/*******************************************************************************
*
* TRIQS: a Toolbox for Research in Interacting Quantum Systems
*
* Copyright (C) 2011-2013 by M. Ferrero, O. Parcollet
*
* TRIQS is free software: you can redistribute it and/or modify it under the
* terms of the GNU General Public License as published by the Free Software
* Foundation, either version 3 of the License, or (at your option) any later
* version.
*
* TRIQS is distributed in the hope that it will be useful, but WITHOUT ANY
* WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
* FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
* details.
*
* You should have received a copy of the GNU General Public License along with
* TRIQS. If not, see .
*
******************************************************************************/
#ifndef TRIQS_DETMANIP_H
#define TRIQS_DETMANIP_H
#include
#include
#include
#include
//#include
#include
#include
#include
#include
#include
#include
#include
#include
namespace triqs { namespace det_manip {
/**
* \brief Standard matrix/det manipulations used in several QMC.
*/
template
class det_manip {
private:
typedef utility::function_arg_ret_type f_tr;
static_assert(f_tr::arity == 2, "det_manip : the function must take two arguments !");
// Do we REALLY need this ?
static_assert(std::is_same< typename f_tr::template decay_arg<0>::type, typename f_tr::template decay_arg<1>::type>::value,
"det_manip : the two arguments must of the function must have the same type");
public:
typedef typename f_tr::template decay_arg<0>::type xy_type;
typedef typename f_tr::result_type value_type;
static_assert( std::is_floating_point::value || boost::is_complex::value, "det_manip : the function must return a floating number or a complex number");
typedef arrays::vector vector_type;
typedef arrays::matrix matrix_type;
typedef arrays::matrix_view matrix_view_type;
protected: // the data
typedef std::ptrdiff_t int_type;
typedef arrays::range range;
FunctionType f;
// serialized data. There are all VALUES.
value_type det;
size_t Nmax,N, last_try;
std::vector row_num,col_num;
std::vector x_values,y_values;
int sign;
matrix_type mat_inv;
long long n_opts, n_opts_max_before_check;
private:
// ------------ BOOST Serialization ------------
// What about f ? Not serialized at the moment.
friend class boost::serialization::access;
template
void serialize(Archive & ar) {
using boost::serialization::make_nvp;
ar & make_nvp("Nmax",Nmax) & make_nvp("N",N)
& make_nvp("n_opts",n_opts) & make_nvp("n_opts_max_before_check",n_opts_max_before_check)
& make_nvp("det",det) & make_nvp("sign",sign)
& make_nvp("Minv",mat_inv)
& make_nvp("row_num",row_num) & make_nvp("col_num",col_num)
& make_nvp("x_values",x_values) & make_nvp("y_values",y_values);
}
/// Write into HDF5
friend void h5_write (h5::group fg, std::string subgroup_name, det_manip const & g) {
auto gr = fg.create_group(subgroup_name);
h5_write(gr,"N",g.N);
h5_write(gr,"mat_inv",g.mat_inv);
h5_write(gr,"det",g.det);
h5_write(gr,"sign",g.sign);
//h5_write(gr,"row_num",g.row_num);
//h5_write(gr,"col_num",g.col_num);
h5_write(gr,"x_values",g.x_values);
h5_write(gr,"y_values",g.y_values);
h5_write(gr,"n_opts",g.n_opts);
h5_write(gr,"n_opts_max_before_check",g.n_opts_max_before_check);
}
/// Read from HDF5
friend void h5_read (h5::group fg, std::string subgroup_name, det_manip & g){
auto gr = fg.open_group(subgroup_name);
h5_read(gr,"N",g.N);
h5_read(gr,"mat_inv",g.mat_inv);
g.Nmax = g.mat_inv.dim0(); // restore Nmax
g.last_try = 0;
h5_read(gr,"det",g.det);
h5_read(gr,"sign",g.sign);
//h5_read(gr,"row_num",g.row_num);
//h5_read(gr,"col_num",g.col_num);
h5_read(gr,"x_values",g.x_values);
h5_read(gr,"y_values",g.y_values);
h5_read(gr,"n_opts",g.n_opts);
h5_read(gr,"n_opts_max_before_check",g.n_opts_max_before_check);
}
private:
// temporary work data, not saved, serialized, etc....
struct work_data_type1 {
xy_type x, y;
vector_type MB,MC, B, C;
value_type ksi;
size_t i,j,ireal,jreal;
void reserve(size_t s) { B.resize(s); C.resize(s); MB.resize(s); MC.resize(s); MB()=0; MC()=0; }
};
struct work_data_type2 {
xy_type x[2], y[2];
matrix_type MB,MC, B, C,ksi;
size_t i[2],j[2],ireal[2],jreal[2];
void reserve(size_t s) { MB.resize(s,2); MC.resize(2,s); B.resize(s,2), C.resize(2,s); ksi.resize(2,2); MB() = 0; MC() = 0; }
value_type det_ksi() const { return ksi(0,0) * ksi(1,1) - ksi(1,0)* ksi(0,1);}
};
work_data_type1 w1;
work_data_type2 w2;
value_type newdet;
int newsign;
private: // for the move constructor, I need to separate the swap since f may not be defaulted constructed
void swap_but_f (det_manip & rhs) noexcept {
using std::swap;
#define SW(a) swap(this->a,rhs.a)
SW(det);SW(Nmax);SW(N); SW(last_try);
SW(row_num); SW(col_num);
SW(x_values); SW(y_values);
SW(sign); SW(mat_inv); SW(n_opts); SW(n_opts_max_before_check);
SW(w1); SW(w2); SW(newdet); SW(newsign);
#undef SW
}
friend void swap(det_manip& lhs, det_manip & rhs) noexcept {
using std::swap;
swap(lhs.f, rhs.f);
lhs.swap_but_f(rhs);
}
public:
/**
* Like for std::vector, reserve memory for a bigger size.
* Preserves only the matrix, not the temporary working vectors/matrices, so do NOT use it
* between a try_XXX and acomplete_operation
*/
void reserve (size_t new_size) {
if (new_size <= Nmax) return;
matrix_type Mcopy(mat_inv);
size_t N0 = Nmax; Nmax = new_size;
mat_inv.resize(Nmax,Nmax); mat_inv(range(0,N0), range(0,N0)) = Mcopy; // keep the content of mat_inv ---> into the lib ?
row_num.reserve(Nmax);col_num.reserve(Nmax); x_values.reserve(Nmax);y_values.reserve(Nmax);
w1.reserve(Nmax); w2.reserve(Nmax);
}
private:
void _construct_common() {
last_try=0; sign =1;
n_opts=0; n_opts_max_before_check = 100;
}
public:
/**
* \brief Constructor.
*
* \param F The function (NB : a copy is made of the F object in this class).
* \param init_size The maximum size of the matrix before a resize (like reserve in std::vector).
* Like std::vector, resize is automatic (by a factor 2) but can yield a performance penalty
* if it happens too often.
*/
det_manip(FunctionType F,size_t init_size):
f(std::move(F)), Nmax(0) , N(0){
reserve(init_size);
mat_inv()=0;
det = 1;
_construct_common();
}
/** \brief Constructor.
*
* \param F The function (NB : a copy is made of the F object in this class).
* \tparam ArgumentContainer
* \param X, Y : container for X,Y.
*/
template
det_manip(FunctionType F, ArgumentContainer1 const & X, ArgumentContainer2 const & Y) : f(std::move(F)) {
if (X.size() != Y.size()) TRIQS_RUNTIME_ERROR<< " X.size != Y.size";
_construct_common();
N =X.size();
if (N==0) { det = 1; reserve(30); return;}
if (N>Nmax) reserve(2*N); // put some margin..
std::copy(X.begin(),X.end(), std::back_inserter(x_values));
std::copy(Y.begin(),Y.end(), std::back_inserter(y_values));
mat_inv()=0;
for (size_t i=0; iswap_but_f(rhs);} // f need not have a default constructor and we dont swap the temp data...
//det_manip& operator=(const det_manip&) = default;
det_manip& operator=(const det_manip&) = delete;
det_manip& operator=(det_manip&& rhs) noexcept { assert((last_try==0)&&(rhs.last_try==0)); swap(*this,rhs); return *this; }
/// Put to size 0 : like a vector
void clear () {
N = 0; sign = 1;det =1; last_try = 0;
row_num.clear(); col_num.clear(); x_values.clear(); y_values.clear();
}
//----------------------- READ ACCESS TO DATA ----------------------------------
/// Current size of the matrix
size_t size() const { return N;}
/// Returns the i-th values of x
xy_type const & get_x(size_t i) const { return x_values[row_num[i]];}
/// Returns the j-th values of y
xy_type const & get_y(size_t j) const { return y_values[col_num[j]];}
/** det M of the current state of the matrix. */
value_type determinant() const {return sign*det;}
/** Returns M^{-1}(i,j) */
value_type inverse_matrix(size_t i,size_t j) const {return mat_inv(col_num[i],row_num[j]);} // warning : need to invert the 2 permutations.
/// Returns the inverse matrix. Warning : this is slow, since it create a new copy, and reorder the lines/cols
matrix_view_type inverse_matrix() const {
matrix_type res(N,N);
for (size_t i=0; i
friend void foreach(det_manip const & d, LambdaType const & f) {
//for (size_t i=0; i=0); assert(j>=0);
if (N==Nmax) reserve(2*Nmax);
last_try = 1;
w1.i=i; w1.j=j; w1.x=x; w1.y = y;
// treat empty matrix separately
if (N==0) { newdet = f(x,y); newsign = 1; return newdet; }
// I add the row and col and the end. If the move is rejected,
// no effect since N will not be changed : Minv(i,j) for i,j>=N has no meaning.
for (size_t k= 0; k< N; k++) {
w1.B(k) = f(x_values[k],y);
w1.C(k) = f(x, y_values[k]);
}
range R(0,N);
w1.MB(R) = mat_inv(R,R) * w1.B(R);// CHANGE
w1.ksi = f(x,y) - arrays::dot( w1.C(R) , w1.MB(R) );
newdet = det*w1.ksi;
newsign = ((i + j)%2==0 ? sign : -sign); // since N-i0 + N-j0 = i0+j0 [2]
return (newdet/det)*(newsign*sign); // sign is unity, hence 1/sign == sign
}
//------------------------------------------------------------------------------------------
private :
void complete_insert () {
// store the new value of x,y. They are seen through the same permutations as rows and cols resp.
x_values.push_back(w1.x); y_values.push_back(w1.y);
row_num.push_back(0); col_num.push_back(0);
// special empty case again
if (N==0) { N=1; mat_inv(0,0) = 1/newdet; return; }
range R1(0,N);
w1.MC(R1) = mat_inv(R1,R1).transpose() * w1.C(R1); //CHANGE
w1.MC(N) = -1;
w1.MB(N) = -1;
N++;
// keep the real position of the row/col
// since we insert a col/row, we have first to push the col at the right
// and then say that col w1.i is stored in N, the last col.
// same for rows
for (int_type i =N-2; i>=int_type(w1.i); i--) row_num[i+1]= row_num[i];
row_num[w1.i] = N-1;
for (int_type i =N-2; i>=int_type(w1.j); i--) col_num[i+1]= col_num[i];
col_num[w1.j] = N-1;
// Minv is ok, we need to complete
w1.ksi = 1/w1.ksi;
// compute the change to the inverse
// M += w1.ksi w1.MB w1.MC with BLAS. first put the 0
range R(0,N);
mat_inv(R,N-1) = 0;
mat_inv(N-1,R) = 0;
mat_inv(R,R) += triqs::arrays::a_x_ty(w1.ksi, w1.MB(R) ,w1.MC(R)) ;//mat_inv(R,R) += w1.ksi* w1.MB(R) * w1.MC(R)// CHANGE
}
public :
//------------------------------------------------------------------------------------------
/**
* Double Insert operation at colum j0,j1 and row i0,i1.
*
* The operation consists in adding :
* * a column f(x_i, y_{j0})
* * and a row f(x_{i0}, x_j)
* The new colum/row will be at col j0, row i0.
*
* 0 <= i0,i1,j0,j1 <= N+1, where N is the current size of the matrix.
* Returns the ratio of det Minv_new / det Minv.
* This routine does NOT make any modification. It has to be completed with complete_operation().
*/
value_type try_insert2(size_t i0, size_t i1, size_t j0, size_t j1, xy_type const & x0, xy_type const & x1, xy_type const & y0, xy_type const & y1) {
// check input and store it for complete_operation
assert(i0!=i1); assert(j0!=j1);assert(i0<=N); assert(j0<=N); assert(i0>=0); assert(j0>=0);
assert(i1<=N+1); assert(j1<=N+1); assert(i1>=0); assert(j1>=0);
if (N >= Nmax) reserve(2*Nmax); // check this resize ... we add 2 lines
last_try = 10;
w2.i[0]=i0;w2.i[1]=i1; w2.j[0]=j0;w2.j[1]=j1;
w2.x[0] = x0;w2.y[0] = y0; w2.x[1] = x1;w2.y[1] = y1;
// w1.ksi = Delta(x_values,y_values) - Cw.MB using BLAS
w2.ksi(0,0) = f(x0,y0);
w2.ksi(0,1) = f(x0,y1);
w2.ksi(1,0) = f(x1,y0);
w2.ksi(1,1) = f(x1,y1);
// treat empty matrix separately
if (N==0) {
newdet = w2.det_ksi();
newsign = 1;
return newdet;
}
// I add the rows and cols and the end. If the move is rejected,
// no effect since N will not be changed : inv_mat(i,j) for i,j>=N has no meaning.
for (size_t k= 0; k< N; k++) {
w2.B(k,0) = f(x_values[k],y0);
w2.B(k,1) = f(x_values[k],y1);
w2.C(0,k) = f(x0, y_values[k]);
w2.C(1,k) = f(x1, y_values[k]);
}
range R(0,N), R2(0,2);
w2.MB(R,R2) = mat_inv(R,R) * w2.B(R,R2); // CHANGE
w2.ksi -= w2.C (R2, R) * w2.MB(R, R2); // CHANGE
newdet = det * w2.det_ksi();
newsign = ((i0 + j0 + i1 + j1)%2==0 ? sign : -sign); // since N-i0 + N-j0 + N + 1 -i1 + N+1 -j1 = i0+j0 [2]
return (newdet/det)*(newsign*sign); // sign is unity, hence 1/sign == sign
}
//------------------------------------------------------------------------------------------
private:
void complete_insert2 () {
// store the new value of x,y. They are seen through the same permutations as rows and cols resp.
for (int k=0; k<2; ++k) {
x_values.push_back(w2.x[k]); y_values.push_back(w2.y[k]);
row_num.push_back(0); col_num.push_back(0);
}
range R2(0,2);
if (N==0) {N=2; mat_inv(R2,R2)=inverse(w2.ksi); row_num[w2.i[1]]=1; col_num[w2.j[1]]=1; return;}
range Ri(0,N);
w2.MC(R2,Ri) = w2.C(R2,Ri) * mat_inv(Ri,Ri);// CHANGE
w2.MC(R2, range(N, N+2) ) = -1; // identity matrix
w2.MB(range(N,N+2), R2 ) = -1; // identity matrix !
// keep the real position of the row/col
// since we insert a col/row, we have first to push the col at the right
// and then say that col w2.i[0] is stored in N, the last col.
// same for rows
for (int k =0; k<2; ++k) {
N++;
for (int_type i =N-2; i>=int_type(w2.i[k]); i--) row_num[i+1]= row_num[i];
row_num[w2.i[k]] = N-1;
for (int_type i =N-2; i>=int_type(w2.j[k]); i--) col_num[i+1]= col_num[i];
col_num[w2.j[k]] = N-1;
}
w2.ksi = inverse (w2.ksi);
range R(0,N);
mat_inv(R,range(N-2,N)) = 0;
mat_inv(range(N-2,N),R) = 0;
mat_inv(R,R) += w2.MB(R,R2) * (w2.ksi * w2.MC(R2,R)); // CHANGE
}
public:
//------------------------------------------------------------------------------------------
/**
* Consider the removal the colj0 and row i0 from the matrix.
*
* Returns the ratio of det Minv_new / det Minv.
* This routine does NOT make any modification. It has to be completed with complete_operation().
*/
value_type try_remove(size_t i, size_t j){
assert(i=0); assert(j>=0);
w1.i=i;w1.j=j;last_try = 2;
w1.jreal = col_num[w1.j];
w1.ireal = row_num[w1.i];
// compute the newdet
// first we resolve the w1.ireal,w1.jreal, with the permutation of the Minv, then we pick up what
// will become the 'corner' coefficient, if the move is accepted, after the exchange of row and col.
w1.ksi = mat_inv(w1.jreal,w1.ireal);
newdet = det*w1.ksi;
newsign = ((i + j)%2==0 ? sign : -sign);
return (newdet/det)*(newsign*sign); // sign is unity, hence 1/sign == sign
}
//------------------------------------------------------------------------------------------
private:
void complete_remove() {
if (N==1) { clear(); return; }
// repack the matrix inv_mat
// swap the rows w1.ireal and N, w1.jreal and N in inv_mat
// Remember that for M row/col is interchanged by inversion, transposition.
{
range R(0,N);
if (w1.jreal !=N-1){
arrays::deep_swap( mat_inv(w1.jreal,R), mat_inv(N-1,R));
y_values[w1.jreal] = y_values[N-1];
}
if (w1.ireal !=N-1){
arrays::deep_swap (mat_inv(R,w1.ireal), mat_inv(R,N-1));
x_values[w1.ireal] = x_values[N-1];
}
}
N--;
// M <- a - d^-1 b c with BLAS
w1.ksi = - 1/mat_inv(N,N);
range R(0,N);
mat_inv(R,R) += arrays::a_x_ty(w1.ksi,mat_inv(R,N),mat_inv(N,R));
// modify the permutations
for (size_t k =w1.i; k=2); assert(i0!=i1); assert(j0!=j1);
assert(i0=0); assert(j0>=0);
assert(i1=0); assert(j1>=0);
last_try =11;
w2.i[0]=std::min(i0,i1);
w2.i[1]=std::max(i0,i1);
w2.j[0]=std::min(j0,j1);
w2.j[1]=std::max(j0,j1);
w2.ireal[0] = row_num[w2.i[0]];
w2.ireal[1] = row_num[w2.i[1]];
w2.jreal[0] = col_num[w2.j[0]];
w2.jreal[1] = col_num[w2.j[1]];
// compute the newdet
w2.ksi(0,0) = mat_inv(w2.jreal[0],w2.ireal[0]);
w2.ksi(1,0) = mat_inv(w2.jreal[1],w2.ireal[0]);
w2.ksi(0,1) = mat_inv(w2.jreal[0],w2.ireal[1]);
w2.ksi(1,1) = mat_inv(w2.jreal[1],w2.ireal[1]);
newdet = det * w2.det_ksi();
newsign = ((i0 + j0+ i1 + j1)%2==0 ? sign : -sign);
return (newdet/det)*(newsign*sign); // sign is unity, hence 1/sign == sign
}
//------------------------------------------------------------------------------------------
private:
void complete_remove2() {
if (N==2) { clear(); return;} // put the sign to 1 also .... Change complete_remove...
size_t i_real_max =std::max(w2.ireal[0],w2.ireal[1]);
size_t i_real_min =std::min(w2.ireal[0],w2.ireal[1]);
size_t j_real_max =std::max(w2.jreal[0],w2.jreal[1]);
size_t j_real_min =std::min(w2.jreal[0],w2.jreal[1]);
range R(0,N);
if (j_real_max != N-1) {
arrays::deep_swap( mat_inv(j_real_max,R), mat_inv(N-1,R));
y_values[ j_real_max ] = y_values[N-1];
}
if (j_real_min != N-2) {
arrays::deep_swap( mat_inv(j_real_min,R), mat_inv(N-2,R));
y_values[ j_real_min ] = y_values[N-2];
}
if (i_real_max != N-1) {
arrays::deep_swap (mat_inv(R,i_real_max), mat_inv(R,N-1));
x_values[ i_real_max ] = x_values[N-1];
}
if (i_real_min != N-2) {
arrays::deep_swap (mat_inv(R,i_real_min), mat_inv(R,N-2));
x_values[ i_real_min ] = x_values[N-2];
}
N -= 2;
// M <- a - d^-1 b c with BLAS
range Rn(0,N), Rl(N,N+2);
//w2.ksi = mat_inv(Rl,Rl);
//w2.ksi = inverse( w2.ksi);
w2.ksi = inverse( mat_inv(Rl,Rl));
// write explicitely the second product on ksi for speed ?
mat_inv(Rn,Rn) -= mat_inv(Rn,Rl) * (w2.ksi * mat_inv(Rl,Rn)); // CHANGE
// modify the permutations
for (size_t k =w2.i[0]; k=0);
w1.j=j;last_try = 3;
w1.jreal = col_num[j];
w1.y = y;
// Compute the col B.
for (size_t i= 0; i=0);
w1.i=i;last_try = 4;
w1.ireal = row_num[i];
w1.x = x;
// Compute the col B.
for (size_t i= 0; i n_opts_max_before_check) { check_mat_inv(); n_opts=0;}
}
///
enum RollDirection {None,Up, Down,Left,Right};
/**
* "Cyclic Rolling" of the determinant.
*
* Right : Move the Nth col to the first col cyclically.
* Left : Move the first col to the Nth, cyclically.
* Up : Move the first row to the Nth, cyclically.
* Down : Move the Nth row to the first row cyclically.
*
* Returns -1 is the roll changes the sign of the det, 1 otherwise
* NB : this routine is not a try_xxx : it DOES make the modification and does not need to be completed...
* WHY is it like this ???? : try_roll : return det +1/-1.
*/
int roll_matrix(RollDirection roll) {
size_t tmp;
const int_type NN=N;
switch (roll) {
case(None) :
return 1;
case(Down) :
tmp = row_num[N-1];
for (int_type i =NN-2; i>=0; i--) row_num[i+1]= row_num[i];
row_num[0] = tmp;
break;
case(Up) :
tmp = row_num[0];
for (int_type i =0; i=0; i--) col_num[i+1]= col_num[i];
col_num[0] = tmp;
break;
case(Left):
tmp = col_num[0];
for (int_type i =0; i