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commit 15b59bd67ff029c6d8097467bba9448ecd5b11d7 Author: Pieter Kempeneers <kempe...@gmail.com> Date: Sun Oct 12 22:09:26 2014 +0200 replaced options start and end with bstart and bend in pksvm and pkann --- ChangeLog | 11 ++++++++++- src/apps/pkann.cc | 12 ++++++------ src/apps/pkfsann.cc | 12 ++++++------ src/apps/pkfssvm.cc | 12 ++++++------ src/apps/pkoptsvm.cc | 12 ++++++------ src/apps/pksvm.cc | 12 ++++++------ 6 files changed, 40 insertions(+), 31 deletions(-) diff --git a/ChangeLog b/ChangeLog index 7dda69c..6a522b6 100755 --- a/ChangeLog +++ b/ChangeLog @@ -317,9 +317,18 @@ version 2.5.4 support statistic rules (mean, stdev, median, etc.) for point features by taking into account buffer (default= 3 by 3 pixels). If option -polygon is set, output ogr features are polygons defining the buffer. changed names for maximum and minumum rule to max and min respectively new options -rand and -grid to support simple random sampling and systematic grid (do not provide sample vector dataset) + - pksvm + replaced options s|start and e|end with bs|bstart and be|bend + - pkann + replaced options s|start and e|end with bs|bstart and be|bend + - pkfssvm + replaced options s|start and e|end with bs|bstart and be|bend + - pkfsann + replaced options s|start and e|end with bs|bstart and be|bend + - pkoptsvm + replaced options s|start and e|end with bs|bstart and be|bend - ImgWriteOgr overwrite existing ogr datasets per default - Next versions: - todo for API ImgReaderGdal (ImgWriterGdal) open in update mode (check gdal_edit.py: http://searchcode.com/codesearch/view/18938404) diff --git a/src/apps/pkann.cc b/src/apps/pkann.cc index bccd66d..64c34e4 100644 --- a/src/apps/pkann.cc +++ b/src/apps/pkann.cc @@ -45,9 +45,9 @@ int main(int argc, char *argv[]) Optionpk<unsigned int> balance_opt("bal", "balance", "balance the input data to this number of samples for each class", 0); Optionpk<bool> random_opt("random", "random", "in case of balance, randomize input data", true,2); Optionpk<int> minSize_opt("min", "min", "if number of training pixels is less then min, do not take this class into account (0: consider all classes)", 0); - Optionpk<double> start_opt("s", "start", "start band sequence number",0); - Optionpk<double> end_opt("e", "end", "end band sequence number (set to 0 to include bands)", 0); Optionpk<short> band_opt("b", "band", "band index (starting from 0, either use band option or use start to end)"); + Optionpk<double> bstart_opt("bs", "bstart", "start band sequence number",0); + Optionpk<double> bend_opt("be", "bend", "end band sequence number (set to 0 to include 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<unsigned short> aggreg_opt("a", "aggreg", "how to combine aggregated classifiers, see also rc option (1: sum rule, 2: max rule).",1); @@ -89,9 +89,9 @@ int main(int argc, char *argv[]) balance_opt.retrieveOption(argc,argv); random_opt.retrieveOption(argc,argv); minSize_opt.retrieveOption(argc,argv); - start_opt.retrieveOption(argc,argv); - end_opt.retrieveOption(argc,argv); band_opt.retrieveOption(argc,argv); + bstart_opt.retrieveOption(argc,argv); + bend_opt.retrieveOption(argc,argv); offset_opt.retrieveOption(argc,argv); scale_opt.retrieveOption(argc,argv); aggreg_opt.retrieveOption(argc,argv); @@ -222,7 +222,7 @@ int main(int argc, char *argv[]) if(band_opt.size()) totalSamples=trainingReaderBag.readDataImageOgr(trainingMap,fields,band_opt,label_opt[0],tlayer_opt,verbose_opt[0]); else - totalSamples=trainingReaderBag.readDataImageOgr(trainingMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]); + totalSamples=trainingReaderBag.readDataImageOgr(trainingMap,fields,bstart_opt[0],bend_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]); if(trainingMap.size()<2){ string errorstring="Error: could not read at least two classes from training file, did you provide class labels in training sample (see option label)?"; throw(errorstring); @@ -723,7 +723,7 @@ int main(int argc, char *argv[]) } } else{ - for(int iband=start_opt[0];iband<start_opt[0]+nband;++iband){ + for(int iband=bstart_opt[0];iband<bstart_opt[0]+nband;++iband){ if(verbose_opt[0]==2) std::cout << "reading band " << iband << std::endl; assert(iband>=0); diff --git a/src/apps/pkfsann.cc b/src/apps/pkfsann.cc index 9bee67d..d155158 100644 --- a/src/apps/pkfsann.cc +++ b/src/apps/pkfsann.cc @@ -179,9 +179,9 @@ int main(int argc, char *argv[]) Optionpk<unsigned int> balance_opt("\0", "balance", "balance the input data to this number of samples for each class", 0); Optionpk<bool> random_opt("random","random", "in case of balance, randomize input data", true); Optionpk<int> minSize_opt("min", "min", "if number of training pixels is less then min, do not take this class into account", 0); - Optionpk<double> start_opt("s", "start", "start band sequence number",0); - Optionpk<double> end_opt("e", "end", "end band sequence number (set to 0 to include all bands)", 0); Optionpk<short> band_opt("b", "band", "band index (starting from 0, either use band option or use start to end)"); + Optionpk<double> bstart_opt("bs", "bstart", "start band sequence number",0); + 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<unsigned short> aggreg_opt("a", "aggreg", "how to combine aggregated classifiers, see also rc option (0: no aggregation, 1: sum rule, 2: max rule).",0); @@ -208,9 +208,9 @@ int main(int argc, char *argv[]) balance_opt.retrieveOption(argc,argv); random_opt.retrieveOption(argc,argv); minSize_opt.retrieveOption(argc,argv); - start_opt.retrieveOption(argc,argv); - end_opt.retrieveOption(argc,argv); band_opt.retrieveOption(argc,argv); + bstart_opt.retrieveOption(argc,argv); + bend_opt.retrieveOption(argc,argv); offset_opt.retrieveOption(argc,argv); scale_opt.retrieveOption(argc,argv); aggreg_opt.retrieveOption(argc,argv); @@ -316,10 +316,10 @@ int main(int argc, char *argv[]) } } else{ - totalSamples=trainingReader.readDataImageOgr(trainingMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]); + totalSamples=trainingReader.readDataImageOgr(trainingMap,fields,bstart_opt[0],bend_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]); if(input_opt.size()){ ImgReaderOgr inputReader(input_opt[0]); - totalTestSamples=trainingReader.readDataImageOgr(testMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]); + totalTestSamples=trainingReader.readDataImageOgr(testMap,fields,bstart_opt[0],bend_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]); inputReader.close(); } } diff --git a/src/apps/pkfssvm.cc b/src/apps/pkfssvm.cc index 3a8a222..67c96d0 100644 --- a/src/apps/pkfssvm.cc +++ b/src/apps/pkfssvm.cc @@ -205,9 +205,9 @@ int main(int argc, char *argv[]) Optionpk<unsigned int> balance_opt("bal", "balance", "balance the input data to this number of samples for each class", 0); Optionpk<bool> random_opt("random","random", "in case of balance, randomize input data", true); Optionpk<int> minSize_opt("min", "min", "if number of training pixels is less then min, do not take this class into account", 0); - Optionpk<double> start_opt("s", "start", "start band sequence number",0); - Optionpk<double> end_opt("e", "end", "end band sequence number (set to 0 to include all bands)", 0); Optionpk<short> band_opt("b", "band", "band index (starting from 0, either use band option or use start to end)"); + Optionpk<double> bstart_opt("bs", "bstart", "start band sequence number",0); + 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<string> selector_opt("sm", "sm", "feature selection method (sffs=sequential floating forward search,sfs=sequential forward search, sbs, sequential backward search ,bfs=brute force search)","sffs"); @@ -240,9 +240,9 @@ int main(int argc, char *argv[]) balance_opt.retrieveOption(argc,argv); random_opt.retrieveOption(argc,argv); minSize_opt.retrieveOption(argc,argv); - start_opt.retrieveOption(argc,argv); - end_opt.retrieveOption(argc,argv); band_opt.retrieveOption(argc,argv); + bstart_opt.retrieveOption(argc,argv); + bend_opt.retrieveOption(argc,argv); offset_opt.retrieveOption(argc,argv); scale_opt.retrieveOption(argc,argv); // priors_opt.retrieveOption(argc,argv); @@ -350,10 +350,10 @@ int main(int argc, char *argv[]) } } else{ - totalSamples=trainingReader.readDataImageOgr(trainingMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]); + totalSamples=trainingReader.readDataImageOgr(trainingMap,fields,bstart_opt[0],bend_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]); if(input_opt.size()){ ImgReaderOgr inputReader(input_opt[0]); - totalTestSamples=inputReader.readDataImageOgr(testMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]); + totalTestSamples=inputReader.readDataImageOgr(testMap,fields,bstart_opt[0],bend_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]); inputReader.close(); } } diff --git a/src/apps/pkoptsvm.cc b/src/apps/pkoptsvm.cc index 83fd8cf..0452469 100644 --- a/src/apps/pkoptsvm.cc +++ b/src/apps/pkoptsvm.cc @@ -266,9 +266,9 @@ int main(int argc, char *argv[]) Optionpk<unsigned int> balance_opt("bal", "balance", "balance the input data to this number of samples for each class", 0); Optionpk<bool> random_opt("random","random", "in case of balance, randomize input data", true); Optionpk<int> minSize_opt("min", "min", "if number of training pixels is less then min, do not take this class into account", 0); - Optionpk<double> start_opt("s", "start", "start band sequence number",0); - Optionpk<double> end_opt("e", "end", "end band sequence number (set to 0 to include all bands)", 0); Optionpk<short> band_opt("b", "band", "band index (starting from 0, either use band option or use start to end)"); + Optionpk<double> bstart_opt("bs", "bstart", "start band sequence number",0); + Optionpk<double> bend_opt("be", "bend", "bend 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<float> gamma_opt("g", "gamma", "min max boundaries for gamma in kernel function (optional: initial value)",0); @@ -288,9 +288,9 @@ int main(int argc, char *argv[]) balance_opt.retrieveOption(argc,argv); random_opt.retrieveOption(argc,argv); minSize_opt.retrieveOption(argc,argv); - start_opt.retrieveOption(argc,argv); - end_opt.retrieveOption(argc,argv); band_opt.retrieveOption(argc,argv); + bstart_opt.retrieveOption(argc,argv); + bend_opt.retrieveOption(argc,argv); offset_opt.retrieveOption(argc,argv); scale_opt.retrieveOption(argc,argv); svm_type_opt.retrieveOption(argc,argv); @@ -393,10 +393,10 @@ int main(int argc, char *argv[]) } } else{ - totalSamples=trainingReader.readDataImageOgr(trainingMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]); + totalSamples=trainingReader.readDataImageOgr(trainingMap,fields,bstart_opt[0],bend_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]); if(input_opt.size()){ ImgReaderOgr inputReader(input_opt[0]); - totalTestSamples=inputReader.readDataImageOgr(testMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]); + totalTestSamples=inputReader.readDataImageOgr(testMap,fields,bstart_opt[0],bend_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]); inputReader.close(); } trainingReader.close(); diff --git a/src/apps/pksvm.cc b/src/apps/pksvm.cc index 12ce0e6..d5532f6 100644 --- a/src/apps/pksvm.cc +++ b/src/apps/pksvm.cc @@ -55,9 +55,9 @@ int main(int argc, char *argv[]) Optionpk<unsigned int> balance_opt("bal", "balance", "Balance the input data to this number of samples for each class", 0); Optionpk<bool> random_opt("random", "random", "Randomize training data for balancing and bagging", true, 2); Optionpk<int> minSize_opt("min", "min", "If number of training pixels is less then min, do not take this class into account (0: consider all classes)", 0); - Optionpk<double> start_opt("s", "start", "Start band sequence number",0); - Optionpk<double> end_opt("e", "end", "End band sequence number (set to 0 to include all bands)", 0); Optionpk<short> band_opt("b", "band", "Band index (starting from 0, either use band option or use start to end)"); + Optionpk<double> bstart_opt("bs", "bstart", "Start band sequence number",0); + 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); @@ -117,8 +117,8 @@ int main(int argc, char *argv[]) msknodata_opt.retrieveOption(argc,argv); nodata_opt.retrieveOption(argc,argv); band_opt.retrieveOption(argc,argv); - start_opt.retrieveOption(argc,argv); - end_opt.retrieveOption(argc,argv); + bstart_opt.retrieveOption(argc,argv); + bend_opt.retrieveOption(argc,argv); balance_opt.retrieveOption(argc,argv); minSize_opt.retrieveOption(argc,argv); bag_opt.retrieveOption(argc,argv); @@ -265,7 +265,7 @@ int main(int argc, char *argv[]) if(band_opt.size()) totalSamples=trainingReaderBag.readDataImageOgr(trainingMap,fields,band_opt,label_opt[0],tlayer_opt,verbose_opt[0]); else - totalSamples=trainingReaderBag.readDataImageOgr(trainingMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]); + totalSamples=trainingReaderBag.readDataImageOgr(trainingMap,fields,bstart_opt[0],bend_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]); if(trainingMap.size()<2){ string errorstring="Error: could not read at least two classes from training file, did you provide class labels in training sample (see option label)?"; throw(errorstring); @@ -716,7 +716,7 @@ int main(int argc, char *argv[]) } } else{ - for(int iband=start_opt[0];iband<start_opt[0]+nband;++iband){ + for(int iband=bstart_opt[0];iband<bstart_opt[0]+nband;++iband){ if(verbose_opt[0]==2) std::cout << "reading band " << iband << std::endl; assert(iband>=0); -- Alioth's /usr/local/bin/git-commit-notice on /srv/git.debian.org/git/pkg-grass/pktools.git _______________________________________________ Pkg-grass-devel mailing list Pkg-grass-devel@lists.alioth.debian.org http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-grass-devel