MATH-1592: Remove "NumberTransformer" (transformations should be done by caller).
Closes #186.
This commit is contained in:
Samy Badjoudj
Gilles Sadowski
parent
bcdc7fbba7
commit
9cfd17601b
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@ -1,190 +0,0 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.commons.math4.legacy.stat.descriptive;
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import java.io.Serializable;
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import java.util.Collection;
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import java.util.HashMap;
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import java.util.Map;
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import java.util.Set;
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import org.apache.commons.math4.legacy.exception.MathIllegalArgumentException;
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/**
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* This TansformerMap automates the transformation of mixed object types.
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* It provides a means to set NumberTransformers that will be selected
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* based on the Class of the object handed to the Maps
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* <code>double transform(Object o)</code> method.
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*/
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public class TransformerMap implements UnivariateStatistic.NumberTransformer, Serializable {
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/** Serializable version identifier */
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private static final long serialVersionUID = 4605318041528645258L;
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/**
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* A default Number Transformer for Numbers and numeric Strings.
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*/
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private UnivariateStatistic.NumberTransformer defaultTransformer;
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/**
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* The internal Map.
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*/
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private Map<Class<?>, UnivariateStatistic.NumberTransformer> map;
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/**
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* Build a map containing only the default transformer.
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*/
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public TransformerMap() {
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map = new HashMap<>();
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defaultTransformer = new UnivariateStatistic.DefaultTransformer();
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}
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/**
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* Tests if a Class is present in the TransformerMap.
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* @param key Class to check
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* @return true|false
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*/
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public boolean containsClass(Class<?> key) {
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return map.containsKey(key);
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}
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/**
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* Tests if a NumberTransformer is present in the TransformerMap.
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* @param value NumberTransformer to check
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* @return true|false
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*/
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public boolean containsTransformer(UnivariateStatistic.NumberTransformer value) {
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return map.containsValue(value);
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}
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/**
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* Returns the Transformer that is mapped to a class
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* if mapping is not present, this returns null.
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* @param key The Class of the object
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* @return the mapped NumberTransformer or null.
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*/
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public UnivariateStatistic.NumberTransformer getTransformer(Class<?> key) {
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return map.get(key);
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}
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/**
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* Sets a Class to Transformer Mapping in the Map. If
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* the Class is already present, this overwrites that
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* mapping.
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* @param key The Class
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* @param transformer The NumberTransformer
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* @return the replaced transformer if one is present
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*/
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public UnivariateStatistic.NumberTransformer putTransformer(Class<?> key, UnivariateStatistic.NumberTransformer transformer) {
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return map.put(key, transformer);
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}
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/**
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* Removes a Class to Transformer Mapping in the Map.
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* @param key The Class
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* @return the removed transformer if one is present or
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* null if none was present.
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*/
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public UnivariateStatistic.NumberTransformer removeTransformer(Class<?> key) {
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return map.remove(key);
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}
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/**
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* Clears all the Class to Transformer mappings.
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*/
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public void clear() {
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map.clear();
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}
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/**
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* Returns the Set of Classes used as keys in the map.
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* @return Set of Classes
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*/
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public Set<Class<?>> classes() {
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return map.keySet();
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}
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/**
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* Returns the Set of NumberTransformers used as values
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* in the map.
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* @return Set of NumberTransformers
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*/
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public Collection<UnivariateStatistic.NumberTransformer> transformers() {
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return map.values();
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}
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/**
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* Attempts to transform the Object against the map of
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* NumberTransformers. Otherwise it returns Double.NaN.
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*
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* @param o the Object to be transformed.
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* @return the double value of the Object.
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* @throws MathIllegalArgumentException if the Object can not be
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* transformed into a Double.
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* @see UnivariateStatistic.NumberTransformer#transform(java.lang.Object)
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*/
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@Override
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public double transform(Object o) throws MathIllegalArgumentException {
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double value = Double.NaN;
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if (o instanceof Number || o instanceof String) {
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value = defaultTransformer.transform(o);
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} else {
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UnivariateStatistic.NumberTransformer trans = getTransformer(o.getClass());
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if (trans != null) {
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value = trans.transform(o);
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}
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}
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return value;
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}
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/** {@inheritDoc} */
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@Override
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public boolean equals(Object other) {
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if (this == other) {
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return true;
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}
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if (other instanceof TransformerMap) {
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TransformerMap rhs = (TransformerMap) other;
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if (! defaultTransformer.equals(rhs.defaultTransformer)) {
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return false;
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}
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if (map.size() != rhs.map.size()) {
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return false;
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}
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for (Map.Entry<Class<?>, UnivariateStatistic.NumberTransformer> entry : map.entrySet()) {
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if (! entry.getValue().equals(rhs.map.get(entry.getKey()))) {
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return false;
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}
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}
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return true;
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}
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return false;
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}
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/** {@inheritDoc} */
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@Override
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public int hashCode() {
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int hash = defaultTransformer.hashCode();
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for (UnivariateStatistic.NumberTransformer t : map.values()) {
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hash = hash * 31 + t.hashCode();
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}
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return hash;
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}
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}
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@ -17,12 +17,8 @@
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package org.apache.commons.math4.legacy.stat.descriptive;
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import org.apache.commons.math4.legacy.exception.MathIllegalArgumentException;
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import org.apache.commons.math4.legacy.exception.NullArgumentException;
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import org.apache.commons.math4.legacy.exception.util.LocalizedFormats;
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import org.apache.commons.math4.legacy.util.MathArrays;
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import java.io.Serializable;
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/**
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* Base interface implemented by all statistics.
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@ -57,80 +53,4 @@ public interface UnivariateStatistic extends MathArrays.Function {
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* @return a copy of the statistic
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*/
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UnivariateStatistic copy();
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/**
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* Subclasses implementing this interface can transform Objects to doubles.
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*
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* No longer extends Serializable since 2.0
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*
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*/
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interface NumberTransformer {
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/**
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* Implementing this interface provides a facility to transform
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* from Object to Double.
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*
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* @param o the Object to be transformed.
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* @return the double value of the Object.
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* @throws MathIllegalArgumentException if the Object can not be transformed into a Double.
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*/
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double transform(Object o) throws MathIllegalArgumentException;
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}
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/**
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* A Default NumberTransformer for java.lang.Numbers and Numeric Strings. This
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* provides some simple conversion capabilities to turn any java.lang.Number
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* into a primitive double or to turn a String representation of a Number into
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* a double.
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*/
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class DefaultTransformer implements NumberTransformer, Serializable {
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/** Serializable version identifier */
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private static final long serialVersionUID = 4019938025047800455L;
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/**
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* @param o the object that gets transformed.
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* @return a double primitive representation of the Object o.
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* @throws NullArgumentException if Object <code>o</code> is {@code null}.
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* @throws MathIllegalArgumentException if Object <code>o</code>
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* cannot successfully be transformed
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* @see <a href="http://commons.apache.org/collections/api-release/org/apache/commons/collections/Transformer.html">Commons Collections Transformer</a>
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*/
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@Override
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public double transform(Object o)
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throws NullArgumentException, MathIllegalArgumentException {
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if (o == null) {
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throw new NullArgumentException(LocalizedFormats.OBJECT_TRANSFORMATION);
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}
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if (o instanceof Number) {
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return ((Number)o).doubleValue();
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}
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try {
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return Double.parseDouble(o.toString());
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} catch (NumberFormatException e) {
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throw new MathIllegalArgumentException(LocalizedFormats.CANNOT_TRANSFORM_TO_DOUBLE,
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o.toString());
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}
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}
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/** {@inheritDoc} */
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@Override
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public boolean equals(Object other) {
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if (this == other) {
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return true;
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}
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return other instanceof DefaultTransformer;
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}
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/** {@inheritDoc} */
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@Override
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public int hashCode() {
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// some arbitrary number ...
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return 401993047;
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}
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}
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}
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@ -1,105 +0,0 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.commons.math4.legacy.stat.descriptive;
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import java.math.BigDecimal;
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import org.apache.commons.math4.legacy.TestUtils;
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import org.apache.commons.math4.legacy.exception.MathIllegalArgumentException;
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import org.apache.commons.math4.legacy.exception.NullArgumentException;
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import org.apache.commons.math4.legacy.stat.descriptive.UnivariateStatistic;
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import org.junit.Assert;
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import org.junit.Test;
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/**
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*/
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public class DefaultTransformerTest {
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/**
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*
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*/
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@Test
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public void testTransformDouble() throws Exception {
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double expected = 1.0;
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Double input = Double.valueOf(expected);
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UnivariateStatistic.DefaultTransformer t = new UnivariateStatistic.DefaultTransformer();
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Assert.assertEquals(expected, t.transform(input), 1.0e-4);
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}
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/**
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*
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*/
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@Test
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public void testTransformNull() throws Exception {
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UnivariateStatistic.DefaultTransformer t = new UnivariateStatistic.DefaultTransformer();
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try {
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t.transform(null);
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Assert.fail("Expecting NullArgumentException");
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} catch (NullArgumentException e) {
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// expected
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}
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}
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/**
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*
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*/
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@Test
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public void testTransformInteger() throws Exception {
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double expected = 1.0;
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Integer input = Integer.valueOf(1);
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UnivariateStatistic.DefaultTransformer t = new UnivariateStatistic.DefaultTransformer();
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Assert.assertEquals(expected, t.transform(input), 1.0e-4);
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}
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/**
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*
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*/
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@Test
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public void testTransformBigDecimal() throws Exception {
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double expected = 1.0;
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BigDecimal input = new BigDecimal("1.0");
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UnivariateStatistic.DefaultTransformer t = new UnivariateStatistic.DefaultTransformer();
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Assert.assertEquals(expected, t.transform(input), 1.0e-4);
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}
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/**
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*
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*/
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@Test
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public void testTransformString() throws Exception {
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double expected = 1.0;
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String input = "1.0";
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UnivariateStatistic.DefaultTransformer t = new UnivariateStatistic.DefaultTransformer();
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Assert.assertEquals(expected, t.transform(input), 1.0e-4);
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}
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/**
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*
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*/
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@Test(expected=MathIllegalArgumentException.class)
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public void testTransformObject(){
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Boolean input = Boolean.TRUE;
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UnivariateStatistic.DefaultTransformer t = new UnivariateStatistic.DefaultTransformer();
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t.transform(input);
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}
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@Test
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public void testSerial() {
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Assert.assertEquals(new UnivariateStatistic.DefaultTransformer(), TestUtils.serializeAndRecover(new UnivariateStatistic.DefaultTransformer()));
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}
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}
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@ -32,33 +32,21 @@ public class ListUnivariateImpl extends DescriptiveStatistics implements Seriali
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* Holds a reference to a list - GENERICs are going to make
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* our lives easier here as we could only accept List<Number>
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*/
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protected List<Object> list;
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/** Number Transformer maps Objects to Number for us. */
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protected UnivariateStatistic.NumberTransformer transformer;
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/**
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* No argument constructor
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*/
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public ListUnivariateImpl(){
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this(new ArrayList<>());
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}
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protected List<Double> list = new ArrayList<>();
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/**
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* Construct a ListUnivariate with a specific List.
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* @param list The list that will back this DescriptiveStatistics
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*/
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public ListUnivariateImpl(List<Object> list) {
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this(list, new UnivariateStatistic.DefaultTransformer());
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}
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/**
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* Construct a ListUnivariate with a specific List.
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* @param list The list that will back this DescriptiveStatistics
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* @param transformer the number transformer used to convert the list items.
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*/
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public ListUnivariateImpl(List<Object> list, UnivariateStatistic.NumberTransformer transformer) {
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public ListUnivariateImpl(List<Double> list) {
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this.list = list;
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this.transformer = transformer;
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}
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/**
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* Default constructor
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*/
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public ListUnivariateImpl() {
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}
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/** {@inheritDoc} */
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@ -98,7 +86,7 @@ public class ListUnivariateImpl extends DescriptiveStatistics implements Seriali
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try {
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value = transformer.transform(list.get(calcIndex));
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value = list.get(calcIndex);
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} catch (MathIllegalArgumentException e) {
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e.printStackTrace();
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}
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@ -128,15 +116,7 @@ public class ListUnivariateImpl extends DescriptiveStatistics implements Seriali
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/** {@inheritDoc} */
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@Override
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public void addValue(double v) {
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list.add(Double.valueOf(v));
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}
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/**
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* Adds an object to this list.
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* @param o Object to add to the list
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*/
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public void addObject(Object o) {
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list.add(o);
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list.add(v);
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}
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/**
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@ -165,22 +145,6 @@ public class ListUnivariateImpl extends DescriptiveStatistics implements Seriali
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return Double.NaN;
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}
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/**
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* Access the number transformer.
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* @return the number transformer.
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*/
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public UnivariateStatistic.NumberTransformer getTransformer() {
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return transformer;
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}
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/**
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* Modify the number transformer.
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* @param transformer the new number transformer.
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*/
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public void setTransformer(UnivariateStatistic.NumberTransformer transformer) {
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this.transformer = transformer;
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}
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/** {@inheritDoc} */
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@Override
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public void setWindowSize(int windowSize) {
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|
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@ -48,7 +48,7 @@ public final class ListUnivariateImplTest {
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/** test stats */
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@Test
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public void testStats() {
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List<Object> externalList = new ArrayList<>();
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List<Double> externalList = new ArrayList<>();
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DescriptiveStatistics u = new ListUnivariateImpl( externalList );
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@ -71,9 +71,9 @@ public final class ListUnivariateImplTest {
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@Test
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public void testN0andN1Conditions() {
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List<Object> list = new ArrayList<>();
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List<Double> list = new ArrayList<>();
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DescriptiveStatistics u = new ListUnivariateImpl( list );
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DescriptiveStatistics u = new ListUnivariateImpl(list);
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Assert.assertTrue("Mean of n = 0 set should be NaN", Double.isNaN( u.getMean() ) );
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Assert.assertTrue("Standard Deviation of n = 0 set should be NaN", Double.isNaN( u.getStandardDeviation() ) );
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@ -130,7 +130,7 @@ public final class ListUnivariateImplTest {
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@Test
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public void testSerialization() {
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DescriptiveStatistics u = new ListUnivariateImpl();
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DescriptiveStatistics u = new ListUnivariateImpl(new ArrayList<>());
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Assert.assertEquals("total count",0,u.getN(),tolerance);
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u.addValue(one);
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|
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@ -16,14 +16,13 @@
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*/
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||||
package org.apache.commons.math4.legacy.stat.descriptive;
|
||||
|
||||
import java.io.Serializable;
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
|
||||
import org.apache.commons.math4.legacy.util.FastMath;
|
||||
import org.junit.Assert;
|
||||
import org.junit.Test;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* Test cases for the {@link ListUnivariateImpl} class.
|
||||
*/
|
||||
|
|
@ -42,23 +41,18 @@ public final class MixedListUnivariateImplTest {
|
|||
private final double max = 3;
|
||||
private final double tolerance = 10E-15;
|
||||
|
||||
private TransformerMap transformers = new TransformerMap();
|
||||
|
||||
public MixedListUnivariateImplTest() {
|
||||
transformers = new TransformerMap();
|
||||
|
||||
transformers.putTransformer(Foo.class, new FooTransformer());
|
||||
|
||||
transformers.putTransformer(Bar.class, new BarTransformer());
|
||||
|
||||
}
|
||||
|
||||
/** test stats */
|
||||
@Test
|
||||
public void testStats() {
|
||||
List<Object> externalList = new ArrayList<>();
|
||||
List<Double> externalList = new ArrayList<>();
|
||||
|
||||
DescriptiveStatistics u = new ListUnivariateImpl(externalList,transformers);
|
||||
DescriptiveStatistics u = new ListUnivariateImpl(externalList);
|
||||
|
||||
Assert.assertEquals("total count", 0, u.getN(), tolerance);
|
||||
u.addValue(one);
|
||||
|
|
@ -79,7 +73,7 @@ public final class MixedListUnivariateImplTest {
|
|||
|
||||
@Test
|
||||
public void testN0andN1Conditions() {
|
||||
DescriptiveStatistics u = new ListUnivariateImpl(new ArrayList<>(),transformers);
|
||||
DescriptiveStatistics u = new ListUnivariateImpl(new ArrayList<>());
|
||||
|
||||
Assert.assertTrue(
|
||||
"Mean of n = 0 set should be NaN",
|
||||
|
|
@ -109,30 +103,30 @@ public final class MixedListUnivariateImplTest {
|
|||
@Test
|
||||
public void testSkewAndKurtosis() {
|
||||
ListUnivariateImpl u =
|
||||
new ListUnivariateImpl(new ArrayList<>(), transformers);
|
||||
new ListUnivariateImpl(new ArrayList<>());
|
||||
|
||||
u.addObject("12.5");
|
||||
u.addObject(Integer.valueOf(12));
|
||||
u.addObject("11.8");
|
||||
u.addObject("14.2");
|
||||
u.addObject(new Foo());
|
||||
u.addObject("14.5");
|
||||
u.addObject(Long.valueOf(21));
|
||||
u.addObject("8.2");
|
||||
u.addObject("10.3");
|
||||
u.addObject("11.3");
|
||||
u.addObject(Float.valueOf(14.1f));
|
||||
u.addObject("9.9");
|
||||
u.addObject("12.2");
|
||||
u.addObject(new Bar());
|
||||
u.addObject("12.1");
|
||||
u.addObject("11");
|
||||
u.addObject(Double.valueOf(19.8));
|
||||
u.addObject("11");
|
||||
u.addObject("10");
|
||||
u.addObject("8.8");
|
||||
u.addObject("9");
|
||||
u.addObject("12.3");
|
||||
u.addValue(12.5);
|
||||
u.addValue(12);
|
||||
u.addValue(11.8);
|
||||
u.addValue(14.2);
|
||||
u.addValue(14.5);
|
||||
u.addValue(14.9);
|
||||
u.addValue(12.0);
|
||||
u.addValue(21);
|
||||
u.addValue(8.2);
|
||||
u.addValue(10.3);
|
||||
u.addValue(11.3);
|
||||
u.addValue(14.1f);
|
||||
u.addValue(9.9);
|
||||
u.addValue(12.2);
|
||||
u.addValue(12.1);
|
||||
u.addValue(11);
|
||||
u.addValue(19.8);
|
||||
u.addValue(11);
|
||||
u.addValue(10);
|
||||
u.addValue(8.8);
|
||||
u.addValue(9);
|
||||
u.addValue(12.3);
|
||||
|
||||
|
||||
Assert.assertEquals("mean", 12.40455, u.getMean(), 0.0001);
|
||||
|
|
@ -143,7 +137,7 @@ public final class MixedListUnivariateImplTest {
|
|||
|
||||
@Test
|
||||
public void testProductAndGeometricMean() {
|
||||
ListUnivariateImpl u = new ListUnivariateImpl(new ArrayList<>(),transformers);
|
||||
ListUnivariateImpl u = new ListUnivariateImpl(new ArrayList<>());
|
||||
u.setWindowSize(10);
|
||||
|
||||
u.addValue(1.0);
|
||||
|
|
@ -170,33 +164,4 @@ public final class MixedListUnivariateImplTest {
|
|||
0.00001);
|
||||
|
||||
}
|
||||
|
||||
public static final class Foo {
|
||||
public String heresFoo() {
|
||||
return "14.9";
|
||||
}
|
||||
}
|
||||
|
||||
public static final class FooTransformer implements UnivariateStatistic.NumberTransformer, Serializable {
|
||||
private static final long serialVersionUID = -4252248129291326127L;
|
||||
@Override
|
||||
public double transform(Object o) {
|
||||
return Double.parseDouble(((Foo) o).heresFoo());
|
||||
}
|
||||
}
|
||||
|
||||
public static final class Bar {
|
||||
public String heresBar() {
|
||||
return "12.0";
|
||||
}
|
||||
}
|
||||
|
||||
public static final class BarTransformer implements UnivariateStatistic.NumberTransformer, Serializable {
|
||||
private static final long serialVersionUID = -1768345377764262043L;
|
||||
@Override
|
||||
public double transform(Object o) {
|
||||
return Double.parseDouble(((Bar) o).heresBar());
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
|
|
|||
|
|
@ -1,122 +0,0 @@
|
|||
/*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one or more
|
||||
* contributor license agreements. See the NOTICE file distributed with
|
||||
* this work for additional information regarding copyright ownership.
|
||||
* The ASF licenses this file to You under the Apache License, Version 2.0
|
||||
* (the "License"); you may not use this file except in compliance with
|
||||
* the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
package org.apache.commons.math4.legacy.stat.descriptive;
|
||||
|
||||
import org.apache.commons.math4.legacy.TestUtils;
|
||||
import org.junit.Assert;
|
||||
import org.junit.Test;
|
||||
|
||||
|
||||
/**
|
||||
*/
|
||||
public class TransformerMapTest {
|
||||
/**
|
||||
*
|
||||
*/
|
||||
@Test
|
||||
public void testPutTransformer(){
|
||||
UnivariateStatistic.NumberTransformer expected = new UnivariateStatistic.DefaultTransformer();
|
||||
|
||||
TransformerMap map = new TransformerMap();
|
||||
map.putTransformer(TransformerMapTest.class, expected);
|
||||
Assert.assertEquals(expected, map.getTransformer(TransformerMapTest.class));
|
||||
}
|
||||
|
||||
/**
|
||||
*
|
||||
*/
|
||||
@Test
|
||||
public void testContainsClass(){
|
||||
UnivariateStatistic.NumberTransformer expected = new UnivariateStatistic.DefaultTransformer();
|
||||
TransformerMap map = new TransformerMap();
|
||||
map.putTransformer(TransformerMapTest.class, expected);
|
||||
Assert.assertTrue(map.containsClass(TransformerMapTest.class));
|
||||
}
|
||||
|
||||
/**
|
||||
*
|
||||
*/
|
||||
@Test
|
||||
public void testContainsTransformer(){
|
||||
UnivariateStatistic.NumberTransformer expected = new UnivariateStatistic.DefaultTransformer();
|
||||
TransformerMap map = new TransformerMap();
|
||||
map.putTransformer(TransformerMapTest.class, expected);
|
||||
Assert.assertTrue(map.containsTransformer(expected));
|
||||
}
|
||||
|
||||
/**
|
||||
*
|
||||
*/
|
||||
@Test
|
||||
public void testRemoveTransformer(){
|
||||
UnivariateStatistic.NumberTransformer expected = new UnivariateStatistic.DefaultTransformer();
|
||||
|
||||
TransformerMap map = new TransformerMap();
|
||||
map.putTransformer(TransformerMapTest.class, expected);
|
||||
Assert.assertTrue(map.containsClass(TransformerMapTest.class));
|
||||
Assert.assertTrue(map.containsTransformer(expected));
|
||||
map.removeTransformer(TransformerMapTest.class);
|
||||
Assert.assertFalse(map.containsClass(TransformerMapTest.class));
|
||||
Assert.assertFalse(map.containsTransformer(expected));
|
||||
}
|
||||
|
||||
/**
|
||||
*
|
||||
*/
|
||||
@Test
|
||||
public void testClear(){
|
||||
UnivariateStatistic.NumberTransformer expected = new UnivariateStatistic.DefaultTransformer();
|
||||
|
||||
TransformerMap map = new TransformerMap();
|
||||
map.putTransformer(TransformerMapTest.class, expected);
|
||||
Assert.assertTrue(map.containsClass(TransformerMapTest.class));
|
||||
map.clear();
|
||||
Assert.assertFalse(map.containsClass(TransformerMapTest.class));
|
||||
}
|
||||
|
||||
/**
|
||||
*
|
||||
*/
|
||||
@Test
|
||||
public void testClasses(){
|
||||
UnivariateStatistic.NumberTransformer expected = new UnivariateStatistic.DefaultTransformer();
|
||||
TransformerMap map = new TransformerMap();
|
||||
map.putTransformer(TransformerMapTest.class, expected);
|
||||
Assert.assertTrue(map.classes().contains(TransformerMapTest.class));
|
||||
}
|
||||
|
||||
/**
|
||||
*
|
||||
*/
|
||||
@Test
|
||||
public void testTransformers(){
|
||||
UnivariateStatistic.NumberTransformer expected = new UnivariateStatistic.DefaultTransformer();
|
||||
TransformerMap map = new TransformerMap();
|
||||
map.putTransformer(TransformerMapTest.class, expected);
|
||||
Assert.assertTrue(map.transformers().contains(expected));
|
||||
}
|
||||
|
||||
@Test
|
||||
public void testSerial(){
|
||||
UnivariateStatistic.NumberTransformer expected = new UnivariateStatistic.DefaultTransformer();
|
||||
TransformerMap map = new TransformerMap();
|
||||
map.putTransformer(TransformerMapTest.class, expected);
|
||||
Assert.assertEquals(map, TestUtils.serializeAndRecover(map));
|
||||
}
|
||||
|
||||
}
|
||||
Loading…
Reference in New Issue