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sparse.rst

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.. currentmodule:: Base

Sparse Matrices

Sparse matrices support much of the same set of operations as dense matrices. The following functions are specific to sparse matrices.

.. function:: sparse(I,J,V,[m,n,combine])

   Create a sparse matrix ``S`` of dimensions ``m x n`` such that ``S[I[k], J[k]] = V[k]``. The ``combine`` function is used to combine duplicates. If ``m`` and ``n`` are not specified, they are set to ``max(I)`` and ``max(J)`` respectively. If the ``combine`` function is not supplied, duplicates are added by default.


.. function:: sparsevec(I, V, [m, combine])

   Create a sparse matrix ``S`` of size ``m x 1`` such that ``S[I[k]] = V[k]``. Duplicates are combined using the ``combine`` function, which defaults to ``+`` if it is not provided. In julia, sparse vectors are really just sparse matrices with one column. Given Julia's Compressed Sparse Columns (CSC) storage format, a sparse column matrix with one column is sparse, whereas a sparse row matrix with one row ends up being dense.


.. function:: sparsevec(D::Dict, [m])

   Create a sparse matrix of size ``m x 1`` where the row values are keys from the dictionary, and the nonzero values are the values from the dictionary.


.. function:: issparse(S)

   Returns ``true`` if ``S`` is sparse, and ``false`` otherwise.


.. function:: sparse(A)

   Convert a dense matrix ``A`` into a sparse matrix.


.. function:: sparsevec(A)

   Convert a dense vector ``A`` into a sparse matrix of size ``m x 1``. In julia, sparse vectors are really just sparse matrices with one column.


.. function:: dense(S)

   Convert a sparse matrix ``S`` into a dense matrix.


.. function:: full(S)

   Convert a sparse matrix ``S`` into a dense matrix.


.. function:: spzeros(m,n)

   Create an empty sparse matrix of size ``m x n``.


.. function:: spones(S)

   Create a sparse matrix with the same structure as that of ``S``, but with every nonzero element having the value ``1.0``.


.. function:: speye(type,m[,n])

   Create a sparse identity matrix of specified type of size ``m x m``. In case ``n`` is supplied, create a sparse identity matrix of size ``m x n``.


.. function:: spdiagm(B, d[, m, n])

   Construct a sparse diagonal matrix. ``B`` is a tuple of vectors containing the diagonals and ``d`` is a tuple containing the positions of the diagonals. In the case the input contains only one diagonaly, ``B`` can be a vector (instead of a tuple) and ``d`` can be the diagonal position (instead of a tuple). Optionally, ``m`` and ``n`` specify the size of the resulting sparse matrix.


.. function:: sprand(m,n,density[,rng])

   Create a random sparse matrix with the specified density. Nonzeros are sampled from the distribution specified by ``rng``. The uniform distribution is used in case ``rng`` is not specified.


.. function:: sprandn(m,n,density)

   Create a random sparse matrix of specified density with nonzeros sampled from the normal distribution.


.. function:: sprandbool(m,n,density)

   Create a random sparse boolean matrix with the specified density.


.. function:: etree(A[, post])

   Compute the elimination tree of a symmetric sparse matrix ``A`` from ``triu(A)`` and, optionally, its post-ordering permutation.