2064 lines
45 KiB
C++
2064 lines
45 KiB
C++
/*
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LA: linear algebra C++ interface library
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Copyright (C) 2008 Jiri Pittner <jiri.pittner@jh-inst.cas.cz> or <jiri@pittnerovi.com>
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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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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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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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// g++ -D _GLIBCPP_NO_TEMPLATE_EXPORT -g testblas.cc testblas2.cc nrutil_modif.cc -L/usr/local/lib/atlas -lstrassen -lf77blas -lcblas -latlas -ltraceback -lbfd -liberty
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#include <time.h>
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#include "la.h"
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#include "vecmat3.h"
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#include "quaternion.h"
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#include "permutation.h"
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using namespace std;
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using namespace LA_Vecmat3;
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using namespace LA_Quaternion;
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using namespace LA;
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extern void test(const NRVec<double> &x);
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double ad;
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void f1(const double *c)
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{
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ad=*c;
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}
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void f2(double *c)
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{
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*c=ad;
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}
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inline int randind(const int n)
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{
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return int(random()/(1.+RAND_MAX)*n);
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}
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complex<double> mycident (const complex<double>&x) {return x;}
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int main()
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{
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#ifdef USE_TRACEBACK
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sigtraceback(SIGSEGV,1);
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sigtraceback(SIGABRT,1);
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sigtraceback(SIGBUS,1);
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sigtraceback(SIGFPE,1);
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#endif
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NRVec<double> x(1.,10);
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NRVec<double> y(2.,10);
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NRVec<double> z(-2.,10);
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//cout.setf(ios::scientific);
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cc:cout.setf(ios::fixed);
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cout.precision(10);
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cin.exceptions ( ifstream::eofbit | ifstream::failbit | ifstream::badbit );
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if(0) test(x);
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y.axpy(3,x);
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y+=z;
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/*
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cout <<y;
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NRVec<double> a(x);
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NRVec<double> b;
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b|=x;
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NRVec<double> c;
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c=a;
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y =10. *y ;
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int i;
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for(i=0;i<y.size();i++) cout <<y[i] <<" ";
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cout <<"\n";
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cout << y*z <<"\n";
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z|=x;
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z[1]=5;
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cout <<"zunit= "<<z.unitvector()<<"\n";
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cout <<"z= "<<z<<"\n";
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test(x);
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x = x*5;
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cout <<"x= "<<x<<"\n";
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cout <<"y= "<<y<<"\n";
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NRVec<double> u;
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u=x+y;
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cout <<"u= "<<u<<"\n";
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NRMat<double> aa(0.,3,3);
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aa[0][0]=aa[1][1]=aa(2,2)=2.;
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NRMat<double> bb(aa);
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double *p;
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aa.copyonwrite(); p= &aa[2][2];
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*p=3.;
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bb.copyonwrite(); bb(0,2)=1.;
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cout << "aa= " <<aa <<"\n";
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cout << "bb= " <<bb <<"\n";
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cout <<"aa trace "<<aa.trace() <<"\n";
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cout << "bbt= " <<bb.transpose() <<"\n";
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NRMat<double> cc=aa & bb;
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cout << "aa o+ bb= " << cc <<"\n";
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cout << cc.rsum() <<"\n";
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cout << cc.csum() <<"\n";
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NRVec<double>w(3);
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w[0]=1; w[1]=2;w[2]=3;
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NRVec<double> v(0.,3);
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v.gemv(0.,bb,'n',1.,w);
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cout << " v= " <<v <<"\n";
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v.gemv(0.,bb,'t',1.,w);
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cout << " v= " <<v <<"\n";
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*/
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/*
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const int n=6000;
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NRMat<double> bb(1.,n,n);
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for(int i=0;i<n;i++) for(int j=0;j<n;j++) bb[i][j]=2.;
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for(int i=0;i<n;i++) for(int j=0;j<i;j++) {double t; t=bb[i][j] +bb[j][j]; bb[i][j]=t;bb[j][i]=t;}
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*/
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/*
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NRMat<double> amat,bmat,cmat;
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cin >>amat;
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cin >>bmat;
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cmat=amat*bmat;
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cout<<cmat;
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cmat.copyonwrite(); cmat[0][0]=0;
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NRMat<double> amat(1.,2,2);
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NRMat<double> bmat(amat);
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NRMat<double> dmat(amat);
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//NRMat<double> cmat; cmat=bmat*2.;
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NRMat<double> cmat(bmat*2); //more efficient
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dmat.copyonwrite(); dmat[0][0]=0;
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cout<<amat;
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cout<<bmat;
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cout<<cmat;
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cout<<dmat;
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NRMat<double> amat;
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NRVec<double> avec;
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cin >>amat;
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cin >>avec;
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cout << amat*avec;
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cout << avec*amat;
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NRVec<double> avec(0.,10);
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f1(avec);
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f2(avec);
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NRVec<double> uu(3);
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uu[0]=1; uu[1]=2; uu[2]=3;
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cout << uu << (uu|uu) <<"\n";
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NRSMat<double> sa(0.,3);
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sa(0,0)=1; sa(0,2)=5; sa(2,2)=10;sa(1,0)=2;sa(1,1)=3; sa(2,1)=-1;
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NRSMat<double> sb(0.,3);
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sb(0,0)=-2; sb(0,2)=1; sb(2,2)=2;sb(1,0)=-1;sb(1,1)=7; sb(2,1)=3;
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cout << "symetr\n" <<sa << -sa <<"\n";
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cout << "symetr\n" <<sb <<"\n";
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cout << "sa*sb\n" << sa*sb <<"\n";
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cout << "sb*sa\n" << sb*sa <<"\n";
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NRMat<double> m10(10.,3,3);
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cout << "10 + sa" << m10 + sa <<"\n";
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*/
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/*
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const int dim=256;
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NRMat<double> big1(dim,dim),big2(dim,dim),big3;
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for(int i=0;i<dim;i++)
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for(int j=0;j<dim;j++)
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{
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big1[i][j]=i*i+j*j*j-3*j;
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big2[i][j]=i*i/(j+1)+j*j-3*j;
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}
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double t=clock()/((double) (CLOCKS_PER_SEC));
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big3= big1*big2;
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cout <<" big1*big2 "<<big3[0][0]<<" time "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
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*/
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#ifndef NO_STRASSEN
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if(0)
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{
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NRMat<double> atest, btest,ctest;
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{
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int cc,c1,c2,c3;
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cin >>cc>>c1>>c2>>c3;
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atest.s_cutoff(cc,c1,c2,c3);
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}
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cin>>atest;
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cin>>btest;
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NRMat<double> dtest(atest.nrows(),btest.ncols());
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dtest.gemm(0., atest, 't', btest, 'n', 1.);
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cout << dtest;
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NRMat<double> etest(atest.nrows(),btest.ncols());
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etest.strassen(0., atest, 't', btest, 'n', 1.);
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cout << etest;
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}
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if(0)
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{
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int dim;
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cin >>dim;
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NRMat<double> big1(dim,dim),big2(dim,dim),big3,big4(dim,dim);
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for(int i=0;i<dim;i++)
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for(int j=0;j<dim;j++)
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{
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big1[i][j]=i*i+j*j*j-3*j;
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big2[i][j]=i*i/(j+1)+j*j-3*j;
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}
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double t=clock()/((double) (CLOCKS_PER_SEC));
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big3= big1*big2;
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cout <<" classical big1*big2 "<<big3[0][0]<<" time "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
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for (int c=64; c<=512;c+=64)
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{
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big4.s_cutoff(c,c,c,c);
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t=clock()/((double) (CLOCKS_PER_SEC));
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big4.strassen(0., big1, 'n', big2, 'n', 1.);
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cout <<"cutoff "<<c<<" big1*big2 "<<big4[0][0]<<" time "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
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}
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}
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#endif
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if(0)
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{
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NRMat<double> a(3,3),b;
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NRVec<double> v(3);
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for(int i=0;i<3;i++) for(int j=0;j<3;j++) { a[i][j]= i*i+j; v[i]=10-i;}
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b=a;
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b*= sin(1.)+1;
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cout << a <<v;
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a.diagmultl(v);
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cout << a;
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b.diagmultr(v);
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cout << b;
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}
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if(0)
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{
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NRMat<double> a(3,3),b;
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NRVec<double> v(10);
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v[0]=2;v[1]=3;v[2]=1;v[3]=-3;v[4]=2;v[5]=-1;v[6]=3;v[7]=-2;v[8]=1;v[9]=1;
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for(int i=0;i<3;i++) for(int j=0;j<3;j++) { a[i][j]= (i+j)/10.; }
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cout <<a;
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cout << a.norm() <<"\n";
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b=a*a;
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cout << b.norm() <<"\n";
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cout << exp(a);
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cout << exp(a.norm()) <<"\n";
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cout << ipow(a,3);
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cout<<ipow(a,11);
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cout <<commutator(a,b);
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}
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if(0)
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{
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NRMat<double> a(3,3);
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for(int i=0;i<3;i++) for(int j=0;j<3;j++) { a[i][j]= (i+j)/10.; }
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NRSMat<double> b(a);
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NRMat<double> c(b);
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cout <<a;
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cout <<b;
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cout <<c;
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}
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if(0)
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{
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NRMat<double> a(3,3);
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a[0][0]=1; a[0][1]=2;a[0][2]=3;
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a[1][0]=4; a[1][1]=-5;a[1][2]=7;
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a[2][0]=-3;a[2][1]=10;a[2][2]=2;
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NRMat<double> b(2,3);
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b[0][0]=1;b[0][1]=2;b[0][2]=3;
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b[1][0]=2;b[1][1]=4;b[1][2]=6;
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cout <<a;
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cout <<b;
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linear_solve(a,&b);
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cout <<a;
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cout <<b;
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}
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if(0)
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{
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NRMat<double> a(3,3);
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for(int i=0;i<3;i++) for(int j=0;j<3;j++) { a[i][j]= (i+j)/10.; }
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NRVec<double> b(3);
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cout <<a;
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diagonalize(a,b);
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cout <<a;
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cout <<b;
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}
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if(0)
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{
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NRSMat<double> a(3);
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NRMat<double>v(3,3);
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for(int i=0;i<3;i++) for(int j=0;j<3;j++) { a(i,j)= (i+j)/10.; }
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NRVec<double> b(3);
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cout <<a;
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NRMat<double>c=(NRMat<double>)a; //nebo NRMat<double>c(a);
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NRMat<double>d=exp(c);
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diagonalize(a,b,&v);
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cout <<b;
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cout <<v;
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cout <<d;
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diagonalize(d,b);
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cout <<b;
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cout <<d;
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}
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if(0)
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{
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NRMat<double> a;
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cin >>a ;
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NRMat<double> abak=a;
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NRMat<double> u(a.nrows(),a.nrows()),v(a.ncols(),a.ncols());
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NRVec<double>s(a.ncols()<a.nrows()?a.ncols():a.nrows());
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singular_decomposition(a,&u,s,&v,0);
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cout <<u;
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NRMat<double> sdiag(0., u.ncols(),v.nrows());
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sdiag.diagonalset(s);
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cout <<sdiag;
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cout <<v;
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cout << "Error "<<(u*sdiag*v-abak).norm()<<endl;
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}
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if(0)
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{
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NRMat<complex<double> > a;
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cin >>a ;
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NRMat<complex<double> > abak=a;
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NRMat<complex<double> > u(a.nrows(),a.nrows()),v(a.ncols(),a.ncols());
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NRVec<double>s(a.ncols()<a.nrows()?a.ncols():a.nrows());
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singular_decomposition(a,&u,s,&v,0);
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cout <<u;
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NRMat<complex<double> > sdiag(0., u.ncols(),v.nrows());
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NRVec<complex<double> > ss = s;
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sdiag.diagonalset(ss);
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cout <<sdiag;
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cout <<v;
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cout << "Error "<<(u*sdiag*v-abak).norm()<<endl;
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}
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if(0)
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{
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//diagonalize a general matrix and reconstruct it back; assume real eigenvalues
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//double aa[]={1,2,3,4,-5,7,-3,10,2};
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//NRMat<double> a(aa,3,3);
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NRMat<double> a;
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cin >>a;
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cout <<a ;
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int n=a.nrows();
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NRMat<double> u(n,n),v(n,n);
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NRVec<double>wr(n),wi(n);
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gdiagonalize(a,wr,wi,&u,&v,0);
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cout <<u;
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cout <<wr;
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cout <<wi;
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cout <<v;
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NRVec<double>z=diagofproduct(u,v,1);
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for(int i=0;i<a.nrows();++i) wr[i]/=z[i];//account for normalization of eigenvectors
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u.diagmultl(wr);
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v.transposeme();
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cout <<v*u;
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}
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if(0)
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{
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//diagonalize a general matrix and reconstruct it back; allow complex eigenvalues
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NRMat<double> a;
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cin >>a;
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cout <<a ;
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int n=a.nrows();
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NRMat<complex<double> > u(n,n),v(n,n);
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NRVec<complex<double> >w(n);
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gdiagonalize(a,w,&u,&v);
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cout <<u;
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cout <<w;
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cout <<v;
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NRVec<complex<double> >z=diagofproduct(u,v,1,1);
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//NRMat<complex<double> > zz=u*v.transpose(1);
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cout <<z;
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//cout <<zz;
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for(int i=0;i<a.nrows();++i) w[i]/=z[i];//account for normalization of eigenvectors
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u.diagmultl(w);
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cout <<v.transpose(1)*u;
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}
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if(0)
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{
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NRMat<double> a;
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cin >>a;
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int n=a.nrows();
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NRMat<complex<double> > u(n,n),v(n,n);
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NRVec<complex<double> >w(n);
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gdiagonalize(a,w,&u,&v,0,n,0,1);
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cout <<u;
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cout <<w;
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cout <<v;
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NRVec<complex<double> >z=diagofproduct(u,v,1,1);
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cout <<z;
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for(int i=0;i<a.nrows();++i) w[i]/=z[i];//account for normalization of eigenvectors
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cout <<u*v.transpose(1); //check biorthonormality
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u.diagmultl(w);
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cout <<v.transpose(1)*u;
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}
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if(0)
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{
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NRMat<complex<double> > a;
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cin >>a;
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int n=a.nrows();
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NRMat<complex<double> > u(n,n),v(n,n);
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NRVec<complex<double> >w(n);
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gdiagonalize(a,w,&u,&v);
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//gdiagonalize(a,w,&u,&v,0,n,0,1);
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cout <<u;
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cout <<w;
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cout <<v;
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NRVec<complex<double> >z=diagofproduct(u,v,1,1);
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cout <<z;
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for(int i=0;i<a.nrows();++i) w[i]/=z[i];//account for normalization of eigenvectors
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cout <<u*v.transpose(1); //check biorthonormality
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u.diagmultl(w);
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cout <<v.transpose(1)*u;
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}
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if(0)
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{
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SparseMat<double> a(4,4);
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NRVec<double> v(4);
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v[0]=1;v[1]=2;v[2]=3;v[3]=4;
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a=1.;
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a.copyonwrite();
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a.add(3,0,.5);
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a.add(0,2,.2);
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a.add(2,1,.1);
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a.add(3,3,1.);
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a.add(1,1,-1.);
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|
SparseMat<double> c(a);
|
|
c*=10.;
|
|
cout <<a;
|
|
a.simplify();
|
|
cout <<a;
|
|
cout <<c;
|
|
NRMat<double>b(c);
|
|
cout <<b;
|
|
cout << b*v;
|
|
cout <<c*v;
|
|
cout <<v*b;
|
|
cout <<v*c;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
SparseMat<double> a(4,4),b(4,4);
|
|
a=1.;
|
|
a.copyonwrite();
|
|
a.add(3,0,.5);
|
|
b.add(0,2,.2);
|
|
b.add(2,1,.1);
|
|
b.add(3,3,1.);
|
|
b.add(1,1,-1.);
|
|
SparseMat<double>c=a+b;
|
|
cout <<c;
|
|
a.join(b);
|
|
cout<<a;
|
|
cout<<b;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
SparseMat<double> a(4,4),b(4,4);
|
|
a=0.; b=2;
|
|
a.add(3,0,.5);
|
|
a.add(0,2,.2);
|
|
a.add(1,1,1);
|
|
a.add(1,0,.2);
|
|
b.add(2,1,.1);
|
|
b.add(3,3,1.);
|
|
b.add(1,1,-1.);
|
|
NRMat<double> aa(a),bb(b);
|
|
SparseMat<double>c;
|
|
NRMat<double>cc;
|
|
//cout << NRMat<double>(c);
|
|
//cout <<cc;
|
|
//cout <<"norms "<<c.norm()<<" " <<cc.norm()<<endl;
|
|
cout <<"original matrix \n"<<aa;
|
|
cout <<(cc=exp(aa));
|
|
c=exp(a);
|
|
cout <<NRMat<double>(c);
|
|
cout <<"norms2 "<<c.norm()<<" " <<cc.norm()<<endl;
|
|
}
|
|
|
|
#define sparsity (n/4)
|
|
if(0)
|
|
{
|
|
for(int n=8; n<=1024*1024;n+=n)
|
|
{
|
|
SparseMat<double> aa(n,n);
|
|
cout << "\n\n\ntiming for size "<<n<<endl;
|
|
if(n<=512) {
|
|
NRMat<double> a(0.,n,n);
|
|
for(int i=0; i<sparsity;i++) a(randind(n),randind(n))=random()/(1.+RAND_MAX);
|
|
double t0=clock()/((double) (CLOCKS_PER_SEC));
|
|
//cout <<a;
|
|
NRMat<double> b(exp(a));
|
|
//cout <<b;
|
|
cout <<"dense norm "<<b.norm() <<"\n";
|
|
cout << "test commutator " <<commutator(a,b).norm() <<endl;
|
|
double t1=clock()/((double) (CLOCKS_PER_SEC));
|
|
cout << "dense time " <<n<<' '<< t1-t0 <<endl;
|
|
aa=SparseMat<double>(a);
|
|
}
|
|
else
|
|
{
|
|
for(int i=0; i<sparsity;i++) aa.add(randind(n),randind(n),random()/(1.+RAND_MAX));
|
|
}
|
|
//cout <<aa;
|
|
double t2=clock()/((double) (CLOCKS_PER_SEC));
|
|
SparseMat<double> bb(exp(aa));
|
|
//cout <<bb;
|
|
cout <<"sparse norm "<<bb.norm() <<"\n";
|
|
cout << "test commutator " <<commutator(aa,bb).norm() <<endl;
|
|
double t3=clock()/((double) (CLOCKS_PER_SEC));
|
|
cout <<"sparse length "<<bb.length()<<"\n";
|
|
cout << "sparse time "<<n<<' ' << t3-t2 <<endl;
|
|
}
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
int n;
|
|
cin>>n;
|
|
SparseMat<double> aa(n,n);
|
|
for(int i=0; i<sparsity;i++) aa.add(randind(n),randind(n),random()/(1.+RAND_MAX));
|
|
SparseMat<double> bb=exp(aa);
|
|
NRVec<double> v(n);
|
|
for(int i=0; i<n;++i) v[i]=random()/(1.+RAND_MAX);
|
|
NRVec<double> res1=bb*v;
|
|
NRVec<double> res2=exptimes(aa,v);
|
|
cout <<"difference = "<<(res1-res2).norm()<<endl;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
int n,k,m;
|
|
cin >>n>>k>>m;
|
|
{
|
|
NRMat<double> a(n,k),b(k,m),c(n,m),d(n,m);
|
|
for(int i=0;i<n;++i) for(int j=0;j<k;++j) a(i,j)= random()/(1.+RAND_MAX);
|
|
for(int i=0;i<k;++i) for(int j=0;j<m;++j) b(i,j)= random()/(1.+RAND_MAX);
|
|
c.gemm(0., a, 'n', b, 'n', .6);
|
|
SparseMat<double> aa(a);
|
|
d.gemm(0., aa, 'n', b, 'n', .6);
|
|
cout<<c<<d;
|
|
cout <<"test error = "<<(c-d).norm()<<endl;
|
|
}
|
|
{
|
|
NRMat<double> a(k,n),b(k,m),c(n,m),d(n,m);
|
|
for(int i=0;i<k;++i) for(int j=0;j<n;++j) a(i,j)= random()/(1.+RAND_MAX);
|
|
for(int i=0;i<k;++i) for(int j=0;j<m;++j) b(i,j)= random()/(1.+RAND_MAX);
|
|
c.gemm(0., a, 't', b, 'n', .7);
|
|
SparseMat<double> aa(a);
|
|
d.gemm(0., aa, 't', b, 'n', .7);
|
|
cout<<c<<d;
|
|
cout <<"test error = "<<(c-d).norm()<<endl;
|
|
}
|
|
{
|
|
NRMat<double> a(n,k),b(m,k),c(n,m),d(n,m);
|
|
for(int i=0;i<n;++i) for(int j=0;j<k;++j) a(i,j)= random()/(1.+RAND_MAX);
|
|
for(int i=0;i<m;++i) for(int j=0;j<k;++j) b(i,j)= random()/(1.+RAND_MAX);
|
|
c.gemm(0., a, 'n', b, 't', .8);
|
|
SparseMat<double> aa(a);
|
|
d.gemm(0., aa, 'n', b, 't', .8);
|
|
cout<<c<<d;
|
|
cout <<"test error = "<<(c-d).norm()<<endl;
|
|
}
|
|
{
|
|
NRMat<double> a(k,n),b(m,k),c(n,m),d(n,m);
|
|
for(int i=0;i<k;++i) for(int j=0;j<n;++j) a(i,j)= random()/(1.+RAND_MAX);
|
|
for(int i=0;i<m;++i) for(int j=0;j<k;++j) b(i,j)= random()/(1.+RAND_MAX);
|
|
c.gemm(0., a, 't', b, 't', .9);
|
|
SparseMat<double> aa(a);
|
|
d.gemm(0., aa, 't', b, 't', .9);
|
|
cout<<c<<d;
|
|
cout <<"test error = "<<(c-d).norm()<<endl;
|
|
}
|
|
|
|
}
|
|
|
|
|
|
if(0)
|
|
{
|
|
SparseMat<double> a(4,4),b(4,4),d;
|
|
a=0.; b=2;
|
|
a.add(3,0,.5);
|
|
a.add(0,2,.2);
|
|
a.add(1,1,1);
|
|
a.add(1,0,.2);
|
|
b.add(2,1,.1);
|
|
b.add(3,3,1.);
|
|
b.add(1,1,-1.);
|
|
NRMat<double> aa(a),bb(b),dd;
|
|
SparseMat<double>c;
|
|
NRMat<double>cc;
|
|
|
|
c=commutator(a,b);
|
|
cc=commutator(aa,bb);
|
|
|
|
cout <<cc;
|
|
cout <<NRMat<double>(c);
|
|
cout <<"norms2 "<<c.norm()<<" " <<cc.norm()<<endl;
|
|
}
|
|
|
|
/*
|
|
NRVec<double> v(10.,10);
|
|
v+= 5.;
|
|
cout <<v;
|
|
*/
|
|
if(0)
|
|
{
|
|
int n;
|
|
cin >>n;
|
|
NRMat<double> a(n,n);
|
|
for(int i=0;i<n;++i) for(int j=0;j<=i;++j)
|
|
{
|
|
a(i,j)= random()/(1.+RAND_MAX);
|
|
a(j,i)= random()/(1.+RAND_MAX);
|
|
}
|
|
NRMat<double> b; b|=a;
|
|
NRVec<double> er(n),ei(n);
|
|
NRMat<double> vr(n,n),vl(n,n);
|
|
gdiagonalize(b,er,ei,&vl,&vr,1,0,1,1);
|
|
cout <<er<<ei;
|
|
cout <<"left eivec\n"<<vl <<"right eivec\n"<<vr;
|
|
cout <<"test orthogonality\n" << vl.transpose() * vr;
|
|
NRMat<double> u=exp(a*.1);
|
|
gdiagonalize(u,er,ei,&vl,&vr,1,0,1,1);
|
|
cout <<er<<ei;
|
|
cout <<"left eivec\n"<<vl <<"right eivec\n"<<vr;
|
|
cout <<"test orthogonality\n" << vl.transpose() * vr;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
int k;
|
|
cin >>k;
|
|
int n=2*k;
|
|
NRMat<double> a(n,n);
|
|
//matrix with known spectrum
|
|
for(int i=0;i<n;++i)
|
|
{
|
|
for(int j=0;j<k;++j) a(i,j)=j+1.+k*k-(i==j?0.:i+1.);
|
|
for(int j=k; j<n; ++j) a(i,j)=i-j-k*k+(i==j?i+1.:0.);
|
|
}
|
|
NRVec<double> er(n),ei(n);
|
|
NRMat<double> vr(n,n),vl(n,n);
|
|
cout <<"input matrix\n"<<a;
|
|
gdiagonalize(a,er,ei,&vl,&vr,1,0,1);
|
|
cout <<er<<ei;
|
|
cout <<"left eivec\n"<<vl <<"right eivec\n"<<vr;
|
|
cout <<"test orthogonality\n" << vl.transpose() * vr;
|
|
}
|
|
|
|
|
|
if(0)
|
|
{
|
|
int n;
|
|
cin>>n;
|
|
NRMat<double> a(n,n);
|
|
for(int i=0;i<n;++i) for(int j=0;j<i;++j)
|
|
{
|
|
a(i,j)= random()/(1.+RAND_MAX);
|
|
a(j,i)= -a(i,j);
|
|
}
|
|
cout <<"a matrix \n"<<a;
|
|
cout<<"EXP\n";
|
|
NRMat<double> b=exp0(a);
|
|
cout <<"b=exp(a) matrix\n"<<b;
|
|
|
|
cout <<"LOG\n";
|
|
NRMat<double> c=log(b); //matrixfunction(a,&mycident,1);
|
|
cout <<"c=log(exp(a))\n"<<c <<"error: "<<(c-a).norm()<<endl;
|
|
cout <<"EXP-MY\n";
|
|
NRMat<double> e=exp(c);
|
|
cout <<"e=exp(c)\n"<<e;
|
|
cout<<"error2 = "<<(e-b).norm()<<endl;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
int n;
|
|
double f;
|
|
cin>>n >>f ;
|
|
NRMat<double> a(n,n);
|
|
NRVec<double>u(n),v,w;
|
|
for(int i=0;i<n;++i)
|
|
{
|
|
u[i]=f*random()/(1.+RAND_MAX);
|
|
for(int j=0;j<n;++j)
|
|
a(i,j)= f*random()/(1.+RAND_MAX);
|
|
}
|
|
//cout <<"a matrix \n"<<a;
|
|
//cout<<"EXP\n";
|
|
double t=clock()/((double) (CLOCKS_PER_SEC));
|
|
NRMat<double> b=exp0(a);
|
|
cout <<"exp0 took "<<clock()/((double) (CLOCKS_PER_SEC))-t<<endl;
|
|
//cout <<"b=exp0(a) matrix\n"<<b;
|
|
t=clock()/((double) (CLOCKS_PER_SEC));
|
|
NRMat<double> c=exp(a,true);
|
|
cout <<" horner exp took "<<clock()/((double) (CLOCKS_PER_SEC))-t<<endl;
|
|
//cout <<"exp(a)\n"<<c;
|
|
cout<<"error1 = "<<(c-b).norm()/b.norm()<<endl;
|
|
t=clock()/((double) (CLOCKS_PER_SEC));
|
|
c=exp(a,false);
|
|
cout <<" tricky exp took "<<clock()/((double) (CLOCKS_PER_SEC))-t<<endl;
|
|
cout<<"error2 = "<<(c-b).norm()/b.norm()<<endl;
|
|
|
|
v=b*u;
|
|
t=clock()/((double) (CLOCKS_PER_SEC));
|
|
w=exptimes(a,u);
|
|
cout <<"exptimes took "<<clock()/((double) (CLOCKS_PER_SEC))-t<<endl;
|
|
cout <<"error of exptimes = "<<(v-w).norm()/v.norm()<<endl;
|
|
|
|
|
|
}
|
|
|
|
|
|
if(0)
|
|
{
|
|
int n;
|
|
cin>>n;
|
|
NRMat<double> a(n,n);
|
|
for(int i=0;i<n;++i) for(int j=0;j<=i;++j)
|
|
{
|
|
a(i,j)= .1*random()/(1.+RAND_MAX);
|
|
a(j,i)= a(i,j);
|
|
}
|
|
NRMat<double> b=exp(a);
|
|
NRMat<double> s=exp(a*.5);
|
|
NRMat<double> y(0.,n,n);
|
|
NRMat<double> z(0.,n,n);
|
|
double r;
|
|
int i=0;
|
|
y=b;z=1.;
|
|
cout << "norm = "<<b.norm(1.)<<endl;
|
|
do
|
|
{
|
|
NRMat<double> tmp=z*y*-1.+3.;
|
|
NRMat<double> ynew=y*tmp*.5;
|
|
z=tmp*z*.5;
|
|
y=ynew;
|
|
cout <<"iter "<<i <<" residue "<< (r=(y-s).norm())<<endl;
|
|
++i;
|
|
} while(abs(r)>1e-10);
|
|
}
|
|
|
|
|
|
if(0)
|
|
{
|
|
int n=3;
|
|
NRMat<double> a(n,n);
|
|
a(0,0)=1.;
|
|
a(0,1)=2.;
|
|
a(1,0)=2.;
|
|
a(1,1)=6.;
|
|
a(2,2)=-4;
|
|
a(0,2)=1;
|
|
cout <<a;
|
|
double d;
|
|
NRMat<double> c=inverse(a,&d);
|
|
cout <<a<<c;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
NRMat<double> a(3,3);
|
|
NRMat<double> b=a;
|
|
for(int i=1; i<4;i++) b=b*b;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
NRMat<double> aa,bb,cc;
|
|
cin >>aa;
|
|
cc=copytest(aa);
|
|
cout <<cc;
|
|
|
|
NRMat<complex<double> > a,b,c;
|
|
a=complexify(aa);
|
|
c=copytest(a);
|
|
cout <<c;
|
|
b=log(a);
|
|
cout <<b;
|
|
cout <<exp(b);
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
NRMat<complex<double> > a,b,c;
|
|
cin>>a;
|
|
c=copytest(a);
|
|
cout <<c;
|
|
b=log(a);
|
|
cout <<b;
|
|
cout <<exp(b);
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
NRMat<double> a,b,c;
|
|
cin >>a;
|
|
c=copytest(a);
|
|
cout <<c;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
NRMat<double> a;
|
|
NRMat<double> b=exp(a);
|
|
NRMat<double> c=log(b);
|
|
cout <<a;
|
|
cout <<b;
|
|
cout <<c;
|
|
cout << (b-exp(c)).norm() <<endl;
|
|
}
|
|
|
|
if(00)
|
|
{
|
|
NRMat<double> a;
|
|
cin >>a;
|
|
NRMat<double> c=log(a); //matrixfunction(a,&mycident,1);
|
|
cout <<c;
|
|
NRMat<double> b=exp(c);
|
|
cout <<"exp(log(x))\n"<<b;
|
|
cout<<(b-a).norm()<<endl;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
//check my exponential with respect to spectral decomposition one
|
|
NRSMat<double> a;
|
|
cin >>a;
|
|
NRMat<double> aa(a);
|
|
NRMat<double> b=exp(aa);
|
|
NRMat<double> c=matrixfunction(a,&exp);
|
|
cout <<a;
|
|
cout <<b;
|
|
cout <<c;
|
|
cout << (b-c).norm()/b.norm() <<endl;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
//verify BCH expansion
|
|
NRMat<double> h;
|
|
NRMat<double> t;
|
|
cin >>h;
|
|
cin >>t;
|
|
NRMat<double> r1= exp(-t) * h * exp(t);
|
|
NRMat<double> r2=BCHexpansion(h,t,30);
|
|
cout <<r1;
|
|
cout <<r2;
|
|
cout <<"error = "<<(r1-r2).norm()<<endl;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
int dim; cin>>dim;
|
|
int degree; cin >>degree;
|
|
NRMat<double> h(dim,dim);
|
|
NRMat<double> t(dim,dim);
|
|
NRVec<double> x(dim);
|
|
h.randomize(1.);
|
|
t.randomize(1.);
|
|
x.randomize(2.);
|
|
NRVec<double> y1 = exp(-t) * h * exp(t) *x;
|
|
NRVec<double> y2 = BCHtimes(h,'n',t,'n',x,degree,true);
|
|
NRVec<double> y3 = exp(t) * h * exp(-t) *x;
|
|
NRVec<double> y4 = BCHtimes(h,'n',t,'n',x,degree,false);
|
|
cout <<"BCHtimes error = "<<(y1-y2).norm()<<endl;
|
|
cout <<"BCHtimes error = "<<(y3-y4).norm()<<endl;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
int n;
|
|
cin >>n;
|
|
SparseMat<double> a(n,n);
|
|
for(int i=0;i<n;++i) for(int j=0;j<=i;++j)
|
|
{
|
|
a.add(i,j,random()/(1.+RAND_MAX));
|
|
}
|
|
a.setsymmetric();
|
|
NRSMat<double> aa(a);
|
|
NRMat<double> aaa(a);
|
|
NRVec<double> w(n);
|
|
NRMat<double> v(n,n);
|
|
//cout <<aa;
|
|
diagonalize(aa, w, &v,0);
|
|
//cout <<w;
|
|
//cout <<v;
|
|
//cout << v*aaa*v.transpose();
|
|
cout << (v*aaa*v.transpose() - diagonalmatrix(w)).norm()<<endl;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
NRMat<complex<double> > a;
|
|
cin >>a;
|
|
NRMat<complex<double> > b=exp(a);
|
|
cout <<b;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
int n;
|
|
double d;
|
|
cin >>n;
|
|
//NRMat<double> a(n,n);
|
|
NRSMat<double> a(n);
|
|
for(int i=0;i<n;++i) for(int j=0;j<=i;++j)
|
|
{
|
|
a(j,i)=a(i,j)=random()/(1.+RAND_MAX)*(i==j?10.:1.);
|
|
}
|
|
cout <<a;
|
|
NRMat<double> y(1,n);
|
|
for(int i=0;i<n;++i) y(0,i)=random()/(1.+RAND_MAX);
|
|
cout <<y;
|
|
linear_solve(a,&y,&d);
|
|
cout << y;
|
|
cout <<"det is "<<d<<endl;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
int n;
|
|
cin >>n;
|
|
SparseMat<double> a(n,n);
|
|
int spars=n*n/3;
|
|
for(int i=0; i<spars;i++) a.add(randind(n),randind(n),random()/(1.+RAND_MAX));
|
|
|
|
NRMat<double> aa(a);
|
|
NRVec<double> v(aa[0],n*n);
|
|
|
|
cout <<a;
|
|
cout <<aa;
|
|
cout <<v;
|
|
|
|
cout <<"test "<<aa.dot(aa)<<endl;
|
|
cout <<"test "<<v*v<<endl;
|
|
cout <<"test "<<a.dot(aa)<<endl;
|
|
cout <<"test "<<a.dot(a)<<endl;
|
|
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
NRMat<double> amat,bmat;
|
|
cin >>amat;
|
|
cin >>bmat;
|
|
NRVec<double> v(amat.nrows());
|
|
diagonalize(amat,v,1,1,0,&bmat,1);
|
|
cout <<amat;
|
|
cout <<v;
|
|
}
|
|
|
|
|
|
if(0)
|
|
{
|
|
int n,m;
|
|
cin>>n >>m;
|
|
NRSMat<double> a(n,n);
|
|
NRVec<double> rr(n);
|
|
|
|
for(int i=0;i<n;++i) for(int j=0;j<=i;++j)
|
|
{
|
|
a(i,j)= random()/(1.+RAND_MAX);
|
|
if(i==j) a(i,i)+= .5*(i-n);
|
|
}
|
|
|
|
NRSMat<double> aa;
|
|
NRMat<double> vv(n,n);
|
|
aa=a; diagonalize(aa,rr,&vv);
|
|
NRVec<double> r(m);
|
|
NRVec<double> *eivecs = new NRVec<double>[m];
|
|
davidson(a,r,eivecs,NULL,m,1,1e-6,1,200);
|
|
|
|
cout <<"Davidson energies " <<r;
|
|
cout <<"Exact energies " ;
|
|
for(int i=0; i<m; ++i) cout <<rr[i]<<" ";
|
|
cout <<endl;
|
|
|
|
cout <<"Eigenvectors compare:\n";
|
|
for(int i=0; i<m; ++i)
|
|
{
|
|
cout <<eivecs[i];
|
|
for(int j=0; j<n;++j) cout <<vv[j][i]<<" ";
|
|
cout <<endl;
|
|
}
|
|
|
|
}
|
|
|
|
if(0) //davidson of a non-symmetric matrix
|
|
{
|
|
int n,m;
|
|
cin>>n >>m;
|
|
NRMat<double> a(n,n);
|
|
NRVec<double> rr(n),ii(n);
|
|
|
|
double tmp=0.;
|
|
for(int i=0;i<n;++i) for(int j=0;j<n;++j)
|
|
{
|
|
a(i,j)= random()/(1.+RAND_MAX);
|
|
a(j,i)= random()/(1.+RAND_MAX);
|
|
if(i==j) a(i,i)+= .5*(i-n);
|
|
tmp+= (a(i,j)-a(j,i))*(a(i,j)-a(j,i));
|
|
}
|
|
cout <<"norm of asymmetry "<<sqrt(tmp)<<endl;
|
|
|
|
NRMat<double> aa=a;
|
|
NRMat<double> vv=aa;
|
|
gdiagonalize(aa, rr, ii, NULL, &vv, 1, 0, 2, 0, NULL,NULL);
|
|
NRVec<double> r(m);
|
|
NRVec<double> *eivecs = new NRVec<double>[m];
|
|
davidson(a,r,eivecs,NULL,m,1,1e-6,1,200);
|
|
|
|
cout <<"Davidson energies " <<r;
|
|
cout <<"Exact energies " ;
|
|
for(int i=0; i<m; ++i) cout <<rr[i]<<" ";
|
|
cout <<endl;
|
|
|
|
cout <<"Eigenvectors compare:\n";
|
|
for(int i=0; i<m; ++i)
|
|
{
|
|
cout <<eivecs[i];
|
|
for(int j=0; j<n;++j) cout <<vv[j][i]<<" ";
|
|
cout <<endl;
|
|
}
|
|
|
|
}
|
|
|
|
//davidson of large very sparse matrix (10n/n^2)
|
|
|
|
#undef sparsity
|
|
#define sparsity (n*2)
|
|
if(0)
|
|
{
|
|
int n,m;
|
|
cin >>n>>m;
|
|
SparseMat<double> aa(n,n);
|
|
aa.setsymmetric();
|
|
for(int i=0; i<sparsity;i++) aa.add(randind(n),randind(n),random()/(1.+RAND_MAX));
|
|
for(int i=0; i<n; ++i) aa.add(i,i,500*random()/(1.+RAND_MAX));
|
|
NRVec<double> r(m);
|
|
davidson(aa,r,(NRVec<double> *)NULL,"eivecs",m,1,1e-5,0,300,300);
|
|
cout <<r;
|
|
}
|
|
|
|
//davidson of symmetric matrix and of its unsymmetric similarity transform
|
|
#undef sparsity
|
|
#define sparsity (n*2)
|
|
#define sparsity2 (n/5)
|
|
if(0)
|
|
{
|
|
int n,m;
|
|
cin >>n>>m;
|
|
SparseMat<double> aa(n,n);
|
|
aa.setsymmetric();
|
|
for(int i=0; i<sparsity;i++) aa.add(randind(n),randind(n),random()/(1.+RAND_MAX));
|
|
for(int i=0; i<n; ++i) aa.add(i,i,500*random()/(1.+RAND_MAX));
|
|
NRVec<double> r(m);
|
|
NRVec<double> r2(m);
|
|
davidson(aa,r,(NRVec<double> *)NULL,"eivecs",m,1,1e-5,1,300,300);
|
|
SparseMat<double> bb(n,n);
|
|
for(int i=0; i<sparsity2;i++) bb.add(randind(n),randind(n),random()/(1.+RAND_MAX));
|
|
SparseMat<double> e1,e2,cc;
|
|
e1=exp(bb);
|
|
e2=exp(bb*-1.);
|
|
aa.setunsymmetric();
|
|
cc=e1*aa*e2;
|
|
davidson(cc,r2,(NRVec<double> *)NULL,"eivecs2",m,1,1e-5,1,300,300);
|
|
cout <<"original matrix" <<r;
|
|
cout <<"transformed matrix" <<r2;
|
|
}
|
|
|
|
//davidson of large very sparse matrix unsymmetric matrix
|
|
#undef sparsity
|
|
#define sparsity (n)
|
|
if(0)
|
|
{
|
|
int n,m;
|
|
cin >>n>>m;
|
|
SparseMat<double> aa(n,n);
|
|
for(int i=0; i<sparsity;i++)
|
|
{
|
|
int k= randind(n);
|
|
int l= randind(n);
|
|
double a=random()/(1.+RAND_MAX);
|
|
double b=random()/(1.+RAND_MAX)-.5;
|
|
aa.add(k,l,a);
|
|
aa.add(l,k,a+b/20);
|
|
}
|
|
for(int i=0; i<n; ++i) aa.add(i,i,500*random()/(1.+RAND_MAX));
|
|
NRVec<double> r(m);
|
|
davidson(aa,r,(NRVec<double> *)NULL,"eivecs",m,1,1e-5,0,300,300);
|
|
cout <<r;
|
|
}
|
|
|
|
|
|
if(0)
|
|
{
|
|
int n,m;
|
|
cin>>n >>m;
|
|
NRMat<double> a(n,m);
|
|
NRVec<double> b(n);
|
|
NRVec<double> x(m);
|
|
|
|
for(int i=0;i<n;++i) for(int j=0;j<m;++j)
|
|
{
|
|
//a(j,i)= 2*i*i*i-5*j+ +9*8*7*6*5*4*3*2/(i+j+1.)+3*(i*i+2*j*j*j);
|
|
a(i,j)= random()/(1.+RAND_MAX);
|
|
if(i==j) a(i,i)+= .5*(i-n);
|
|
}
|
|
for(int i=0;i<n;++i) b[i] = i;
|
|
|
|
NRVec<double> bb=b;
|
|
//cout <<a;
|
|
//cout <<b;
|
|
NRMat<double>aa=a;
|
|
linear_solve(aa,bb);
|
|
//cout <<bb;
|
|
gmres(a,b,x,1,1e-10,100,1,0,1,0);
|
|
//conjgrad(a,b,x,1,1e-10,200,1,0,1);
|
|
|
|
cout <<"\nsolution compare:\n";
|
|
for(int i=0; i<m; ++i)
|
|
{
|
|
cout <<"iterative solver: ";
|
|
cout <<x[i];
|
|
cout <<" direct solver:";
|
|
cout <<bb[i];
|
|
cout <<endl;
|
|
}
|
|
|
|
}
|
|
|
|
|
|
if(0)
|
|
{
|
|
int n,m;
|
|
cin>>n >>m;
|
|
SparseMat<double> aa(n,m);
|
|
NRVec<double> b(n);
|
|
NRVec<double> x(m);
|
|
|
|
//tridiagonal
|
|
for(int i=0; i<n; ++i) aa.add(i,i,random()/(1.+RAND_MAX));
|
|
for(int i=0; i<n-1; i+=1) aa.add(i,i+1,.002*random()/(1.+RAND_MAX));
|
|
for(int i=0; i<n-1; i+=1) aa.add(i+1,i,.002*random()/(1.+RAND_MAX));
|
|
|
|
for(int i=0;i<n;++i) b[i] = i+1;
|
|
gmres(aa,b,x,1,1e-20,20,1,1,1,1000,1);
|
|
//conjgrad(aa,b,x,1,1e-10,1000,1,0,1);
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
NRMat<double> A(3,3);
|
|
A=1.;
|
|
double *p = (double *)A;
|
|
*p=2.;
|
|
cout <<A;
|
|
}
|
|
|
|
#if 0 //@@@make a more realistic test
|
|
{
|
|
int i;
|
|
DIIS<NRVec<double> > diis(5);
|
|
int dim;
|
|
cin>>dim;
|
|
NRVec<double> solution(dim), deviation(dim);
|
|
for(i=0; i<dim; ++i) solution[i]=i&1 ? i/2.:-i-3.;
|
|
for(i=0; i<dim; ++i) deviation[i]= (i&2 ? 1:-1) * random()/(1.+RAND_MAX);
|
|
double norm=1e100;
|
|
for(int iter=1; iter<100 && norm>1e-8 ; ++iter)
|
|
{
|
|
NRVec<double> trial=solution;
|
|
trial.copyonwrite();
|
|
for(i=0; i<dim; ++i) trial[i] += deviation[i]/iter;
|
|
cout <<"iter "<<iter<<endl;
|
|
cout << "trial "<<trial;
|
|
cout <<"diis " << (norm=diis.extrapolate(trial)) <<endl;
|
|
cout << "after diis "<<trial;
|
|
deviation=trial-solution;
|
|
}
|
|
}
|
|
#endif
|
|
|
|
if(0)
|
|
{
|
|
NRMat<double> a,b;
|
|
cin >>a;
|
|
b=realsqrt(a);
|
|
cout <<b;
|
|
cout <<b*b;
|
|
cout <<(b*b-a).norm();
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
NRSMat<double> a;
|
|
NRMat<double> b;
|
|
cin >>a>>b;
|
|
cout <<a*b;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
NRMat<double> a,b;
|
|
cin >>a >>b;
|
|
cout <<a.oplus(b);
|
|
cout <<a.otimes(b);
|
|
}
|
|
|
|
|
|
//test of general square matrix eigenvector derivatives
|
|
if(0)
|
|
{
|
|
const bool biorthonormalize=1;
|
|
|
|
NRMat<double> a;
|
|
cin >>a;
|
|
if(a.nrows()!=a.ncols()) laerror("must be square matrix");
|
|
int n=a.nrows();
|
|
|
|
NRMat<double>vl(n,n),vr(n,n);
|
|
NRVec<double> wr(n),wi(n);
|
|
NRMat<double> awork(a);
|
|
gdiagonalize(awork,wr,wi,&vl,&vr,1,0,1,biorthonormalize);
|
|
for(int i=0; i<n; ++i) if(wi[i]) laerror("try another matrix with real eigenvalues");
|
|
|
|
NRMat<double> eival(0.,n,n);
|
|
eival.diagonalset(wr);
|
|
|
|
cout <<"test biorthonormality "<< (vl.transpose() * vr - 1.).norm()<<endl;
|
|
|
|
NRMat<double> hlp;
|
|
hlp = a *vr - vr * eival;
|
|
cout <<"test right eivectors "<<hlp.norm()<<endl;
|
|
|
|
hlp= vl.transpose() * a - eival * vl.transpose();
|
|
cout <<"test left eivectors "<<hlp.norm()<<endl;
|
|
|
|
hlp = vl.transpose() * a * vr - eival;
|
|
cout <<"test eigenvalues "<<hlp.norm()<<endl;
|
|
|
|
NRMat<double> ader(n,n);
|
|
for(int i=0; i<n; ++i)
|
|
for(int j=0; j<n; ++j)
|
|
ader(i,j) = 2.*random()/(1.+RAND_MAX) -1.;
|
|
|
|
cout <<"eigenvalues\n"<<wr<<endl;
|
|
|
|
|
|
|
|
//compute numerical derivatives of eigenvectors
|
|
double h=1e-5;
|
|
awork = a+ ader*h;
|
|
NRMat<double> vlx(n,n),vrx(n,n);
|
|
NRVec<double> wrx(n),wix(n);
|
|
gdiagonalize(awork,wrx,wix,&vlx,&vrx,1,0,1,biorthonormalize);
|
|
for(int i=0; i<n; ++i) if(wix[i]) laerror("try another matrix with real eigenvalues");
|
|
|
|
awork = a - ader*h;
|
|
NRMat<double> vly(n,n),vry(n,n);
|
|
NRVec<double> wry(n),wiy(n);
|
|
gdiagonalize(awork,wry,wiy,&vly,&vry,1,0,1,biorthonormalize);
|
|
for(int i=0; i<n; ++i) if(wiy[i]) laerror("try another matrix with real eigenvalues");
|
|
|
|
NRMat<double> vld,vrd;
|
|
NRVec<double> wrd;
|
|
vld = (vlx-vly) * (.5/h);
|
|
vrd = (vrx-vry) * (.5/h);
|
|
wrd = (wrx-wry) * (.5/h);
|
|
|
|
NRMat<double> vlg,vrg;
|
|
NRVec<double> wrg(n);
|
|
|
|
//compute analytic derivative
|
|
NRMat<double> tmp(n,n);
|
|
tmp.gemm(0.,vl,'t', ader * vr,'n',1.);
|
|
hlp |= tmp;
|
|
cout <<" C~+ VH C = \n"<<tmp<<endl;
|
|
|
|
tmp.diagonalof(wrg);
|
|
for(int i=0; i<n; ++i)
|
|
for(int j=0; j<n; ++j)
|
|
if(i!=j) tmp(i,j) /= (wr[j] - wr[i]); else tmp(i,j) = 0.;
|
|
cout <<" old X matrix (tmp) \n"<<tmp<<endl;
|
|
|
|
NRMat<double> Y = tmp;
|
|
NRMat<double> S = vr.transpose() * vr;
|
|
cout <<"test S\n"<<S;
|
|
NRMat<double> tmp2 = S * tmp;
|
|
cout <<"test tmp2\n"<<tmp2;
|
|
Y.copyonwrite();
|
|
for(int i=0; i<n; ++i) Y(i,i) -= tmp2(i,i);
|
|
|
|
cout <<"Y matrix \n"<< Y;
|
|
|
|
NRMat<double> vri = inverse(vr);
|
|
|
|
NRMat<double> numX = vri * vrd;
|
|
cout <<" numerical X matrix \n"<< numX;
|
|
cout <<" numerical X matrix test = "<< (vr * numX - vrd).norm()<<endl;
|
|
|
|
vrg = vr * Y;
|
|
|
|
vlg = - (Y*vri).transpose();
|
|
|
|
//and compare
|
|
cout <<"eigenvalue numerical derivative\n"<<wrd<<endl;
|
|
cout <<"eigenvalue analytic derivative\n"<<wrg<<endl;
|
|
cout <<"eigenvalue derivative error = "<<(wrd-wrg).norm()<<endl;
|
|
|
|
//and for right eigenvectors
|
|
cout <<"right eigenvector numerical derivative\n"<<vrd<<endl;
|
|
cout <<"right eigenvector analytic derivative\n"<<vrg<<endl;
|
|
cout <<"right eigenvector derivative error = "<<(vrd-vrg).norm()<<endl;
|
|
|
|
//and for left eigenvectors
|
|
cout <<"left eigenvector numerical derivative\n"<<vld<<endl;
|
|
cout <<"left eigenvector analytic derivative\n"<<vlg<<endl;
|
|
cout <<"left eigenvector derivative error = "<<(vld-vlg).norm()<<endl;
|
|
|
|
|
|
}
|
|
|
|
//@@@@@@@make this derivative check in complex version
|
|
|
|
|
|
if(0)
|
|
{
|
|
try { laerror("test catch exception"); }
|
|
catch(LAerror x)
|
|
{
|
|
cout <<"caught exception: "<<x <<endl;
|
|
}
|
|
laerror("test exception 2");
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
NRVec<double> v(3);
|
|
v[0]=1; v[1]=2; v[2]=3;
|
|
NRVec<complex<double> > vv = v;
|
|
NRVec<double>u(v);
|
|
vv += u;
|
|
cout <<vv;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
complex<double> scale; cin >> scale;
|
|
|
|
NRMat<complex<double> > h; cin >>h;
|
|
NRVec<complex<double> > x(h.nrows());
|
|
NRVec<complex<double> > y,z;
|
|
|
|
x.randomize(1.);
|
|
|
|
y=exptimes(h*scale,x,false,1.);
|
|
z=exptimes(h,x,false,scale);
|
|
|
|
cout <<x;
|
|
cout <<y;
|
|
cout <<z;
|
|
cout <<"Error "<<(y-z).norm()<<endl;
|
|
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
int nocc,nvirt;
|
|
cin >>nocc>>nvirt;
|
|
int n=nocc+nvirt;
|
|
NRMat<double> t(nocc,nvirt);
|
|
t.randomize(0.5);
|
|
NRSMat<double> A(n);
|
|
A=1.;
|
|
for(int i=0; i<nocc;++i) for(int a=nocc; a<n; ++a) A(i,a) = t(i,a-nocc);
|
|
NRMat<double> B(n,n);
|
|
NRVec<double> E(n);
|
|
cout <<A;
|
|
NRSMat<double> Awork=A;
|
|
diagonalize(Awork,E,&B);
|
|
cout <<B<<E;
|
|
NRMat<double> U = A*B;
|
|
for(int p=0; p<n; ++p) E[p] = 1./E[p];
|
|
U.diagmultr(E);
|
|
cout << "Unitary\n"<<U;
|
|
cout <<"Error = "<<(U*U.transpose() -1.).norm()<<endl;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
double t;
|
|
NRMat<complex<double> > ham;
|
|
cin >>ham;
|
|
NRMat<double> hamreal = realpart(ham);
|
|
t=clock()/((double) (CLOCKS_PER_SEC));
|
|
NRMat<complex<double> >hamexp1 = exp(ham*complex<double>(0,1));
|
|
cout <<"dense exp time "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
|
|
SparseMat<complex<double> > h(ham);
|
|
h *= complex<double>(0,1);
|
|
h.simplify();
|
|
cout <<"norms of input (should be same) "<<ham.norm()<<" "<<h.norm()<<endl;
|
|
cout <<"length of hamiltonian "<<h.length()<<endl;
|
|
t=clock()/((double) (CLOCKS_PER_SEC));
|
|
SparseMat<complex<double> > hexp = exp(h);
|
|
cout <<"sparse exp time "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
|
|
cout <<"length of exp of ihamiltonian "<<hexp.length()<<endl;
|
|
NRMat<complex<double> >hamexp2(hexp);
|
|
cout <<"norm of results "<<hamexp1.norm() <<" "<<hamexp2.norm()<<endl;
|
|
cout <<"error = "<<(hamexp1-hamexp2).norm()<<endl;
|
|
NRMat<double> s,c;
|
|
t=clock()/((double) (CLOCKS_PER_SEC));
|
|
sincos(s,c,hamreal);
|
|
cout <<"dense sincos time "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
|
|
NRMat<complex<double> >hamexp3 = complexmatrix(c,s);
|
|
cout <<"sincos error = "<<(hamexp1-hamexp3).norm()<<endl;
|
|
SparseMat<double> hreal(hamreal);
|
|
SparseMat<double> si,co;
|
|
t=clock()/((double) (CLOCKS_PER_SEC));
|
|
sincos(si,co,hreal);
|
|
cout <<"sparse sincos time "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
|
|
cout <<"length of sin,cos "<<si.length()<<" "<<co.length()<<endl;
|
|
NRMat<complex<double> >hamexp4 = complexmatrix(NRMat<double>(co),NRMat<double>(si));
|
|
cout <<"sincos error 2 = "<<(hamexp1-hamexp4).norm()<<endl;
|
|
|
|
NRVec<complex<double> > rhs(ham.ncols());
|
|
rhs.randomize(1.);
|
|
t=clock()/((double) (CLOCKS_PER_SEC));
|
|
NRVec<complex<double> > r1 = exptimes(ham*complex<double>(0,1),rhs);
|
|
cout <<"dense exptimes "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
|
|
t=clock()/((double) (CLOCKS_PER_SEC));
|
|
NRVec<complex<double> > r2 = exptimes(h,rhs);
|
|
cout <<"sparse exptimes "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
|
|
cout <<"exptimes error = "<<(r1-r2).norm()<<endl;
|
|
NRVec<complex<double> > siv,cov;
|
|
t=clock()/((double) (CLOCKS_PER_SEC));
|
|
//sincostimes(ham,siv,cov,rhs);
|
|
sincostimes(hamreal,siv,cov,rhs);
|
|
cout <<"dense sincostimes "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
|
|
cout <<"sincostimes errors = "<<(siv-s*rhs).norm()<<" "<<(cov-c*rhs).norm()<<endl;
|
|
NRVec<complex<double> > r3 = cov + siv*complex<double>(0,1);
|
|
cout <<"sincostimes error = "<<(r1-r3).norm()<<endl;
|
|
/*
|
|
* real sparse matrix times complex vector not implemented
|
|
NRVec<complex<double> > siv2,cov2;
|
|
t=clock()/((double) (CLOCKS_PER_SEC));
|
|
sincostimes(hreal,siv2,cov2,rhs);
|
|
cout <<"sparse sincostimes "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
|
|
NRVec<complex<double> > r4 = cov2 + siv2*complex<double>(0,1);
|
|
cout <<"sincostimes error 2 = "<<(r1-r4).norm()<<endl;
|
|
*/
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
double t;
|
|
SparseMat<complex<double> > h;
|
|
cin >> h;
|
|
h *= complex<double>(0,1);
|
|
h.simplify();
|
|
cout <<"length of hamiltonian "<<h.length()<<endl;
|
|
t=clock()/((double) (CLOCKS_PER_SEC));
|
|
SparseMat<complex<double> > hexp = exp(h);
|
|
cout <<"sparse exp time "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
|
|
cout <<"length of exp hamiltonian "<<hexp.length()<<endl;
|
|
NRMat<complex<double> > he(hexp);
|
|
NRMat<complex<double> > hec(he);
|
|
NRMat<complex<double> > het(he);
|
|
hec.conjugateme();
|
|
het.transposeme();
|
|
//cout <<he;
|
|
cout <<"unitarity error "<<(hec*he).norm(1)<<endl;
|
|
cout <<"symmetry error "<<(het-he).norm()<<endl;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
int n;
|
|
cin >>n;
|
|
NRSMat<double> hd(n);
|
|
hd.randomize(1);
|
|
SparseSMat<double> h(hd);
|
|
NRMat<double> rd = hd*hd;
|
|
SparseSMat<double> r = h*h;
|
|
NRSMat<double>rx(r);
|
|
NRMat<double> r2(rx);
|
|
cout <<"Error = "<<(r2-rd).norm()<<endl;
|
|
}
|
|
|
|
|
|
if(0)
|
|
{
|
|
SparseSMat<double> h0;
|
|
cin>>h0;
|
|
cout <<"matrix read\n"; cout.flush();
|
|
SparseSMat<double> h1 = h0; //.submatrix(0,2047,0,2047);
|
|
SparseSMat<complex<double> > h = imagmatrix(h1);
|
|
double t=clock()/((double) (CLOCKS_PER_SEC));
|
|
SparseSMat<complex<double> > r = h*h;
|
|
cout <<"SparseSMat mult time "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
|
|
cout.flush();
|
|
t=clock()/((double) (CLOCKS_PER_SEC));
|
|
r = exp(h);
|
|
cout <<"SparseSMat exp time "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
|
|
cout.flush();
|
|
if(h.nrows()<=1024)
|
|
{
|
|
NRSMat<complex<double> > h3(h);
|
|
NRMat<complex<double> > h2(h3);
|
|
NRMat<complex<double> >r2 = exp(h2);
|
|
cout <<"error = "<<(r2-NRMat<complex<double> >(NRSMat<complex<double> >(r))).norm()<<endl;
|
|
cout <<"errorx = "<<(r2-NRSMat<complex<double> >(r)).norm()<<endl;
|
|
}
|
|
}
|
|
|
|
|
|
if(0)
|
|
{
|
|
int n;
|
|
cin >>n;
|
|
NRMat<double> a(n,n);
|
|
a.randomize(1);
|
|
for(int i=0; i<n; ++i) for(int j=0; j<i; ++j) {a(i,j)=0.;}
|
|
cout <<a;
|
|
NRMat<double> bb=a.transpose()*a;
|
|
NRMat<double> cc(bb);
|
|
NRMat<double> b(bb);
|
|
NRMat<double> c(cc);
|
|
cholesky(b,0);
|
|
cout <<b;
|
|
cout << "Error = "<<(b*b.transpose()-bb).norm()<<endl;
|
|
cholesky(c,1);
|
|
cout <<c;
|
|
cout << "Error = "<<(c.transpose()*c-cc).norm()<<endl;
|
|
}
|
|
|
|
|
|
|
|
if(0)
|
|
{
|
|
int n;
|
|
cin >>n;
|
|
NRMat<complex<double> > a(n,n);
|
|
a.randomize(1);
|
|
for(int i=0; i<n; ++i) for(int j=0; j<i; ++j) {a(i,j)=0.;}
|
|
for(int i=0; i<n; ++i) {a(i,i).imag(0.); if(a(i,i).real()<0) a(i,i).real(-a(i,i).real());}
|
|
cout <<a;
|
|
NRMat<complex<double> > bb=a.transpose(true)*a;
|
|
NRMat<complex<double> > cc(bb);
|
|
NRMat<complex<double> > b(bb);
|
|
NRMat<complex<double> > c(cc);
|
|
cholesky(b,0);
|
|
cout <<b;
|
|
cout << "Error = "<<(b*b.transpose(true)-bb).norm()<<endl;
|
|
cholesky(c,1);
|
|
cout <<c;
|
|
cout << "Error = "<<(c.transpose(true)*c-cc).norm()<<endl;
|
|
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
int n;
|
|
cin >>n;
|
|
NRMat<double> bb(0.,n,n);
|
|
int nn=0;
|
|
for(int i=0; i<n; ++i) for(int j=i; j<n; ++j) {if((double)random()/RAND_MAX>0.995 || i==j) {++nn; bb(i,j)=bb(j,i)=(double)random()/RAND_MAX*(i==j?10.:.5/(i+j)*(random()>RAND_MAX/2?1:-1));}}
|
|
bb=bb*bb.transpose();
|
|
//cout <<bb;
|
|
nn=0;
|
|
for(int i=0; i<n; ++i) for(int j=i; j<n; ++j) if(abs(bb(i,j))>1e-16 || abs(bb(j,i))>1e-16 ) ++nn;
|
|
cout <<"Original filling = "<<nn*2./n/(n+1)<<endl;
|
|
NRMat<double> b(bb);
|
|
cholesky(b,0);
|
|
//cout <<b;
|
|
cout << "Error = "<<(b*b.transpose()-bb).norm()<<endl;
|
|
nn=0;
|
|
for(int i=0; i<n; ++i) for(int j=i; j<n; ++j) if(abs(b(i,j))>1e-16 || abs(b(j,i))>1e-16 ) ++nn;
|
|
cout <<"Cholesky factor filling = "<<nn*2./n/(n+1)<<endl;
|
|
}
|
|
|
|
|
|
if(0)
|
|
{
|
|
int n;
|
|
cin >>n;
|
|
NRMat<double> a(n,n);
|
|
a.randomize(1);
|
|
for(int i=0; i<n; ++i) for(int j=0; j<i; ++j) {a(i,j)=0.;}
|
|
cout <<a;
|
|
NRMat<double> bb=a.transpose()*a;
|
|
SparseSMat<double> cc(bb);
|
|
NRMat<double> b(bb);
|
|
cholesky(b,0);
|
|
cout <<b;
|
|
SparseSMat<double> c;
|
|
c= cc.cholesky();
|
|
cout <<c;
|
|
}
|
|
|
|
|
|
if(0)
|
|
{
|
|
int n;
|
|
cin >>n;
|
|
NRMat<complex<double> > a(n,n);
|
|
a.randomize(1);
|
|
for(int i=0; i<n; ++i) for(int j=0; j<i; ++j) {a(i,j)=0.;}
|
|
for(int i=0; i<n; ++i) {a(i,i).imag(0.); if(a(i,i).real()<0) a(i,i).real(-10.*a(i,i).real()); else a(i,i).real(10.*a(i,i).real());}
|
|
if(n<100)cout <<a;
|
|
NRMat<complex<double> > bb=a.transpose(true)*a;
|
|
SparseSMat<complex<double> > cc(bb);
|
|
if(n<100)cout <<"Input matrix\n"<<bb;
|
|
NRMat<complex<double> > b(bb);
|
|
//cholesky(b,0);
|
|
//if(n<100)cout <<"Dense Cholesky result\n"<<b;
|
|
SparseSMat<complex<double> > c;
|
|
c= cc.cholesky();
|
|
NRMat<complex<double> > cx(c);
|
|
if(n<100)cout <<"Sparse pivoted Cholesky result \n"<<cx;
|
|
if(n<100)cout <<"result of reconstruction\n"<<cx.transpose(true)*cx<<endl;
|
|
cout <<"Error = "<<(cx.transpose(true)*cx -bb).norm()<<endl;
|
|
}
|
|
|
|
|
|
if(0)
|
|
{
|
|
int n;
|
|
cin >>n;
|
|
SparseSMat<double> bh(n,n);
|
|
for(int i=0; i<=n/400; ++i) for(int j=i; j<n; ++j) {if((double)random()/RAND_MAX>0.995 || i==j)
|
|
{bh.add(i,j,(double)random()/RAND_MAX*(i==j?10.:(random()>RAND_MAX/2?1:-1)),false);}}
|
|
if(n<1000) cout <<"Random matrix\n"<<bh;
|
|
SparseSMat<double> bb(n,n);
|
|
bb.gemm(0.,bh,'c',bh,'n',1.);
|
|
if(n<1000) cout <<"Input matrix\n"<<bb;
|
|
cout <<"Original filling = "<<bb.simplify()<<endl;
|
|
SparseSMat<double> b = bb.cholesky();
|
|
if(n<1000) cout <<"Cholesky result\n"<<b;
|
|
SparseSMat<double> br(n,n);
|
|
br.gemm(0.,b,'c',b,'n',1.);
|
|
if(n<1000) cout <<"Result of reconstruction\n"<<br;
|
|
if(n<1000) cout <<"Difference\n"<<br-bb;
|
|
cout << "Error = "<<(br-bb).norm()<<endl;
|
|
cout <<"Cholesky factor filling = "<<b.simplify()<<endl;
|
|
}
|
|
|
|
|
|
if(0)
|
|
{
|
|
int n;
|
|
cin >>n;
|
|
NRMat<double> a(n,n),b(n,n);
|
|
a.randomize(1.);
|
|
b.randomize(1.);
|
|
NRMat<double>c;
|
|
double t=clock()/((double) (CLOCKS_PER_SEC));
|
|
int rep=1+10000000000LL/n/n/n;
|
|
cout <<"Repetitions " <<rep<<endl;
|
|
for(int i=0; i<rep; ++i) c=a*b;
|
|
cout <<"CPU time (ms) "<<(clock()/((double) (CLOCKS_PER_SEC))-t)*1000./rep <<"\n";
|
|
NRMat<double>cgpu;
|
|
a.moveto(gpu1);
|
|
b.moveto(gpu1);
|
|
t=clock()/((double) (CLOCKS_PER_SEC));
|
|
for(int i=0; i<rep; ++i) cgpu=a*b;
|
|
cout <<"GPU time (ms) "<<(clock()/((double) (CLOCKS_PER_SEC))-t)*1000./rep <<"\n";
|
|
cgpu.moveto(cpu);
|
|
cout << "Error = "<<(c-cgpu).norm()<<endl;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
int n;
|
|
cin >>n;
|
|
NRMat<double> a(n,n);
|
|
a.randomize(1.);
|
|
NRVec<double> v(n);
|
|
v.randomize(1.);
|
|
NRSMat<double> as(n);
|
|
as.randomize(1.);
|
|
NRVec<double>w = a*v;
|
|
NRVec<double>ws = as*v;
|
|
NRMat<double>c(n,n);
|
|
c=exp(a);
|
|
a.moveto(gpu1);
|
|
v.moveto(gpu1);
|
|
as.moveto(gpu1);
|
|
NRVec<double>wgpu = a*v;
|
|
NRVec<double>wsgpu = as*v;
|
|
w.moveto(gpu1);
|
|
ws.moveto(gpu1);
|
|
cout << "Error gemv = "<<(w-wgpu).norm()<<endl;
|
|
cout << "Error symv = "<<(ws-wsgpu).norm()<<endl;
|
|
NRMat<double>cgpu;
|
|
cgpu=exp(a);
|
|
c.moveto(gpu1);
|
|
cout << "Error = "<<(c-cgpu).norm()<<endl;
|
|
}
|
|
|
|
/*
|
|
if(0)
|
|
{
|
|
CSRMat<double> h0;
|
|
cin>>h0;
|
|
cout <<"matrix read\n"; cout.flush();
|
|
CSRMat<double> h1 = h0;
|
|
CSRMat<complex<double> > h = imagmatrix(h1);
|
|
double t=clock()/((double) (CLOCKS_PER_SEC));
|
|
CSRMat<complex<double> > r = h*h;
|
|
cout <<"CSRMat mult time "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
|
|
cout.flush();
|
|
t=clock()/((double) (CLOCKS_PER_SEC));
|
|
r = exp(h);
|
|
cout <<"CSRMat exp time "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
|
|
cout.flush();
|
|
if(h.nrows()<=1024)
|
|
{
|
|
NRMat<complex<double> > h2(h);
|
|
NRMat<complex<double> >r2 = exp(h2);
|
|
cout <<"error = "<<(r2-NRMat<complex<double> >(r)).norm()<<endl;
|
|
}
|
|
}
|
|
*/
|
|
|
|
|
|
if(0)
|
|
{
|
|
NRMat<complex<double> > m;
|
|
ifstream f("libormat");
|
|
f >> m;
|
|
f.close();
|
|
|
|
NRVec<double> eivals(m.nrows());
|
|
NRMat<complex<double> > m_aux = m;
|
|
NRMat<complex<double> > m_test = m;
|
|
|
|
cout << "hermiticity error = " <<(m_aux.transpose(true) - m_aux).norm()<<endl;
|
|
diagonalize(m,eivals);
|
|
cout << "eivals "<<eivals;
|
|
cout <<"eivecs "<<m<<endl;
|
|
NRVec<complex<double> > eivalsc(eivals);
|
|
|
|
NRMat<complex<double> > m4 = m.transpose(true);
|
|
|
|
cout <<"unitarity error "<< (m4*m).norm(true)<<endl;
|
|
|
|
NRMat<complex<double> > m5(m.nrows(),m.nrows());
|
|
for(int i=0; i<m.nrows(); ++i) for(int j=0; j<m.nrows(); ++j)
|
|
m5(i,j) = complex<double>(m(j,i).real(), - m(j,i).imag());
|
|
|
|
cout << "conjugatetest "<<(m4-m5).norm()<<endl;
|
|
|
|
NRMat<complex<double> > m1= m_aux * m;
|
|
NRMat<complex<double> > m1x = m; m1x.diagmultr(eivalsc);
|
|
cout << "test m1 m1x "<<(m1-m1x).norm()<<endl;
|
|
NRMat<complex<double> > m2= m.transpose(true) * m1;
|
|
//NRMat<complex<double> > m2b= m * m_aux * m.transpose(true);
|
|
cout <<"check "<<m2<<endl;
|
|
//cout <<"checkb "<<m2b<<endl;
|
|
double err=0.;
|
|
for(int i=0; i<m.nrows(); ++i) for(int j=0; j<m.nrows(); ++j)
|
|
if(i!=j) err += abs(m2(i,j));
|
|
cout <<"offdiagonality error = "<<err<<endl;
|
|
|
|
err=0;
|
|
for(int i=0; i<m.nrows(); ++i) err += abs(m2(i,i) - eivals[i]);
|
|
cout <<"eigenvalue error = "<<err<<endl;
|
|
|
|
|
|
//test as general matrix
|
|
NRVec<complex<double> > ww(m.nrows());
|
|
NRMat<complex<double> > vl(m.nrows(),m.nrows()), vr(m.nrows(),m.nrows());
|
|
gdiagonalize(m_test,ww,&vl,&vr);
|
|
cout << "eivals "<<ww<<endl;
|
|
cout << "eivecs "<<vl<<vr<<endl;
|
|
NRMat<complex<double> > m3= vl.transpose(true)* m_aux *vr;
|
|
cout <<"check2 "<<m3;
|
|
err=0.;
|
|
for(int i=0; i<m.nrows(); ++i) for(int j=0; j<m.nrows(); ++j)
|
|
if(i!=j) err += abs(m3(i,j));
|
|
cout <<"offdiagonality error 2 = "<<err<<endl;
|
|
|
|
err=0;
|
|
for(int i=0; i<m.nrows(); ++i) err += abs(m3(i,i) - ww[i]);
|
|
cout <<"eigenvalue error = "<<err<<endl;
|
|
|
|
|
|
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
NRMat<double> a;
|
|
cin >>a ;
|
|
double det=determinant_destroy(a);
|
|
cout << "det= "<<det<<endl;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
bitvector v(3);
|
|
v.assign(0,0);
|
|
v.assign(1,1);
|
|
v.assign(2,0);
|
|
cin >>v;
|
|
cout <<v;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
Quaternion<double> q(1.);
|
|
Quaternion<double> p,r(q);
|
|
p=r;
|
|
q+=p;
|
|
q-=r;
|
|
r=p+q;
|
|
r+=Quaternion<double>(0,8,8,8);
|
|
r+= 2.;
|
|
r/=4.;
|
|
cout<<r<<endl;
|
|
Quaternion<double> s(-1,2,1,2);
|
|
Quaternion<double> t=r*s.conjugate();
|
|
cout <<t<<" "<<t[0]<<" "<<t.norm()<<endl;
|
|
Quaternion<double>tt = t.inverse();
|
|
cout <<tt<<" "<<t*tt<<endl;
|
|
r=s/t;
|
|
r.normalize();
|
|
cout<<r<<endl;
|
|
Mat3<double> rotmat;
|
|
quat2rotmat(r,rotmat);
|
|
cout << rotmat[0][1]<<endl;
|
|
r.normalize(NULL,true);
|
|
NRMat<double> rotmat2(3,3),rotmat3(3,3);
|
|
Quaternion<NRMat<double> > rotmatder;
|
|
rotmatder[0].resize(3,3);
|
|
rotmatder[1].resize(3,3);
|
|
rotmatder[2].resize(3,3);
|
|
rotmatder[3].resize(3,3);
|
|
normquat2rotmatder(r,rotmatder);
|
|
cout << rotmatder;
|
|
normquat2rotmat(r,rotmat2);
|
|
normquat2rotmat(-r,rotmat3);
|
|
cout << rotmat2<<endl;
|
|
cout << rotmat3<<endl;
|
|
Quaternion<double> rr;
|
|
rotmat2normquat(rotmat2,rr);
|
|
cout <<"orig "<<r<<endl;
|
|
cout <<"reconstruct "<<rr<<endl;
|
|
cout <<"diff " <<r-rr<<endl;
|
|
Vec3<double> eul;
|
|
r.normalize(NULL,true);
|
|
r.normquat2eulerzyx(eul);
|
|
cout<< "euler "<<eul[0]<<" " <<eul[1]<<" "<<eul[2]<<endl;
|
|
Quaternion<double> rback;
|
|
rback.eulerzyx2normquat(eul);
|
|
cout <<"q from euler back "<<endl<<r<<endl<<rback<<endl;
|
|
Mat3<double> rm;
|
|
euler2rotmat((double *)eul,rm,"xyz",false,false,false);
|
|
cout <<rm;
|
|
Vec3<double> eulback;
|
|
rotmat2euler((double *)eulback,rm,"xyz",false,false,false);
|
|
cout <<"euler back from rm error "<<eulback-eul<<endl;
|
|
Vec3<double> axis={0,1/sqrt(2),1/sqrt(2)};
|
|
Quaternion<double> rrr;
|
|
rrr.axis2normquat(axis,0.5);
|
|
NRVec<double> axis2(3);
|
|
double angle;
|
|
rrr.normquat2axis(&axis2[0],angle);
|
|
cout <<"back angle "<<angle<<" "<<axis2<<endl;
|
|
Vec3<double> vec={1,2,3};
|
|
Quaternion<double> qvec(vec);
|
|
Quaternion<double> rvec = qvec.rotateby(rrr);
|
|
Quaternion<double> rvec2 = qvec.rotateby(rrr.conjugate());
|
|
cout <<rvec<<endl;
|
|
cout <<rvec2<<endl;
|
|
Quaternion<double> rrvec = rvec.rotateby(rrr.conjugate());
|
|
cout <<rrvec<<endl;
|
|
Vec3<double> rotvec;
|
|
rrr.rotate(rotvec,vec);
|
|
Quaternion<double> qq={1.5,2,-2,-1.123};
|
|
cout << " test "<<qq*qq<<endl;
|
|
cout <<"exp " <<exp(qq)<< " "<< log(exp(qq))-qq<<endl;
|
|
cout <<"log " <<log(qq)<<" "<< exp(log(qq))-qq<<endl;
|
|
cout <<"pow " <<pow(qq,0.5)<<" " <<pow(qq,0.5)*pow(qq,0.5)-qq<<endl;
|
|
Quaternion<double> qq2={-.5,1,2,3.23};
|
|
Mat3<double> m(1,2,3,4,5,6,7,8,-9);
|
|
NRMat<double> mm(m,3,3);
|
|
Vec3<double> v(10,20,30);
|
|
NRVec<double> vv(v,3);
|
|
cout << m*v<<mm*vv<<endl;
|
|
cout << v*m<<vv*mm<<endl;
|
|
Mat3<double> m2 = m.inverse();
|
|
cout<<m2<<m*m2<<m2*m<<endl;
|
|
NRMat<double> mm2(3,3); mm2=1.;
|
|
multiply_by_inverse(mm2,mm);
|
|
cout <<mm<<endl;
|
|
qq.normalize(NULL,true);
|
|
Vec3<double> xeul,yeul;
|
|
qq.normquat2euler((double *)xeul,"zyx");
|
|
qq.normquat2eulerzyx((double *)yeul);
|
|
cout <<xeul<< " "<<yeul<<endl;
|
|
Quaternion<double> xqq;
|
|
xqq.euler2normquat((double *)xeul,"zyx");
|
|
cout <<"normquat2euler test "<<endl<<qq<<endl<<xqq<<endl<<qq-xqq<<endl;
|
|
}
|
|
|
|
|
|
if(0)
|
|
{
|
|
NRVec<double> a,b,c;
|
|
cin >>a>>b;
|
|
c=a+b;
|
|
cout<<c;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
NRPerm<int> p;
|
|
cin >>p;
|
|
int n=p.size();
|
|
NRVec_from1<double> v(n);
|
|
int i;
|
|
for(i=1; i<=n; ++i) v[i]=10.*i;
|
|
cout <<v.permuted(p);
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
CyclePerm<int> c;
|
|
cin>>c;
|
|
cout<<c<<endl;
|
|
NRPerm<int> p(c);
|
|
cout <<p;
|
|
CyclePerm<int> cc(p);
|
|
cout <<cc<<endl;
|
|
}
|
|
|
|
if(0)
|
|
{
|
|
int seed;
|
|
int f=open("/dev/random",O_RDONLY);
|
|
if(sizeof(int)!=read(f,&seed,sizeof(int))) laerror("cannot read /dev/random");
|
|
close(f);
|
|
srand(seed);
|
|
int n;
|
|
cin >>n;
|
|
NRPerm<int> p(n);
|
|
p.randomize();
|
|
cout <<p;
|
|
CyclePerm<int> cc(p);
|
|
cout <<cc<<endl;
|
|
NRPerm<int> pp(cc,n);
|
|
cout <<pp;
|
|
if(pp!=p) laerror("inconsistency");
|
|
NRVec<double> v(n);
|
|
for(int i=0; i<n; ++i) v[i]=10.*(i+1);
|
|
NRVec<double> vv(v);
|
|
v.permuteme(cc);
|
|
cout <<v;
|
|
NRVec<double> vvv= vv.permuted(pp);
|
|
cout<<vvv;
|
|
cout<<"error "<<(v-vvv).norm()<<endl;
|
|
}
|
|
|
|
if(1)
|
|
{
|
|
int seed;
|
|
int f=open("/dev/random",O_RDONLY);
|
|
if(sizeof(int)!=read(f,&seed,sizeof(int))) laerror("cannot read /dev/random");
|
|
close(f);
|
|
srand(seed);
|
|
int n;
|
|
cin >>n;
|
|
NRVec<double> v(n);
|
|
v.randomize(1.);
|
|
NRVec<double> vv(v);
|
|
NRPerm<int> p(n);
|
|
vv.sort(0,p);
|
|
NRVec<double> vvv=v.permuted(p,true);
|
|
NRVec<double> v4=vv.permuted(p,false);
|
|
cout<<v<<vv;
|
|
cout<<vvv<<v4<<p;
|
|
cout <<"error "<<(vv-vvv).norm() <<" "<<(v-v4).norm()<<endl;
|
|
|
|
}
|
|
|
|
}
|