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rtomiyasu |
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/* |
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* The MIT License |
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Conograph (powder auto-indexing program) |
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Copyright (c) <2012> <Ryoko Oishi-Tomiyasu, KEK> |
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Permission is hereby granted, free of charge, to any person obtaining a copy |
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of this software and associated documentation files (the "Software"), to deal |
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in the Software without restriction, including without limitation the rights |
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell |
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copies of the Software, and to permit persons to whom the Software is |
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furnished to do so, subject to the following conditions: |
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The above copyright notice and this permission notice shall be included in |
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all copies or substantial portions of the Software. |
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN |
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THE SOFTWARE. |
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* |
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*/ |
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#include <limits> |
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#include <algorithm> |
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#include "gather_q_of_Ndim_lattice.hh" |
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#include "../utility_func/zmath.hh" |
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// S_super is a Selling-reduced positive definite symmetric matrix. |
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// - sum_{i != j} (ci-cj)^2*Sij <= maxQ |
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static void set_max_range(const SymMat<Double>& S_super, const Double& maxQ, |
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SymMat<Int4>& max_range) |
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{ |
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const Int4 ISIZE = max_range.size(); |
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assert( S_super.size() == ISIZE + 1 ); |
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assert( 1 <= ISIZE && ISIZE <= 4 ); |
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static const Int4 MAX_INT = numeric_limits<Int4>::max(); |
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static const Int4 SQUARE_MAX_INT = ifloor( sqrt( (Double)MAX_INT ) ); |
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const Double min_dp = - maxQ / Double(MAX_INT); |
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max_range = SQUARE_MAX_INT; |
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// From (ci-cj)^2 <= (ci-ck)^2 + (cj-ck)^2 + (ci-cl)^2 + (cj-cl)^2, |
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// Sij > 0 |
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// => -Sij*(ci-cj)^2 >= -Sij * { (ci-ck)^2 + (cj-ck)^2 + (ci-cl)^2 + (cj-cl)^2 }. |
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// Sij > 0, Skl > 0 for distinct 1 <= i, j, k, l, m <= 5 |
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// => -Sij*(ci-cj)^2 - Skl*(ck-cl)^2 >= -(Sij + Skl) * { (ci-ck)^2 + (cj-ck)^2 + (ci-cl)^2 + (cj-cl)^2 }, |
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// -Sij*(ci-cj)^2 - Skl*(ck-cl)^2 >= -Sij * { (ci-cm)^2 + (cj-cm)^2 + (ci-cl)^2 } - Skl * { (cm-ck)^2 + (cj-ck)^2 + (cm-cl)^2 } - (Sij + Skl) * (cj-cl)^2 |
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for(Int4 n=0; n<ISIZE; n++) |
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{ |
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for(Int4 n2=n+1; n2<ISIZE; n2++) |
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{ |
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if( S_super(n, n2) < min_dp ) max_range(n, n2) = ifloor( sqrt( - maxQ / S_super(n, n2) ) ); |
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} |
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if( S_super(n, ISIZE) < min_dp ) max_range(n, n) = ifloor( sqrt( - maxQ / S_super(n, ISIZE) ) ); |
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} |
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} |
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static void arrange_max_range(SymMat<Int4>& max_range) |
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{ |
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const Int4 ISIZE = max_range.size(); |
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Int4 num; |
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bool flag = true; |
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while( flag ) |
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{ |
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flag = false; |
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for(Int4 i=0; i<ISIZE; i++) |
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{ |
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for(Int4 i2=0; i2<i; i2++) |
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{ |
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num = max_range(i,i)+max_range(i2,i2); |
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for(Int4 k=0; k<ISIZE; k++) |
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{ |
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// |ci - ci2| <= |ci - ck| + |ci2 - ck| |
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num = min( max_range(i,k)+max_range(i2,k), num); |
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} |
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if( num < max_range(i,i2) ) |
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{ |
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max_range(i,i2) = num; |
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flag = true; |
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} |
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} |
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num = max_range(i,i); |
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for(Int4 k=0; k<ISIZE; k++) |
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{ |
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// |ci| <= |ci - ck| + |ck| |
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num = min( max_range(i,k)+max_range(k,k), num ); |
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} |
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if( num < max_range(i,i) ) |
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{ |
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max_range(i,i) = num; |
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flag = true; |
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} |
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} |
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} |
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} |
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inline Double norm(const NRVec<Int4>& vec_Zn, const SymMat<Double>& S_super) |
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{ |
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const Int4 ISIZE = vec_Zn.size(); |
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assert( ISIZE + 1 == S_super.size() ); |
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Double ans = 0.0; |
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for(Int4 i=0; i<ISIZE; i++) |
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{ |
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for(Int4 j=0; j<i; j++) |
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{ |
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ans += S_super(i,j)*(vec_Zn[i]*vec_Zn[j]*2); |
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} |
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ans += S_super(i,i)*(vec_Zn[i]*vec_Zn[i]); |
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} |
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return ans; |
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} |
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static void set_candidate_Q(const Int4& index, |
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const SymMat<Double>& S_super, |
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const Double& maxQ, |
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const SymMat<Int4>& max_range, |
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NRVec<Int4>& vec_Zn, vector<HKL_Q>& qcal_tray) |
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{ |
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const Int4 ISIZE = vec_Zn.size(); |
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assert( ISIZE + 1 == S_super.size() ); |
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if( index >= ISIZE ) // coef is determined. |
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{ |
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const Double Q = norm( vec_Zn, S_super ); |
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if( maxQ >= Q ) |
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{ |
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qcal_tray.push_back(HKL_Q(vec_Zn, Q)); |
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} |
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return; |
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} |
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// vec_Zn[index] <= max_coef |
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// vec_Zn[index] >= min_coef |
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Int4 max_coef = max_range(index,index); |
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Int4 min_coef = -max_range(index,index); |
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for(Int4 k=0; k<index; k++) |
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{ |
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// vec_Zn[index] - vec_Zn[k] <= max_range(k,index). |
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max_coef = min( max_coef, max_range(k,index) + vec_Zn[k] ); |
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// -max_range(k,index) <= vec_Zn[index] - vec_Zn[k]. |
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min_coef = max( min_coef, -max_range(k,index) + vec_Zn[k] ); |
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} |
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// First non-zero entry should be positive. |
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bool non_zero_entry = false; |
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for(Int4 i=0; i<index; i++) |
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{ |
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if( vec_Zn[i] != 0 ) |
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{ |
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non_zero_entry = true; |
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break; |
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} |
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} |
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if( !non_zero_entry ) min_coef = 0; |
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for(Int4 ic=max_coef; ic>=min_coef; ic--) |
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{ |
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vec_Zn[index] = ic; |
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set_candidate_Q(index+1, S_super, maxQ, max_range, vec_Zn, qcal_tray); |
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} |
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} |
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void gatherQcal(const SymMat<Double>& S_super, |
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const Double& maxQ, |
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vector<HKL_Q>& qcal_tray |
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) |
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{ |
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qcal_tray.clear(); |
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const Int4 ISIZE = S_super.size() - 1; |
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assert( 1 <= ISIZE && ISIZE <= 4 ); |
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SymMat<Int4> max_range(ISIZE); |
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set_max_range(S_super, maxQ, max_range); |
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arrange_max_range(max_range); |
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NRVec<Int4> vec_ZN(ISIZE); |
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set_candidate_Q(0, S_super, maxQ, max_range, vec_ZN, qcal_tray); |
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sort( qcal_tray.begin(), qcal_tray.end() ); |
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} |
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rtomiyasu |
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inline VecDat3<Int4> product_hkl(const VecDat3<Int4>& lhs, const NRMat<Int4>& rhs) |
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{ |
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assert( rhs.nrows() >= 3 && rhs.ncols() == 3 ); |
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VecDat3<Int4> ans; |
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ans[0] = lhs[0]*rhs[0][0] + lhs[1]*rhs[1][0] + lhs[2]*rhs[2][0]; |
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ans[1] = lhs[0]*rhs[0][1] + lhs[1]*rhs[1][1] + lhs[2]*rhs[2][1]; |
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ans[2] = lhs[0]*rhs[0][2] + lhs[1]*rhs[1][2] + lhs[2]*rhs[2][2]; |
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return ans; |
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} |
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// On input, S_super = TransMat * S * transpose(TransMat). |
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void gatherQcal(const SymMat<Double>& S_super, |
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const Double& maxQ, |
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const NRMat<Int4>& transform_hkl, |
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vector<HKL_Q>& qcal_tray |
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) |
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{ |
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gatherQcal(S_super, maxQ, qcal_tray); |
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for(vector<HKL_Q>::iterator it=qcal_tray.begin(); it<qcal_tray.end(); it++) |
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{ |
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it->setHKL( product_hkl(it->HKL(), transform_hkl) ); |
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} |
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} |
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rtomiyasu |
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bool associateQcalWithQobs( |
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const vector<HKL_Q>::const_iterator& it_begin, |
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const vector<HKL_Q>::const_iterator& it_end, |
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const Int4& scale_of_qcal, |
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const vector<Double>& qobs_tray, |
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const Double& resol) |
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{ |
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vector<Double>::const_iterator it_begin2, it_end2; |
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for(vector<HKL_Q>::const_iterator it=it_begin; it<it_end; it++) |
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{ |
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it_begin2 = lower_bound( qobs_tray.begin(), qobs_tray.end(), it->Q()*scale_of_qcal*(1.0 - resol) ); |
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it_end2 = upper_bound( it_begin2, qobs_tray.end(), it->Q()*scale_of_qcal*(1.0 + resol) ); |
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if( it_begin2 >= it_end2 ) return false; |
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} |
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return true; |
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} |
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void associateQobsWithQcal( |
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vector<Double>::const_iterator it_begin, vector<Double>::const_iterator it_end, |
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const vector<HKL_Q>& qcal_tray, |
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vector< vector<HKL_Q>::const_iterator >& closest_qcal_tray) |
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{ |
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closest_qcal_tray.clear(); |
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for(vector<Double>::const_iterator it=it_begin; it<it_end; it++) |
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{ |
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closest_qcal_tray.push_back( closest_data(qcal_tray.begin(), qcal_tray.end(), *it) ); |
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} |
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} |
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vector<Double>::const_iterator associateQobsWithQcal( |
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const vector<Double>::const_iterator& it_begin, |
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const vector<Double>::const_iterator& it_end, |
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const vector<HKL_Q>& qcal_tray, const Double& resol, |
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vector< vector<HKL_Q>::const_iterator >& closest_qcal_tray) |
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{ |
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closest_qcal_tray.clear(); |
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vector<HKL_Q>::const_iterator it_begin2, it_end2; |
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for(vector<Double>::const_iterator it=it_begin; it<it_end; it++) |
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{ |
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it_begin2 = lower_bound( qcal_tray.begin(), qcal_tray.end(), HKL_Q(NRVec<Int4>(), *it*(1.0 - resol) ) ); |
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it_end2 = upper_bound( it_begin2, qcal_tray.end(), HKL_Q(NRVec<Int4>(), *it*(1.0 + resol) ) ); |
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if( it_begin2 >= it_end2 ) return it; |
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else closest_qcal_tray.push_back( closest_data(it_begin2, it_end2, *it) ); |
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} |
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return it_end; |
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} |