/*
  ==============================================================================

   This file is part of the JUCE library.
   Copyright (c) 2017 - ROLI Ltd.

   JUCE is an open source library subject to commercial or open-source
   licensing.

   The code included in this file is provided under the terms of the ISC license
   http://www.isc.org/downloads/software-support-policy/isc-license. Permission
   To use, copy, modify, and/or distribute this software for any purpose with or
   without fee is hereby granted provided that the above copyright notice and
   this permission notice appear in all copies.

   JUCE IS PROVIDED "AS IS" WITHOUT ANY WARRANTY, AND ALL WARRANTIES, WHETHER
   EXPRESSED OR IMPLIED, INCLUDING MERCHANTABILITY AND FITNESS FOR PURPOSE, ARE
   DISCLAIMED.

  ==============================================================================
*/

#pragma once


//==============================================================================
/**
    A class that measures various statistics about a series of floating point
    values that it is given.
*/
template <typename FloatType>
class StatisticsAccumulator
{
public:
    //==============================================================================
    /** Constructs a new StatisticsAccumulator. */
    StatisticsAccumulator() noexcept
        : count (0),
          minimum ( std::numeric_limits<FloatType>::infinity()),
          maximum (-std::numeric_limits<FloatType>::infinity())
    {}

    //==============================================================================
    /** Add a new value to the accumulator.
        This will update all running statistics accordingly.
    */
    void addValue (FloatType v) noexcept
    {
        jassert (juce_isfinite (v));

        sum += v;
        sumSquares += v * v;
        ++count;

        if (v > maximum) maximum = v;
        if (v < minimum) minimum = v;
    }

    /** Reset the accumulator.
        This will reset all currently saved statistcs.
    */
    void reset() noexcept               { *this = StatisticsAccumulator<FloatType>(); }

    //==============================================================================
    /** Returns the average (arithmetic mean) of all previously added values.
        If no values have been added yet, this will return zero.
    */
    FloatType getAverage() const noexcept
    {
        return count > 0 ? sum / (FloatType) count
                         : FloatType();
    }

    /** Returns the variance of all previously added values.
        If no values have been added yet, this will return zero.
    */
    FloatType getVariance() const noexcept
    {
        return count > 0 ? (sumSquares - sum * sum / (FloatType) count) / (FloatType) count
                         : FloatType();
    }

    /** Returns the standard deviation of all previously added values.
        If no values have been added yet, this will return zero.
    */
    FloatType getStandardDeviation() const noexcept
    {
        return std::sqrt (getVariance());
    }

    /** Returns the smallest of all previously added values.
        If no values have been added yet, this will return positive infinity.
    */
    FloatType getMinValue() const noexcept
    {
        return minimum;
    }

    /** Returns the largest of all previously added values.
        If no values have been added yet, this will return negative infinity.
    */
    FloatType getMaxValue() const noexcept
    {
        return maximum;
    }

    /** Returns how many values have been added to this accumulator. */
    size_t getCount() const noexcept
    {
        return count;
    }

private:
    //==============================================================================
    struct KahanSum
    {
        KahanSum() noexcept : sum(), error() {}
        operator FloatType() const noexcept             { return sum; }

        void JUCE_NO_ASSOCIATIVE_MATH_OPTIMISATIONS operator+= (FloatType value) noexcept
        {
            FloatType correctedValue = value - error;
            FloatType newSum = sum + correctedValue;
            error = (newSum - sum) - correctedValue;
            sum = newSum;
        }

        FloatType sum, error;
    };

    //==============================================================================
    size_t count;
    KahanSum sum, sumSquares;
    FloatType minimum, maximum;
};
