Line data    Source code

       1             : /* +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
       2             :    Copyright (c) 2013-2020 The plumed team
       3             :    (see the PEOPLE file at the root of the distribution for a list of names)
       4             : 
       5             :    See http://www.plumed.org for more information.
       6             : 
       7             :    This file is part of plumed, version 2.
       8             : 
       9             :    plumed is free software: you can redistribute it and/or modify
      10             :    it under the terms of the GNU Lesser General Public License as published by
      11             :    the Free Software Foundation, either version 3 of the License, or
      12             :    (at your option) any later version.
      13             : 
      14             :    plumed is distributed in the hope that it will be useful,
      15             :    but WITHOUT ANY WARRANTY; without even the implied warranty of
      16             :    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
      17             :    GNU Lesser General Public License for more details.
      18             : 
      19             :    You should have received a copy of the GNU Lesser General Public License
      20             :    along with plumed.  If not, see <http://www.gnu.org/licenses/>.
      21             : +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ */
      22             : #include "MatrixTimesVectorBase.h"
      23             : #include "core/ActionRegister.h"
      24             : #include "core/ActionShortcut.h"
      25             : #include "core/ActionWithArguments.h"
      26             : #include "core/PlumedMain.h"
      27             : #include "core/ActionSet.h"
      28             : 
      29             : //+PLUMEDOC MCOLVAR MATRIX_VECTOR_PRODUCT
      30             : /*
      31             : Calculate the product of the matrix and the vector
      32             : 
      33             : Thiis action allows you to [multiply](https://en.wikipedia.org/wiki/Matrix_multiplication) a matrix and a vector together.
      34             : This action is primarily used to calculate coordination numbers and symmetry functions, which is what is done by the example below:
      35             : 
      36             : ```plumed
      37             : c1: CONTACT_MATRIX GROUP=1-7 SWITCH={RATIONAL R_0=2.6 NN=6 MM=12}
      38             : ones: ONES SIZE=7
      39             : cc: MATRIX_VECTOR_PRODUCT ARG=c1,ones
      40             : PRINT ARG=cc FILE=colvar
      41             : ```
      42             : 
      43             : Notice that you can use this action to multiply multiple matrices by a single vector as shown below:
      44             : 
      45             : ```plumed
      46             : c1: CONTACT_MATRIX COMPONENTS GROUP=1-7 SWITCH={RATIONAL R_0=2.6 NN=6 MM=12 D_MAX=10.0}
      47             : ones: ONES SIZE=7
      48             : cc: MATRIX_VECTOR_PRODUCT ARG=c1.x,c1.y,c1.z,ones
      49             : PRINT ARG=cc.x,cc.y,cc.z FILE=colvar
      50             : ```
      51             : 
      52             : Notice that if you use this options all the input matrices must have the same sparsity pattern.  This feature
      53             : was implemented in order to making caluclating Steinhardt parameters such as [Q6](Q6.md) straightforward.
      54             : 
      55             : You can also multiply a single matrix by multiple vectors:
      56             : 
      57             : ```plumed
      58             : c1: CONTACT_MATRIX GROUP=1-7 SWITCH={RATIONAL R_0=2.6 NN=6 MM=12 D_MAX=10.0}
      59             : ones: ONES SIZE=7
      60             : twos: CONSTANT VALUES=1,2,3,4,5,6,7
      61             : cc: MATRIX_VECTOR_PRODUCT ARG=c1,ones,twos
      62             : PRINT ARG=cc.ones,cc.twos FILE=colvar
      63             : ```
      64             : 
      65             : This feature was implemented to make calculating local averages of the Steinhard parameters straightforward.
      66             : 
      67             : */
      68             : //+ENDPLUMEDOC
      69             : 
      70             : namespace PLMD {
      71             : namespace matrixtools {
      72             : 
      73             : class MatrixTimesVector : public ActionShortcut {
      74             : public:
      75             :   static void registerKeywords( Keywords& keys );
      76             :   explicit MatrixTimesVector(const ActionOptions&ao);
      77             : };
      78             : 
      79             : PLUMED_REGISTER_ACTION(MatrixTimesVector,"MATRIX_VECTOR_PRODUCT")
      80             : 
      81         687 : void MatrixTimesVector::registerKeywords( Keywords& keys ) {
      82         687 :   ActionShortcut::registerKeywords(keys);
      83             :   // registerLocalKeywords() does not depend on the CV type. Instantiate the
      84             :   // template with a concrete CV that provides performTask()/getAdditionalIndices()
      85             :   // so that the class is well-formed: MSVC instantiates the member bodies
      86             :   // eagerly and would otherwise require those members from PLMD::Vector.
      87         687 :   MatrixTimesVectorBase<MatrixTimesVectorRowSums<double>>::registerLocalKeywords( keys );
      88         687 :   keys.addActionNameSuffix("_ROWSUMS");
      89         687 :   keys.addActionNameSuffix("_ROWSUMSACC");
      90         687 :   keys.addActionNameSuffix("_PROPER");
      91        1374 :   keys.addActionNameSuffix("_PROPERACC");
      92             : 
      93         687 :   if(!keys.exists("USEGPU")) {
      94           0 :     keys.addFlag("USEGPU",false,"run this calculation on the GPU");
      95           0 :     keys.addLinkInDocForFlag("USEGPU","plugin_openaccPTM.md.md");
      96             :   }
      97         687 : }
      98             : 
      99         395 : MatrixTimesVector::MatrixTimesVector( const ActionOptions& ao):
     100             :   Action(ao),
     101         395 :   ActionShortcut(ao) {
     102         395 :   std::vector<std::string> args;
     103         395 :   parseVector("ARG",args);
     104         395 :   std::vector<Value*> myargs;
     105         395 :   ActionWithArguments::interpretArgumentList( args, plumed.getActionSet(), this, myargs );
     106         395 :   std::string usegpustr=" ";
     107             :   {
     108             :     bool usegpu;
     109         395 :     parseFlag("USEGPU",usegpu);
     110         395 :     if( usegpu ) {
     111             :       usegpustr = "ACC ";
     112             :     }
     113             :   }
     114             :   unsigned nvectors=0, nmatrices=0;
     115        2057 :   for(unsigned i=0; i<myargs.size(); ++i) {
     116        1662 :     if( myargs[i]->hasDerivatives() ) {
     117           0 :       error("arguments should be vectors or matrices");
     118             :     }
     119        1662 :     if( myargs[i]->getRank()<=1 ) {
     120         580 :       nvectors++;
     121             :     }
     122        1662 :     if( myargs[i]->getRank()==2 ) {
     123        1082 :       nmatrices++;
     124             :     }
     125             :   }
     126         395 :   std::string argstr = args[0];
     127         975 :   for(unsigned i=1; i<args.size(); ++i) {
     128        1160 :     argstr += "," + args[i];
     129             :   }
     130             : 
     131             :   bool sumrows=false;
     132         395 :   if( nvectors==1 ) {
     133         386 :     unsigned n = myargs.size()-1;
     134        1459 :     for(unsigned i=0; i<n; ++i) {
     135        1073 :       if( myargs[i]->getRank()!=2 || myargs[i]->hasDerivatives() ) {
     136           0 :         error("all arguments other than last argument should be matrices");
     137             :       }
     138        1073 :       if( myargs[n]->getRank()==0 ) {
     139           1 :         if( myargs[i]->getShape()[1]!=1 ) {
     140           0 :           error("number of columns in input matrix does not equal number of elements in vector");
     141             :         }
     142        1072 :       } else if( myargs[i]->getShape()[1]!=myargs[n]->getShape()[0] ) {
     143             :         std::string str_nmat, str_nvec;
     144           0 :         Tools::convert( myargs[i]->getShape()[1], str_nmat);
     145           0 :         Tools::convert( myargs[n]->getShape()[0], str_nvec );
     146           0 :         error("number of columns in input matrix is " + str_nmat + " which does not equal number of elements in vector, which is " + str_nvec);
     147             :       }
     148             :     }
     149         386 :     if( myargs[n]->getRank()>0 ) {
     150         385 :       if( myargs[n]->getRank()!=1 || myargs[n]->hasDerivatives() ) {
     151           0 :         error("last argument to this action should be a vector");
     152             :       }
     153             :     }
     154         386 :     if( (myargs[n]->getPntrToAction())->getName()=="CONSTANT" ) {
     155             :       sumrows=true;
     156         347 :       if( myargs[n]->getRank()==0 ) {
     157           1 :         if( fabs( myargs[n]->get() - 1.0 )>epsilon ) {
     158             :           sumrows = false;
     159             :         }
     160             :       } else {
     161      204311 :         for(unsigned i=0; i<myargs[n]->getShape()[0]; ++i) {
     162      203973 :           if( fabs( myargs[n]->get(i) - 1.0 )>epsilon ) {
     163             :             sumrows=false;
     164             :             break;
     165             :           }
     166             :         }
     167             :       }
     168             :     }
     169         346 :     if( sumrows ) {
     170         678 :       readInputLine( getShortcutLabel() + ": MATRIX_VECTOR_PRODUCT_ROWSUMS"+usegpustr
     171        1356 :                      +"ARG="+ argstr + " " + convertInputLineToString() );
     172             :     } else {
     173          94 :       readInputLine( getShortcutLabel() + ": MATRIX_VECTOR_PRODUCT_PROPER"+usegpustr
     174         188 :                      +"ARG="+ argstr + " " + convertInputLineToString() );
     175             :     }
     176           9 :   } else if( nmatrices==1 ) {
     177           9 :     if( myargs[0]->getRank()!=2 || myargs[0]->hasDerivatives() ) {
     178           0 :       error("first argument to this action should be a matrix");
     179             :     }
     180         203 :     for(unsigned i=1; i<myargs.size(); ++i) {
     181         194 :       if( myargs[i]->getRank()>1 || myargs[i]->hasDerivatives() ) {
     182           0 :         error("all arguments other than first argument should be vectors");
     183             :       }
     184         194 :       if( myargs[i]->getRank()==0 ) {
     185           0 :         if( myargs[0]->getShape()[1]!=1 ) {
     186           0 :           error("number of columns in input matrix does not equal number of elements in vector");
     187             :         }
     188         194 :       } else if( myargs[0]->getShape()[1]!=myargs[i]->getShape()[0] ) {
     189           0 :         error("number of columns in input matrix does not equal number of elements in vector");
     190             :       }
     191             :     }
     192          18 :     readInputLine( getShortcutLabel() + ": MATRIX_VECTOR_PRODUCT_PROPER"+usegpustr
     193          36 :                    +"ARG="+ argstr + " " + convertInputLineToString() );
     194             :   } else {
     195           0 :     error("You should either have one vector or one matrix in input");
     196             :   }
     197         395 : }
     198             : 
     199             : }
     200             : }