int I, J;
    double val;
    int time;
    int rc = fscanf(f, "%d %d %d %lg\n", &I, &J, &time, &val);
    if (rc != 4)
      logstream(LOG_FATAL)<<"Error when reading input file: " << i << std::endl;
    I--;  /* adjust from 1-based to 0-based */
    J--;
    double prediction;
    (*prediction_func)(latent_factors_inmem[I], latent_factors_inmem[J+M], latent_factors_inmem[time+M+N], 1, prediction);
    fprintf(fout, "%d %d %12.8lg\n", I+1, J+1, prediction);
  }
  fclose(f);
  fclose(fout);

  logstream(LOG_INFO)<<"Finished writing " << nz << " predictions to file: " << test << ".predict" << std::endl;
}
Ejemplo n.º 10
0
int mm_read_mtx_crd(char *fname, int *M, int *N, int *nz, int **I, int **J,
	double **val, MM_typecode *matcode)
{
    int ret_code;
    ZOLTAN_FILE* f;

    if ((f = ZOLTAN_FILE_open(fname, "r", STANDARD)) == NULL)
      return MM_COULD_NOT_READ_FILE;


    if ((ret_code = mm_read_banner(f, matcode)) != 0)
	return ret_code;

    if (!(mm_is_valid(*matcode) && mm_is_sparse(*matcode) &&
	    mm_is_matrix(*matcode)))
	return MM_UNSUPPORTED_TYPE;

    if ((ret_code = mm_read_mtx_crd_size(f, M, N, nz)) != 0)
	return ret_code;


    *I = (int *)  malloc(*nz * sizeof(int));
    *J = (int *)  malloc(*nz * sizeof(int));
    *val = NULL;

    if (mm_is_complex(*matcode))
    {
	*val = (double *) malloc(*nz * 2 * sizeof(double));
	ret_code = mm_read_mtx_crd_data(f, *M, *N, *nz, *I, *J, *val,
		*matcode);
	if (ret_code != 0) return ret_code;
    }
    else if (mm_is_real(*matcode))
    {
	*val = (double *) malloc(*nz * sizeof(double));
	ret_code = mm_read_mtx_crd_data(f, *M, *N, *nz, *I, *J, *val,
		*matcode);
	if (ret_code != 0) return ret_code;
    }

    else if (mm_is_pattern(*matcode))
    {
	ret_code = mm_read_mtx_crd_data(f, *M, *N, *nz, *I, *J, *val,
		*matcode);
	if (ret_code != 0) return ret_code;
    }

    ZOLTAN_FILE_close(f);
    return 0;
}
Ejemplo n.º 11
0
void read_matrix_market_banner_and_size(FILE * f, MM_typecode & matcode, uint & Me, uint & Ne, size_t & nz, const std::string & filename){

  if (mm_read_banner(f, &matcode) != 0)
    logstream(LOG_FATAL) << "Could not process Matrix Market banner. File: " << filename << std::endl;

  /*  This is how one can screen matrix types if their application */
  /*  only supports a subset of the Matrix Market data types.      */
  if (mm_is_complex(matcode) || !mm_is_sparse(matcode))
    logstream(LOG_FATAL) << "Sorry, this application does not support complex values and requires a sparse matrix." << std::endl;

  /* find out size of sparse matrix .... */
  if (mm_read_mtx_crd_size(f, &Me, &Ne, &nz) != 0) {
    logstream(LOG_FATAL) << "Failed reading matrix size: error" << std::endl;
  }
}
Ejemplo n.º 12
0
/*** fread MatrixMarket format file ***/
mm_real *
mm_real_fread (FILE *fp)
{
	MM_typecode	typecode;
	mm_real		*x;
	if (mm_read_banner (fp, &typecode) != 0) error_and_exit ("mm_real_fread", "failed to read mm_real.", __FILE__, __LINE__);
	if (!is_type_supported (typecode)) {
		char	msg[128];
		sprintf (msg, "matrix type does not supported :[%s].", mm_typecode_to_str (typecode));
		error_and_exit ("mm_real_fread", msg, __FILE__, __LINE__);
	}
	x = (mm_is_sparse (typecode)) ? mm_real_fread_sparse (fp, typecode) : mm_real_fread_dense (fp, typecode);
	if (!x) error_and_exit ("mm_real_fread", "failed to read mm_real.", __FILE__, __LINE__);
	if (mm_real_is_symmetric (x) && x->m != x->n) error_and_exit ("mm_real_fread", "symmetric matrix must be square.", __FILE__, __LINE__);
	return x;
}
Ejemplo n.º 13
0
bool loadMmProperties(int *rowsCount,
	int *columnsCount,
	int *nonZerosCount,
	bool *isStoredSparse,
	int* matrixStorage,
	int* matrixType,
	FILE *file)
{
	MM_typecode matcode;

	// supports only valid matrices
	if ((mm_read_banner(file, &matcode) != 0) 
		|| (!mm_is_matrix(matcode))
		|| (!mm_is_valid(matcode))) 
		return false;

	if ( mm_read_mtx_crd_size(file, rowsCount, columnsCount, nonZerosCount) != 0 ) 
		return false;

	// is it stored sparse?
	if (mm_is_sparse(matcode))
		*isStoredSparse = true;
	else
		*isStoredSparse = false;

	if (mm_is_integer(matcode))
		*matrixStorage = MATRIX_STORAGE_INTEGER;
	else if (mm_is_real(matcode))
		*matrixStorage = MATRIX_STORAGE_REAL;
	else if (mm_is_complex(matcode))
		*matrixStorage = MATRIX_STORAGE_COMPLEX;
	else if (mm_is_pattern(matcode))
		*matrixStorage = MATRIX_STORAGE_PATTERN;
	
	if (mm_is_general(matcode))
		*matrixType = MATRIX_TYPE_GENERAL;
	else if (mm_is_symmetric(matcode))
		*matrixType = MATRIX_TYPE_SYMMETRIC;
	else if (mm_is_skew(matcode))
		*matrixType = MATRIX_TYPE_SKEW;
	else if (mm_is_hermitian(matcode))
		*matrixType = MATRIX_TYPE_HERMITIAN;

	return true;
}
Ejemplo n.º 14
0
int DenseMatrix_mm_read_strassen(DenseMatrix *m, char *file_name, int *nr_rows, int *nr_cols) {
	int res;
	MM_typecode matcode;
	FILE *file;

	file = fopen(file_name, "r");
	CHECK_NULL_RETURN(file);

	res = mm_read_banner(file, &matcode);
	CHECK_ZERO_ERROR_RETURN(res, "Failed to read matrix code");

	CHECK_ERROR_RETURN(!mm_is_matrix(matcode), "File is not a matrix", 1);

	if (mm_is_sparse(matcode)) {
		int nr_sparse_elements;

		res = mm_read_mtx_crd_size(file, nr_rows, nr_cols, &nr_sparse_elements);
		CHECK_ZERO_ERROR_RETURN(res, "Failed to read sparse mm dimensions");

		int dim = pow2dim(*nr_rows, *nr_cols);

		// Initialzie matrix to zero to fill in with sparse elements
		res = DenseMatrix_init_zero(m, dim, dim);
		CHECK_ZERO_ERROR_RETURN(res, "Failed to allocate memory for mm matrix");

		res = DenseMatrix_parse_mm_sparse(m, file, nr_sparse_elements);
	} else if (mm_is_dense(matcode)) {
		res = mm_read_mtx_array_size(file, nr_rows, nr_cols);
		CHECK_ZERO_ERROR_RETURN(res, "Failed to read dense mm dimensions");

		int dim = pow2dim(*nr_rows, *nr_cols);

		res = DenseMatrix_init_zero(m, dim, dim);
		CHECK_ZERO_ERROR_RETURN(res, "Failed to allocate memory for mm matrix");

		res = DenseMatrix_parse_mm_dense(m, file);
	} else {
		ERROR("mm matrix code is not supported. Only supports dense and sparse matrices");
	}
	CHECK_ZERO_ERROR_RETURN(res, "Failed to parse mm file");

	return 0;
}
Ejemplo n.º 15
0
int get_mm_info(const char *file, int *m, int *n, int *nz)
{
    FILE *fp;
    MM_typecode matcode;

    if ((fp = fopen(file, "r")) == NULL)
    {
        fprintf(stderr,"ERROR: Could not open file: %s\n",file);
        exit(1);
    }
    if (mm_read_banner(fp, &matcode) != 0) 
    {
        fprintf(stderr,"ERROR: Could not process Matrix Market banner.\n");
        exit(1);
    }
    if (!(mm_is_real(matcode) || mm_is_integer(matcode))) 
    {
        fprintf(stderr,"ERROR: Market Market type: [%s] not supported\n",
                mm_typecode_to_str(matcode));
        exit(1);
    }

    if (mm_is_sparse(matcode))
    {
        if (mm_read_mtx_crd_size(fp, m, n, nz) !=0) 
        {   /* find out size of sparse matrix */
            exit(1);
        }
    }
    else
    {
        if (mm_read_mtx_array_size(fp, m, n) !=0) 
        {   /* find out size of dense matrix */
            exit(1);
        }
        *nz = -1;
    }
    fclose(fp);

    return 0;
}
Ejemplo n.º 16
0
/*---------------------------------------------*
 *             READ COO Matrix Market          *
 *---------------------------------------------*/
int read_coo_MM(coo_t *coo, options_t *opts) {
    char *matfile = opts->fmatname;
    MM_typecode matcode;
    FILE *p = fopen(matfile,"r");
    if (p == NULL) {
        printf("Unable to open file %s\n", matfile);
        exit(1);
    }
    /*----------- READ MM banner */
    if (mm_read_banner(p, &matcode) != 0) {
        printf("Could not process Matrix Market banner.\n");
        exit(1);
    }
    if (!mm_is_valid(matcode)) {
        printf("Invalid Matrix Market file.\n");
        exit(1);
    }
    if (!(mm_is_real(matcode) && mm_is_coordinate(matcode)
            && mm_is_sparse(matcode))) {
        printf("Only sparse real-valued coordinate \
    matrices are supported\n");
        exit(1);
    }
Ejemplo n.º 17
0
//------------------------------------------------------------------------
int test_mm_read(std::string filename)
{
    int ret_code;
    MM_typecode matcode;
    FILE *f;
    int M, N, nz;   
    int i, *I, *J;
    double *val;    
    int err=0; 

    if ((f = fopen(filename.c_str(), "r")) == NULL) 
        return -1;

    if (mm_read_banner(f, &matcode) != 0)
    {
        printf("Could not process Matrix Market banner.\n");
        return -2;
    }


    /*  This is how one can screen matrix types if their application */
    /*  only supports a subset of the Matrix Market data types.      */

    if (mm_is_complex(matcode) && mm_is_matrix(matcode) && 
            mm_is_sparse(matcode) )
    {
        printf("Sorry, this application does not support ");
        printf("Market Market type: [%s]\n", mm_typecode_to_str(matcode));
        return -3;
    }

    /* find out size of sparse matrix .... */

    if ((ret_code = mm_read_mtx_crd_size(f, &M, &N, &nz)) !=0)
        return -4;


    /* reseve memory for matrices */

    I = (int *) malloc(nz * sizeof(int));
    J = (int *) malloc(nz * sizeof(int));
    val = (double *) malloc(nz * sizeof(double));


    /* NOTE: when reading in doubles, ANSI C requires the use of the "l"  */
    /*   specifier as in "%lg", "%lf", "%le", otherwise errors will occur */
    /*  (ANSI C X3.159-1989, Sec. 4.9.6.2, p. 136 lines 13-15)            */

    for (i=0; i<nz; i++)
    {
        fscanf(f, "%d %d %lg\n", &I[i], &J[i], &val[i]);
        I[i]--;  /* adjust from 1-based to 0-based */
        J[i]--;
    }

    if (f !=stdin) fclose(f);

    /************************/
    /* now write out matrix */
    /************************/

    fprintf(stdout, "Read full file contents: \n================================\n"); 
    err += mm_write_banner(stdout, matcode);
    err += mm_write_mtx_crd_size(stdout, M, N, nz);
    for (i=0; i<nz; i++)
    {
        fprintf(stdout, "%d %d %lg\n", I[i]+1, J[i]+1, val[i]);
    }

    return err;
}
Ejemplo n.º 18
0
int mm_read_unsymmetric_sparse(const char *fname, int *M_, int *N_, int *nz_,
                double **val_, int **I_, int **J_)
{
    FILE *f;
    MM_typecode matcode;
    int M, N, nz;
    int i;
    double *val;
    int *I, *J;
 
    if ((f = fopen(fname, "r")) == NULL)
            return -1;
 
 
    if (mm_read_banner(f, &matcode) != 0)
    {
        printf("mm_read_unsymetric: Could not process Matrix Market banner ");
        printf(" in file [%s]\n", fname);
        return -1;
    }
 
 
 
    if ( !(mm_is_real(matcode) && mm_is_matrix(matcode) &&
            mm_is_sparse(matcode)))
    {
        fprintf(stderr, "Sorry, this application does not support ");
        fprintf(stderr, "Market Market type: [%s]\n",
                mm_typecode_to_str(matcode));
        return -1;
    }
 
    /* find out size of sparse matrix: M, N, nz .... */
 
    if (mm_read_mtx_crd_size(f, &M, &N, &nz) !=0)
    {
        fprintf(stderr, "read_unsymmetric_sparse(): could not parse matrix size.\n");
        return -1;
    }
 
    *M_ = M;
    *N_ = N;
    *nz_ = nz;
 
    /* reseve memory for matrices */
 
    I = (int *) malloc(nz * sizeof(int));
    J = (int *) malloc(nz * sizeof(int));
    val = (double *) malloc(nz * sizeof(double));
 
    *val_ = val;
    *I_ = I;
    *J_ = J;
 
    /* NOTE: when reading in doubles, ANSI C requires the use of the "l"  */
    /*   specifier as in "%lg", "%lf", "%le", otherwise errors will occur */
    /*  (ANSI C X3.159-1989, Sec. 4.9.6.2, p. 136 lines 13-15)            */
 
    for (i=0; i<nz; i++)
    {
        fscanf(f, "%d %d %lg\n", &I[i], &J[i], &val[i]);
        I[i]--;  /* adjust from 1-based to 0-based */
        J[i]--;
    }
    fclose(f);
 
    return 0;
}
Ejemplo n.º 19
0
int mm_read_mtx_crd(char *fname, int *M, int *N, int *nz, int **I, int **J, 
        double **val, MM_typecode *matcode)

/******************************************************************************/
/*
  Purpose:

    MM_READ_MTX_CRD reads the values in an MM coordinate file.

  Discussion:

    This function allocates the storage for the arrays.

  Modified:

    31 October 2008

  Parameters:

*/
/*
    mm_read_mtx_crd()  fills M, N, nz, array of values, and return
                        type code, e.g. 'MCRS'

                        if matrix is complex, values[] is of size 2*nz,
                            (nz pairs of real/imaginary values)
*/
{
    int ret_code;
    FILE *f;

    if (strcmp(fname, "stdin") == 0) f=stdin;
    else
    if ((f = fopen(fname, "r")) == NULL)
        return MM_COULD_NOT_READ_FILE;


    if ((ret_code = mm_read_banner(f, matcode)) != 0)
        return ret_code;

    if (!(mm_is_valid(*matcode) && mm_is_sparse(*matcode) && 
            mm_is_matrix(*matcode)))
        return MM_UNSUPPORTED_TYPE;

    if ((ret_code = mm_read_mtx_crd_size(f, M, N, nz)) != 0)
        return ret_code;


    *I = (int *)  malloc(*nz * sizeof(int));
    *J = (int *)  malloc(*nz * sizeof(int));
    *val = NULL;

    if (mm_is_complex(*matcode))
    {
        *val = (double *) malloc(*nz * 2 * sizeof(double));
        ret_code = mm_read_mtx_crd_data(f, *M, *N, *nz, *I, *J, *val, 
                *matcode);
        if (ret_code != 0) return ret_code;
    }
    else if (mm_is_real(*matcode))
    {
        *val = (double *) malloc(*nz * sizeof(double));
        ret_code = mm_read_mtx_crd_data(f, *M, *N, *nz, *I, *J, *val, 
                *matcode);
        if (ret_code != 0) return ret_code;
    }

    else if (mm_is_pattern(*matcode))
    {
        ret_code = mm_read_mtx_crd_data(f, *M, *N, *nz, *I, *J, *val, 
                *matcode);
        if (ret_code != 0) return ret_code;
    }

    if (f != stdin) fclose(f);
    return 0;
}
Ejemplo n.º 20
0
vec load_matrix_market_vector(const std::string & filename,  bool optional_field, bool allow_zeros)
{

  int ret_code;
  MM_typecode matcode;
  uint M, N;
  size_t i,nz;

  logstream(LOG_INFO) <<"Going to read matrix market vector from input file: " << filename << std::endl;

  FILE * f = open_file(filename.c_str(), "r", optional_field);
  //if optional file not found return
  if (f== NULL && optional_field){
    return zeros(1);
  }

  if (mm_read_banner(f, &matcode) != 0)
    logstream(LOG_FATAL) << "Could not process Matrix Market banner." << std::endl;

  /*  This is how one can screen matrix types if their application */
  /*  only supports a subset of the Matrix Market data types.      */

  if (mm_is_complex(matcode) && mm_is_matrix(matcode) &&
      mm_is_sparse(matcode) )
    logstream(LOG_FATAL) << "sorry, this application does not support " << std::endl <<
      "Market Market type: " << mm_typecode_to_str(matcode) << std::endl;

  /* find out size of sparse matrix .... */
  if (mm_is_sparse(matcode)){
    if ((ret_code = mm_read_mtx_crd_size(f, &M, &N, &nz)) !=0)
      logstream(LOG_FATAL) << "failed to read matrix market cardinality size " << std::endl;
  }
  else {
    if ((ret_code = mm_read_mtx_array_size(f, &M, &N))!= 0)
      logstream(LOG_FATAL) << "failed to read matrix market vector size " << std::endl;
    if (N > M){ //if this is a row vector, transpose
      int tmp = N;
      N = M;
      M = tmp;
    }
    nz = M*N;
  }

  vec ret = zeros(M);
  uint row,col;
  double val;

  for (i=0; i<nz; i++)
  {
    if (mm_is_sparse(matcode)){
      int rc = fscanf(f, "%u %u %lg\n", &row, &col, &val);
      if (rc != 3){
        logstream(LOG_FATAL) << "Failed reading input file: " << filename << "Problm at data row " << i << " (not including header and comment lines)" << std::endl;
      }
      row--;  /* adjust from 1-based to 0-based */
      col--;
    }
    else {
      int rc = fscanf(f, "%lg\n", &val);
      if (rc != 1){
        logstream(LOG_FATAL) << "Failed reading input file: " << filename << "Problm at data row " << i << " (not including header and comment lines)" << std::endl;
      }
      row = i;
      col = 0;
    }
    //some users have gibrish in text file - better check both I and J are >=0 as well
    assert(row >=0 && row< M);
    assert(col == 0);
    if (val == 0 && !allow_zeros)
      logstream(LOG_FATAL)<<"Zero entries are not allowed in a sparse matrix market vector. Use --zero=true to avoid this error"<<std::endl;
    //set observation value
    ret[row] = val;
  }
  fclose(f);
  logstream(LOG_INFO)<<"Succesfully read a vector of size: " << M << " [ " << nz << "]" << std::endl;
  return ret;
}
Ejemplo n.º 21
0
cs *read_matrix(const char *filename, MM_typecode &matcode)
{
    LogInfo("Reading Matrix from " << std::string(filename) << "\n");
    FILE *file = fopen(filename, "r");
    if (!file)
    {
        LogError("Error: Cannot read file " << std::string(filename) << "\n");
        return NULL;
    }

    LogInfo("Reading Matrix Market banner...");
    if (mm_read_banner(file, &matcode) != 0)
    {
        LogError("Error: Could not process Matrix Market banner\n");
        fclose(file);
        return NULL;
    }
    if (!mm_is_matrix(matcode) || !mm_is_sparse(matcode)
        || mm_is_complex(matcode))
    {
        LogError(
            "Error: Unsupported matrix format - Must be real and sparse\n");
        fclose(file);
        return NULL;
    }

    Int M, N, nz;
    if ((mm_read_mtx_crd_size(file, &M, &N, &nz)) != 0)
    {
        LogError("Error: Could not parse matrix dimension and size.\n");
        fclose(file);
        return NULL;
    }
    if (M != N)
    {
        LogError("Error: Matrix must be square.\n");
        fclose(file);
        return NULL;
    }

    LogInfo("Reading matrix data...\n");
    Int *I = (Int *)SuiteSparse_malloc(static_cast<size_t>(nz), sizeof(Int));
    Int *J = (Int *)SuiteSparse_malloc(static_cast<size_t>(nz), sizeof(Int));
    double *val
        = (double *)SuiteSparse_malloc(static_cast<size_t>(nz), sizeof(double));

    if (!I || !J || !val)
    {
        LogError("Error: Ran out of memory in Mongoose::read_matrix\n");
        SuiteSparse_free(I);
        SuiteSparse_free(J);
        SuiteSparse_free(val);
        fclose(file);
        return NULL;
    }

    mm_read_mtx_crd_data(file, M, N, nz, I, J, val, matcode);
    fclose(file); // Close the file

    for (Int k = 0; k < nz; k++)
    {
        --I[k];
        --J[k];
        if (mm_is_pattern(matcode))
            val[k] = 1;
    }

    cs *A = (cs *)SuiteSparse_malloc(1, sizeof(cs));
    if (!A)
    {
        LogError("Error: Ran out of memory in Mongoose::read_matrix\n");
        SuiteSparse_free(I);
        SuiteSparse_free(J);
        SuiteSparse_free(val);
        return NULL;
    }

    A->nzmax = nz;
    A->m     = M;
    A->n     = N;
    A->p     = J;
    A->i     = I;
    A->x     = val;
    A->nz    = nz;

    LogInfo("Compressing matrix from triplet to CSC format...\n");
    cs *compressed_A = cs_compress(A);
    cs_spfree(A);
    if (!compressed_A)
    {
        LogError("Error: Ran out of memory in Mongoose::read_matrix\n");
        return NULL;
    }

    return compressed_A;
}
Ejemplo n.º 22
0
static void read_mtx_and_return_csr(
	int argc, char **argv, int *mm, int *nn, int **ia, int **ja, double **aa)
{
	int ret_code;
    MM_typecode matcode;
    FILE *f;
    int m, n, nz;   
    int i, *I, *J;
    double *val;

	if (argc < 2)
	{
		fprintf(stderr, "Usage: %s [martix-market-filename]\n", argv[0]);
		exit(1);
	}
    else    
    {
		printf("\n===================================\n");
		printf("mtx file = %s\n", argv[1]);
		if ((f = fopen(argv[1], "r")) == NULL)
		{
			printf("Could not open %s\n", argv[1]); 
            exit(1);
		}
    }

    if (mm_read_banner(f, &matcode) != 0)
    {
        printf("Could not process Matrix Market banner.\n");
        exit(1);
    }

    /*  This is how one can screen matrix types if their application */
    /*  only supports a subset of the Matrix Market data types.      */
	if ( mm_is_pattern(matcode) 
		|| mm_is_dense(matcode)
		|| mm_is_array(matcode) )
	{
		printf("Sorry, this application does not support ");
        printf("Market Market type: [%s]\n", mm_typecode_to_str(matcode));
		exit(1);
	}
	

    if (mm_is_complex(matcode) && mm_is_matrix(matcode) && 
            mm_is_sparse(matcode) )
    {
        printf("Sorry, this application does not support ");
        printf("Market Market type: [%s]\n", mm_typecode_to_str(matcode));
        exit(1);
    }

    /* find out size of sparse matrix .... */

    if ((ret_code = mm_read_mtx_crd_size(f, &m, &n, &nz)) !=0)
        exit(1);

    /* reseve memory for matrices */

    I = (int *) malloc(nz * sizeof(int));
    J = (int *) malloc(nz * sizeof(int));
    val = (double *) malloc(nz * sizeof(double));


    /* NOTE: when reading in doubles, ANSI C requires the use of the "l"  */
    /*   specifier as in "%lg", "%lf", "%le", otherwise errors will occur */
    /*  (ANSI C X3.159-1989, Sec. 4.9.6.2, p. 136 lines 13-15)            */

    for (i=0; i<nz; i++)
    {
        fscanf(f, "%d %d %lg\n", &I[i], &J[i], &val[i]);
        I[i]--;  /* adjust from 1-based to 0-based */
        J[i]--;
    }

    if (f !=stdin) fclose(f);

	if (m != n) exit(1);
	
	*mm = m;	
	*nn = n;
	*ia = (int*) malloc (sizeof(int) * (n+1));
    *ja = (int*) malloc (sizeof(int) * nz);
    *aa = (double*) malloc (sizeof(double) * nz);
	coo2csr(n, nz, val, I, J, *aa, *ja, *ia);
	
	free (I);
	free (J);
	free (val);
}  
Ejemplo n.º 23
0
magma_int_t
magma_d_csr_mtx(
    magma_d_matrix *A,
    const char *filename,
    magma_queue_t queue )
{
    char buffer[ 1024 ];
    magma_int_t info = 0;

    int csr_compressor = 0;       // checks for zeros in original file
    
    magma_d_matrix B={Magma_CSR};

    magma_index_t *coo_col = NULL;
    magma_index_t *coo_row = NULL;
    double *coo_val = NULL;
    double *new_val = NULL;
    magma_index_t* new_row = NULL;
    magma_index_t* new_col = NULL;
    magma_int_t symmetric = 0;
    
    std::vector< std::pair< magma_index_t, double > > rowval;
    
    FILE *fid = NULL;
    MM_typecode matcode;
    fid = fopen(filename, "r");
    
    if (fid == NULL) {
        printf("%% Unable to open file %s\n", filename);
        info = MAGMA_ERR_NOT_FOUND;
        goto cleanup;
    }
    
    printf("%% Reading sparse matrix from file (%s):", filename);
    fflush(stdout);
    
    if (mm_read_banner(fid, &matcode) != 0) {
        printf("\n%% Could not process Matrix Market banner: %s.\n", matcode);
        info = MAGMA_ERR_NOT_SUPPORTED;
        goto cleanup;
    }
    
    if (!mm_is_valid(matcode)) {
        printf("\n%% Invalid Matrix Market file.\n");
        info = MAGMA_ERR_NOT_SUPPORTED;
        goto cleanup;
    }
    
    if ( ! ( ( mm_is_real(matcode)    ||
               mm_is_integer(matcode) ||
               mm_is_pattern(matcode) ||
               mm_is_real(matcode) ) &&
             mm_is_coordinate(matcode)  &&
             mm_is_sparse(matcode) ) )
    {
        mm_snprintf_typecode( buffer, sizeof(buffer), matcode );
        printf("\n%% Sorry, MAGMA-sparse does not support Market Market type: [%s]\n", buffer );
        printf("%% Only real-valued or pattern coordinate matrices are supported.\n");
        info = MAGMA_ERR_NOT_SUPPORTED;
        goto cleanup;
    }

    magma_index_t num_rows, num_cols, num_nonzeros;
    if (mm_read_mtx_crd_size(fid, &num_rows, &num_cols, &num_nonzeros) != 0) {
        info = MAGMA_ERR_UNKNOWN;
        goto cleanup;
    }
    
    A->storage_type    = Magma_CSR;
    A->memory_location = Magma_CPU;
    A->num_rows        = num_rows;
    A->num_cols        = num_cols;
    A->nnz             = num_nonzeros;
    A->fill_mode       = MagmaFull;
    
    CHECK( magma_index_malloc_cpu( &coo_col, A->nnz ) );
    CHECK( magma_index_malloc_cpu( &coo_row, A->nnz ) );
    CHECK( magma_dmalloc_cpu( &coo_val, A->nnz ) );

    if (mm_is_real(matcode) || mm_is_integer(matcode)) {
        for(magma_int_t i = 0; i < A->nnz; ++i) {
            magma_index_t ROW, COL;
            double VAL;  // always read in a double and convert later if necessary
            
            fscanf(fid, " %d %d %lf \n", &ROW, &COL, &VAL);
            if ( VAL == 0 )
                csr_compressor = 1;
            coo_row[i] = ROW - 1;
            coo_col[i] = COL - 1;
            coo_val[i] = MAGMA_D_MAKE( VAL, 0.);
        }
    } else if (mm_is_pattern(matcode) ) {
        for(magma_int_t i = 0; i < A->nnz; ++i) {
            magma_index_t ROW, COL;
            
            fscanf(fid, " %d %d \n", &ROW, &COL );
            
            coo_row[i] = ROW - 1;
            coo_col[i] = COL - 1;
            coo_val[i] = MAGMA_D_MAKE( 1.0, 0.);
        }
    } else if (mm_is_real(matcode) ){
       for(magma_int_t i = 0; i < A->nnz; ++i) {
            magma_index_t ROW, COL;
            double VAL, VALC;  // always read in a double and convert later if necessary
            
            fscanf(fid, " %d %d %lf %lf\n", &ROW, &COL, &VAL, &VALC);
            
            coo_row[i] = ROW - 1;
            coo_col[i] = COL - 1;
            coo_val[i] = MAGMA_D_MAKE( VAL, VALC);
        }
        // printf(" ...successfully read real matrix... ");
    } else {
        printf("\n%% Unrecognized data type\n");
        info = MAGMA_ERR_NOT_SUPPORTED;
        goto cleanup;
    }
    fclose(fid);
    fid = NULL;
    printf(" done. Converting to CSR:");
    fflush(stdout);
    
    A->sym = Magma_GENERAL;


    if( mm_is_symmetric(matcode) ) {
        symmetric = 1;
    }
    if ( mm_is_symmetric(matcode) || mm_is_symmetric(matcode) ) { 
                                        // duplicate off diagonal entries
        printf("\n%% Detected symmetric case.");
        A->sym = Magma_SYMMETRIC;
        magma_index_t off_diagonals = 0;
        for(magma_int_t i = 0; i < A->nnz; ++i) {
            if (coo_row[i] != coo_col[i])
                ++off_diagonals;
        }
        magma_index_t true_nonzeros = 2*off_diagonals + (A->nnz - off_diagonals);
        
        //printf("%% total number of nonzeros: %d\n%%", int(A->nnz));

        CHECK( magma_index_malloc_cpu( &new_row, true_nonzeros ));
        CHECK( magma_index_malloc_cpu( &new_col, true_nonzeros ));
        CHECK( magma_dmalloc_cpu( &new_val, true_nonzeros ));
        
        magma_index_t ptr = 0;
        for(magma_int_t i = 0; i < A->nnz; ++i) {
            if (coo_row[i] != coo_col[i]) {
                new_row[ptr] = coo_row[i];
                new_col[ptr] = coo_col[i];
                new_val[ptr] = coo_val[i];
                ptr++;
                new_col[ptr] = coo_row[i];
                new_row[ptr] = coo_col[i];
                new_val[ptr] = (symmetric == 0) ? coo_val[i] : conj(coo_val[i]);
                ptr++;
            } else {
                new_row[ptr] = coo_row[i];
                new_col[ptr] = coo_col[i];
                new_val[ptr] = coo_val[i];
                ptr++;
            }
        }
        
        magma_free_cpu(coo_row);
        magma_free_cpu(coo_col);
        magma_free_cpu(coo_val);

        coo_row = new_row;
        coo_col = new_col;
        coo_val = new_val;
        A->nnz = true_nonzeros;
        //printf("total number of nonzeros: %d\n", A->nnz);
    } // end symmetric case
    
    CHECK( magma_dmalloc_cpu( &A->val, A->nnz ));
    CHECK( magma_index_malloc_cpu( &A->col, A->nnz ));
    CHECK( magma_index_malloc_cpu( &A->row, A->num_rows+1 ));
    
    // original code from Nathan Bell and Michael Garland
    for (magma_index_t i = 0; i < num_rows; i++)
        (A->row)[i] = 0;
    
    for (magma_index_t i = 0; i < A->nnz; i++)
        (A->row)[coo_row[i]]++;
        
    // cumulative sum the nnz per row to get row[]
    magma_int_t cumsum;
    cumsum = 0;
    for(magma_int_t i = 0; i < num_rows; i++) {
        magma_index_t temp = (A->row)[i];
        (A->row)[i] = cumsum;
        cumsum += temp;
    }
    (A->row)[num_rows] = A->nnz;
    
    // write Aj,Ax into Bj,Bx
    for(magma_int_t i = 0; i < A->nnz; i++) {
        magma_index_t row_ = coo_row[i];
        magma_index_t dest = (A->row)[row_];
        (A->col)[dest] = coo_col[i];
        (A->val)[dest] = coo_val[i];
        (A->row)[row_]++;
    }    
    magma_free_cpu(coo_row);
    magma_free_cpu(coo_col);
    magma_free_cpu(coo_val);
    coo_row = NULL;
    coo_col = NULL;
    coo_val = NULL;

    int last;
    last = 0;
    for(int i = 0; i <= num_rows; i++) {
        int temp    = (A->row)[i];
        (A->row)[i] = last;
        last        = temp;
    }
    (A->row)[A->num_rows] = A->nnz;
    
    // sort column indices within each row
    // copy into vector of pairs (column index, value), sort by column index, then copy back
    for (magma_index_t k=0; k < A->num_rows; ++k) {
        int kk  = (A->row)[k];
        int len = (A->row)[k+1] - (A->row)[k];
        rowval.resize( len );
        for( int i=0; i < len; ++i ) {
            rowval[i] = std::make_pair( (A->col)[kk+i], (A->val)[kk+i] );
        }
        std::sort( rowval.begin(), rowval.end(), compare_first );
        for( int i=0; i < len; ++i ) {
            (A->col)[kk+i] = rowval[i].first;
            (A->val)[kk+i] = rowval[i].second;
        }
    }

    if ( csr_compressor > 0) { // run the CSR compressor to remove zeros
        //printf("removing zeros: ");
        CHECK( magma_dmtransfer( *A, &B, Magma_CPU, Magma_CPU, queue ));
        CHECK( magma_d_csr_compressor(
            &(A->val), &(A->row), &(A->col),
            &B.val, &B.row, &B.col, &B.num_rows, queue ));
        B.nnz = B.row[num_rows];
        //printf(" remaining nonzeros:%d ", B.nnz);
        magma_free_cpu( A->val );
        magma_free_cpu( A->row );
        magma_free_cpu( A->col );
        CHECK( magma_dmtransfer( B, A, Magma_CPU, Magma_CPU, queue ));
        //printf("done.\n");
    }
    A->true_nnz = A->nnz;
    printf(" done.\n");
cleanup:
    if ( fid != NULL ) {
        fclose( fid );
        fid = NULL;
    }
    magma_dmfree( &B, queue );
    magma_free_cpu(coo_row);
    magma_free_cpu(coo_col);
    magma_free_cpu(coo_val);
    return info;
}
Ejemplo n.º 24
0
bool LoadMatrixMarketFile(const std::string& file_path, 
                          SparseMatrix<T>& A,
                          unsigned int& height,
                          unsigned int& width,
                          unsigned int& nnz)
{
    std::ifstream infile(file_path);
    if (!infile)
        return false;

    char mm_typecode[4];

    // read the matrix market banner (header)
    if (0 != mm_read_banner(infile, mm_typecode))
        return false;

    if (!mm_is_valid(mm_typecode))
        return false;

    // this reader supports these matrix types:
    //
    //  sparse, real/integer/pattern, general/symm/skew
    //

    if (!mm_is_sparse(mm_typecode))
    {
        std::cerr << "Only sparse MatrixMarket files are supported." << std::endl;
        return false;
    }

    if (!mm_is_real(mm_typecode) && !mm_is_integer(mm_typecode) && !mm_is_pattern(mm_typecode))
    {
        std::cerr << "Only real, integer, and pattern MatrixMarket formats are supported." << std::endl;
        return false;
    }

    if (!mm_is_general(mm_typecode) && !mm_is_symmetric(mm_typecode) && !mm_is_skew(mm_typecode))
    {
        std::cerr << "Only general, symmetric, and skew-symmetric MatrixMarket formats are supported." 
                  << std::endl;
        return false;
    }

    // read the number of rows, cols, nonzeros
    if (0 != mm_read_mtx_crd_size(infile, height, width, nnz))
    {
        std::cerr << "could not read matrix coordinate information" << std::endl;
        height = width = nnz = 0;
        return false;
    }

    // read the data according to the type 

    bool is_real      = mm_is_real(mm_typecode);
    bool is_int       = mm_is_integer(mm_typecode);
    bool is_symmetric = mm_is_symmetric(mm_typecode);
    bool is_skew      = mm_is_skew(mm_typecode);

    std::string line;
    unsigned int reserve_size = nnz;
    if (is_symmetric || is_skew)
        reserve_size *= 2;

    A.Clear();
    A.Reserve(height, width, reserve_size);

    // load num random entries of A
    A.BeginLoad();
    
    unsigned int row, col, count;

    if (is_real)
    {
        double val;
        for (count=0; count != nnz; ++count)
        {
            infile >> row; assert(row >= 1);
            infile >> col; assert(col >= 1);
            infile >> val;
            
            // convert to 0-based indexing
            row -= 1;
            col -= 1;
            A.Load(row, col, val);

            if (row != col)
            {
                if (is_symmetric)
                    A.Load(col, row, val);
                else if (is_skew)
                    A.Load(col, row, -val);
            }
        }
    }
    else if (is_int)
Ejemplo n.º 25
0
Archivo: mmio.c Proyecto: blickly/ptii
csr_matrix_t *csr_mm_load(char *filename)
{
    int ret_code;
    MM_typecode matcode;
    FILE *f;

    int entry_count;
    int i, M, N, nz;
    matrix_entry_t *entries;
    matrix_entry_t *entry;

    int *row_start;
    int *col_index;
    double *val;

    csr_matrix_t *A;

    if ((f = fopen(filename, "r")) == NULL)
        exit(1);

    if (mm_read_banner(f, &matcode) != 0) {
        printf("Could not process Matrix Market banner.\n");
        exit(1);
    }

    if (!mm_is_sparse(matcode) || !mm_is_symmetric(matcode) ||
        !mm_is_real(matcode)) {

        printf("Sorry, this application does not support ");
        printf("Market Market type: [%s]\n", mm_typecode_to_str(matcode));
        exit(1);
    }

    /* find out size of sparse matrix .... */

    if ((ret_code = mm_read_mtx_crd_size(f, &M, &N, &nz)) != 0)
        exit(1);


    /* reserve memory for matrices */

    row_start = (int *) malloc((M + 1) * sizeof(int));
    col_index = (int *) malloc((2 * nz - M) * sizeof(int));
    val = (double *) malloc((2 * nz - M) * sizeof(double));

    entries =
        (matrix_entry_t *) malloc((2 * nz - M) * sizeof(matrix_entry_t));


    /* NOTE: when reading in doubles, ANSI C requires the use of the "l"  */
    /*   specifier as in "%lg", "%lf", "%le", otherwise errors will occur */
    /*  (ANSI C X3.159-1989, Sec. 4.9.6.2, p. 136 lines 13-15)            */

    entry = entries;
    entry_count = 0;

    for (i = 0; i < nz; i++) {

        int row, col;
        double val;

        fscanf(f, "%d %d %lg\n", &row, &col, &val);
        --row;                  /* adjust to 0-based */
        --col;

        assert(row >= 0 && col >= 0);
        assert(entry_count++ < 2 * nz - M);
        entry->i = row;
        entry->j = col;
        entry->val = val;
        ++entry;

        if (row != col) {       /* Fill out the other half... */
            assert(entry_count++ < 2 * nz - M);
            entry->i = col;
            entry->j = row;
            entry->val = val;
            ++entry;
        }
    }

    if (f != stdin)
        fclose(f);

    /**********************************/
    /* now make CSR version of matrix */
    /**********************************/

    nz = 2 * nz - M;
    qsort(entries, nz, sizeof(matrix_entry_t), entry_comparison);

    entry = entries;

    row_start[0] = 0;
    for (i = 0; i < nz; ++i) {
        row_start[entry->i + 1] = i + 1;
        col_index[i] = entry->j;
        val[i] = entry->val;
        ++entry;
    }

    free(entries);

    A = (csr_matrix_t *) malloc(sizeof(csr_matrix_t));
    A->m = M;
    A->n = N;
    A->nz = nz;
    A->row_start = row_start;
    A->col_idx = col_index;
    A->val = val;

    return A;
}
Ejemplo n.º 26
0
char *mm_typecode_to_str ( MM_typecode matcode )
/******************************************************************************/
/*
  Purpose:
    MM_TYPECODE_TO_STR converts the internal typecode to an MM header string.
  Modified:
    31 October 2008
*/
{
    char buffer[MM_MAX_LINE_LENGTH];
    char *types[4];
	char *mm_strdup(const char *);
	//int error =0;
/* 
  check for MTX type 
*/
    if (mm_is_matrix(matcode)) 
      types[0] = MM_MTX_STR;
    //    else
    //    error=1;
/* 
  check for CRD or ARR matrix 
*/
    if (mm_is_sparse(matcode))
        types[1] = MM_SPARSE_STR;
    else
    if (mm_is_dense(matcode))
        types[1] = MM_DENSE_STR;
    else
        return NULL;
/* 
  check for element data type 
*/
    if (mm_is_real(matcode))
        types[2] = MM_REAL_STR;
    else
    if (mm_is_complex(matcode))
        types[2] = MM_COMPLEX_STR;
    else
    if (mm_is_pattern(matcode))
        types[2] = MM_PATTERN_STR;
    else
    if (mm_is_integer(matcode))
        types[2] = MM_INT_STR;
    else
        return NULL;
/* 
  check for symmetry type 
*/
    if (mm_is_general(matcode))
        types[3] = MM_GENERAL_STR;
    else
    if (mm_is_symmetric(matcode))
        types[3] = MM_SYMM_STR;
    else 
    if (mm_is_hermitian(matcode))
        types[3] = MM_HERM_STR;
    else 
    if (mm_is_skew(matcode))
        types[3] = MM_SKEW_STR;
    else
        return NULL;
    sprintf(buffer,"%s %s %s %s", types[0], types[1], types[2], types[3]);
    return mm_strdup(buffer);
}
Ejemplo n.º 27
0
  bool MatrixMarket::read_matrix(const char *file_name) {
    int ret_code;
    MM_typecode matcode;
    FILE *f;
     int i;//, *I(NULL); //, *J;
    //    double *val;

    if ((f = fopen(file_name, "r")) == NULL)
      return false;

    if (mm_read_banner(f, &matcode) != 0)
      {
        printf("Could not process Matrix Market banner.\n");
	return false;
      }


    /*  This is how one can screen matrix types if their application */
    /*  only supports a subset of the Matrix Market data types.      */

    if (mm_is_complex(matcode) && mm_is_matrix(matcode) &&
        mm_is_sparse(matcode) )
      {
        printf("Sorry, this application does not support ");
        printf("Market Market type: [%s]\n", mm_typecode_to_str(matcode));
        return false;
      }

    /* find out size of sparse matrix .... */
    int _num_rows, _num_cols, _num_nnzs;
    if ((ret_code = mm_read_mtx_crd_size(f, &_num_rows, &_num_cols, &_num_nnzs)) !=0)
      return false;

    bool is_vector = (_num_rows == _num_nnzs) && (_num_cols == 1);
    // convert to 64 bit
    m_num_rows = _num_rows;
    m_num_cols = _num_cols;
    m_num_nnzs = _num_nnzs;
    /* reseve memory for matrices */

    //    I = (int *) malloc(nz * sizeof(int));
    //    J = (int *) malloc(nz * sizeof(int));
    //    val = (double *) malloc(nz * sizeof(double));
    m_rows.resize(m_num_nnzs);
    m_cols.resize(m_num_nnzs);
    m_coefs.resize(m_num_nnzs);


    /* NOTE: when reading in doubles, ANSI C requires the use of the "l"  */
    /*   specifier as in "%lg", "%lf", "%le", otherwise errors will occur */
    /*  (ANSI C X3.159-1989, Sec. 4.9.6.2, p. 136 lines 13-15)            */
    
    if (is_vector) {
      for (i=0; i<m_num_nnzs; i++) {
	fscanf(f, "%lg\n", &(m_coefs[i]));	
	m_rows[i] = i;
	m_cols[i] = 0;
      }
      if (f !=stdin) fclose(f);
      return true;
    } 

    std::vector<std::map<int32_t,double> > elements;
    elements.resize(m_num_rows);

    for (i=0; i<m_num_nnzs; i++)
      {
	fscanf(f, "%d %d %lg\n", &(m_rows[i]), &(m_cols[i]), &(m_coefs[i]));
	m_rows[i]--;  /* adjust from 1-based to 0-based */
	m_cols[i]--;
	  
	elements[m_rows[i]][m_cols[i]] += m_coefs[i];
      }

    // now sort by rows
    std::vector<int> m_rows2;
    std::vector<int32_t> m_cols2;
    std::vector<double> m_coefs2;

    m_rows2.resize(m_num_nnzs);
    m_cols2.resize(m_num_nnzs);
    m_coefs2.resize(m_num_nnzs);
    int index=0;
    
    for (int row=0; row<m_num_rows; row++) {
      assert((int)elements[row].size() > 0);

      // Make sure diagonal element is first
      if (elements[row].find(row) != elements[row].end()) {
        m_cols2[index]  = row;
        m_rows2[index] = row;        
        m_coefs2[index] = elements[row][row];
        assert (m_coefs2[index] != 0.0);
        index++;
      }
      else
        assert(0);

      for (auto iter = elements[row].begin(); iter != elements[row].end(); iter++) {
        int col = iter->first;
        if (col != row) {
          double C = iter->second;
          assert(col < m_num_cols);
          m_rows2[index] = row;
          m_cols2[index] = col;
          m_coefs2[index] = C;
          index++;
        }
      }

    }
    
    if (f !=stdin) fclose(f);

    m_rows.swap(m_rows2);
    m_cols.swap(m_cols2);
    m_coefs.swap(m_coefs2);    


    /* convert coo to csr row ptrs */
    coo_to_csr_rows(m_rows, m_num_rows, m_row_ptrs);

    return true;
    // /************************/
    // /* now write out matrix */
    // /************************/

    //    mm_write_banner(stdout, matcode);
    //    mm_write_mtx_crd_size(stdout, m_num_rows, m_num_cols, m_num_nnzs);
    // for (i=0; i<nz; i++)
    //   fprintf(stdout, "%d %d %20.19g\n", I[i]+1, J[i]+1, val[i]);
    //    free(I);
  }
Ejemplo n.º 28
0
int convert_matrixmarket(std::string base_filename, SharderPreprocessor<als_edge_type> * preprocessor = NULL) {
  // Note, code based on: http://math.nist.gov/MatrixMarket/mmio/c/example_read.c
  int ret_code;
  MM_typecode matcode;
  FILE *f;
  size_t nz;   

  std::string suffix = "";
  if (preprocessor != NULL) {
    suffix = preprocessor->getSuffix();
  }

  /**
   * Create sharder object
   */
  int nshards;
  if ((nshards = find_shards<als_edge_type>(base_filename+ suffix, get_option_string("nshards", "auto")))) {
    logstream(LOG_INFO) << "File " << base_filename << " was already preprocessed, won't do it again. " << std::endl;
    FILE * inf = fopen((base_filename + ".gm").c_str(), "r");
    int rc = fscanf(inf,"%d\n%d\n%ld\n%lg\n%d\n",&M, &N, &L, &globalMean, &K);
    if (rc != 5)
      logstream(LOG_FATAL)<<"Failed to read global mean from file" << base_filename+ suffix << ".gm" << std::endl;
    fclose(inf);
    logstream(LOG_INFO) << "Opened matrix size: " <<M << " x " << N << " Global mean is: " << globalMean << " time bins: " << K << " Now creating shards." << std::endl;
    return nshards;
  }   

  sharder<als_edge_type> sharderobj(base_filename + suffix);
  sharderobj.start_preprocessing();


  if ((f = fopen(base_filename.c_str(), "r")) == NULL) {
    logstream(LOG_FATAL) << "Could not open file: " << base_filename << ", error: " << strerror(errno) << std::endl;
  }


  if (mm_read_banner(f, &matcode) != 0)
    logstream(LOG_FATAL) << "Could not process Matrix Market banner. File: " << base_filename << std::endl;


  /*  This is how one can screen matrix types if their application */
  /*  only supports a subset of the Matrix Market data types.      */

  if (mm_is_complex(matcode) || !mm_is_sparse(matcode))
    logstream(LOG_FATAL) << "Sorry, this application does not support complex values and requires a sparse matrix." << std::endl;

  /* find out size of sparse matrix .... */

  if ((ret_code = mm_read_mtx_crd_size(f, &M, &N, &nz)) !=0) {
    logstream(LOG_FATAL) << "Failed reading matrix size: error=" << ret_code << std::endl;
  }

  L=nz;

  logstream(LOG_INFO) << "Starting to read matrix-market input. Matrix dimensions: " 
    << M << " x " << N << ", non-zeros: " << nz << std::endl;

  uint I, J;
  double val;
  if (!sharderobj.preprocessed_file_exists()) {
    for (size_t i=0; i<nz; i++)
    {

      int rc = fscanf(f, "%d %d %lg\n", &I, &J, &val);
      if (rc != 3)
        logstream(LOG_FATAL)<<"Error when reading input file: " << i << std::endl;
      I--;  /* adjust from 1-based to 0-based */
      J--;
      if (I >= M)
        logstream(LOG_FATAL)<<"Row index larger than the matrix row size " << I << " > " << M << " in line: " << i << std::endl;
      if (J >= N)
        logstream(LOG_FATAL)<<"Col index larger than the matrix col size " << J << " > " << N << " in line; " << i << std::endl;
      globalMean += val; 
      sharderobj.preprocessing_add_edge(I, M + J, als_edge_type((float)val));
    }
    uint toadd = 0;
    if (implicitratingtype == IMPLICIT_RATING_RANDOM)
      toadd = add_implicit_edges(implicitratingtype, sharderobj);
    globalMean += implicitratingvalue * toadd;
    L += toadd;

    sharderobj.end_preprocessing();
    globalMean /= L;
    logstream(LOG_INFO) << "Global mean is: " << globalMean << " Now creating shards." << std::endl;

    if (preprocessor != NULL) {
      preprocessor->reprocess(sharderobj.preprocessed_name(), base_filename);
    }

    FILE * outf = fopen((base_filename + ".gm").c_str(), "w");
    fprintf(outf, "%d\n%d\n%ld\n%lg\n%d\n", M, N, L, globalMean, K);
    fclose(outf);


  } else {
    logstream(LOG_INFO) << "Matrix already preprocessed, just run sharder." << std::endl;
  }
  fclose(f);


  logstream(LOG_INFO) << "Now creating shards." << std::endl;

  // Shard with a specified number of shards, or determine automatically if not defined
  nshards = sharderobj.execute_sharding(get_option_string("nshards", "auto"));
  logstream(LOG_INFO) << "Successfully finished sharding for " << base_filename + suffix << std::endl;
  logstream(LOG_INFO) << "Created " << nshards << " shards." << std::endl;

  return nshards;
}
Ejemplo n.º 29
0
void HostMatrixCOO<ValueType>::ReadFileMTX(const std::string filename) { 

  // Follow example_read.c (from Matrix Market web site)
  int ret_code;
  MM_typecode matcode;
  FILE *f;
  int M, N;
  int fnz, nnz;  // file nnz, real nnz
  bool sym = false;

  LOG_INFO("ReadFileMTX: filename="<< filename << "; reading...");

  if ((f = fopen(filename.c_str(), "r")) == NULL) {
    LOG_INFO("ReadFileMTX cannot open file " << filename);
    FATAL_ERROR(__FILE__, __LINE__);
  }

  if (mm_read_banner(f, &matcode) != 0)
    {
      LOG_INFO("ReadFileMTX could not process Matrix Market banner.");
      FATAL_ERROR(__FILE__, __LINE__);
    }


  /*  This is how one can screen matrix types if their application */
  /*  only supports a subset of the Matrix Market data types.      */

  if (mm_is_complex(matcode) && mm_is_matrix(matcode) && 
      mm_is_sparse(matcode) )
    {
      LOG_INFO("ReadFileMTX does not support Market Market type:" << mm_typecode_to_str(matcode));
      FATAL_ERROR(__FILE__, __LINE__);
    }

  /* find out size of sparse matrix .... */

  if ((ret_code = mm_read_mtx_crd_size(f, &M, &N, &fnz)) !=0) {
    LOG_INFO("ReadFileMTX matrix size error");
    FATAL_ERROR(__FILE__, __LINE__);
  }

  nnz = fnz ; 

  /* reseve memory for matrices */
  if(mm_is_symmetric(matcode)) {

    if (N != M) {
      LOG_INFO("ReadFileMTX non-squared symmetric matrices are not supported");
      LOG_INFO("What is symmetric and non-squared matrix? e-mail me");
      FATAL_ERROR(__FILE__, __LINE__);
    }

    nnz = 2*(nnz - N) + N;
    sym = true ;
  }

  this->AllocateCOO(nnz,M,N);

  int ii=0;
  int col, row;
  double val;
  int ret;
  for (int i=0; i<fnz; ++i) {
    ret = fscanf(f, "%d %d %lg\n", &row, &col, &val);
    if (!ret) FATAL_ERROR(__FILE__, __LINE__);

    row--; /* adjust from 1-based to 0-based */
    col--;

    assert (ret == 3);

    //    LOG_INFO(row << " " << col << " " << val);

    this->mat_.row[ii] = row;
    this->mat_.col[ii] = col;
    this->mat_.val[ii] = val;

    if (sym && (row!=col)) {
      ++ii;
      this->mat_.row[ii] = col;
      this->mat_.col[ii] = row;
      this->mat_.val[ii] = val;
    }
      
    ++ii;
  }

  LOG_INFO("ReadFileMTX: filename="<< filename << "; done");

  fclose(f);

}
Ejemplo n.º 30
0
int convert_matrixmarket4(std::string base_filename, bool add_time_edges = false, bool square = false) {
  // Note, code based on: http://math.nist.gov/MatrixMarket/mmio/c/example_read.c
  int ret_code;
  MM_typecode matcode;
  FILE *f;
  size_t nz;
  /**
   * Create sharder object
   */
  int nshards;
  if ((nshards = find_shards<als_edge_type>(base_filename, get_option_string("nshards", "auto")))) {
    logstream(LOG_INFO) << "File " << base_filename << " was already preprocessed, won't do it again. " << std::endl;
    FILE * inf = fopen((base_filename + ".gm").c_str(), "r");
    int rc = fscanf(inf,"%d\n%d\n%ld\n%lg\n%d\n",&M, &N, &L, &globalMean, &K);
    if (rc != 5)
      logstream(LOG_FATAL)<<"Failed to read global mean from file" << base_filename << ".gm" << std::endl;
    fclose(inf);
    if (K <= 0)
      logstream(LOG_FATAL)<<"Incorrect number of time bins K in .gm file " << base_filename << ".gm" << std::endl;

    logstream(LOG_INFO) << "Read matrix of size " << M << " x " << N << " Global mean is: " << globalMean << " time bins: " << K << " Now creating shards." << std::endl;
    return nshards;
  }   

  sharder<als_edge_type> sharderobj(base_filename);
  sharderobj.start_preprocessing();


  if ((f = fopen(base_filename.c_str(), "r")) == NULL) {
    logstream(LOG_FATAL) << "Could not open file: " << base_filename << ", error: " << strerror(errno) << std::endl;
  }


  if (mm_read_banner(f, &matcode) != 0)
    logstream(LOG_FATAL) << "Could not process Matrix Market banner. File: " << base_filename << std::endl;


  /*  This is how one can screen matrix types if their application */
  /*  only supports a subset of the Matrix Market data types.      */

  if (mm_is_complex(matcode) || !mm_is_sparse(matcode))
    logstream(LOG_FATAL) << "Sorry, this application does not support complex values and requires a sparse matrix." << std::endl;

  /* find out size of sparse matrix .... */

  if ((ret_code = mm_read_mtx_crd_size(f, &M, &N, &nz)) !=0) {
    logstream(LOG_FATAL) << "Failed reading matrix size: error=" << ret_code << std::endl;
  }

  logstream(LOG_INFO) << "Starting to read matrix-market input. Matrix dimensions: " 
    << M << " x " << N << ", non-zeros: " << nz << std::endl;

  uint I, J;
  double val, time;

  if (!sharderobj.preprocessed_file_exists()) {
    for (size_t i=0; i<nz; i++)
    {
      int rc = fscanf(f, "%d %d %lg %lg\n", &I, &J, &time, &val);
      if (rc != 4)
        logstream(LOG_FATAL)<<"Error when reading input file: " << i << std::endl;
      if (time < 0)
        logstream(LOG_FATAL)<<"Time (third columns) should be >= 0 " << std::endl;
      I--;  /* adjust from 1-based to 0-based */
      J--;
      if (I >= M)
        logstream(LOG_FATAL)<<"Row index larger than the matrix row size " << I << " > " << M << " in line: " << i << std::endl;
      if (J >= N)
        logstream(LOG_FATAL)<<"Col index larger than the matrix col size " << J << " > " << N << " in line; " << i << std::endl;
      K = std::max((int)time, (int)K);
      //avoid self edges
      if (square && I == J)
        continue;
      globalMean += val; 
      L++;
      sharderobj.preprocessing_add_edge(I, (square? J : (M + J)), als_edge_type(val, time+M+N));
      //in case of a tensor, add besides of the user-> movie edge also
      //time -> user and time-> movie edges
      if (add_time_edges){
        sharderobj.preprocessing_add_edge((uint)time + M + N, I, als_edge_type(val, M+J));
        sharderobj.preprocessing_add_edge((uint)time + M + N, M+J , als_edge_type(val, I));
      }
    }

    uint toadd = 0;
    if (implicitratingtype == IMPLICIT_RATING_RANDOM)
      toadd = add_implicit_edges4(implicitratingtype, sharderobj);
    globalMean += implicitratingvalue * toadd;
    L += toadd;

    sharderobj.end_preprocessing();
    globalMean /= L;
    logstream(LOG_INFO) << "Global mean is: " << globalMean << " time bins: " << K << " . Now creating shards." << std::endl;
    FILE * outf = fopen((base_filename + ".gm").c_str(), "w");
    fprintf(outf, "%d\n%d\n%ld\n%lg\n%d\n", M, N, L, globalMean, K);
    fclose(outf);


  } else {
    logstream(LOG_INFO) << "Matrix already preprocessed, just run sharder." << std::endl;
  }

  fclose(f);
  logstream(LOG_INFO) << "Now creating shards." << std::endl;

  // Shard with a specified number of shards, or determine automatically if not defined
  nshards = sharderobj.execute_sharding(get_option_string("nshards", "auto"));

  return nshards;
}