mirror of https://github.com/apache/lucene.git
SOLR-14544: Fix or suppress warnings in solr/client/solrj/io/eval
This commit is contained in:
parent
04ba04c29d
commit
7bf59a16bd
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@ -304,7 +304,9 @@ Other Changes
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* SOLR-13492: Ensure explicit GCs are concurrent by adding '+ExplicitGCInvokesConcurrent'.
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(Guna Sekhar Dora, Shawn Heisey, Munendra S N)
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* SOLR-14542: Fix or suppress warnings in solr/handler/dataimport (Erick Erickson)
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* SOLR-14542: Fix or suppress warnings in solr/handler/dataimport (Erick Erickson)
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* SOLR-14544: Fix or suppress warnings in solr/client/solrj/io/eval (Erick Erickson)
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* SOLR-14543: Fix or suppress warnings in apache/solr/search (Erick Erickson)
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@ -33,6 +33,7 @@ public class AkimaEvaluator extends RecursiveNumericEvaluator implements ManyVal
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}
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@Override
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@SuppressWarnings({"unchecked"})
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public Object doWork(Object... objects) throws IOException{
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Object first = objects[0];
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@ -56,7 +57,7 @@ public class AkimaEvaluator extends RecursiveNumericEvaluator implements ManyVal
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AkimaSplineInterpolator interpolator = new AkimaSplineInterpolator();
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PolynomialSplineFunction spline = interpolator.interpolate(x, y);
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List<Number> list = new ArrayList();
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List<Number> list = new ArrayList<>();
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for(double xvalue : x) {
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list.add(spline.value(xvalue));
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}
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@ -45,6 +45,7 @@ public class AnovaEvaluator extends RecursiveNumericListEvaluator implements Man
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// at this point we know every incoming value is an array of BigDecimals
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@SuppressWarnings({"unchecked"})
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List<double[]> anovaInput = Arrays.stream(values)
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// for each List, convert to double[]
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.map(value -> ((List<Number>)value).stream().mapToDouble(Number::doubleValue).toArray())
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@ -31,8 +31,10 @@ import org.apache.solr.client.solrj.io.stream.expr.StreamFactory;
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public class ArrayEvaluator extends RecursiveObjectEvaluator implements ManyValueWorker {
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protected static final long serialVersionUID = 1L;
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@SuppressWarnings({"rawtypes"})
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private Comparator<Comparable> sortComparator;
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@SuppressWarnings({"unchecked"})
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public ArrayEvaluator(StreamExpression expression, StreamFactory factory) throws IOException{
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super(expression, factory, Arrays.asList("sort"));
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@ -32,6 +32,7 @@ public class AscEvaluator extends RecursiveObjectEvaluator implements OneValueWo
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}
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@Override
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@SuppressWarnings({"unchecked"})
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public Object doWork(Object value) throws IOException {
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if(null == value){
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return value;
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@ -22,5 +22,6 @@ import java.util.Map;
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public interface Attributes {
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Object getAttribute(String key);
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void setAttribute(String key, Object value);
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@SuppressWarnings({"rawtypes"})
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Map getAttributes();
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}
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@ -47,6 +47,7 @@ public class BicubicSplineEvaluator extends RecursiveObjectEvaluator implements
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double[][] grid = null;
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if(first instanceof List && second instanceof List && third instanceof Matrix) {
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@SuppressWarnings({"unchecked"})
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List<Number> xlist = (List<Number>) first;
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x = new double[xlist.size()];
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@ -54,6 +55,7 @@ public class BicubicSplineEvaluator extends RecursiveObjectEvaluator implements
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x[i]=xlist.get(i).doubleValue();
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}
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@SuppressWarnings({"unchecked"})
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List<Number> ylist = (List<Number>) second;
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y = new double[ylist.size()];
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@ -33,6 +33,7 @@ public class ChebyshevDistanceEvaluator extends RecursiveNumericEvaluator implem
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}
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@Override
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@SuppressWarnings({"unchecked"})
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public Object doWork(Object first, Object second) throws IOException{
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if(null == first){
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throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - null found for the first value",toExpression(constructingFactory)));
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@ -38,7 +38,9 @@ public class ChiSquareDataSetEvaluator extends RecursiveNumericListEvaluator imp
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@Override
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public Object doWork(Object value1, Object value2) throws IOException {
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@SuppressWarnings({"unchecked"})
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List<Number> listA = (List<Number>) value1;
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@SuppressWarnings({"unchecked"})
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List<Number> listB = (List<Number>) value2;
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long[] sampleA = new long[listA.size()];
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@ -43,7 +43,7 @@ public class ColumnAtEvaluator extends RecursiveObjectEvaluator implements TwoVa
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Matrix matrix = (Matrix) value1;
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Number index = (Number) value2;
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double[][] data = matrix.getData();
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List<Number> list = new ArrayList();
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List<Number> list = new ArrayList<>();
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for(double[] row : data) {
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list.add(row[index.intValue()]);
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}
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@ -45,7 +45,7 @@ public class ConvexHullEvaluator extends RecursiveObjectEvaluator implements Man
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public static ConvexHull2D getConvexHull(Matrix matrix) throws IOException {
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double[][] data = matrix.getData();
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List<Vector2D> points = new ArrayList(data.length);
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List<Vector2D> points = new ArrayList<>(data.length);
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if(data[0].length == 2) {
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for(double[] row : data) {
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points.add(new Vector2D(row[0], row[1]));
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@ -34,6 +34,7 @@ public class ConvolutionEvaluator extends RecursiveNumericEvaluator implements T
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}
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@Override
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@SuppressWarnings({"unchecked"})
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public Object doWork(Object first, Object second) throws IOException{
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if(null == first){
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throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - null found for the first value",toExpression(constructingFactory)));
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@ -60,6 +60,7 @@ public class CorrelationEvaluator extends RecursiveObjectEvaluator implements Ma
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}
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@Override
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@SuppressWarnings({"unchecked"})
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public Object doWork(Object ... values) throws IOException{
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if(values.length == 2) {
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@ -150,7 +151,7 @@ public class CorrelationEvaluator extends RecursiveObjectEvaluator implements Ma
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if(labels != null) {
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return labels;
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} else {
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List<String> l = new ArrayList();
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List<String> l = new ArrayList<>();
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for(int i=0; i<length; i++) {
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String label = "col"+ ZplotStream.pad(Integer.toString(i), length);
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l.add(label);
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@ -46,7 +46,9 @@ public class CosineSimilarityEvaluator extends RecursiveNumericEvaluator impleme
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throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - found type %s for the second value, expecting a list of numbers",toExpression(constructingFactory), first.getClass().getSimpleName()));
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}
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@SuppressWarnings({"unchecked"})
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double[] d1 = ((List) first).stream().mapToDouble(value -> ((Number) value).doubleValue()).toArray();
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@SuppressWarnings({"unchecked"})
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double[] d2 = ((List) second).stream().mapToDouble(value -> ((Number) value).doubleValue()).toArray();
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return cosineSimilarity(d1, d2);
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@ -32,6 +32,7 @@ public class CovarianceEvaluator extends RecursiveObjectEvaluator implements Man
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}
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@Override
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@SuppressWarnings({"unchecked"})
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public Object doWork(Object ... values) throws IOException{
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if(values.length == 2) {
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@ -41,6 +41,7 @@ public class DbscanEvaluator extends RecursiveObjectEvaluator implements ManyVal
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}
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@Override
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@SuppressWarnings({"unchecked"})
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public Object doWork(Object... values) throws IOException {
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Matrix matrix = null;
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@ -74,8 +75,9 @@ public class DbscanEvaluator extends RecursiveObjectEvaluator implements ManyVal
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distanceMeasure = (DistanceMeasure)values[3];
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}
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@SuppressWarnings({"rawtypes"})
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DBSCANClusterer<ClusterPoint> dbscan = new DBSCANClusterer(e, minPoints, distanceMeasure);
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List<ClusterPoint> points = new ArrayList();
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List<ClusterPoint> points = new ArrayList<>();
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double[][] data = matrix.getData();
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List<String> ids = matrix.getRowLabels();
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@ -88,6 +90,7 @@ public class DbscanEvaluator extends RecursiveObjectEvaluator implements ManyVal
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}
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}
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@SuppressWarnings({"rawtypes"})
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Map fields = new HashMap();
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fields.put("e", e);
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@ -121,7 +124,7 @@ public class DbscanEvaluator extends RecursiveObjectEvaluator implements ManyVal
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private List<String> columnLabels;
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private List<Cluster<ClusterPoint>> clusters;
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public ClusterTuple(Map fields,
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public ClusterTuple(@SuppressWarnings({"rawtypes"})Map fields,
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List<Cluster<ClusterPoint>> clusters,
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List<String> columnLabels) {
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super(fields);
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@ -42,6 +42,7 @@ public class DensityEvaluator extends RecursiveObjectEvaluator implements TwoVal
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}
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MultivariateRealDistribution multivariateRealDistribution = (MultivariateRealDistribution) first;
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@SuppressWarnings({"unchecked"})
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List<Number> nums = (List<Number>) second;
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double[] vec = new double[nums.size()];
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@ -38,6 +38,7 @@ public class DistanceEvaluator extends RecursiveObjectEvaluator implements ManyV
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}
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@Override
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@SuppressWarnings({"unchecked"})
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public Object doWork(Object ... values) throws IOException{
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if(values.length == 1) {
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@ -48,7 +48,9 @@ public class DotProductEvaluator extends RecursiveNumericEvaluator implements Tw
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throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - found type %s for the second value, expecting a list of numbers",toExpression(constructingFactory), first.getClass().getSimpleName()));
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}
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@SuppressWarnings({"unchecked", "rawtypes"})
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RealVector v = new ArrayRealVector(((List) first).stream().mapToDouble(value -> ((Number) value).doubleValue()).toArray());
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@SuppressWarnings({"unchecked", "rawtypes"})
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RealVector v2 = new ArrayRealVector(((List) second).stream().mapToDouble(value -> ((Number) value).doubleValue()).toArray());
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return v.dotProduct(v2);
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@ -34,6 +34,7 @@ public class EBEAddEvaluator extends RecursiveObjectEvaluator implements TwoValu
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}
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@Override
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@SuppressWarnings({"unchecked"})
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public Object doWork(Object first, Object second) throws IOException{
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if(null == first){
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throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - null found for the first value",toExpression(constructingFactory)));
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@ -48,7 +49,7 @@ public class EBEAddEvaluator extends RecursiveObjectEvaluator implements TwoValu
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((List) second).stream().mapToDouble(value -> ((Number) value).doubleValue()).toArray()
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);
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List<Number> numbers = new ArrayList();
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List<Number> numbers = new ArrayList<>();
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for (double d : result) {
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numbers.add(d);
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}
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@ -47,12 +47,13 @@ public class EBEDivideEvaluator extends RecursiveNumericEvaluator implements Two
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throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - found type %s for the second value, expecting a list of numbers",toExpression(constructingFactory), first.getClass().getSimpleName()));
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}
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@SuppressWarnings({"unchecked"})
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double[] result = MathArrays.ebeDivide(
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((List) first).stream().mapToDouble(value -> ((Number) value).doubleValue()).toArray(),
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((List) second).stream().mapToDouble(value -> ((Number) value).doubleValue()).toArray()
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);
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List<Number> numbers = new ArrayList();
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List<Number> numbers = new ArrayList<>();
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for(double d : result) {
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numbers.add(d);
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}
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@ -33,6 +33,7 @@ public class EBEMultiplyEvaluator extends RecursiveNumericEvaluator implements T
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}
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@Override
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@SuppressWarnings({"unchecked"})
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public Object doWork(Object first, Object second) throws IOException{
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if(null == first){
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throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - null found for the first value",toExpression(constructingFactory)));
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@ -52,7 +53,7 @@ public class EBEMultiplyEvaluator extends RecursiveNumericEvaluator implements T
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((List) second).stream().mapToDouble(value -> ((Number) value).doubleValue()).toArray()
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);
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List<Number> numbers = new ArrayList();
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List<Number> numbers = new ArrayList<>();
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for(double d : result) {
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numbers.add(d);
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}
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@ -34,6 +34,7 @@ public class EBESubtractEvaluator extends RecursiveObjectEvaluator implements Tw
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}
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@Override
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@SuppressWarnings({"unchecked"})
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public Object doWork(Object first, Object second) throws IOException{
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if(null == first){
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throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - null found for the first value",toExpression(constructingFactory)));
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@ -47,7 +48,7 @@ public class EBESubtractEvaluator extends RecursiveObjectEvaluator implements Tw
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((List) second).stream().mapToDouble(value -> ((Number) value).doubleValue()).toArray()
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);
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List<Number> numbers = new ArrayList();
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List<Number> numbers = new ArrayList<>();
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for (double d : result) {
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numbers.add(d);
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}
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@ -45,14 +45,17 @@ public class EnclosingDiskEvaluator extends RecursiveObjectEvaluator implements
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}
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}
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@SuppressWarnings({"rawtypes"})
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public static EnclosingBall getEnclosingDisk(Matrix matrix) throws IOException {
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double[][] data = matrix.getData();
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List<Vector2D> points = new ArrayList(data.length);
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List<Vector2D> points = new ArrayList<>(data.length);
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if(data[0].length == 2) {
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for(double[] row : data) {
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points.add(new Vector2D(row[0], row[1]));
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}
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@SuppressWarnings({"unchecked"})
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WelzlEncloser<Euclidean2D, Vector2D> welzlEncloser = new WelzlEncloser(.001, new DiskGenerator());
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EnclosingBall enclosingBall = welzlEncloser.enclose(points);
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return enclosingBall;
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@ -39,13 +39,19 @@ public class EnumeratedDistributionEvaluator extends RecursiveNumericEvaluator i
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}
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if(values.length == 1) {
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@SuppressWarnings({"unchecked"})
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List<Number> first = (List<Number>)values[0];
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@SuppressWarnings({"unchecked", "rawtypes"})
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int[] samples = ((List) first).stream().mapToInt(value -> ((Number) value).intValue()).toArray();
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return new EnumeratedIntegerDistribution(samples);
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} else {
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@SuppressWarnings({"unchecked"})
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List<Number> first = (List<Number>)values[0];
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@SuppressWarnings({"unchecked"})
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List<Number> second = (List<Number>)values[1];
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@SuppressWarnings({"unchecked", "rawtypes"})
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int[] singletons = ((List) first).stream().mapToInt(value -> ((Number) value).intValue()).toArray();
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@SuppressWarnings({"unchecked", "rawtypes"})
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double[] probs = ((List) second).stream().mapToDouble(value -> ((Number) value).doubleValue()).toArray();
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return new EnumeratedIntegerDistribution(singletons, probs);
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}
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@ -33,6 +33,7 @@ public class EuclideanDistanceEvaluator extends RecursiveNumericEvaluator implem
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}
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@Override
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@SuppressWarnings({"unchecked"})
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public Object doWork(Object first, Object second) throws IOException{
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if(null == first){
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throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - null found for the first value",toExpression(constructingFactory)));
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@ -31,7 +31,7 @@ import org.apache.solr.client.solrj.io.stream.expr.StreamFactory;
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public class FFTEvaluator extends RecursiveNumericEvaluator implements OneValueWorker {
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protected static final long serialVersionUID = 1L;
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private static List<String> clabels = new ArrayList();
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private static List<String> clabels = new ArrayList<>();
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static {
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clabels.add("real");
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@ -44,10 +44,10 @@ public class FeatureSelectEvaluator extends RecursiveObjectEvaluator implements
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double[][] data = matrix.getData();
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List<String> labels = matrix.getColumnLabels();
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Set<String> features = new HashSet();
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Set<String> features = new HashSet<>();
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loadFeatures(value2, features);
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List<String> newColumnLabels = new ArrayList();
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List<String> newColumnLabels = new ArrayList<>();
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for(String label : labels) {
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if(features.contains(label)) {
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@ -81,6 +81,7 @@ public class FeatureSelectEvaluator extends RecursiveObjectEvaluator implements
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}
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private void loadFeatures(Object o, Set<String> features) {
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@SuppressWarnings({"rawtypes"})
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List list = (List)o;
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for(Object v : list) {
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if(v instanceof List) {
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@ -42,6 +42,7 @@ public class FieldValueEvaluator extends SourceEvaluator {
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}
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@Override
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@SuppressWarnings({"unchecked"})
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public Object evaluate(Tuple tuple) throws IOException {
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Object value = tuple.get(fieldName);
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@ -52,7 +52,9 @@ public class FindDelayEvaluator extends RecursiveNumericEvaluator implements Two
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}
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// Get first and second lists as arrays, where second is in reverse order
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@SuppressWarnings({"unchecked", "rawtypes"})
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double[] firstArray = ((List)first).stream().mapToDouble(value -> ((Number)value).doubleValue()).toArray();
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@SuppressWarnings({"unchecked", "rawtypes"})
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double[] secondArray = StreamSupport.stream(Spliterators.spliteratorUnknownSize(
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((LinkedList)((List)second).stream().collect(Collectors.toCollection(LinkedList::new))).descendingIterator(),
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Spliterator.ORDERED), false).mapToDouble(value -> ((Number)value).doubleValue()).toArray();
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@ -67,6 +67,7 @@ public class FrequencyTableEvaluator extends RecursiveNumericEvaluator implement
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List<Tuple> histogramBins = new ArrayList<>();
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@SuppressWarnings({"rawtypes"})
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Iterator iterator = frequency.valuesIterator();
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while(iterator.hasNext()){
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@ -56,6 +56,7 @@ public class FuzzyKmeansEvaluator extends RecursiveObjectEvaluator implements Tw
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}
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@Override
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@SuppressWarnings({"unchecked"})
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public Object doWork(Object value1, Object value2) throws IOException {
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@ -75,11 +76,12 @@ public class FuzzyKmeansEvaluator extends RecursiveObjectEvaluator implements Tw
|
|||
throw new IOException("The second parameter for fuzzyKmeans should be k.");
|
||||
}
|
||||
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
FuzzyKMeansClusterer<KmeansEvaluator.ClusterPoint> kmeans = new FuzzyKMeansClusterer(k,
|
||||
fuzziness,
|
||||
maxIterations,
|
||||
new EuclideanDistance());
|
||||
List<KmeansEvaluator.ClusterPoint> points = new ArrayList();
|
||||
List<KmeansEvaluator.ClusterPoint> points = new ArrayList<>();
|
||||
double[][] data = matrix.getData();
|
||||
|
||||
List<String> ids = matrix.getRowLabels();
|
||||
|
@ -89,6 +91,7 @@ public class FuzzyKmeansEvaluator extends RecursiveObjectEvaluator implements Tw
|
|||
points.add(new KmeansEvaluator.ClusterPoint(ids.get(i), vec));
|
||||
}
|
||||
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
Map fields = new HashMap();
|
||||
|
||||
fields.put("k", k);
|
||||
|
@ -101,7 +104,7 @@ public class FuzzyKmeansEvaluator extends RecursiveObjectEvaluator implements Tw
|
|||
double[][] mmData = realMatrix.getData();
|
||||
Matrix mmMatrix = new Matrix(mmData);
|
||||
mmMatrix.setRowLabels(matrix.getRowLabels());
|
||||
List<String> clusterCols = new ArrayList();
|
||||
List<String> clusterCols = new ArrayList<>();
|
||||
for(int i=0; i<clusters.size(); i++) {
|
||||
clusterCols.add("cluster"+ ZplotStream.pad(Integer.toString(i), clusters.size()));
|
||||
}
|
||||
|
|
|
@ -38,7 +38,9 @@ public class GTestDataSetEvaluator extends RecursiveNumericListEvaluator impleme
|
|||
@Override
|
||||
public Object doWork(Object value1, Object value2) throws IOException {
|
||||
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> listA = (List<Number>) value1;
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> listB = (List<Number>) value2;
|
||||
|
||||
long[] sampleA = new long[listA.size()];
|
||||
|
|
|
@ -37,6 +37,7 @@ public class GaussFitEvaluator extends RecursiveNumericEvaluator implements Many
|
|||
}
|
||||
|
||||
@Override
|
||||
@SuppressWarnings({"unchecked", "rawtypes"})
|
||||
public Object doWork(Object... objects) throws IOException{
|
||||
|
||||
if(objects.length >= 3) {
|
||||
|
|
|
@ -41,7 +41,7 @@ public class GetBaryCenterEvaluator extends RecursiveObjectEvaluator implements
|
|||
} else {
|
||||
ConvexHull2D convexHull2D = (ConvexHull2D)value;
|
||||
Vector2D vector2D = (Vector2D)convexHull2D.createRegion().getBarycenter();
|
||||
List<Number> vec = new ArrayList();
|
||||
List<Number> vec = new ArrayList<>();
|
||||
vec.add(vector2D.getX());
|
||||
vec.add(vector2D.getY());
|
||||
return vec;
|
||||
|
|
|
@ -37,12 +37,14 @@ public class GetCacheEvaluator extends RecursiveObjectEvaluator implements ManyV
|
|||
|
||||
@Override
|
||||
public Object doWork(Object... values) throws IOException {
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
ConcurrentMap objectCache = this.streamContext.getObjectCache();
|
||||
if(values.length == 2) {
|
||||
String space = (String)values[0];
|
||||
String key = (String)values[1];
|
||||
space = space.replace("\"", "");
|
||||
key = key.replace("\"", "");
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
ConcurrentMap spaceCache = (ConcurrentMap)objectCache.get(space);
|
||||
|
||||
if(spaceCache != null) {
|
||||
|
|
|
@ -41,9 +41,10 @@ public class GetCenterEvaluator extends RecursiveObjectEvaluator implements OneV
|
|||
if(!(value instanceof EnclosingBall)){
|
||||
throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - found type %s for value, expecting an EnclosingBall",toExpression(constructingFactory), value.getClass().getSimpleName()));
|
||||
} else {
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
EnclosingBall enclosingBall = (EnclosingBall)value;
|
||||
Vector2D vec = (Vector2D)enclosingBall.getCenter();
|
||||
List<Number> center = new ArrayList();
|
||||
List<Number> center = new ArrayList<>();
|
||||
center.add(vec.getX());
|
||||
center.add(vec.getY());
|
||||
return center;
|
||||
|
|
|
@ -44,9 +44,11 @@ public class GetClusterEvaluator extends RecursiveObjectEvaluator implements Two
|
|||
List<CentroidCluster<KmeansEvaluator.ClusterPoint>> clusters = clusterTuple.getClusters();
|
||||
|
||||
Number index = (Number)value2;
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
CentroidCluster cluster = clusters.get(index.intValue());
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
List points = cluster.getPoints();
|
||||
List<String> rowLabels = new ArrayList();
|
||||
List<String> rowLabels = new ArrayList<>();
|
||||
double[][] data = new double[points.size()][];
|
||||
|
||||
for(int i=0; i<points.size(); i++) {
|
||||
|
|
|
@ -37,6 +37,7 @@ public class GetRadiusEvaluator extends RecursiveObjectEvaluator implements OneV
|
|||
if(!(value instanceof EnclosingBall)){
|
||||
throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - found type %s for value, expecting an EnclosingBall",toExpression(constructingFactory), value.getClass().getSimpleName()));
|
||||
} else {
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
EnclosingBall enclosingBall = (EnclosingBall)value;
|
||||
return enclosingBall.getRadius();
|
||||
}
|
||||
|
|
|
@ -39,11 +39,13 @@ public class GetSupportPointsEvaluator extends RecursiveObjectEvaluator implemen
|
|||
if(!(value instanceof EnclosingBall)){
|
||||
throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - found type %s for value, expecting an EnclosingBall",toExpression(constructingFactory), value.getClass().getSimpleName()));
|
||||
} else {
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
EnclosingBall enclosingBall = (EnclosingBall)value;
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
Point[] points = enclosingBall.getSupport();
|
||||
double[][] data = new double[points.length][2];
|
||||
int i=0;
|
||||
for(Point point : points) {
|
||||
for(@SuppressWarnings({"rawtypes"})Point point : points) {
|
||||
Vector2D eu = (Vector2D)point;
|
||||
data[i][0] = eu.getX();
|
||||
data[i][1] = eu.getY();
|
||||
|
|
|
@ -34,6 +34,7 @@ public class HarmonicFitEvaluator extends RecursiveNumericEvaluator implements M
|
|||
}
|
||||
|
||||
@Override
|
||||
@SuppressWarnings({"unchecked"})
|
||||
public Object doWork(Object... objects) throws IOException{
|
||||
|
||||
if(objects.length > 3) {
|
||||
|
@ -76,12 +77,14 @@ public class HarmonicFitEvaluator extends RecursiveNumericEvaluator implements M
|
|||
double[] coef = curveFitter.fit(points.toList());
|
||||
HarmonicOscillator pf = new HarmonicOscillator(coef[0], coef[1], coef[2]);
|
||||
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
List list = new ArrayList();
|
||||
for(double xvalue : x) {
|
||||
double yvalue= pf.value(xvalue);
|
||||
list.add(yvalue);
|
||||
}
|
||||
|
||||
@SuppressWarnings({"unchecked"})
|
||||
VectorFunction vectorFunction = new VectorFunction(pf, list);
|
||||
vectorFunction.addToContext("amplitude", coef[0]);
|
||||
vectorFunction.addToContext("angularFrequency", coef[1]);
|
||||
|
|
|
@ -58,7 +58,7 @@ public class IFFTEvaluator extends RecursiveObjectEvaluator implements OneValueW
|
|||
FastFourierTransformer fastFourierTransformer = new FastFourierTransformer(DftNormalization.STANDARD);
|
||||
Complex[] result = fastFourierTransformer.transform(complex, TransformType.INVERSE);
|
||||
|
||||
List<Number> realResult = new ArrayList();
|
||||
List<Number> realResult = new ArrayList<>();
|
||||
for (int i = 0; i < result.length; ++i) {
|
||||
realResult.add(result[i].getReal());
|
||||
}
|
||||
|
|
|
@ -36,6 +36,7 @@ public class IndexOfEvaluator extends RecursiveObjectEvaluator implements TwoVal
|
|||
if(!(value1 instanceof List)){
|
||||
throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - found type %s for value, expecting an array",toExpression(constructingFactory), value1.getClass().getSimpleName()));
|
||||
} else {
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
List list = (List)value1;
|
||||
String find = value2.toString().replace("\"","");
|
||||
for(int i=0; i<list.size(); i++) {
|
||||
|
|
|
@ -75,7 +75,7 @@ public class IntegrateEvaluator extends RecursiveObjectEvaluator implements Many
|
|||
|
||||
double[] x = (double[])vectorFunction.getFromContext("x");
|
||||
double[] y = (double[])vectorFunction.getFromContext("y");
|
||||
ArrayList<Number> out = new ArrayList();
|
||||
ArrayList<Number> out = new ArrayList<>();
|
||||
out.add(0);
|
||||
for(int i=1; i<x.length; i++) {
|
||||
out.add(integrator.integrate(5000, func, x[0], x[i]));
|
||||
|
|
|
@ -42,6 +42,7 @@ public class IsNullEvaluator extends RecursiveBooleanEvaluator implements ManyVa
|
|||
|
||||
if(values[0] instanceof String) {
|
||||
//Check to see if the this tuple had a null value for that string.
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
Map tupleContext = getStreamContext().getTupleContext();
|
||||
String nullField = (String)tupleContext.get("null");
|
||||
if(nullField != null && nullField.equals(values[0])) {
|
||||
|
|
|
@ -52,6 +52,7 @@ public class KmeansEvaluator extends RecursiveObjectEvaluator implements TwoValu
|
|||
}
|
||||
|
||||
@Override
|
||||
@SuppressWarnings({"unchecked"})
|
||||
public Object doWork(Object value1, Object value2) throws IOException {
|
||||
|
||||
Matrix matrix = null;
|
||||
|
@ -70,8 +71,9 @@ public class KmeansEvaluator extends RecursiveObjectEvaluator implements TwoValu
|
|||
}
|
||||
|
||||
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
KMeansPlusPlusClusterer<ClusterPoint> kmeans = new KMeansPlusPlusClusterer(k, maxIterations);
|
||||
List<ClusterPoint> points = new ArrayList();
|
||||
List<ClusterPoint> points = new ArrayList<>();
|
||||
double[][] data = matrix.getData();
|
||||
|
||||
List<String> ids = matrix.getRowLabels();
|
||||
|
@ -85,6 +87,7 @@ public class KmeansEvaluator extends RecursiveObjectEvaluator implements TwoValu
|
|||
}
|
||||
}
|
||||
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
Map fields = new HashMap();
|
||||
|
||||
fields.put("k", k);
|
||||
|
@ -119,7 +122,7 @@ public class KmeansEvaluator extends RecursiveObjectEvaluator implements TwoValu
|
|||
private List<CentroidCluster<ClusterPoint>> clusters;
|
||||
private Matrix membershipMatrix;
|
||||
|
||||
public ClusterTuple(Map fields,
|
||||
public ClusterTuple(@SuppressWarnings({"rawtypes"})Map fields,
|
||||
List<CentroidCluster<ClusterPoint>> clusters,
|
||||
List<String> columnLabels) {
|
||||
super(fields);
|
||||
|
@ -127,7 +130,7 @@ public class KmeansEvaluator extends RecursiveObjectEvaluator implements TwoValu
|
|||
this.columnLabels = columnLabels;
|
||||
}
|
||||
|
||||
public ClusterTuple(Map fields,
|
||||
public ClusterTuple(@SuppressWarnings({"rawtypes"})Map fields,
|
||||
List<CentroidCluster<ClusterPoint>> clusters,
|
||||
List<String> columnLabels,
|
||||
Matrix membershipMatrix) {
|
||||
|
|
|
@ -52,6 +52,7 @@ public class KnnEvaluator extends RecursiveObjectEvaluator implements ManyValueW
|
|||
}
|
||||
|
||||
if(values[1] instanceof List) {
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> nums = (List<Number>)values[1];
|
||||
vec = new double[nums.size()];
|
||||
for(int i=0; i<nums.size(); i++) {
|
||||
|
@ -84,7 +85,7 @@ public class KnnEvaluator extends RecursiveObjectEvaluator implements ManyValueW
|
|||
DistanceMeasure distanceMeasure) {
|
||||
|
||||
double[][] data = observations.getData();
|
||||
TreeSet<Neighbor> neighbors = new TreeSet();
|
||||
TreeSet<Neighbor> neighbors = new TreeSet<>();
|
||||
for(int i=0; i<data.length; i++) {
|
||||
double distance = distanceMeasure.compute(vec, data[i]);
|
||||
neighbors.add(new Neighbor(i, distance));
|
||||
|
@ -95,9 +96,9 @@ public class KnnEvaluator extends RecursiveObjectEvaluator implements ManyValueW
|
|||
|
||||
double[][] out = new double[neighbors.size()][];
|
||||
List<String> rowLabels = observations.getRowLabels();
|
||||
List<String> newRowLabels = new ArrayList();
|
||||
List<Number> indexes = new ArrayList();
|
||||
List<Number> distances = new ArrayList();
|
||||
List<String> newRowLabels = new ArrayList<>();
|
||||
List<Number> indexes = new ArrayList<>();
|
||||
List<Number> distances = new ArrayList<>();
|
||||
int i=-1;
|
||||
|
||||
while(neighbors.size() > 0) {
|
||||
|
|
|
@ -54,6 +54,7 @@ public class KnnRegressionEvaluator extends RecursiveObjectEvaluator implements
|
|||
}
|
||||
|
||||
@Override
|
||||
@SuppressWarnings({"unchecked"})
|
||||
public Object doWork(Object ... values) throws IOException {
|
||||
|
||||
if(values.length < 3) {
|
||||
|
@ -105,6 +106,7 @@ public class KnnRegressionEvaluator extends RecursiveObjectEvaluator implements
|
|||
outcomeData[i] = outcomes.get(i).doubleValue();
|
||||
}
|
||||
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
Map map = new HashMap();
|
||||
map.put("k", k);
|
||||
map.put("observations", observations.getRowCount());
|
||||
|
@ -222,6 +224,7 @@ public class KnnRegressionEvaluator extends RecursiveObjectEvaluator implements
|
|||
|
||||
Matrix obs = scaledObservations != null ? scaledObservations : observations;
|
||||
Matrix knn = KnnEvaluator.search(obs, values, k, distanceMeasure);
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> indexes = (List<Number>)knn.getAttribute("indexes");
|
||||
|
||||
if(robust) {
|
||||
|
|
|
@ -41,6 +41,7 @@ public class L1NormEvaluator extends RecursiveObjectEvaluator implements OneValu
|
|||
throw new IOException(String.format(Locale.ROOT, "Unable to find %s(...) because the value is null", constructingFactory.getFunctionName(getClass())));
|
||||
}
|
||||
else if(value instanceof List){
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> c = (List<Number>) value;
|
||||
double[] data = new double[c.size()];
|
||||
for(int i=0; i< c.size(); i++) {
|
||||
|
|
|
@ -41,6 +41,7 @@ public class LInfNormEvaluator extends RecursiveObjectEvaluator implements OneVa
|
|||
throw new IOException(String.format(Locale.ROOT, "Unable to find %s(...) because the value is null", constructingFactory.getFunctionName(getClass())));
|
||||
}
|
||||
else if(value instanceof List){
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> c = (List<Number>) value;
|
||||
double[] data = new double[c.size()];
|
||||
for(int i=0; i< c.size(); i++) {
|
||||
|
|
|
@ -67,6 +67,7 @@ public class LatLonVectorsEvaluator extends RecursiveObjectEvaluator implements
|
|||
if(!(objects[0] instanceof List)) {
|
||||
throw new IOException("The latlonVectors function expects a list of Tuples as a parameter.");
|
||||
} else {
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
List list = (List)objects[0];
|
||||
if(list.size() > 0) {
|
||||
Object o = list.get(0);
|
||||
|
@ -78,14 +79,15 @@ public class LatLonVectorsEvaluator extends RecursiveObjectEvaluator implements
|
|||
}
|
||||
}
|
||||
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Tuple> tuples = (List<Tuple>) objects[0];
|
||||
|
||||
double[][] locationVectors = new double[tuples.size()][2];
|
||||
List<String> features = new ArrayList();
|
||||
List<String> features = new ArrayList<>();
|
||||
features.add("lat");
|
||||
features.add("lon");
|
||||
|
||||
List<String> rowLabels = new ArrayList();
|
||||
List<String> rowLabels = new ArrayList<>();
|
||||
|
||||
for(int i=0; i< tuples.size(); i++) {
|
||||
Tuple tuple = tuples.get(i);
|
||||
|
|
|
@ -33,6 +33,7 @@ public class LerpEvaluator extends RecursiveNumericEvaluator implements ManyValu
|
|||
}
|
||||
|
||||
@Override
|
||||
@SuppressWarnings({"unchecked"})
|
||||
public Object doWork(Object... objects) throws IOException{
|
||||
|
||||
Object first = objects[0];
|
||||
|
@ -56,7 +57,7 @@ public class LerpEvaluator extends RecursiveNumericEvaluator implements ManyValu
|
|||
LinearInterpolator interpolator = new LinearInterpolator();
|
||||
PolynomialSplineFunction spline = interpolator.interpolate(x, y);
|
||||
|
||||
List<Number> list = new ArrayList();
|
||||
List<Number> list = new ArrayList<>();
|
||||
for(double xvalue : x) {
|
||||
list.add(spline.value(xvalue));
|
||||
}
|
||||
|
|
|
@ -41,12 +41,17 @@ public class ListCacheEvaluator extends RecursiveObjectEvaluator implements Many
|
|||
}
|
||||
|
||||
@Override
|
||||
@SuppressWarnings({"unchecked"})
|
||||
public Object doWork(Object... values) throws IOException {
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
ConcurrentMap objectCache = this.streamContext.getObjectCache();
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
List list = new ArrayList();
|
||||
|
||||
if(values.length == 0) {
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
ConcurrentHashMap m = (ConcurrentHashMap)objectCache;
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
Enumeration en = m.keys();
|
||||
while(en.hasMoreElements()) {
|
||||
list.add(en.nextElement());
|
||||
|
@ -55,9 +60,12 @@ public class ListCacheEvaluator extends RecursiveObjectEvaluator implements Many
|
|||
} else if(values.length == 1) {
|
||||
String space = (String)values[0];
|
||||
space = space.replace("\"", "");
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
ConcurrentMap spaceCache = (ConcurrentMap)objectCache.get(space);
|
||||
if(spaceCache != null) {
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
ConcurrentHashMap spaceMap = (ConcurrentHashMap)objectCache.get(space);
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
Enumeration en = spaceMap.keys();
|
||||
while(en.hasMoreElements()) {
|
||||
list.add(en.nextElement());
|
||||
|
|
|
@ -52,6 +52,7 @@ public class LoessEvaluator extends RecursiveNumericEvaluator implements ManyVal
|
|||
}
|
||||
|
||||
@Override
|
||||
@SuppressWarnings({"unchecked"})
|
||||
public Object doWork(Object... objects) throws IOException{
|
||||
|
||||
Object first = objects[0];
|
||||
|
@ -75,7 +76,7 @@ public class LoessEvaluator extends RecursiveNumericEvaluator implements ManyVal
|
|||
LoessInterpolator interpolator = new LoessInterpolator(bandwidth, robustIterations);
|
||||
double[] smooth = interpolator.smooth(x, y);
|
||||
|
||||
List<Number> list = new ArrayList();
|
||||
List<Number> list = new ArrayList<>();
|
||||
for(double yvalue : smooth) {
|
||||
list.add(yvalue);
|
||||
}
|
||||
|
|
|
@ -44,6 +44,7 @@ public class MannWhitneyUEvaluator extends RecursiveNumericListEvaluator impleme
|
|||
|
||||
@Override
|
||||
public Object doWork(Object... values) throws IOException {
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<double[]> mannWhitneyUInput = Arrays.stream(values)
|
||||
.map(value -> ((List<Number>) value).stream().mapToDouble(Number::doubleValue).toArray())
|
||||
.collect(Collectors.toList());
|
||||
|
|
|
@ -23,18 +23,20 @@ import java.util.ArrayList;
|
|||
|
||||
import java.util.Iterator;
|
||||
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
public class Matrix implements Iterable, Attributes {
|
||||
|
||||
private double[][] data;
|
||||
private List<String> columnLabels;
|
||||
private List<String> rowLabels;
|
||||
|
||||
private Map<String, Object> attributes = new HashMap();
|
||||
private Map<String, Object> attributes = new HashMap<>();
|
||||
|
||||
public Matrix(double[][] data) {
|
||||
this.data = data;
|
||||
}
|
||||
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
public Map getAttributes() {
|
||||
return this.attributes;
|
||||
}
|
||||
|
@ -75,10 +77,12 @@ public class Matrix implements Iterable, Attributes {
|
|||
return data[0].length;
|
||||
}
|
||||
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
public Iterator iterator() {
|
||||
return new MatrixIterator(data);
|
||||
}
|
||||
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
private static class MatrixIterator implements Iterator {
|
||||
|
||||
private double[][] d;
|
||||
|
@ -88,6 +92,7 @@ public class Matrix implements Iterable, Attributes {
|
|||
d = data;
|
||||
}
|
||||
|
||||
@SuppressWarnings({"unchecked"})
|
||||
public Object next() {
|
||||
double[] row = d[index++];
|
||||
List list = new ArrayList();
|
||||
|
|
|
@ -39,6 +39,7 @@ public class MatrixEvaluator extends RecursiveNumericListEvaluator implements Ma
|
|||
public Object doWork(Object... values) throws IOException {
|
||||
double[][] data = new double[values.length][];
|
||||
for(int i=0; i<values.length; i++) {
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> vec = (List<Number>)values[i];
|
||||
double[] array = new double[vec.size()];
|
||||
for(int j=0; j<array.length; j++) {
|
||||
|
|
|
@ -52,6 +52,7 @@ public class MatrixMultiplyEvaluator extends RecursiveObjectEvaluator implements
|
|||
Matrix matrix = (Matrix)o;
|
||||
return new Array2DRowRealMatrix(matrix.getData(), false);
|
||||
} else if(o instanceof List) {
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> vec = (List<Number>)o;
|
||||
double[][] data1 = new double[1][vec.size()];
|
||||
for(int i=0; i<vec.size(); i++) {
|
||||
|
|
|
@ -32,6 +32,7 @@ public class MeanDifferenceEvaluator extends RecursiveNumericEvaluator implement
|
|||
}
|
||||
|
||||
@Override
|
||||
@SuppressWarnings({"unchecked"})
|
||||
public Object doWork(Object first, Object second) throws IOException{
|
||||
if(null == first){
|
||||
throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - null found for the first value",toExpression(constructingFactory)));
|
||||
|
|
|
@ -41,6 +41,7 @@ public class MeanEvaluator extends RecursiveObjectEvaluator implements OneValueW
|
|||
throw new IOException(String.format(Locale.ROOT, "Unable to find %s(...) because the value is null", constructingFactory.getFunctionName(getClass())));
|
||||
}
|
||||
else if(value instanceof List){
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> c = (List<Number>) value;
|
||||
double[] data = new double[c.size()];
|
||||
for(int i=0; i< c.size(); i++) {
|
||||
|
|
|
@ -119,14 +119,14 @@ public class MemsetEvaluator extends RecursiveEvaluator {
|
|||
try {
|
||||
in.setStreamContext(streamContext);
|
||||
in.open();
|
||||
Map<String, List<Number>> arrays = new HashMap();
|
||||
Map<String, List<Number>> arrays = new HashMap<>();
|
||||
|
||||
//Initialize the variables
|
||||
for(String var : vars) {
|
||||
if(size > -1) {
|
||||
arrays.put(var, new ArrayList(size));
|
||||
arrays.put(var, new ArrayList<>(size));
|
||||
} else {
|
||||
arrays.put(var, new ArrayList());
|
||||
arrays.put(var, new ArrayList<>());
|
||||
}
|
||||
}
|
||||
|
||||
|
|
|
@ -57,6 +57,7 @@ public class MinMaxScaleEvaluator extends RecursiveObjectEvaluator implements Ma
|
|||
return new Matrix(scaled);
|
||||
|
||||
} else if(values[0] instanceof List) {
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> vec = (List)values[0];
|
||||
double[] data = new double[vec.size()];
|
||||
|
||||
|
@ -65,7 +66,7 @@ public class MinMaxScaleEvaluator extends RecursiveObjectEvaluator implements Ma
|
|||
}
|
||||
|
||||
data = scale(data, min, max);
|
||||
List<Number> scaled = new ArrayList(data.length);
|
||||
List<Number> scaled = new ArrayList<>(data.length);
|
||||
for(double d : data) {
|
||||
scaled.add(d);
|
||||
}
|
||||
|
|
|
@ -43,6 +43,7 @@ public class ModeEvaluator extends RecursiveObjectEvaluator implements OneValueW
|
|||
throw new IOException(String.format(Locale.ROOT, "Unable to find %s(...) because the value is null", constructingFactory.getFunctionName(getClass())));
|
||||
}
|
||||
else if(value instanceof List){
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> c = (List<Number>) value;
|
||||
double[] data = new double[c.size()];
|
||||
for(int i=0; i< c.size(); i++) {
|
||||
|
@ -50,7 +51,7 @@ public class ModeEvaluator extends RecursiveObjectEvaluator implements OneValueW
|
|||
}
|
||||
|
||||
double[] mode = StatUtils.mode(data);
|
||||
List<Number> l = new ArrayList();
|
||||
List<Number> l = new ArrayList<>();
|
||||
for(double d : mode) {
|
||||
l.add(d);
|
||||
}
|
||||
|
|
|
@ -35,8 +35,10 @@ import org.apache.solr.client.solrj.io.stream.expr.StreamFactory;
|
|||
public class MonteCarloEvaluator extends RecursiveEvaluator {
|
||||
protected static final long serialVersionUID = 1L;
|
||||
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
private Map variables = new LinkedHashMap();
|
||||
|
||||
@SuppressWarnings({"unchecked"})
|
||||
public MonteCarloEvaluator(StreamExpression expression, StreamFactory factory) throws IOException{
|
||||
super(expression, factory);
|
||||
|
||||
|
@ -44,11 +46,8 @@ public class MonteCarloEvaluator extends RecursiveEvaluator {
|
|||
//Get all the named params
|
||||
Set<String> echo = null;
|
||||
boolean echoAll = false;
|
||||
String currentName = null;
|
||||
for(StreamExpressionParameter np : namedParams) {
|
||||
String name = ((StreamExpressionNamedParameter)np).getName();
|
||||
currentName = name;
|
||||
|
||||
|
||||
StreamExpressionParameter param = ((StreamExpressionNamedParameter)np).getParameter();
|
||||
if(factory.isEvaluator((StreamExpression)param)) {
|
||||
|
@ -83,7 +82,7 @@ public class MonteCarloEvaluator extends RecursiveEvaluator {
|
|||
StreamEvaluator iterationsEvaluator = containedEvaluators.get(1);
|
||||
Number itNum = (Number)iterationsEvaluator.evaluate(tuple);
|
||||
int it = itNum.intValue();
|
||||
List<Number> results = new ArrayList();
|
||||
List<Number> results = new ArrayList<>();
|
||||
for(int i=0; i<it; i++) {
|
||||
populateVariables(tuple);
|
||||
Number result = (Number)function.evaluate(tuple);
|
||||
|
@ -106,13 +105,14 @@ public class MonteCarloEvaluator extends RecursiveEvaluator {
|
|||
|
||||
private void populateVariables(Tuple contextTuple) throws IOException {
|
||||
|
||||
@SuppressWarnings({"unchecked"})
|
||||
Set<Map.Entry<String, Object>> entries = variables.entrySet();
|
||||
|
||||
for(Map.Entry<String, Object> entry : entries) {
|
||||
String name = entry.getKey();
|
||||
Object o = entry.getValue();
|
||||
if(o instanceof TupleStream) {
|
||||
List<Tuple> tuples = new ArrayList();
|
||||
List<Tuple> tuples = new ArrayList<>();
|
||||
TupleStream tStream = (TupleStream)o;
|
||||
tStream.setStreamContext(streamContext);
|
||||
try {
|
||||
|
|
|
@ -49,6 +49,7 @@ public class MultiKmeansEvaluator extends RecursiveObjectEvaluator implements Ma
|
|||
}
|
||||
|
||||
@Override
|
||||
@SuppressWarnings({"unchecked"})
|
||||
public Object doWork(Object... values) throws IOException {
|
||||
|
||||
if(values.length != 3) {
|
||||
|
@ -81,10 +82,12 @@ public class MultiKmeansEvaluator extends RecursiveObjectEvaluator implements Ma
|
|||
throw new IOException("The third parameter for multiKmeans should be trials.");
|
||||
}
|
||||
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
KMeansPlusPlusClusterer<KmeansEvaluator.ClusterPoint> kmeans = new KMeansPlusPlusClusterer(k, maxIterations);
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
MultiKMeansPlusPlusClusterer multiKmeans = new MultiKMeansPlusPlusClusterer(kmeans, trials);
|
||||
|
||||
List<KmeansEvaluator.ClusterPoint> points = new ArrayList();
|
||||
List<KmeansEvaluator.ClusterPoint> points = new ArrayList<>();
|
||||
double[][] data = matrix.getData();
|
||||
|
||||
List<String> ids = matrix.getRowLabels();
|
||||
|
@ -94,6 +97,7 @@ public class MultiKmeansEvaluator extends RecursiveObjectEvaluator implements Ma
|
|||
points.add(new KmeansEvaluator.ClusterPoint(ids.get(i), vec));
|
||||
}
|
||||
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
Map fields = new HashMap();
|
||||
|
||||
fields.put("k", k);
|
||||
|
|
|
@ -41,6 +41,7 @@ public class MultiVariateNormalDistributionEvaluator extends RecursiveObjectEval
|
|||
throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - null found for the second value",toExpression(constructingFactory)));
|
||||
}
|
||||
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> means = (List<Number>)first;
|
||||
Matrix covar = (Matrix)second;
|
||||
|
||||
|
|
|
@ -38,7 +38,7 @@ public class NaturalEvaluator extends RecursiveNumericEvaluator implements OneVa
|
|||
@Override
|
||||
public Object doWork(Object value){
|
||||
int natural = ((Number)value).intValue();
|
||||
List<Number> naturals = new ArrayList();
|
||||
List<Number> naturals = new ArrayList<>();
|
||||
for(int i=0; i<natural; i++) {
|
||||
naturals.add(i);
|
||||
}
|
||||
|
|
|
@ -41,6 +41,7 @@ public class NormEvaluator extends RecursiveObjectEvaluator implements OneValueW
|
|||
throw new IOException(String.format(Locale.ROOT, "Unable to find %s(...) because the value is null", constructingFactory.getFunctionName(getClass())));
|
||||
}
|
||||
else if(value instanceof List){
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> c = (List<Number>) value;
|
||||
double[] data = new double[c.size()];
|
||||
for(int i=0; i< c.size(); i++) {
|
||||
|
|
|
@ -67,13 +67,14 @@ public class NormalizeSumEvaluator extends RecursiveObjectEvaluator implements M
|
|||
m.setColumnLabels(matrix.getColumnLabels());
|
||||
return m;
|
||||
} else if(value instanceof List) {
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> vals = (List<Number>)value;
|
||||
double[] doubles = new double[vals.size()];
|
||||
for(int i=0; i<doubles.length; i++) {
|
||||
doubles[i] = vals.get(i).doubleValue();
|
||||
}
|
||||
|
||||
List<Number> unitList = new ArrayList(doubles.length);
|
||||
List<Number> unitList = new ArrayList<>(doubles.length);
|
||||
double[] unitArray = MathArrays.normalizeArray(doubles, sumTo);
|
||||
for(double d : unitArray) {
|
||||
unitList.add(d);
|
||||
|
|
|
@ -42,6 +42,7 @@ public class NotNullEvaluator extends RecursiveBooleanEvaluator implements ManyV
|
|||
|
||||
if(values[0] instanceof String) {
|
||||
//Check to see if the this tuple had a null value for that string.
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
Map tupleContext = getStreamContext().getTupleContext();
|
||||
String nullField = (String)tupleContext.get("null");
|
||||
if(nullField != null && nullField.equals(values[0])) {
|
||||
|
|
|
@ -37,6 +37,7 @@ public class OLSRegressionEvaluator extends RecursiveObjectEvaluator implements
|
|||
}
|
||||
|
||||
@Override
|
||||
@SuppressWarnings({"unchecked"})
|
||||
public Object doWork(Object ... values) throws IOException {
|
||||
|
||||
Matrix observations = null;
|
||||
|
@ -62,6 +63,7 @@ public class OLSRegressionEvaluator extends RecursiveObjectEvaluator implements
|
|||
|
||||
OLSMultipleLinearRegression multipleLinearRegression = (OLSMultipleLinearRegression)regress(observationData, outcomeData);
|
||||
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
Map map = new HashMap();
|
||||
|
||||
map.put("regressandVariance", multipleLinearRegression.estimateRegressandVariance());
|
||||
|
@ -80,7 +82,9 @@ public class OLSRegressionEvaluator extends RecursiveObjectEvaluator implements
|
|||
return new MultipleRegressionTuple(multipleLinearRegression, map);
|
||||
}
|
||||
|
||||
@SuppressWarnings({"unchecked"})
|
||||
private List<Number> list(double[] values) {
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
List list = new ArrayList();
|
||||
for(double d : values) {
|
||||
list.add(d);
|
||||
|
@ -105,9 +109,10 @@ public class OLSRegressionEvaluator extends RecursiveObjectEvaluator implements
|
|||
}
|
||||
|
||||
public double predict(double[] values) {
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> weights = (List<Number>)get("regressionParameters");
|
||||
double prediction = 0.0;
|
||||
List<Number> predictors = new ArrayList();
|
||||
List<Number> predictors = new ArrayList<>();
|
||||
predictors.add(1.0D);
|
||||
for(double d : values) {
|
||||
predictors.add(d);
|
||||
|
|
|
@ -38,7 +38,7 @@ public class OnesEvaluator extends RecursiveNumericEvaluator implements OneValue
|
|||
@Override
|
||||
public Object doWork(Object value){
|
||||
int size = ((Number)value).intValue();
|
||||
List<Number> ones = new ArrayList();
|
||||
List<Number> ones = new ArrayList<>();
|
||||
for(int i=0; i<size; i++) {
|
||||
ones.add(1);
|
||||
}
|
||||
|
|
|
@ -32,6 +32,7 @@ public class OscillateEvaluator extends RecursiveNumericEvaluator implements Man
|
|||
}
|
||||
|
||||
@Override
|
||||
@SuppressWarnings({"unchecked"})
|
||||
public Object doWork(Object... objects) throws IOException{
|
||||
|
||||
if(objects.length != 3) {
|
||||
|
@ -46,6 +47,7 @@ public class OscillateEvaluator extends RecursiveNumericEvaluator implements Man
|
|||
HarmonicOscillator pf = new HarmonicOscillator(amp, om, phase);
|
||||
double[] x = new double[128];
|
||||
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
List list = new ArrayList();
|
||||
for(int i=0; i<128; i++) {
|
||||
double yvalue= pf.value(i);
|
||||
|
|
|
@ -35,6 +35,7 @@ public class OutliersEvaluator extends RecursiveObjectEvaluator implements ManyV
|
|||
}
|
||||
|
||||
@Override
|
||||
@SuppressWarnings({"unchecked", "rawtypes"})
|
||||
public Object doWork(Object... values) throws IOException{
|
||||
|
||||
if(values.length < 4) {
|
||||
|
@ -74,13 +75,13 @@ public class OutliersEvaluator extends RecursiveObjectEvaluator implements ManyV
|
|||
throw new IOException("The optional fifth parameter of the outliers function is an array of Tuples that are paired with the numeric array of values to be tested.");
|
||||
}
|
||||
} else {
|
||||
tuples = new ArrayList();
|
||||
tuples = new ArrayList<>();
|
||||
for(int i=0; i<vec.size(); i++) {
|
||||
tuples.add(new Tuple(new HashMap()));
|
||||
}
|
||||
}
|
||||
|
||||
List<Tuple> outliers = new ArrayList();
|
||||
List<Tuple> outliers = new ArrayList<>();
|
||||
|
||||
if(dist instanceof IntegerDistribution) {
|
||||
|
||||
|
|
|
@ -34,6 +34,7 @@ public class PairSortEvaluator extends RecursiveNumericEvaluator implements TwoV
|
|||
}
|
||||
|
||||
@Override
|
||||
@SuppressWarnings({"unchecked"})
|
||||
public Object doWork(Object first, Object second) throws IOException{
|
||||
if(null == first){
|
||||
throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - null found for the first value",toExpression(constructingFactory)));
|
||||
|
@ -55,7 +56,7 @@ public class PairSortEvaluator extends RecursiveNumericEvaluator implements TwoV
|
|||
throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - first list (%d) has a different size than the second list (%d)",toExpression(constructingFactory), l1.size(), l2.size()));
|
||||
}
|
||||
|
||||
List<double[]> pairs = new ArrayList();
|
||||
List<double[]> pairs = new ArrayList<>();
|
||||
for(int idx = 0; idx < l1.size(); ++idx){
|
||||
double[] pair = new double[2];
|
||||
pair[0]= l1.get(idx).doubleValue();
|
||||
|
|
|
@ -42,9 +42,11 @@ public class PairedTTestEvaluator extends RecursiveNumericListEvaluator implemen
|
|||
public Object doWork(Object value1, Object value2) throws IOException {
|
||||
|
||||
TTest tTest = new TTest();
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
Map map = new HashMap();
|
||||
Tuple tuple = new Tuple(map);
|
||||
if(value1 instanceof List) {
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> values1 = (List<Number>)value1;
|
||||
double[] samples1 = new double[values1.size()];
|
||||
|
||||
|
@ -53,6 +55,7 @@ public class PairedTTestEvaluator extends RecursiveNumericListEvaluator implemen
|
|||
}
|
||||
|
||||
if(value2 instanceof List) {
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> values2 = (List<Number>) value2;
|
||||
double[] samples2 = new double[values2.size()];
|
||||
|
||||
|
|
|
@ -50,8 +50,9 @@ public class PercentileEvaluator extends RecursiveNumericEvaluator implements Tw
|
|||
} else if(second instanceof List){
|
||||
Percentile percentile = new Percentile();
|
||||
percentile.setData(((List<?>) first).stream().mapToDouble(value -> ((Number) value).doubleValue()).toArray());
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> values = (List<Number>) second;
|
||||
List<Number> percentiles = new ArrayList();
|
||||
List<Number> percentiles = new ArrayList<>();
|
||||
for(Number value : values) {
|
||||
percentiles.add(percentile.evaluate(value.doubleValue()));
|
||||
}
|
||||
|
|
|
@ -53,6 +53,7 @@ public class PivotEvaluator extends RecursiveObjectEvaluator implements ManyValu
|
|||
Object value4 = values[3];
|
||||
|
||||
if(value1 instanceof List) {
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Tuple> tuples = (List<Tuple>)value1;
|
||||
String x = (String)value2;
|
||||
x = x.replace("\"", "");
|
||||
|
@ -62,8 +63,8 @@ public class PivotEvaluator extends RecursiveObjectEvaluator implements ManyValu
|
|||
String vlabel = (String)value4;
|
||||
vlabel = vlabel.replace("\"", "");
|
||||
|
||||
Set<String> xset = new TreeSet();
|
||||
Set<String> yset = new TreeSet();
|
||||
Set<String> xset = new TreeSet<>();
|
||||
Set<String> yset = new TreeSet<>();
|
||||
|
||||
for(int i=0; i<tuples.size(); i++) {
|
||||
Tuple tuple = tuples.get(i);
|
||||
|
@ -73,8 +74,8 @@ public class PivotEvaluator extends RecursiveObjectEvaluator implements ManyValu
|
|||
|
||||
double[][] data = new double[xset.size()][yset.size()];
|
||||
|
||||
List<String> xlabels = new ArrayList(xset.size());
|
||||
Map<String, Integer> xindexes = new HashMap();
|
||||
List<String> xlabels = new ArrayList<>(xset.size());
|
||||
Map<String, Integer> xindexes = new HashMap<>();
|
||||
int xindex = 0;
|
||||
for (String xlabel :xset) {
|
||||
xlabels.add(xlabel);
|
||||
|
@ -82,8 +83,8 @@ public class PivotEvaluator extends RecursiveObjectEvaluator implements ManyValu
|
|||
++xindex;
|
||||
}
|
||||
|
||||
List<String> ylabels = new ArrayList(yset.size());
|
||||
Map<String, Integer> yindexes = new HashMap();
|
||||
List<String> ylabels = new ArrayList<>(yset.size());
|
||||
Map<String, Integer> yindexes = new HashMap<>();
|
||||
int yindex = 0;
|
||||
for (String ylabel : yset) {
|
||||
ylabels.add(ylabel);
|
||||
|
|
|
@ -36,6 +36,7 @@ public class PolyFitDerivativeEvaluator extends RecursiveNumericEvaluator implem
|
|||
}
|
||||
|
||||
@Override
|
||||
@SuppressWarnings({"unchecked"})
|
||||
public Object doWork(Object... objects) throws IOException{
|
||||
|
||||
if(objects.length > 3) {
|
||||
|
@ -92,6 +93,7 @@ public class PolyFitDerivativeEvaluator extends RecursiveNumericEvaluator implem
|
|||
PolynomialFunction pf = new PolynomialFunction(coef);
|
||||
UnivariateFunction univariateFunction = pf.derivative();
|
||||
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
List list = new ArrayList();
|
||||
for(double xvalue : x) {
|
||||
double yvalue= univariateFunction.value(xvalue);
|
||||
|
|
|
@ -35,6 +35,7 @@ public class PolyFitEvaluator extends RecursiveNumericEvaluator implements ManyV
|
|||
}
|
||||
|
||||
@Override
|
||||
@SuppressWarnings({"unchecked", "rawtypes"})
|
||||
public Object doWork(Object... objects) throws IOException{
|
||||
|
||||
if(objects.length > 3) {
|
||||
|
|
|
@ -49,8 +49,9 @@ public class PowerEvaluator extends RecursiveNumericEvaluator implements TwoValu
|
|||
Number exponent = (Number) second;
|
||||
return Math.pow(value.doubleValue(), exponent.doubleValue());
|
||||
} else if(second instanceof List) {
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> exponents = (List<Number>) second;
|
||||
List<Number> pows = new ArrayList();
|
||||
List<Number> pows = new ArrayList<>();
|
||||
for(Number exponent : exponents) {
|
||||
pows.add(Math.pow(value.doubleValue(), exponent.doubleValue()));
|
||||
}
|
||||
|
@ -59,11 +60,12 @@ public class PowerEvaluator extends RecursiveNumericEvaluator implements TwoValu
|
|||
throw new IOException("The second parameter to the pow function must either be a scalar or list of scalars");
|
||||
}
|
||||
} else if(first instanceof List) {
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> values = (List<Number>) first;
|
||||
if(second instanceof Number) {
|
||||
Number exponent = (Number) second;
|
||||
|
||||
List<Number> out = new ArrayList(values.size());
|
||||
List<Number> out = new ArrayList<>(values.size());
|
||||
for (Number value : values) {
|
||||
out.add(Math.pow(value.doubleValue(), exponent.doubleValue()));
|
||||
}
|
||||
|
@ -71,7 +73,8 @@ public class PowerEvaluator extends RecursiveNumericEvaluator implements TwoValu
|
|||
return out;
|
||||
} else if(second instanceof List) {
|
||||
|
||||
List<Number> out = new ArrayList(values.size());
|
||||
List<Number> out = new ArrayList<>(values.size());
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> exponents = (List<Number>)second;
|
||||
if(values.size() != exponents.size()) {
|
||||
throw new IOException("The pow function requires vectors of equal size if two vectors are provided.");
|
||||
|
|
|
@ -68,6 +68,7 @@ public class PredictEvaluator extends RecursiveObjectEvaluator implements ManyVa
|
|||
|
||||
OLSRegressionEvaluator.MultipleRegressionTuple regressedTuple = (OLSRegressionEvaluator.MultipleRegressionTuple) first;
|
||||
if (second instanceof List) {
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> list = (List<Number>) second;
|
||||
double[] predictors = new double[list.size()];
|
||||
|
||||
|
@ -80,7 +81,7 @@ public class PredictEvaluator extends RecursiveObjectEvaluator implements ManyVa
|
|||
|
||||
Matrix m = (Matrix) second;
|
||||
double[][] data = m.getData();
|
||||
List<Number> predictions = new ArrayList();
|
||||
List<Number> predictions = new ArrayList<>();
|
||||
for (double[] predictors : data) {
|
||||
predictions.add(regressedTuple.predict(predictors));
|
||||
}
|
||||
|
@ -97,8 +98,9 @@ public class PredictEvaluator extends RecursiveObjectEvaluator implements ManyVa
|
|||
predictors[0] = ((Number)second).doubleValue();
|
||||
return regressedTuple.predict(predictors);
|
||||
} else if(second instanceof List) {
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> vec = (List<Number>)second;
|
||||
List<Number> predictions = new ArrayList();
|
||||
List<Number> predictions = new ArrayList<>();
|
||||
for(Number num : vec) {
|
||||
double[] predictors = new double[1];
|
||||
predictors[0] = num.doubleValue();
|
||||
|
@ -109,6 +111,7 @@ public class PredictEvaluator extends RecursiveObjectEvaluator implements ManyVa
|
|||
} else {
|
||||
//Handle multi-variate regression
|
||||
if (second instanceof List) {
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> list = (List<Number>) second;
|
||||
double[] predictors = new double[list.size()];
|
||||
|
||||
|
@ -128,7 +131,7 @@ public class PredictEvaluator extends RecursiveObjectEvaluator implements ManyVa
|
|||
m = regressedTuple.scale(m);
|
||||
}
|
||||
double[][] data = m.getData();
|
||||
List<Number> predictions = new ArrayList();
|
||||
List<Number> predictions = new ArrayList<>();
|
||||
for (double[] predictors : data) {
|
||||
predictions.add(regressedTuple.predict(predictors));
|
||||
}
|
||||
|
@ -162,7 +165,7 @@ public class PredictEvaluator extends RecursiveObjectEvaluator implements ManyVa
|
|||
Matrix m = (Matrix) second;
|
||||
double[][] data = m.getData();
|
||||
if (data[0].length == 2) {
|
||||
List<Number> out = new ArrayList();
|
||||
List<Number> out = new ArrayList<>();
|
||||
for (double[] row : data) {
|
||||
out.add(bivariateFunction.value(row[0], row[1]));
|
||||
}
|
||||
|
|
|
@ -44,7 +44,7 @@ public class PrimesEvaluator extends RecursiveNumericEvaluator implements ManyVa
|
|||
|
||||
int sizeNum = ((Number)values[0]).intValue();
|
||||
int startNum = ((Number)values[1]).intValue();
|
||||
List<Number> primes = new ArrayList();
|
||||
List<Number> primes = new ArrayList<>();
|
||||
|
||||
for(int i=0; i< sizeNum; i++) {
|
||||
int prime = Primes.nextPrime(startNum);
|
||||
|
|
|
@ -37,6 +37,7 @@ public class PutCacheEvaluator extends RecursiveObjectEvaluator implements ManyV
|
|||
}
|
||||
|
||||
@Override
|
||||
@SuppressWarnings({"unchecked", "rawtypes"})
|
||||
public Object doWork(Object... values) throws IOException {
|
||||
ConcurrentMap objectCache = this.streamContext.getObjectCache();
|
||||
if(values.length == 3) {
|
||||
|
|
|
@ -76,7 +76,7 @@ public abstract class RecursiveEvaluator implements StreamEvaluator, ValueWorker
|
|||
//Let's first check to see if we have a List of Strings.
|
||||
//If we do let's try and convert to a list of doubles and see what happens
|
||||
try {
|
||||
List<Number> vector = new ArrayList();
|
||||
List<Number> vector = new ArrayList<>();
|
||||
boolean allDoubles = true;
|
||||
for(Object o : (Collection)value) {
|
||||
if(o instanceof String) {
|
||||
|
@ -119,6 +119,7 @@ public abstract class RecursiveEvaluator implements StreamEvaluator, ValueWorker
|
|||
|
||||
}
|
||||
|
||||
@SuppressWarnings({"unchecked"})
|
||||
protected Object normalizeOutputType(Object value) {
|
||||
if(null == value){
|
||||
return null;
|
||||
|
@ -144,7 +145,9 @@ public abstract class RecursiveEvaluator implements StreamEvaluator, ValueWorker
|
|||
//If its a tuple and not a inner class that has extended tuple, which is done in a number of cases so that mathematical models
|
||||
//can be contained within a tuple.
|
||||
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
Tuple tuple = (Tuple)value;
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
Map map = new HashMap();
|
||||
for(Object o : tuple.fields.keySet()) {
|
||||
Object v = tuple.fields.get(o);
|
||||
|
|
|
@ -49,7 +49,9 @@ public class RegressionEvaluator extends RecursiveNumericEvaluator implements Tw
|
|||
throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - found type %s for the second value, expecting a list of numbers",toExpression(constructingFactory), first.getClass().getSimpleName()));
|
||||
}
|
||||
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> l1 = (List<Number>)first;
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> l2 = (List<Number>)second;
|
||||
|
||||
if(l2.size() < l1.size()){
|
||||
|
|
|
@ -37,12 +37,14 @@ public class RemoveCacheEvaluator extends RecursiveObjectEvaluator implements Ma
|
|||
|
||||
@Override
|
||||
public Object doWork(Object... values) throws IOException {
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
ConcurrentMap objectCache = this.streamContext.getObjectCache();
|
||||
if(values.length == 2) {
|
||||
String space = (String)values[0];
|
||||
String key = (String)values[1];
|
||||
space = space.replace("\"", "");
|
||||
key = key.replace("\"", "");
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
ConcurrentMap spaceCache = (ConcurrentMap)objectCache.get(space);
|
||||
|
||||
if(spaceCache != null) {
|
||||
|
|
|
@ -39,7 +39,7 @@ public class RepeatEvaluator extends RecursiveNumericEvaluator implements TwoVal
|
|||
public Object doWork(Object value1, Object value2){
|
||||
double d = ((Number)value1).doubleValue();
|
||||
int size = ((Number)value2).intValue();
|
||||
List<Number> repeated = new ArrayList();
|
||||
List<Number> repeated = new ArrayList<>();
|
||||
for(int i=0; i<size; i++) {
|
||||
repeated.add(d);
|
||||
}
|
||||
|
|
|
@ -43,7 +43,7 @@ public class RowAtEvaluator extends RecursiveObjectEvaluator implements TwoValue
|
|||
Matrix matrix = (Matrix) value1;
|
||||
Number index = (Number) value2;
|
||||
double[] row = matrix.getData()[index.intValue()];
|
||||
List<Number> list = new ArrayList();
|
||||
List<Number> list = new ArrayList<>();
|
||||
for(double d : row) {
|
||||
list.add(d);
|
||||
}
|
||||
|
|
|
@ -83,7 +83,7 @@ public class SampleEvaluator extends RecursiveObjectEvaluator implements ManyVal
|
|||
} else {
|
||||
MultivariateNormalDistribution multivariateNormalDistribution = (MultivariateNormalDistribution)first;
|
||||
double[] sample = multivariateNormalDistribution.sample();
|
||||
List<Number> sampleList = new ArrayList(sample.length);
|
||||
List<Number> sampleList = new ArrayList<>(sample.length);
|
||||
for(int i=0; i<sample.length; i++) {
|
||||
sampleList.add(sample[i]);
|
||||
}
|
||||
|
|
|
@ -40,8 +40,9 @@ public class ScalarAddEvaluator extends RecursiveObjectEvaluator implements TwoV
|
|||
|
||||
double d = ((Number)value1).doubleValue();
|
||||
if(value2 instanceof List){
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> nums = (List<Number>)value2;
|
||||
List<Number> out = new ArrayList();
|
||||
List<Number> out = new ArrayList<>();
|
||||
for(Number num : nums) {
|
||||
out.add(operate(num.doubleValue(), d));
|
||||
}
|
||||
|
|
|
@ -51,7 +51,7 @@ public class ScaleEvaluator extends RecursiveNumericEvaluator implements TwoValu
|
|||
|
||||
double[] scaleOver;
|
||||
if(second instanceof Number){
|
||||
scaleOver = Arrays.asList((Number)second).stream().mapToDouble(value -> ((Number)value).doubleValue()).toArray();
|
||||
scaleOver = Arrays.asList((Number)second).stream().mapToDouble(value -> (value).doubleValue()).toArray();
|
||||
}
|
||||
else{
|
||||
scaleOver = ((List<?>)second).stream().mapToDouble(value -> ((Number)value).doubleValue()).toArray();
|
||||
|
|
|
@ -41,9 +41,10 @@ public class SetColumnLabelsEvaluator extends RecursiveObjectEvaluator implement
|
|||
} else {
|
||||
Matrix matrix = (Matrix)value1;
|
||||
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
List colLabels = (List)value2;
|
||||
//Convert numeric labels to strings.
|
||||
List<String> strLabels = new ArrayList(colLabels.size());
|
||||
List<String> strLabels = new ArrayList<>(colLabels.size());
|
||||
for(Object o : colLabels) {
|
||||
strLabels.add(o.toString());
|
||||
}
|
||||
|
|
|
@ -40,11 +40,12 @@ public class SetRowLabelsEvaluator extends RecursiveObjectEvaluator implements T
|
|||
throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - found type %s for value, expecting an array of labels.",toExpression(constructingFactory), value2.getClass().getSimpleName()));
|
||||
} else {
|
||||
Matrix matrix = (Matrix)value1;
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
List rowlabels = (List)value2;
|
||||
|
||||
//Convert numeric labels to strings.
|
||||
|
||||
List<String> strLabels = new ArrayList(rowlabels.size());
|
||||
List<String> strLabels = new ArrayList<>(rowlabels.size());
|
||||
|
||||
for(Object o : rowlabels) {
|
||||
strLabels.add(o.toString());
|
||||
|
|
|
@ -38,6 +38,7 @@ public class SetValueEvaluator extends RecursiveObjectEvaluator implements ManyV
|
|||
}
|
||||
|
||||
@Override
|
||||
@SuppressWarnings({"unchecked"})
|
||||
public Object doWork(Object... values) throws IOException {
|
||||
if(values[0] instanceof Tuple) {
|
||||
Tuple tuple = (Tuple)values[0];
|
||||
|
@ -47,6 +48,7 @@ public class SetValueEvaluator extends RecursiveObjectEvaluator implements ManyV
|
|||
value = ((String)value).replace("\"", "");
|
||||
}
|
||||
key = key.replace("\"", "");
|
||||
@SuppressWarnings({"rawtypes"})
|
||||
Map map = new HashMap(tuple.fields);
|
||||
map.put(key, value);
|
||||
return new Tuple(map);
|
||||
|
|
|
@ -33,6 +33,7 @@ public class SplineEvaluator extends RecursiveNumericEvaluator implements ManyVa
|
|||
}
|
||||
|
||||
@Override
|
||||
@SuppressWarnings({"unchecked"})
|
||||
public Object doWork(Object... objects) throws IOException{
|
||||
|
||||
Object first = objects[0];
|
||||
|
@ -56,7 +57,7 @@ public class SplineEvaluator extends RecursiveNumericEvaluator implements ManyVa
|
|||
SplineInterpolator interpolator = new SplineInterpolator();
|
||||
PolynomialSplineFunction spline = interpolator.interpolate(x, y);
|
||||
|
||||
List<Number> list = new ArrayList();
|
||||
List<Number> list = new ArrayList<>();
|
||||
for(double xvalue : x) {
|
||||
list.add(spline.value(xvalue));
|
||||
}
|
||||
|
|
|
@ -43,7 +43,7 @@ public class SplitEvaluator extends RecursiveObjectEvaluator implements TwoValue
|
|||
String s = value1.toString();
|
||||
String p = value2.toString();
|
||||
String[] tokens = s.split(p, -1);
|
||||
List<String> strings = new ArrayList(tokens.length);
|
||||
List<String> strings = new ArrayList<>(tokens.length);
|
||||
for(String tok : tokens) {
|
||||
strings.add(tok);
|
||||
}
|
||||
|
|
|
@ -44,6 +44,7 @@ public class StandardDeviationEvaluator extends RecursiveObjectEvaluator impleme
|
|||
throw new IOException(String.format(Locale.ROOT, "Unable to find %s(...) because the value is null", constructingFactory.getFunctionName(getClass())));
|
||||
}
|
||||
else if(value instanceof List){
|
||||
@SuppressWarnings({"unchecked"})
|
||||
List<Number> c = (List<Number>) value;
|
||||
double[] data = new double[c.size()];
|
||||
for(int i=0; i< c.size(); i++) {
|
||||
|
|
|
@ -48,7 +48,7 @@ public class SumColumnsEvaluator extends RecursiveObjectEvaluator implements One
|
|||
double[][] data = matrix.getData();
|
||||
RealMatrix realMatrix = new Array2DRowRealMatrix(data, false);
|
||||
|
||||
List<Number> sums = new ArrayList(data[0].length);
|
||||
List<Number> sums = new ArrayList<>(data[0].length);
|
||||
|
||||
for(int i=0; i<data[0].length; i++) {
|
||||
double sum = 0;
|
||||
|
|
|
@ -32,6 +32,7 @@ public class SumDifferenceEvaluator extends RecursiveNumericEvaluator implements
|
|||
}
|
||||
|
||||
@Override
|
||||
@SuppressWarnings({"unchecked"})
|
||||
public Object doWork(Object first, Object second) throws IOException{
|
||||
if(null == first){
|
||||
throw new IOException(String.format(Locale.ROOT,"Invalid expression %s - null found for the first value",toExpression(constructingFactory)));
|
||||
|
|
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in New Issue