DGtal  0.9.2
OrderedLinearRegression.h
1 
17 #pragma once
18 
34 #if defined(OrderedLinearRegression_RECURSES)
35 #error Recursive header files inclusion detected in OrderedLinearRegression.h
36 #else // defined(OrderedLinearRegression_RECURSES)
37 
38 #define OrderedLinearRegression_RECURSES
39 
40 #if !defined OrderedLinearRegression_h
41 
42 #define OrderedLinearRegression_h
43 
44 
46 #include <iostream>
47 #include <vector>
48 #include "DGtal/math/SimpleLinearRegression.h"
50 namespace DGtal
51 {
53  // class OrderedLinearRegression
55 
66  {
67  // ----------------------- Standard services ------------------------------
68  public:
69 
74  {}
75 
83  OrderedLinearRegression( double eps_zero = 1e-8 ):
84  myEpsilonZero(eps_zero),
85  myN(0)
86  {}
87 
91  void clear()
92  {
93  myX.clear();
94  myY.clear();
95  myN = 0;
96  }
97 
110  template <class XIterator, class YIterator>
111  void addSamples( XIterator begin_x, XIterator end_x, YIterator begin_y )
112  {
113  for ( ; begin_x != end_x; ++begin_x, ++begin_y )
114  {
115  addSample( *begin_x, *begin_y );
116  }
117  }
118 
119 
131  void addSample( const double x, const double y )
132  {
133  myX.push_back( x );
134  myY.push_back( y );
135  ++myN;
136  }
137 
138 
139  // ----------------------- Interface --------------------------------------
158  const unsigned int n = 4,
159  const double alpha = 0.01) const
160  {
161  linearModel.setEpsilonZero(myEpsilonZero);
162  linearModel.clear();
163  std::vector<double>::const_iterator itx = myX.begin();
164  std::vector<double>::const_iterator itxe = myX.end();
165  std::vector<double>::const_iterator ity = myY.begin();
166  linearModel.addSamples( itx, itx + n, ity );
167  linearModel.computeRegression();
168  itx += n;
169  ity += n;
170  unsigned int l = myX.size() - n + 1;
171  for ( ; itx != itxe; ++itx, ++ity, --l )
172  {
173  std::pair<double,double> ic;
174  ic = linearModel.trustIntervalForY( *itx, alpha );
175  if ( ( *ity < ic.first ) || ( *ity > ic.second ) )
176  break;
177  linearModel.addSample( *itx, *ity );
178  linearModel.computeRegression();
179  }
180  }
181 
182 
201  const unsigned int n = 4,
202  const double alpha = 0.01 ) const
203  {
204  linearModel.setEpsilonZero(myEpsilonZero);
205  linearModel.clear();
206  std::vector<double>::const_reverse_iterator itx = myX.rbegin();
207  std::vector<double>::const_reverse_iterator itxe = myX.rend();
208  std::vector<double>::const_reverse_iterator ity = myY.rbegin();
209  linearModel.addSamples( itx, itx + n, ity );
210  linearModel.computeRegression();
211  itx += n;
212  ity += n;
213  unsigned int l = myX.size() - n + 1;
214  for ( ; itx != itxe; ++itx, ++ity, --l )
215  {
216  std::pair<double,double> ic;
217  ic = linearModel.trustIntervalForY( *itx, alpha );
218  if ( ( *ity < ic.first ) || ( *ity > ic.second ) )
219  break;
220  linearModel.addSample( *itx, *ity );
221  linearModel.computeRegression();
222  }
223  }
224 
225  // ----------------------- Interface --------------------------------------
226  public:
227 
232  void selfDisplay( std::ostream & that_stream ) const
233  {
234  that_stream << "[OrderedLinearRegression] Number of samples="<< myN;
235  }
236 
241  bool isValid() const
242  {
243  return true;
244  }
245 
246 
247  // ------------------------- Datas ----------------------------------------
248 
249  private:
250 
253 
255  unsigned int myN;
256 
258  std::vector<double> myY;
259 
261  std::vector<double> myX;
262 
263 
264  // ------------------------- Hidden services ------------------------------
265  protected:
266 
267  private:
268 
275 
283 
284  // ------------------------- Internals ------------------------------------
285  private:
286 
287 
288  };
289 
296  std::ostream&
297  operator<<( std::ostream & that_stream,
298  const OrderedLinearRegression & that_object_to_display );
299 
300 
301 } // namespace DGtal
302 
303 // //
305 #endif // !defined OrderedLinearRegression_h
306 
307 #undef OrderedLinearRegression_RECURSES
308 #endif // else defined(OrderedLinearRegression_RECURSES)
void backwardSLR(SimpleLinearRegression &linearModel, const unsigned int n=4, const double alpha=0.01) const
OrderedLinearRegression(double eps_zero=1e-8)
std::pair< double, double > trustIntervalForY(const double x, const double a) const
std::vector< double > myY
Ordinate values of sample points.
Description of class 'SimpleLinearRegression'.
Description of class 'OrderedLinearRegression'.
double myEpsilonZero
Epsilon zero value.
std::ostream & operator<<(std::ostream &out, const ClosedIntegerHalfPlane< TSpace > &object)
OrderedLinearRegression & operator=(const OrderedLinearRegression &other)
void addSample(const double x, const double y)
DGtal is the top-level namespace which contains all DGtal functions and types.
void forwardSLR(SimpleLinearRegression &linearModel, const unsigned int n=4, const double alpha=0.01) const
void addSample(const double x, const double y)
unsigned int myN
Number of samples.
void addSamples(XIterator begin_x, XIterator end_x, YIterator begin_y)
void addSamples(XIterator begin_x, XIterator end_x, YIterator begin_y)
std::vector< double > myX
Abscissa values of sample points.
void setEpsilonZero(const double aEpsilonZero)
void selfDisplay(std::ostream &that_stream) const