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/*
 *
 *  * Copyright 2015 Skymind,Inc.
 *  *
 *  *    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 org.deeplearning4j.util;

import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.factory.Nd4j;
import org.nd4j.linalg.indexing.INDArrayIndex;
import org.nd4j.linalg.indexing.NDArrayIndex;

/**
 * Basic time series utils
 * @author Adam Gibson
 */
public class TimeSeriesUtils {


    private TimeSeriesUtils() {
    }

    /**
     * Calculate a moving average given the length
     * @param toAvg the array to average
     * @param n the length of the moving window
     * @return the moving averages for each row
     */
    public static INDArray movingAverage(INDArray toAvg,int n) {
        INDArray ret = Nd4j.cumsum(toAvg);
        INDArrayIndex[] ends = new INDArrayIndex[]{NDArrayIndex.interval(n ,toAvg.columns())};
        INDArrayIndex[] begins = new INDArrayIndex[]{NDArrayIndex.interval(0,toAvg.columns() - n,false)};
        INDArrayIndex[] nMinusOne = new INDArrayIndex[]{NDArrayIndex.interval(n - 1,toAvg.columns())};
        ret.put(ends,ret.get(ends).sub(ret.get(begins)));
        return ret.get(nMinusOne).divi(n);
    }

    /**
     * Reshape time series mask arrays. This should match the assumptions (f order, etc) in RnnOutputLayer
     * @param timeSeriesMask    Mask array to reshape to a column vector
     * @return                  Mask array as a column vector
     */
    public static INDArray reshapeTimeSeriesMaskToVector(INDArray timeSeriesMask){
        if(timeSeriesMask.rank() != 2) throw new IllegalArgumentException("Cannot reshape mask: rank is not 2");

        if(timeSeriesMask.ordering() != 'f') timeSeriesMask = timeSeriesMask.dup('f');

        return timeSeriesMask.reshape('f',new int[]{timeSeriesMask.length(),1});
    }

}