/*
    Copyright 2005-2015 Intel Corporation.  All Rights Reserved.

    This file is part of Threading Building Blocks. Threading Building Blocks is free software;
    you can redistribute it and/or modify it under the terms of the GNU General Public License
    version 2  as  published  by  the  Free Software Foundation.  Threading Building Blocks 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 General Public License for more details.   You should have received a copy of
    the  GNU General Public License along with Threading Building Blocks; if not, write to the
    Free Software Foundation, Inc.,  51 Franklin St,  Fifth Floor,  Boston,  MA 02110-1301 USA

    As a special exception,  you may use this file  as part of a free software library without
    restriction.  Specifically,  if other files instantiate templates  or use macros or inline
    functions from this file, or you compile this file and link it with other files to produce
    an executable,  this file does not by itself cause the resulting executable to be covered
    by the GNU General Public License. This exception does not however invalidate any other
    reasons why the executable file might be covered by the GNU General Public License.
*/

/**
    The test checks that for different ranges of random numbers (from 0 to 
    [MinThread, MaxThread]) generated with different seeds the probability 
    of each number in the range deviates from the ideal random distribution
    by no more than AcceptableDeviation percent.
**/

#define HARNESS_DEFAULT_MIN_THREADS 2
#define HARNESS_DEFAULT_MAX_THREADS 32

#define HARNESS_DEFINE_PRIVATE_PUBLIC 1
#include "harness_inject_scheduler.h"

#define TEST_TOTAL_SEQUENCE 0

#include "harness.h"
#include "tbb/atomic.h"

//! Coefficient defining tolerable deviation from ideal random distribution
const double AcceptableDeviation = 2.1;
//! Tolerable probability of failure to achieve tolerable distribution
const double AcceptableProbabilityOfOutliers = 1e-5;
//! Coefficient defining the length of random numbers series used to estimate the distribution
/** Number of random values generated per each range element. I.e. the larger is 
    the range, the longer is the series of random values. **/
const uintptr_t SeriesBaseLen = 100;
//! Number of random numbers series to generate
const uintptr_t NumSeries = 100;
//! Number of random number generation series with different seeds
const uintptr_t NumSeeds = 100;

tbb::atomic<uintptr_t> NumHighOutliers;
tbb::atomic<uintptr_t> NumLowOutliers;

inline void CheckProbability ( double probability, double expectedProbability, int index, int numIndices, void* seed ) {
    double lowerBound = expectedProbability / AcceptableDeviation,
           upperBound = expectedProbability * AcceptableDeviation;
    if ( probability < lowerBound ) {
        if ( !NumLowOutliers )
            REMARK( "Warning: Probability %.3f of hitting index %d among %d elements is out of acceptable range (%.3f - %.3f) for seed %p\n",
                    probability, index, numIndices, lowerBound, upperBound, seed );
        ++NumLowOutliers;
    }
    else if ( probability > upperBound ) {
        if ( !NumHighOutliers )
            REMARK( "Warning: Probability %.3f of hitting index %d among %d elements is out of acceptable range (%.3f - %.3f) for seed %p\n",
                    probability, index, numIndices, lowerBound, upperBound, seed );
        ++NumHighOutliers;
    }
}

struct CheckDistributionBody {
    void operator() ( int id ) const {
        uintptr_t randomRange = id + MinThread;
        uintptr_t *curHits = new uintptr_t[randomRange]
#if TEST_TOTAL_SEQUENCE
                , *totalHits = new uintptr_t[randomRange]
#endif
        ;
        double expectedProbability = 1./randomRange;
        // Loop through different seeds
        for ( uintptr_t i = 0; i < NumSeeds; ++i ) {
            // Seed value mimics the one used by the TBB task scheduler
            void* seed = (char*)&curHits + i * 16;
            tbb::internal::FastRandom random( seed );
            // According to Section 3.2.1.2 of Volume 2 of Knuth's Art of Computer Programming
            // the following conditions must be hold for m=2^32:
            ASSERT((random.c&1)!=0, "c is relatively prime to m");
            ASSERT((random.a-1)%4==0, "a-1 is a multiple of p, for every prime p dividing m."
                   " And a-1 is a multiple of 4, if m is a multiple of 4");

            memset( curHits, 0, randomRange * sizeof(uintptr_t) );
#if TEST_TOTAL_SEQUENCE
            memset( totalHits, 0, randomRange * sizeof(uintptr_t) );
#endif
            const uintptr_t seriesLen = randomRange * SeriesBaseLen,
                            experimentLen = NumSeries * seriesLen;
            uintptr_t *curSeries = new uintptr_t[seriesLen],  // circular buffer
                       randsGenerated = 0;
            // Initialize statistics
            while ( randsGenerated < seriesLen ) {
                uintptr_t idx = random.get() % randomRange;
                ++curHits[idx];
#if TEST_TOTAL_SEQUENCE
                ++totalHits[idx];
#endif
                curSeries[randsGenerated++] = idx;
            }
            while ( randsGenerated < experimentLen ) {
                for ( uintptr_t j = 0; j < randomRange; ++j ) {
                    CheckProbability( double(curHits[j])/seriesLen, expectedProbability, j, randomRange, seed );
#if TEST_TOTAL_SEQUENCE
                    CheckProbability( double(totalHits[j])/randsGenerated, expectedProbability, j, randomRange, seed );
#endif
                }
                --curHits[curSeries[randsGenerated % seriesLen]];
                int idx = random.get() % randomRange;
                ++curHits[idx];
#if TEST_TOTAL_SEQUENCE
                ++totalHits[idx];
#endif
                curSeries[randsGenerated++ % seriesLen] = idx;
            }
            delete [] curSeries;
        }
        delete [] curHits;
#if TEST_TOTAL_SEQUENCE
        delete [] totalHits;
#endif
    }
};

struct rng {
    tbb::internal::FastRandom my_fast_random;
    rng (unsigned seed):my_fast_random(seed) {}
    unsigned short operator()(){return my_fast_random.get();}
};

template <std::size_t seriesLen >
struct SingleCheck{
    bool operator()(unsigned seed)const{
        std::size_t series1[seriesLen]={0};
        std::size_t series2[seriesLen]={0};
        std::generate(series1,series1+seriesLen,rng(seed));
        std::generate(series2,series2+seriesLen,rng(seed));
        return std::equal(series1,series1+seriesLen,series2);
    }
};

template <std::size_t seriesLen ,size_t seedsNum>
struct CheckReproducibilityBody:NoAssign{
    unsigned short seeds[seedsNum];
    const std::size_t grainSize;
    CheckReproducibilityBody(std::size_t GrainSize): grainSize(GrainSize){
       //first generate seeds to check on, and make sure that sequence is reproducible
       ASSERT(SingleCheck<seedsNum>()(0),"Series generated by FastRandom must be reproducible");
       std::generate(seeds,seeds+seedsNum,rng(0));
    }

    void operator()(int id)const{
       for (size_t i=id*grainSize; (i<seedsNum)&&(i< ((id+1)*grainSize));++i ){
           ASSERT(SingleCheck<seriesLen>()(i),"Series generated by FastRandom must be reproducible");
       }
    }

};
#include "tbb/tbb_thread.h"

int TestMain () {
    ASSERT( AcceptableDeviation < 100, NULL );
    MinThread = max(MinThread, 2);
    MaxThread = max(MinThread, MaxThread);
    double NumChecks = double(NumSeeds) * (MaxThread - MinThread + 1) * (MaxThread + MinThread) / 2.0 * (SeriesBaseLen * NumSeries - SeriesBaseLen);
    REMARK( "Number of distribution quality checks %g\n", NumChecks );
    NumLowOutliers = NumHighOutliers = 0;
    // Parallelism is used in this test only to speed up the long serial checks
    // Essentially it is a loop over random number ranges
    // Ideally tbb::parallel_for could be used to parallelize the outermost loop 
    // in CheckDistributionBody, but it is not used to avoid unit test contamination.
    int P = tbb::tbb_thread::hardware_concurrency();
    enum {reproducibilitySeedsToTest=1000};
    enum {reproducibilitySeriesLen=100};
    CheckReproducibilityBody<reproducibilitySeriesLen,reproducibilitySeedsToTest>  CheckReproducibility(reproducibilitySeedsToTest/MaxThread);
    while ( MinThread <= MaxThread ) {
        int ThreadsToRun = min(P, MaxThread - MinThread + 1);
        REMARK("Checking random range [%d;%d)\n", MinThread, MinThread+ThreadsToRun);
        NativeParallelFor( ThreadsToRun, CheckDistributionBody() );
        NativeParallelFor( ThreadsToRun, CheckReproducibility );
        MinThread += P;
    }
    double observedProbabilityOfOutliers = (NumLowOutliers + NumHighOutliers) / NumChecks;
    if ( observedProbabilityOfOutliers > AcceptableProbabilityOfOutliers ) {
        if ( NumLowOutliers )
            REPORT( "Warning: %d cases of too low probability of a given number detected\n", (int)NumLowOutliers );
        if ( NumHighOutliers )
            REPORT( "Warning: %d cases of too high probability of a given number detected\n", (int)NumHighOutliers );
        ASSERT( observedProbabilityOfOutliers <= AcceptableProbabilityOfOutliers, NULL );
    }
    return Harness::Done;
}
