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commit 2861fdc36c8faef9c4cb1d1e25783169986b052d
Author: Pieter Kempeneers <>
Date:   Mon Mar 31 14:19:59 2014 +0200

    added dox for pkcomposite and pksvm
 doc/examples_pkcomposite.dox                    | 26 +++++++++++++++++++++++++
 doc/examples_pksvm.dox                          | 16 +++++++++++++++
 doc/{faq_pkcomposit.dox => faq_pkcomposite.dox} |  0
 3 files changed, 42 insertions(+)

diff --git a/doc/examples_pkcomposite.dox b/doc/examples_pkcomposite.dox
new file mode 100644
index 0000000..cc77223
--- /dev/null
+++ b/doc/examples_pkcomposite.dox
@@ -0,0 +1,26 @@
+\section examples_pkcomposit Examples of pkcomposit
+pkcomposit -i input1.tif -i input2.tif -o output.tif
+create composit from two input images. If images overlap, keep only last image 
(default rule)
+pkcomposit -i input1.tif -i input2.tif -srcnodata 255 -bndnodata 1 -dstnodata 
0 -o output.tif 
+create composit from two input images. Values of 255 in band 1 (starting from 
0) are masked as invalid. Typically used when second band of input image is a 
cloud mask
+pkcomposit -i input1.tif -i input2.tif -cr maxndvi -rb 0 -rb 1 -srcnodata 255 
-bndnodata 0 -dstnodata 0 -o output.tif
+create maximum NDVI (normalized difference vegetation index) composit. Values 
of 255 in band 0 are masked as invalid and flagged as 0 if no other valid 
coverage. Typically used for (e.g., MODIS) images where red and near infrared 
spectral bands are stored in bands 0 and 1 respectively. In this particular 
case, a value of 255 in the first input band indicates a nodata value (e.g., 
cloud mask is coded within the data values).
+pkcomposit -i input1.tif -i input2.tif -i input3.tif -o output.tif -cr mean -w 
0.75 -w 1.5 -w 0.75
+create composite image using weighted mean: 
+pkcomposit -i large.tif $(for IMAGE in *.tif;do pkinfo -i $IMAGE --cover 
$(pkinfo -i coverage.tif -bb);done) -cr median -min 0 -o output.tif
+create median composit of all GTiff images found in current directory that 
cover (at least part of) the image coverage.tif. Values smaller or equal to 0 
are set as nodata 0 (default value for -dstnodata)
diff --git a/doc/examples_pksvm.dox b/doc/examples_pksvm.dox
new file mode 100644
index 0000000..3eac3ed
--- /dev/null
+++ b/doc/examples_pksvm.dox
@@ -0,0 +1,16 @@
+\section examples_pksvm Examples of pksvm
+pksvm -i input.tif -t training.shp -o output.tif -cv 2 -ct colourtable.txt -cc 
1000 -g 0.1
+Classify input image input.tif with a support vector machine. A training 
sample that is provided as a vector (shp) file. It contains all features (same 
dimensionality as input.tif) in its fields (please check \ref pkextract 
"pkextract" on how to obtain such a file from a "clean" vector file containing 
locations only). A two-fold cross validation (cv) is performed (output on 
screen). The parameters cost and gamma of the support vector machine are set to 
1000 and 0.1 respectively. A colour [...]
+pksvm -i input.tif -t training.shp -o output.tif -bs 33 -bag 3
+Classification using bootstrap aggregation. The training sample is randomly 
split in three subsamples (33% of the original sample each).
+pksvm -i input.tif -t training.shp -o output.tif -p 1 -p 1 -p 1 -p 1 -p 1 -p 1 
-p 1 -p 1 -p 1 -p 1 -p 1 -p 0.2 -p 1 -p 1 -p 1
+Classification using prior probabilities for each class. The priors are 
automatically normalized. The order in which the options -p are provide should 
respect the alphanumeric order of the class names (class 10 comes before 2...)
\ No newline at end of file
diff --git a/doc/faq_pkcomposit.dox b/doc/faq_pkcomposite.dox
similarity index 100%
rename from doc/faq_pkcomposit.dox
rename to doc/faq_pkcomposite.dox

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