UAIWriter_tpl.h

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#ifndef DOXYGEN_SHOULD_SKIP_THIS

#  include <agrum/BN/io/UAI/UAIWriter.h>

namespace gum {

  /*
   * Default constructor.
   */
  template < typename GUM_SCALAR >
  INLINE UAIWriter< GUM_SCALAR >::UAIWriter() {
    GUM_CONSTRUCTOR(UAIWriter);
  }

  /*
   * Destructor.
   */
  template < typename GUM_SCALAR >
  INLINE UAIWriter< GUM_SCALAR >::~UAIWriter() {
    GUM_DESTRUCTOR(UAIWriter);
  }

  /*
   * Writes a bayes net in the given ouput stream.
   *
   * @param output The output stream.
   * @param bn The bayes net writen in the stream.
   * @throws IOError Raised if an I/O error occurs.
   */
  template < typename GUM_SCALAR >
  INLINE void UAIWriter< GUM_SCALAR >::write(std::ostream&                  output,
                                             const IBayesNet< GUM_SCALAR >& bn) {
    if (!output.good()) {
      GUM_ERROR(IOError, "Stream states flags are not all unset.");
    }

    output << __preambule(bn) << std::endl;

    for (auto node : bn.nodes())
      output << __cptBloc(bn, node) << std::endl;

    output << std::endl;

    output.flush();

    if (output.fail()) { GUM_ERROR(IOError, "Writing in the ostream failed."); }
  }

  /*
   * Writes a bayes net in the file referenced by filePath.
   * If the file doesn't exists, it is created.
   * If the file exists, it's content will be erased.
   *
   * @param filePath The path to the file used to write the bayes net.
   * @param bn The bayes net writen in the file.
   * @throw IOError Raised if an I/O error occurs.
   */
  template < typename GUM_SCALAR >
  INLINE void UAIWriter< GUM_SCALAR >::write(const std::string& filePath,
                                             const IBayesNet< GUM_SCALAR >& bn) {
    std::ofstream output(filePath.c_str(), std::ios_base::trunc);

    write(output, bn);

    output.close();

    if (output.fail()) { GUM_ERROR(IOError, "Writing in the ostream failed."); }
  }

  template < typename GUM_SCALAR >
  INLINE std::string
         UAIWriter< GUM_SCALAR >::__preambule(const IBayesNet< GUM_SCALAR >& bn) {
    std::stringstream str;

    str << "BAYES" << std::endl;

    str << bn.size() << std::endl;

    for (auto node : bn.nodes())
      str << bn.variable(node).domainSize() << " ";
    str << std::endl;

    str << bn.size() << std::endl;   // number of potentials

    for (auto node : bn.nodes()) {
      const auto& p = bn.cpt(node);
      str << p.nbrDim() << " ";
      // P(X|Y,Z) has to be written "Y Z X". So we need to keep the first var (X)
      // in order to print it at last
      NodeId first = 0;
      bool   isFirst = true;
      for (auto k : p.variablesSequence()) {
        if (isFirst) {
          isFirst = false;
          first = bn.idFromName(k->name());
        } else {
          str << bn.idFromName(k->name()) << " ";
        }
      }
      str << first << "   # " << bn.variable(node).name() << std::endl;
    }
    str << std::endl;

    return str.str();
  }
  template < typename GUM_SCALAR >
  INLINE std::string
         UAIWriter< GUM_SCALAR >::__cptBloc(const IBayesNet< GUM_SCALAR >& bn,
                                        NodeId                         node) {
    std::stringstream str;

    const auto& p = bn.cpt(node);
    str << p.domainSize();
    Instantiation I(p);
    for (I.setFirst(); !I.end(); ++I) {
      if (I.val(0) == 0) str << std::endl << "  ";
      str << p[I] << " ";
    }
    str << std::endl;

    return str.str();
  }

} /* namespace gum */

#endif   // DOXYGEN_SHOULD_SKIP_THIS