Added a wrapper for the t-SNE DR method; added an integration test fo…

…r it (black-listed for now).

examples/undocumented/python_modular/converter_tdistributedstochasticneighborembedding_modular.py

@@ -0,0 +1,27 @@
+#!/usr/bin/env python
+from tools.load import LoadMatrix
+
+lm=LoadMatrix()
+data = lm.load_numbers('../data/fm_train_real.dat')
+
+parameter_list = [[data]]
+
+def converter_tdistributedstochasticneighborembedding_modular(data):
+	try:
+		from shogun.Features import RealFeatures
+		from shogun.Converter import TDistributedStochasticNeighborEmbedding
+
+		features = RealFeatures(data)
+
+		converter = TDistributedStochasticNeighborEmbedding()
+		converter.set_target_dim(2)
+
+		embedding = converter.apply(features)
+
+		return embedding
+	except ImportError:
+		print('No Eigen3 available')
+
+if __name__=='__main__':
+	print('TDistributedStochasticNeighborEmbedding')
+	converter_tdistributedstochasticneighborembedding_modular(*parameter_list[0])

src/interfaces/modular/Converter.i

@@ -22,6 +22,7 @@
 %rename(Isomap) CIsomap;
 %rename(StochasticProximityEmbedding) CStochasticProximityEmbedding;
 %rename(FactorAnalysis) CFactorAnalysis;
+%rename (TDistributedStochasticNeighborEmbedding) CTDistributedStochasticNeighborEmbedding;
 
 %newobject shogun::CEmbeddingConverter::apply;
 %newobject shogun::*::embed_kernel;
@@ -42,3 +43,4 @@
 %include <shogun/converter/Isomap.h>
 %include <shogun/converter/StochasticProximityEmbedding.h>
 %include <shogun/converter/FactorAnalysis.h>
+%include <shogun/converter/TDistributedStochasticNeighborEmbedding.h>

src/interfaces/modular/Converter_includes.i

@@ -14,4 +14,5 @@
 #include <shogun/converter/Isomap.h>
 #include <shogun/converter/StochasticProximityEmbedding.h>
 #include <shogun/converter/FactorAnalysis.h>
+#include <shogun/converter/TDistributedStochasticNeighborEmbedding.h>
 %}

tests/integration/python_modular/generator.py

@@ -7,6 +7,7 @@
 example_dir = '../../../examples/undocumented/python_modular'
 test_dir = '../../../tests/integration/tests'
 blacklist = ("__init__.py", "classifier_libsvm_minimal_modular.py",
+		"converter_tdistributedstochasticneighborembedding_modular.py",
 		"kernel_combined_modular.py",
 		"kernel_distance_modular.py",
 		"distribution_hmm_modular.py",