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Class jnt.linear_algebra.CoordinateSparseMatrixDouble
java.lang.Object

+jnt.linear_algebra.CoordinateSparseMatrixDouble
 public class CoordinateSparseMatrixDouble
 extends Object
A coordinatestorage representation of sparse matrices in which
the nonzeros at location A[i][j] are stored explicity. No
order is imposed on the storage order.
and basic algebraic operations.
The nonzero value, together with its offset are stored.
Thus, the 5element matrix
0 1 0
4 2 0
0 0 7
could be represented by the following contstructor:
double val[] = new double[3];
int row[] = new int[3];
int col[] = new int[3];
val[0] = 1.0; col[0] = 0; row[0] = 1;
val[1] = 4.0; col[1] = 1; row[1] = 0;
val[2] = 2.0; col[2] = 1; row[2] = 1;
val[3] = 7.0; col[3] = 2; row[3] = 2;
CoordinateSparseMatrixDouble S = new
CoordinateSparseMatrixDouble(3, 3, 4, val, row, col);
or, equivalently
CoordinateSparseMatrixDouble S = new
CoordinateSparseMatrixDouble(3, 3, 4);
for (int i=0; i<3; i++)
S.set_ith_element(i, row[i], col[i], val[i]);
General set/get functions which treat the matrix as dense, are
available but are not very efficient (i.e. they have an O(nz) cost).
S.set(i,j, val); // equivalent to A[i][j] = val;
v = S.get(i,j); // equivalent to v = A[i][j];
The elements are unoreded, and offsets begin at 0.
Note, also, that coordinate matrix representations are not
unique  the elements are unordered, and explicit zeros
could be stored.
 Version:
 0.5
 Author:
 Roldan Pozo

CoordinateSparseMatrixDouble(int, int)
 Initialize a sparse vector of a given dimension.

CoordinateSparseMatrixDouble(int, int, int)
 Initialize a sparse vector of a given dimension and nonzeros.

CoordinateSparseMatrixDouble(int, int, int, int[], int[], double[])
 Initialize a sparse vector of dimension N, with nz nonzeros,
given values from
val[]
and integer positions
in ind[]
.

col()
 Return vector of column indices as a contiguous array.

col(int)


copy()
 Create a copy of an existing sparse vector.

M()
 Return the first dimension of the sparse matrix.

mult(double[])
 Compute A*x

mult(double[], double[])
 Compute y += A*x;

N()
 Return the second dimension of the sparse matrix.

num_nonzeros()
 Return the number of number of nonzeros in sparse matrix.

print()


readfile(String)

Read a sparse matrix from an ASCII text file.

readfile(String, int)
 Reads sparse form file, similar to readfile(String)
but has an optional baseoffset parameter to denote
the starting position of matrix indices.

row()
 Return vector of row indices as a contiguous array.

row(int)


val()
 Return vector of nonzero values.

val(int)


write()


write(CoordinateSparseMatrixDouble)

CoordinateSparseMatrixDouble
public CoordinateSparseMatrixDouble(int M,
int N)
 Initialize a sparse vector of a given dimension. No storage space
for nonzeros is actually created.
 Parameters:
 N  the dimension of the vector (not the
number of nonzeros.)
CoordinateSparseMatrixDouble
public CoordinateSparseMatrixDouble(int M,
int N,
int nz)
 Initialize a sparse vector of a given dimension and nonzeros.
 Parameters:
 N  the dimension of the vector.
 nz  the number of nonzeros.
CoordinateSparseMatrixDouble
public CoordinateSparseMatrixDouble(int M,
int N,
int nz,
int row[],
int col[],
double val[])
 Initialize a sparse vector of dimension N, with nz nonzeros,
given values from
val[]
and integer positions
in ind[]
.
 Parameters:
 N  the dimension of the vector.
 nz  the number of nonzeros.
 val[nz]  vector of nonzero values
 ind[nz]  vector of positions of elements in val[].
copy
public CoordinateSparseMatrixDouble copy()
 Create a copy of an existing sparse vector.
val
public final double[] val()
 Return vector of nonzero values.
NOTE: this access method is here for efficiency.
It should be used by 'trusted' apps only, because
it essentially bypasses the 'private' status
of these variables.
val
public final double val(int i)
row
public final int[] row()
 Return vector of row indices as a contiguous array.
NOTE: this access method is here for efficiency.
It should be used by 'trusted' apps only, because
it essentially bypasses the 'private' status
of these variables.
row
public final int row(int i)
col
public final int col(int i)
col
public final int[] col()
 Return vector of column indices as a contiguous array.
NOTE: this access method is here for efficiency.
It should be used by 'trusted' apps only, because
it essentially bypasses the 'private' status
of these variables.
mult
public final double[] mult(double x[])
 Compute A*x
mult
public final void mult(double y[],
double x[])
 Compute y += A*x;
 Parameters:
 x  the vector to multiply
 y  the vector to update
print
public void print()
write
public static void write(CoordinateSparseMatrixDouble S)
write
public void write()
readfile
public static CoordinateSparseMatrixDouble readfile(String s) throws IOException
 Read a sparse matrix from an ASCII text file.
The file format lists the matrix size (M, N),
the number of nonzeros (nz), followed by the
triplet (i, j, a_ij) for each nonzero. For
example,
5 7 3
1 1 2.0
3 4 9.9
6 3 7.5
denotes the 5x7 sparse matrix with 3 nonzeros:
The base offsets are assumed to be zero (ie. A[0][0]
is the first element), but can be overridden by an
optional baseoffset. (see readfile(String, int).)
readfile
public static CoordinateSparseMatrixDouble readfile(String s,
int base_offset) throws IOException
 Reads sparse form file, similar to readfile(String)
but has an optional baseoffset parameter to denote
the starting position of matrix indices. For example,
a value of 1 denotes that the index pair "1 1" is the
first element of the matrix. Typically, this value
is zero for Java/C/C++ arrays.
This option is here mainly for compatibility with
MatrixMarket files and other data formats that use
1based offsets.
M
public int M()
 Return the first dimension of the sparse matrix.
N
public int N()
 Return the second dimension of the sparse matrix.
num_nonzeros
public int num_nonzeros()
 Return the number of number of nonzeros in sparse matrix.
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