org.drugis.mtc.presentation.results.NetworkInconsistencyFactorsTableModel.java Source code

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Here is the source code for org.drugis.mtc.presentation.results.NetworkInconsistencyFactorsTableModel.java

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/*
 * This file is part of the GeMTC software for MTC model generation and
 * analysis. GeMTC is distributed from http://drugis.org/gemtc.
 * Copyright (C) 2009-2012 Gert van Valkenhoef.
 *
 * This program is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * This program is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with this program.  If not, see <http://www.gnu.org/licenses/>.
 */

package org.drugis.mtc.presentation.results;

import java.beans.PropertyChangeEvent;
import java.beans.PropertyChangeListener;
import java.util.List;
import java.util.Set;
import java.util.TreeSet;

import javax.swing.table.AbstractTableModel;

import org.apache.commons.lang.StringUtils;
import org.drugis.mtc.Parameter;
import org.drugis.mtc.model.Treatment;
import org.drugis.mtc.parameterization.InconsistencyParameter;
import org.drugis.mtc.presentation.InconsistencyWrapper;
import org.drugis.mtc.summary.QuantileSummary;
import org.drugis.mtc.summary.Summary;

import com.jgoodies.binding.value.ValueModel;

@SuppressWarnings("serial")
public class NetworkInconsistencyFactorsTableModel extends AbstractTableModel {
    private static final String NA = "N/A";
    private PropertyChangeListener d_listener;
    private final InconsistencyWrapper<?> d_model;
    private boolean d_listenersAttached;
    private ValueModel d_modelConstructed;
    private boolean d_preferDescription = false;

    public NetworkInconsistencyFactorsTableModel(InconsistencyWrapper<?> networkModel, ValueModel modelConstructed,
            boolean preferDescription) {
        this(networkModel, modelConstructed);
        d_preferDescription = preferDescription;
    }

    public NetworkInconsistencyFactorsTableModel(InconsistencyWrapper<?> networkModel,
            ValueModel modelConstructed) {
        d_model = networkModel;
        d_modelConstructed = modelConstructed;
        d_listener = new PropertyChangeListener() {
            public void propertyChange(PropertyChangeEvent evt) {
                fireTableDataChanged();
            }
        };

        if (d_modelConstructed.getValue().equals(true)) {
            attachListeners();
        }
        d_modelConstructed.addValueChangeListener(new PropertyChangeListener() {
            public void propertyChange(PropertyChangeEvent evt) {
                if (evt.getNewValue().equals(true)) {
                    fireTableStructureChanged();
                    attachListeners();
                }
            }
        });
    }

    private void attachListeners() {
        if (d_listenersAttached)
            return;

        List<Parameter> parameterList = d_model.getInconsistencyFactors();
        for (Parameter p : parameterList) {
            QuantileSummary summary = d_model.getQuantileSummary(p);
            summary.addPropertyChangeListener(d_listener);
        }
        d_listenersAttached = true;
    }

    @Override
    public Class<?> getColumnClass(int column) {
        return column == 0 ? String.class : Summary.class;

    }

    @Override
    public String getColumnName(int column) {
        return column == 0 ? "Cycle" : "Median (95% CrI)";
    }

    public int getColumnCount() {
        return 2;
    }

    public int getRowCount() {
        if (d_modelConstructed.getValue().equals(true)) {
            return d_model.getInconsistencyFactors().size();
        }
        return 0;
    }

    public Object getValueAt(int row, int col) {
        if (d_modelConstructed.getValue().equals(false)) {
            return NA;
        }
        InconsistencyParameter ip = (InconsistencyParameter) d_model.getInconsistencyFactors().get(row);
        if (col == 0) {
            Set<String> descriptions = new TreeSet<String>();
            for (Treatment t : ip.getCycle()) {
                descriptions.add(t.format(d_preferDescription));
            }
            return StringUtils.join(descriptions, ", ");
        } else {
            return d_model.getQuantileSummary(ip);
        }
    }
}