/*
 * Copyright (c) 2013 DataTorrent, Inc. ALL Rights Reserved.
 *
 * 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.datatorrent.lib.multiwindow;

import java.util.ArrayList;

import com.datatorrent.api.DefaultOutputPort;
import com.datatorrent.api.annotation.OperatorAnnotation;
import com.datatorrent.api.annotation.OutputPortFieldAnnotation;
import com.datatorrent.lib.util.KeyValPair;

/**
 * Calculates simple moving average (SMA) of last N window. <br>
 * <p>
 * <b>StateFull : Yes</b>, operator store values  for n-1 th windows. <br>
 * <b>Partitions : No</b>, sum is not unified on output ports. <br>
 * <br>
 * <b>Ports</b>:<br>
 * <b>data</b>: Expects KeyValPair where K is Object and V is Number.<br>
 * <b>doubleSMA</b>: Emits simple moving average of N window as Double.<br>
 * <b>floatSMA</b>: Emits simple moving average of N window as Float.<br>
 * <b>longSMA</b>: Emits simple moving average of N window as Long.<br>
 * <b>integerSMA</b>: Emits simple moving average of N window as Integer.<br>
 * <br>
 * <b>Properties</b>:<br>
 * <b>windowSize</b>: Number of windows to keep state on<br>
 * <br>
 * @displayName Simple Moving Average
 * @category Multi-Window
 * @tags key value, numeric, average
 * @since 0.3.3
 */
@OperatorAnnotation(partitionable = false)
public class SimpleMovingAverage<K, V extends Number> extends
		AbstractSlidingWindowKeyVal<K, V, SimpleMovingAverageObject>
{
	/**
	 * Output port to emit simple moving average (SMA) of last N window as Double.
	 */
	@OutputPortFieldAnnotation(name = "doubleSMA", optional = true)
	public final transient DefaultOutputPort<KeyValPair<K, Double>> doubleSMA = new DefaultOutputPort<KeyValPair<K, Double>>();
	/**
	 * Output port to emit simple moving average (SMA) of last N window as Float.
	 */
	@OutputPortFieldAnnotation(name = "floatSMA", optional = true)
	public final transient DefaultOutputPort<KeyValPair<K, Float>> floatSMA = new DefaultOutputPort<KeyValPair<K, Float>>();
	/**
	 * Output port to emit simple moving average (SMA) of last N window as Long.
	 */
	@OutputPortFieldAnnotation(name = "longSMA", optional = true)
	public final transient DefaultOutputPort<KeyValPair<K, Long>> longSMA = new DefaultOutputPort<KeyValPair<K, Long>>();
	/**
	 * Output port to emit simple moving average (SMA) of last N window as
	 * Integer.
	 */
	@OutputPortFieldAnnotation(name = "integerSMA", optional = true)
	public final transient DefaultOutputPort<KeyValPair<K, Integer>> integerSMA = new DefaultOutputPort<KeyValPair<K, Integer>>();

	/**
	 * Create the list if key doesn't exist. Add value to buffer and increment
	 * counter.
	 * 
	 * @param tuple
	 */
	@Override
	public void processDataTuple(KeyValPair<K, V> tuple)
	{
		K key = tuple.getKey();
		double val = tuple.getValue().doubleValue();
		ArrayList<SimpleMovingAverageObject> dataList = buffer.get(key);

		if (dataList == null) {
			dataList = new ArrayList<SimpleMovingAverageObject>(windowSize);
			for (int i = 0; i < windowSize; ++i) {
				dataList.add(new SimpleMovingAverageObject());
			}
		}

		dataList.get(currentstate).add(val); // add to previous value
		buffer.put(key, dataList);
	}

	/**
	 * Calculate average and emit in appropriate port.
	 * 
	 * @param key
	 * @param obj
	 */
	@Override
	public void emitTuple(K key, ArrayList<SimpleMovingAverageObject> obj)
	{
		double sum = 0;
		int count = 0;
		for (int i = 0; i < windowSize; i++) {
			SimpleMovingAverageObject d = obj.get(i);
			sum += d.getSum();
			count += d.getCount();
		}

		if (count == 0) { // Nothing to emit.
			return;
		}
		if (doubleSMA.isConnected()) {
			doubleSMA.emit(new KeyValPair<K, Double>(key, (sum / count)));
		}
		if (floatSMA.isConnected()) {
			floatSMA.emit(new KeyValPair<K, Float>(key, (float) (sum / count)));
		}
		if (longSMA.isConnected()) {
			longSMA.emit(new KeyValPair<K, Long>(key, (long) (sum / count)));
		}
		if (integerSMA.isConnected()) {
			integerSMA.emit(new KeyValPair<K, Integer>(key, (int) (sum / count)));
		}
	}
}