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commit f11cf50e912f46dc470504fd5663969f79828e88
Author: Pieter Kempeneers <kempe...@gmail.com>
Date:   Sun Nov 23 16:35:08 2014 +0100

    completed descriptions
---
 doc/description_pkann.dox        |  2 +-
 doc/description_pkfilterdem.dox  | 14 ++++++++++++++
 doc/description_pkgetmask.dox    |  2 +-
 doc/description_pklas2img.dox    | 14 ++++++++++++++
 doc/description_pkpolygonize.dox | 12 ++++++++++++
 doc/description_pkregann.dox     | 13 +++++++++++++
 doc/description_pksetmask.dox    | 14 ++++++++++++++
 doc/description_pksieve.dox      | 12 ++++++++++++
 doc/description_pkstatascii.dox  | 14 ++++++++++++++
 src/apps/pkann.cc                |  2 +-
 src/apps/pkfilterdem.cc          |  4 ++--
 src/apps/pkpolygonize.cc         |  2 +-
 src/apps/pkregann.cc             |  8 +++-----
 src/apps/pkstatascii.cc          |  2 +-
 14 files changed, 103 insertions(+), 12 deletions(-)

diff --git a/doc/description_pkann.dox b/doc/description_pkann.dox
index 29acd4d..068b0b2 100644
--- a/doc/description_pkann.dox
+++ b/doc/description_pkann.dox
@@ -4,7 +4,7 @@
   Usage: pkann -t training [-i input -o output] [-cv value]
 
   
-  Options: [-tln layer]* [-c name -r value]* [-of GDALformat|-f OGRformat] 
[-co NAME=VALUE]* [-ct filename] [-label attribute] [-prior value]* [--nn 
number]* [-m filename [-msknodata value]*] [-nodata value]
+  Options: [-tln layer]* [-c name -r value]* [-of GDALformat|-f OGRformat] 
[-co NAME=VALUE]* [-ct filename] [-label attribute] [-prior value]* [-nn 
number]* [-m filename [-msknodata value]*] [-nodata value]
 
   Advanced options:
        [-b band] [-s band] [-e band] [-bal size]* [-min] [-bag value] [-bs 
value] [-comb rule] [-cb filename] [-prob filename] [-pim priorimage] [--offset 
value] [--scale value] [--connection 0|1] [-w weights]* [--learning rate] 
[--maxit number] 
diff --git a/doc/description_pkfilterdem.dox b/doc/description_pkfilterdem.dox
index e69de29..f651206 100644
--- a/doc/description_pkfilterdem.dox
+++ b/doc/description_pkfilterdem.dox
@@ -0,0 +1,14 @@
+## SYNOPSIS
+
+<code>
+  Usage: pkfilterdem -i input.txt -o output 
+  
+  Options: [-f filter] [-dim maxsize] [-ot type] [-of format] [-ct colortable] 
[-nodata value] 
+
+  Advanced options: [-circ] [-st threshold] [-ht threshold] [-minchange value]
+
+</code>
+
+\section pkfilterdem_description Description
+
+The utility pkfilterdem can be used to filter digital elevation models. It is 
typically used after the utility \ref pklas2img "pklas2img" to create a digital 
terrain model. The default filter operation is the <a 
href="http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=1202973&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D1202973";>progressive
 morphological filter</a>. 
diff --git a/doc/description_pkgetmask.dox b/doc/description_pkgetmask.dox
index 8545483..c66fbd4 100644
--- a/doc/description_pkgetmask.dox
+++ b/doc/description_pkgetmask.dox
@@ -5,7 +5,7 @@
   
   Options: [-min value]* [-max value]* [-data value]* [-nodata value]*
  
-  Advanced options: [-b band]* [-operator AND|OR] [-ot type] [-of format] [-co 
option]* [-ct table] 
+  Advanced options: [-b band]* [--operator AND|OR] [-ot type] [-of format] 
[-co option]* [-ct table] 
 
 </code>
 
diff --git a/doc/description_pklas2img.dox b/doc/description_pklas2img.dox
index e69de29..0a117b9 100644
--- a/doc/description_pklas2img.dox
+++ b/doc/description_pklas2img.dox
@@ -0,0 +1,14 @@
+## SYNOPSIS
+
+<code>
+  Usage: pklas2img -i lasfile -o output 
+  
+  Options: [-n attribute] [-comp method] [-fir type] [-a_srs] [-ulx value -uly 
value -lrx value -lry value] [-dx value -dy value] [-ot type] [-of format] 
[-ret value]* [-class number]* 
+
+  Advanced options: [-nbin value] [-nodata value] [-co option]* [-ct 
colortable] 
+
+</code>
+
+\section pklas2img_description Description
+
+The utility pklas2img converts a las/laz point cloud into a gridded raster 
dataset. The implementation is based on <a href="www.liblas.org">liblas</a> 
API. You can define the bounding box, grid cell size and spatial reference set. 
The composite rule for multiple returns within a single grid cell can be set 
with the option -comp. The default attribute is z (heiht), but can also be 
intensity (if available), the return number (-n return) or the total number of 
returns in that grid cell (-n  [...]
diff --git a/doc/description_pkpolygonize.dox b/doc/description_pkpolygonize.dox
index e69de29..5d6c62a 100644
--- a/doc/description_pkpolygonize.dox
+++ b/doc/description_pkpolygonize.dox
@@ -0,0 +1,12 @@
+## SYNOPSIS
+
+<code>
+  Usage: pkpolygonize -i input [-m mask] -o output 
+  
+  Options: [-f format] [-b band] [-n fieldname] [-nodata value]
+
+</code>
+
+\section pkpolygonize_description Description
+
+The utility pkpolygonize converts a raster to a vector dataset. All pixels in 
the mask band with a value other than zero will be considered suitable for 
collection as polygons. Use the same input file as mask to remove the 
background polygon (recommended).
diff --git a/doc/description_pkregann.dox b/doc/description_pkregann.dox
index e69de29..517f329 100644
--- a/doc/description_pkregann.dox
+++ b/doc/description_pkregann.dox
@@ -0,0 +1,13 @@
+## SYNOPSIS
+
+<code>
+  Usage: pkregann -i input -t training [-ic col]* [-oc col]* -o output 
+  
+  Options: [-from row] [-to row] [-cv size] [-nn number]
+
+  Advanced options: [--offset value] [--scale value] [--connection rate] 
[--learning rate] [--maxit number]
+</code>
+
+\section pkregann_description Description
+
+The utility pkregann performs a regression based on an artificial neural 
network. The regression is trained from the input (-ic) and output (-oc) 
columns in a training text file. Each row in the training file represents one 
sampling unit. Multi-dimensional input features can be defined with multiple 
input options (e.g., -ic 0 -ic 1 -ic 2 for three dimensional features).
diff --git a/doc/description_pksetmask.dox b/doc/description_pksetmask.dox
index e69de29..6670fc0 100644
--- a/doc/description_pksetmask.dox
+++ b/doc/description_pksetmask.dox
@@ -0,0 +1,14 @@
+## SYNOPSIS
+
+<code>
+  Usage: pksetmask -i input -m mask [-msknodata value] -o output
+  
+  Options: [-min value]* [-max value]* [-data value]* [-nodata value]*
+ 
+  Advanced options: [-b band]* [--operator '<'|'='|'<'] [-ot type] [-of 
format] [-co option]* [-ct table] 
+
+</code>
+
+\section pksetmask_description Description
+
+The utility pksetmask sets a mask provided with option -m to an input raster 
dataset. The default operator is '='. Values in the input raster data where the 
mask has a nodata value (set with the option -msknodata) will then be set to 
nodata (set with -nodata). Other operators are less than (--operator '<') and 
larger than (--operator '>').
\ No newline at end of file
diff --git a/doc/description_pksieve.dox b/doc/description_pksieve.dox
index e69de29..659b67d 100644
--- a/doc/description_pksieve.dox
+++ b/doc/description_pksieve.dox
@@ -0,0 +1,12 @@
+## SYNOPSIS
+
+<code>
+  Usage: pksieve -i input [-s size] -o output
+  
+  Options: [-c 4|8] [-b band] [-m mask] [-ot type] [-of format] [-co option]* 
[-ct table] 
+
+</code>
+
+\section pksieve_description Description
+
+The utility pksieve filters small objects (maximum size defined with the 
option -s) in a raster by replacing them to the largest neighbor object. In 
this context, objects are defined as pixels of the same value that are also 
connected. The connection can be defined in four directions (N-S and W-E: set 
option -c 4) or eight directions (N-S, W-E and diagonals NW-SE, NE-SW: set 
option -c 8).
\ No newline at end of file
diff --git a/doc/description_pkstatascii.dox b/doc/description_pkstatascii.dox
index e69de29..95481c4 100644
--- a/doc/description_pkstatascii.dox
+++ b/doc/description_pkstatascii.dox
@@ -0,0 +1,14 @@
+## SYNOPSIS
+
+<code>
+  Usage: pkstatascii -i input [-c column]*
+  
+  Options: [-size] [-rnd number [-dist function] [-rnda value -rndb value]] 
[-mean] [-median] [-var] [-skew] [-stdev] [-sum] [-mm] [-min] [-max] [-hist 
[-nbin value] [-rel] [-kde]] [-hist2d [-nbin value] [-rel] [-kde]] [-cor] 
[-rmse] [-reg] [-regerr]
+
+  Advanced options: [-srcmin value] [-srcmax value] [-fs separator] [-r 
startrow [-r endrow]] [-o [-t]] [--comment character]
+
+</code>
+
+\section pkstatascii_description Description
+
+The utility pkstatascii calculates basic statistics of a data series in a text 
file.
\ No newline at end of file
diff --git a/src/apps/pkann.cc b/src/apps/pkann.cc
index d20271b..8148c45 100644
--- a/src/apps/pkann.cc
+++ b/src/apps/pkann.cc
@@ -54,7 +54,7 @@ int main(int argc, char *argv[])
   Optionpk<double> priors_opt("prior", "prior", "prior probabilities for each 
class (e.g., -p 0.3 -p 0.3 -p 0.2 )", 0.0); 
   Optionpk<string> priorimg_opt("pim", "priorimg", "prior probability image 
(multi-band img with band for each class","",2); 
   Optionpk<unsigned short> cv_opt("cv", "cv", "n-fold cross validation 
mode",0);
-  Optionpk<unsigned int> nneuron_opt("n", "nneuron", "number of neurons in 
hidden layers in neural network (multiple hidden layers are set by defining 
multiple number of neurons: -n 15 -n 1, default is one hidden layer with 5 
neurons)", 5); 
+  Optionpk<unsigned int> nneuron_opt("nn", "nneuron", "number of neurons in 
hidden layers in neural network (multiple hidden layers are set by defining 
multiple number of neurons: -n 15 -n 1, default is one hidden layer with 5 
neurons)", 5); 
   Optionpk<float> connection_opt("\0", "connection", "connection reate 
(default: 1.0 for a fully connected network)", 1.0); 
   Optionpk<float> weights_opt("w", "weights", "weights for neural network. 
Apply to fully connected network only, starting from first input neuron to last 
output neuron, including the bias neurons (last neuron in each but last 
layer)", 0.0); 
   Optionpk<float> learning_opt("l", "learning", "learning rate (default: 
0.7)", 0.7); 
diff --git a/src/apps/pkfilterdem.cc b/src/apps/pkfilterdem.cc
index da040a5..c2448dd 100644
--- a/src/apps/pkfilterdem.cc
+++ b/src/apps/pkfilterdem.cc
@@ -36,7 +36,7 @@ int main(int argc,char **argv) {
   Optionpk<std::string> tmpdir_opt("tmp", "tmp", "Temporary 
directory","/tmp",2);
   Optionpk<bool> disc_opt("circ", "circular", "circular disc kernel for 
dilation and erosion", false);
   Optionpk<string> postFilter_opt("f", "filter", "post processing filter: 
vito, etew_min, promorph (progressive morphological filter),open,close).");
-  Optionpk<double> dim_opt("dim", "dim", "maximum filter kernel size 
(optionally you can set both initial and maximum filter kernel size", 3);
+  Optionpk<double> dim_opt("dim", "dim", "maximum filter kernel size", 17);
   Optionpk<double> maxSlope_opt("st", "st", "slope threshold used for 
morphological filtering. Use a low values to remove more height objects in flat 
terrains", 0.0);
   Optionpk<double> hThreshold_opt("ht", "ht", "initial height threshold for 
progressive morphological filtering. Use low values to remove more height 
objects. Optionally, a maximum height threshold can be set via a second 
argument (e.g., -ht 0.2 -ht 2.5 sets an initial threshold at 0.2 m and caps the 
threshold at 2.5 m).", 0.2);
   Optionpk<short> minChange_opt("minchange", "minchange", "Stop iterations 
when no more pixels are changed than this threshold.", 0);
@@ -44,7 +44,7 @@ int main(int argc,char **argv) {
   Optionpk<string>  oformat_opt("of", "oformat", "Output image format (see 
also gdal_translate). Empty string: inherit from input image");
   Optionpk<string>  colorTable_opt("ct", "ct", "color table (file with 5 
columns: id R G B ALFA (0: transparent, 255: solid). Use none to ommit color 
table");
   Optionpk<string> option_opt("co", "co", "Creation option for output file. 
Multiple options can be specified.");
-  Optionpk<short> nodata_opt("nodata", "nodata", "nodata value(s) for 
smoothnodata filter");
+  Optionpk<short> nodata_opt("nodata", "nodata", "nodata value");
   Optionpk<short> verbose_opt("v", "verbose", "verbose mode if > 0", 0);
 
   bool doProcess;//stop process when program was invoked with help option (-h 
--help)
diff --git a/src/apps/pkpolygonize.cc b/src/apps/pkpolygonize.cc
index ef2e85b..99fb6aa 100644
--- a/src/apps/pkpolygonize.cc
+++ b/src/apps/pkpolygonize.cc
@@ -41,7 +41,7 @@ int main(int argc,char **argv) {
   Optionpk<string> mask_opt("m", "mask", "All pixels in the mask band with a 
value other than zero will be considered suitable for collection as polygons. 
Use input file as mask to remove background polygon! ");
   Optionpk<double> nodata_opt("nodata", "nodata", "Disgard this nodata value 
when creating polygons.");
   Optionpk<string> output_opt("o", "output", "Output vector file");
-  Optionpk<string> ogrformat_opt("f", "f", "Output OGR file format","ESRI 
Shapefile");
+  Optionpk<string> ogrformat_opt("f", "f", "Output OGR file format","SQLite");
   Optionpk<int> band_opt("b", "band", "the band to be used from input file", 
0);
   Optionpk<string> fname_opt("n", "name", "the field name of the output 
layer", "DN");
   Optionpk<short> verbose_opt("v", "verbose", "verbose mode if > 0", 0);
diff --git a/src/apps/pkregann.cc b/src/apps/pkregann.cc
index cd4ebae..96a6d40 100644
--- a/src/apps/pkregann.cc
+++ b/src/apps/pkregann.cc
@@ -35,13 +35,12 @@ int main(int argc, char *argv[])
   Optionpk<string> training_opt("t", "training", "training ASCII file (each 
row represents one sampling unit. Input features should be provided as columns, 
followed by output)"); 
   Optionpk<double> from_opt("from", "from", "start from this row in training 
file (start from 0)",0); 
   Optionpk<double> to_opt("to", "to", "read until this row in training file 
(start from 0 or set leave 0 as default to read until end of file)", 0); 
-  Optionpk<short> band_opt("b", "band", "band index (starting from 0, either 
use band option or use start to end)");
   Optionpk<double> offset_opt("\0", "offset", "offset value for each spectral 
band input features: refl[band]=(DN[band]-offset[band])/scale[band]", 0.0);
   Optionpk<double> scale_opt("\0", "scale", "scale value for each spectral 
band input features: refl=(DN[band]-offset[band])/scale[band] (use 0 if scale 
min and max in each band to -1.0 and 1.0)", 0.0);
   Optionpk<unsigned short> cv_opt("cv", "cv", "n-fold cross validation 
mode",0);
-  Optionpk<unsigned int> nneuron_opt("\0", "nneuron", "number of neurons in 
hidden layers in neural network (multiple hidden layers are set by defining 
multiple number of neurons: -n 15 -n 1, default is one hidden layer with 5 
neurons)", 5); 
+  Optionpk<unsigned int> nneuron_opt("nn", "nneuron", "number of neurons in 
hidden layers in neural network (multiple hidden layers are set by defining 
multiple number of neurons: -n 15 -n 1, default is one hidden layer with 5 
neurons)", 5); 
   Optionpk<float> connection_opt("\0", "connection", "connection reate 
(default: 1.0 for a fully connected network)", 1.0); 
-  Optionpk<float> weights_opt("w", "weights", "weights for neural network. 
Apply to fully connected network only, starting from first input neuron to last 
output neuron, including the bias neurons (last neuron in each but last 
layer)", 0.0); 
+  // Optionpk<float> weights_opt("w", "weights", "weights for neural network. 
Apply to fully connected network only, starting from first input neuron to last 
output neuron, including the bias neurons (last neuron in each but last 
layer)", 0.0); 
   Optionpk<float> learning_opt("l", "learning", "learning rate (default: 
0.7)", 0.7); 
   Optionpk<unsigned int> maxit_opt("\0", "maxit", "number of maximum 
iterations (epoch) (default: 500)", 500); 
   Optionpk<short> verbose_opt("v", "verbose", "set to: 0 (results only), 1 
(confusion matrix), 2 (debug)",0);
@@ -55,13 +54,12 @@ int main(int argc, char *argv[])
     training_opt.retrieveOption(argc,argv);
     from_opt.retrieveOption(argc,argv);
     to_opt.retrieveOption(argc,argv);
-    band_opt.retrieveOption(argc,argv);
     offset_opt.retrieveOption(argc,argv);
     scale_opt.retrieveOption(argc,argv);
     cv_opt.retrieveOption(argc,argv);
     nneuron_opt.retrieveOption(argc,argv);
     connection_opt.retrieveOption(argc,argv);
-    weights_opt.retrieveOption(argc,argv);
+    // weights_opt.retrieveOption(argc,argv);
     learning_opt.retrieveOption(argc,argv);
     maxit_opt.retrieveOption(argc,argv);
     verbose_opt.retrieveOption(argc,argv);
diff --git a/src/apps/pkstatascii.cc b/src/apps/pkstatascii.cc
index fe3b842..1c38460 100644
--- a/src/apps/pkstatascii.cc
+++ b/src/apps/pkstatascii.cc
@@ -1,5 +1,5 @@
 /**********************************************************************
-pkstatascii.cc: program to calculate basic statistics from raster image
+pkstatascii.cc: program to calculate basic statistics from text file
 Copyright (C) 2008-2014 Pieter Kempeneers
 
 This file is part of pktools

-- 
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/srv/git.debian.org/git/pkg-grass/pktools.git

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