// -*- C++ -*-
/***************************************************************************
 * blitz/array/reduce.h   Reductions of an array (or array expression) in a 
 *                        single rank: sum, mean, min, minIndex, max, maxIndex,
 *                        product, count, any, all
 *
 * $Id$
 *
 * Copyright (C) 1997-2011 Todd Veldhuizen <tveldhui@acm.org>
 *
 * This file is a part of Blitz.
 *
 * Blitz is free software: you can redistribute it and/or modify 
 * it under the terms of the GNU Lesser General Public License
 * as published by the Free Software Foundation, either version 3
 * of the License, or (at your option) any later version.
 *
 * Blitz 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 Lesser General Public License for more details.
 *
 * You should have received a copy of the GNU Lesser General Public 
 * License along with Blitz.  If not, see <http://www.gnu.org/licenses/>.
 * 
 * Suggestions:          blitz-devel@lists.sourceforge.net
 * Bugs:                 blitz-support@lists.sourceforge.net    
 *
 * For more information, please see the Blitz++ Home Page:
 *    https://sourceforge.net/projects/blitz/
 *
 ****************************************************************************/
#ifndef BZ_ARRAYREDUCE_H
#define BZ_ARRAYREDUCE_H

#include <blitz/reduce.h>
#include <blitz/meta/vecassign.h>

namespace blitz {

template<bool needIndex,bool needInit> struct _bz_ReduceReset;

template<>
struct _bz_ReduceReset<true,true> {
    template<typename T_reduction,typename T_index,typename T_expr>
    void operator()(T_reduction& reduce,const T_index& index,const T_expr& expr) {
        reduce.reset(index,expr.first_value());
    }
};

template<>
struct _bz_ReduceReset<false,true> {
    template<typename T_reduction,typename T_index,typename T_expr>
    void operator()(T_reduction& reduce,const T_index&,const T_expr& expr) {
        reduce.reset(expr.first_value());
    }
};

template<>
struct _bz_ReduceReset<true,false> {
    template<typename T_reduction,typename T_index,typename T_expr>
    void operator()(T_reduction& reduce,const T_index& index,const T_expr&) {
        reduce.reset(index);
    }
};

template<>
struct _bz_ReduceReset<false,false> {
    template<typename T_reduction,typename T_index,typename T_expr>
    void operator()(T_reduction& reduce,const T_index&,const T_expr&) {
        reduce.reset();
    }
};


/** Expression template class for reductions. \todo We should be able
    to do vectorization, at least for complete reduction. */
template<typename T_expr, int N_index, typename T_reduction>
class _bz_ArrayExprReduce {

public:   
    typedef _bz_typename T_reduction::T_numtype T_numtype;

  // select return type
  typedef typename unwrapET<typename T_expr::T_result>::T_unwrapped test;
  typedef typename selectET<typename T_expr::T_typeprop,
			    T_numtype,
			    _bz_ArrayExprReduce<test, N_index, T_reduction> >::T_selected T_typeprop;
  typedef typename unwrapET<T_typeprop>::T_unwrapped T_result;
  typedef T_numtype T_optype;

    typedef T_expr      T_ctorArg1;
    typedef T_reduction T_ctorArg2;
  typedef int  T_range_result; // dummy

    static const int 
        numArrayOperands = T_expr::numArrayOperands,
        numTVOperands = T_expr::numTVOperands,
        numTMOperands = T_expr::numTMOperands,
        numIndexPlaceholders = T_expr::numIndexPlaceholders + 1,
      minWidth = simdTypes<T_numtype>::vecWidth,
      maxWidth = simdTypes<T_numtype>::vecWidth,
        rank_ = T_expr::rank_ - 1;

  /** Vectorization doesn't work for index expressions, so we can use
      a dummy here. */
  template<int N> struct tvresult {
    typedef FastTV2Iterator<T_numtype, N> Type;
  };

    _bz_ArrayExprReduce(const _bz_ArrayExprReduce& reduce)
        : reduce_(reduce.reduce_), iter_(reduce.iter_), ordering_(reduce.ordering_) { }

    _bz_ArrayExprReduce(T_expr expr)
        : iter_(expr)
    { computeOrdering(); }

#if 0
    _bz_ArrayExprReduce(T_expr expr, T_reduction reduce)
        : iter_(expr), reduce_(reduce)
    { computeOrdering(); }
#endif

    int ascending(const int r) const { return iter_.ascending(r); }
    int ordering(const int r)  const { return ordering_[r];       }
    int lbound(const int r)    const { return iter_.lbound(r);    }
    int ubound(const int r)    const { return iter_.ubound(r);    }
    RectDomain<rank_> domain() const { return iter_.domain(); }

    template<int N_destRank>
    T_numtype operator()(const TinyVector<int, N_destRank>& destIndex) const
    {
        BZPRECHECK(N_destRank == N_index,  
            "Array reduction performed over rank " << N_index 
            << " to produce a rank " << N_destRank << " expression." << endl
            << "You must reduce over rank " << N_destRank << " instead.");

        TinyVector<int, N_destRank + 1> index;

        // This metaprogram copies elements 0..N-1 of destIndex into index
        _bz_meta_vecAssign<N_index, 0>::assign(index, destIndex, 
            _bz_update<int,int>());

        int lbound = iter_.lbound(N_index);
        int ubound = iter_.ubound(N_index);

        BZPRECHECK((lbound != tiny(int())) && (ubound != huge(int())),
           "Array reduction performed over rank " << N_index
           << " is unbounded." << endl 
           << "There must be an array object in the expression being reduced"
           << endl << "which provides a bound in rank " << N_index << ".");

        // If we are doing minIndex/maxIndex, initialize with lower bound

        _bz_ReduceReset<T_reduction::needIndex,T_reduction::needInit> reset;
        reset(reduce_,lbound,iter_);

        for (index[N_index]=lbound; index[N_index]<=ubound; ++index[N_index]) {
            if (!reduce_(iter_(index), index[N_index]))
                break;
        }

        return reduce_.result(ubound-lbound+1);
    }

    // If you have a precondition failure on these routines, it means
    // you are trying to use stack iteration mode on an expression
    // which contains an index placeholder.  You must use index
    // iteration mode instead.

    int operator*()        const {
      BZPRECHECK(0,"Can't use stack iteration on a reduction."); return 0; }
    int suggestStride(int) const { 
      BZPRECHECK(0,"Can't use stack iteration on a reduction."); return 0; }

    void push(int)           const { 
      BZPRECHECK(0,"Can't use stack iteration on a reduction."); }
    void pop(int)            const { 
      BZPRECHECK(0,"Can't use stack iteration on a reduction."); }
    void advance()           const { 
      BZPRECHECK(0,"Can't use stack iteration on a reduction."); }
    void advance(int)        const { 
      BZPRECHECK(0,"Can't use stack iteration on a reduction."); }
    void loadStride(int)     const { 
      BZPRECHECK(0,"Can't use stack iteration on a reduction."); }
    void advanceUnitStride() const { 
      BZPRECHECK(0,"Can't use stack iteration on a reduction."); }

    template<int N_rank>
    void moveTo(const TinyVector<int,N_rank>&) const { 
      BZPRECHECK(0,"Stencils of reductions are not implemented"); }

    bool isUnitStride(int)    const { 
      BZPRECHECK(0,"Can't use stack iteration on a reduction."); return false; }
    bool isUnitStride()       const { 
      BZPRECHECK(0,"Can't use stack iteration on a reduction."); return false; }
    bool canCollapse(int,int) const { 
      BZPRECHECK(0,"Can't use stack iteration on a reduction."); return false; }
    bool isStride(int,int)    const { 
      BZPRECHECK(0,"Can't use stack iteration on a reduction."); return true;  }

    T_numtype operator[](int) const { 
      BZPRECHECK(0,"Can't use stack iteration on a reduction."); return T_numtype(); }
    T_numtype fastRead(int)   const { 
      BZPRECHECK(0,"Can't use stack iteration on a reduction."); return T_numtype(); }

  template<int N>
  typename tvresult<N>::Type fastRead_tv(int) const {
    BZPRECHECK(0,"Can't use stack iteration on an index mapping.");
    return TinyVector<T_numtype, N>();
    }

    /** Determining whether the resulting expression is aligned is
	difficult, so to be safe we say no. It shouldn't be attempted
	anyway, though. */
    bool isVectorAligned(diffType offset) const {
      return false; }

    // don't know how to define these, so stencil expressions won't work
    T_result shift(int offset, int dim) const
  { BZPRECHECK(0,"Stencils of reductions are not implemented"); return T_numtype(); }
    T_result shift(int offset1, int dim1,int offset2, int dim2) const 
  { BZPRECHECK(0,"Stencils of reductions are not implemented"); return T_numtype(); }
    void _bz_offsetData(sizeType i) { BZPRECONDITION(0); }

  // Unclear how to define this, and stencils don't work anyway
  T_range_result operator()(RectDomain<rank_> d) const
  { BZPRECHECK(0,"Stencils of reductions are not implemented");
    return T_range_result();  }

    void prettyPrint(std::string &str, prettyPrintFormat& format) const
    {
        // NEEDS_WORK-- do real formatting for reductions
        str += "reduce[NEEDS_WORK](";
        iter_.prettyPrint(str,format);
        str += ")";
    }

  /** \todo do a real shape check (tricky) */
    template<typename T_shape>
    bool shapeCheck(const T_shape&) const
    { 
        return true; 
    }

  // sliceinfo for expressions
  template<typename T1, typename T2 = nilArraySection, 
	   class T3 = nilArraySection, typename T4 = nilArraySection, 
	   class T5 = nilArraySection, typename T6 = nilArraySection, 
	   class T7 = nilArraySection, typename T8 = nilArraySection, 
	   class T9 = nilArraySection, typename T10 = nilArraySection, 
	   class T11 = nilArraySection>
  class SliceInfo {
  public:
    typedef typename T_expr::template SliceInfo<T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11>::T_slice T_slice1;
    typedef _bz_ArrayExprReduce<T_slice1, N_index, T_reduction> T_slice;
};

    template<typename T1, typename T2, typename T3, typename T4, typename T5, typename T6,
        typename T7, typename T8, typename T9, typename T10, typename T11>
    typename SliceInfo<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11>::T_slice
    operator()(T1 r1, T2 r2, T3 r3, T4 r4, T5 r5, T6 r6, T7 r7, T8 r8, T9 r9, T10 r10, T11 r11) const
    {
      // for slicing reduction results, we would need to set the
      // dimension reduced over to Range::all(). That's not easy to do
      // because it requires us to change the type of one of the rn's.
      BZPRECONDITION(0);
    }

private: 
    _bz_ArrayExprReduce() { }

  /** Method for properly initializing the ordering values. \todo If
      the expression being reduced consist of arrays with different
      orderings, the call to iter_.ordering() will fail with a
      "different orderings" error. But just like it can happen that
      ordering values are missing from the expression, it seems
      equally valid that ordering is indefinite in cases where the
      expression has differing values. This doesn't prevent us from
      assigning the expression to an array, and it shouldn't prevent
      the expression from being used in a reduction either. (This is
      bug 2058441.) */
    void computeOrdering()
    {
        TinyVector<bool,rank_> in_ordering;
        in_ordering = false;

        int j = 0;
        for (int i=0; i<rank_; ++i) {
            const int orderingj = iter_.ordering(i);
            if (orderingj != tiny(int()) && orderingj < rank_ && !in_ordering(orderingj)) {
                // unique value in ordering array
                in_ordering(orderingj) = true;
                ordering_(j++) = orderingj;
            }
        }

        // It is possible that ordering is not a permutation of 0,...,rank-1.
        // In that case j will be less than rank. We fill in ordering with
        // the unused values in decreasing order.
        for (int i = rank_; j < rank_; ++j) {
            while (in_ordering(--i)); // find an unused index
            ordering_(j) = i;
        }
    }

    T_reduction reduce_;
    T_expr iter_;
    TinyVector<int,rank_> ordering_;
};

#define BZ_DECL_ARRAY_PARTIAL_REDUCE(fn,reduction)                      \
template<typename T_expr, int N_index>                                  \
inline                                                                  \
 _bz_ArrayExpr<_bz_ArrayExprReduce<_bz_typename blitz::asExpr<T_expr>::T_expr, \
				   N_index,				\
				   reduction<_bz_typename T_expr::T_numtype> > > \
 fn(const blitz::ETBase<T_expr>& expr,				\
    const IndexPlaceholder<N_index>&)					\
{                                                                       \
  return _bz_ArrayExprReduce<_bz_typename blitz::asExpr<T_expr>::T_expr, \
			     N_index,					\
			     reduction<_bz_typename T_expr::T_numtype> > \
    (blitz::asExpr<T_expr>::getExpr(expr.unwrap()));		\
}

BZ_DECL_ARRAY_PARTIAL_REDUCE(sum,      ReduceSum)
BZ_DECL_ARRAY_PARTIAL_REDUCE(mean,     ReduceMean)
BZ_DECL_ARRAY_PARTIAL_REDUCE((min),    ReduceMin)
BZ_DECL_ARRAY_PARTIAL_REDUCE(minIndex, ReduceMinIndex)
BZ_DECL_ARRAY_PARTIAL_REDUCE((max),    ReduceMax)
BZ_DECL_ARRAY_PARTIAL_REDUCE(maxIndex, ReduceMaxIndex)
BZ_DECL_ARRAY_PARTIAL_REDUCE(product,  ReduceProduct)
BZ_DECL_ARRAY_PARTIAL_REDUCE(count,    ReduceCount)
BZ_DECL_ARRAY_PARTIAL_REDUCE(any,      ReduceAny)
BZ_DECL_ARRAY_PARTIAL_REDUCE(all,      ReduceAll)
BZ_DECL_ARRAY_PARTIAL_REDUCE(first,    ReduceFirst)
BZ_DECL_ARRAY_PARTIAL_REDUCE(last,     ReduceLast)

/*
 * Complete reductions
 */

// Prototype of reduction functions
template<typename T_expr, typename T_reduction>
_bz_typename T_reduction::T_resulttype
_bz_ArrayExprFullReduce(T_expr expr, T_reduction reduction);

template<typename T_expr, typename T_reduction>
_bz_typename T_reduction::T_resulttype
_bz_reduceWithIndexTraversal(T_expr expr, T_reduction reduction);

template<typename T_expr, typename T_reduction>
_bz_typename T_reduction::T_resulttype
_bz_reduceWithIndexVectorTraversal(T_expr expr, T_reduction reduction);

#define BZ_DECL_ARRAY_FULL_REDUCE(fn,reduction)				\
template<typename T_expr>                                               \
 _bz_inline_et								\
_bz_typename reduction<_bz_typename T_expr::T_numtype>::T_resulttype    \
 fn(const blitz::ETBase<T_expr>& expr)				\
{                                                                       \
  return _bz_ArrayExprFullReduce					\
    (blitz::asExpr<T_expr>::getExpr(expr.unwrap()),		\
     reduction<_bz_typename T_expr::T_numtype>());			\
}                                                                       \

BZ_DECL_ARRAY_FULL_REDUCE(sum,      ReduceSum)
BZ_DECL_ARRAY_FULL_REDUCE(mean,     ReduceMean)
BZ_DECL_ARRAY_FULL_REDUCE((min),    ReduceMin)
BZ_DECL_ARRAY_FULL_REDUCE((max),    ReduceMax)
BZ_DECL_ARRAY_FULL_REDUCE((minmax), ReduceMinMax)
BZ_DECL_ARRAY_FULL_REDUCE(product,  ReduceProduct)
BZ_DECL_ARRAY_FULL_REDUCE(count,    ReduceCount)
BZ_DECL_ARRAY_FULL_REDUCE(any,      ReduceAny)
BZ_DECL_ARRAY_FULL_REDUCE(all,      ReduceAll)
BZ_DECL_ARRAY_FULL_REDUCE(first,    ReduceFirst)
BZ_DECL_ARRAY_FULL_REDUCE(last,     ReduceLast)

// Special versions of complete reductions: minIndex and
// maxIndex

#define BZ_DECL_ARRAY_FULL_REDUCE_INDEXVECTOR(fn,reduction)             \
template<typename T_expr>                                               \
 _bz_inline_et								\
 _bz_typename reduction<_bz_typename T_expr::T_numtype,			\
			T_expr::rank_>::T_resulttype			\
 fn(const blitz::ETBase<T_expr>& expr)				\
{                                                                       \
  return _bz_reduceWithIndexVectorTraversal				\
    (blitz::asExpr<T_expr>::getExpr(expr.unwrap()),		\
     reduction<_bz_typename T_expr::T_numtype, T_expr::rank_>());	\
}

BZ_DECL_ARRAY_FULL_REDUCE_INDEXVECTOR(minIndex, ReduceMinIndexVector)
BZ_DECL_ARRAY_FULL_REDUCE_INDEXVECTOR(maxIndex, ReduceMaxIndexVector)

}

#include <blitz/array/reduce.cc>

#endif // BZ_ARRAYREDUCE_H
