sparse

Create a sparse array. More...

Functions
AFAPI array	sparse (const dim_t nRows, const dim_t nCols, const array values, const array rowIdx, const array colIdx, const af::storage stype=AF_STORAGE_CSR)
	This function converts af::array of values, row indices and column indices into a sparse array. More...
AFAPI array	sparse (const dim_t nRows, const dim_t nCols, const dim_t nNZ, const void *const values, const int *const rowIdx, const int *const colIdx, const dtype type=f32, const af::storage stype=AF_STORAGE_CSR, const af::source src=afHost)
	This function converts host or device arrays of values, row indices and column indices into a sparse array on the device. More...
AFAPI array	sparse (const array dense, const af::storage stype=AF_STORAGE_CSR)
	This function converts a dense af::array into a sparse array. More...
AFAPI af_err	af_create_sparse_array (af_array *out, const dim_t nRows, const dim_t nCols, const af_array values, const af_array rowIdx, const af_array colIdx, const af_storage stype)
	This function converts af::array of values, row indices and column indices into a sparse array. More...
AFAPI af_err	af_create_sparse_array_from_ptr (af_array *out, const dim_t nRows, const dim_t nCols, const dim_t nNZ, const void *const values, const int *const rowIdx, const int *const colIdx, const af_dtype type, const af_storage stype, const af_source src)
	This function converts host or device arrays of values, row indices and column indices into a sparse array on the device. More...
AFAPI af_err	af_create_sparse_array_from_dense (af_array *out, const af_array dense, const af_storage stype)
	This function converts a dense af_array into a sparse array. More...

Detailed Description

Create a sparse array.

The sparse creation function has 3 different types of inputs it can accept.

1. Independent af::array for values, row indices and column indices.
2. Independent host or device native arrays for values, row indices and column indices.
3. A dense af::array.

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Function Documentation

af_create_sparse_array()

AFAPI af_err af_create_sparse_array	(	af_array *	out,
		const dim_t	nRows,
		const dim_t	nCols,
		const af_array	values,
		const af_array	rowIdx,
		const af_array	colIdx,
		const af_storage	stype
	)

This function converts af::array of values, row indices and column indices into a sparse array.

Note

This function only create references of these arrays into the sparse data structure and does not do deep copies.

Parameters

[out]	out	af::array for the sparse array
[in]	nRows	is the number of rows in the dense matrix
[in]	nCols	is the number of columns in the dense matrix
[in]	values	is the af_array containing the non-zero elements of the matrix
[in]	rowIdx	is the row indices for the sparse array
[in]	colIdx	is the column indices for the sparse array
[in]	stype	is the storage format of the sparse array

Returns

AF_SUCCESS if the execution completes properly

af_create_sparse_array_from_dense()

AFAPI af_err af_create_sparse_array_from_dense	(	af_array *	out,
		const af_array	dense,
		const af_storage	stype
	)

This function converts a dense af_array into a sparse array.

Parameters

[out]	out	af_array for the sparse array with the given storage type
[in]	dense	is the source dense matrix
[in]	stype	is the storage format of the sparse array

Returns

AF_SUCCESS if the execution completes properly

af_create_sparse_array_from_ptr()

AFAPI af_err af_create_sparse_array_from_ptr	(	af_array *	out,
		const dim_t	nRows,
		const dim_t	nCols,
		const dim_t	nNZ,
		const void *const	values,
		const int *const	rowIdx,
		const int *const	colIdx,
		const af_dtype	type,
		const af_storage	stype,
		const af_source	src
	)

This function converts host or device arrays of values, row indices and column indices into a sparse array on the device.

Note

The rules for deep copy/shallow copy/reference are the same as for creating a regular af::array.

Parameters

[out]	out	af::array for the sparse array
[in]	nRows	is the number of rows in the dense matrix
[in]	nCols	is the number of columns in the dense matrix
[in]	nNZ	is the number of non zero elements in the dense matrix
[in]	values	is the host array containing the non-zero elements of the matrix
[in]	rowIdx	is the row indices for the sparse array
[in]	colIdx	is the column indices for the sparse array
[in]	type	is the data type for the matrix
[in]	stype	is the storage format of the sparse array
[in]	src	is afHost if inputs are host arrays and afDevice if the arrays are device arrays.

Returns

AF_SUCCESS if the execution completes properly

sparse() [1/3]

AFAPI array sparse	(	const array	dense,
		const af::storage	stype = AF_STORAGE_CSR
	)

This function converts a dense af::array into a sparse array.

Parameters

[in]	dense	is the source dense matrix
[in]	stype	is the storage format of the sparse array

Returns

af::array for the sparse array with the given storage type

 
    // dense
    //     0     0     0     0
    //     5     8     0     0
    //     0     0     3     0
    //     0     6     0     0
 
    // Convert dense af::array to its sparse (CSR) representation.
    array sparse = af::sparse(dense, AF_STORAGE_CSR);
 
    // sparse
    //     values:  [ 5.0, 8.0, 3.0, 6.0 ]
    //     row_ptr: [ 0, 0, 2, 3, 4 ]
    //     col_idx: [ 0, 1, 2, 1 ]
 

sparse() [2/3]

AFAPI array sparse	(	const dim_t	nRows,
		const dim_t	nCols,
		const array	values,
		const array	rowIdx,
		const array	colIdx,
		const af::storage	stype = AF_STORAGE_CSR
	)

This function converts af::array of values, row indices and column indices into a sparse array.

Note

This function only create references of these arrays into the sparse data structure and does not do deep copies.

Parameters

[in]	nRows	is the number of rows in the dense matrix
[in]	nCols	is the number of columns in the dense matrix
[in]	values	is the af::array containing the non-zero elements of the matrix
[in]	rowIdx	is the row indices for the sparse array
[in]	colIdx	is the column indices for the sparse array
[in]	stype	is the storage format of the sparse array

Returns

af::array for the sparse array

 
    float v[]   = {5, 8, 3, 6};
    int r[]     = {0, 0, 2, 3, 4};
    int c[]     = {0, 1, 2, 1};
    const int M = 4, N = 4, nnz = 4;
    array vals    = array(dim4(nnz), v);
    array row_ptr = array(dim4(M + 1), r);
    array col_idx = array(dim4(nnz), c);
 
    // Create sparse array (CSR) from af::arrays containing values,
    // row pointers, and column indices.
    array sparse = af::sparse(M, N, vals, row_ptr, col_idx, AF_STORAGE_CSR);
 
    // sparse
    //     values:  [ 5.0, 8.0, 3.0, 6.0 ]
    //     row_ptr: [ 0, 0, 2, 3, 4 ]
    //     col_idx: [ 0, 1, 2, 1 ]
 

sparse() [3/3]

AFAPI array sparse	(	const dim_t	nRows,
		const dim_t	nCols,
		const dim_t	nNZ,
		const void *const	values,
		const int *const	rowIdx,
		const int *const	colIdx,
		const dtype	type = f32,
		const af::storage	stype = AF_STORAGE_CSR,
		const af::source	src = afHost
	)

This function converts host or device arrays of values, row indices and column indices into a sparse array on the device.

Note

The rules for deep copy/shallow copy/reference are the same as for creating a regular af::array.

Parameters

[in]	nRows	is the number of rows in the dense matrix
[in]	nCols	is the number of columns in the dense matrix
[in]	nNZ	is the number of non zero elements in the dense matrix
[in]	values	is the host array containing the non-zero elements of the matrix
[in]	rowIdx	is the row indices for the sparse array
[in]	colIdx	is the column indices for the sparse array
[in]	type	is the data type for the matrix
[in]	stype	is the storage format of the sparse array
[in]	src	is afHost if inputs are host arrays and afDevice if the arrays are device arrays.

Returns

af::array for the sparse array

 
    float vals[]  = {5, 8, 3, 6};
    int row_ptr[] = {0, 0, 2, 3, 4};
    int col_idx[] = {0, 1, 2, 1};
    const int M = 4, N = 4, nnz = 4;
 
    // Create sparse array (CSR) from host pointers to values, row
    // pointers, and column indices.
    array sparse = af::sparse(M, N, nnz, vals, row_ptr, col_idx, f32,
                              AF_STORAGE_CSR, afHost);
 
    // sparse
    //     values:  [ 5.0, 8.0, 3.0, 6.0 ]
    //     row_ptr: [ 0, 0, 2, 3, 4 ]
    //     col_idx: [ 0, 1, 2, 1 ]