Merge pull request #94 from schalkdaniel/general_updates

update some destructors

src/baselearner_list.cpp

@@ -84,6 +84,7 @@ blearner_factory_map BaselearnerList::GetMap ()
 // Remove all registered factorys:
 void BaselearnerList::ClearMap ()
 {
+  std::cout << "Delete BaselearnerList!" << std::cout;
   // This deletes all the data which are sometimes necessary to re register 
   // factorys!
   // for (blearner_factory_map::iterator it = my_factory_map.begin(); it != my_factory_map.end(); ++it) {

src/baselearner_list.h

@@ -80,6 +80,8 @@ class BaselearnerList
 
     // Get the data used for modelling:
     std::pair<std::vector<std::string>, arma::mat> GetModelFrame ();
+
+    // ~BaselearnerList () {std::cout << "Destroy BaselearnerList!" << std::endl; }
 };
 
 } // namespace blearnerlist

src/compboost.cpp

@@ -37,11 +37,6 @@
 //
 // ========================================================================== //
 
-
-
-// THIS ONE IS UNDER PROGRESS!
-
-
 #include "compboost.h"
 
 namespace cboost {
@@ -193,10 +188,10 @@ std::vector<std::string> Compboost::GetSelectedBaselearner ()
 // Destructor:
 Compboost::~Compboost ()
 {
-  std::cout << "Call Compboost Destructor" << std::endl;
-  delete used_optimizer;
-  delete used_loss;
-  delete used_logger;
+  // std::cout << "Call Compboost Destructor" << std::endl;
+  // delete used_optimizer;
+  // delete used_loss;
+  // delete used_logger;
 }
 
 } // namespace cboost

src/compboost_modules.cpp

@@ -211,9 +211,9 @@ class BaselearnerListWrapper
     obj.ClearMap();
   }
 
-  blearnerlist::BaselearnerList getFactoryList ()
+  blearnerlist::BaselearnerList* getFactoryList ()
   {
-    return obj;
+    return &obj;
   }
 
   Rcpp::List getModelFrame ()
@@ -477,15 +477,20 @@ class GreedyOptimizer : public OptimizerWrapper
 {
 public:
   GreedyOptimizer () { obj = new optimizer::Greedy(); }
+
   Rcpp::List testOptimizer (arma::vec& response, BaselearnerListWrapper factory_list)
   {
     std::string temp_str = "test run";
-    blearner::Baselearner* blearner_test = obj->FindBestBaselearner(temp_str, response, factory_list.getFactoryList().GetMap());
+    blearner::Baselearner* blearner_test = obj->FindBestBaselearner(temp_str, response, factory_list.getFactoryList()->GetMap());
 
-    return Rcpp::List::create(
+    Rcpp::List out = Rcpp::List::create(
       Rcpp::Named("selected.learner") = blearner_test->GetIdentifier(),
       Rcpp::Named("parameter")        = blearner_test->GetParameter()
     );
+
+    delete blearner_test;
+
+    return out;
   }
 };
 
@@ -522,6 +527,7 @@ class CompboostWrapper
     learning_rate0 = learning_rate;
     used_logger    = logger_list.getLoggerList();
     used_optimizer = optimizer.getOptimizer();
+    blearner_list_ptr = factory_list.getFactoryList();
 
     // used_optimizer = new optimizer::Greedy();
     // std::cout << "<<CompboostWrapper>> Create new Optimizer" << std::endl;
@@ -538,7 +544,7 @@ class CompboostWrapper
     // // std::cout << "<<CompboostWrapper>> Register Logger" << std::endl;
 
     obj = new cboost::Compboost(response, learning_rate0, stop_if_all_stopper_fulfilled, 
-      used_optimizer, loss.getLoss(), used_logger, factory_list.getFactoryList());
+      used_optimizer, loss.getLoss(), used_logger, *blearner_list_ptr);
     // std::cout << "<<CompboostWrapper>> Create Compboost" << std::endl;
   }
 
@@ -578,10 +584,11 @@ class CompboostWrapper
 
 private:
 
+  blearnerlist::BaselearnerList* blearner_list_ptr;
   loggerlist::LoggerList* used_logger;
-  optimizer::Optimizer* used_optimizer = NULL;
+  optimizer::Optimizer* used_optimizer;
   cboost::Compboost* obj;
-  arma::mat* eval_data = NULL;
+  arma::mat* eval_data;
 
   unsigned int max_iterations;
   double learning_rate0;

src/optimizer.cpp

@@ -86,14 +86,15 @@ blearner::Baselearner* Greedy::FindBestBaselearner (std::string& iteration_id,
     // baselearner:
     if (ssq_best == 0) {
       ssq_best = ssq_temp;
-      blearner_best = blearner_temp;
+      blearner_best = blearner_temp->Clone();
     }
 
     if (ssq_temp < ssq_best) {
       ssq_best = ssq_temp;
-      blearner_best = blearner_temp;
+      blearner_best = blearner_temp->Clone();
     }
 
+    delete blearner_temp;
     blearner_temp = NULL;
 
     // if (k > 0) {

tests/testthat/test_factory.R

@@ -6,6 +6,7 @@ test_that("polynomial factory works", {
   X.linear = 1:10
   X.cubic  = X.linear^3
 
+  set.seed(pi)
   X.test = as.matrix(runif(200))
 
   y = 3 * X.linear + rnorm(10, 0, 2)
@@ -77,6 +78,7 @@ test_that("custom factory works", {
   }
 
   # Data X and response y:
+  set.seed(pi)
   X = matrix(1:10, ncol = 1)
   y = sin(as.numeric(X)) + rnorm(10, 0, 0.6)
 

tests/testthat/test_optimizer.R

@@ -2,7 +2,9 @@ context("The optimizer works")
 
 test_that("greedy optimizer works", {
 
+  set.seed(pi)
   X = as.matrix(runif(100, -4, 4))
+
   y.linear = as.numeric(32 * X)
   y.cubic  = as.numeric(16 * X^3)
   y.pow5   = as.numeric(8 * X^5)

tests/testthat/test_printer.R

@@ -1,5 +1,25 @@
 context("Printer works")
 
+test_that("factory list printer works", {
+
+  factory.list = FactoryList$new()
+
+  # A hack to suppress console output:
+  tc = textConnection(NULL, "w") 
+  sink(tc) 
+
+  test.factory.list.printer = show(factory.list)
+
+  sink() 
+  close(tc) 
+
+  # Test:
+  # ---------
+
+  expect_equal(test.factory.list.printer, "FactoryListPrinter")
+
+})
+
 test_that("Loss printer works", {
 
   quadratic.loss = QuadraticLoss$new()

tutorials/compboost_vs_mboost.R

@@ -107,12 +107,12 @@ cboost.xselect = match(
   )
 )
 
-all.equal(predict(mod), cboost$getPrediction())
+all.equal(mod$xselect(), cboost.xselect)
 
 # Check if the prediction is the same:
 # ------------------------------------
 
-all.equal(mod$xselect(), cboost.xselect)
+all.equal(predict(mod), cboost$getPrediction())
 # cboost$GetParameter()
 
 # Benchmark:

tutorials/run_optimizer.R

@@ -1,43 +1,29 @@
-# Define a 'BaselearnerList':
-# ===================================
+set.seed(pi)
+X = as.matrix(runif(100, -4, 4))
 
-X = matrix(1:10, ncol = 1)
-y = 3 * as.numeric(X^3) + rnorm(10, 0, 2)
+y.linear = as.numeric(32 * X)
+y.cubic  = as.numeric(16 * X^3)
+y.pow5   = as.numeric(8 * X^5)
 
-# Create some stupid baselearner (obviously the linear one is the best):
-bl.linear = BaselearnerWrapper$new("l1", X, "x", 1)
-bl.quadratic = BaselearnerWrapper$new("q1", X, "x", 2)
-bl.cubic = BaselearnerWrapper$new("c1", X, "x", 3)
-bl.linear2 = BaselearnerWrapper$new("l0", 2 * X, "x", 1)
+# Create new linear baselearner of hp and wt:
+linear.factory = PolynomialFactory$new(X, "X", 1)
+cubic.factory  = PolynomialFactory$new(X, "X", 3)
+pow5.factory   = PolynomialFactory$new(X, "X", 5)
 
-# Register the learner:
-bl.quadratic$RegisterFactory("x")
-bl.cubic$RegisterFactory("x")
-bl.linear2$RegisterFactory("2*x")
-bl.linear$RegisterFactory("x")
+# Create new factory list:
+factory.list = FactoryList$new()
 
-# Train the lienar one to compare with the result of the optimizer:
-bl.linear$train(y)
+# Register factorys:
+factory.list$registerFactory(linear.factory)
+factory.list$registerFactory(cubic.factory)
+factory.list$registerFactory(pow5.factory)
 
-# Print all registered baselearner:
-printRegisteredFactorys()
+# Optimizer:
+greedy.optimizer = GreedyOptimizer$new()
 
-# Get best Baselearner:
-# ===================================
+res.linear = greedy.optimizer$testOptimizer(y.linear, factory.list)
+res.cubic  = greedy.optimizer$testOptimizer(y.cubic, factory.list)
+res.pow5   = greedy.optimizer$testOptimizer(y.pow5, factory.list)
 
-# Use the greedy algorithm:
-getBestBaselearner(y)
-
-bl.linear$GetParameter()
-
-# What happens here? Why aren't we get the linear parameter?
-# Register that we have also used 2*x as linear baselearner which basically
-# is exactly the same as x. The parameter here is just divided by 2:
-bl.linear2$train(y)
-bl.linear2$GetParameter()
-
-# Clear the registry:
-clearRegisteredFactorys()
-
-# Take a look if all registrys were deleted:
-printRegisteredFactorys()
+res.cubic
+res.linear