[pktools] 353/375: worked on descriptions in documentation
Bas Couwenberg
sebastic at xs4all.nl
Wed Dec 3 21:54:29 UTC 2014
This is an automated email from the git hooks/post-receive script.
sebastic-guest pushed a commit to branch upstream-master
in repository pktools.
commit e97c508524ed21e0667582fb2c588dcd86d44893
Author: Pieter Kempeneers <kempenep at gmail.com>
Date: Fri Nov 14 18:02:41 2014 +0100
worked on descriptions in documentation
---
doc/description_pkann.dox | 16 ++++++++++++++++
doc/description_pkascii2img.dox | 14 ++++++++++++++
doc/description_pkascii2ogr.dox | 14 ++++++++++++++
doc/description_pkcreatect.dox | 15 +++++++++++++++
doc/description_pkdsm2shadow.dox | 15 +++++++++++++++
doc/description_pksvm.dox | 2 +-
src/apps/pkann.cc | 2 +-
src/apps/pkascii2ogr.cc | 2 --
src/apps/pkfilterascii.cc | 2 +-
src/apps/pksvm.cc | 2 +-
10 files changed, 78 insertions(+), 6 deletions(-)
diff --git a/doc/description_pkann.dox b/doc/description_pkann.dox
index e69de29..4727397 100644
--- a/doc/description_pkann.dox
+++ b/doc/description_pkann.dox
@@ -0,0 +1,16 @@
+## SYNOPSIS
+
+<code>
+ 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]
+
+ Advanced options:
+ [-b band] [-bs band] [-be 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]
+</code>
+
+\section pkann_description Description
+
+The utility pkann implements an artificial neural network (ANN) to solve a supervised classification problem. The implementation is based on the open source C++ library <a href="http://leenissen.dk/fann/wp/">fann</a>). Both raster and vector files are supported as input. The output will contain the classification result, either in raster or vector format, corresponding to the format of the input. A training sample must be provided as an OGR vector dataset that contains the class labels a [...]
+
diff --git a/doc/description_pkascii2img.dox b/doc/description_pkascii2img.dox
index e69de29..33c7e4f 100644
--- a/doc/description_pkascii2img.dox
+++ b/doc/description_pkascii2img.dox
@@ -0,0 +1,14 @@
+## SYNOPSIS
+
+<code>
+ Usage: pkascii2img -i input.txt -o output
+
+
+ Options: [-ot type] [-of GDALformat] [-co NAME=VALUE]* [-dx value] [-dy value] [-ulx value] [-uly value] [-ct filename] [-a_srs EPSG:number] [-d description]
+
+</code>
+
+\section pkascii2img_description Description
+
+The utility pkascii2img creates a raster dataset from an ASCII textfile. The textfile is in matrix format (rows and columns). The dimensions in x and y are defined by the number of columns and rows respectively. The georeferencing can be defined by providing the options for cell size (-dx -dy), upper left position (-ulx -uly) and the projection (-a_srs). Some dataset formats can also store a description (-d) and a color table (-ct).
+
diff --git a/doc/description_pkascii2ogr.dox b/doc/description_pkascii2ogr.dox
index e69de29..5073875 100644
--- a/doc/description_pkascii2ogr.dox
+++ b/doc/description_pkascii2ogr.dox
@@ -0,0 +1,14 @@
+## SYNOPSIS
+
+<code>
+ Usage: pkascii2ogr -i input.txt -o output
+
+
+ Options: [-f OGRformat] [-x col] [-y col] [--line] [-n fieldname -ot type]* [-fs separator]
+
+</code>
+
+\section pkascii2ogr_description Description
+
+Poor man's utility to create a vector dataset (points or single polygon) from an ASCII textfile. A better alternative is to use <a href="http://www.gdal.org/drv_vrt.html">virtual vector datasets</a>. Specify the position of the vertices (x and y) in the columns defined by the options (-x -y), starting from 0. The default is to use the first (-dx 0) and second (-dx 1) columns for x and y respectvely. Specify the names and types of the remaining columns in your input file via the option pa [...]
+
diff --git a/doc/description_pkcreatect.dox b/doc/description_pkcreatect.dox
index e69de29..25880d2 100644
--- a/doc/description_pkcreatect.dox
+++ b/doc/description_pkcreatect.dox
@@ -0,0 +1,15 @@
+## SYNOPSIS
+
+<code>
+ Usage: pkcreatect -i input.txt -o output [-ct colortable | -min value -max value]
+
+
+ Options: [--grey] [-of GDALformat] [-co option]* [-d description]
+
+ Advanced options: [--legend filename [--dim cols --dim rows]]
+</code>
+
+\section pkascii2ogr_description Description
+
+Utility to include a color table to a raster dataset. You can either define an existing color table (ASCII text file) with the option -ct or define a minimum (-min) and maximum (-max) value.
+
diff --git a/doc/description_pkdsm2shadow.dox b/doc/description_pkdsm2shadow.dox
index e69de29..3b94967 100644
--- a/doc/description_pkdsm2shadow.dox
+++ b/doc/description_pkdsm2shadow.dox
@@ -0,0 +1,15 @@
+## SYNOPSIS
+
+<code>
+ Usage: pkdsm2shadow -i input.txt -o output [-sza angle] [-saa angle]
+
+
+ Options: [-f value] [-ot type] [-of GDALformat] [-ct filename] [-co option]*
+
+ Advanced options: [--scale value] [--offset value]
+</code>
+
+\section pkdsm2shadow_description Description
+
+Utility to create a binary shadow mask from a digital surface model, based on Sun zenith (-sza) and azimuth angles (-saa).
+
diff --git a/doc/description_pksvm.dox b/doc/description_pksvm.dox
index 9fca90b..e4d0ddd 100644
--- a/doc/description_pksvm.dox
+++ b/doc/description_pksvm.dox
@@ -6,7 +6,7 @@
Options: [-tln layer]* [-c name -r value]* [-of GDALformat|-f OGRformat] [-co NAME=VALUE]* [-ct filename] [-label attribute] [-prior value]* [-g gamma] [-cc cost] [-m filename [-msknodata value]*] [-nodata value]
Advanced options:
- [-b band] [-bs band] [-be band] [-balance size]* [-min] [-bag value] [-bs value] [-comb rule] [-cb filename] [-prob filename] [-pim priorimage] [--offset value] [--scale value] [-svmt type] [-kt type] [-kd value] [-c0 value] [-nu value] [-eloss value] [-cache value] [-etol value] [-shrink]
+ [-b band] [-bs band] [-be band] [-bal size]* [-min] [-bag value] [-bs value] [-comb rule] [-cb filename] [-prob filename] [-pim priorimage] [--offset value] [--scale value] [-svmt type] [-kt type] [-kd value] [-c0 value] [-nu value] [-eloss value] [-cache value] [-etol value] [-shrink]
</code>
\section pksvm_description Description
diff --git a/src/apps/pkann.cc b/src/apps/pkann.cc
index 64c34e4..b173597 100644
--- a/src/apps/pkann.cc
+++ b/src/apps/pkann.cc
@@ -51,7 +51,7 @@ int main(int argc, char *argv[])
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> aggreg_opt("a", "aggreg", "how to combine aggregated classifiers, see also rc option (1: sum rule, 2: max rule).",1);
- Optionpk<double> priors_opt("p", "prior", "prior probabilities for each class (e.g., -p 0.3 -p 0.3 -p 0.2 )", 0.0);
+ 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);
diff --git a/src/apps/pkascii2ogr.cc b/src/apps/pkascii2ogr.cc
index 47989b3..ddc648b 100644
--- a/src/apps/pkascii2ogr.cc
+++ b/src/apps/pkascii2ogr.cc
@@ -35,7 +35,6 @@ int main(int argc, char *argv[])
Optionpk<bool> polygon_opt("l", "line", "create OGRPolygon as geometry instead of points. Fields are taken from first point and polygon is automatically closed (no need to repeat first point at last line). (false: use OGRPoint)", false);
Optionpk<string> fname_opt("n", "name", "Field names for the columns in the input ascii file");
Optionpk<string> ftype_opt("ot", "ot", "Field type (Real, Integer, String) for each of the fields as defined by name","Real");
- Optionpk<string> itype_opt("of", "of", "image type string", "ESRI Shapefile");
Optionpk<string> projection_opt("a_srs", "a_srs", "Override the projection for the output file, use epsg:<code> or Wkt string", "epsg:4326");
Optionpk<char> fs_opt("fs","fs","field separator.",' ');
Optionpk<int> verbose_opt("v", "verbose", "verbose (0)", 0);
@@ -50,7 +49,6 @@ int main(int argc, char *argv[])
polygon_opt.retrieveOption(argc,argv);
fname_opt.retrieveOption(argc,argv);
ftype_opt.retrieveOption(argc,argv);
- itype_opt.retrieveOption(argc,argv);
projection_opt.retrieveOption(argc,argv);
fs_opt.retrieveOption(argc,argv);
verbose_opt.retrieveOption(argc,argv);
diff --git a/src/apps/pkfilterascii.cc b/src/apps/pkfilterascii.cc
index f6922a7..7e43e55 100644
--- a/src/apps/pkfilterascii.cc
+++ b/src/apps/pkfilterascii.cc
@@ -1,5 +1,5 @@
/**********************************************************************
-pkfilterascii.cc: program to filter data in ASCII file (spectral respons function, dwt)
+pkfilterascii.cc: program to filter data in an ASCII file
Copyright (C) 2008-2014 Pieter Kempeneers
This file is part of pktools
diff --git a/src/apps/pksvm.cc b/src/apps/pksvm.cc
index d5532f6..e441f96 100644
--- a/src/apps/pksvm.cc
+++ b/src/apps/pksvm.cc
@@ -60,7 +60,7 @@ int main(int argc, char *argv[])
Optionpk<double> bend_opt("be", "bend", "End band sequence number (set to 0 to include all bands)", 0);
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<double> priors_opt("p", "prior", "Prior probabilities for each class (e.g., -p 0.3 -p 0.3 -p 0.2 ). Used for input only (ignored for cross validation)", 0.0);
+ Optionpk<double> priors_opt("prior", "prior", "Prior probabilities for each class (e.g., -p 0.3 -p 0.3 -p 0.2 ). Used for input only (ignored for cross validation)", 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<std::string> svm_type_opt("svmt", "svmtype", "Type of SVM (C_SVC, nu_SVC,one_class, epsilon_SVR, nu_SVR)","C_SVC");
--
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