| 1 | /*
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| 2 |  * $Id: methods.cc,v 1.1.1.1 1999-04-09 17:59:03 ansari Exp $
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| 3 |  *
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| 4 |  * $Log: not supported by cvs2svn $
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| 5 |  * Revision 1.4  1998/03/14 00:04:47  tveldhui
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| 6 |  * 0.2-alpha-05
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| 7 |  *
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| 8 |  * Revision 1.3  1997/08/18 19:13:08  tveldhui
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| 9 |  * Just prior to implementing fastRead() optimization for array
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| 10 |  * expression evaluation.
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| 11 |  *
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| 12 |  * Revision 1.2  1997/08/15 21:14:10  tveldhui
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| 13 |  * Just prior to loop-collapse change
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| 14 |  *
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| 15 |  */
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| 16 | 
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| 17 | #ifndef BZ_ARRAYMETHODS_CC
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| 18 | #define BZ_ARRAYMETHODS_CC
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| 19 | 
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| 20 | #ifndef BZ_ARRAY_H
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| 21 |  #error <blitz/array/methods.cc> must be included via <blitz/array.h>
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| 22 | #endif
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| 23 | 
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| 24 | #include <blitz/minmax.h>  // Needed for resizeAndPreserve()
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| 25 | 
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| 26 | BZ_NAMESPACE(blitz)
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| 27 | 
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| 28 | template<class P_numtype, int N_rank> template<class T_expr>
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| 29 | Array<P_numtype,N_rank>::Array(_bz_ArrayExpr<T_expr> expr)
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| 30 | {
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| 31 |     BZ_NOT_IMPLEMENTED();
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| 32 | 
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| 33 |     // Obtain storage order from an operand in the expression
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| 34 |     // (if possible).  Probably best to assume C-style storage,
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| 35 |     // then pass the storage object to the expression for possible
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| 36 |     // modification.
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| 37 | 
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| 38 |     // Obtain ubounds/lbounds from array operands.  Precondition
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| 39 |     // failure if any bounds missing.
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| 40 | 
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| 41 |     // Size array.
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| 42 | 
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| 43 |     // assignment of expression.
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| 44 | }
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| 45 | 
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| 46 | template<class T_numtype, int N_rank>
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| 47 | Array<T_numtype,N_rank>::Array(const TinyVector<int, N_rank>& lbounds,
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| 48 |     const TinyVector<int, N_rank>& extent,
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| 49 |     const GeneralArrayStorage<N_rank>& storage)
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| 50 |     : storage_(storage)
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| 51 | {
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| 52 |     length_ = extent;
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| 53 |     storage_.setBase(lbounds);
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| 54 |     setupStorage(N_rank - 1);
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| 55 | }
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| 56 | 
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| 57 | 
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| 58 | /*
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| 59 |  * This routine takes the storage information for the array
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| 60 |  * (ascendingFlag_[], base_[], and ordering_[]) and the size
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| 61 |  * of the array (length_[]) and computes the stride vector
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| 62 |  * (stride_[]) and the zero offset (see explanation in array.h).
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| 63 |  */
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| 64 | template<class P_numtype, int N_rank>
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| 65 | _bz_inline2 void Array<P_numtype, N_rank>::computeStrides()
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| 66 | {
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| 67 |     if (N_rank > 1)
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| 68 |     {
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| 69 |       int stride = 1;
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| 70 | 
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| 71 |       // This flag simplifies the code in the loop, encouraging
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| 72 |       // compile-time computation of strides through constant folding.
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| 73 |       _bz_bool allAscending = storage_.allRanksStoredAscending();
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| 74 | 
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| 75 |       // BZ_OLD_FOR_SCOPING
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| 76 |       int n;
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| 77 |       for (n=0; n < N_rank; ++n)
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| 78 |       {
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| 79 |           int strideSign = +1;
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| 80 | 
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| 81 |           // If this rank is stored in descending order, then the stride
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| 82 |           // will be negative.
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| 83 |           if (!allAscending)
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| 84 |           {
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| 85 |             if (!isRankStoredAscending(ordering(n)))
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| 86 |                 strideSign = -1;
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| 87 |           }
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| 88 | 
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| 89 |           // The stride for this rank is the product of the lengths of
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| 90 |           // the ranks minor to it.
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| 91 |           stride_[ordering(n)] = stride * strideSign;
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| 92 | 
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| 93 |           stride *= length_[ordering(n)];
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| 94 |       }
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| 95 |     }
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| 96 |     else {
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| 97 |         // Specialization for N_rank == 1
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| 98 |         // This simpler calculation makes it easier for the compiler
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| 99 |         // to propagate stride values.
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| 100 | 
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| 101 |         if (isRankStoredAscending(0))
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| 102 |             stride_[0] = 1;
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| 103 |         else
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| 104 |             stride_[0] = -1;
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| 105 |     }
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| 106 | 
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| 107 |     calculateZeroOffset();
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| 108 | }
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| 109 | 
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| 110 | template<class T_numtype, int N_rank>
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| 111 | void Array<T_numtype, N_rank>::calculateZeroOffset()
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| 112 | {
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| 113 |     // Calculate the offset of (0,0,...,0)
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| 114 |     zeroOffset_ = 0;
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| 115 | 
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| 116 |     // zeroOffset_ = - sum(where(ascendingFlag_, stride_ * base_,
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| 117 |     //     (length_ - 1 + base_) * stride_))
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| 118 |     for (int n=0; n < N_rank; ++n)
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| 119 |     {
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| 120 |         if (!isRankStoredAscending(n))
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| 121 |             zeroOffset_ -= (length_[n] - 1 + base(n)) * stride_[n];
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| 122 |         else
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| 123 |             zeroOffset_ -= stride_[n] * base(n);
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| 124 |     }
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| 125 | }
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| 126 | 
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| 127 | 
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| 128 | 
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| 129 | template<class P_numtype, int N_rank>
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| 130 | void Array<P_numtype, N_rank>::dumpStructureInformation(ostream& os) const
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| 131 | {
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| 132 |     os << "Dump of Array<" << BZ_DEBUG_TEMPLATE_AS_STRING_LITERAL(P_numtype) 
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| 133 |        << ", " << N_rank << ">:" << endl
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| 134 |        << "ordering_      = " << storage_.ordering() << endl
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| 135 |        << "ascendingFlag_ = " << storage_.ascendingFlag() << endl
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| 136 |        << "base_          = " << storage_.base() << endl
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| 137 |        << "length_        = " << length_ << endl
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| 138 |        << "stride_        = " << stride_ << endl
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| 139 |        << "zeroOffset_    = " << zeroOffset_ << endl
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| 140 |        << "numElements()  = " << numElements() << endl
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| 141 |        << "storageContiguous = " << storageContiguous_ << endl;
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| 142 | }
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| 143 | 
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| 144 | /*
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| 145 |  * Make this array a view of another array's data.
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| 146 |  */
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| 147 | template<class P_numtype, int N_rank>
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| 148 | void Array<P_numtype, N_rank>::reference(Array<P_numtype, N_rank>& array)
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| 149 | {
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| 150 |     storage_ = array.storage_;
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| 151 |     length_ = array.length_;
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| 152 |     stride_ = array.stride_;
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| 153 |     zeroOffset_ = array.zeroOffset_;
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| 154 |     storageContiguous_ = array.storageContiguous_;
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| 155 | 
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| 156 |     MemoryBlockReference<P_numtype>::changeBlock(array, array.zeroOffset_);
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| 157 | 
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| 158 |     data_ = array.data_;
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| 159 | }
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| 160 | 
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| 161 | /*
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| 162 |  * This method is called to allocate memory for a new array.  
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| 163 |  */
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| 164 | template<class P_numtype, int N_rank>
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| 165 | _bz_inline2 void Array<P_numtype, N_rank>::setupStorage(int lastRankInitialized)
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| 166 | {
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| 167 |     TAU_TYPE_STRING(p1, "Array<T,N>::setupStorage() [T="
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| 168 |         + CT(P_numtype) + ",N=" + CT(N_rank) + "]");
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| 169 |     TAU_PROFILE(" ", p1, TAU_BLITZ);
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| 170 | 
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| 171 |     /*
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| 172 |      * If the length of some of the ranks was unspecified, fill these
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| 173 |      * in using the last specified value.
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| 174 |      *
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| 175 |      * e.g. Array<int,3> A(40) results in a 40x40x40 array.
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| 176 |      */
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| 177 |     for (int i=lastRankInitialized + 1; i < N_rank; ++i)
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| 178 |     {
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| 179 |         storage_.setBase(i, storage_.base(lastRankInitialized));
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| 180 |         length_[i] = length_[lastRankInitialized];
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| 181 |     }
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| 182 | 
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| 183 |     // Compute strides
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| 184 |     computeStrides();
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| 185 | 
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| 186 |     // Allocate a block of memory
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| 187 |     MemoryBlockReference<P_numtype>::newBlock(numElements());
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| 188 | 
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| 189 |     // Adjust the base of the array to account for non-zero base
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| 190 |     // indices and reversals
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| 191 |     data_ += zeroOffset_;
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| 192 | 
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| 193 |     // A new array will always have contiguous storage
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| 194 |     storageContiguous_ = _bz_true;
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| 195 | }
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| 196 | 
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| 197 | template<class T_numtype, int N_rank>
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| 198 | Array<T_numtype, N_rank> Array<T_numtype, N_rank>::copy() const
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| 199 | {
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| 200 |     if (numElements())
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| 201 |     {
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| 202 |         Array<T_numtype, N_rank> z(length_, storage_);
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| 203 |         z = *this;
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| 204 |         return z;
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| 205 |     }
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| 206 |     else {
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| 207 |         // Null array-- don't bother allocating an empty block.
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| 208 |         return *this;
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| 209 |     }
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| 210 | }
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| 211 | 
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| 212 | template<class T_numtype, int N_rank>
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| 213 | void Array<T_numtype, N_rank>::makeUnique()
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| 214 | {
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| 215 |     if (numReferences() > 1)
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| 216 |     {
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| 217 |         T_array tmp = copy();
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| 218 |         reference(tmp);
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| 219 |     }
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| 220 | }
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| 221 | 
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| 222 | template<class T_numtype, int N_rank>
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| 223 | Array<T_numtype, N_rank> Array<T_numtype, N_rank>::transpose(int r0, int r1, 
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| 224 |     int r2, int r3, int r4, int r5, int r6, int r7, int r8, int r9, int r10)
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| 225 | {
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| 226 |     T_array B(*this);
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| 227 |     B.transposeSelf(r0,r1,r2,r3,r4,r5,r6,r7,r8,r9,r10);
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| 228 |     return B;
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| 229 | }
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| 230 | 
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| 231 | template<class T_numtype, int N_rank>
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| 232 | void Array<T_numtype, N_rank>::transposeSelf(int r0, int r1, int r2, int r3,
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| 233 |     int r4, int r5, int r6, int r7, int r8, int r9, int r10)
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| 234 | {
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| 235 |     BZPRECHECK(r0+r1+r2+r3+r4+r5+r6+r7+r8+r9+r10 == N_rank * (N_rank-1) / 2,
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| 236 |         "Invalid array transpose() arguments." << endl
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| 237 |         << "Arguments must be a permutation of the numerals (0,...,"
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| 238 |         << (N_rank - 1) << ")");
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| 239 | 
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| 240 |     // Create a temporary reference copy of this array
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| 241 |     Array<T_numtype, N_rank> x(*this);
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| 242 | 
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| 243 |     // Now reorder the dimensions using the supplied permutation
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| 244 |     doTranspose(0, r0, x);
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| 245 |     doTranspose(1, r1, x);
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| 246 |     doTranspose(2, r2, x);
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| 247 |     doTranspose(3, r3, x);
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| 248 |     doTranspose(4, r4, x);
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| 249 |     doTranspose(5, r5, x);
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| 250 |     doTranspose(6, r6, x);
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| 251 |     doTranspose(7, r7, x);
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| 252 |     doTranspose(8, r8, x);
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| 253 |     doTranspose(9, r9, x);
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| 254 |     doTranspose(10, r10, x);
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| 255 | }
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| 256 | 
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| 257 | template<class T_numtype, int N_rank>
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| 258 | void Array<T_numtype, N_rank>::doTranspose(int destRank, int sourceRank,
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| 259 |     Array<T_numtype, N_rank>& array)
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| 260 | {
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| 261 |     // BZ_NEEDS_WORK: precondition check
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| 262 | 
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| 263 |     if (destRank >= N_rank)
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| 264 |         return;
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| 265 | 
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| 266 |     length_[destRank] = array.length_[sourceRank];
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| 267 |     stride_[destRank] = array.stride_[sourceRank];
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| 268 |     storage_.setAscendingFlag(destRank, 
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| 269 |         array.isRankStoredAscending(sourceRank));
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| 270 |     storage_.setBase(destRank, array.base(sourceRank));
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| 271 | 
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| 272 |     // BZ_NEEDS_WORK: Handling the storage ordering is currently O(N^2)
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| 273 |     // but it can be done fairly easily in linear time by constructing
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| 274 |     // the appropriate permutation.
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| 275 | 
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| 276 |     // Find sourceRank in array.storage_.ordering_
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| 277 |     int i=0;
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| 278 |     for (; i < N_rank; ++i)
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| 279 |         if (array.storage_.ordering(i) == sourceRank)
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| 280 |             break;
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| 281 | 
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| 282 |     storage_.setOrdering(i, destRank);
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| 283 | }
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| 284 | 
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| 285 | template<class T_numtype, int N_rank>
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| 286 | void Array<T_numtype, N_rank>::reverseSelf(int rank)
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| 287 | {
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| 288 |     BZPRECONDITION(rank < N_rank);
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| 289 | 
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| 290 |     storage_.setAscendingFlag(rank, !isRankStoredAscending(rank));
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| 291 | 
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| 292 |     int adjustment = stride_[rank] * (length_[rank] - 1);
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| 293 |     zeroOffset_ += adjustment;
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| 294 |     data_ += adjustment;
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| 295 |     stride_[rank] *= -1;
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| 296 | }
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| 297 | 
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| 298 | template<class T_numtype, int N_rank>
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| 299 | Array<T_numtype, N_rank> Array<T_numtype,N_rank>::reverse(int rank)
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| 300 | {
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| 301 |     T_array B(*this);
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| 302 |     B.reverseSelf(rank);
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| 303 |     return B;
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| 304 | }
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| 305 | 
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| 306 | template<class T_numtype, int N_rank> template<class T_numtype2>
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| 307 | Array<T_numtype2,N_rank> Array<T_numtype,N_rank>::extractComponent(T_numtype2, 
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| 308 |     int componentNumber, int numComponents)
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| 309 | {
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| 310 |     BZPRECONDITION((componentNumber >= 0) && (componentNumber < numComponents));
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| 311 | 
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| 312 |     TinyVector<int,N_rank> stride2;
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| 313 |     stride2 = stride_ * numComponents;
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| 314 |     T_numtype2* dataFirst2 = ((T_numtype2*)dataFirst()) + componentNumber;
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| 315 |     return Array<T_numtype2,N_rank>(dataFirst2, length_, stride2, storage_);
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| 316 | }
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| 317 | 
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| 318 | BZ_NAMESPACE_END
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| 319 | 
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| 320 | #endif // BZ_ARRAY_CC
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| 321 | 
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