Line data    Source code

       1             : /* +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
       2             :    Copyright (c) 2015-2020 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 "core/ActionWithValue.h"
      23             : #include "core/ActionWithArguments.h"
      24             : #include "core/ActionRegister.h"
      25             : #include "core/ActionShortcut.h"
      26             : #include "core/PlumedMain.h"
      27             : #include "multicolvar/MultiColvarShortcuts.h"
      28             : #include "ClusteringBase.h"
      29             : 
      30             : //+PLUMEDOC CONCOMP CLUSTER_DISTRIBUTION
      31             : /*
      32             : Calculate functions of the distribution of properties in your connected components.
      33             : 
      34             : This collective variable was developed for looking at nucleation phenomena, where you are
      35             : interested in using studying the behavior of atoms in small aggregates or nuclei.  In these sorts of
      36             : problems you might be interested in the distribution of the sizes of the clusters in your system.
      37             : A detailed description of this CV can be found in \cite tribello-clustering.
      38             : 
      39             : \par Examples
      40             : 
      41             : The input provided below calculates the local q6 Steinhardt parameter on each atom.  The coordination number
      42             : that atoms with a high value for the local q6 Steinhardt parameter have with other atoms that have a high
      43             : value for the local q6 Steinhardt parameter is then computed.  A contact matrix is then computed that measures
      44             : whether atoms atoms \f$i\f$ and \f$j\f$ have a high value for this coordination number and if they are within
      45             : 3.6 nm of each other.  The connected components of this matrix are then found using a depth first clustering
      46             : algorithm on the corresponding graph. The number of components in this graph that contain more than 27 atoms is then computed.
      47             : As discussed in \cite tribello-clustering an input similar to this one was used to analyze the formation of a polycrystal of GeTe from amorphous
      48             : GeTe.
      49             : 
      50             : \plumedfile
      51             : q6: Q6 SPECIES=1-300 SWITCH={GAUSSIAN D_0=5.29 R_0=0.01 D_MAX=5.3} LOWMEM
      52             : lq6: LOCAL_Q6 SPECIES=q6 SWITCH={GAUSSIAN D_0=5.29 R_0=0.01 D_MAX=5.3} LOWMEM
      53             : flq6: MFILTER_MORE DATA=lq6 SWITCH={GAUSSIAN D_0=0.19 R_0=0.01 D_MAX=0.2}
      54             : cc: COORDINATIONNUMBER SPECIES=flq6 SWITCH={GAUSSIAN D_0=3.59 R_0=0.01 D_MAX=3.6}
      55             : fcc: MFILTER_MORE DATA=cc SWITCH={GAUSSIAN D_0=5.99 R_0=0.01 D_MAX=6.0}
      56             : mat: CONTACT_MATRIX ATOMS=fcc SWITCH={GAUSSIAN D_0=3.59 R_0=0.01 D_MAX=3.6}
      57             : dfs: DFSCLUSTERING MATRIX=mat
      58             : nclust: CLUSTER_DISTRIBUTION CLUSTERS=dfs TRANSFORM={GAUSSIAN D_0=5.99 R_0=0.01 D_MAX=6.0} MORE_THAN={GAUSSIAN D_0=26.99 R_0=0.01 D_MAX=27}
      59             : PRINT ARG=nclust.* FILE=colvar
      60             : \endplumedfile
      61             : 
      62             : */
      63             : //+ENDPLUMEDOC
      64             : 
      65             : //+PLUMEDOC CONCOMP CLUSTER_DISTRIBUTION_CALC
      66             : /*
      67             : Calculate functions of the distribution of properties in your connected components.
      68             : 
      69             : See \ref CLUSTER_DISTRIBUTION
      70             : 
      71             : \par Examples
      72             : 
      73             : */
      74             : //+ENDPLUMEDOC
      75             : 
      76             : 
      77             : namespace PLMD {
      78             : namespace clusters {
      79             : 
      80             : class ClusterDistribution :
      81             :   public ActionWithArguments,
      82             :   public ActionWithValue {
      83             : public:
      84             : /// Create manual
      85             :   static void registerKeywords( Keywords& keys );
      86             : /// Constructor
      87             :   explicit ClusterDistribution(const ActionOptions&);
      88             : /// The number of derivatives
      89             :   unsigned getNumberOfDerivatives() override ;
      90             : /// Do the calculation
      91             :   void calculate() override;
      92             : /// We can use ActionWithVessel to run all the calculation
      93           2 :   void apply() override {}
      94             : };
      95             : 
      96             : PLUMED_REGISTER_ACTION(ClusterDistribution,"CLUSTER_DISTRIBUTION_CALC")
      97             : 
      98           6 : void ClusterDistribution::registerKeywords( Keywords& keys ) {
      99           6 :   Action::registerKeywords( keys );
     100           6 :   ActionWithArguments::registerKeywords( keys );
     101           6 :   ActionWithValue::registerKeywords( keys ); keys.remove("NUMERICAL_DERIVATIVES");
     102          12 :   keys.addInputKeyword("compulsory","CLUSTERS","vector","the label of the action that does the clustering"); keys.setDisplayName("CLUSTER_DISTRIBUTION");
     103          12 :   keys.addInputKeyword("optional","WEIGHTS","vector","use the vector of values calculated by this action as weights rather than giving each atom a unit weight");
     104          12 :   keys.setValueDescription("vector","a vector containing the sum of a atomic-cv that is calculated for each of the identified clusters");
     105           6 : }
     106             : 
     107           2 : ClusterDistribution::ClusterDistribution(const ActionOptions&ao):
     108             :   Action(ao),
     109             :   ActionWithArguments(ao),
     110           2 :   ActionWithValue(ao)
     111             : {
     112             :   // Read in the clustering object
     113           4 :   std::vector<Value*> clusters; parseArgumentList("CLUSTERS",clusters);
     114           2 :   if( clusters.size()!=1 ) error("should pass only one matrix to clustering base");
     115           2 :   ClusteringBase* cc = dynamic_cast<ClusteringBase*>( clusters[0]->getPntrToAction() );
     116           2 :   if( !cc ) error("input to CLUSTERS keyword should be a clustering action");
     117           4 :   std::vector<Value*> weights; parseArgumentList("WEIGHTS",weights);
     118           2 :   if( weights.size()==0 ) {
     119           1 :     log.printf("  using unit weights in cluster distribution \n");
     120           1 :   } else if( weights.size()==1 ) {
     121           1 :     if( weights[0]->getRank()!=1 ) error("input weights has wrong shape");
     122           1 :     if( weights[0]->getShape()[0]!=clusters[0]->getShape()[0] ) error("mismatch between number of weights and number of atoms");
     123           1 :     log.printf("  using weights from action with label %s in cluster distribution \n", weights[0]->getName().c_str() );
     124           1 :     clusters.push_back( weights[0] );
     125             :   } else {
     126           0 :     error("should have only one argument for weights \n");
     127             :   }
     128             :   // Request the arguments
     129           2 :   requestArguments( clusters );
     130           2 :   getPntrToArgument(0)->buildDataStore();
     131           2 :   if( getNumberOfArguments()>1 ) getPntrToArgument(1)->buildDataStore();
     132             :   // Now create the value
     133           2 :   std::vector<unsigned> shape(1); shape[0]=clusters[0]->getShape()[0];
     134           2 :   addValue( shape ); setNotPeriodic(); getPntrToValue()->buildDataStore();
     135           2 : }
     136             : 
     137           0 : unsigned ClusterDistribution::getNumberOfDerivatives() {
     138           0 :   return 0;
     139             : }
     140             : 
     141           2 : void ClusterDistribution::calculate() {
     142           2 :   plumed_assert( getPntrToArgument(0)->valueHasBeenSet() );
     143           2 :   if( getNumberOfArguments()>1 ) plumed_assert( getPntrToArgument(1)->valueHasBeenSet() );
     144           2 :   double csize = getPntrToArgument(0)->get(0);
     145          12 :   for(unsigned i=1; i<getPntrToArgument(0)->getShape()[0]; ++i) {
     146          10 :     if( getPntrToArgument(0)->get(i)>csize ) csize = getPntrToArgument(0)->get(i);
     147             :   }
     148           2 :   unsigned ntasks = static_cast<unsigned>( csize );
     149           8 :   for(unsigned i=0; i<ntasks; ++i) {
     150          42 :     for(unsigned j=0; j<getPntrToArgument(0)->getShape()[0]; ++j) {
     151          36 :       if( fabs(getPntrToArgument(0)->get(j)-i)<epsilon ) {
     152          10 :         if( getNumberOfArguments()==2 ) getPntrToValue()->add( i, getPntrToArgument(1)->get(j) );
     153           5 :         else getPntrToValue()->add( i, 1.0 );
     154             :       }
     155             :     }
     156             :   }
     157           2 : }
     158             : 
     159             : class ClusterDistributionShortcut : public ActionShortcut {
     160             : public:
     161             :   static void registerKeywords( Keywords& keys );
     162             :   ClusterDistributionShortcut(const ActionOptions&);
     163             : };
     164             : 
     165             : PLUMED_REGISTER_ACTION(ClusterDistributionShortcut,"CLUSTER_DISTRIBUTION")
     166             : 
     167           6 : void ClusterDistributionShortcut::registerKeywords( Keywords& keys ) {
     168           6 :   ActionShortcut::registerKeywords( keys );
     169          12 :   keys.add("compulsory","CLUSTERS","the label of the action that does the clustering");
     170          12 :   keys.add("optional","WEIGHTS","use the vector of values calculated by this action as weights rather than giving each atom a unit weight");
     171           6 :   multicolvar::MultiColvarShortcuts::shortcutKeywords( keys );
     172           6 :   keys.addActionNameSuffix("_CALC");
     173           6 : }
     174             : 
     175           2 : ClusterDistributionShortcut::ClusterDistributionShortcut(const ActionOptions&ao):
     176             :   Action(ao),
     177           2 :   ActionShortcut(ao)
     178             : {
     179           2 :   std::map<std::string,std::string> keymap; multicolvar::MultiColvarShortcuts::readShortcutKeywords( keymap, this );
     180           4 :   readInputLine( getShortcutLabel() + ": CLUSTER_DISTRIBUTION_CALC " + convertInputLineToString() );
     181           4 :   multicolvar::MultiColvarShortcuts::expandFunctions( getShortcutLabel(),  getShortcutLabel(),  "", keymap, this );
     182           2 : }
     183             : 
     184             : }
     185             : }