[Scipy-svn] r5121 - trunk/doc/releases

scipy-svn@scip... scipy-svn@scip...
Sun Nov 16 00:57:03 CST 2008


Author: jarrod.millman
Date: 2008-11-16 00:57:02 -0600 (Sun, 16 Nov 2008)
New Revision: 5121

Modified:
   trunk/doc/releases/0.7.0-notes.rst
Log:
rest clean-up


Modified: trunk/doc/releases/0.7.0-notes.rst
===================================================================
--- trunk/doc/releases/0.7.0-notes.rst	2008-11-16 06:47:06 UTC (rev 5120)
+++ trunk/doc/releases/0.7.0-notes.rst	2008-11-16 06:57:02 UTC (rev 5121)
@@ -1,13 +1,26 @@
-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.
+=========================
+SciPy 0.7.0 Release Notes
+=========================
 
-= Changes =
+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.
 
-== scipy.io ==
+Changes
+-------
 
-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, while !SciPy will house file readers and writers for various data formats (data, audio, video, images, matlab, excel, etc.).  This will take place in stages.  The first stage was completed with the release of !NumPy 1.1.0.  As part of this phase:
- * many of the functions in scipy.io have been deprecated
+SciPy IO
+~~~~~~~~
 
-mention specific improvements to io, e.g. MATLAB sparse support (TODO)
+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,
+while SciPy will house file readers and writers for various data formats
+(data, audio, video, images, matlab, excel, etc.).  This reworking started
+NumPy 1.1.0 and will take place over many release.  SciPy 0.7.0 has several
+changes including:
+* many of the functions in scipy.io have been deprecated
+* the Matlab (TM) file readers/writers have a number of improvements:
+ * default version 5
 
 Hierarchical Clustering
 =======================
@@ -27,12 +40,34 @@
 matplotlib extension is provided for plotting dendrograms, which
 may be outputted to postscript or any other supported format.
 
+== New Hierarchical Clustering module ==
+This module adds new hierarchical clustering functionality to the
+cluster package. Its interface is similar to the hierarchical
+clustering functions provided in MATLAB(TM)'s Statistics Toolbox to
+facilitate easier migration to the NumPy/SciPy framework. Linkage
+methods implemented include single, complete, average, weighted,
+centroid, median, and ward. Several functions are provided for
+computing statistics on clusters including inconsistency statistics,
+cophenetic distance, and maximum distance of descendants. The fcluster
+and fclusterdata functions take hierarchical tree clusterings
+generated by these algorithms, cuts the tree, and labels the flat
+clusters. The leaders function finds the root of each flat cluster
+given a hierarchical clustering and labellings of its leaves. Finally, a
+matplotlib extension is provided for plotting dendrograms, which
+may be outputted to postscript or any other supported format.
+
+http://scipy.org/scipy/scipy/browser/trunk/scipy/cluster/hierarchy.py
+
 Spatial Package
 ===============
 
 The new scipy.spatial package provides routines for distance computation
 and kd-tree manipulation.
 
+== New Spatial package ==
+Collection of spatial algorithms and data structures useful for spatial statistics and clustering applications. Includes fast compiled code for computing exact and approximate nearest neighbors, as well as a pure-python kd-tree with the same interface but that supports annotation and a variety of other algorithms. The API for both modules may change somewhat as user requirements become clearer. Also includes a submodule "distance" containing fast code for many definitions of "distance" between vectors. Distance and dissimilarity functions are provided include Bray-Curtis, Canberra, Chebyshev, City Block, Cosine, Dice, Euclidean, Hamming, Jaccard, Kulsinski, Mahalanobis, Matching, Minkowski, Rogers-Tanimoto, Russell-Rao, Squared Euclidean, Standardized Euclidean, Sokal-Michener, Sokal-Sneath, and Yule. Two functions are provided for computing distances between collections of vectors: pdist and cdist. pdist is similar to the MATLAB(TM) function and computes pairwise distances between a collection of vectors. cdist computes distances between vectors in two sets of vectors. squareform converts between square distance matrices and condensed distance matrices.
+
+
 Distance Module
 ----------------
 
@@ -50,15 +85,16 @@
 a square distance matrix to a condensed matrix and vice versa.
 
 
-== scipy.fftpack ==
-FFTW2, FFTW3, MKL and DJBFFT wrappers have been removed. Only (NETLIB) fftpack remains. By focusing on one backend, we hope to add new features - like float32 support - more easily.
+fftpack
+~~~~~~~
 
-=== scipy.io.matlab ===
+FFTW2, FFTW3, MKL and DJBFFT wrappers have been removed. Only (NETLIB)
+fftpack remains. By focusing on one backend, we hope to add new
+features -- like float32 support -- more easily.
 
-The Matlab (TM) file readers/writers have a number of improvements:
- * default version 5
+Sparse Matrices
+~~~~~~~~~~~~~~~
 
-== scipy.sparse ==
  * 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
@@ -82,31 +118,11 @@
    * sparse matrix arithmetic
  * numerous bugfixes
 
-== New Spatial package ==
-Collection of spatial algorithms and data structures useful for spatial statistics and clustering applications. Includes fast compiled code for computing exact and approximate nearest neighbors, as well as a pure-python kd-tree with the same interface but that supports annotation and a variety of other algorithms. The API for both modules may change somewhat as user requirements become clearer. Also includes a submodule "distance" containing fast code for many definitions of "distance" between vectors. Distance and dissimilarity functions are provided include Bray-Curtis, Canberra, Chebyshev, City Block, Cosine, Dice, Euclidean, Hamming, Jaccard, Kulsinski, Mahalanobis, Matching, Minkowski, Rogers-Tanimoto, Russell-Rao, Squared Euclidean, Standardized Euclidean, Sokal-Michener, Sokal-Sneath, and Yule. Two functions are provided for computing distances between collections of vectors: pdist and cdist. pdist is similar to the MATLAB(TM) function and computes pairwise distances between a collection of vectors. cdist computes distances between vectors in two sets of vectors. squareform converts between square distance matrices and condensed distance matrices.
-
 == New Constants package ==
 Collection of physical constants and conversion factors:
 http://scipy.org/scipy/scipy/browser/trunk/scipy/constants/
 
-== New Hierarchical Clustering module ==
-This module adds new hierarchical clustering functionality to the
-cluster package. Its interface is similar to the hierarchical
-clustering functions provided in MATLAB(TM)'s Statistics Toolbox to
-facilitate easier migration to the NumPy/SciPy framework. Linkage
-methods implemented include single, complete, average, weighted,
-centroid, median, and ward. Several functions are provided for
-computing statistics on clusters including inconsistency statistics,
-cophenetic distance, and maximum distance of descendants. The fcluster
-and fclusterdata functions take hierarchical tree clusterings
-generated by these algorithms, cuts the tree, and labels the flat
-clusters. The leaders function finds the root of each flat cluster
-given a hierarchical clustering and labellings of its leaves. Finally, a
-matplotlib extension is provided for plotting dendrograms, which
-may be outputted to postscript or any other supported format.
 
-http://scipy.org/scipy/scipy/browser/trunk/scipy/cluster/hierarchy.py
-
 == New Radial Basis Function module ==
 http://scipy.org/scipy/scipy/browser/trunk/scipy/interpolate/rbf.py
 
@@ -114,8 +130,14 @@
 
 TODO
 
-== Running Tests ==
-We are moving away from having our own testing framework and are adopting [http://code.google.com/p/python-nose/ nose].
+Running Tests
+~~~~~~~~~~~~~
 
-== Building !SciPy ==
-Support for !NumScons has been added. numscons is a tentative new build system for numpy/scipy, using scons at its core.
+We are moving away from having our own testing framework and are
+adopting `nose <http://code.google.com/p/python-nose/>`.
+
+Building SciPy
+~~~~~~~~~~~~~~
+
+Support for !NumScons has been added. numscons is a tentative new
+build system for numpy/scipy, using scons at its core.



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