[GRASS-SVN] r63376 - grass-addons/grass7/vector/v.nnstat

[svn_grass at osgeo.org]

Author: martinl
Date: 2014-12-05 06:48:35 -0800 (Fri, 05 Dec 2014)
New Revision: 63376

Modified:
   grass-addons/grass7/vector/v.nnstat/v.nnstat.html
Log:
v.nnstat: fix compilation issue

Modified: grass-addons/grass7/vector/v.nnstat/v.nnstat.html
===================================================================
--- grass-addons/grass7/vector/v.nnstat/v.nnstat.html	2014-12-05 14:38:18 UTC (rev 63375)
+++ grass-addons/grass7/vector/v.nnstat/v.nnstat.html	2014-12-05 14:48:35 UTC (rev 63376)
@@ -1,4 +1,3 @@
-<<<<<<< .mine
 <h2>DESCRIPTION</h2>
 
 <em>v.nnstat</em> indicates clusters, separations or random distribution of point dataset in 2D or 3D space using Nearest Neighbour Analysis (NNA). The method is based on comparison of observed average distance between the nearest neighbours and the distance which would be expected if points in the dataset are distributed randomly. More detailed information about theoretical background is provided in (<a href="https://courses.washington.edu/bio480/Week1-PAPER-Clark_and_Evans1954.pdf">Clark and Evans, 1954</a>), (<a href="http://journals.aps.org/rmp/pdf/10.1103/RevModPhys.15.1">Chandrasekhar, 1943, p. 86-87</a>). Details about the module and testing are summarized in (<a href="http://geoinformatics.fsv.cvut.cz/pdf/geoinformatics-fce-ctu-2013-11.pdf">Stopkova, 2013</a>).
@@ -48,28 +47,9 @@
 <img src="images/rand_2000_2_5D.png" border=0><br>
 <i>3D NNA using 2D vector layer and elevation values obtained from attribute table of the layer</i>
 </div>
-=======
->>>>>>> .r62696
 
-<<<<<<< .mine
 <li> <b>Warning</b>: If flag <i>-2</i> is set up together with <i>zcolumn</i>, the flag will have higher priority and 2D NNA will be performed.
 </ul>
-=======
-<em>v.nnstat</em> indicates clusters, separations or random
-distribution of point dataset in 2D or 3D space using Nearest
-Neighbour Analysis. The method is based on comparison of observed
-average distance between the nearest neighbours and the distance which
-would be expected if points in the dataset are distributed
-randomly. More detailed information about theoretical background is
-provided in
-(<a href="https://courses.washington.edu/bio480/Week1-PAPER-Clark_and_Evans1954.pdf">Clark
-and Evans, 1954</a>),
-(<a href="http://journals.aps.org/rmp/pdf/10.1103/RevModPhys.15.1">Chandrasekhar,
-1943, p. 86-87</a>). Details about the module and testing are
-summarized in
-(<a href="http://geoinformatics.fsv.cvut.cz/pdf/geoinformatics-fce-ctu-2013-11.pdf">Stopkova,
-2013</a>).
->>>>>>> .r62696
 
 <h3>Comparison of various datasets</h3>
 <p>
@@ -96,9 +76,7 @@
 volume (Minimum Bounding Rectangle area) are based on functions for
 computing convex hull from the module <i>v.hull</i> (Aime, A.,
 Neteler, M., Ducke, B., Landa, M.)
-<<<<<<< .mine
-=======
 
 <p>
 <i>Last changed: $Date$</i>
->>>>>>> .r62696
+