Line data    Source code

       1             : /* +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
       2             :    Copyright (c) 2014-2023 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 "ClusterAnalysisBase.h"
      23             : #include "AdjacencyMatrixVessel.h"
      24             : #include "core/ActionRegister.h"
      25             : 
      26             : //+PLUMEDOC CONCOMP CLUSTER_PROPERTIES
      27             : /*
      28             : Calculate properties of the distribution of some quantities that are part of a connected component
      29             : 
      30             : This collective variable was developed for looking at nucleation phenomena, where you are
      31             : interested in using studying the behavior of atoms in small aggregates or nuclei.  In these sorts of
      32             : problems you might be interested in the degree the atoms in a nucleus have adopted their crystalline
      33             : structure or (in the case of heterogeneous nucleation of a solute from a solvent) you might be
      34             : interested in how many atoms are present in the largest cluster \cite tribello-clustering.
      35             : 
      36             : \par Examples
      37             : 
      38             : The input below calculates the coordination numbers of atoms 1-100 and then computes the an adjacency
      39             : matrix whose elements measures whether atoms \f$i\f$ and \f$j\f$ are within 0.55 nm of each other.  The action
      40             : labelled dfs then treats the elements of this matrix as zero or ones and thus thinks of the matrix as defining
      41             : a graph.  This dfs action then finds the largest connected component in this graph.  The sum of the coordination
      42             : numbers for the atoms in this largest connected component are then computed and this quantity is output to a colvar
      43             : file.  The way this input can be used is described in detail in \cite tribello-clustering.
      44             : 
      45             : \plumedfile
      46             : lq: COORDINATIONNUMBER SPECIES=1-100 SWITCH={CUBIC D_0=0.45  D_MAX=0.55} LOWMEM
      47             : cm: CONTACT_MATRIX ATOMS=lq  SWITCH={CUBIC D_0=0.45  D_MAX=0.55}
      48             : dfs: DFSCLUSTERING MATRIX=cm
      49             : clust1: CLUSTER_PROPERTIES CLUSTERS=dfs CLUSTER=1 SUM
      50             : PRINT ARG=clust1.* FILE=colvar
      51             : \endplumedfile
      52             : 
      53             : */
      54             : //+ENDPLUMEDOC
      55             : 
      56             : namespace PLMD {
      57             : namespace adjmat {
      58             : 
      59             : class ClusterProperties : public ClusterAnalysisBase {
      60             : private:
      61             : /// The cluster we are looking for
      62             :   unsigned clustr;
      63             : public:
      64             : /// Create manual
      65             :   static void registerKeywords( Keywords& keys );
      66             : /// Constructor
      67             :   explicit ClusterProperties(const ActionOptions&);
      68             : /// Do the calculation
      69             :   void calculate() override;
      70             : /// We can use ActionWithVessel to run all the calculation
      71             :   void performTask( const unsigned&, const unsigned&, MultiValue& ) const override;
      72             : };
      73             : 
      74       10473 : PLUMED_REGISTER_ACTION(ClusterProperties,"CLUSTER_PROPERTIES")
      75             : 
      76          28 : void ClusterProperties::registerKeywords( Keywords& keys ) {
      77          28 :   ClusterAnalysisBase::registerKeywords( keys );
      78          56 :   keys.add("compulsory","CLUSTER","1","which cluster would you like to look at 1 is the largest cluster, 2 is the second largest, 3 is the the third largest and so on.");
      79          84 :   keys.use("MEAN"); keys.use("MORE_THAN"); keys.use("LESS_THAN");
      80          84 :   if( keys.reserved("VMEAN") ) keys.use("VMEAN");
      81          84 :   if( keys.reserved("VSUM") ) keys.use("VSUM");
      82         112 :   keys.use("BETWEEN"); keys.use("HISTOGRAM"); keys.use("MOMENTS"); keys.use("ALT_MIN");
      83         140 :   keys.use("MIN"); keys.use("MAX"); keys.use("SUM"); keys.use("LOWEST"); keys.use("HIGHEST");
      84          28 : }
      85             : 
      86          27 : ClusterProperties::ClusterProperties(const ActionOptions&ao):
      87             :   Action(ao),
      88          27 :   ClusterAnalysisBase(ao)
      89             : {
      90             :   // Find out which cluster we want
      91          27 :   parse("CLUSTER",clustr);
      92             : 
      93          27 :   if( clustr<1 ) error("cannot look for a cluster larger than the largest cluster");
      94          27 :   if( clustr>getNumberOfNodes() ) error("cluster selected is invalid - too few atoms in system");
      95             : 
      96             :   // Create all tasks by copying those from underlying DFS object (which is actually MultiColvar)
      97       18214 :   for(unsigned i=0; i<getNumberOfNodes(); ++i) addTaskToList(i);
      98             : 
      99             :   // And now finish the setup of everything in the base
     100          27 :   std::vector<AtomNumber> fake_atoms; setupMultiColvarBase( fake_atoms );
     101          27 : }
     102             : 
     103          34 : void ClusterProperties::calculate() {
     104             :   // Retrieve the atoms in the largest cluster
     105          34 :   std::vector<unsigned> myatoms; retrieveAtomsInCluster( clustr, myatoms );
     106             :   // Activate the relevant tasks
     107          34 :   deactivateAllTasks();
     108        1373 :   for(unsigned i=0; i<myatoms.size(); ++i) taskFlags[myatoms[i]]=1;
     109          34 :   lockContributors();
     110             :   // Now do the calculation
     111          34 :   runAllTasks();
     112          34 : }
     113             : 
     114        1795 : void ClusterProperties::performTask( const unsigned& task_index, const unsigned& current, MultiValue& myvals ) const {
     115        1795 :   std::vector<double> vals( myvals.getNumberOfValues() ); getPropertiesOfNode( current, vals );
     116        1795 :   if( !doNotCalculateDerivatives() ) getNodePropertyDerivatives( current, myvals );
     117        5385 :   for(unsigned k=0; k<vals.size(); ++k) myvals.setValue( k, vals[k] );
     118        1795 : }
     119             : 
     120             : }
     121             : }