122 lines
4.8 KiB
Java
122 lines
4.8 KiB
Java
package org.gcube.portlets.user.dataminermanager.server;
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import java.util.ArrayList;
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import java.util.List;
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import org.gcube.portlets.user.dataminermanager.client.bean.Operator;
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import org.gcube.portlets.user.dataminermanager.client.bean.OperatorCategory;
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public class DescriptionRepository {
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static List<OperatorCategory> categories;
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static List<Operator> operators;
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private static void initCategories() {
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if (categories==null) {
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categories = new ArrayList<OperatorCategory>();
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categories.add(new OperatorCategory(
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"DISTRIBUTIONS",
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"Distributions description",
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"This category includes probability distributions, classifications, matching or distance measurements etc.",
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true));
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categories.add(new OperatorCategory(
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"MODELS",
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"Models description",
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"This category includes models to be trained, e.g. neural networks, species envelopes, support vector machines etc.. The result will be typically a binary file.",
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false));
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categories.add(new OperatorCategory(
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"EVALUATORS",
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"A set of procedures for measuring the quality of a model",
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"This category represent a set of procedures for measuring the quality of a model.",
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false));
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}
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}
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private static void initOperators() {
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if (operators==null) {
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operators = new ArrayList<Operator>();
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operators.add(new Operator(
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"AQUAMAPS_NATIVE_2050",
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"Aquamaps Native for 2050 scenario",
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"Aquamaps Native for 2050 scenario.", null, true));
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operators.add(new Operator(
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"REMOTE_AQUAMAPS_SUITABLE_2050",
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"Aquamaps Suitable for 2050 scenario",
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"Aquamaps Suitable for 2050 scenario.", null, true));
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operators.add(new Operator(
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"AQUAMAPS_SUITABLE_NEURALNETWORK",
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"Aquamaps Suitable Distribution using a feed-Forward Neural Network",
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"Aquamaps Suitable Distribution using a feed-Forward Neural Network.", null, true));
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operators.add(new Operator(
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"REMOTE_AQUAMAPS_NATIVE",
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"Aquamaps Native habitat generated by invoking Rainy Cloud",
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"Aquamaps Native habitat generated by invoking Rainy Cloud.", null, true));
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operators.add(new Operator(
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"AQUAMAPS_NEURAL_NETWORK_NS",
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"Aquamaps Suitable Distribution using a Feed-Forward Neural Network provided by Neurosolutions",
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"Aquamaps Suitable Distribution using a Feed-Forward Neural Network provided by Neurosolutions (<a href='http://www.neurosolutions.com/' target='blank'>http://www.neurosolutions.com</a>).", null, true));
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operators.add(new Operator(
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"REMOTE_AQUAMAPS_NATIVE_2050",
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"Aquamaps Native 2050 habitat generated by invoking Rainy Cloud",
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"Aquamaps Native 2050 habitat generated by invoking Rainy Cloud.", null, true));
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operators.add(new Operator(
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"REMOTE_AQUAMAPS_SUITABLE",
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"Aquamaps Suitable habitat generated by invoking Rainy Cloud",
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"Aquamaps Suitable habitat generated by invoking Rainy Cloud.", null, true));
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operators.add(new Operator(
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"AQUAMAPS_SUITABLE",
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"Aquamaps Suitable habitat production",
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"Aquamaps Suitable habitat production.", null, true));
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operators.add(new Operator(
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"AQUAMAPS_NATIVE_NEURALNETWORK",
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"Aquamaps Native Distribution using a Feed-Forward Neural Network",
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"Aquamaps Native Distribution using a Feed-Forward Neural Network.", null, true));
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operators.add(new Operator(
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"AQUAMAPS_NATIVE",
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"Aquamaps Native habitat production",
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"Aquamaps Native habitat production.", null, true));
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operators.add(new Operator(
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"AQUAMAPS_SUITABLE_2050",
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"Aquamaps Suitable for 2050 scenario",
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"Aquamaps Suitable for 2050 scenario.", null, true));
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operators.add(new Operator(
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"AQUAMAPSNN",
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"Feed-Forward Neural Network for usage in Aquamaps generations",
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"Feed-Forward Neural Network for usage in Aquamaps generations.", null, true));
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operators.add(new Operator(
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"AQUAMAPSNNNS",
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"Feed-Forward Neural Network by Neurosolutions for usage in Aquamaps generations",
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"Feed-Forward Neural Network by Neurosolutions (<a href='http://www.neurosolutions.com/' target='blank'>http://www.neurosolutions.com</a>) for usage in Aquamaps generations.", null, true));
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operators.add(new Operator(
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"HSPEN",
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"Hspen model by Aquamaps",
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"Hspen model by Aquamaps.", null, true));
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operators.add(new Operator(
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"QUALITY_ANALYSIS",
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"",
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".", null));
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operators.add(new Operator(
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"DISCREPANCY_ANALYSIS",
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"",
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".", null));
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}
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}
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public static OperatorCategory getOperatorCategory(OperatorCategory operatorCategory) {
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initCategories();
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for (OperatorCategory cat : categories)
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if (operatorCategory.getId().contentEquals(cat.getId()))
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return cat;
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return null;
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}
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public static Operator getOperator(Operator operator) {
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initOperators();
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for (Operator op : operators)
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if (operator.getId().contentEquals(op.getId()))
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return op;
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return null;
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}
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}
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