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The main module contains the GeoTools public interfaces that are used by other GeoTools modules (and GeoTools applications). Where possible we make use industry standard terms as provided by OGC and ISO standards. The formal GeoTools public api consists of gt-metadata, jts and the gt-main module. The main module contains the default implementations that are available provided to other GeoTools modules using our factory system. Factories are obtained from an appropriate FactoryFinder, giving applications a chance configure the factory used using the Factory Hints facilities. FilterFactory ff = CommonFactoryFinder.getFilterFactory(); Expression expr = ff.add( expression1, expression2 ); If you find yourself using implementation specific classes chances are you doing it wrong: Expression expr = new AddImpl( expression1, expressiom2 );

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/*
 *    GeoTools - The Open Source Java GIS Toolkit
 *    http://geotools.org
 *
 *    (C) 2005-2008, Open Source Geospatial Foundation (OSGeo)
 *
 *    This library is free software; you can redistribute it and/or
 *    modify it under the terms of the GNU Lesser General Public
 *    License as published by the Free Software Foundation;
 *    version 2.1 of the License.
 *
 *    This library 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
 *    Lesser General Public License for more details.
 */
package org.geotools.feature.visitor;

import java.util.Arrays;
import java.util.Collections;
import java.util.List;
import java.util.Optional;
import org.geotools.data.simple.SimpleFeatureCollection;
import org.opengis.feature.simple.SimpleFeature;
import org.opengis.filter.expression.Expression;

/**
 * Determines the standard deviation.
 *
 *  *            ----------------------------
 *            |  1   ---
 * Std dev =  | ___  \   ( x - mean ) ^ 2
 *           \|  N   /__
 * 
 *
 * aka std dev = sqrt((sum((x-mean)^2))/N) where N is the number of samples.
 *
 * It uses the rolling variance algorithm described here:
 * http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#On-line_algorithm
 *
 * @author Cory Horner, Refractions Research Inc.
 * @author Andrea Aime, GeoSolutions
 */
public class StandardDeviationVisitor implements FeatureCalc, FeatureAttributeVisitor {
    public static class Result extends AbstractCalcResult {
        final Double deviation;

        public Result() {
            this.deviation = null;
        }

        public Result(double deviation) {
            this.deviation = deviation;
        }

        public Object getValue() {
            return deviation;
        }
    }

    private Expression expr;

    boolean visited = false;
    int countNull = 0;
    int countNaN = 0;
    int count = 0;
    double mean = 0;
    double m2 = 0;

    /** Constructs a standard deviation visitor based on the specified expression */
    public StandardDeviationVisitor(Expression expr) {
        this.expr = expr;
    }

    public void init(SimpleFeatureCollection collection) {
        // do nothing
    }

    @Override
    public List getExpressions() {
        return Arrays.asList(expr);
    }

    @Override
    public Optional> getResultType(List inputTypes) {
        if (inputTypes == null || inputTypes.size() != 1)
            throw new IllegalArgumentException(
                    "Expecting a single type in input, not " + inputTypes);

        return Optional.of(Collections.singletonList(Double.class));
    }

    public CalcResult getResult() {
        if (count == 0) {
            return CalcResult.NULL_RESULT;
        }
        return new Result(Math.sqrt(m2 / count));
    }

    public void visit(SimpleFeature feature) {
        visit((org.opengis.feature.Feature) feature);
    }

    public void visit(org.opengis.feature.Feature feature) {
        Object value = expr.evaluate(feature);

        if (value == null) {
            countNull++; // increment the null count
            return; // don't store this value
        }

        if (value instanceof Double) {
            double doubleVal = ((Double) value).doubleValue();
            if (Double.isNaN(doubleVal) || Double.isInfinite(doubleVal)) {
                countNaN++; // increment the NaN count
                return; // don't store NaN value
            }
        }

        double x = ((Number) value).doubleValue();
        count++;
        double delta = x - mean;
        mean = mean + delta / count;
        m2 = m2 + delta * (x - mean); // This expression uses the new value of mean
    }

    public void reset() {
        this.count = 0;
        this.countNull = 0;
        this.countNaN = 0;
        this.m2 = 0;
        this.mean = 0;
    }

    /** mean value generated when calcualting standard deviation */
    public double getMean() {
        return mean;
    }
    /** @return the number of features which returned a NaN */
    public int getNaNCount() {
        return countNaN;
    }

    /** @return the number of features which returned a null */
    public int getNullCount() {
        return countNull;
    }
}