[mlpack-svn] r10125 - in mlpack/trunk/src/mlpack/methods: emst fastica hmm infomax_ica linear_regression mog naive_bayes nca neighbor_search nnsvm regression svm
fastlab-svn at coffeetalk-1.cc.gatech.edu
fastlab-svn at coffeetalk-1.cc.gatech.edu
Wed Nov 2 21:21:09 EDT 2011
Author: rcurtin
Date: 2011-11-02 21:21:09 -0400 (Wed, 02 Nov 2011)
New Revision: 10125
Modified:
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/hmm/mixtureDST.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.cpp
mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression_main.cpp
mlpack/trunk/src/mlpack/methods/mog/mog_em_main.cpp
mlpack/trunk/src/mlpack/methods/mog/mog_l2e_main.cpp
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/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 data::Load and data::Save. This should fix our tests being slow.
Modified: mlpack/trunk/src/mlpack/methods/emst/emst_main.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/emst/emst_main.cpp 2011-11-03 00:16:59 UTC (rev 10124)
+++ mlpack/trunk/src/mlpack/methods/emst/emst_main.cpp 2011-11-03 01:21:09 UTC (rev 10125)
@@ -3,10 +3,10 @@
*
* Calls the DualTreeBoruvka algorithm from dtb.h
* Can optionally call Naive Boruvka's method
- *
- * For algorithm details, see:
+ *
+ * For algorithm details, see:
* March, W.B., Ram, P., and Gray, A.G.
- * Fast Euclidean Minimum Spanning Tree: Algorithm, Analysis, Applications.
+ * Fast Euclidean Minimum Spanning Tree: Algorithm, Analysis, Applications.
* In KDD, 2010.
*
* @author Bill March (march at gatech.edu)
@@ -36,40 +36,38 @@
std::string data_file_name = CLI::GetParam<std::string>("emst/input_file");
Log::Info << "Reading in data.\n";
-
+
arma::mat data_points;
- data_points.load(data_file_name.c_str());
-
+ data::Load(data_file_name.c_str(), data_points, true);
+
// Do naive
if (CLI::GetParam<bool>("naive/do_naive")) {
-
+
Log::Info << "Running naive algorithm.\n";
-
+
DualTreeBoruvka naive;
//CLI::GetParam<bool>("naive/do_naive") = true;
-
+
naive.Init(data_points);
-
+
arma::mat naive_results;
naive.ComputeMST(naive_results);
-
+
std::string naive_output_filename =
CLI::GetParam<std::string>("naive/output_file");
-
- naive_results.save(naive_output_filename.c_str(), arma::csv_ascii, false,
- true);
-
+
+ data::Save(naive_output_filename.c_str(), naive_results, true);
}
else {
-
+
Log::Info << "Data read, building tree.\n";
/////////////// Initialize DTB //////////////////////
DualTreeBoruvka dtb;
dtb.Init(data_points);
-
+
Log::Info << "Tree built, running algorithm.\n\n";
-
+
////////////// Run DTB /////////////////////
arma::mat results;
@@ -81,8 +79,7 @@
std::string output_filename =
CLI::GetParam<std::string>("emst/output_file");
- results.save(output_filename.c_str(), arma::csv_ascii, false, true);
-
+ data::Save(output_filename.c_str(), results, true);
}
return 0;
Modified: mlpack/trunk/src/mlpack/methods/fastica/fastica_main.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/fastica/fastica_main.cpp 2011-11-03 00:16:59 UTC (rev 10124)
+++ mlpack/trunk/src/mlpack/methods/fastica/fastica_main.cpp 2011-11-03 01:21:09 UTC (rev 10125)
@@ -57,7 +57,7 @@
CLI::ParseCommandLine(argc, argv);
const char* data = CLI::GetParam<std::string>("fastica/input_file").c_str();
- X.load(data, arma::auto_detect, false, true);
+ data::Load(data, X);
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, arma::csv_ascii, false, true);
+ data::Save(ic_filename, Y, true);
arma::mat Z = trans(W);
- Z.save(unmixing_filename, arma::csv_ascii, false, true);
+ data::Save(unmixing_filename, Z, 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 2011-11-03 00:16:59 UTC (rev 10124)
+++ mlpack/trunk/src/mlpack/methods/fastica/lin_alg_test.cpp 2011-11-03 01:21:09 UTC (rev 10125)
@@ -84,7 +84,7 @@
// We are loading a matrix from an external file... bad choice.
mat tmp, tmp_centered, whitened, whitening_matrix;
- tmp.load("trainSet.csv", arma::auto_detect, false, true);
+ data::Load("trainSet.csv", tmp);
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.csv", arma::auto_detect, false, true);
+ data::Load("fake.csv", tmp);
Orthogonalize(tmp, orth);
// test orthogonality
Modified: mlpack/trunk/src/mlpack/methods/hmm/mixtureDST.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/hmm/mixtureDST.cpp 2011-11-03 00:16:59 UTC (rev 10124)
+++ mlpack/trunk/src/mlpack/methods/hmm/mixtureDST.cpp 2011-11-03 01:21:09 UTC (rev 10125)
@@ -75,14 +75,14 @@
void MixtureGauss::InitFromFile(const char* mean_fn, const char* covs_fn, const char* prior_fn) {
arma::mat meansmat;
- meansmat.load(mean_fn, arma::auto_detect, false, true);
+ data::Load(mean_fn, meansmat);
mat2arrlst(meansmat, means);
size_t N = means[0].n_elem;
size_t K = means.size();
if (covs_fn != NULL) {
arma::mat covsmat;
- covsmat.load(covs_fn, arma::auto_detect, false, true);
+ data::Load(covs_fn, covsmat);
mat2arrlstmat(N, covsmat, covs);
mlpack::Log::Assert(K == covs.size(), "MixtureGauss::InitFromFile(): sizes do not match!");
@@ -100,7 +100,7 @@
if (prior_fn != NULL) {
arma::mat priormat;
- priormat.load(prior_fn, arma::auto_detect, false, true);
+ data::Load(prior_fn, priormat);
mlpack::Log::Assert(K == priormat.n_cols, "MixtureGauss::InitFromFile(): sizes do not match!");
Modified: mlpack/trunk/src/mlpack/methods/infomax_ica/infomax_ica_test.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/infomax_ica/infomax_ica_test.cc 2011-11-03 00:16:59 UTC (rev 10124)
+++ mlpack/trunk/src/mlpack/methods/infomax_ica/infomax_ica_test.cc 2011-11-03 01:21:09 UTC (rev 10125)
@@ -22,7 +22,7 @@
int bb_ = 5;
double epsilonb_ = 0.001;
- testdatab_.load("fake.csv", arma::auto_detect, false, true);
+ data::Load("fake.csv", testdatab_);
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.csv", arma::auto_detect, false, true);
+ data::Load("fake.csv", testdata_);
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.csv", arma::auto_detect, false, true);
+ data::Load("fake.csv", testdata_);
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 2011-11-03 00:16:59 UTC (rev 10124)
+++ mlpack/trunk/src/mlpack/methods/infomax_ica/main.cc 2011-11-03 01:21:09 UTC (rev 10125)
@@ -22,7 +22,7 @@
double epsilon = CLI::GetParam<double>("info/epsilon");
arma::mat dataset;
- dataset.load(data_file_name, arma::auto_detect, false, true);
+ data::Load(data_file_name, dataset, true);
InfomaxICA ica(lambda, B, epsilon);
ica.applyICA(dataset);
Modified: mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression.cpp 2011-11-03 00:16:59 UTC (rev 10124)
+++ mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression.cpp 2011-11-03 01:21:09 UTC (rev 10125)
@@ -46,7 +46,7 @@
for(size_t j = 0; j < n_cols; ++j)
{
predictions(j) += parameters(i) * points(i-1,j);
-
+
}
}
}
@@ -59,12 +59,12 @@
bool LinearRegression::load(const std::string& filename)
{
- return parameters.load(filename);
+ return data::Load(filename, parameters);
}
bool LinearRegression::save(const std::string& filename)
{
- return parameters.save(filename);
+ return data::Save(filename, parameters);
}
}; // namespace linear_regression
Modified: mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression_main.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression_main.cpp 2011-11-03 00:16:59 UTC (rev 10124)
+++ mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression_main.cpp 2011-11-03 01:21:09 UTC (rev 10125)
@@ -30,7 +30,7 @@
const std::string response_name =
CLI::GetParam<std::string>("linear_regression/responses");
- file.load(train_name.c_str(), arma::auto_detect, false, true);
+ data::Load(train_name.c_str(), file, true);
size_t n_cols = file.n_cols,
n_rows = file.n_rows;
@@ -45,7 +45,7 @@
{
predictors = file;
// The initial predictors for y, Nx1
- responses.load(response_name.c_str(), arma::auto_detect, false, true);
+ data::Load(response_name.c_str(), responses, true);
if(responses.n_rows > 1)
{
std::cerr << "Error: The responses must have one column.\n";
@@ -59,7 +59,7 @@
}
}
- points.load(test_name.c_str(), arma::auto_detect, false, true);
+ data::Load(test_name.c_str(), points, true);
if(points.n_rows != n_rows)
{
std::cerr << "Error: The test data must have the same number of cols as\
Modified: mlpack/trunk/src/mlpack/methods/mog/mog_em_main.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/mog/mog_em_main.cpp 2011-11-03 00:16:59 UTC (rev 10124)
+++ mlpack/trunk/src/mlpack/methods/mog/mog_em_main.cpp 2011-11-03 01:21:09 UTC (rev 10125)
@@ -39,8 +39,7 @@
////// READING PARAMETERS AND LOADING DATA //////
arma::mat data_points;
- data_points.load(CLI::GetParam<std::string>("mog/data").c_str(),
- arma::auto_detect, false, true);
+ data::Load(CLI::GetParam<std::string>("mog/data").c_str(), data_points, true);
////// MIXTURE OF GAUSSIANS USING EM //////
MoGEM mog;
Modified: mlpack/trunk/src/mlpack/methods/mog/mog_l2e_main.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/mog/mog_l2e_main.cpp 2011-11-03 00:16:59 UTC (rev 10124)
+++ mlpack/trunk/src/mlpack/methods/mog/mog_l2e_main.cpp 2011-11-03 01:21:09 UTC (rev 10125)
@@ -40,8 +40,8 @@
////// READING PARAMETERS AND LOADING DATA //////
arma::mat data_points;
- data_points.load(CLI::GetParam<std::string>("mog_l2e/data").c_str(),
- arma::auto_detect, false, true);
+ data::Load(CLI::GetParam<std::string>("mog_l2e/data").c_str(), data_points,
+ true);
////// MIXTURE OF GAUSSIANS USING L2 ESTIMATCLIN //////
size_t number_of_gaussians = CLI::GetParam<int>("mog_l2e/k");
Modified: mlpack/trunk/src/mlpack/methods/naive_bayes/nbc_main.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/naive_bayes/nbc_main.cc 2011-11-03 00:16:59 UTC (rev 10124)
+++ mlpack/trunk/src/mlpack/methods/naive_bayes/nbc_main.cc 2011-11-03 01:21:09 UTC (rev 10125)
@@ -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, arma::auto_detect, false, true);
+ data::Load(training_data_filename, training_data, true);
const char *testing_data_filename = CLI::GetParam<std::string>("nbc/test").c_str();
arma::mat testing_data;
- testing_data.load(testing_data_filename, arma::auto_detect, false, true);
+ data::Load(testing_data_filename, testing_data, 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(), arma::csv_ascii, false, true);
+ data::Save(output_filename.c_str(), results, true);
return 1;
}
Modified: mlpack/trunk/src/mlpack/methods/naive_bayes/nbc_test.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/naive_bayes/nbc_test.cc 2011-11-03 00:16:59 UTC (rev 10124)
+++ mlpack/trunk/src/mlpack/methods/naive_bayes/nbc_test.cc 2011-11-03 01:21:09 UTC (rev 10125)
@@ -15,8 +15,8 @@
size_t number_of_classes_ = 2;
arma::mat train_data, train_res, calc_mat;
- train_data.load(filename_train_, arma::auto_detect, false, true);
- train_res.load(train_result_, arma::auto_detect, false, true);
+ data::Load(filename_train_, train_data, true);
+ data::Load(train_result_, train_res, true);
CLI::GetParam<int>("nbc/classes") = number_of_classes_;
SimpleNaiveBayesClassifier nbc_test_(train_data);
@@ -41,8 +41,8 @@
arma::mat test_data, test_res;
arma::vec test_res_vec, calc_vec;
- test_data.load(filename_test_, arma::auto_detect, false, true);
- test_res.load(test_result_, arma::auto_detect, false, true);
+ data::Load(filename_test_, test_data, true);
+ data::Load(test_result_, test_res, true);
nbc_test_.Classify(test_data, calc_vec);
Modified: mlpack/trunk/src/mlpack/methods/nca/nca_main.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/nca/nca_main.cc 2011-11-03 00:16:59 UTC (rev 10124)
+++ mlpack/trunk/src/mlpack/methods/nca/nca_main.cc 2011-11-03 01:21:09 UTC (rev 10125)
@@ -25,8 +25,7 @@
CLI::ParseCommandLine(argc, argv);
arma::mat data;
- data.load(CLI::GetParam<string>("input_file").c_str(), arma::auto_detect,
- false, true);
+ data::Load(CLI::GetParam<string>("input_file").c_str(), data, true);
arma::uvec labels(data.n_cols);
for (size_t i = 0; i < data.n_cols; i++)
@@ -40,6 +39,5 @@
nca.LearnDistance(distance);
- distance.save(CLI::GetParam<string>("output_file").c_str(), arma::csv_ascii,
- false, true);
+ data::Save(CLI::GetParam<string>("output_file").c_str(), distance, true);
}
Modified: mlpack/trunk/src/mlpack/methods/neighbor_search/allkfn_main.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/neighbor_search/allkfn_main.cc 2011-11-03 00:16:59 UTC (rev 10124)
+++ mlpack/trunk/src/mlpack/methods/neighbor_search/allkfn_main.cc 2011-11-03 01:21:09 UTC (rev 10125)
@@ -50,8 +50,7 @@
arma::Mat<size_t> neighbors;
arma::mat distances;
- if (!reference_data.load(reference_file.c_str(), arma::auto_detect, false,
- true))
+ if (!data::Load(reference_file.c_str(), reference_data))
Log::Fatal << "Reference file " << reference_file << "not found." << endl;
Log::Info << "Loaded reference data from " << reference_file << endl;
@@ -67,8 +66,8 @@
// Sanity check on leaf size.
if (CLI::GetParam<int>("tree/leaf_size") <= 0) {
- Log::Fatal << "Invalid leaf size: " << CLI::GetParam<int>("allknn/leaf_size")
- << endl;
+ Log::Fatal << "Invalid leaf size: "
+ << CLI::GetParam<int>("allknn/leaf_size") << endl;
}
AllkFN* allkfn = NULL;
@@ -77,7 +76,7 @@
string query_file = CLI::GetParam<string>("query_file");
arma::mat query_data;
- if(!query_data.load(query_file.c_str(), arma::auto_detect, false, true))
+ if (!data::Load(query_file.c_str(), query_data))
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 2011-11-03 00:16:59 UTC (rev 10124)
+++ mlpack/trunk/src/mlpack/methods/neighbor_search/allkfn_test.cc 2011-11-03 01:21:09 UTC (rev 10125)
@@ -323,8 +323,7 @@
arma::mat data_for_tree_;
// Hard-coded filename: bad!
- if (!data_for_tree_.load("test_data_3_1000.csv", arma::auto_detect, false,
- true))
+ if (!data::Load("test_data_3_1000.csv", data_for_tree_))
BOOST_FAIL("Cannot load test dataset test_data_3_1000.csv!");
// Set up matrices to work with.
@@ -365,8 +364,7 @@
// Hard-coded filename: bad!
// Code duplication: also bad!
- if (!data_for_tree_.load("test_data_3_1000.csv", arma::auto_detect, false,
- true))
+ if (!data::Load("test_data_3_1000.csv", data_for_tree_))
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?).
@@ -405,8 +403,7 @@
// Hard-coded filename: bad!
// Code duplication: also bad!
- if (!data_for_tree_.load("test_data_3_1000.csv", arma::auto_detect, false,
- true))
+ if (!data::Load("test_data_3_1000.csv", data_for_tree_))
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 2011-11-03 00:16:59 UTC (rev 10124)
+++ mlpack/trunk/src/mlpack/methods/neighbor_search/allknn_main.cc 2011-11-03 01:21:09 UTC (rev 10125)
@@ -50,8 +50,7 @@
arma::Mat<size_t> neighbors;
arma::mat distances;
- if (!reference_data.load(reference_file.c_str(), arma::auto_detect, false,
- true))
+ if (!data::Load(reference_file.c_str(), reference_data))
Log::Fatal << "Reference file " << reference_file << " not found." << endl;
Log::Info << "Loaded reference data from " << reference_file << endl;
@@ -77,7 +76,7 @@
string query_file = CLI::GetParam<string>("query_file");
arma::mat query_data;
- if (!query_data.load(query_file.c_str(), arma::auto_detect, false, true))
+ if (!data::Load(query_file.c_str(), query_data))
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 2011-11-03 00:16:59 UTC (rev 10124)
+++ mlpack/trunk/src/mlpack/methods/neighbor_search/allknn_test.cc 2011-11-03 01:21:09 UTC (rev 10125)
@@ -323,8 +323,7 @@
arma::mat data_for_tree_;
// Hard-coded filename: bad!
- if (!data_for_tree_.load("test_data_3_1000.csv", arma::auto_detect, false,
- true))
+ if (!data::Load("test_data_3_1000.csv", data_for_tree_))
BOOST_FAIL("Cannot load test dataset test_data_3_1000.csv!");
// Set up matrices to work with.
@@ -368,8 +367,7 @@
// Hard-coded filename: bad!
// Code duplication: also bad!
- if (!data_for_tree_.load("test_data_3_1000.csv", arma::auto_detect, false,
- true))
+ if (!data::Load("test_data_3_1000.csv", data_for_tree_))
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?).
@@ -410,8 +408,7 @@
// Hard-coded filename: bad!
// Code duplication: also bad!
- if (!data_for_tree_.load("test_data_3_1000.csv", arma::auto_detect, false,
- true))
+ if (!data::Load("test_data_3_1000.csv", data_for_tree_))
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 2011-11-03 00:16:59 UTC (rev 10124)
+++ mlpack/trunk/src/mlpack/methods/nnsvm/nnsvm_main.cpp 2011-11-03 01:21:09 UTC (rev 10125)
@@ -47,12 +47,8 @@
std::string trainFile = CLI::GetParam<std::string>("nnsvm/train_data");
// Load training data
arma::mat dataSet;
- 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;
+ if (!data::Load(trainFile.c_str(), dataSet))
return 1;
- }
// Begin NNSVM Training
if (kernel == "linear")
@@ -74,13 +70,9 @@
/* Load testing data */
std::string testFile = CLI::GetParam<std::string>("nnsvm/test_data");
arma::mat testset;
- 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" <<
- std::endl;
+ if (!data::Load(testFile.c_str(), testset))
return 1;
- }
+
nnsvm.BatchClassify(testset, "testlabels");
}
}
Modified: mlpack/trunk/src/mlpack/methods/regression/ridge_main.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/regression/ridge_main.cc 2011-11-03 00:16:59 UTC (rev 10124)
+++ mlpack/trunk/src/mlpack/methods/regression/ridge_main.cc 2011-11-03 01:21:09 UTC (rev 10125)
@@ -69,14 +69,14 @@
std::string predictions_file = CLI::GetParam<std::string>("ridge/predictions");
arma::mat predictors;
- if (predictors.load(predictors_file.c_str(), arma::auto_detect, false, true)
- == false) {
+ if (!data::Load(predictors_file.c_str(), predictors))
+ {
Log::Fatal << "Unable to open file " << predictors_file << std::endl;
}
arma::mat predictions;
- if (predictions.load(predictions_file.c_str(), arma::auto_detect, false, true)
- == false) {
+ if (!data::Load(predictions_file.c_str(), predictions))
+ {
Log::Fatal << "Unable to open file " << predictions_file << std::endl;
}
@@ -107,14 +107,15 @@
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(),
- arma::auto_detect, false, true) == false) {
+ if (!data::Load(predictor_indices_file.c_str(),
+ predictor_indices_intermediate))
+ {
Log::Fatal << "Unable to open file " << prune_predictor_indices_file
<< std::endl;
}
- if (prune_predictor_indices_intermediate.load(
- prune_predictor_indices_file.c_str(), arma::auto_detect, false, true)
- == false) {
+ if (!data::Load(prune_predictor_indices_file.c_str(),
+ prune_predictor_indices_intermediate))
+ {
Log::Fatal << "Unable to open file " << prune_predictor_indices_file << std::endl;
}
@@ -138,7 +139,7 @@
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(), arma::csv_ascii, false, true);
+ data::Save(factors_file.c_str(), factors, true);
return 0;
}
Modified: mlpack/trunk/src/mlpack/methods/svm/svm_main.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/svm/svm_main.cc 2011-11-03 00:16:59 UTC (rev 10124)
+++ mlpack/trunk/src/mlpack/methods/svm/svm_main.cc 2011-11-03 01:21:09 UTC (rev 10125)
@@ -94,7 +94,7 @@
Log::Info << "Training SVM..." << std::endl;
/* Load training data */
- if (!dataSet.load(trainFile.c_str(), arma::auto_detect, false, true))
+ if (!data::Load(trainFile.c_str(), dataSet))
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(), arma::auto_detect, false, true))
+ if (!data::Load(testFile.c_str(), dataSet))
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(), arma::auto_detect, false, true))
+ if (!data::Load(testFile.c_str(), dataSet))
return 1;
svm.BatchPredict(learner_typeid, dataSet, "predicted_values"); // TODO:param_req
@@ -138,7 +138,7 @@
/* Load testing data */
arma::mat dataSet;
std::string testFile = CLI::GetParam<std::string>("svm/test_data");
- if (dataSet.load(testFile.c_str()) == false)
+ if (!data::Load(testFile.c_str(), dataSet))
return 1;
/* Begin Prediction */
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