[GRASS-SVN] r71094 - grass/trunk/vector/v.surf.bspline

[svn_grass at osgeo.org]

Author: mlennert
Date: 2017-05-17 06:18:18 -0700 (Wed, 17 May 2017)
New Revision: 71094

Modified:
   grass/trunk/vector/v.surf.bspline/main.c
   grass/trunk/vector/v.surf.bspline/v.surf.bspline.html
Log:
v.surf.bspline: document units used for step parameters

Modified: grass/trunk/vector/v.surf.bspline/main.c
===================================================================
--- grass/trunk/vector/v.surf.bspline/main.c	2017-05-17 13:00:51 UTC (rev 71093)
+++ grass/trunk/vector/v.surf.bspline/main.c	2017-05-17 13:18:18 UTC (rev 71094)
@@ -146,7 +146,7 @@
     stepE_opt->required = NO;
     stepE_opt->answer = "4";
     stepE_opt->description =
-	_("Length of each spline step in the east-west direction");
+	_("Length of each spline step (pixels) in the east-west direction");
     stepE_opt->guisection = _("Settings");
 
     stepN_opt = G_define_option();
@@ -155,7 +155,7 @@
     stepN_opt->required = NO;
     stepN_opt->answer = "4";
     stepN_opt->description =
-	_("Length of each spline step in the north-south direction");
+	_("Length of each spline step (pixels) in the north-south direction");
     stepN_opt->guisection = _("Settings");
 
     type_opt = G_define_option();

Modified: grass/trunk/vector/v.surf.bspline/v.surf.bspline.html
===================================================================
--- grass/trunk/vector/v.surf.bspline/v.surf.bspline.html	2017-05-17 13:00:51 UTC (rev 71093)
+++ grass/trunk/vector/v.surf.bspline/v.surf.bspline.html	2017-05-17 13:18:18 UTC (rev 71094)
@@ -19,13 +19,13 @@
 here, the splines are 2D piece-wise non-zero polynomial functions
 calculated within a limited, 2D area. The length of each spline step
 is defined by <b>ew_step</b> for the east-west direction and
-<b>ns_step</b> for the north-south direction. For optimal performance, the
-length of spline step should be no less than the distance between observation
-points. Each vector point observation is modeled as a linear function of the
-non-zero splines in the area around the observation. The least squares
-regression predicts the the coefficients of these linear functions.
-Regularization, avoids the need to have one observation and one
-coefficient for each spline (in order to avoid instability). 
+<b>ns_step</b> for the north-south direction. Step is defined in number of 
+pixels. For optimal performance, the length of spline step should be no less
+than the distance between observation points. Each vector point observation is
+modeled as a linear function of the non-zero splines in the area around the 
+observation. The least squares regression predicts the the coefficients of these
+linear functions. Regularization, avoids the need to have one observation and 
+one coefficient for each spline (in order to avoid instability). 
 
 <p>With regularly distributed data points, a spline step corresponding
 to the maximum distance between two points in both the east and north