[mlpack-svn] r10069 - in mlpack/trunk/src/mlpack/methods: . emst fastica infomax_ica linear_regression mog mvu naive_bayes nca neighbor_search nnsvm regression svm
fastlab-svn at coffeetalk-1.cc.gatech.edu
fastlab-svn at coffeetalk-1.cc.gatech.edu
Sat Oct 29 00:26:39 EDT 2011
Author: rcurtin
Date: 2011-10-29 00:26:38 -0400 (Sat, 29 Oct 2011)
New Revision: 10069
Modified:
mlpack/trunk/src/mlpack/methods/CMakeLists.txt
mlpack/trunk/src/mlpack/methods/emst/emst_main.cpp
mlpack/trunk/src/mlpack/methods/fastica/fastica_main.cpp
mlpack/trunk/src/mlpack/methods/fastica/lin_alg_test.cpp
mlpack/trunk/src/mlpack/methods/infomax_ica/infomax_ica_test.cc
mlpack/trunk/src/mlpack/methods/infomax_ica/main.cc
mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression_main.cpp
mlpack/trunk/src/mlpack/methods/mog/mog_em_main.cc
mlpack/trunk/src/mlpack/methods/mog/mog_l2e_main.cc
mlpack/trunk/src/mlpack/methods/mvu/CMakeLists.txt
mlpack/trunk/src/mlpack/methods/mvu/mvu.h
mlpack/trunk/src/mlpack/methods/mvu/mvu_impl.h
mlpack/trunk/src/mlpack/methods/mvu/mvu_objective_function.h
mlpack/trunk/src/mlpack/methods/naive_bayes/nbc_main.cc
mlpack/trunk/src/mlpack/methods/naive_bayes/nbc_test.cc
mlpack/trunk/src/mlpack/methods/nca/nca_main.cc
mlpack/trunk/src/mlpack/methods/nca/nca_softmax_error_function.h
mlpack/trunk/src/mlpack/methods/neighbor_search/allkfn_main.cc
mlpack/trunk/src/mlpack/methods/neighbor_search/allkfn_test.cc
mlpack/trunk/src/mlpack/methods/neighbor_search/allknn_main.cc
mlpack/trunk/src/mlpack/methods/neighbor_search/allknn_test.cc
mlpack/trunk/src/mlpack/methods/nnsvm/nnsvm_main.cpp
mlpack/trunk/src/mlpack/methods/regression/ridge_main.cc
mlpack/trunk/src/mlpack/methods/svm/svm_main.cc
Log:
Use overloaded mat.save() and mat.load() functions.
Modified: mlpack/trunk/src/mlpack/methods/CMakeLists.txt
===================================================================
--- mlpack/trunk/src/mlpack/methods/CMakeLists.txt 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/CMakeLists.txt 2011-10-29 04:26:38 UTC (rev 10069)
@@ -9,7 +9,7 @@
# kernel_pca # (required sparse and is known to not work or compile)
linear_regression
mog
- # mvu # (currently known to not work)
+ mvu # (currently known to not work)
naive_bayes
nca
neighbor_search
Modified: mlpack/trunk/src/mlpack/methods/emst/emst_main.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/emst/emst_main.cpp 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/emst/emst_main.cpp 2011-10-29 04:26:38 UTC (rev 10069)
@@ -143,7 +143,8 @@
std::string naive_output_filename =
CLI::GetParam<std::string>("naive/output_file");
- naive_results.save(naive_output_filename.c_str());
+ naive_results.save(naive_output_filename.c_str(), arma::csv_ascii, false,
+ true);
}
//////////////// Output the Results ////////////////
@@ -151,7 +152,7 @@
std::string output_filename =
CLI::GetParam<std::string>("emst/output_file");
- results.save(output_filename.c_str());
+ results.save(output_filename.c_str(), arma::csv_ascii, false, true);
}// end else (if using_thor)
Modified: mlpack/trunk/src/mlpack/methods/fastica/fastica_main.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/fastica/fastica_main.cpp 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/fastica/fastica_main.cpp 2011-10-29 04:26:38 UTC (rev 10069)
@@ -57,7 +57,7 @@
CLI::ParseCommandLine(argc, argv);
const char* data = CLI::GetParam<std::string>("fastica/input_file").c_str();
- X.load(data);
+ X.load(data, arma::auto_detect, false, true);
const char* ic_filename = CLI::GetParam<std::string>("fastica/ic_file").c_str();
const char* unmixing_filename =
@@ -69,9 +69,9 @@
if(fastica.Init(X) == true) {
arma::mat W, Y;
if(fastica.DoFastICA(W, Y) == true) {
- Y.save(ic_filename);
+ Y.save(ic_filename, arma::csv_ascii, false, true);
arma::mat Z = trans(W);
- Z.save(unmixing_filename);
+ Z.save(unmixing_filename, arma::csv_ascii, false, true);
success_status = true;
mlpack::Log::Debug << W << std::endl;
}
Modified: mlpack/trunk/src/mlpack/methods/fastica/lin_alg_test.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/fastica/lin_alg_test.cpp 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/fastica/lin_alg_test.cpp 2011-10-29 04:26:38 UTC (rev 10069)
@@ -84,7 +84,7 @@
// We are loading a matrix from an external file... bad choice.
mat tmp, tmp_centered, whitened, whitening_matrix;
- tmp.load("fake.arff");
+ tmp.load("trainSet.csv", arma::auto_detect, false, true);
Center(tmp, tmp_centered);
WhitenUsingEig(tmp_centered, whitened, whitening_matrix);
@@ -107,7 +107,7 @@
// Generate a random matrix; then, orthogonalize it and test if it's
// orthogonal.
mat tmp, orth;
- tmp.load("fake.arff");
+ tmp.load("fake.csv", arma::auto_detect, false, true);
Orthogonalize(tmp, orth);
// test orthogonality
Modified: mlpack/trunk/src/mlpack/methods/infomax_ica/infomax_ica_test.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/infomax_ica/infomax_ica_test.cc 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/infomax_ica/infomax_ica_test.cc 2011-10-29 04:26:38 UTC (rev 10069)
@@ -22,7 +22,7 @@
int bb_ = 5;
double epsilonb_ = 0.001;
- testdatab_.load("fake.arff");
+ testdatab_.load("fake.csv", arma::auto_detect, false, true);
InfomaxICA icab_(lambdab_, bb_, epsilonb_);
@@ -39,7 +39,7 @@
// load some test data that has been verified using the matlab
// implementation of infomax
- testdata_.load("fake.arff");
+ testdata_.load("fake.csv", arma::auto_detect, false, true);
InfomaxICA ica_(lambda_, b_, epsilon_);
ica_.sampleCovariance(testdata_);
@@ -53,7 +53,7 @@
// load some test data that has been verified using the matlab
// implementation of infomax
- testdata_.load("fake.arff");
+ testdata_.load("fake.csv", arma::auto_detect, false, true);
InfomaxICA ica_(lambda_, b_, epsilon_);
arma::mat unmixing;
Modified: mlpack/trunk/src/mlpack/methods/infomax_ica/main.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/infomax_ica/main.cc 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/infomax_ica/main.cc 2011-10-29 04:26:38 UTC (rev 10069)
@@ -22,7 +22,7 @@
double epsilon = CLI::GetParam<double>("info/epsilon");
arma::mat dataset;
- dataset.load(data_file_name);
+ dataset.load(data_file_name, arma::auto_detect, false, true);
InfomaxICA ica(lambda, B, epsilon);
ica.applyICA(dataset);
Modified: mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression_main.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression_main.cpp 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression_main.cpp 2011-10-29 04:26:38 UTC (rev 10069)
@@ -29,9 +29,9 @@
const std::string response_name =
CLI::GetParam<std::string>("linear_regression/responses");
- file.load(train_name.c_str());
+ file.load(train_name.c_str(), arma::auto_detect, false, true);
size_t n_cols = file.n_cols,
- n_rows = file.n_rows;
+ n_rows = file.n_rows;
if(response_name == "") {
predictors = file.submat(0,0, n_rows-2, n_cols-1);
@@ -42,7 +42,7 @@
else {
predictors = file;
// The initial predictors for y, Nx1
- responses.load(response_name.c_str());
+ responses.load(response_name.c_str(), arma::auto_detect, false, true);
if(responses.n_rows > 1) {
std::cerr << "Error: The responses must have one column.\n";
return 0;
@@ -54,7 +54,7 @@
}
}
- points.load(test_name.c_str());
+ points.load(test_name.c_str(), arma::auto_detect, false, true);
if(points.n_rows != n_rows) {
std::cerr << "Error: The test data must have the same number of cols as\
the training file.\n";
Modified: mlpack/trunk/src/mlpack/methods/mog/mog_em_main.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/mog/mog_em_main.cc 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/mog/mog_em_main.cc 2011-10-29 04:26:38 UTC (rev 10069)
@@ -39,7 +39,8 @@
////// READING PARAMETERS AND LOADING DATA //////
arma::mat data_points;
- data_points.load(CLI::GetParam<std::string>("mog/data").c_str());
+ data_points.load(CLI::GetParam<std::string>("mog/data").c_str(),
+ arma::auto_detect, false, true);
////// MIXTURE OF GAUSSIANS USING EM //////
MoGEM mog;
Modified: mlpack/trunk/src/mlpack/methods/mog/mog_l2e_main.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/mog/mog_l2e_main.cc 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/mog/mog_l2e_main.cc 2011-10-29 04:26:38 UTC (rev 10069)
@@ -40,7 +40,8 @@
////// READING PARAMETERS AND LOADING DATA //////
arma::mat data_points;
- data_points.load(CLI::GetParam<std::string>("mog_l2e/data").c_str());
+ data_points.load(CLI::GetParam<std::string>("mog_l2e/data").c_str(),
+ arma::auto_detect, false, true);
////// MIXTURE OF GAUSSIANS USING L2 ESTIMATCLIN //////
size_t number_of_gaussians = CLI::GetParam<int>("mog_l2e/k");
Modified: mlpack/trunk/src/mlpack/methods/mvu/CMakeLists.txt
===================================================================
--- mlpack/trunk/src/mlpack/methods/mvu/CMakeLists.txt 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/mvu/CMakeLists.txt 2011-10-29 04:26:38 UTC (rev 10069)
@@ -5,8 +5,8 @@
set(SOURCES
mvu.h
mvu_impl.h
- mvu_objective_function.h
- mvu_objective_function.cc
+# mvu_objective_function.h
+# mvu_objective_function.cc
)
# Add directory name to sources.
@@ -19,7 +19,7 @@
set(MLPACK_SRCS ${MLPACK_SRCS} ${DIR_SRCS} PARENT_SCOPE)
add_executable(ncmvu
- main.cc
+ mvu_main.cpp
)
target_link_libraries(ncmvu
mlpack
Modified: mlpack/trunk/src/mlpack/methods/mvu/mvu.h
===================================================================
--- mlpack/trunk/src/mlpack/methods/mvu/mvu.h 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/mvu/mvu.h 2011-10-29 04:26:38 UTC (rev 10069)
@@ -11,8 +11,7 @@
#ifndef __MLPACK_MVU_H
#define __MLPACK_MVU_H
-#include <fastlib/fastlib.h>
-#include <armadillo>
+#include <mlpack/core.h>
namespace mlpack {
namespace mvu {
Modified: mlpack/trunk/src/mlpack/methods/mvu/mvu_impl.h
===================================================================
--- mlpack/trunk/src/mlpack/methods/mvu/mvu_impl.h 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/mvu/mvu_impl.h 2011-10-29 04:26:38 UTC (rev 10069)
@@ -8,7 +8,7 @@
#ifndef __MLPACK_MVU_IMPL_H
#define __MLPACK_MVU_IMPL_H
-#include <fastlib/optimization/aug_lagrangian/aug_lagrangian.h>
+#include <mlpack/core/optimizers/aug_lagrangian/aug_lagrangian.hpp>
namespace mlpack {
namespace mvu {
Modified: mlpack/trunk/src/mlpack/methods/mvu/mvu_objective_function.h
===================================================================
--- mlpack/trunk/src/mlpack/methods/mvu/mvu_objective_function.h 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/mvu/mvu_objective_function.h 2011-10-29 04:26:38 UTC (rev 10069)
@@ -22,8 +22,7 @@
#ifndef __MLPACK_MVU_OBJECTIVE_FUNCTCLIN_H
#define __MLPACK_MVU_OBJECTIVE_FUNCTCLIN_H
-#include <fastlib/fastlib.h>
-#include <armadillo>
+#include <mlpack/core.h>
namespace mlpack {
namespace mvu {
@@ -42,7 +41,7 @@
*
* max (R * R^T) subject to
* (1) sum (R * R^T) = 0
- * (2) (R R^T)_ii - 2 (R R^T)_ij + (R R^T)_jj = || x_i - x_j ||^2 ;
+ * (2) (R R^T)_ii - 2 (R R^T)_ij + (R R^T)_jj = || x_i - x_j ||^2 ;
* for all (i, j) nearest neighbors
*
* Now, our optimization problem is easier. The total number of constraints is
Modified: mlpack/trunk/src/mlpack/methods/naive_bayes/nbc_main.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/naive_bayes/nbc_main.cc 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/naive_bayes/nbc_main.cc 2011-10-29 04:26:38 UTC (rev 10069)
@@ -78,11 +78,11 @@
const char *training_data_filename = CLI::GetParam<std::string>("nbc/train").c_str();
arma::mat training_data;
- training_data.load(training_data_filename);
+ training_data.load(training_data_filename, arma::auto_detect, false, true);
const char *testing_data_filename = CLI::GetParam<std::string>("nbc/test").c_str();
arma::mat testing_data;
- testing_data.load(testing_data_filename);
+ testing_data.load(testing_data_filename, arma::auto_detect, false, true);
////// SIMPLE NAIVE BAYES CLASSIFICATCLIN ASSUMING THE DATA TO BE UNIFORMLY DISTRIBUTED //////
@@ -110,7 +110,7 @@
////// OUTPUT RESULTS //////
std::string output_filename = CLI::GetParam<std::string>("nbc/output");
- results.save(output_filename.c_str());
+ results.save(output_filename.c_str(), arma::csv_ascii, false, true);
return 1;
}
Modified: mlpack/trunk/src/mlpack/methods/naive_bayes/nbc_test.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/naive_bayes/nbc_test.cc 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/naive_bayes/nbc_test.cc 2011-10-29 04:26:38 UTC (rev 10069)
@@ -8,15 +8,15 @@
using namespace naive_bayes;
BOOST_AUTO_TEST_CASE(SimpleNBCTest) {
- const char* filename_train_ = "trainSet.arff";
- const char* filename_test_ = "testSet.arff";
- const char* train_result_ = "trainRes.arff";
- const char* test_result_ = "testRes.arff";
+ const char* filename_train_ = "trainSet.csv";
+ const char* filename_test_ = "testSet.csv";
+ const char* train_result_ = "trainRes.csv";
+ const char* test_result_ = "testRes.csv";
size_t number_of_classes_ = 2;
arma::mat train_data, train_res, calc_mat;
- train_data.load(filename_train_, arma::auto_detect, true, true);
- train_res.load(train_result_, arma::auto_detect, true, true);
+ train_data.load(filename_train_, arma::auto_detect, false, true);
+ train_res.load(train_result_, arma::auto_detect, false, true);
CLI::GetParam<int>("nbc/classes") = number_of_classes_;
SimpleNaiveBayesClassifier nbc_test_(train_data);
@@ -41,8 +41,9 @@
arma::mat test_data, test_res;
arma::vec test_res_vec, calc_vec;
- test_data.load(filename_test_, arma::auto_detect, true, true);
- test_res.load(test_result_, arma::auto_detect, true, true);
+ test_data.load(filename_test_, arma::auto_detect, false, true);
+ test_res.load(test_result_, arma::auto_detect, false, true);
+
nbc_test_.Classify(test_data, calc_vec);
size_t number_of_datum = test_data.n_cols;
Modified: mlpack/trunk/src/mlpack/methods/nca/nca_main.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/nca/nca_main.cc 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/nca/nca_main.cc 2011-10-29 04:26:38 UTC (rev 10069)
@@ -25,7 +25,8 @@
CLI::ParseCommandLine(argc, argv);
arma::mat data;
- data.load(CLI::GetParam<string>("input_file").c_str());
+ data.load(CLI::GetParam<string>("input_file").c_str(), arma::auto_detect,
+ false, true);
arma::uvec labels(data.n_cols);
for (size_t i = 0; i < data.n_cols; i++)
@@ -39,5 +40,6 @@
nca.LearnDistance(distance);
- distance.save(CLI::GetParam<string>("output_file").c_str());
+ distance.save(CLI::GetParam<string>("output_file").c_str(), arma::csv_ascii,
+ false, true);
}
Modified: mlpack/trunk/src/mlpack/methods/nca/nca_softmax_error_function.h
===================================================================
--- mlpack/trunk/src/mlpack/methods/nca/nca_softmax_error_function.h 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/nca/nca_softmax_error_function.h 2011-10-29 04:26:38 UTC (rev 10069)
@@ -8,8 +8,7 @@
#ifndef __MLPACK_METHODS_NCA_NCA_SOFTMAX_ERROR_FUNCTCLIN_H
#define __MLPACK_METHODS_NCA_NCA_SOFTMAX_ERROR_FUNCTCLIN_H
-#include <armadillo>
-#include <map>
+#include <mlpack/core.h>
namespace mlpack {
namespace nca {
Modified: mlpack/trunk/src/mlpack/methods/neighbor_search/allkfn_main.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/neighbor_search/allkfn_main.cc 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/neighbor_search/allkfn_main.cc 2011-10-29 04:26:38 UTC (rev 10069)
@@ -13,8 +13,6 @@
#include <fstream>
#include <iostream>
-#include <armadillo>
-
using namespace std;
using namespace mlpack;
using namespace mlpack::neighbor;
@@ -52,7 +50,8 @@
arma::Mat<size_t> neighbors;
arma::mat distances;
- if (reference_data.load(reference_file.c_str()) == false)
+ if (!reference_data.load(reference_file.c_str(), arma::auto_detect, false,
+ true))
Log::Fatal << "Reference file " << reference_file << "not found." << endl;
Log::Info << "Loaded reference data from " << reference_file << endl;
@@ -78,7 +77,7 @@
string query_file = CLI::GetParam<string>("query_file");
arma::mat query_data;
- if(query_data.load(query_file.c_str()) == false)
+ if(!query_data.load(query_file.c_str(), arma::auto_detect, false, true))
Log::Fatal << "Query file " << query_file << " not found" << endl;
Log::Info << "Query data loaded from " << query_file << endl;
Modified: mlpack/trunk/src/mlpack/methods/neighbor_search/allkfn_test.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/neighbor_search/allkfn_test.cc 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/neighbor_search/allkfn_test.cc 2011-10-29 04:26:38 UTC (rev 10069)
@@ -323,7 +323,8 @@
arma::mat data_for_tree_;
// Hard-coded filename: bad!
- if (data_for_tree_.load("test_data_3_1000.csv") !=true )
+ if (!data_for_tree_.load("test_data_3_1000.csv", arma::auto_detect, false,
+ true))
BOOST_FAIL("Cannot load test dataset test_data_3_1000.csv!");
// Set up matrices to work with.
@@ -353,7 +354,7 @@
}
}
-/***
+/**
* Test the dual-tree furthest-neighbors method with the naive method. This
* uses only a reference dataset.
*
@@ -364,7 +365,8 @@
// Hard-coded filename: bad!
// Code duplication: also bad!
- if (data_for_tree_.quiet_load("test_data_3_1000.csv") !=true )
+ if (!data_for_tree_.load("test_data_3_1000.csv", arma::auto_detect, false,
+ true))
BOOST_FAIL("Cannot load test dataset test_data_3_1000.csv!");
// Set up matrices to work with (may not be necessary with no ALIAS_MATRIX?).
@@ -392,7 +394,7 @@
}
}
-/***
+/**
* Test the single-tree furthest-neighbors method with the naive method. This
* uses only a reference dataset.
*
@@ -403,7 +405,8 @@
// Hard-coded filename: bad!
// Code duplication: also bad!
- if (data_for_tree_.load("test_data_3_1000.csv") !=true )
+ if (!data_for_tree_.load("test_data_3_1000.csv", arma::auto_detect, false,
+ true))
BOOST_FAIL("Cannot load test dataset test_data_3_1000.csv!");
arma::mat single_query(data_for_tree_);
Modified: mlpack/trunk/src/mlpack/methods/neighbor_search/allknn_main.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/neighbor_search/allknn_main.cc 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/neighbor_search/allknn_main.cc 2011-10-29 04:26:38 UTC (rev 10069)
@@ -13,8 +13,6 @@
#include <fstream>
#include <iostream>
-#include <armadillo>
-
using namespace std;
using namespace mlpack;
using namespace mlpack::neighbor;
@@ -52,7 +50,8 @@
arma::Mat<size_t> neighbors;
arma::mat distances;
- if (reference_data.load(reference_file.c_str()) == false)
+ if (!reference_data.load(reference_file.c_str(), arma::auto_detect, false,
+ true))
Log::Fatal << "Reference file " << reference_file << " not found." << endl;
Log::Info << "Loaded reference data from " << reference_file << endl;
@@ -78,7 +77,7 @@
string query_file = CLI::GetParam<string>("query_file");
arma::mat query_data;
- if (query_data.load(query_file.c_str()) == false)
+ if (!query_data.load(query_file.c_str(), arma::auto_detect, false, true))
Log::Fatal << "Query file " << query_file << " not found" << endl;
Log::Info << "Query data loaded from " << query_file << endl;
Modified: mlpack/trunk/src/mlpack/methods/neighbor_search/allknn_test.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/neighbor_search/allknn_test.cc 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/neighbor_search/allknn_test.cc 2011-10-29 04:26:38 UTC (rev 10069)
@@ -313,7 +313,7 @@
}
}
-/***
+/**
* Test the dual-tree nearest-neighbors method with the naive method. This
* uses both a query and reference dataset.
*
@@ -323,7 +323,8 @@
arma::mat data_for_tree_;
// Hard-coded filename: bad!
- if (data_for_tree_.load("test_data_3_1000.csv") !=true )
+ if (!data_for_tree_.load("test_data_3_1000.csv", arma::auto_detect, false,
+ true))
BOOST_FAIL("Cannot load test dataset test_data_3_1000.csv!");
// Set up matrices to work with.
@@ -356,7 +357,7 @@
}
}
-/***
+/**
* Test the dual-tree nearest-neighbors method with the naive method. This uses
* only a reference dataset.
*
@@ -367,7 +368,8 @@
// Hard-coded filename: bad!
// Code duplication: also bad!
- if (data_for_tree_.load("test_data_3_1000.csv") !=true )
+ if (!data_for_tree_.load("test_data_3_1000.csv", arma::auto_detect, false,
+ true))
BOOST_FAIL("Cannot load test dataset test_data_3_1000.csv!");
// Set up matrices to work with (may not be necessary with no ALIAS_MATRIX?).
@@ -397,7 +399,7 @@
}
}
-/***
+/**
* Test the single-tree nearest-neighbors method with the naive method. This
* uses only a reference dataset.
*
@@ -408,7 +410,8 @@
// Hard-coded filename: bad!
// Code duplication: also bad!
- if (data_for_tree_.load("test_data_3_1000.csv") !=true )
+ if (!data_for_tree_.load("test_data_3_1000.csv", arma::auto_detect, false,
+ true))
BOOST_FAIL("Cannot load test dataset test_data_3_1000.csv!");
// Set up matrices to work with (may not be necessary with no ALIAS_MATRIX?).
Modified: mlpack/trunk/src/mlpack/methods/nnsvm/nnsvm_main.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/nnsvm/nnsvm_main.cpp 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/nnsvm/nnsvm_main.cpp 2011-10-29 04:26:38 UTC (rev 10069)
@@ -47,7 +47,7 @@
std::string trainFile = CLI::GetParam<std::string>("nnsvm/train_data");
// Load training data
arma::mat dataSet;
- if (dataSet.load(trainFile.c_str()) == false) // TODO:param_req
+ if (!dataSet.load(trainFile.c_str(), arma::auto_detect, false, true))
{
/* TODO: eventually, we need better exception handling */
Log::Debug << "Could not open " << trainFile << " for reading" << std::endl;
@@ -74,7 +74,7 @@
/* Load testing data */
std::string testFile = CLI::GetParam<std::string>("nnsvm/test_data");
arma::mat testset;
- if (testset.load(testFile.c_str()) == false)// TODO:param_req
+ if (!testset.load(testFile.c_str(), arma::auto_detect, false, true))
{
/* TODO: eventually, we need better exception handling */
Log::Debug << "Could not open " << testFile << " for reading" <<
Modified: mlpack/trunk/src/mlpack/methods/regression/ridge_main.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/regression/ridge_main.cc 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/regression/ridge_main.cc 2011-10-29 04:26:38 UTC (rev 10069)
@@ -69,12 +69,14 @@
std::string predictions_file = CLI::GetParam<std::string>("ridge/predictions");
arma::mat predictors;
- if (predictors.load(predictors_file.c_str()) == false) {
+ if (predictors.load(predictors_file.c_str(), arma::auto_detect, false, true)
+ == false) {
Log::Fatal << "Unable to open file " << predictors_file << std::endl;
}
arma::mat predictions;
- if (predictions.load(predictions_file.c_str()) == false) {
+ if (predictions.load(predictions_file.c_str(), arma::auto_detect, false, true)
+ == false) {
Log::Fatal << "Unable to open file " << predictions_file << std::endl;
}
@@ -83,15 +85,14 @@
if(mode == "regress") {
-
engine = RidgeRegression(predictors, predictions,
- CLI::GetParam<std::string>("ridge/inversion_method") == "normalsvd");
+ CLI::GetParam<std::string>("ridge/inversion_method") == "normalsvd");
engine.QRRegress(lambda_min);
}
else if(mode == "cvregress") {
Log::Info << "Crossvalidating for the optimal lambda in ["
- << lambda_min << " " << lambda_max << " ] "
- << "by trying " << num_lambdas_to_cv << " values..." << std::endl;
+ << lambda_min << " " << lambda_max << " ] "
+ << "by trying " << num_lambdas_to_cv << " values..." << std::endl;
engine = RidgeRegression(predictors, predictions);
engine.CrossValidatedRegression(lambda_min, lambda_max, num_lambdas_to_cv);
@@ -106,10 +107,14 @@
CLI::GetParam<std::string>("ridge/predictor_indices");
std::string prune_predictor_indices_file =
CLI::GetParam<std::string>("ridge/prune_predictor_indices");
- if (predictor_indices_intermediate.load(predictor_indices_file.c_str()) == false) {
- Log::Fatal << "Unable to open file " << prune_predictor_indices_file << std::endl;
+ if (predictor_indices_intermediate.load(predictor_indices_file.c_str(),
+ arma::auto_detect, false, true) == false) {
+ Log::Fatal << "Unable to open file " << prune_predictor_indices_file
+ << std::endl;
}
- if (prune_predictor_indices_intermediate.load(prune_predictor_indices_file.c_str()) == false) {
+ if (prune_predictor_indices_intermediate.load(
+ prune_predictor_indices_file.c_str(), arma::auto_detect, false, true)
+ == false) {
Log::Fatal << "Unable to open file " << prune_predictor_indices_file << std::endl;
}
@@ -119,9 +124,9 @@
{ // Convert from double rowvec -> size_t colvec
typedef arma::Col<size_t> size_t_vec;
predictor_indices = arma::conv_to<size_t_vec>::
- from(predictor_indices_intermediate.row(0));
+ from(predictor_indices_intermediate.row(0));
prune_predictor_indices = arma::conv_to<size_t_vec>::
- from(prune_predictor_indices_intermediate.row(0));
+ from(prune_predictor_indices_intermediate.row(0));
}
}
@@ -133,8 +138,7 @@
engine.factors(&factors);
std::string factors_file = CLI::GetParam<std::string>("ridge/factors");
Log::Info << "Saving factors..." << std::endl;
- factors.save(factors_file.c_str());
-// data::Save(factors_file.c_str(), factors);
+ factors.save(factors_file.c_str(), arma::csv_ascii, false, true);
return 0;
}
Modified: mlpack/trunk/src/mlpack/methods/svm/svm_main.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/svm/svm_main.cc 2011-10-29 04:18:01 UTC (rev 10068)
+++ mlpack/trunk/src/mlpack/methods/svm/svm_main.cc 2011-10-29 04:26:38 UTC (rev 10069)
@@ -94,7 +94,7 @@
Log::Info << "Training SVM..." << std::endl;
/* Load training data */
- if (dataSet.load(trainFile.c_str()) == false)
+ if (!dataSet.load(trainFile.c_str(), arma::auto_detect, false, true))
return 1;
/* Begin SVM Training | Training and Testing */
@@ -108,7 +108,7 @@
/* Load testing data */
arma::mat dataSet;
std::string testFile = CLI::GetParam<std::string>("svm/test_data");
- if (dataSet.load(testFile.c_str()) == false)
+ if (!dataSet.load(testFile.c_str(), arma::auto_detect, false, true))
return 1;
svm.BatchPredict(learner_typeid, dataSet, "predicted_values");
@@ -123,7 +123,7 @@
/* Load testing data */
arma::mat dataSet;
std::string testFile = CLI::GetParam<std::string>("svm/test_data");
- if (dataSet.load(testFile.c_str()) == false)
+ if (!dataSet.load(testFile.c_str(), arma::auto_detect, false, true))
return 1;
svm.BatchPredict(learner_typeid, dataSet, "predicted_values"); // TODO:param_req
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