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comparison m-toolbox/test/test_smodel_double.m @ 0:f0afece42f48

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author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 23 Nov 2011 19:22:13 +0100
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1 % test_smodel_double tests the double method of the SMODEL class.
2 %
3 % M Hueller 02-05-2011
4 %
5 % $Id: test_smodel_double.m,v 1.2 2011/05/05 21:04:13 mauro Exp $
6 %
7 function results = test_smodel_double(varargin)
8
9 %% List of runs
10 if nargin == 1
11 list = varargin{1};
12 if isa(list, 'cell')
13 list = list{:};
14 end
15 else
16 list = [];
17 end
18
19 if isempty(list)
20 list = [10 11 20 21 30 31 40 41 50 51];
21 end
22
23 %% Run tests
24 results = [];
25
26 %% 10 Oscillator step, default values
27 test = 10;
28 if any(ismember(list, test))
29
30 % Pick the model
31 model_def = 'oscillator_step';
32
33 % Decide the tolerance of the test ([] or 0 for no tolerance)
34 TOL = 0;
35
36 % Set parameters: duration and rate
37 nsecs = 100;
38 fs = 1;
39
40 % Extract the information from the ao model default plist
41 ao_mdl_info = eval(['ao_model_' model_def '(''info'')']);
42 pl = ao_mdl_info.plists;
43
44 F0 = find(pl, 'F0');
45 toff = find(pl, 'toff');
46 m = find(pl, 'm');
47 k = find(pl, 'k');
48 tau = find(pl, 'tau');
49 x0 = find(pl, 'x0');
50 v0 = find(pl, 'v0');
51
52 % Build the ao model
53 ao_mdl = ao(plist('built-in', model_def, 'nsecs', nsecs, 'fs', fs));
54
55 % Build the smodel model
56 smodel_mdl = smodel(plist('built-in', model_def));
57
58 % Set smodel parameters
59 smodel_mdl.setParameters({'m','k','tau','F0','x0','v0','toff'}, {m,k,tau,F0,x0,v0,toff});
60
61 % Set smodel xvals
62 smodel_mdl.setXvals(ao_mdl.x);
63
64 % Eval the smodel
65 d = smodel_mdl.double();
66
67 % Compare the numbers
68 results = [results; test check_correctness(d, ao_mdl.y, plist('tolerance', TOL))];
69 end
70
71 %% 11 Oscillator step, high fs and high nsecs
72 test = 11;
73 if any(ismember(list, test))
74
75 % Pick the model
76 model_def = 'oscillator_step';
77
78 % Decide the tolerance of the test ([] or 0 for no tolerance)
79 TOL = 0;
80
81 % Set parameters: duration and rate
82 nsecs = 10000;
83 fs = 1000;
84
85 % Extract the information from the ao model default plist
86 ao_mdl_info = eval(['ao_model_' model_def '(''info'')']);
87 pl = ao_mdl_info.plists;
88
89 F0 = find(pl, 'F0');
90 toff = find(pl, 'toff');
91 m = find(pl, 'm');
92 k = find(pl, 'k');
93 tau = find(pl, 'tau');
94 x0 = find(pl, 'x0');
95 v0 = find(pl, 'v0');
96
97 % Build the ao model
98 ao_mdl = ao(plist('built-in', model_def, 'nsecs', nsecs, 'fs', fs));
99
100 % Build the smodel model
101 smodel_mdl = smodel(plist('built-in', model_def));
102
103 % Set smodel parameters
104 smodel_mdl.setParameters({'m','k','tau','F0','x0','v0','toff'}, {m,k,tau,F0,x0,v0,toff});
105
106 % Set smodel xvals
107 smodel_mdl.setXvals(ao_mdl.x);
108
109 % Eval the smodel
110 d = smodel_mdl.double();
111
112 % Compare the numbers
113 results = [results; test check_correctness(d, ao_mdl.y, plist('tolerance', TOL))];
114 end
115
116 %% 20 Oscillator sine, default values
117 test = 20;
118 if any(ismember(list, test))
119
120 % Pick the model
121 model_def = 'oscillator_sine';
122
123 % Decide the tolerance of the test ([] or 0 for no tolerance)
124 TOL = 0e-13;
125
126 % Set parameters: duration and rate
127 nsecs = 100;
128 fs = 1;
129
130 % Extract the information from the ao model default plist
131 ao_mdl_info = eval(['ao_model_' model_def '(''info'')']);
132 pl = ao_mdl_info.plists;
133
134 F0 = find(pl, 'F0');
135 toff = find(pl, 'toff');
136 phi = find(pl, 'phi');
137 phi = 0.0;
138 f = find(pl, 'f');
139 m = find(pl, 'm');
140 k = find(pl, 'k');
141 tau = find(pl, 'tau');
142 x0 = find(pl, 'x0');
143 x0 = 0.0;
144 v0 = find(pl, 'v0');
145
146 % Build the ao model
147 ao_mdl = ao(plist('built-in', model_def, 'nsecs', nsecs, 'fs', fs, 'x0', x0, 'phi', phi));
148
149 % Build the smodel model
150 smodel_mdl = smodel(plist('built-in', model_def));
151
152 % Set smodel parameters
153 smodel_mdl.setParameters({'m','k','tau','F0','f','phi','x0','v0','toff'}, {m,k,tau,F0,f,phi,x0,v0,toff});
154
155 % Set smodel xvals
156 smodel_mdl.setXvals(ao_mdl.x);
157
158 % Eval the smodel
159 d = smodel_mdl.double();
160
161 % Compare the numbers
162 results = [results; test check_correctness(d, ao_mdl.y, plist('tol', TOL))];
163 end
164
165 %% 21 Oscillator sine, high fs and high nsecs
166 test = 21;
167 if any(ismember(list, test))
168
169 % Pick the model
170 model_def = 'oscillator_sine';
171
172 % Decide the tolerance of the test ([] or 0 for no tolerance)
173 TOL = 1e-12;
174
175 % Set parameters: duration and rate
176 nsecs = 10000;
177 fs = 1000;
178
179 % Extract the information from the ao model default plist
180 ao_mdl_info = eval(['ao_model_' model_def '(''info'')']);
181 pl = ao_mdl_info.plists;
182
183 F0 = find(pl, 'F0');
184 toff = find(pl, 'toff');
185 phi = find(pl, 'phi');
186 f = find(pl, 'f');
187 m = find(pl, 'm');
188 k = find(pl, 'k');
189 tau = find(pl, 'tau');
190 x0 = find(pl, 'x0');
191 v0 = find(pl, 'v0');
192
193 % Build the ao model
194 ao_mdl = ao(plist('built-in', model_def, 'nsecs', nsecs, 'fs', fs));
195
196 % Build the smodel model
197 smodel_mdl = smodel(plist('built-in', model_def));
198
199 % Set smodel parameters
200 smodel_mdl.setParameters({'m','k','tau','F0','f','phi','x0','v0','toff'}, {m,k,tau,F0,f,phi,x0,v0,toff});
201
202 % Set smodel xvals
203 smodel_mdl.setXvals(ao_mdl.x);
204
205 % Eval the smodel
206 d = smodel_mdl.double();
207
208 % Compare the numbers
209 results = [results; test check_correctness(d, ao_mdl.y, plist('tol', TOL))];
210 end
211
212 %% 30 Sinewave, default values
213 test = 30;
214 if any(ismember(list, test))
215
216 % Pick the model
217 model_def = 'sinewave';
218
219 % Decide the tolerance of the test ([] or 0 for no tolerance)
220 TOL = 0;
221
222 % Set parameters: duration and rate
223 nsecs = 100;
224 fs = 1;
225
226 % Extract the information from the ao model default plist
227 ao_mdl_info = eval(['ao_model_' model_def '(''info'')']);
228 pl = ao_mdl_info.plists;
229
230 A = find(pl, 'A');
231 phi = find(pl, 'phi');
232 f = find(pl, 'f');
233
234 % Build the ao model
235 ao_mdl = ao(plist('built-in', model_def, 'nsecs', nsecs, 'fs', fs));
236
237 % Build the smodel model
238 smodel_mdl = smodel(plist('built-in', model_def));
239
240 % Set smodel parameters
241 smodel_mdl.setParameters({'A','f','phi'}, {A,f,phi});
242
243 % Set smodel yunits
244 smodel_mdl.setYunits(ao_mdl.yunits);
245
246 % Set smodel xvals
247 smodel_mdl.setXvals(ao_mdl.x);
248
249 % Eval the smodel
250 d = smodel_mdl.double();
251
252 % Compare the numbers
253 results = [results; test check_correctness(d, ao_mdl.y, plist('tol', TOL))];
254 end
255
256 %% 31 Sinewave, high fs and high nsecs
257 test = 31;
258 if any(ismember(list, test))
259
260 % Pick the model
261 model_def = 'sinewave';
262
263 % Decide the tolerance of the test ([] or 0 for no tolerance)
264 TOL = 0;
265
266 % Set parameters: duration and rate
267 nsecs = 10000;
268 fs = 1000;
269
270 % Extract the information from the ao model default plist
271 ao_mdl_info = eval(['ao_model_' model_def '(''info'')']);
272 pl = ao_mdl_info.plists;
273
274 A = find(pl, 'A');
275 phi = find(pl, 'phi');
276 f = find(pl, 'f');
277
278 % Build the ao model
279 ao_mdl = ao(plist('built-in', model_def, 'nsecs', nsecs, 'fs', fs));
280
281 % Build the smodel model
282 smodel_mdl = smodel(plist('built-in', model_def));
283
284 % Set smodel parameters
285 smodel_mdl.setParameters({'A','f','phi'}, {A,f,phi});
286
287 % Set smodel yunits
288 smodel_mdl.setYunits(ao_mdl.yunits);
289
290 % Set smodel xvals
291 smodel_mdl.setXvals(ao_mdl.x);
292
293 % Eval the smodel
294 d = smodel_mdl.double();
295
296 % Compare the numbers
297 results = [results; test check_correctness(d, ao_mdl.y, plist('tol', TOL))];
298 end
299
300 %% 40 Squarewave, default values
301 test = 40;
302 if any(ismember(list, test))
303
304 % Pick the model
305 model_def = 'squarewave';
306
307 % Decide the tolerance of the test ([] or 0 for no tolerance)
308 TOL = 0;
309
310 % Set parameters: duration and rate
311 nsecs = 100;
312 fs = 1;
313
314 % Extract the information from the ao model default plist
315 ao_mdl_info = eval(['ao_model_' model_def '(''info'')']);
316 pl = ao_mdl_info.plists;
317
318 phi = find(pl, 'phi');
319 f = find(pl, 'f');
320
321 % Build the ao model
322 ao_mdl = ao(plist('built-in', model_def, 'nsecs', nsecs, 'fs', fs));
323
324 % Build the smodel model
325 smodel_mdl = smodel(plist('built-in', model_def));
326
327 % Set smodel parameters
328 smodel_mdl.setParameters({'f','phi'}, {f,phi});
329
330 % Set smodel yunits
331 smodel_mdl.setYunits(ao_mdl.yunits);
332
333 % Set smodel xvals
334 smodel_mdl.setXvals(ao_mdl.x);
335
336 % Eval the smodel
337 d = smodel_mdl.double();
338
339 % Compare the numbers
340 results = [results; test check_correctness(d, ao_mdl.y, plist('tol', TOL))];
341 end
342
343 %% 41 Squarewave, high fs and high nsecs
344 test = 41;
345 if any(ismember(list, test))
346
347 % Pick the model
348 model_def = 'squarewave';
349
350 % Decide the tolerance of the test ([] or 0 for no tolerance)
351 TOL = 0;
352
353 % Set parameters: duration and rate
354 nsecs = 10000;
355 fs = 1000;
356
357 % Extract the information from the ao model default plist
358 ao_mdl_info = eval(['ao_model_' model_def '(''info'')']);
359 pl = ao_mdl_info.plists;
360
361 phi = find(pl, 'phi');
362 f = find(pl, 'f');
363
364 % Build the ao model
365 ao_mdl = ao(plist('built-in', model_def, 'nsecs', nsecs, 'fs', fs));
366
367 % Build the smodel model
368 smodel_mdl = smodel(plist('built-in', model_def));
369
370 % Set smodel parameters
371 smodel_mdl.setParameters({'f','phi'}, {f,phi});
372
373 % Set smodel yunits
374 smodel_mdl.setYunits(ao_mdl.yunits);
375
376 % Set smodel xvals
377 smodel_mdl.setXvals(ao_mdl.x);
378
379 % Eval the smodel
380 d = smodel_mdl.double();
381
382 % Compare the numbers
383 results = [results; test check_correctness(d, ao_mdl.y, plist('tol', TOL))];
384 end
385
386 %% 50 Step, default values
387 test = 50;
388 if any(ismember(list, test))
389
390 % Pick the model
391 model_def = 'step';
392
393 % Decide the tolerance of the test ([] or 0 for no tolerance)
394 TOL = 0;
395
396 % Set parameters: duration and rate
397 nsecs = 100;
398 fs = 1;
399
400 % Extract the information from the ao model default plist
401 ao_mdl_info = eval(['ao_model_' model_def '(''info'')']);
402 pl = ao_mdl_info.plists;
403
404 A = find(pl, 'A');
405 toff = find(pl, 'toff');
406
407 % Build the ao model
408 ao_mdl = ao(plist('built-in', model_def, 'nsecs', nsecs, 'fs', fs));
409
410 % Build the smodel model
411 smodel_mdl = smodel(plist('built-in', model_def));
412
413 % Set smodel parameters
414 smodel_mdl.setParameters({'A','toff'}, {A,toff});
415
416 % Set smodel yunits
417 smodel_mdl.setYunits(ao_mdl.yunits);
418
419 % Set smodel xvals
420 smodel_mdl.setXvals(ao_mdl.x);
421
422 % Eval the smodel
423 d = smodel_mdl.double();
424
425 % Compare the numbers
426 results = [results; test check_correctness(d, ao_mdl.y, plist('tol', TOL))];
427 end
428
429 %% 51 Step, high fs and high nsecs
430 test = 51;
431 if any(ismember(list, test))
432
433 % Pick the model
434 model_def = 'step';
435
436 % Decide the tolerance of the test ([] or 0 for no tolerance)
437 TOL = 0;
438
439 % Set parameters: duration and rate
440 nsecs = 10000;
441 fs = 1000;
442
443 % Extract the information from the ao model default plist
444 ao_mdl_info = eval(['ao_model_' model_def '(''info'')']);
445 pl = ao_mdl_info.plists;
446
447 A = find(pl, 'A');
448 toff = find(pl, 'toff');
449
450 % Build the ao model
451 ao_mdl = ao(plist('built-in', model_def, 'nsecs', nsecs, 'fs', fs));
452
453 % Build the smodel model
454 smodel_mdl = smodel(plist('built-in', model_def));
455
456 % Set smodel parameters
457 smodel_mdl.setParameters({'A','toff'}, {A,toff});
458
459 % Set smodel yunits
460 smodel_mdl.setYunits(ao_mdl.yunits);
461
462 % Set smodel xvals
463 smodel_mdl.setXvals(ao_mdl.x);
464
465 % Eval the smodel
466 d = smodel_mdl.double();
467
468 % Compare the numbers
469 results = [results; test check_correctness(d, ao_mdl.y, plist('tol', TOL))];
470 end
471
472 end
473
474 function atest = check_correctness(smodel_y, ao_y, pl)
475
476 % Exceptions plist for ao/eq
477 ple = plist('Exceptions', ...
478 {'created', 'proctime', 'UUID', 'param/desc', 'name', 'methodInvars', 'version'});
479
480 % Start testing
481 atest = true;
482
483 % Strict check or with tolerance?
484 tol = mfind(pl, 'tolerance', 'tol');
485 if ~isempty(tol) && tol > 0
486 % Check within tolerance
487 if any(abs(smodel_y - ao_y) ./ max(abs(smodel_y)) >= tol)
488 atest = false;
489 end
490 else
491 % Strict check on the values
492 if ~isequal(smodel_y, ao_y)
493 atest = false;
494 end
495 end
496
497 end