com.badlogic.gdx.math.WindowedMean.java Source code

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Here is the source code for com.badlogic.gdx.math.WindowedMean.java

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/*******************************************************************************
 * Copyright 2011 See AUTHORS file.
 * 
 * Licensed 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 com.badlogic.gdx.math;

/** A simple class keeping track of the mean of a stream of values within a certain window. the WindowedMean will only return a
 * value in case enough data has been sampled. After enough data has been sampled the oldest sample will be replaced by the newest
 * in case a new sample is added.
 * 
 * @author badlogicgames@gmail.com */
public final class WindowedMean {
    float values[];
    int added_values = 0;
    int last_value;
    float mean = 0;
    boolean dirty = true;

    /** constructor, window_size specifies the number of samples we will continuously get the mean and variance from. the class will
     * only return meaning full values if at least window_size values have been added.
     * 
     * @param window_size size of the sample window */
    public WindowedMean(int window_size) {
        values = new float[window_size];
    }

    /** @return whether the value returned will be meaningful */
    public boolean hasEnoughData() {
        return added_values >= values.length;
    }

    /** clears this WindowedMean. The class will only return meaningful values after enough data has been added again. */
    public void clear() {
        added_values = 0;
        last_value = 0;
        for (int i = 0; i < values.length; i++)
            values[i] = 0;
        dirty = true;
    }

    /** adds a new sample to this mean. In case the window is full the oldest value will be replaced by this new value.
     * 
     * @param value The value to add */
    public void addValue(float value) {
        if (added_values < values.length)
            added_values++;
        values[last_value++] = value;
        if (last_value > values.length - 1)
            last_value = 0;
        dirty = true;
    }

    /** returns the mean of the samples added to this instance. Only returns meaningful results when at least window_size samples
     * as specified in the constructor have been added.
     * @return the mean */
    public float getMean() {
        if (hasEnoughData()) {
            if (dirty == true) {
                float mean = 0;
                for (int i = 0; i < values.length; i++)
                    mean += values[i];

                this.mean = mean / values.length;
                dirty = false;
            }
            return this.mean;
        } else
            return 0;
    }

    /** @return the oldest value in the window */
    public float getOldest() {
        return last_value == values.length - 1 ? values[0] : values[last_value + 1];
    }

    /** @return the value last added */
    public float getLatest() {
        return values[last_value - 1 == -1 ? values.length - 1 : last_value - 1];
    }

    /** @return The standard deviation */
    public float standardDeviation() {
        if (!hasEnoughData())
            return 0;

        float mean = getMean();
        float sum = 0;
        for (int i = 0; i < values.length; i++) {
            sum += (values[i] - mean) * (values[i] - mean);
        }

        return (float) Math.sqrt(sum / values.length);
    }

    public int getWindowSize() {
        return values.length;
    }
}