pktools  2.6.7
Processing Kernel for geospatial data
ImgRegression.cc
1 /**********************************************************************
2 ImgRegression.cc: class to calculate regression between two raster datasets
3 Copyright (C) 2008-2014 Pieter Kempeneers
4 
5 This file is part of pktools
6 
7 pktools is free software: you can redistribute it and/or modify
8 it under the terms of the GNU General Public License as published by
9 the Free Software Foundation, either version 3 of the License, or
10 (at your option) any later version.
11 
12 pktools is distributed in the hope that it will be useful,
13 but WITHOUT ANY WARRANTY; without even the implied warranty of
14 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
15 GNU General Public License for more details.
16 
17 You should have received a copy of the GNU General Public License
18 along with pktools. If not, see <http://www.gnu.org/licenses/>.
19 ***********************************************************************/
20 #include "ImgRegression.h"
21 #include <iostream>
22 
23 using namespace imgregression;
24 
25 ImgRegression::ImgRegression(void)
26 : m_threshold(0), m_down(1)
27 {}
28 
29 ImgRegression::~ImgRegression(void)
30 {}
31 
32 double ImgRegression::getRMSE(ImgReaderGdal& imgReader1, ImgReaderGdal& imgReader2, double& c0, double& c1, unsigned short band1, unsigned short band2, short verbose) const{
33  c0=0;
34  c1=1;
35  int icol1=0,irow1=0;
36  std::vector<double> rowBuffer1(imgReader1.nrOfCol());
37  std::vector<double> rowBuffer2(imgReader2.nrOfCol());
38  std::vector<double> buffer1;
39  std::vector<double> buffer2;
40 
41  srand(time(NULL));
42  for(irow1=0;irow1<imgReader1.nrOfRow();++irow1){
43  if(irow1%m_down)
44  continue;
45  icol1=0;
46  double icol2=0,irow2=0;
47  double geox=0,geoy=0;
48  imgReader1.readData(rowBuffer1,GDT_Float64,irow1,band1);
49  imgReader1.image2geo(icol1,irow1,geox,geoy);
50  imgReader2.geo2image(geox,geoy,icol2,irow2);
51  icol2=static_cast<int>(icol2);
52  irow2=static_cast<int>(irow2);
53  if(irow2<0||irow2>=imgReader2.nrOfRow())
54  continue;
55  imgReader2.readData(rowBuffer2,GDT_Float64,irow2,band2);
56  for(icol1=0;icol1<imgReader1.nrOfCol();++icol1){
57  if(icol1%m_down)
58  continue;
59  if(m_threshold>0){//percentual value
60  double p=static_cast<double>(rand())/(RAND_MAX);
61  p*=100.0;
62  if(p>m_threshold)
63  continue;//do not select for now, go to next column
64  }
65  imgReader1.image2geo(icol1,irow1,geox,geoy);
66  imgReader2.geo2image(geox,geoy,icol2,irow2);
67  if(icol2<0||icol2>=imgReader2.nrOfCol())
68  continue;
69  icol2=static_cast<int>(icol2);
70  irow2=static_cast<int>(irow2);
71  //check for nodata
72  double value1=rowBuffer1[icol1];
73  double value2=rowBuffer2[icol2];
74  if(imgReader1.isNoData(value1)||imgReader2.isNoData(value2))
75  continue;
76 
77  buffer1.push_back(value1);
78  buffer2.push_back(value2);
79  if(verbose>1)
80  std::cout << geox << " " << geoy << " " << icol1 << " " << irow1 << " " << icol2 << " " << irow2 << " " << buffer1.back() << " " << buffer2.back() << std::endl;
81  }
82  }
83  double err=0;
84  if(buffer1.size()&&buffer2.size()){
86  err=stat.linear_regression_err(buffer1,buffer2,c0,c1);
87  }
88  if(verbose)
89  std::cout << "linear regression based on " << buffer1.size() << " points: " << c0 << "+" << c1 << " * x " << " with rmse: " << err << std::endl;
90  return err;
91 }
92 
93 double ImgRegression::getR2(ImgReaderGdal& imgReader1, ImgReaderGdal& imgReader2, double& c0, double& c1, unsigned short band1, unsigned short band2, short verbose) const{
94  c0=0;
95  c1=1;
96  int icol1=0,irow1=0;
97  std::vector<double> rowBuffer1(imgReader1.nrOfCol());
98  std::vector<double> rowBuffer2(imgReader2.nrOfCol());
99  std::vector<double> buffer1;
100  std::vector<double> buffer2;
101 
102  srand(time(NULL));
103  for(irow1=0;irow1<imgReader1.nrOfRow();++irow1){
104  if(irow1%m_down)
105  continue;
106  icol1=0;
107  double icol2=0,irow2=0;
108  double geox=0,geoy=0;
109  imgReader1.readData(rowBuffer1,GDT_Float64,irow1,band1);
110  imgReader1.image2geo(icol1,irow1,geox,geoy);
111  imgReader2.geo2image(geox,geoy,icol2,irow2);
112  icol2=static_cast<int>(icol2);
113  irow2=static_cast<int>(irow2);
114  if(irow2<0||irow2>=imgReader2.nrOfRow())
115  continue;
116  imgReader2.readData(rowBuffer2,GDT_Float64,irow2,band2);
117  for(icol1=0;icol1<imgReader1.nrOfCol();++icol1){
118  if(icol1%m_down)
119  continue;
120  if(m_threshold>0){//percentual value
121  double p=static_cast<double>(rand())/(RAND_MAX);
122  p*=100.0;
123  if(p>m_threshold)
124  continue;//do not select for now, go to next column
125  }
126  imgReader1.image2geo(icol1,irow1,geox,geoy);
127  imgReader2.geo2image(geox,geoy,icol2,irow2);
128  if(icol2<0||icol2>=imgReader2.nrOfCol())
129  continue;
130  icol2=static_cast<int>(icol2);
131  irow2=static_cast<int>(irow2);
132  //check for nodata
133  double value1=rowBuffer1[icol1];
134  double value2=rowBuffer2[icol2];
135  if(imgReader1.isNoData(value1)||imgReader2.isNoData(value2))
136  continue;
137 
138  buffer1.push_back(value1);
139  buffer2.push_back(value2);
140  if(verbose>1)
141  std::cout << geox << " " << geoy << " " << icol1 << " " << irow1 << " " << icol2 << " " << irow2 << " " << buffer1.back() << " " << buffer2.back() << std::endl;
142  }
143  }
144  double r2=0;
145  if(buffer1.size()&&buffer2.size()){
147  r2=stat.linear_regression(buffer1,buffer2,c0,c1);
148  }
149  if(verbose)
150  std::cout << "linear regression based on " << buffer1.size() << " points: " << c0 << "+" << c1 << " * x " << " with r^2: " << r2 << std::endl;
151  return r2;
152 }
153 
154 double ImgRegression::pgetR2(ImgReaderGdal& imgReader1, ImgReaderGdal& imgReader2, double& c0, double& c1, unsigned short band1, unsigned short band2, short verbose) const{
155  c0=0;
156  c1=1;
157  int icol1=0,irow1=0;
158  std::vector<double> rowBuffer1(imgReader1.nrOfCol());
159  std::vector<double> rowBuffer2(imgReader2.nrOfCol());
160  std::vector<double> buffer1;
161  std::vector<double> buffer2;
162 
163  srand(time(NULL));
164  for(irow1=0;irow1<imgReader1.nrOfRow();++irow1){
165  if(irow1%m_down)
166  continue;
167  icol1=0;
168  double icol2=0,irow2=0;
169  double geox=0,geoy=0;
170  imgReader1.readData(rowBuffer1,GDT_Float64,irow1,band1);
171  imgReader1.image2geo(icol1,irow1,geox,geoy);
172  imgReader2.geo2image(geox,geoy,icol2,irow2);
173  icol2=static_cast<int>(icol2);
174  irow2=static_cast<int>(irow2);
175  if(irow2<0||irow2>=imgReader2.nrOfRow())
176  continue;
177  imgReader2.readData(rowBuffer2,GDT_Float64,irow2,band2);
178  for(icol1=0;icol1<imgReader1.nrOfCol();++icol1){
179  if(icol1%m_down)
180  continue;
181  if(m_threshold>0){//percentual value
182  double p=static_cast<double>(rand())/(RAND_MAX);
183  p*=100.0;
184  if(p>m_threshold)
185  continue;//do not select for now, go to next column
186  }
187  imgReader1.image2geo(icol1,irow1,geox,geoy);
188  imgReader2.geo2image(geox,geoy,icol2,irow2);
189  if(icol2<0||icol2>=imgReader2.nrOfCol())
190  continue;
191  icol2=static_cast<int>(icol2);
192  irow2=static_cast<int>(irow2);
193  //check for nodata
194  double value1=rowBuffer1[icol1];
195  double value2=rowBuffer2[icol2];
196  if(imgReader1.isNoData(value1)||imgReader2.isNoData(value2))
197  continue;
198 
199  buffer1.push_back(value1);
200  buffer2.push_back(value2);
201  if(verbose>1)
202  std::cout << geox << " " << geoy << " " << icol1 << " " << irow1 << " " << icol2 << " " << irow2 << " " << buffer1.back() << " " << buffer2.back() << std::endl;
203  }
204  }
205  double r=0;
206  if(buffer1.size()&&buffer2.size()){
208  r=stat.correlation(buffer1,buffer2);
209  // r=stat.gsl_correlation(buffer1,buffer2);
210  double m1=0;
211  double v1=0;
212  double m2=0;
213  double v2=0;
214  stat.meanVar(buffer1,m1,v1);
215  stat.meanVar(buffer2,m2,v2);
216  if(v1>0){
217  if(r>=0)
218  c1=v2/v1;
219  else
220  c1=-v2/v1;
221  }
222  c0=m2-c1*m1;
223  }
224  if(verbose)
225  std::cout << "orthogonal regression based on " << buffer1.size() << " points: " << c0 << "+" << c1 << " * x " << " with r^2: " << r*r << std::endl;
226  return r*r;
227 }
228 
229 double ImgRegression::getRMSE(ImgReaderGdal& imgReader, unsigned short band1, unsigned short band2, double& c0, double& c1, short verbose) const{
230  c0=0;
231  c1=1;
232  int icol=0,irow=0;
233  std::vector<double> rowBuffer1(imgReader.nrOfCol());
234  std::vector<double> rowBuffer2(imgReader.nrOfCol());
235  std::vector<double> buffer1;
236  std::vector<double> buffer2;
237 
238  srand(time(NULL));
239  assert(band1>=0);
240  assert(band1<imgReader.nrOfBand());
241  assert(band2>=0);
242  assert(band2<imgReader.nrOfBand());
243  for(irow=0;irow<imgReader.nrOfRow();++irow){
244  if(irow%m_down)
245  continue;
246  icol=0;
247  imgReader.readData(rowBuffer1,GDT_Float64,irow,band1);
248  imgReader.readData(rowBuffer2,GDT_Float64,irow,band2);
249  for(icol=0;icol<imgReader.nrOfCol();++icol){
250  if(icol%m_down)
251  continue;
252  if(m_threshold>0){//percentual value
253  double p=static_cast<double>(rand())/(RAND_MAX);
254  p*=100.0;
255  if(p>m_threshold)
256  continue;//do not select for now, go to next column
257  }
258  //check for nodata
259  double value1=rowBuffer1[icol];
260  double value2=rowBuffer2[icol];
261  if(imgReader.isNoData(value1)||imgReader.isNoData(value2))
262  continue;
263 
264  buffer1.push_back(value1);
265  buffer2.push_back(value2);
266  if(verbose>1)
267  std::cout << icol << " " << irow << " " << buffer1.back() << " " << buffer2.back() << std::endl;
268  }
269  }
270  double err=0;
271  if(buffer1.size()&&buffer2.size()){
273  err=stat.linear_regression_err(buffer1,buffer2,c0,c1);
274  }
275  if(verbose)
276  std::cout << "linear regression based on " << buffer1.size() << " points: " << c0 << "+" << c1 << " * x " << " with rmse: " << err << std::endl;
277  return err;
278 }
279 
280 double ImgRegression::getR2(ImgReaderGdal& imgReader, unsigned short band1, unsigned short band2, double& c0, double& c1, short verbose) const{
281  c0=0;
282  c1=1;
283  int icol=0,irow=0;
284  std::vector<double> rowBuffer1(imgReader.nrOfCol());
285  std::vector<double> rowBuffer2(imgReader.nrOfCol());
286  std::vector<double> buffer1;
287  std::vector<double> buffer2;
288 
289  srand(time(NULL));
290  assert(band1>=0);
291  assert(band1<imgReader.nrOfBand());
292  assert(band2>=0);
293  assert(band2<imgReader.nrOfBand());
294  for(irow=0;irow<imgReader.nrOfRow();++irow){
295  if(irow%m_down)
296  continue;
297  icol=0;
298  imgReader.readData(rowBuffer1,GDT_Float64,irow,band1);
299  imgReader.readData(rowBuffer2,GDT_Float64,irow,band2);
300  for(icol=0;icol<imgReader.nrOfCol();++icol){
301  if(icol%m_down)
302  continue;
303  if(m_threshold>0){//percentual value
304  double p=static_cast<double>(rand())/(RAND_MAX);
305  p*=100.0;
306  if(p>m_threshold)
307  continue;//do not select for now, go to next column
308  }
309  //check for nodata
310  double value1=rowBuffer1[icol];
311  double value2=rowBuffer2[icol];
312  if(imgReader.isNoData(value1)||imgReader.isNoData(value2))
313  continue;
314 
315  buffer1.push_back(value1);
316  buffer2.push_back(value2);
317  if(verbose>1)
318  std::cout << icol << " " << irow << " " << buffer1.back() << " " << buffer2.back() << std::endl;
319  }
320  }
321  double r2=0;
322  if(buffer1.size()&&buffer2.size()){
324  r2=stat.linear_regression(buffer1,buffer2,c0,c1);
325  }
326  if(verbose)
327  std::cout << "linear regression based on " << buffer1.size() << " points: " << c0 << "+" << c1 << " * x " << " with r^2: " << r2 << std::endl;
328  return r2;
329 }
330 
331 double ImgRegression::pgetR2(ImgReaderGdal& imgReader, unsigned short band1, unsigned short band2, double& c0, double& c1, short verbose) const{
332  c0=0;
333  c1=1;
334  int icol=0,irow=0;
335  std::vector<double> rowBuffer1(imgReader.nrOfCol());
336  std::vector<double> rowBuffer2(imgReader.nrOfCol());
337  std::vector<double> buffer1;
338  std::vector<double> buffer2;
339 
340  srand(time(NULL));
341  assert(band1>=0);
342  assert(band1<imgReader.nrOfBand());
343  assert(band2>=0);
344  assert(band2<imgReader.nrOfBand());
345  for(irow=0;irow<imgReader.nrOfRow();++irow){
346  if(irow%m_down)
347  continue;
348  icol=0;
349  imgReader.readData(rowBuffer1,GDT_Float64,irow,band1);
350  imgReader.readData(rowBuffer2,GDT_Float64,irow,band2);
351  for(icol=0;icol<imgReader.nrOfCol();++icol){
352  if(icol%m_down)
353  continue;
354  if(m_threshold>0){//percentual value
355  double p=static_cast<double>(rand())/(RAND_MAX);
356  p*=100.0;
357  if(p>m_threshold)
358  continue;//do not select for now, go to next column
359  }
360  //check for nodata
361  double value1=rowBuffer1[icol];
362  double value2=rowBuffer2[icol];
363  if(imgReader.isNoData(value1)||imgReader.isNoData(value2))
364  continue;
365 
366  buffer1.push_back(value1);
367  buffer2.push_back(value2);
368  if(verbose>1)
369  std::cout << icol << " " << irow << " " << buffer1.back() << " " << buffer2.back() << std::endl;
370  }
371  }
372  double r=0;
373  if(buffer1.size()&&buffer2.size()){
375  r=stat.correlation(buffer1,buffer2);
376  // r=stat.gsl_correlation(buffer1,buffer2);
377  double m1=0;
378  double v1=0;
379  double m2=0;
380  double v2=0;
381  stat.meanVar(buffer1,m1,v1);
382  stat.meanVar(buffer2,m2,v2);
383  if(v1>0){
384  if(r>=0)
385  c1=v2/v1;
386  else
387  c1=-v2/v1;
388  }
389  c0=m2-c1*m1;
390  }
391  if(verbose)
392  std::cout << "orthogonal regression based on " << buffer1.size() << " points: " << c0 << "+" << c1 << " * x " << " with r^2: " << r*r << std::endl;
393  return r*r;
394 }
bool isNoData(double value) const
Check if value is nodata in this dataset.
bool geo2image(double x, double y, double &i, double &j) const
Convert georeferenced coordinates (x and y) to image coordinates (column and row) ...
int nrOfBand(void) const
Get the number of bands of this dataset.
int nrOfRow(void) const
Get the number of rows of this dataset.
bool image2geo(double i, double j, double &x, double &y) const
Convert image coordinates (column and row) to georeferenced coordinates (x and y) ...
void readData(T &value, int col, int row, int band=0)
Read a single pixel cell value at a specific column and row for a specific band (all indices start co...
Definition: ImgReaderGdal.h:95
int nrOfCol(void) const
Get the number of columns of this dataset.
Definition: ImgRasterGdal.h:98