128 lines
4.9 KiB
Java
Executable File
128 lines
4.9 KiB
Java
Executable File
package org.gcube.portlets.user.dataminerexecutor.server;
|
|
|
|
import java.util.ArrayList;
|
|
import java.util.List;
|
|
|
|
import org.gcube.data.analysis.dataminermanagercl.shared.process.Operator;
|
|
import org.gcube.data.analysis.dataminermanagercl.shared.process.OperatorCategory;
|
|
|
|
/**
|
|
*
|
|
* @author Giancarlo Panichi
|
|
*
|
|
*
|
|
*/
|
|
public class DescriptionRepository {
|
|
|
|
static List<OperatorCategory> categories;
|
|
static List<Operator> operators;
|
|
|
|
private static void initCategories() {
|
|
if (categories==null) {
|
|
categories = new ArrayList<OperatorCategory>();
|
|
categories.add(new OperatorCategory(
|
|
"DISTRIBUTIONS",
|
|
"Distributions description",
|
|
"This category includes probability distributions, classifications, matching or distance measurements etc.",
|
|
true));
|
|
categories.add(new OperatorCategory(
|
|
"MODELS",
|
|
"Models description",
|
|
"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.",
|
|
false));
|
|
categories.add(new OperatorCategory(
|
|
"EVALUATORS",
|
|
"A set of procedures for measuring the quality of a model",
|
|
"This category represent a set of procedures for measuring the quality of a model.",
|
|
false));
|
|
}
|
|
}
|
|
|
|
private static void initOperators() {
|
|
if (operators==null) {
|
|
operators = new ArrayList<Operator>();
|
|
operators.add(new Operator(
|
|
"AQUAMAPS_NATIVE_2050",
|
|
"Aquamaps Native for 2050 scenario",
|
|
"Aquamaps Native for 2050 scenario.", null, true));
|
|
operators.add(new Operator(
|
|
"REMOTE_AQUAMAPS_SUITABLE_2050",
|
|
"Aquamaps Suitable for 2050 scenario",
|
|
"Aquamaps Suitable for 2050 scenario.", null, true));
|
|
operators.add(new Operator(
|
|
"AQUAMAPS_SUITABLE_NEURALNETWORK",
|
|
"Aquamaps Suitable Distribution using a feed-Forward Neural Network",
|
|
"Aquamaps Suitable Distribution using a feed-Forward Neural Network.", null, true));
|
|
operators.add(new Operator(
|
|
"REMOTE_AQUAMAPS_NATIVE",
|
|
"Aquamaps Native habitat generated by invoking Rainy Cloud",
|
|
"Aquamaps Native habitat generated by invoking Rainy Cloud.", null, true));
|
|
operators.add(new Operator(
|
|
"AQUAMAPS_NEURAL_NETWORK_NS",
|
|
"Aquamaps Suitable Distribution using a Feed-Forward Neural Network provided by Neurosolutions",
|
|
"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));
|
|
operators.add(new Operator(
|
|
"REMOTE_AQUAMAPS_NATIVE_2050",
|
|
"Aquamaps Native 2050 habitat generated by invoking Rainy Cloud",
|
|
"Aquamaps Native 2050 habitat generated by invoking Rainy Cloud.", null, true));
|
|
operators.add(new Operator(
|
|
"REMOTE_AQUAMAPS_SUITABLE",
|
|
"Aquamaps Suitable habitat generated by invoking Rainy Cloud",
|
|
"Aquamaps Suitable habitat generated by invoking Rainy Cloud.", null, true));
|
|
operators.add(new Operator(
|
|
"AQUAMAPS_SUITABLE",
|
|
"Aquamaps Suitable habitat production",
|
|
"Aquamaps Suitable habitat production.", null, true));
|
|
operators.add(new Operator(
|
|
"AQUAMAPS_NATIVE_NEURALNETWORK",
|
|
"Aquamaps Native Distribution using a Feed-Forward Neural Network",
|
|
"Aquamaps Native Distribution using a Feed-Forward Neural Network.", null, true));
|
|
operators.add(new Operator(
|
|
"AQUAMAPS_NATIVE",
|
|
"Aquamaps Native habitat production",
|
|
"Aquamaps Native habitat production.", null, true));
|
|
operators.add(new Operator(
|
|
"AQUAMAPS_SUITABLE_2050",
|
|
"Aquamaps Suitable for 2050 scenario",
|
|
"Aquamaps Suitable for 2050 scenario.", null, true));
|
|
operators.add(new Operator(
|
|
"AQUAMAPSNN",
|
|
"Feed-Forward Neural Network for usage in Aquamaps generations",
|
|
"Feed-Forward Neural Network for usage in Aquamaps generations.", null, true));
|
|
operators.add(new Operator(
|
|
"AQUAMAPSNNNS",
|
|
"Feed-Forward Neural Network by Neurosolutions for usage in Aquamaps generations",
|
|
"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));
|
|
operators.add(new Operator(
|
|
"HSPEN",
|
|
"Hspen model by Aquamaps",
|
|
"Hspen model by Aquamaps.", null, true));
|
|
operators.add(new Operator(
|
|
"QUALITY_ANALYSIS",
|
|
"",
|
|
".", null));
|
|
operators.add(new Operator(
|
|
"DISCREPANCY_ANALYSIS",
|
|
"",
|
|
".", null));
|
|
}
|
|
}
|
|
|
|
public static OperatorCategory getOperatorCategory(OperatorCategory operatorCategory) {
|
|
initCategories();
|
|
for (OperatorCategory cat : categories)
|
|
if (operatorCategory.getId().contentEquals(cat.getId()))
|
|
return cat;
|
|
return null;
|
|
}
|
|
|
|
public static Operator getOperator(Operator operator) {
|
|
initOperators();
|
|
for (Operator op : operators)
|
|
if (operator.getId().contentEquals(op.getId()))
|
|
return op;
|
|
return null;
|
|
}
|
|
}
|
|
|