More swig cleanup (#5064)

* remove kernel normalizer * cleanup library.i * cleanup features.i * Removed string kernels from interface
shogun-toolbox · Jul 3, 2020 · f751f94 · f751f94
1 parent 3899822
commit f751f94
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Showing 142 changed files with 1,123 additions and 2,217 deletions.
diff --git a/data b/data
diff --git a/doc/ipython-notebooks/classification/MKL.ipynb b/doc/ipython-notebooks/classification/MKL.ipynb
@@ -686,20 +686,20 @@
     "labels_rem = sg.MulticlassLabels(Yrem)\n",
     "\n",
     "kernel = sg.create_kernel(\"CombinedKernel\")\n",
-    "feats_train = sg.CombinedFeatures()\n",
-    "feats_test = sg.CombinedFeatures()\n",
+    "feats_train = sg.create_features(\"CombinedFeatures\")\n",
+    "feats_test = sg.create_features(\"CombinedFeatures\")\n",
     "\n",
     "#append gaussian kernel\n",
     "subkernel = sg.create_kernel(\"GaussianKernel\", log_width=np.log(15))\n",
-    "feats_train.append_feature_obj(feats)\n",
-    "feats_test.append_feature_obj(feats_rem)\n",
+    "feats_train.add(\"feature_array\", feats)\n",
+    "feats_test.add(\"feature_array\", feats_rem)\n",
     "kernel.add(\"kernel_array\", subkernel)\n",
     "\n",
     "#append PolyKernel\n",
     "feats  = sg.create_features(Xtrain)\n",
     "subkernel = sg.create_kernel('PolyKernel', degree=10, c=2)\n",
-    "feats_train.append_feature_obj(feats)\n",
-    "feats_test.append_feature_obj(feats_rem)\n",
+    "feats_train.add(\"feature_array\", feats)\n",
+    "feats_test.add(\"feature_array\", feats_rem)\n",
     "kernel.add(\"kernel_array\", subkernel)\n",
     "\n",
     "kernel.init(feats_train, feats_train)\n",
@@ -846,26 +846,26 @@
     "feats_out=sg.create_features(x_out)\n",
     "\n",
     "kernel=sg.create_kernel(\"CombinedKernel\")\n",
-    "feats_train=sg.CombinedFeatures()\n",
-    "feats_test=sg.CombinedFeatures()\n",
-    "feats_test_out=sg.CombinedFeatures()\n",
-    "feats_grid=sg.CombinedFeatures()\n",
+    "feats_train=sg.create_features(\"CombinedFeatures\")\n",
+    "feats_test=sg.create_features(\"CombinedFeatures\")\n",
+    "feats_test_out=sg.create_features(\"CombinedFeatures\")\n",
+    "feats_grid=sg.create_features(\"CombinedFeatures\")\n",
     "\n",
     "#append gaussian kernel\n",
     "subkernel=sg.create_kernel(\"GaussianKernel\", log_width=np.log(8))\n",
-    "feats_train.append_feature_obj(feats)\n",
-    "feats_test.append_feature_obj(feats_t)\n",
-    "feats_test_out.append_feature_obj(feats_out)\n",
-    "feats_grid.append_feature_obj(grid)\n",
+    "feats_train.add(\"feature_array\", feats)\n",
+    "feats_test.add(\"feature_array\", feats_t)\n",
+    "feats_test_out.add(\"feature_array\", feats_out)\n",
+    "feats_grid.add(\"feature_array\", grid)\n",
     "kernel.add(\"kernel_array\", subkernel)\n",
     "\n",
     "#append PolyKernel\n",
     "feats  = sg.create_features(traindata)\n",
     "subkernel = sg.create_kernel('PolyKernel', degree=10, c=3)\n",
-    "feats_train.append_feature_obj(feats)\n",
-    "feats_test.append_feature_obj(feats_t)\n",
-    "feats_test_out.append_feature_obj(feats_out)\n",
-    "feats_grid.append_feature_obj(grid)\n",
+    "feats_train.add(\"feature_array\", feats)\n",
+    "feats_test.add(\"feature_array\", feats_t)\n",
+    "feats_test_out.add(\"feature_array\", feats_out)\n",
+    "feats_grid.add(\"feature_array\", grid)\n",
     "kernel.add(\"kernel_array\", subkernel)\n",
     "\n",
     "kernel.init(feats_train, feats_train)\n",
@@ -985,7 +985,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.7.1"
   }
  },
  "nbformat": 4,

diff --git a/doc/ipython-notebooks/intro/Introduction.ipynb b/doc/ipython-notebooks/intro/Introduction.ipynb
@@ -102,7 +102,7 @@
    "outputs": [],
    "source": [
     "#Load the file\n",
-    "data_file=sg.LibSVMFile(os.path.join(SHOGUN_DATA_DIR, 'uci/diabetes/diabetes_scale.svm'))"
+    "data_file=sg.read_libsvm(os.path.join(SHOGUN_DATA_DIR, 'uci/diabetes/diabetes_scale.svm'))"
    ]
   },
   {
@@ -542,8 +542,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "temp_feats = sg.create_features(sg.CSVFile(os.path.join(SHOGUN_DATA_DIR, 'uci/housing/fm_housing.dat')))\n",
-    "labels=sg.create_labels(sg.CSVFile(os.path.join(SHOGUN_DATA_DIR, 'uci/housing/housing_label.dat')))\n",
+    "temp_feats = sg.create_features(sg.read_csv(os.path.join(SHOGUN_DATA_DIR, 'uci/housing/fm_housing.dat')))\n",
+    "labels=sg.create_labels(sg.read_csv(os.path.join(SHOGUN_DATA_DIR, 'uci/housing/housing_label.dat')))\n",
     "\n",
     "#rescale to 0...1\n",
     "preproc=sg.create_transformer(\"RescaleFeatures\")\n",

diff --git a/doc/ipython-notebooks/metric/LMNN.ipynb b/doc/ipython-notebooks/metric/LMNN.ipynb
@@ -452,8 +452,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ape_features = sg.create_features(sg.CSVFile(os.path.join(SHOGUN_DATA_DIR, 'multiclass/fm_ape_gut.dat')))\n",
-    "ape_labels = sg.create_labels(sg.CSVFile(os.path.join(SHOGUN_DATA_DIR, 'multiclass/label_ape_gut.dat')))"
+    "ape_features = sg.create_features(sg.read_csv(os.path.join(SHOGUN_DATA_DIR, 'multiclass/fm_ape_gut.dat')))\n",
+    "ape_labels = sg.create_labels(sg.read_csv(os.path.join(SHOGUN_DATA_DIR, 'multiclass/label_ape_gut.dat')))"
    ]
   },
   {
@@ -619,7 +619,7 @@
    "outputs": [],
    "source": [
     "statistics = lmnn.get_statistics()\n",
-    "plt.plot(statistics.obj.get())\n",
+    "plt.plot(statistics.get(\"obj\"))\n",
     "plt.grid(True)\n",
     "plt.xlabel('Number of iterations')\n",
     "plt.ylabel('LMNN objective')\n",
@@ -660,8 +660,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "wine_features = sg.create_features(sg.CSVFile(os.path.join(SHOGUN_DATA_DIR, 'uci/wine/fm_wine.dat')))\n",
-    "wine_labels = sg.create_labels(sg.CSVFile(os.path.join(SHOGUN_DATA_DIR, 'uci/wine/label_wine.dat')))\n",
+    "wine_features = sg.create_features(sg.read_csv(os.path.join(SHOGUN_DATA_DIR, 'uci/wine/fm_wine.dat')))\n",
+    "wine_labels = sg.create_labels(sg.read_csv(os.path.join(SHOGUN_DATA_DIR, 'uci/wine/label_wine.dat')))\n",
     "\n",
     "assert(wine_features.get(\"num_vectors\") == wine_labels.get(\"num_labels\"))\n",
     "print('%d feature vectors with %d features from %d different classes.' % (wine_features.get(\"num_vectors\"), \\\n",

diff --git a/doc/ipython-notebooks/multiclass/Tree/DecisionTrees.ipynb b/doc/ipython-notebooks/multiclass/Tree/DecisionTrees.ipynb
@@ -1539,8 +1539,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "train_feats = sg.create_features(sg.CSVFile( os.path.join(SHOGUN_DATA_DIR, 'uci/wine/fm_wine.dat')))\n",
-    "train_labels = sg.create_labels(sg.CSVFile( os.path.join(SHOGUN_DATA_DIR, 'uci/wine/label_wine.dat')))"
+    "train_feats = sg.create_features(sg.read_csv( os.path.join(SHOGUN_DATA_DIR, 'uci/wine/fm_wine.dat')))\n",
+    "train_labels = sg.create_labels(sg.read_csv( os.path.join(SHOGUN_DATA_DIR, 'uci/wine/label_wine.dat')))"
    ]
   },
   {
@@ -1616,8 +1616,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "train_feats=sg.create_features(sg.CSVFile( os.path.join(SHOGUN_DATA_DIR, 'uci/housing/fm_housing.dat')))\n",
-    "train_labels=sg.create_labels(sg.CSVFile( os.path.join(SHOGUN_DATA_DIR, 'uci/housing/housing_label.dat')))\n",
+    "train_feats=sg.create_features(sg.read_csv( os.path.join(SHOGUN_DATA_DIR, 'uci/housing/fm_housing.dat')))\n",
+    "train_labels=sg.create_labels(sg.read_csv( os.path.join(SHOGUN_DATA_DIR, 'uci/housing/housing_label.dat')))\n",
     "\n",
     "# print range of regression labels - this is useful for calculating relative deviation later \n",
     "print('labels range : '+str(np.ptp(train_labels.get(\"labels\"))))"

diff --git a/doc/ipython-notebooks/multiclass/Tree/TreeEnsemble.ipynb b/doc/ipython-notebooks/multiclass/Tree/TreeEnsemble.ipynb
@@ -63,8 +63,8 @@
     "%matplotlib inline\n",
     "\n",
     "def load_file(feat_file,label_file):\n",
-    "    feats=sg.create_features(sg.CSVFile(feat_file))\n",
-    "    labels=sg.create_labels(sg.CSVFile(label_file))\n",
+    "    feats=sg.create_features(sg.read_csv(feat_file))\n",
+    "    labels=sg.create_labels(sg.read_csv(label_file))\n",
     "    return (feats, labels)\n",
     "\n",
     "trainfeat_file=os.path.join(SHOGUN_DATA_DIR, 'uci/letter/train_fm_letter.dat')\n",

diff --git a/doc/ipython-notebooks/regression/Regression.ipynb b/doc/ipython-notebooks/regression/Regression.ipynb
@@ -647,8 +647,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "feats = sg.create_features(sg.CSVFile(os.path.join(SHOGUN_DATA_DIR, 'uci/housing/fm_housing.dat')))\n",
-    "train_labels = sg.create_labels(sg.CSVFile(os.path.join(SHOGUN_DATA_DIR, 'uci/housing/housing_label.dat')))\n",
+    "feats = sg.create_features(sg.read_csv(os.path.join(SHOGUN_DATA_DIR, 'uci/housing/fm_housing.dat')))\n",
+    "train_labels = sg.create_labels(sg.read_csv(os.path.join(SHOGUN_DATA_DIR, 'uci/housing/housing_label.dat')))\n",
     "mat = feats.get('feature_matrix')\n",
     "\n",
     "crime_rate = mat[0]\n",

diff --git a/examples/meta/generator/targets/cpp.json b/examples/meta/generator/targets/cpp.json
@@ -148,9 +148,8 @@
             "create_evaluation_result": "create<EvaluationResult>($arguments)",
             "create_distribution": "create<Distribution>($arguments)",
             "create_combination_rule": "create<CombinationRule>($arguments)",
-            "create_int_string_features": "create<StringFeatures<uint16_t>>($arguments)",
+            "create_string_features": "details::string_features($arguments)",
             "create_subset_features": "create<DenseSubsetFeatures<float64_t>>($arguments)",
-            "create_char_string_features": " create<StringFeatures<char>>($arguments)",
             "create_gaussian_process": "create<GaussianProcess>($arguments)"
         },
         "Identifier": "$identifier",

diff --git a/examples/meta/generator/targets/csharp.json b/examples/meta/generator/targets/csharp.json
@@ -11,6 +11,7 @@
             "Separator": ";\n",
             "InitialSeperatorWhenArgs>0": false
         },
+        "BoolVector": "var $name = new byte[$arguments]",
         "CharVector": "var $name = new char[$arguments]",
         "ByteVector": "var $name = new byte[$arguments]",
         "WordVector": "var $name = new ushort[$arguments]",
@@ -21,6 +22,7 @@
         "RealVector": "var $name = new double[$arguments]",
         "LongRealVector": "var $name = new double[$arguments]",
         "ComplexVector": "var $name = new Complex[$arguments]",
+        "BoolMatrix": "var $name = new byte[$arguments]",
         "CharMatrix": "var $name = new char[$arguments]",
         "ByteMatrix": "var $name = new byte[$arguments]",
         "WordMatrix": "var $name = new ushort[$arguments]",
@@ -33,7 +35,7 @@
         "ComplexMatrix": "var $name = new Complex[$arguments]"
     },
     "ListInit": {
-        "BoolVector": "var $name = new bool[] {$arguments}",
+        "BoolVector": "var $name = new byte[] {$arguments}",
         "CharVector": "var $name = new char[] {$arguments}",
         "ByteVector": "var $name = new byte[] {$arguments}",
         "WordVector": "var $name = new ushort[] {$arguments}",
@@ -101,14 +103,14 @@
         "Access": {
             "Vector": "$identifier[$indices]",
             "Matrix": "$identifier[$indices]",
-            "BoolVector": "$identifier.get_element($indices)",
-            "BoolMatrix": "$identifier.get_element($indices)"
+            "BoolVector": "$identifier[$indices] == 1 ? true : false",
+            "BoolMatrix": "$identifier[$indices] == 1 ? true : false"
         },
         "Assign": {
             "Vector": "$identifier[$indices] = $expr",
             "Matrix": "$identifier[$indices] = $expr",
-            "BoolVector": "$identifier.set_element($expr, $indices)",
-            "BoolMatrix": "$identifier.set_element($expr, $indices)"
+            "BoolVector": "$identifier[$indices] = $expr ? (byte)1 : (byte)0",
+            "BoolMatrix": "$identifier[$indices] = $expr ? (byte)1 : (byte)0"
         },
         "ZeroIndexed": true
     },

diff --git a/examples/meta/generator/targets/java.json b/examples/meta/generator/targets/java.json
@@ -6,7 +6,7 @@
         "IncludeGlobalFunctions": false,
         "DependencyListElement": "import org.shogun.$typeName;",
         "DependencyListSeparator": "\n",
-        "ExcludeImport": ["StringCharList", "StringWordList"]
+        "ExcludeImport": ["StringCharList", "StringWordList", "RealVector", "RealMatrix", "BoolMatrix", "ByteMatrix", "WordMatrix", "IntMatrix", "LongIntMatrix", "ShortRealMatrix", "BoolVector", "IntVector", "ByteVector", "LongIntVector", "ShortRealVector", "WordVector"]
     },
     "Statement": "$statement;\n",
     "Comment": "//$comment\n",
@@ -19,6 +19,7 @@
             "Separator": ";\n",
             "InitialSeperatorWhenArgs>0": false
         },
+        "BoolVector": "DoubleMatrix $name = new DoubleMatrix(1, $arguments)",
         "CharVector": "DoubleMatrix $name = new DoubleMatrix(1, $arguments)",
         "ByteVector": "DoubleMatrix $name = new DoubleMatrix(1, $arguments)",
         "WordVector": "DoubleMatrix $name = new DoubleMatrix(1, $arguments)",
@@ -28,6 +29,7 @@
         "ShortRealVector": "FloatMatrix $name = new FloatMatrix(1, $arguments)",
         "RealVector": "DoubleMatrix $name = new DoubleMatrix(1, $arguments)",
         "LongRealVector": "DoubleMatrix $name = new DoubleMatrix(1, $arguments)",
+        "BoolMatrix": "DoubleMatrix $name = new DoubleMatrix($arguments)",
         "CharMatrix": "DoubleMatrix $name = new DoubleMatrix($arguments)",
         "ByteMatrix": "DoubleMatrix $name = new DoubleMatrix($arguments)",
         "WordMatrix": "DoubleMatrix $name = new DoubleMatrix($arguments)",
@@ -39,7 +41,7 @@
         "LongRealMatrix": "DoubleMatrix $name = new DoubleMatrix($arguments)"
     },
     "ListInit": {
-        "BoolVector": "BoolVector $name = new BoolVector({$arguments})",
+        "BoolVector": "DoubleMatrix $name = new DoubleMatrix(new double [][] {{$arguments}})",
         "CharVector": "DoubleMatrix $name = new DoubleMatrix(new double [][] {{$arguments}})",
         "ByteVector": "DoubleMatrix $name = new DoubleMatrix(new double [][] {{$arguments}})",
         "WordVector": "DoubleMatrix $name = new DoubleMatrix(new double [][] {{$arguments}})",
@@ -107,14 +109,14 @@
         "Access": {
             "Vector": "$identifier.get($indices)",
             "Matrix": "$identifier.get($indices)",
-            "BoolVector": "$identifier.get_element($indices)",
-            "BoolMatrix": "$identifier.get_element($indices)"
+            "BoolVector": "$identifier.get($indices) == 1.0 ? true : false",
+            "BoolMatrix": "$identifier.get($indices) == 1.0 ? true : false"
         },
         "Assign": {
             "Vector": "$identifier.put($indices, $expr)",
             "Matrix": "$identifier.put($indices, $expr)",
-            "BoolVector": "$identifier.set_element($expr, $indices)",
-            "BoolMatrix": "$identifier.set_element($expr, $indices)"
+            "BoolVector": "$identifier.put($indices, $expr ? 1.0 : 0.0)",
+            "BoolMatrix": "$identifier.put($indices, $expr ? 1.0 : 0.0)"
         },
         "ZeroIndexed": true
     },

diff --git a/examples/meta/generator/targets/octave.json b/examples/meta/generator/targets/octave.json
@@ -12,6 +12,7 @@
             "InitialSeperatorWhenArgs>0": false
         },
         "string": "$name = $arguments",
+        "BoolVector": "$name = false(1, $arguments)",
         "ByteVector": "$name = zeros(1, $arguments, 'int8')",
         "WordVector": "$name = zeros(1, $arguments, 'int16')",
         "IntVector": "$name = zeros(1, $arguments, 'int32')",
@@ -20,6 +21,7 @@
         "ShortRealVector": "$name = zeros(1, $arguments, 'float32')",
         "RealVector": "$name = zeros(1, $arguments, 'float64')",
         "LongRealVector": "$name = zeros(1, $arguments, 'float64')",
+        "BoolMatrix": "$name = false($arguments)",
         "CharMatrix": "$name = zeros($arguments, 'char')",
         "ByteMatrix": "$name = zeros($arguments, 'int8')",
         "WordMatrix": "$name = zeros($arguments, 'int16')",
@@ -31,6 +33,7 @@
         "LongRealMatrix": "$name = zeros($arguments, 'float64')"
     },
     "ListInit": {
+        "BoolVector": "$name = logical([$arguments])",
         "ByteVector": "$name = int8([$arguments])",
         "WordVector": "$name = int16([$arguments])",
         "IntVector": "$name = int32([$arguments])",
@@ -65,15 +68,11 @@
     "Element": {
         "Access": {
             "Vector": "$identifier($indices)",
-            "Matrix": "$identifier($indices)",
-            "BoolVector": "$identifier.get_element($indices)",
-            "BoolMatrix": "$identifier.get_element($indices)"
+            "Matrix": "$identifier($indices)"
         },
         "Assign": {
             "Vector": "$identifier($indices) = $expr",
-            "Matrix": "$identifier($indices) = $expr",
-            "BoolVector": "$identifier.set_element($expr, $indices)",
-            "BoolMatrix": "$identifier.set_element($expr, $indices)"
+            "Matrix": "$identifier($indices) = $expr"
         },
         "ZeroIndexed": false
     },

diff --git a/examples/meta/src/base_api/put_get_add.sg.in b/examples/meta/src/base_api/put_get_add.sg.in
@@ -40,7 +40,7 @@ svm.put("libsvm_solver_type", "LIBSVM_C_SVC")
 #![option is always returned as a string]
 string option = svm.get_option("libsvm_solver_type")
 
-CSVFile f_feats("@SHOGUN_DATA@/regression_1d_sinc_features_train.dat")
+File f_feats = read_csv("@SHOGUN_DATA@/regression_1d_sinc_features_train.dat")
 Features feats = create_features(f_feats)
 Kernel k3 = create_kernel("PolyKernel", degree=2)
 Kernel k4 = create_kernel("GaussianKernel", log_width=2.0)

diff --git a/examples/meta/src/binary/domainadaptationsvm.sg.in b/examples/meta/src/binary/domainadaptationsvm.sg.in
@@ -3,8 +3,8 @@ File f_feats_test = read_csv("@SHOGUN_DATA@/fm_test_dna.dat")
 File f_labels_train = read_csv("@SHOGUN_DATA@/label_train_dna.dat")
 
 #![create_features]
-Features feats_train = create_char_string_features(f_feats_train, enum EAlphabet.DNA)
-Features feats_test = create_char_string_features(f_feats_test, enum EAlphabet.DNA) 
+Features feats_train = create_string_features(f_feats_train, enum EAlphabet.DNA)
+Features feats_test = create_string_features(f_feats_test, enum EAlphabet.DNA) 
 Labels labels_train = create_labels(f_labels_train)
 #![create_features]
 

diff --git a/examples/meta/src/binary/gpbtsvm.sg.in b/examples/meta/src/binary/gpbtsvm.sg.in
@@ -1,6 +1,6 @@
-CSVFile f_feats_train("@SHOGUN_DATA@/fm_train_real.dat")
-CSVFile f_feats_test("@SHOGUN_DATA@/fm_test_real.dat")
-CSVFile f_labels_train("@SHOGUN_DATA@/label_train_twoclass.dat")
+File f_feats_train = read_csv("@SHOGUN_DATA@/fm_train_real.dat")
+File f_feats_test = read_csv("@SHOGUN_DATA@/fm_test_real.dat")
+File f_labels_train = read_csv("@SHOGUN_DATA@/label_train_twoclass.dat")
 
 #![create_features]
 Features feats_train = create_features(f_feats_train)

diff --git a/examples/meta/src/binary/libsvmoneclass.sg b/examples/meta/src/binary/libsvmoneclass.sg
@@ -1,5 +1,5 @@
-CSVFile traindat("../../data/fm_train_real.dat")
-CSVFile testdat("../../data/fm_test_real.dat")
+File traindat = read_csv("../../data/fm_train_real.dat")
+File testdat = read_csv("../../data/fm_test_real.dat")
 
 #![create_features]
 Features feats_train = create_features(traindat)

diff --git a/examples/meta/src/binary/svm_ssk.sg.in b/examples/meta/src/binary/svm_ssk.sg.in
@@ -3,13 +3,13 @@ File f_feats_test = read_csv("@SHOGUN_DATA@/fm_test_dna.dat")
 File f_labels_train = read_csv("@SHOGUN_DATA@/label_train_dna.dat")
 
 #![create_features]
-Features feats_train = create_char_string_features(f_feats_train, enum EAlphabet.DNA)
-Features feats_test = create_char_string_features(f_feats_test, enum EAlphabet.DNA)
+Features feats_train = create_string_features(f_feats_train, enum EAlphabet.DNA)
+Features feats_test = create_string_features(f_feats_test, enum EAlphabet.DNA)
 Labels labels_train = create_labels(f_labels_train)
 #![create_features]
 
 #![create_kernel]
-Kernel svm_kernel = create_kernel("SubsequenceStringKernel", m_maxlen=5, m_lambda=0.9)
+Kernel svm_kernel = create_kernel("SubsequenceStringKernel", maxlen=5, decay=0.9)
 svm_kernel.init(feats_train, feats_train)
 #![create_kernel]
 

diff --git a/examples/meta/src/binary/svmlight.sg.in b/examples/meta/src/binary/svmlight.sg.in
@@ -3,8 +3,8 @@ File f_feats_test = read_csv("@SHOGUN_DATA@/fm_test_dna.dat")
 File f_labels_train = read_csv("@SHOGUN_DATA@/label_train_dna.dat")
 
  #![create_features]
-Features feats_train = create_char_string_features(f_feats_train, enum EAlphabet.DNA)
-Features feats_test = create_char_string_features(f_feats_test, enum EAlphabet.DNA)
+Features feats_train = create_string_features(f_feats_train, enum EAlphabet.DNA)
+Features feats_test = create_string_features(f_feats_test, enum EAlphabet.DNA)
 Labels labels_train = create_labels(f_labels_train)
 #![create_features]
 

diff --git a/examples/meta/src/binary/svmlight_batch_linadd.sg.in b/examples/meta/src/binary/svmlight_batch_linadd.sg.in
@@ -3,8 +3,8 @@ File f_feats_test = read_csv("@SHOGUN_DATA@/fm_test_dna.dat")
 File f_labels_train = read_csv("@SHOGUN_DATA@/label_train_dna.dat")
 
 #![create_features]
-Features feats_train = create_char_string_features(f_feats_train, enum EAlphabet.DNA)
-Features feats_test = create_char_string_features(f_feats_test, enum EAlphabet.DNA)
+Features feats_train = create_string_features(f_feats_train, enum EAlphabet.DNA)
+Features feats_test = create_string_features(f_feats_test, enum EAlphabet.DNA)
 Labels labels_train = create_labels(f_labels_train)
 #![create_features]