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linlsq.h
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1 /**********************************************************************
2 * File: linlsq.h (Formerly llsq.h)
3 * Description: Linear Least squares fitting code.
4 * Author: Ray Smith
5 * Created: Thu Sep 12 08:44:51 BST 1991
6 *
7 * (C) Copyright 1991, Hewlett-Packard Ltd.
8 ** Licensed under the Apache License, Version 2.0 (the "License");
9 ** you may not use this file except in compliance with the License.
10 ** You may obtain a copy of the License at
11 ** http://www.apache.org/licenses/LICENSE-2.0
12 ** Unless required by applicable law or agreed to in writing, software
13 ** distributed under the License is distributed on an "AS IS" BASIS,
14 ** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
15 ** See the License for the specific language governing permissions and
16 ** limitations under the License.
17 *
18 **********************************************************************/
19
20 #ifndef TESSERACT_CCSTRUCT_LINLSQ_H_
21 #define TESSERACT_CCSTRUCT_LINLSQ_H_
22
23 #include "points.h"
24 #include "params.h"
25
26 class LLSQ {
27 public:
28 LLSQ() { // constructor
29 clear(); // set to zeros
30 }
31 void clear(); // initialize
32
33 // Adds an element with a weight of 1.
34 void add(double x, double y);
35 // Adds an element with a specified weight.
36 void add(double x, double y, double weight);
37 // Adds a whole LLSQ.
38 void add(const LLSQ& other);
39 // Deletes an element with a weight of 1.
40 void remove(double x, double y);
41 inT32 count() const { // no of elements
42 return static_cast<int>(total_weight + 0.5);
43 }
44
45 double m() const; // get gradient
46 double c(double m) const; // get constant
47 double rms(double m, double c) const; // get error
48 double pearson() const; // get correlation coefficient.
49
50 // Returns the x,y means as an FCOORD.
51 FCOORD mean_point() const;
52 // Returns the direction of the fitted line as a unit vector, using the
53 // least mean squared perpendicular distance. The line runs through the
54 // mean_point, i.e. a point p on the line is given by:
55 // p = mean_point() + lambda * vector_fit() for some real number lambda.
56 // Note that the result (0<=x<=1, -1<=y<=-1) is directionally ambiguous
57 // and may be negated without changing its meaning.
58 FCOORD vector_fit() const;
59 // Returns the covariance.
60 double covariance() const {
61 if (total_weight > 0.0)
62 return (sigxy - sigx * sigy / total_weight) / total_weight;
63 else
64 return 0.0;
65 }
66 double x_variance() const {
67 if (total_weight > 0.0)
68 return (sigxx - sigx * sigx / total_weight) / total_weight;
69 else
70 return 0.0;
71 }
72 double y_variance() const {
73 if (total_weight > 0.0)
74 return (sigyy - sigy * sigy / total_weight) / total_weight;
75 else
76 return 0.0;
77 }
78
79 private:
80 double total_weight; // no of elements or sum of weights.
81 double sigx; // sum of x
82 double sigy; // sum of y
83 double sigxx; // sum x squared
84 double sigxy; // sum of xy
85 double sigyy; // sum y squared
86 };
87
88 #endif // TESSERACT_CCSTRUCT_LINLSQ_H_