v.univar: messages improved; manual: notes added and example updated to NC

git-svn-id: https://svn.osgeo.org/grass/grass/branches/releasebranch_7_0@63383 15284696-431f-4ddb-bdfa-cd5b030d7da7

vector/v.univar/main.c

@@ -9,7 +9,7 @@
  *               
  * PURPOSE:      Univariate Statistics for attribute
  *               
- * COPYRIGHT:    (C) 2004-2010 by the GRASS Development Team
+ * COPYRIGHT:    (C) 2004-2014 by the GRASS Development Team
  *
  *               This program is free software under the GNU General
  *               Public License (>=v2).  Read the file COPYING that
@@ -92,6 +92,8 @@ int main(int argc, char *argv[])
     G_add_keyword(_("vector"));
     G_add_keyword(_("statistics"));
     G_add_keyword(_("univariate statistics"));
+    G_add_keyword(_("attribute table"));
+    G_add_keyword(_("geometry"));
     module->label =
 	_("Calculates univariate statistics for attribute.");
     module->description = _("Variance and standard "
@@ -133,7 +135,7 @@ int main(int argc, char *argv[])
 
     geometry = G_define_flag();
     geometry->key = 'd';
-    geometry->description = _("Calculate geometry distances instead of table data");
+    geometry->description = _("Calculate geometric distances instead of attribute statistics");
 
     G_gisinit(argv[0]);
 
@@ -246,10 +248,12 @@ static void select_from_geometry(void)
     count = 0;
 
     nlines = Vect_get_num_lines(&Map);
+    G_message(_("Calculating geometric distances between %d primitives..."), nlines);
     /* Start calculating the statistics based on distance to all other primitives.
        Use the centroid of areas and the first point of lines */
     for (i = 1; i <= nlines; i++) {
 
+	G_percent(i, nlines, 2);
 	type = Vect_read_line(&Map, iPoints, Cats, i);
 
 	if (!(type & otype))
@@ -348,7 +352,7 @@ static void select_from_database(void)
     nrec =
 	db_select_CatValArray(Driver, Fi->table, Fi->key, col_opt->answer,
 			      where_opt->answer, &Cvarr);
-    G_debug(2, "nrec = %d", nrec);
+    G_debug(2, "db_select_CatValArray() nrec = %d", nrec);
 
     ctype = Cvarr.ctype;
     if (ctype != DB_C_TYPE_INT && ctype != DB_C_TYPE_DOUBLE)
@@ -366,18 +370,20 @@ static void select_from_database(void)
     if ((otype & GV_POINTS) || (otype & GV_LINES))
 	nlines = Vect_get_num_lines(&Map);
 
+    G_debug(1, "select_from_database: %d points", nlines);
     for (line = 1; line <= nlines; line++) {
 	int i, type;
 
 	G_debug(3, "line = %d", line);
 
+	G_percent(line, nlines, 2);
 	type = Vect_read_line(&Map, Points, Cats, line);
 	if (!(type & otype))
 	    continue;
 
 	for (i = 0; i < Cats->n_cats; i++) {
 	    if (Cats->field[i] == ofield) {
-		double val;
+		double val = 0.0;
 		dbCatVal *catval;
 
 		G_debug(3, "cat = %d", Cats->cat[i]);
@@ -459,7 +465,7 @@ static void select_from_database(void)
 
 	    for (i = 0; i < Cats->n_cats; i++) {
 		if (Cats->field[i] == ofield) {
-		    double val;
+		    double val = 0.0;
 		    dbCatVal *catval;
 
 		    G_debug(3, "cat = %d", Cats->cat[i]);

vector/v.univar/v.univar.html

@@ -7,18 +7,39 @@ Variance and standard deviation is calculated only for points if
 <tt>type=point</tt> is defined.
 
 <p>Extended statistics adds median, 1st and 3rd quartiles, and 90th
-percentile.
+percentile to the output.
+
+<h2>NOTES</h2>
+
+When using the <em>-d</em> flag, univariate statistics of vector
+geometry are calculated. Depending on the selected vector <em>type</em>,
+distances are calculated as follows:
+
+<ul>
+<li> <em>type=point</em>: point distances are considered;</li>
+<li> <em>type=line</em>: the first point of each line is considered;</li>
+<li> <em>type=area</em>: the centroid of each area is considered.</li>
+</ul>
 
 <h2>EXAMPLE</h2>
 
+The example is based on the North Carolina sample dataset:
+
 <div class="code"><pre>
-g.region rast=elevation.10m -p
-v.random out=samples n=100
-v.db.addtable samples col="heights double precision"
-v.what.rast samples rast=elevation.10m col=heights
-v.db.select samples
+g.region rast=elevation -p
+v.random output=samples npoints=100
+v.db.addtable map=samples columns="heights double precision"
+v.what.rast map=samples rast=elevation column=heights
+v.db.select map=samples
+
+# calculate height attribute statistics:
+v.univar -e samples column=heights type=point
+
+# compare to statistics of original raster map:
+r.univar -e elevation
 
-v.univar samples col=heights type=point
+# calculate distance between sampling points statistics:
+v.univar -d samples column=heights type=point
 </pre></div>
 
 
@@ -30,8 +51,12 @@ v.univar samples col=heights type=point
 </em>
 
 
-<h2>AUTHOR</h2>
+<h2>AUTHORS</h2>
 
 Radim Blazek, ITC-irst
+<p>
+extended by:<br>
+Hamish Bowman, University of Otago, New Zealand<br>
+Martin Landa 
 
 <p><i>Last changed: $Date$</i>