[mlpack-svn] r13725 - mlpack/trunk/src/mlpack/bindings/matlab/emst

[fastlab-svn at coffeetalk-1.cc.gatech.edu]

Author: rcurtin
Date: 2012-10-17 14:58:30 -0400 (Wed, 17 Oct 2012)
New Revision: 13725

Modified:
   mlpack/trunk/src/mlpack/bindings/matlab/emst/CMakeLists.txt
   mlpack/trunk/src/mlpack/bindings/matlab/emst/emst.m
Log:
Change name of output and update MATLAB binding accordingly.


Modified: mlpack/trunk/src/mlpack/bindings/matlab/emst/CMakeLists.txt
===================================================================
--- mlpack/trunk/src/mlpack/bindings/matlab/emst/CMakeLists.txt	2012-10-17 02:55:28 UTC (rev 13724)
+++ mlpack/trunk/src/mlpack/bindings/matlab/emst/CMakeLists.txt	2012-10-17 18:58:30 UTC (rev 13725)
@@ -1,5 +1,6 @@
 # Simple rules for building mex file.  The _mex suffix is necessary to avoid
-# target name conflicts.
+# target name conflicts, and the mex file must have a different name than the .m
+# file.
 add_library(emst_mex SHARED
   emst.cpp
 )
@@ -8,11 +9,6 @@
   ${LIBXML2_LIBRARIES}
 )
 
-# Change the name of the output library.
-set_target_properties(emst_mex
-  PROPERTIES OUTPUT_NAME emst
-)
-
 # Installation rule.  Install both the mex and the MATLAB file.
 install(TARGETS emst_mex
   LIBRARY DESTINATION "${MATLAB_TOOLBOX_DIR}/mlpack/"

Modified: mlpack/trunk/src/mlpack/bindings/matlab/emst/emst.m
===================================================================
--- mlpack/trunk/src/mlpack/bindings/matlab/emst/emst.m	2012-10-17 02:55:28 UTC (rev 13724)
+++ mlpack/trunk/src/mlpack/bindings/matlab/emst/emst.m	2012-10-17 18:58:30 UTC (rev 13725)
@@ -1,25 +1,25 @@
 function result = emst(dataPoints, varargin)
 % Fast Euclidean Minimum Spanning Tree. This script can compute
-% the Euclidean minimum spanning tree of a set of input points using the 
+% the Euclidean minimum spanning tree of a set of input points using the
 % dual-tree Boruvka algorithm.
-% 
+%
 % The output is saved in a three-column matrix, where each row indicates an
 % edge.  The first column corresponds to the lesser index of the edge; the
 % second column corresponds to the greater index of the edge; and the third
 % column corresponds to the distance between the two points.
 %
 % Parameters:
-% dataPoints - the matrix of data points. Columns are assumed to represent dimensions, 
-%              with rows representing seperate points. 
-% method     - the algorithm for computing the tree. 'naive' or 'boruvka', with 
+% dataPoints - the matrix of data points. Columns are assumed to represent dimensions,
+%              with rows representing seperate points.
+% method     - the algorithm for computing the tree. 'naive' or 'boruvka', with
 %              'boruvka' being the default algorithm.
-% leafSize   - Leaf size in the kd-tree.  One-element leaves give the 
+% leafSize   - Leaf size in the kd-tree.  One-element leaves give the
 %              empirically best performance, but at the cost of greater memory
-%              requirements. One is default. 
-% 
+%              requirements. One is default.
+%
 % Examples:
 % result = emst(dataPoints);
-% or 
+% or
 % esult = emst(dataPoints,'method','naive');
 
 % a parser for the inputs
@@ -31,13 +31,13 @@
 p.parse(varargin{:});
 parsed = p.Results;
 
-% interfacing with mlpack. transposing to machine learning standards. 
+% interfacing with mlpack. transposing to machine learning standards.
 if strcmpi(parsed.method, 'boruvka')
-  result = mex_emst(dataPoints', 1, parsed.leafSize);
+  result = emst_mex(dataPoints', 1, parsed.leafSize);
 	result = result';
   return;
 else
-  result = mex_emst(dataPoints', 0, 1);
+  result = emst_mex(dataPoints', 0, 1);
 	result = result';
   return;
 end