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             : 
      39             : $$
      40             : p(s) =
      41             : \frac
      42             : {1}
      43             : {\sigma \, 2^{\frac{k}{2}}  \,  \Gamma\left(\frac{k}{2}\right) }
      44             : \, \left(\frac{s-a}{\sigma}\right)^{\frac{k}{2}-1} \, \exp\left(- \frac{1}{2}
      45             : \left(\frac{s-a}{\sigma}\right) \right),
      46             : $$
      47             : 
      48             : where $a$ is the minimum of the distribution that is defined on the interval $[a,\infty)$,
      49             : the parameter $k$ (given as a positive integer larger than 2) determines how far
      50             : the peak of the distribution is from the minimum (known as the "degrees of freedom"),
      51             : and the parameter $\sigma>0$ determines the broadness of the distribution.
      52             : 
      53             : The minimum $a$ is given using the MINIMUM keyword, the parameter $k$ is given
      54             : using the KAPPA keyword, and the parameter $\sigma$ is given using the SIGMA keyword.
      55             : 
      56             : This target distribution action is only defined for one dimension, for multiple dimensions
      57             : it should be used in combination with the [TD_PRODUCT_DISTRIBUTION](TD_PRODUCT_DISTRIBUTION.md) action.
      58             : 
      59             : ## Examples
      60             : 
      61             : Chi-squared distribution with $a=-10.0$, $\sigma=2.0$, and $k=2$
      62             : 
      63             : ```plumed
      64             : td: TD_CHISQUARED  MINIMUM=-10.0  SIGMA=2.0  KAPPA=2
      65             : ```
      66             : 
      67             : The Chi-squared distribution is only defined for one dimension so for multiple
      68             : dimensions we have to use it in combination with the [TD_PRODUCT_DISTRIBUTION](TD_PRODUCT_DISTRIBUTION.md) action as shown in
      69             : the following example where we have a Chi-squared distribution for argument 1
      70             : and uniform distribution for argument 2
      71             : 
      72             : ```plumed
      73             : td_chisq: TD_CHISQUARED  MINIMUM=10.0  SIGMA=2.0  KAPPA=2
      74             : 
      75             : td_uni: TD_UNIFORM
      76             : 
      77             : td_pd: TD_PRODUCT_DISTRIBUTION DISTRIBUTIONS=td_chisq,td_uni
      78             : ```
      79             : 
      80             : */
      81             : //+ENDPLUMEDOC
      82             : 
      83             : class TD_ChiSquared: public TargetDistribution {
      84             :   std::vector<double> minima_;
      85             :   std::vector<double> sigma_;
      86             :   std::vector<double> kappa_;
      87             :   std::vector<double> normalization_;
      88             : public:
      89             :   static void registerKeywords(Keywords&);
      90             :   explicit TD_ChiSquared(const ActionOptions& ao);
      91             :   double getValue(const std::vector<double>&) const override;
      92             : };
      93             : 
      94             : 
      95             : PLUMED_REGISTER_ACTION(TD_ChiSquared,"TD_CHISQUARED")
      96             : 
      97             : 
      98          11 : void TD_ChiSquared::registerKeywords(Keywords& keys) {
      99          11 :   TargetDistribution::registerKeywords(keys);
     100          11 :   keys.add("compulsory","MINIMUM","The minimum of the chi-squared distribution.");
     101          11 :   keys.add("compulsory","SIGMA","The sigma parameter of the chi-squared distribution given as a positive number.");
     102          11 :   keys.add("compulsory","KAPPA","The k parameter of the chi-squared distribution given as positive integer larger than 2.");
     103          11 :   keys.use("WELLTEMPERED_FACTOR");
     104          11 :   keys.use("SHIFT_TO_ZERO");
     105          11 :   keys.use("NORMALIZE");
     106          11 : }
     107             : 
     108             : 
     109           9 : TD_ChiSquared::TD_ChiSquared(const ActionOptions& ao):
     110             :   PLUMED_VES_TARGETDISTRIBUTION_INIT(ao),
     111          18 :   minima_(0),
     112           9 :   sigma_(0),
     113           9 :   kappa_(0),
     114          18 :   normalization_(0) {
     115           9 :   parseVector("MINIMUM",minima_);
     116           9 :   parseVector("SIGMA",sigma_);
     117          18 :   for(unsigned int k=0; k<sigma_.size(); k++) {
     118           9 :     if(sigma_[k] < 0.0) {
     119           0 :       plumed_merror(getName()+": the value given in SIGMA should be positive.");
     120             :     }
     121             :   }
     122             : 
     123           9 :   std::vector<unsigned int> kappa_int(0);
     124          18 :   parseVector("KAPPA",kappa_int);
     125           9 :   if(kappa_int.size()==0) {
     126           0 :     plumed_merror(getName()+": some problem with KAPPA keyword, should given as positive integer larger than 2");
     127             :   }
     128           9 :   kappa_.resize(kappa_int.size());
     129          18 :   for(unsigned int k=0; k<kappa_int.size(); k++) {
     130           9 :     if(kappa_int[k] < 2) {
     131           0 :       plumed_merror(getName()+": KAPPA should be an integer 2 or higher");
     132             :     }
     133           9 :     kappa_[k] = static_cast<double>(kappa_int[k]);
     134             :   }
     135             : 
     136           9 :   setDimension(minima_.size());
     137           9 :   if(getDimension()>1) {
     138           0 :     plumed_merror(getName()+": only defined for one dimension, for multiple dimensions it should be used in combination with the TD_PRODUCT_DISTRIBUTION action.");
     139             :   }
     140           9 :   if(sigma_.size()!=getDimension()) {
     141           0 :     plumed_merror(getName()+": the SIGMA keyword does not match the given dimension in MINIMUM");
     142             :   }
     143           9 :   if(kappa_.size()!=getDimension()) {
     144           0 :     plumed_merror(getName()+": the KAPPA keyword does not match the given dimension in MINIMUM");
     145             :   }
     146             : 
     147           9 :   normalization_.resize(getDimension());
     148          18 :   for(unsigned int k=0; k<getDimension(); k++) {
     149           9 :     normalization_[k] = 1.0/(pow(2.0,0.5*kappa_[k])*tgamma(0.5*kappa_[k])*sigma_[k]);
     150             :   }
     151           9 :   checkRead();
     152           9 : }
     153             : 
     154             : 
     155        1509 : double TD_ChiSquared::getValue(const std::vector<double>& argument) const {
     156             :   double value = 1.0;
     157        3018 :   for(unsigned int k=0; k<argument.size(); k++) {
     158        1509 :     double arg=(argument[k]-minima_[k])/sigma_[k];
     159        1509 :     if(arg<0.0) {
     160           0 :       plumed_merror(getName()+": the chi-squared istribution is not defined for values less that ones given in MINIMUM");
     161             :     }
     162        1509 :     value *= normalization_[k] * pow(arg,0.5*kappa_[k]-1.0) * exp(-0.5*arg);
     163             :   }
     164        1509 :   return value;
     165             : }
     166             : 
     167             : 
     168             : }
     169             : }