[pktools] 363/375: completed descriptions
Bas Couwenberg
sebastic at xs4all.nl
Wed Dec 3 21:54:30 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 f11cf50e912f46dc470504fd5663969f79828e88
Author: Pieter Kempeneers <kempenep at 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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