scaling_layer.h

//   OpenNN: Open Neural Networks Library
//   www.opennn.net
//
//   S C A L I N G   L A Y E R   C L A S S   H E A D E R                   
//
//   Artificial Intelligence Techniques SL
//   artelnics@artelnics.com
 
#ifndef SCALINGLAYER_H
#define SCALINGLAYER_H
 
// System includes
 
#include <cmath>
#include <cstdlib>
#include <fstream>
#include <iostream>
#include <string>
#include <sstream>
 
// OpenNN includes
 
#include "layer.h"
#include "statistics.h"
#include "scaling.h"
#include "opennn_strings.h"
 
namespace OpenNN
{
 
 
 
class ScalingLayer : public Layer
{
 
public:
 
   // Constructors
 
   explicit ScalingLayer();
 
   explicit ScalingLayer(const Index&);
   explicit ScalingLayer(const Tensor<Index, 1>&);
 
   explicit ScalingLayer(const Tensor<Descriptives, 1>&);
 
   // Destructors
 
   virtual ~ScalingLayer();
 
   // Get methods
   
   Tensor<Index, 1> get_outputs_dimensions() const;
 
   Index get_inputs_number() const;
   Index get_neurons_number() const;
 
   // Inputs descriptives
 
   Tensor<Descriptives, 1> get_descriptives() const;
   Descriptives get_descriptives(const Index&) const;
 
   Tensor<type, 1> get_minimums() const;
   Tensor<type, 1> get_maximums() const;
   Tensor<type, 1> get_means() const;
   Tensor<type, 1> get_standard_deviations() const;
 
   // Variables scaling and unscaling
 
   const Tensor<Scaler, 1> get_scaling_methods() const;
 
   Tensor<string, 1> write_scalers() const;
   Tensor<string, 1> write_scalers_text() const;
 
   // Display messages
 
   const bool& get_display() const;
 
   // Set methods
 
   void set();
   void set(const Index&);
   void set(const Tensor<Index, 1>&);
   void set(const Tensor<Descriptives, 1>&);
   void set(const Tensor<Descriptives, 1>&, const Tensor<Scaler, 1>&);
   void set(const tinyxml2::XMLDocument&);
 
   void set_inputs_number(const Index&);
   void set_neurons_number(const Index&);
 
   void set_default();
 
   // Descriptives
 
   void set_descriptives(const Tensor<Descriptives, 1>&);
   void set_item_descriptives(const Index&, const Descriptives&);
 
   void set_minimum(const Index&, const type&);
   void set_maximum(const Index&, const type&);
   void set_mean(const Index&, const type&);
   void set_standard_deviation(const Index&, const type&);
 
   void set_min_max_range(const type& min, const type& max);
 
   // Scaling method
 
   void set_scalers(const Tensor<Scaler, 1>&);
   void set_scalers(const Tensor<string, 1>&);
 
   void set_scalers(const Scaler&);
   void set_scalers(const string&);
 
   // Display messages
 
   void set_display(const bool&);
 
   // Check methods
 
   bool is_empty() const;
 
   void check_range(const Tensor<type, 1>&) const;
 
   Tensor<type, 2> calculate_outputs(const Tensor<type, 2>&);
   Tensor<type, 4> calculate_outputs(const Tensor<type, 4>&);
 
   // Expression methods
 
   string write_no_scaling_expression(const Tensor<string, 1>&, const Tensor<string, 1>&) const;
 
   string write_minimum_maximum_expression(const Tensor<string, 1>&, const Tensor<string, 1>&) const;
 
   string write_mean_standard_deviation_expression(const Tensor<string, 1>&, const Tensor<string, 1>&) const;
 
   string write_standard_deviation_expression(const Tensor<string, 1>&, const Tensor<string, 1>&) const;
 
   string write_expression(const Tensor<string, 1>&, const Tensor<string, 1>&) const;
 
   string write_expression_c() const;
 
   string write_expression_python() const;
 
   // Serialization methods
   
   virtual void from_XML(const tinyxml2::XMLDocument&);
 
   void write_XML(tinyxml2::XMLPrinter&) const;
 
protected:
 
   Tensor<Index, 1> input_variables_dimensions;
 
 
   Tensor<Descriptives, 1> descriptives;
 
 
   Tensor<Scaler, 1> scalers;
 
 
   type min_range;
   type max_range;
 
 
   bool display = true;
 
};
 
}
 
#endif
 
 
// OpenNN: Open Neural Networks Library.
// Copyright(C) 2005-2021 Artificial Intelligence Techniques, SL.
//
// This library is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 2.1 of the License, or any later version.
//
// This library is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
// Lesser General Public License for more details.
 
// You should have received a copy of the GNU Lesser General Public
// License along with this library; if not, write to the Free Software
 
// Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA  02110-1301  USA