migrating & scaffolding & reformatting

Added more cmdline options

5 files changed, 60 insertions, 43 deletions

diff --git a/CMakeLists.txt b/CMakeLists.txt
index 99c798e..6ccf0c8 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -1,5 +1,5 @@
 cmake_minimum_required(VERSION 2.8.4)
-project(eigenTest)
+project(ranksvm)
 
 # Use Eigen3 Library for Linear Algebra
 INCLUDE_DIRECTORIES ( "/usr/include/eigen3" )
@@ -12,5 +12,5 @@ FIND_PACKAGE( Boost COMPONENTS program_options REQUIRED )
 INCLUDE_DIRECTORIES( ${Boost_INCLUDE_DIR})
 
 set(SOURCE_FILES main.cpp ./model/ranksvm.cpp)
-add_executable(eigenTest ${SOURCE_FILES})
-TARGET_LINK_LIBRARIES( eigenTest ${Boost_LIBRARIES} )
\ No newline at end of file
+add_executable(ranksvm ${SOURCE_FILES})
+TARGET_LINK_LIBRARIES( ranksvm ${Boost_LIBRARIES} )
\ No newline at end of file
diff --git a/main.cpp b/main.cpp
index d23ded2..8d5b393 100644
--- a/main.cpp
+++ b/main.cpp
@@ -13,42 +13,58 @@ namespace po = boost::program_options;
 
 po::variables_map vm;
 
-int train()
-{
-  RSVM* rsvm;
-  rsvm=RSVM::loadModel(vm["model"].as<std::string>().c_str());
-  FileDP dp(vm["feature"].as<std::string>().c_str());
-  rsvm->train(dp);
-  rsvm->predict(dp);
-  rsvm->saveModel(vm["output"].as<std::string>().c_str());
-  delete rsvm;
-  return 0;
+int train() {
+    RSVM *rsvm;
+    rsvm = RSVM::loadModel(vm["model"].as<std::string>().c_str());
+    FileDP dp(vm["feature"].as<std::string>().c_str());
+    rsvm->train(dp);
+    rsvm->saveModel(vm["output"].as<std::string>().c_str());
+    delete rsvm;
+    return 0;
 }
 
-int main(int argc,char ** argv)
-{
-  // Defining program options
-  po::options_description desc("Allowed options");
-  desc.add_options()
-          ("help,h", "produce help message")
-          ("model,m", po::value<std::string>()->default_value("test.m"), "set input model file")
-          ("feature,i", po::value<std::string>()->default_value("test.f"), "set input feature file")
-          ("output,o", po::value<std::string>()->default_value("test.m.out"), "set output model file")
-          ;
-
-  // Parsing program options
-  po::store(po::parse_command_line(argc, argv, desc), vm);
-  po::notify(vm);
-
-  if (vm.count("help")) {
-    std::cout << desc << "\n";
-    return 1;
-  }
-
-  MatrixXd m(2,2);
-  m(0,0) = 3;
-  m(1,0) = 2.5;
-  m(0,1) = -1;
-  m(1,1) = m(1,0) + m(0,1);
-  std::cout << m << std::endl;
+int predict() {
+    RSVM *rsvm;
+    rsvm = RSVM::loadModel(vm["model"].as<std::string>().c_str());
+    FileDP dp(vm["feature"].as<std::string>().c_str());
+    rsvm->predict(dp);
+    delete rsvm;
+    return 0;
+}
+
+int main(int argc, char **argv) {
+    // Defining program options
+    po::options_description desc("Allowed options");
+    desc.add_options()
+            ("help,h", "produce help message")
+            ("train,T", "training model")
+            ("validate,V", "validate model")
+            ("predict,P", "use model for prediction")
+            ("model,m", po::value<std::string>(), "set input model file")
+            ("output,o", po::value<std::string>(), "set output model file")
+            ("feature,i", po::value<std::string>(), "set input feature file");
+
+    // Parsing program options
+    po::store(po::parse_command_line(argc, argv, desc), vm);
+    po::notify(vm);
+
+    // Print help if necessary
+    if (vm.count("help") || !(vm.count("train") || vm.count("validate") || vm.count("predict"))) {
+        std::cout << desc;
+        return 0;
+    }
+
+    if (vm.count("train")) {
+        LOG(INFO) << "Program option: training";
+        train();
+    }
+    else if (vm.count("validate")) {
+        LOG(INFO) << "Program option: validate";
+        predict();
+    }
+    else if (vm.count("predict")) {
+        LOG(INFO) << "Program option: predict";
+        predict();
+    }
+    return 0;
 }
diff --git a/model/ranksvm.cpp b/model/ranksvm.cpp
index 58a097a..6294245 100644
--- a/model/ranksvm.cpp
+++ b/model/ranksvm.cpp
@@ -25,7 +25,6 @@ RSVM* RSVM::loadModel(const string fname){
 
     RSVM* rsvm;
 
-    // TODO multiplex type
     if (type=="TN")
         rsvm = new RSVMTN();
 
@@ -39,7 +38,7 @@ RSVM* RSVM::loadModel(const string fname){
 
 int RSVM::setModel(const Eigen::VectorXd &model) {
     if (model.cols()!=fsize)
-        LOG(FATAL) << "Feature size mismatch";;
+        LOG(FATAL) << "Feature size mismatch";
     this->model=model;
     return 0;
 }
\ No newline at end of file
diff --git a/model/ranksvm.h b/model/ranksvm.h
index fad790d..e7b7c4a 100644
--- a/model/ranksvm.h
+++ b/model/ranksvm.h
@@ -12,8 +12,8 @@ protected:
     Eigen::VectorXd model;
     int fsize;
 public:
-    virtual int train(DataProvider &D)=0;
-    virtual int predict(DataProvider &D)=0;
+    virtual int train(DataProvider &D)=0; // Dataprovider will have to provide label
+    virtual int predict(DataProvider &D)=0;  // TODO Not sure how to construct this
     int saveModel(const std::string fname);
     static RSVM* loadModel(const std::string fname);
     virtual std::string getName()=0;
diff --git a/tools/dataProvider.h b/tools/dataProvider.h
index b2384c9..d9440ce 100644
--- a/tools/dataProvider.h
+++ b/tools/dataProvider.h
@@ -4,6 +4,8 @@
 #include<Eigen/Dense>
 #include "../tools/easylogging++.h"
 
+// TODO decide how to construct training data
+
 class DataProvider  //Virtual base class for data input
 {
 protected: