Line data    Source code

       1             : /* +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
       2             :    Copyright (c) 2011-2023 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             : #ifndef __PLUMED_function_FunctionOfScalar_h
      23             : #define __PLUMED_function_FunctionOfScalar_h
      24             : 
      25             : #include "Function.h"
      26             : #include "FunctionSetup.h"
      27             : 
      28             : namespace PLMD {
      29             : namespace function {
      30             : 
      31             : /**
      32             : \ingroup INHERIT
      33             : This is the abstract base class to use for implementing new CV function, within it there is
      34             : \ref AddingAFunction "information" as to how to go about implementing a new function.
      35             : */
      36             : 
      37             : template <class T>
      38             : class FunctionOfScalar : public Function {
      39             : private:
      40             : /// Set equal to one if we are doing evaluateGridFunction
      41             :   unsigned argstart;
      42             : /// The function that is being computed
      43             :   T myfunc;
      44             : public:
      45             :   explicit FunctionOfScalar(const ActionOptions&);
      46        1914 :   virtual ~FunctionOfScalar() {}
      47             : /// Get the label to write in the graph
      48             :   std::string writeInGraph() const override ;
      49             :   std::string getOutputComponentDescription( const std::string& cname, const Keywords& keys ) const override ;
      50             :   void calculate() override;
      51             :   static void registerKeywords(Keywords&);
      52             : };
      53             : 
      54             : template <class T>
      55        1948 : void FunctionOfScalar<T>::registerKeywords(Keywords& keys) {
      56        1948 :   Function::registerKeywords(keys);
      57        1948 :   std::string name = keys.getDisplayName();
      58        1948 :   std::size_t und=name.find("_SCALAR");
      59        3896 :   keys.setDisplayName( name.substr(0,und) );
      60        1948 :   keys.add("hidden","NO_ACTION_LOG","suppresses printing from action on the log");
      61        1948 :   T::registerKeywords( keys );
      62        3896 :   if( keys.getDisplayName()=="SUM" ) {
      63           0 :     keys.setValueDescription("scalar","the sum of all the input arguments");
      64        3896 :   } else if( keys.getDisplayName()=="MEAN" ) {
      65           0 :     keys.setValueDescription("scalar","the mean of all the input arguments");
      66        3896 :   } else if( keys.getDisplayName()=="EVALUATE_FUNCTION_FROM_GRID" ) {
      67           8 :     keys.addInputKeyword("compulsory","ARG","scalar/grid","");
      68             :   }
      69        1948 : }
      70             : 
      71             : template <class T>
      72         962 : FunctionOfScalar<T>::FunctionOfScalar(const ActionOptions&ao):
      73             :   Action(ao),
      74             :   Function(ao),
      75         962 :   argstart(0) {
      76             :   // Check if first argument is grid
      77         962 :   if( getPntrToArgument(0)->getRank()>0 && getPntrToArgument(0)->hasDerivatives() ) {
      78           1 :     argstart=1;
      79             :   }
      80             :   // Create the values to hold the output
      81             :   std::vector<std::size_t> shape;
      82         962 :   FunctionData<T>::setup( myfunc, keywords.getOutputComponents(), shape, true, this );
      83         967 : }
      84             : 
      85             : template <class T>
      86           0 : std::string FunctionOfScalar<T>::writeInGraph() const {
      87           0 :   std::size_t und = getName().find_last_of("_");
      88           0 :   return getName().substr(0,und);
      89             : }
      90             : 
      91             : template <class T>
      92           3 : std::string FunctionOfScalar<T>::getOutputComponentDescription( const std::string& cname, const Keywords& keys ) const {
      93           3 :   if( getName().find("SORT")==std::string::npos ) {
      94           0 :     return ActionWithValue::getOutputComponentDescription( cname, keys );
      95             :   }
      96           6 :   return "the " + cname + "th largest of the input scalars";
      97             : }
      98             : 
      99             : template <class T>
     100       93483 : void FunctionOfScalar<T>::calculate() {
     101       93483 :   std::vector<double> args( getNumberOfArguments() - argstart );
     102      213393 :   for(unsigned i=argstart; i<getNumberOfArguments(); ++i) {
     103      119910 :     args[i-argstart]=getPntrToArgument(i)->get();
     104             :   }
     105       93483 :   std::vector<double> vals( getNumberOfComponents() ), deriv( getNumberOfComponents()*args.size() );
     106             :   auto funcout = FunctionOutput::create( getNumberOfComponents(),
     107             :                                          vals.data(),
     108             :                                          args.size(),
     109             :                                          deriv.data() );
     110       93483 :   T::calc( myfunc,
     111       93483 :            doNotCalculateDerivatives(),
     112           0 :            View<const double>(args.data(),args.size()),
     113             :            funcout );
     114      187003 :   for(unsigned i=0; i<vals.size(); ++i) {
     115       93520 :     copyOutput(i)->set(vals[i]);
     116             :   }
     117       93483 :   if( doNotCalculateDerivatives() ) {
     118             :     return;
     119             :   }
     120             :   unsigned dstart = 0;
     121       83238 :   for(unsigned i=0; i<argstart; ++i) {
     122        1675 :     dstart += getPntrToArgument(i)->getNumberOfStoredValues();
     123             :   }
     124             : 
     125      163156 :   for(unsigned i=0; i<vals.size(); ++i) {
     126       81593 :     Value* val = getPntrToComponent(i);
     127      181447 :     for(unsigned j=0; j<args.size(); ++j) {
     128       99854 :       setDerivative( val, dstart+j, funcout.derivs[i][j] );
     129             :     }
     130             :   }
     131             : }
     132             : 
     133             : }
     134             : }
     135             : #endif