[Scipy-svn] r6658 - in trunk: doc/source scipy/spatial

scipy-svn@scip... scipy-svn@scip...
Tue Aug 31 16:59:25 CDT 2010


Author: ptvirtan
Date: 2010-08-31 16:59:25 -0500 (Tue, 31 Aug 2010)
New Revision: 6658

Modified:
   trunk/doc/source/spatial.distance.rst
   trunk/doc/source/spatial.rst
   trunk/scipy/spatial/distance.py
   trunk/scipy/spatial/info.py
Log:
DOC: spatial: move scipy.spatial docs to the module docstrings

Modified: trunk/doc/source/spatial.distance.rst
===================================================================
--- trunk/doc/source/spatial.distance.rst	2010-08-31 21:58:55 UTC (rev 6657)
+++ trunk/doc/source/spatial.distance.rst	2010-08-31 21:59:25 UTC (rev 6658)
@@ -1,6 +1 @@
-=====================================================
-Distance computations (:mod:`scipy.spatial.distance`)
-=====================================================
-
 .. automodule:: scipy.spatial.distance
-   :members:

Modified: trunk/doc/source/spatial.rst
===================================================================
--- trunk/doc/source/spatial.rst	2010-08-31 21:58:55 UTC (rev 6657)
+++ trunk/doc/source/spatial.rst	2010-08-31 21:59:25 UTC (rev 6658)
@@ -1,14 +1,6 @@
-=============================================================
-Spatial algorithms and data structures (:mod:`scipy.spatial`)
-=============================================================
+.. automodule:: scipy.spatial
 
-.. warning::
-
-   This documentation is work-in-progress and unorganized.
-
 .. toctree::
+   :hidden:
 
    spatial.distance
-
-.. automodule:: scipy.spatial
-   :members:

Modified: trunk/scipy/spatial/distance.py
===================================================================
--- trunk/scipy/spatial/distance.py	2010-08-31 21:58:55 UTC (rev 6657)
+++ trunk/scipy/spatial/distance.py	2010-08-31 21:59:25 UTC (rev 6658)
@@ -1,90 +1,65 @@
 """
+=====================================================
+Distance computations (:mod:`scipy.spatial.distance`)
+=====================================================
+
+.. sectionauthor:: Damian Eads
+
 Function Reference
 ------------------
 
 Distance matrix computation from a collection of raw observation vectors
 stored in a rectangular array.
 
-+------------------+-------------------------------------------------+
-|*Function*        | *Description*                                   |
-+------------------+-------------------------------------------------+
-|pdist             | pairwise distances between observation          |
-|                  | vectors.                                        |
-+------------------+-------------------------------------------------+
-|cdist             | distances between between two collections of    |
-|                  | observation vectors.                            |
-+------------------+-------------------------------------------------+
-|squareform        | converts a square distance matrix to a          |
-|                  | condensed one and vice versa.                   |
-+------------------+-------------------------------------------------+
+.. autosummary::
+   :toctree: generated/
 
+   pdist   -- pairwise distances between observation vectors.
+   cdist   -- distances between between two collections of observation vectors
+   squareform -- convert distance matrix to a condensed one and vice versa
+
 Predicates for checking the validity of distance matrices, both
 condensed and redundant. Also contained in this module are functions
 for computing the number of observations in a distance matrix.
 
-+------------------+-------------------------------------------------+
-|*Function*        | *Description*                                   |
-+------------------+-------------------------------------------------+
-|is_valid_dm       | checks for a valid distance matrix.             |
-+------------------+-------------------------------------------------+
-|is_valid_y        | checks for a valid condensed distance matrix.   |
-+------------------+-------------------------------------------------+
-|num_obs_dm        | # of observations in a distance matrix.         |
-+------------------+-------------------------------------------------+
-|num_obs_y         | # of observations in a condensed distance       |
-|                  | matrix.                                         |
-+------------------+-------------------------------------------------+
+.. autosummary::
+   :toctree: generated/
 
+   is_valid_dm -- checks for a valid distance matrix
+   is_valid_y  -- checks for a valid condensed distance matrix
+   num_obs_dm  -- # of observations in a distance matrix
+   num_obs_y   -- # of observations in a condensed distance matrix
+
 Distance functions between two vectors ``u`` and ``v``. Computing
 distances over a large collection of vectors is inefficient for these
 functions. Use ``pdist`` for this purpose.
 
-+------------------+-------------------------------------------------+
-|*Function*        | *Description*                                   |
-+------------------+-------------------------------------------------+
-| braycurtis       | the Bray-Curtis distance.                       |
-+------------------+-------------------------------------------------+
-| canberra         | the Canberra distance.                          |
-+------------------+-------------------------------------------------+
-| chebyshev        | the Chebyshev distance.                         |
-+------------------+-------------------------------------------------+
-| cityblock        | the Manhattan distance.                         |
-+------------------+-------------------------------------------------+
-| correlation      | the Correlation distance.                       |
-+------------------+-------------------------------------------------+
-| cosine           | the Cosine distance.                            |
-+------------------+-------------------------------------------------+
-| dice             | the Dice dissimilarity (boolean).               |
-+------------------+-------------------------------------------------+
-| euclidean        | the Euclidean distance.                         |
-+------------------+-------------------------------------------------+
-| hamming          | the Hamming distance (boolean).                 |
-+------------------+-------------------------------------------------+
-| jaccard          | the Jaccard distance (boolean).                 |
-+------------------+-------------------------------------------------+
-| kulsinski        | the Kulsinski distance (boolean).               |
-+------------------+-------------------------------------------------+
-| mahalanobis      | the Mahalanobis distance.                       |
-+------------------+-------------------------------------------------+
-| matching         | the matching dissimilarity (boolean).           |
-+------------------+-------------------------------------------------+
-| minkowski        | the Minkowski distance.                         |
-+------------------+-------------------------------------------------+
-| rogerstanimoto   | the Rogers-Tanimoto dissimilarity (boolean).    |
-+------------------+-------------------------------------------------+
-| russellrao       | the Russell-Rao dissimilarity (boolean).        |
-+------------------+-------------------------------------------------+
-| seuclidean       | the normalized Euclidean distance.              |
-+------------------+-------------------------------------------------+
-| sokalmichener    | the Sokal-Michener dissimilarity (boolean).     |
-+------------------+-------------------------------------------------+
-| sokalsneath      | the Sokal-Sneath dissimilarity (boolean).       |
-+------------------+-------------------------------------------------+
-| sqeuclidean      | the squared Euclidean distance.                 |
-+------------------+-------------------------------------------------+
-| yule             | the Yule dissimilarity (boolean).               |
-+------------------+-------------------------------------------------+
+.. autosummary::
+   :toctree: generated/
 
+   braycurtis       -- the Bray-Curtis distance.
+   canberra         -- the Canberra distance.
+   chebyshev        -- the Chebyshev distance.
+   cityblock        -- the Manhattan distance.
+   correlation      -- the Correlation distance.
+   cosine           -- the Cosine distance.
+   dice             -- the Dice dissimilarity (boolean).
+   euclidean        -- the Euclidean distance.
+   hamming          -- the Hamming distance (boolean).
+   jaccard          -- the Jaccard distance (boolean).
+   kulsinski        -- the Kulsinski distance (boolean).
+   mahalanobis      -- the Mahalanobis distance.
+   matching         -- the matching dissimilarity (boolean).
+   minkowski        -- the Minkowski distance.
+   rogerstanimoto   -- the Rogers-Tanimoto dissimilarity (boolean).
+   russellrao       -- the Russell-Rao dissimilarity (boolean).
+   seuclidean       -- the normalized Euclidean distance.
+   sokalmichener    -- the Sokal-Michener dissimilarity (boolean).
+   sokalsneath      -- the Sokal-Sneath dissimilarity (boolean).
+   sqeuclidean      -- the squared Euclidean distance.
+   yule             -- the Yule dissimilarity (boolean).
+
+
 References
 ----------
 

Modified: trunk/scipy/spatial/info.py
===================================================================
--- trunk/scipy/spatial/info.py	2010-08-31 21:58:55 UTC (rev 6657)
+++ trunk/scipy/spatial/info.py	2010-08-31 21:59:25 UTC (rev 6658)
@@ -1,12 +1,25 @@
 """
-Spatial data structures and algorithms
-======================================
+=============================================================
+Spatial algorithms and data structures (:mod:`scipy.spatial`)
+=============================================================
 
 Nearest-neighbor queries:
 
-    KDTree      -- class for efficient nearest-neighbor queries
-    distance    -- module containing many different distance measures
+.. autosummary::
+   :toctree: generated/
 
+   KDTree      -- class for efficient nearest-neighbor queries
+   cKDTree     -- class for efficient nearest-neighbor queries (faster impl.)
+   distance    -- module containing many different distance measures
+
+Delaunay triangulation:
+
+.. autosummary::
+   :toctree: generated/
+
+   Delaunay
+   tsearch
+
 """
 
 postpone_import = 1



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