Adding correct parsing of the input param

sources/core/data.h

@@ -14,7 +14,7 @@
  */
 class data
 {
-		public: // methods
+	public: // methods
 
 		// Load data from a file
 		virtual void load(const std::string& filename) = 0 ;
@@ -35,18 +35,36 @@ class data
 		virtual vec min() const = 0 ;
 		virtual vec max() const = 0 ;
 
-        virtual int dimX() const { return _nX ; }
-        virtual int dimY() const { return _nY ; }
+		virtual int dimX() const { return _nX ; }
+		virtual int dimY() const { return _nY ; }
 
-        virtual params::input parametrization() const
-        {
-            return params::UNKNOWN_INPUT;
-        }
-	
-    protected: // data
+		//! \brief provide the parametrization of the function.
+		//! \note some function type can modify the parametrization to adapt
+		//! to the data.
+		virtual params::input parametrization() const
+		{
+			return _in_param;
+		}
+
+		//! \brief can set the input parametrization of a non-parametrized
+		//! function. Throw an exception if it tries to erase a previously
+		//! defined one.
+		virtual void setParametrization(params::input new_param)
+		{
+			if(_in_param != params::UNKNOWN_INPUT)
+				throw("A parametrization is already defined");
+
+			_in_param = new_param;
+		}
+
+	protected: // data
 
-        // Dimensions of the data
+		// Dimensions of the data
 		int _nX, _nY ;
+
+		// Input and output parametrization
+		params::input  _in_param ;
+		params::output _out_param ;
 } ;
 	 
 Q_DECLARE_INTERFACE(data, "Fitter.Data")
@@ -60,87 +78,87 @@ Q_DECLARE_INTERFACE(data, "Fitter.Data")
  */
 class data_params : public data
 {
-public: // structures
-
-    //! \brief when changing from a parametrization to another, you might
-    //! lose some dimensions. This list enumerate the different operators
-    //! that can be applied on the raw data to be clusterized.
-    //! \note by default we use <em>none</em>, but if the input space
-    //! dimension is reduced, the program will halt.
-    enum clustrering
-    {
-        MEAN,
-        MEDIAN,
-        NONE
-    };
-
-public: // methods
-
-    //! \brief contructor requires the definition of a base class that
-    //! has a parametrization, and a new parametrization.
-    data_params(const data* d, params::input param,
-                data_params::clustrering method = data_params::NONE) :
-        _d(d), _param_in(param), _clustering_method(method)
-    {
-        _nX = params::dimension(param);
-        _nY = d->dimY();
-
-        if(_nX < _d->dimX() && method == data_params::NONE)
-        {
-            throw("No cluster method provided");
-        }
-    }
-
-    // Load data from a file
-    virtual void load(const std::string& filename)
-    {
-        std::cerr << "<<ERROR>> this data type cannot load data" << std::endl;
-        throw;
-    }
-
-    virtual void load(const std::string& filename, const arguments& args)
-    {
-        std::cerr << "<<ERROR>> this data type cannot load data" << std::endl;
-        throw;
-    }
-
-    // Acces to data
-    virtual vec get(int i) const
-    {
-        vec res(_nX + _nY);
-        vec in = _d->get(i);
-
-        params::convert(&in[0], _d->parametrization(), _param_in, &res[0]);
-        memcpy(&res[_nX], &in[_d->dimX()], _nY*sizeof(double));
-
-        return res;
-    }
-    virtual vec operator[](int i) const
-    {
-        return this->get(i);
-    }
-
-    // Get data size, e.g. the number of samples to fit
-    virtual int size() const
-    {
-        return _d->size();
-    }
-
-    // Get min and max input space values
-    virtual vec min() const
-    {
-        return _d->min();
-    }
-    virtual vec max() const
-    {
-        return _d->max();
-    }
-
-protected: // data
-
-    const data* _d;
-    params::input _param_in;
-    data_params::clustrering _clustering_method;
-
-    //! \todo Add a cluster object that will duplicate data or store indices.
+	public: // structures
+
+		//! \brief when changing from a parametrization to another, you might
+		//! lose some dimensions. This list enumerate the different operators
+		//! that can be applied on the raw data to be clusterized.
+		//! \note by default we use <em>none</em>, but if the input space
+		//! dimension is reduced, the program will halt.
+		enum clustrering
+		{
+			MEAN,
+			MEDIAN,
+			NONE
+		};
+
+	public: // methods
+
+		//! \brief contructor requires the definition of a base class that
+		//! has a parametrization, and a new parametrization.
+		data_params(const data* d, params::input param,
+				data_params::clustrering method = data_params::NONE) :
+			_d(d), _param_in(param), _clustering_method(method)
+		{
+			_nX = params::dimension(param);
+			_nY = d->dimY();
+
+			if(_nX < _d->dimX() && method == data_params::NONE)
+			{
+				throw("No cluster method provided");
+			}
+		}
+
+		// Load data from a file
+		virtual void load(const std::string& filename)
+		{
+			std::cerr << "<<ERROR>> this data type cannot load data" << std::endl;
+			throw;
+		}
+
+		virtual void load(const std::string& filename, const arguments& args)
+		{
+			std::cerr << "<<ERROR>> this data type cannot load data" << std::endl;
+			throw;
+		}
+
+		// Acces to data
+		virtual vec get(int i) const
+		{
+			vec res(_nX + _nY);
+			vec in = _d->get(i);
+
+			params::convert(&in[0], _d->parametrization(), _param_in, &res[0]);
+			memcpy(&res[_nX], &in[_d->dimX()], _nY*sizeof(double));
+
+			return res;
+		}
+		virtual vec operator[](int i) const
+		{
+			return this->get(i);
+		}
+
+		// Get data size, e.g. the number of samples to fit
+		virtual int size() const
+		{
+			return _d->size();
+		}
+
+		// Get min and max input space values
+		virtual vec min() const
+		{
+			return _d->min();
+		}
+		virtual vec max() const
+		{
+			return _d->max();
+		}
+
+	protected: // data
+
+		const data* _d;
+		params::input _param_in;
+		data_params::clustrering _clustering_method;
+
+		//! \todo Add a cluster object that will duplicate data or store indices.
 };

sources/core/vertical_segment.cpp

@@ -72,12 +72,18 @@ void vertical_segment::load(const std::string& filename, const arguments& args)
 				linestream >> t ;
 				vs[current_vs] = t ; ++current_vs ;
 			}
-            else if(comment == std::string("PARAM_IN"))
-            {
-            }
-            else if(comment == std::string("PARAM_OUT"))
-            {
-            }
+         else if(comment == std::string("PARAM_IN"))
+         {
+				std::string param;
+				linestream >> param;
+				_in_param = params::parse_input(param);
+         }
+         else if(comment == std::string("PARAM_OUT"))
+         {
+				std::string param;
+				linestream >> param;
+				_out_param = params::parse_output(param);
+         }
 			continue ;
 		} 
 		else if(line.empty())