499 lines
		
	
	
		
			11 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
			
		
		
	
	
			499 lines
		
	
	
		
			11 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
| /*
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|     LA: linear algebra C++ interface library
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|     Copyright (C) 2024 Jiri Pittner <jiri.pittner@jh-inst.cas.cz> or <jiri@pittnerovi.com>
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| 
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|     This program is free software: you can redistribute it and/or modify
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|     it under the terms of the GNU General Public License as published by
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|     the Free Software Foundation, either version 3 of the License, or
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|     (at your option) any later version.
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| 
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|     This program is distributed in the hope that it will be useful,
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|     but WITHOUT ANY WARRANTY; without even the implied warranty of
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|     MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
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|     GNU General Public License for more details.
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| 
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|     You should have received a copy of the GNU General Public License
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|     along with this program.  If not, see <http://www.gnu.org/licenses/>.
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| */
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| 
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| #include <iostream>
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| #include "tensor.h"
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| #include "laerror.h"
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| #include "qsort.h"
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| #include "miscfunc.h"
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| #include <complex>
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| 
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| 
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| namespace LA {
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| 
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| template<typename T>
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| int Tensor<T>:: calcrank()  
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| {
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| int r=0;
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| for(int i=0; i<shape.size(); ++i)
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|         {
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|         if(shape[i].number==0) laerror("empty index group");
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|         r+=shape[i].number;
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|         }
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| myrank=r;
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| return r;
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| }
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| 
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| 
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| 
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| template<typename T>
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| LA_largeindex Tensor<T>::calcsize()
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| {
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| groupsizes.resize(shape.size()); 
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| cumsizes.resize(shape.size());
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| LA_largeindex s=1;
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| for(int i=0; i<shape.size(); ++i)
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|         {
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|         if(shape[i].number==0) laerror("empty index group");
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|         if(shape[i].range==0) return 0;
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|         cumsizes[i]=s;
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|         switch(shape[i].symmetry)
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|                 {
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|                 case 0:
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|                         s *= groupsizes[i] = longpow(shape[i].range,shape[i].number);
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|                         break;
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|                 case 1:
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|                         s *= groupsizes[i] = simplicial(shape[i].number,shape[i].range);
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|                         break;
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|                 case -1:
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|                         s *= groupsizes[i] = simplicial(shape[i].number,shape[i].range-shape[i].number+1);
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|                         break;
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|                 default: 
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|                         laerror("illegal index group symmetry");
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|                         break;
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|                 }
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|         }
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| return s;
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| }
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| 
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| 
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| 
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| 
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| LA_largeindex subindex(int *sign, const INDEXGROUP &g, const NRVec<LA_index> &I) //index of one subgroup 
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| {
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| #ifdef DEBUG
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| if(I.size()<=0) laerror("empty index group in subindex");
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| if(g.number!=I.size()) laerror("mismatch in the number of indices in a group");
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| for(int i=0; i<I.size(); ++i) if(I[i]<g.offset || I[i] >= g.offset+g.range) laerror("index out of range in tensor subindex");
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| #endif
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| 
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| switch(I.size()) //a few special cases for efficiency
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| 	{
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| 	case 0:
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| 		*sign=0;
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| 		return 0;
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| 		break;
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| 	case 1:
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| 		*sign=1;
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| 		return I[0]-g.offset;
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| 		break;
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| 	case 2:
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| 		{
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| 		*sign=1;
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| 		if(g.symmetry==0) return (I[1]-g.offset)*g.range+I[0]-g.offset;
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| 		LA_index i0,i1;
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| 		if(I[0]>I[1]) {i1=I[0]; i0=I[1]; if(g.symmetry<0) *sign = -1;} else {i1=I[1]; i0=I[0];}
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| 		i0 -= g.offset;
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| 		i1 -= g.offset;
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| 		if(g.symmetry<0)
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| 			{
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| 			if(i0==i1) {*sign=0; return -1;}
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| 			return i1*(i1-1)/2+i0;
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| 			}
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| 		else
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| 			{
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| 			return i1*(i1+1)/2+i0;
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| 			}
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| 		}
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| 		break;
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| 
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| 	default: //general case
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| 		{
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| 		*sign=1;
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| 
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|                 if(g.symmetry==0) //rectangular case
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| 			{
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| 			LA_largeindex r=0;
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| 			for(int i=I.size()-1; i>=0; --i)
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| 				{
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| 				r*= g.range;
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| 				r+= I[i]-g.offset;
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| 				}
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| 			return r;
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| 			}
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| 		}
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| 
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| 		//compressed storage case
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| 		NRVec<LA_index> II(I);
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| 		II.copyonwrite();
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| 		if(g.offset!=0) II -= g.offset;
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| 		int parity=netsort(II.size(),&II[0]);
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| 		if(g.symmetry<0 && (parity&1)) *sign= -1;
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| 		if(g.symmetry<0) //antisymmetric
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| 			{
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| 			for(int i=0; i<I.size()-1; ++i) 
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| 				if(II[i]==II[i+1])
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| 					{*sign=0; return -1;} //identical indices of antisymmetric tensor
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| 
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| 			LA_largeindex r=0;
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|                         for(int i=0; i<II.size(); ++i) r += simplicial(i+1,II[i]-i);
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|                         return r;
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| 			}
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| 		else	//symmetric
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| 			{
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| 			LA_largeindex r=0;
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| 			for(int i=0; i<II.size(); ++i) r += simplicial(i+1,II[i]);
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| 			return r;
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| 			}
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| 		break;
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| 	}
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| laerror("this error should not happen");
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| return -1;
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| }
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| 
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| 
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| //inverse map of group superindex to canonically ordered index list
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| NRVec<LA_index>  inverse_subindex(const INDEXGROUP &g, LA_largeindex s)
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| {
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| NRVec<LA_index> I(g.number);
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| if(g.number==1) {I[0]=s+g.offset; return I;}
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| switch(g.symmetry)
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| 	{
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| 	case 0:
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| 		for(int i=0; i<g.number; ++i)
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| 			{
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| 			I[i] = s%g.range;
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| 			s /= g.range;
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| 			}
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| 		break;
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| 	case 1:
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| 		for(int i=g.number; i>0; --i)
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| 			{
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| 			I[i-1] = inverse_simplicial(i,s);
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| 			s -= simplicial(i,I[i-1]);
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| 			}
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| 		break;
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| 	case -1:
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| 		for(int i=g.number-1; i>=0; --i)
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|                         {
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|                         I[i] = i + inverse_simplicial(i+1,s);
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|                         s -= simplicial(i+1,I[i]-i);
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|                         }
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| 		break;
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| 	default: laerror("illegal index symmetry");
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| 	}
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| 
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| if(g.offset!=0) I += g.offset;
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| return I;
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| }
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| 
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| 
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| template<typename T>
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| SUPERINDEX Tensor<T>::inverse_index(LA_largeindex s) const
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| {
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| SUPERINDEX I(shape.size());
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| for(int g=shape.size()-1; g>=0; --g)
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| 	{
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| 	LA_largeindex groupindex;
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| 	if(g>0) 
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| 		{
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| 		groupindex = s/cumsizes[g];
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| 		s %= cumsizes[g];
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| 		}
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| 	else groupindex=s;
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| 	I[g] = inverse_subindex(shape[g],groupindex);
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| 	}
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| return I;
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| }
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| 
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| 
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| 
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| template<typename T>
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| LA_largeindex Tensor<T>::index(int *sign, const SUPERINDEX &I) const
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| {
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| //check index structure and ranges
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| #ifdef DEBUG
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| if(I.size()!=shape.size()) laerror("mismatch in the number of tensor index groups");
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| for(int i=0; i<I.size(); ++i)
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| 	{
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| 	if(shape[i].number!=I[i].size()) {std::cerr<<"error in index group no. "<<i<<std::endl; laerror("mismatch in the size of tensor index group");}
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| 	for(int j=0; j<shape[i].number; ++j)
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| 		{
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| 		if(I[i][j] <shape[i].offset || I[i][j] >= shape[i].offset+shape[i].range) 
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| 			{
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| 			std::cerr<<"error in index group no. "<<i<<" index no. "<<j<<std::endl;
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| 			laerror("tensor index out of range");
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| 			}
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| 		}
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| 	}
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| #endif
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| 
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| LA_largeindex r=0;
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| *sign=1;
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| for(int g=0; g<shape.size(); ++g) //loop over index groups
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| 	{
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| 	int gsign;
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| 	LA_largeindex groupindex =  subindex(&gsign,shape[g],I[g]);
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| 	//std::cout <<"INDEX TEST group "<<g<<" cumsizes "<< cumsizes[g]<<" groupindex "<<groupindex<<std::endl;
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| 	*sign *= gsign;
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| 	if(groupindex == -1) return -1;
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| 	r += groupindex * cumsizes[g];
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| 	}
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| return r;
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| }
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| 
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| 
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| template<typename T>
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| LA_largeindex Tensor<T>::index(int *sign, const FLATINDEX &I) const
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| {
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| #ifdef DEBUG
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| if(rank()!=I.size()) laerror("tensor rank mismatch in index");
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| #endif
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| 
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| LA_largeindex r=0;
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| *sign=1;
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| int gstart=0;
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| for(int g=0; g<shape.size(); ++g) //loop over index groups
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|         {
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|         int gsign;
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| 	int gend= gstart+shape[g].number-1;
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| 	NRVec<LA_index> subI = I.subvector(gstart,gend); 
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| 	gstart=gend+1;
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|         LA_largeindex groupindex =  subindex(&gsign,shape[g],subI);
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|         //std::cout <<"FLATINDEX TEST group "<<g<<" cumsizes "<< cumsizes[g]<<" groupindex "<<groupindex<<std::endl;
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|         *sign *= gsign;
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|         if(groupindex == -1) return -1;
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|         r += groupindex * cumsizes[g];
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|         }
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| return r;
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| }
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| 
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| 
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| template<typename T>
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| LA_largeindex Tensor<T>::vindex(int *sign,  LA_index i1, va_list args) const
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| {
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| NRVec<LA_index> I(rank());
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| I[0]=i1;
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| for(int i=1; i<rank(); ++i)
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| 	{
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| 	I[i] = va_arg(args,LA_index);
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| 	}
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| va_end(args);
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| 
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| return index(sign,I);
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| }
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| 
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| 
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| //binary I/O
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| 
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| template<typename T>
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| void Tensor<T>::put(int fd) const
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| {
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| shape.put(fd,true);
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| groupsizes.put(fd,true);
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| cumsizes.put(fd,true);
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| data.put(fd,true);
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| }
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| 
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| template<typename T>
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| void Tensor<T>::get(int fd)
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| {
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| shape.get(fd,true);
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| myrank=calcrank(); //is not stored but recomputed
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| groupsizes.put(fd,true);
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| cumsizes.get(fd,true);
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| data.get(fd,true);
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| }
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| 
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| 
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| template<typename T>
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| Tensor<T>::Tensor(const NRVec<T> &x)
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| : data(x)
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| {
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| myrank=1;
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| shape.resize(1);
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| shape[0].number=1;
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| shape[0].symmetry=0;
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| #ifndef LA_TENSOR_ZERO_OFFSET
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| shape[0].offset=0;
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| #endif
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| shape[0].range=x.size();
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| calcsize();
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| }
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| 
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| template<typename T>
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| Tensor<T>::Tensor(const NRMat<T> &x)
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| : data(&x(0,0),x.nrows()*x.ncols())
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| {
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| myrank=2;
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| if(x.nrows()==x.ncols())
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| 	{
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| 	shape.resize(1);
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| 	shape[0].number=2;
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| 	shape[0].symmetry=0;
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| #ifndef LA_TENSOR_ZERO_OFFSET
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| 	shape[0].offset=0;
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| #endif
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| 	shape[0].range=x.nrows();
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| 	}
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| else
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| 	{
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| 	shape.resize(2);
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| 	shape[0].number=1; shape[1].number=1;
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| 	shape[0].symmetry=0; shape[1].symmetry=0;
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| #ifndef LA_TENSOR_ZERO_OFFSET
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|         shape[0].offset=0; shape[1].offset=0;
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| #endif
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| 	shape[0].range=x.ncols();
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| 	shape[1].range=x.nrows();
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| 	}
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| calcsize();
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| }
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| 
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| 
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| template<typename T>
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| Tensor<T>::Tensor(const NRSMat<T> &x)
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| : data(NRVec<T>(x))
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| {
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| myrank=2;
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| shape.resize(1);
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| shape[0].number=2;
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| shape[0].symmetry=1;
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| #ifndef LA_TENSOR_ZERO_OFFSET
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|         shape[0].offset=0;
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| #endif
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| shape[0].range=x.nrows();
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| calcsize();
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| }
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| 
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| 
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| template<typename T>
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| void loopingroups(Tensor<T> &t, int ngroup, int igroup, T **p, SUPERINDEX &I, void (*callback)(const SUPERINDEX &, T *))
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| {
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| LA_index istart,iend;
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| switch(t.shape[ngroup].symmetry)
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| 	{
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| 	case 0:
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| 		istart= t.shape[ngroup].offset;
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| 		iend=   t.shape[ngroup].offset+t.shape[ngroup].range-1;
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| 		break;
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| 	case 1:
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| 		istart= t.shape[ngroup].offset;
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| 		if(igroup==t.shape[ngroup].number-1) iend=   t.shape[ngroup].offset+t.shape[ngroup].range-1;
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| 		else iend = I[ngroup][igroup+1];
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| 		break;
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| 	case -1:
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| 		istart= t.shape[ngroup].offset + igroup;
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| 		if(igroup==t.shape[ngroup].number-1) iend=   t.shape[ngroup].offset+t.shape[ngroup].range-1;
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|                 else iend = I[ngroup][igroup+1]-1;
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| 		break;
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| 	}
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| 
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| for(LA_index i = istart; i<=iend; ++i)
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| 	{
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| 	I[ngroup][igroup]=i;
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| 	if(ngroup==0 && igroup==0) 
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| 		{
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| 		int sign;
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| 		//std::cout <<"TEST  "<<t.index(&sign,I)<<" ";
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| 		(*callback)(I,(*p)++);
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| 		}
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| 	else 
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| 		{
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| 		int newigroup= igroup-1;
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| 		int newngroup=ngroup;
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| 		if(newigroup<0)
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| 			{
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| 			--newngroup;
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| 			newigroup=t.shape[newngroup].number-1;
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| 			}
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| 		loopingroups(t,newngroup,newigroup,p,I,callback);
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| 		}
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| 	}
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| }
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| 
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| 
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| template<typename T>
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| void Tensor<T>::loopover(void (*callback)(const SUPERINDEX &, T *))
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| {
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| SUPERINDEX I(shape.size());
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| for(int i=0; i<I.size(); ++i) {I[i].resize(shape[i].number); I[i] = shape[i].offset;}
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| T *pp=&data[0];
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| loopingroups(*this,shape.size()-1,shape[shape.size()-1].number-1,&pp,I,callback);
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| }
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| 
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| 
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| static std::ostream *sout;
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| template<typename T>
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| static void outputcallback(const SUPERINDEX &I, T *v)
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| {
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| //print indices flat
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| for(int i=0; i<I.size(); ++i)
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| 	for(int j=0; j<I[i].size(); ++j) *sout << I[i][j]<<" ";
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| *sout<<" "<< *v<<std::endl;
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| }
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| 
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| 
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| std::ostream & operator<<(std::ostream &s, const INDEXGROUP &x)
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| {
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| s<<x.number <<" "<<x.symmetry<<" ";
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| #ifndef LA_TENSOR_ZERO_OFFSET
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| s<<x.offset<<" ";
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| #endif
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| s<< x.range<<std::endl;
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| return s;
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| }
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| 
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| std::istream & operator>>(std::istream &s, INDEXGROUP &x)
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| {
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| s>>x.number>>x.symmetry;
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| #ifndef LA_TENSOR_ZERO_OFFSET
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| s>>x.offset;
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| #endif
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| s>>x.range;
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| return s;
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| }
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| 
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| 
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| 
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| template<typename T>
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| std::ostream & operator<<(std::ostream &s, const Tensor<T> &x)
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| {
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| s<<x.shape;
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| sout= &s;
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| const_cast<Tensor<T> *>(&x)->loopover(&outputcallback<T>);
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| return s;
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| }
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| 
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| template <typename T>
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| std::istream & operator>>(std::istream &s, Tensor<T> &x)
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| {
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| s>>x.shape;
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| x.data.resize(x.calcsize()); x.calcrank();
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| FLATINDEX I(x.rank());
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| for(LA_largeindex i=0; i<x.data.size(); ++i)
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| 	{
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| 	for(int j=0; j<I.size(); ++j) s>>I[j];
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| 	T val; s>>val;
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| 	x.lhs(I) = val;
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| 	}
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| return s;
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| }
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| 
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| 
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| 
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| template class Tensor<double>;
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| template class Tensor<std::complex<double> >;
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| template std::ostream & operator<<(std::ostream &s, const Tensor<double> &x);
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| template std::ostream & operator<<(std::ostream &s, const Tensor<std::complex<double> > &x);
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| template std::istream & operator>>(std::istream &s, Tensor<double> &x);
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| template std::istream & operator>>(std::istream &s, Tensor<std::complex<double> > &x);
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| 
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| 
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| }//namespace
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