<commit_before>=========================
SciPy 0.7.0 Release Notes
=========================

This is a new stable release.  Please note that unlike previous versions
of SciPy, this release requires Python 2.4 or greater.  This release also
requires NumPy 1.2.0 or greater.

Changes
-------

Sparse Matrices
~~~~~~~~~~~~~~~

* added support for integer dtypes such ``int8``, ``uint32``, etc.
* new class ``dia_matrix`` : the sparse DIAgonal format
* new class ``bsr_matrix`` : sparse Block CSR format
* new sparse matrix construction functions

 * ``sparse.kron`` : sparse Kronecker product
 * ``sparse.bmat`` : sparse version of ``numpy.bmat``
 * ``sparse.vstack`` : sparse version of ``numpy.vstack``
 * ``sparse.hstack`` : sparse version of ``numpy.hstack``

* extraction of submatrices and nonzero values

 * ``sparse.tril`` : extract lower triangle
 * ``sparse.kron`` : extract upper triangle
 * ``sparse.find`` : nonzero values and their indices

* ``csr_matrix`` and ``csc_matrix`` now support slicing and fancy indexing

 * e.g. ``A[1:3, 4:7]`` and ``A[[3,2,6,8],:]``

* conversions among all sparse formats are now possible

 * all formats have member functions such as ``.tocsr()`` and ``.tolil()``

* sparse constructors now accept dense matrices and other sparse formats

 * e.g. ``A = csr_matrix( rand(3,3) )`` and ``B = lil_matrix( [[1,2],[3,4]] )``

* efficiency improvements to:

 * format conversions
 * sparse matrix arithmetic

* numerous bugfixes

Reworking of IO package
~~~~~~~~~~~~~~~~~~~~~~~

The IO code in both NumPy and SciPy is undergoing a major reworking. NumPy
will be where basic code for reading and writing NumPy arrays is located,<commit_msg>minor edits to list of sparse changes<commit_after>=========================
SciPy 0.7.0 Release Notes
=========================

This is a new stable release.  Please note that unlike previous versions
of SciPy, this release requires Python 2.4 or greater.  This release also
requires NumPy 1.2.0 or greater.

Changes
-------

Sparse Matrices
~~~~~~~~~~~~~~~

* added support for integer dtypes such ``int8``, ``uint32``, etc.
* new class ``dia_matrix`` : the sparse DIAgonal format
* new class ``bsr_matrix`` : the Block CSR format
* new sparse matrix construction functions

 * ``sparse.kron`` : sparse Kronecker product
 * ``sparse.bmat`` : sparse version of ``numpy.bmat``
 * ``sparse.vstack`` : sparse version of ``numpy.vstack``
 * ``sparse.hstack`` : sparse version of ``numpy.hstack``

* extraction of submatrices and nonzero values

 * ``sparse.tril`` : extract lower triangle
 * ``sparse.triu`` : extract upper triangle
 * ``sparse.find`` : nonzero values and their indices

* ``csr_matrix`` and ``csc_matrix`` now support slicing and fancy indexing

 * e.g. ``A[1:3, 4:7]`` and ``A[[3,2,6,8],:]``

* conversions among all sparse formats are now possible

 * using member functions such as ``.tocsr()`` and ``.tolil()``
 * using the ``.asformat()`` member function, e.g. ``A.asformat('csr')``
 * using constructors ``A = lil_matrix([[1,2]]); B = csr_matrix(A)``

* all sparse constructors now accept dense matrices and lists of lists

 * e.g. ``A = csr_matrix( rand(3,3) )`` and ``B = lil_matrix( [[1,2],[3,4]] )``

* efficiency improvements to:

 * format conversions
 * sparse matrix arithmetic

* numerous bugfixes

Reworking of IO package
~~~~~~~~~~~~~~~~~~~~~~~

The IO code in both NumPy and SciPy is undergoing a major reworking. NumPy
will be where basic code for reading and writing NumPy arrays is located,
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