Updated JPMML-Python dependency

pmml-sklearn-extension/src/main/java/category_encoders/BaseEncoder.java

@@ -49,7 +49,7 @@ public DataType getDataType(){
 	@Override
 	public List<String> getFeatureNamesIn(){
 
-		if(containsKey(SkLearnFields.FEATURE_NAMES_IN)){
+		if(hasattr(SkLearnFields.FEATURE_NAMES_IN)){
 			return getListLike(SkLearnFields.FEATURE_NAMES_IN, String.class);
 		}
 
@@ -61,19 +61,19 @@ public PMML encodePMML(){
 		return TransformerUtil.encodePMML(this);
 	}
 
-	public List<?> getCols(){
-		return getList("cols");
+	public List<Object> getCols(){
+		return getObjectList("cols");
 	}
 
 	public List<String> getInvariantCols(){
 
 		// CategoryEncoders 2.3
-		if(containsKey("drop_cols")){
-			return getList("drop_cols", String.class);
+		if(hasattr("drop_cols")){
+			return getStringList("drop_cols");
 		}
 
 		// CategoryEncoders 2.5+
-		return getList("invariant_cols", String.class);
+		return getStringList("invariant_cols");
 	}
 
 	public Boolean getDropInvariant(){
@@ -83,12 +83,12 @@ public Boolean getDropInvariant(){
 	public List<String> getFeatureNamesOut(){
 
 		// CategoryEncoders 2.5.1post0
-		if(containsKey("feature_names")){
-			return getList("feature_names", String.class);
+		if(hasattr("feature_names")){
+			return getStringList("feature_names");
 		}
 
 		// CategoryEncoders 2.6+
-		return getList("feature_names_out_", String.class);
+		return getStringList("feature_names_out_");
 	}
 
 	public String getHandleMissing(){

pmml-sklearn-extension/src/main/java/category_encoders/BinaryEncoder.java

@@ -43,7 +43,7 @@ public List<Feature> encode(List<Feature> features, SkLearnEncoder encoder){
 	public BaseNEncoder getBaseNEncoder(){
 
 		// CategoryEncoders 2.3
-		if(containsKey("base_n_encoder")){
+		if(hasattr("base_n_encoder")){
 			return get("base_n_encoder", BaseNEncoder.class);
 		}
 

pmml-sklearn-extension/src/main/java/category_encoders/OrdinalEncoder.java

@@ -28,6 +28,7 @@
 import org.dmg.pmml.DataType;
 import org.jpmml.converter.Feature;
 import org.jpmml.converter.ValueUtil;
+import org.jpmml.python.AttributeException;
 import org.jpmml.python.ClassDictUtil;
 import org.jpmml.python.PythonObject;
 import org.jpmml.sklearn.SkLearnEncoder;
@@ -107,7 +108,7 @@ public List<Mapping> getMapping(){
 			@Override
 			public Mapping apply(Map<String, ?> map){
 				Mapping mapping = new Mapping(getClassName(), "mapping");
-				mapping.putAll(map);
+				mapping.update(map);
 
 				return mapping;
 			}
@@ -130,7 +131,7 @@ public Map<?, Integer> getCategoryMapping(){
 				Series mapping = get("mapping", Series.class);
 
 				return SeriesUtil.toMap(mapping, Functions.identity(), ValueUtil::asInteger);
-			} catch(IllegalArgumentException iae){
+			} catch(AttributeException ae){
 				return (Map)getDict("mapping");
 			}
 		}

pmml-sklearn-extension/src/main/java/optbinning/BinningProcess.java

@@ -84,8 +84,8 @@ public List<Feature> encodeFeatures(List<Feature> features, SkLearnEncoder encod
 					String key = entry.getKey();
 					Object value = entry.getValue();
 
-					if(!optimalBinning.containsKey(key)){
-						optimalBinning.put(key, value);
+					if(!optimalBinning.hasattr(key)){
+						optimalBinning.setattr(key, value);
 					}
 				}
 			}
@@ -135,7 +135,7 @@ public List<Boolean> getSupport(){
 	}
 
 	public List<String> getVariableNames(){
-		return (List)getListLike("variable_names", String.class);
+		return getListLike("variable_names", String.class);
 	}
 
 	public Map<String, String> getVariableDTypes(){

pmml-sklearn-extension/src/main/java/optbinning/OptimalBinning.java

@@ -276,8 +276,8 @@ private MapValues encodeCategoricalBinning(Feature feature, List<Number> splits,
 		return mapValues;
 	}
 
-	public List<?> getCategoriesIn(){
-		return getArray("_categories");
+	public List<Object> getCategoriesIn(){
+		return getObjectArray("_categories");
 	}
 
 	public List<Double> getCategoriesOut(){
@@ -333,15 +333,15 @@ public String getDefaultMetric(){
 
 	public String getMetric(){
 
-		if(!containsKey("metric")){
+		if(!hasattr("metric")){
 			return getDefaultMetric();
 		}
 
 		return getString("metric");
 	}
 
 	public OptimalBinning setMetric(String metric){
-		put("metric", metric);
+		setattr("metric", metric);
 
 		return this;
 	}
@@ -355,7 +355,7 @@ public List<Integer> getNumberOfNonEvents(){
 	}
 
 	public List<Number> getSpecialCodes(){
-		Object specialCodes = get("special_codes");
+		Object specialCodes = getOptionalObject("special_codes");
 
 		if(specialCodes == null){
 			return Collections.emptyList();

pmml-sklearn-extension/src/main/java/pycaret/preprocess/RareCategoryGrouping.java

@@ -73,7 +73,7 @@ public List<Feature> encodeFeatures(List<Feature> features, SkLearnEncoder encod
 	public Map<String, ?> getToOther(){
 
 		// PyCaret 3.0.0-RC
-		if(containsKey("_to_other")){
+		if(hasattr("_to_other")){
 			return getDict("_to_other");
 		}
 

pmml-sklearn-extension/src/main/java/pycaret/preprocess/RemoveMulticollinearity.java

@@ -57,11 +57,11 @@ public List<Feature> encodeFeatures(List<Feature> features, SkLearnEncoder encod
 	public List<String> getDrop(){
 
 		// PyCaret 3.0.0-RC
-		if(containsKey("_drop")){
-			return getList("_drop", String.class);
+		if(hasattr("_drop")){
+			return getStringList("_drop");
 		}
 
 		// PyCaret 3.0.0+
-		return getList("drop_", String.class);
+		return getStringList("drop_");
 	}
 }

pmml-sklearn-extension/src/main/java/pycaret/preprocess/TransformerWrapper.java

@@ -181,15 +181,15 @@ public List<Feature> encodeFeatures(List<Feature> features, SkLearnEncoder encod
 	}
 
 	public List<String> getFeatureNames(){
-		return getList("_feature_names_in", String.class);
+		return getStringList("_feature_names_in");
 	}
 
 	public List<String> getExclude(){
-		return getList("_exclude", String.class);
+		return getStringList("_exclude");
 	}
 
 	public List<String> getInclude(){
-		return getList("_include", String.class);
+		return getStringList("_include");
 	}
 
 	public String getTargetName(){

pmml-sklearn-extension/src/main/java/sklego/meta/OrdinalClassifier.java

@@ -177,7 +177,7 @@ public Object apply(Object object){
 
 			@Override
 			protected String formatMessage(Object object){
-				return "Dict attribute \'estimators_\' contains an unsupported item value (" + ClassDictUtil.formatClass(object) + ")";
+				return "The item value object (" + ClassDictUtil.formatClass(object) + ") is not a supported Classifier";
 			}
 		};
 
@@ -189,7 +189,7 @@ protected String formatMessage(Object object){
 
 	private Map<?, ?> getEstimatorCategories(){
 
-		if(!containsKey(SkLearn2PMMLFields.PMML_CLASSES)){
+		if(!hasattr(SkLearn2PMMLFields.PMML_CLASSES)){
 			return null;
 		}
 

pmml-sklearn-h2o/src/main/java/h2o/estimators/H2OEstimator.java

@@ -109,7 +109,7 @@ public int getNumberOfOutputs(){
 	public List<?> getClasses(){
 		MojoModel mojoModel = getMojoModel();
 
-		if(containsKey(SkLearn2PMMLFields.PMML_CLASSES)){
+		if(hasattr(SkLearn2PMMLFields.PMML_CLASSES)){
 			List<?> values = getListLike(SkLearn2PMMLFields.PMML_CLASSES);
 
 			return Classifier.canonicalizeValues(values);
@@ -260,7 +260,7 @@ public String getMojoPath(){
 	}
 
 	public H2OEstimator setMojoPath(String mojoPath){
-		put("_mojo_path", mojoPath);
+		setattr("_mojo_path", mojoPath);
 
 		return this;
 	}
@@ -291,7 +291,7 @@ private MojoModel loadMojoModel(){
 
 		try {
 
-			if(containsKey("_mojo_bytes")){
+			if(hasattr("_mojo_bytes")){
 				byte[] mojoBytes = getMojoBytes();
 
 				try(InputStream is = new ByteArrayInputStream(mojoBytes)){

pmml-sklearn-lightgbm/src/main/java/lightgbm/sklearn/Booster.java

@@ -60,7 +60,7 @@ private GBDT loadGBDT(){
 	public String getHandle(){
 
 		// LightGBM 3.3.5
-		if(containsKey("handle")){
+		if(hasattr("handle")){
 			return getString("handle");
 		}
 

pmml-sklearn-xgboost/src/main/java/xgboost/sklearn/Booster.java

@@ -57,7 +57,7 @@ private Learner loadLearner(ByteOrder byteOrder, String charset){
 
 	public Integer getBestNTreeLimit(){
 
-		if(!containsKey("best_ntree_limit")){
+		if(!hasattr("best_ntree_limit")){
 			return null;
 		}
 

pmml-sklearn-xgboost/src/main/java/xgboost/sklearn/XGBClassifier.java

@@ -54,7 +54,7 @@ public DataType getDataType(){
 	public List<?> getClasses(){
 
 		// XGBoost 0.4 through 1.7
-		if(containsKey("_le") || containsKey(SkLearnFields.CLASSES) || containsKey(SkLearn2PMMLFields.PMML_CLASSES)){
+		if(hasattr("_le") || hasattr(SkLearnFields.CLASSES) || hasattr(SkLearn2PMMLFields.PMML_CLASSES)){
 			return super.getClasses();
 		}
 

pmml-sklearn/src/main/java/chaid/Split.java

@@ -32,27 +32,21 @@ public Split(String module, String name){
 	}
 
 	public Integer getColumnId(){
-		Object columnId = get("column_id");
-
-		if(columnId == null){
-			return null;
-		}
-
-		return getInteger("column_id");
+		return getOptionalInteger("column_id");
 	}
 
 	public InvalidSplitReason getInvalidReason(){
 		return getOptional("_invalid_reason", InvalidSplitReason.class);
 	}
 
 	public List<List<Integer>> getSplits(){
-		List<?> splits = getList("splits");
+		List<Object> splits = getObjectList("splits");
 
 		return decodeSplits(splits);
 	}
 
-	public List<List<?>> getSplitMap(){
-		List<?> splitMap = getList("split_map");
+	public List<List<Object>> getSplitMap(){
+		List<Object> splitMap = getObjectList("split_map");
 
 		return decodeSplitMap(splitMap);
 	}
@@ -67,7 +61,7 @@ private List<List<Integer>> decodeSplits(List<?> splits){
 	}
 
 	static
-	public List<List<?>> decodeSplitMap(List<?> splits){
+	public List<List<Object>> decodeSplitMap(List<?> splits){
 		return Lists.transform(splits, split -> {
 			return Lists.transform((List<?>)split, value -> {
 				return ScalarUtil.decode(value);

pmml-sklearn/src/main/java/org/jpmml/sklearn/EncodableUtil.java

@@ -22,6 +22,7 @@
 import java.util.Collections;
 import java.util.List;
 
+import org.jpmml.python.AttributeException;
 import org.jpmml.python.ClassDictUtil;
 import sklearn.Estimator;
 import sklearn.HasNumberOfFeatures;
@@ -63,7 +64,7 @@ public List<String> generateFeatureNames(Step step){
 		int numberOfFeatures = step.getNumberOfFeatures();
 
 		if(numberOfFeatures == HasNumberOfFeatures.UNKNOWN){
-			throw new IllegalArgumentException("Attribute \'" + ClassDictUtil.formatMember(step, SkLearnFields.N_FEATURES_IN) + "\' is not set");
+			throw new AttributeException("Attribute \'" + ClassDictUtil.formatMember(step, SkLearnFields.N_FEATURES_IN) + "\' is not set");
 		}
 
 		return generateNames("x", numberOfFeatures, true);
@@ -74,7 +75,7 @@ public List<String> generateOutputNames(Estimator estimator){
 		int numberOfOutputs = estimator.getNumberOfOutputs();
 
 		if(numberOfOutputs == HasNumberOfOutputs.UNKNOWN){
-			throw new IllegalArgumentException("Attribute \'" + ClassDictUtil.formatMember(estimator, SkLearnFields.N_OUTPUTS) + "\' is not set");
+			throw new AttributeException("Attribute \'" + ClassDictUtil.formatMember(estimator, SkLearnFields.N_OUTPUTS) + "\' is not set");
 		}
 
 		return generateNames("y", numberOfOutputs, false);

pmml-sklearn/src/main/java/scipy/interpolate/BSplineUtil.java

@@ -49,8 +49,7 @@ public List<DefineFunction> createSplineFunction(BSpline bspline, SkLearnEncoder
 		List<Number> c = bspline.getC();
 		List<Number> t = bspline.getT();
 
-		// XXX
-		int[] cShape = bspline.getArrayShape("c");
+		int[] cShape = bspline.getCShape();
 
 		int n = (t.size() - k - 1);
 

pmml-sklearn/src/main/java/sklearn/Classifier.java

@@ -82,7 +82,7 @@ public int getNumberOfOutputs(){
 	@Override
 	public List<?> getClasses(){
 
-		if(containsKey(SkLearn2PMMLFields.PMML_CLASSES)){
+		if(hasattr(SkLearn2PMMLFields.PMML_CLASSES)){
 			return getClasses(SkLearn2PMMLFields.PMML_CLASSES);
 		}
 
@@ -93,7 +93,16 @@ protected List<?> getClasses(String name){
 		List<?> values = getListLike(name);
 
 		values = values.stream()
-			.map(value -> (value instanceof HasArray) ? canonicalizeValues(((HasArray)value).getArrayContent()) : value)
+			.map(value -> {
+
+				if(value instanceof HasArray){
+					HasArray hasArray = (HasArray)value;
+
+					return canonicalizeValues(hasArray.getArrayContent());
+				}
+
+				return value;
+			})
 			.collect(Collectors.toList());
 
 		return canonicalizeValues(values);