Line data    Source code

       1             : /* +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
       2             :    Copyright (c) 2016-2021 The VES code team
       3             :    (see the PEOPLE-VES file at the root of this folder for a list of names)
       4             : 
       5             :    See http://www.ves-code.org for more information.
       6             : 
       7             :    This file is part of VES code module.
       8             : 
       9             :    The VES code module 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             :    The VES code module 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 the VES code module.  If not, see <http://www.gnu.org/licenses/>.
      21             : +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ */
      22             : 
      23             : #include "TargetDistribution.h"
      24             : 
      25             : #include "core/ActionRegister.h"
      26             : 
      27             : 
      28             : namespace PLMD {
      29             : namespace ves {
      30             : 
      31             : //+PLUMEDOC VES_TARGETDIST TD_CHISQUARED
      32             : /*
      33             : Chi-squared distribution (static).
      34             : 
      35             : Employ a target distribution given by a
      36             : [chi-squared distribution](https://en.wikipedia.org/wiki/Chi-squared_distribution)
      37             : that is defined as
      38             : \f[
      39             : p(s) =
      40             : \frac
      41             : {1}
      42             : {\sigma \, 2^{\frac{k}{2}}  \,  \Gamma\left(\frac{k}{2}\right) }
      43             : \, \left(\frac{s-a}{\sigma}\right)^{\frac{k}{2}-1} \, \exp\left(- \frac{1}{2}
      44             : \left(\frac{s-a}{\sigma}\right) \right),
      45             : \f]
      46             : where \f$a\f$ is the minimum of the distribution that is defined on the interval \f$[a,\infty)\f$,
      47             : the parameter \f$k\f$ (given as a positive integer larger than 2) determines how far
      48             : the peak of the distribution is from the minimum (known as the "degrees of freedom"),
      49             : and the parameter \f$\sigma>0\f$ determines the broadness of the distribution.
      50             : 
      51             : The minimum \f$a\f$ is given using the MINIMUM keyword, the parameter \f$k\f$ is given
      52             : using the KAPPA keyword, and the parameter \f$\sigma\f$ is given using the SIGMA keyword.
      53             : 
      54             : This target distribution action is only defined for one dimension, for multiple dimensions
      55             : it should be used in combination with the \ref TD_PRODUCT_DISTRIBUTION action.
      56             : 
      57             : \par Examples
      58             : 
      59             : Chi-squared distribution with \f$a=-10.0\f$, \f$\sigma=2.0\f$, and \f$k=2\f$
      60             : \plumedfile
      61             : td: TD_CHISQUARED  MINIMUM=-10.0  SIGMA=2.0  KAPPA=2
      62             : \endplumedfile
      63             : 
      64             : The Chi-squared distribution is only defined for one dimension so for multiple
      65             : dimensions we have to use it in combination with the \ref TD_PRODUCT_DISTRIBUTION action as shown in
      66             : the following example where we have a Chi-squared distribution for argument 1
      67             : and uniform distribution for argument 2
      68             : \plumedfile
      69             : td_chisq: TD_CHISQUARED  MINIMUM=10.0  SIGMA=2.0  KAPPA=2
      70             : 
      71             : td_uni: TD_UNIFORM
      72             : 
      73             : td_pd: TD_PRODUCT_DISTRIBUTION DISTRIBUTIONS=td_chisq,td_uni
      74             : \endplumedfile
      75             : 
      76             : */
      77             : //+ENDPLUMEDOC
      78             : 
      79             : class TD_ChiSquared: public TargetDistribution {
      80             :   std::vector<double> minima_;
      81             :   std::vector<double> sigma_;
      82             :   std::vector<double> kappa_;
      83             :   std::vector<double> normalization_;
      84             : public:
      85             :   static void registerKeywords(Keywords&);
      86             :   explicit TD_ChiSquared(const ActionOptions& ao);
      87             :   double getValue(const std::vector<double>&) const override;
      88             : };
      89             : 
      90             : 
      91             : PLUMED_REGISTER_ACTION(TD_ChiSquared,"TD_CHISQUARED")
      92             : 
      93             : 
      94          11 : void TD_ChiSquared::registerKeywords(Keywords& keys) {
      95          11 :   TargetDistribution::registerKeywords(keys);
      96          22 :   keys.add("compulsory","MINIMUM","The minimum of the chi-squared distribution.");
      97          22 :   keys.add("compulsory","SIGMA","The sigma parameter of the chi-squared distribution given as a positive number.");
      98          22 :   keys.add("compulsory","KAPPA","The k parameter of the chi-squared distribution given as positive integer larger than 2.");
      99          11 :   keys.use("WELLTEMPERED_FACTOR");
     100          11 :   keys.use("SHIFT_TO_ZERO");
     101          11 :   keys.use("NORMALIZE");
     102          11 : }
     103             : 
     104             : 
     105           9 : TD_ChiSquared::TD_ChiSquared(const ActionOptions& ao):
     106             :   PLUMED_VES_TARGETDISTRIBUTION_INIT(ao),
     107          18 :   minima_(0),
     108           9 :   sigma_(0),
     109           9 :   kappa_(0),
     110          18 :   normalization_(0)
     111             : {
     112           9 :   parseVector("MINIMUM",minima_);
     113           9 :   parseVector("SIGMA",sigma_);
     114          18 :   for(unsigned int k=0; k<sigma_.size(); k++) {
     115           9 :     if(sigma_[k] < 0.0) {plumed_merror(getName()+": the value given in SIGMA should be positive.");}
     116             :   }
     117             : 
     118           9 :   std::vector<unsigned int> kappa_int(0);
     119          18 :   parseVector("KAPPA",kappa_int);
     120           9 :   if(kappa_int.size()==0) {plumed_merror(getName()+": some problem with KAPPA keyword, should given as positive integer larger than 2");}
     121           9 :   kappa_.resize(kappa_int.size());
     122          18 :   for(unsigned int k=0; k<kappa_int.size(); k++) {
     123           9 :     if(kappa_int[k] < 2) {plumed_merror(getName()+": KAPPA should be an integer 2 or higher");}
     124           9 :     kappa_[k] = static_cast<double>(kappa_int[k]);
     125             :   }
     126             : 
     127           9 :   setDimension(minima_.size());
     128           9 :   if(getDimension()>1) {plumed_merror(getName()+": only defined for one dimension, for multiple dimensions it should be used in combination with the TD_PRODUCT_DISTRIBUTION action.");}
     129           9 :   if(sigma_.size()!=getDimension()) {plumed_merror(getName()+": the SIGMA keyword does not match the given dimension in MINIMUM");}
     130           9 :   if(kappa_.size()!=getDimension()) {plumed_merror(getName()+": the KAPPA keyword does not match the given dimension in MINIMUM");}
     131             : 
     132           9 :   normalization_.resize(getDimension());
     133          18 :   for(unsigned int k=0; k<getDimension(); k++) {
     134           9 :     normalization_[k] = 1.0/(pow(2.0,0.5*kappa_[k])*tgamma(0.5*kappa_[k])*sigma_[k]);
     135             :   }
     136           9 :   checkRead();
     137           9 : }
     138             : 
     139             : 
     140        1509 : double TD_ChiSquared::getValue(const std::vector<double>& argument) const {
     141             :   double value = 1.0;
     142        3018 :   for(unsigned int k=0; k<argument.size(); k++) {
     143        1509 :     double arg=(argument[k]-minima_[k])/sigma_[k];
     144        1509 :     if(arg<0.0) {plumed_merror(getName()+": the chi-squared istribution is not defined for values less that ones given in MINIMUM");}
     145        1509 :     value *= normalization_[k] * pow(arg,0.5*kappa_[k]-1.0) * exp(-0.5*arg);
     146             :   }
     147        1509 :   return value;
     148             : }
     149             : 
     150             : 
     151             : }
     152             : }