| 1 | """ |
|---|
| 2 | Inferface containing information to store data, model, range of data, etc... |
|---|
| 3 | and retreive this information. This is an inferface |
|---|
| 4 | for a fitProblem i.e relationship between data and model. |
|---|
| 5 | """ |
|---|
| 6 | ################################################################################ |
|---|
| 7 | #This software was developed by the University of Tennessee as part of the |
|---|
| 8 | #Distributed Data Analysis of Neutron Scattering Experiments (DANSE) |
|---|
| 9 | #project funded by the US National Science Foundation. |
|---|
| 10 | # |
|---|
| 11 | #See the license text in license.txt |
|---|
| 12 | # |
|---|
| 13 | #copyright 2009, University of Tennessee |
|---|
| 14 | ################################################################################ |
|---|
| 15 | import copy |
|---|
| 16 | from sans.models.qsmearing import smear_selection |
|---|
| 17 | |
|---|
| 18 | class FitProblemComponent(object): |
|---|
| 19 | """ |
|---|
| 20 | Inferface containing information to store data, model, range of data, etc... |
|---|
| 21 | and retreive this information. This is an inferface |
|---|
| 22 | for a fitProblem i.e relationship between data and model. |
|---|
| 23 | """ |
|---|
| 24 | def enable_smearing(self, flag=False): |
|---|
| 25 | """ |
|---|
| 26 | :param flag: bool.When flag is 1 get the computer smear value. When |
|---|
| 27 | flag is 0 ingore smear value. |
|---|
| 28 | """ |
|---|
| 29 | |
|---|
| 30 | def get_smearer(self): |
|---|
| 31 | """ |
|---|
| 32 | return smear object |
|---|
| 33 | """ |
|---|
| 34 | def save_model_name(self, name): |
|---|
| 35 | """ |
|---|
| 36 | """ |
|---|
| 37 | |
|---|
| 38 | def get_name(self): |
|---|
| 39 | """ |
|---|
| 40 | """ |
|---|
| 41 | |
|---|
| 42 | def set_model(self, model): |
|---|
| 43 | """ |
|---|
| 44 | associates each model with its new created name |
|---|
| 45 | :param model: model selected |
|---|
| 46 | :param name: name created for model |
|---|
| 47 | """ |
|---|
| 48 | |
|---|
| 49 | def get_model(self): |
|---|
| 50 | """ |
|---|
| 51 | :return: saved model |
|---|
| 52 | """ |
|---|
| 53 | |
|---|
| 54 | def set_residuals(self, residuals): |
|---|
| 55 | """ |
|---|
| 56 | save a copy of residual |
|---|
| 57 | :param data: data selected |
|---|
| 58 | """ |
|---|
| 59 | |
|---|
| 60 | def get_residuals(self): |
|---|
| 61 | """ |
|---|
| 62 | :return: residuals |
|---|
| 63 | """ |
|---|
| 64 | |
|---|
| 65 | def set_theory_data(self, data): |
|---|
| 66 | """ |
|---|
| 67 | save a copy of the data select to fit |
|---|
| 68 | :param data: data selected |
|---|
| 69 | """ |
|---|
| 70 | |
|---|
| 71 | def get_theory_data(self): |
|---|
| 72 | """ |
|---|
| 73 | :return: list of data dList |
|---|
| 74 | """ |
|---|
| 75 | |
|---|
| 76 | def set_fit_data(self, data): |
|---|
| 77 | """ |
|---|
| 78 | Store of list of data and create by create new fitproblem of each data |
|---|
| 79 | id , if there was existing information about model, this information |
|---|
| 80 | get copy to the new fitproblem |
|---|
| 81 | :param data: list of data selected |
|---|
| 82 | """ |
|---|
| 83 | |
|---|
| 84 | def get_fit_data(self): |
|---|
| 85 | """ |
|---|
| 86 | """ |
|---|
| 87 | |
|---|
| 88 | def set_model_param(self, name, value=None): |
|---|
| 89 | """ |
|---|
| 90 | Store the name and value of a parameter of this fitproblem's model |
|---|
| 91 | :param name: name of the given parameter |
|---|
| 92 | :param value: value of that parameter |
|---|
| 93 | """ |
|---|
| 94 | |
|---|
| 95 | def set_param2fit(self, list): |
|---|
| 96 | """ |
|---|
| 97 | Store param names to fit (checked) |
|---|
| 98 | :param list: list of the param names |
|---|
| 99 | """ |
|---|
| 100 | |
|---|
| 101 | def get_param2fit(self): |
|---|
| 102 | """ |
|---|
| 103 | return the list param names to fit |
|---|
| 104 | """ |
|---|
| 105 | |
|---|
| 106 | def get_model_param(self): |
|---|
| 107 | """ |
|---|
| 108 | return list of couple of parameter name and value |
|---|
| 109 | """ |
|---|
| 110 | |
|---|
| 111 | def schedule_tofit(self, schedule=0): |
|---|
| 112 | """ |
|---|
| 113 | set schedule to true to decide if this fit must be performed |
|---|
| 114 | """ |
|---|
| 115 | |
|---|
| 116 | def get_scheduled(self): |
|---|
| 117 | """ |
|---|
| 118 | return true or false if a problem as being schedule for fitting |
|---|
| 119 | """ |
|---|
| 120 | |
|---|
| 121 | def set_range(self, qmin=None, qmax=None): |
|---|
| 122 | """ |
|---|
| 123 | set fitting range |
|---|
| 124 | """ |
|---|
| 125 | |
|---|
| 126 | def get_range(self): |
|---|
| 127 | """ |
|---|
| 128 | :return: fitting range |
|---|
| 129 | """ |
|---|
| 130 | |
|---|
| 131 | def set_weight(self, flag=None): |
|---|
| 132 | """ |
|---|
| 133 | set fitting range |
|---|
| 134 | """ |
|---|
| 135 | |
|---|
| 136 | def get_weight(self): |
|---|
| 137 | """ |
|---|
| 138 | get fitting weight |
|---|
| 139 | """ |
|---|
| 140 | |
|---|
| 141 | def clear_model_param(self): |
|---|
| 142 | """ |
|---|
| 143 | clear constraint info |
|---|
| 144 | """ |
|---|
| 145 | |
|---|
| 146 | def set_fit_tab_caption(self, caption): |
|---|
| 147 | """ |
|---|
| 148 | store the caption of the page associated with object |
|---|
| 149 | """ |
|---|
| 150 | |
|---|
| 151 | def get_fit_tab_caption(self): |
|---|
| 152 | """ |
|---|
| 153 | Return the caption of the page associated with object |
|---|
| 154 | """ |
|---|
| 155 | |
|---|
| 156 | def set_graph_id(self, id): |
|---|
| 157 | """ |
|---|
| 158 | Set graph id (from data_group_id at the time the graph produced) |
|---|
| 159 | """ |
|---|
| 160 | |
|---|
| 161 | def get_graph_id(self): |
|---|
| 162 | """ |
|---|
| 163 | Get graph_id |
|---|
| 164 | """ |
|---|
| 165 | |
|---|
| 166 | def set_result(self, result): |
|---|
| 167 | """ |
|---|
| 168 | """ |
|---|
| 169 | |
|---|
| 170 | def get_result(self): |
|---|
| 171 | """ |
|---|
| 172 | get result |
|---|
| 173 | """ |
|---|
| 174 | |
|---|
| 175 | |
|---|
| 176 | class FitProblemDictionary(FitProblemComponent, dict): |
|---|
| 177 | """ |
|---|
| 178 | This module implements a dictionary of fitproblem objects |
|---|
| 179 | """ |
|---|
| 180 | def __init__(self): |
|---|
| 181 | FitProblemComponent.__init__(self) |
|---|
| 182 | dict.__init__(self) |
|---|
| 183 | ## the current model |
|---|
| 184 | self.model = None |
|---|
| 185 | ## if 1 this fit problem will be selected to fit , if 0 |
|---|
| 186 | ## it will not be selected for fit |
|---|
| 187 | self.schedule = 0 |
|---|
| 188 | ##list containing parameter name and value |
|---|
| 189 | self.list_param = [] |
|---|
| 190 | ## fitting range |
|---|
| 191 | self.qmin = None |
|---|
| 192 | self.qmax = None |
|---|
| 193 | self.graph_id = None |
|---|
| 194 | self._smear_on = False |
|---|
| 195 | self.scheduled = 0 |
|---|
| 196 | self.fit_tab_caption = '' |
|---|
| 197 | self.nbr_residuals_computed = 0 |
|---|
| 198 | self.batch_inputs = {} |
|---|
| 199 | self.batch_outputs = {} |
|---|
| 200 | |
|---|
| 201 | def enable_smearing(self, flag=False, fid=None): |
|---|
| 202 | """ |
|---|
| 203 | :param flag: bool.When flag is 1 get the computer smear value. When |
|---|
| 204 | flag is 0 ingore smear value. |
|---|
| 205 | """ |
|---|
| 206 | self._smear_on = flag |
|---|
| 207 | if fid is None: |
|---|
| 208 | for value in self.itervalues(): |
|---|
| 209 | value.enable_smearing(flag) |
|---|
| 210 | else: |
|---|
| 211 | if fid in self.iterkeys(): |
|---|
| 212 | self[fid].enable_smearing(flag) |
|---|
| 213 | |
|---|
| 214 | def set_smearer(self, smearer, fid=None): |
|---|
| 215 | """ |
|---|
| 216 | save reference of smear object on fitdata |
|---|
| 217 | :param smear: smear object from DataLoader |
|---|
| 218 | """ |
|---|
| 219 | if fid is None: |
|---|
| 220 | for value in self.itervalues(): |
|---|
| 221 | value.set_smearer(smearer) |
|---|
| 222 | else: |
|---|
| 223 | if fid in self.iterkeys(): |
|---|
| 224 | self[fid].set_smearer(smearer) |
|---|
| 225 | |
|---|
| 226 | def get_smearer(self, fid=None): |
|---|
| 227 | """ |
|---|
| 228 | return smear object |
|---|
| 229 | """ |
|---|
| 230 | if fid in self.iterkeys(): |
|---|
| 231 | return self[fid].get_smearer() |
|---|
| 232 | |
|---|
| 233 | def save_model_name(self, name, fid=None): |
|---|
| 234 | """ |
|---|
| 235 | """ |
|---|
| 236 | if fid is None: |
|---|
| 237 | for value in self.itervalues(): |
|---|
| 238 | value.save_model_name(name) |
|---|
| 239 | else: |
|---|
| 240 | if fid in self.iterkeys(): |
|---|
| 241 | self[fid].save_model_name(name) |
|---|
| 242 | |
|---|
| 243 | def get_name(self, fid=None): |
|---|
| 244 | """ |
|---|
| 245 | """ |
|---|
| 246 | result = [] |
|---|
| 247 | if fid is None: |
|---|
| 248 | for value in self.itervalues(): |
|---|
| 249 | result.append(value.get_name()) |
|---|
| 250 | else: |
|---|
| 251 | if fid in self.iterkeys(): |
|---|
| 252 | result.append(self[fid].get_name()) |
|---|
| 253 | return result |
|---|
| 254 | |
|---|
| 255 | def set_model(self, model, fid=None): |
|---|
| 256 | """ |
|---|
| 257 | associates each model with its new created name |
|---|
| 258 | :param model: model selected |
|---|
| 259 | :param name: name created for model |
|---|
| 260 | """ |
|---|
| 261 | self.model = model |
|---|
| 262 | if fid is None: |
|---|
| 263 | for value in self.itervalues(): |
|---|
| 264 | value.set_model(self.model) |
|---|
| 265 | else: |
|---|
| 266 | if fid in self.iterkeys(): |
|---|
| 267 | self[fid].set_model(self.model) |
|---|
| 268 | |
|---|
| 269 | def get_model(self, fid): |
|---|
| 270 | """ |
|---|
| 271 | :return: saved model |
|---|
| 272 | """ |
|---|
| 273 | if fid in self.iterkeys(): |
|---|
| 274 | return self[fid].get_model() |
|---|
| 275 | |
|---|
| 276 | def set_fit_tab_caption(self, caption): |
|---|
| 277 | """ |
|---|
| 278 | store the caption of the page associated with object |
|---|
| 279 | """ |
|---|
| 280 | self.fit_tab_caption = caption |
|---|
| 281 | |
|---|
| 282 | def get_fit_tab_caption(self): |
|---|
| 283 | """ |
|---|
| 284 | Return the caption of the page associated with object |
|---|
| 285 | """ |
|---|
| 286 | return self.fit_tab_caption |
|---|
| 287 | |
|---|
| 288 | def set_residuals(self, residuals, fid): |
|---|
| 289 | """ |
|---|
| 290 | save a copy of residual |
|---|
| 291 | :param data: data selected |
|---|
| 292 | """ |
|---|
| 293 | if fid in self.iterkeys(): |
|---|
| 294 | self[fid].set_residuals(residuals) |
|---|
| 295 | |
|---|
| 296 | def get_residuals(self, fid): |
|---|
| 297 | """ |
|---|
| 298 | :return: residuals |
|---|
| 299 | """ |
|---|
| 300 | if fid in self.iterkeys(): |
|---|
| 301 | return self[fid].get_residuals() |
|---|
| 302 | |
|---|
| 303 | def set_theory_data(self, fid, data=None): |
|---|
| 304 | """ |
|---|
| 305 | save a copy of the data select to fit |
|---|
| 306 | :param data: data selected |
|---|
| 307 | """ |
|---|
| 308 | if fid in self.iterkeys(): |
|---|
| 309 | self[fid].set_theory_data(data) |
|---|
| 310 | |
|---|
| 311 | def get_theory_data(self, fid): |
|---|
| 312 | """ |
|---|
| 313 | :return: list of data dList |
|---|
| 314 | """ |
|---|
| 315 | if fid in self.iterkeys(): |
|---|
| 316 | return self[fid].get_theory_data() |
|---|
| 317 | |
|---|
| 318 | def add_data(self, data): |
|---|
| 319 | """ |
|---|
| 320 | Add data to the current dictionary of fitproblem. if data id does not |
|---|
| 321 | exist create a new fit problem. |
|---|
| 322 | :note: only data changes in the fit problem |
|---|
| 323 | """ |
|---|
| 324 | if data.id not in self.iterkeys(): |
|---|
| 325 | self[data.id] = FitProblem() |
|---|
| 326 | self[data.id].set_fit_data(data) |
|---|
| 327 | |
|---|
| 328 | def set_fit_data(self, data): |
|---|
| 329 | """ |
|---|
| 330 | save a copy of the data select to fit |
|---|
| 331 | :param data: data selected |
|---|
| 332 | |
|---|
| 333 | """ |
|---|
| 334 | self.clear() |
|---|
| 335 | if data is None: |
|---|
| 336 | data = [] |
|---|
| 337 | for d in data: |
|---|
| 338 | if (d is not None): |
|---|
| 339 | if (d.id not in self.iterkeys()): |
|---|
| 340 | self[d.id] = FitProblem() |
|---|
| 341 | self[d.id].set_fit_data(d) |
|---|
| 342 | self[d.id].set_model(self.model) |
|---|
| 343 | self[d.id].set_range(self.qmin, self.qmax) |
|---|
| 344 | |
|---|
| 345 | def get_fit_data(self, fid): |
|---|
| 346 | """ |
|---|
| 347 | return data for the given fitproblem id |
|---|
| 348 | :param fid: is key representing a fitproblem. usually extract from data |
|---|
| 349 | id |
|---|
| 350 | """ |
|---|
| 351 | if fid in self.iterkeys(): |
|---|
| 352 | return self[fid].get_fit_data() |
|---|
| 353 | |
|---|
| 354 | def set_model_param(self, name, value=None, fid=None): |
|---|
| 355 | """ |
|---|
| 356 | Store the name and value of a parameter of this fitproblem's model |
|---|
| 357 | :param name: name of the given parameter |
|---|
| 358 | :param value: value of that parameter |
|---|
| 359 | """ |
|---|
| 360 | if fid is None: |
|---|
| 361 | for value in self.itervalues(): |
|---|
| 362 | value.set_model_param(name, value) |
|---|
| 363 | else: |
|---|
| 364 | if fid in self.iterkeys(): |
|---|
| 365 | self[fid].set_model_param(name, value) |
|---|
| 366 | |
|---|
| 367 | def get_model_param(self, fid): |
|---|
| 368 | """ |
|---|
| 369 | return list of couple of parameter name and value |
|---|
| 370 | """ |
|---|
| 371 | if fid in self.iterkeys(): |
|---|
| 372 | return self[fid].get_model_param() |
|---|
| 373 | |
|---|
| 374 | def set_param2fit(self, list): |
|---|
| 375 | """ |
|---|
| 376 | Store param names to fit (checked) |
|---|
| 377 | :param list: list of the param names |
|---|
| 378 | """ |
|---|
| 379 | self.list_param2fit = list |
|---|
| 380 | |
|---|
| 381 | def get_param2fit(self): |
|---|
| 382 | """ |
|---|
| 383 | return the list param names to fit |
|---|
| 384 | """ |
|---|
| 385 | return self.list_param2fit |
|---|
| 386 | |
|---|
| 387 | def schedule_tofit(self, schedule=0): |
|---|
| 388 | """ |
|---|
| 389 | set schedule to true to decide if this fit must be performed |
|---|
| 390 | """ |
|---|
| 391 | self.scheduled = schedule |
|---|
| 392 | for value in self.itervalues(): |
|---|
| 393 | value.schedule_tofit(schedule) |
|---|
| 394 | |
|---|
| 395 | def get_scheduled(self): |
|---|
| 396 | """ |
|---|
| 397 | return true or false if a problem as being schedule for fitting |
|---|
| 398 | """ |
|---|
| 399 | return self.scheduled |
|---|
| 400 | |
|---|
| 401 | def set_range(self, qmin=None, qmax=None, fid=None): |
|---|
| 402 | """ |
|---|
| 403 | set fitting range |
|---|
| 404 | """ |
|---|
| 405 | self.qmin = qmin |
|---|
| 406 | self.qmax = qmax |
|---|
| 407 | if fid is None: |
|---|
| 408 | for value in self.itervalues(): |
|---|
| 409 | value.set_range(self.qmin, self.qmax) |
|---|
| 410 | else: |
|---|
| 411 | if fid in self.iterkeys(): |
|---|
| 412 | self[fid].value.set_range(self.qmin, self.qmax) |
|---|
| 413 | |
|---|
| 414 | def get_range(self, fid): |
|---|
| 415 | """ |
|---|
| 416 | :return: fitting range |
|---|
| 417 | """ |
|---|
| 418 | if fid in self.iterkeys(): |
|---|
| 419 | return self[fid].get_range() |
|---|
| 420 | |
|---|
| 421 | def set_weight(self, is2d, flag=None, fid=None): |
|---|
| 422 | """ |
|---|
| 423 | fit weight |
|---|
| 424 | """ |
|---|
| 425 | if fid is None: |
|---|
| 426 | for value in self.itervalues(): |
|---|
| 427 | value.set_weight(flag=flag, is2d=is2d) |
|---|
| 428 | else: |
|---|
| 429 | if fid in self.iterkeys(): |
|---|
| 430 | self[fid].set_weight(flag=flag, is2d=is2d) |
|---|
| 431 | |
|---|
| 432 | def get_weight(self, fid=None): |
|---|
| 433 | """ |
|---|
| 434 | return fit weight |
|---|
| 435 | """ |
|---|
| 436 | if fid in self.iterkeys(): |
|---|
| 437 | return self[fid].get_weight() |
|---|
| 438 | |
|---|
| 439 | def clear_model_param(self, fid=None): |
|---|
| 440 | """ |
|---|
| 441 | clear constraint info |
|---|
| 442 | """ |
|---|
| 443 | if fid is None: |
|---|
| 444 | for value in self.itervalues(): |
|---|
| 445 | value.clear_model_param() |
|---|
| 446 | else: |
|---|
| 447 | if fid in self.iterkeys(): |
|---|
| 448 | self[fid].clear_model_param() |
|---|
| 449 | |
|---|
| 450 | def get_fit_problem(self): |
|---|
| 451 | """ |
|---|
| 452 | return fitproblem contained in this dictionary |
|---|
| 453 | """ |
|---|
| 454 | return self.itervalues() |
|---|
| 455 | |
|---|
| 456 | def set_result(self, result, fid): |
|---|
| 457 | """ |
|---|
| 458 | """ |
|---|
| 459 | if fid in self.iterkeys(): |
|---|
| 460 | self[fid].set_result(result) |
|---|
| 461 | |
|---|
| 462 | def set_batch_result(self, batch_inputs, batch_outputs): |
|---|
| 463 | """ |
|---|
| 464 | set a list of result |
|---|
| 465 | """ |
|---|
| 466 | self.batch_inputs = batch_inputs |
|---|
| 467 | self.batch_outputs = batch_outputs |
|---|
| 468 | |
|---|
| 469 | def get_result(self, fid): |
|---|
| 470 | """ |
|---|
| 471 | get result |
|---|
| 472 | """ |
|---|
| 473 | if fid in self.iterkeys(): |
|---|
| 474 | return self[fid].get_result() |
|---|
| 475 | |
|---|
| 476 | def get_batch_result(self): |
|---|
| 477 | """ |
|---|
| 478 | get result |
|---|
| 479 | """ |
|---|
| 480 | return self.batch_inputs, self.batch_outputs |
|---|
| 481 | |
|---|
| 482 | def set_graph_id(self, id): |
|---|
| 483 | """ |
|---|
| 484 | Set graph id (from data_group_id at the time the graph produced) |
|---|
| 485 | """ |
|---|
| 486 | self.graph_id = id |
|---|
| 487 | |
|---|
| 488 | def get_graph_id(self): |
|---|
| 489 | """ |
|---|
| 490 | Get graph_id |
|---|
| 491 | """ |
|---|
| 492 | return self.graph_id |
|---|
| 493 | |
|---|
| 494 | |
|---|
| 495 | class FitProblem(FitProblemComponent): |
|---|
| 496 | """ |
|---|
| 497 | FitProblem class allows to link a model with the new name created in _on_model, |
|---|
| 498 | a name theory created with that model and the data fitted with the model. |
|---|
| 499 | FitProblem is mostly used as value of the dictionary by fitting module. |
|---|
| 500 | """ |
|---|
| 501 | def __init__(self): |
|---|
| 502 | FitProblemComponent.__init__(self) |
|---|
| 503 | """ |
|---|
| 504 | contains information about data and model to fit |
|---|
| 505 | """ |
|---|
| 506 | ## data used for fitting |
|---|
| 507 | self.fit_data = None |
|---|
| 508 | self.theory_data = None |
|---|
| 509 | self.residuals = None |
|---|
| 510 | # original data: should not be modified |
|---|
| 511 | self.original_data = None |
|---|
| 512 | ## the current model |
|---|
| 513 | self.model = None |
|---|
| 514 | ## if 1 this fit problem will be selected to fit , if 0 |
|---|
| 515 | ## it will not be selected for fit |
|---|
| 516 | self.schedule = 0 |
|---|
| 517 | ##list containing parameter name and value |
|---|
| 518 | self.list_param = [] |
|---|
| 519 | ## smear object to smear or not data1D |
|---|
| 520 | self.smearer_computed = False |
|---|
| 521 | self.smearer_enable = False |
|---|
| 522 | self.smearer_computer_value = None |
|---|
| 523 | ## fitting range |
|---|
| 524 | self.qmin = None |
|---|
| 525 | self.qmax = None |
|---|
| 526 | # fit weight |
|---|
| 527 | self.weight = None |
|---|
| 528 | self.result = None |
|---|
| 529 | |
|---|
| 530 | def enable_smearing(self, flag=False): |
|---|
| 531 | """ |
|---|
| 532 | :param flag: bool.When flag is 1 get the computer smear value. When |
|---|
| 533 | flag is 0 ingore smear value. |
|---|
| 534 | """ |
|---|
| 535 | self.smearer_enable = flag |
|---|
| 536 | |
|---|
| 537 | def set_smearer(self, smearer): |
|---|
| 538 | """ |
|---|
| 539 | save reference of smear object on fitdata |
|---|
| 540 | |
|---|
| 541 | :param smear: smear object from DataLoader |
|---|
| 542 | |
|---|
| 543 | """ |
|---|
| 544 | self.smearer_computer_value = smearer |
|---|
| 545 | |
|---|
| 546 | def get_smearer(self): |
|---|
| 547 | """ |
|---|
| 548 | return smear object |
|---|
| 549 | """ |
|---|
| 550 | if not self.smearer_enable: |
|---|
| 551 | return None |
|---|
| 552 | if not self.smearer_computed: |
|---|
| 553 | #smeari_selection should be call only once per fitproblem |
|---|
| 554 | self.smearer_computer_value = smear_selection(self.fit_data, |
|---|
| 555 | self.model) |
|---|
| 556 | self.smearer_computed = True |
|---|
| 557 | return self.smearer_computer_value |
|---|
| 558 | |
|---|
| 559 | def save_model_name(self, name): |
|---|
| 560 | """ |
|---|
| 561 | """ |
|---|
| 562 | self.name_per_page = name |
|---|
| 563 | |
|---|
| 564 | def get_name(self): |
|---|
| 565 | """ |
|---|
| 566 | """ |
|---|
| 567 | return self.name_per_page |
|---|
| 568 | |
|---|
| 569 | def set_model(self, model): |
|---|
| 570 | """ |
|---|
| 571 | associates each model with its new created name |
|---|
| 572 | :param model: model selected |
|---|
| 573 | :param name: name created for model |
|---|
| 574 | """ |
|---|
| 575 | self.model = model |
|---|
| 576 | self.smearer_computer_value = smear_selection(self.fit_data, |
|---|
| 577 | self.model) |
|---|
| 578 | self.smearer_computed = True |
|---|
| 579 | |
|---|
| 580 | def get_model(self): |
|---|
| 581 | """ |
|---|
| 582 | :return: saved model |
|---|
| 583 | """ |
|---|
| 584 | return self.model |
|---|
| 585 | |
|---|
| 586 | def set_residuals(self, residuals): |
|---|
| 587 | """ |
|---|
| 588 | save a copy of residual |
|---|
| 589 | :param data: data selected |
|---|
| 590 | """ |
|---|
| 591 | self.residuals = residuals |
|---|
| 592 | |
|---|
| 593 | def get_residuals(self): |
|---|
| 594 | """ |
|---|
| 595 | :return: residuals |
|---|
| 596 | """ |
|---|
| 597 | return self.residuals |
|---|
| 598 | |
|---|
| 599 | def set_theory_data(self, data): |
|---|
| 600 | """ |
|---|
| 601 | save a copy of the data select to fit |
|---|
| 602 | |
|---|
| 603 | :param data: data selected |
|---|
| 604 | |
|---|
| 605 | """ |
|---|
| 606 | self.theory_data = copy.deepcopy(data) |
|---|
| 607 | |
|---|
| 608 | def get_theory_data(self): |
|---|
| 609 | """ |
|---|
| 610 | :return: theory generated with the current model and data of this class |
|---|
| 611 | """ |
|---|
| 612 | return self.theory_data |
|---|
| 613 | |
|---|
| 614 | def set_fit_data(self, data): |
|---|
| 615 | """ |
|---|
| 616 | Store data associated with this class |
|---|
| 617 | :param data: list of data selected |
|---|
| 618 | """ |
|---|
| 619 | self.original_data = None |
|---|
| 620 | self.fit_data = None |
|---|
| 621 | # original data: should not be modified |
|---|
| 622 | self.original_data = data |
|---|
| 623 | # fit data: used for fit and can be modified for convenience |
|---|
| 624 | self.fit_data = copy.deepcopy(data) |
|---|
| 625 | self.smearer_computer_value = smear_selection(self.fit_data, |
|---|
| 626 | self.model) |
|---|
| 627 | self.smearer_computed = True |
|---|
| 628 | self.result = None |
|---|
| 629 | |
|---|
| 630 | def get_fit_data(self): |
|---|
| 631 | """ |
|---|
| 632 | :return: data associate with this class |
|---|
| 633 | """ |
|---|
| 634 | return self.fit_data |
|---|
| 635 | |
|---|
| 636 | def get_origin_data(self): |
|---|
| 637 | """ |
|---|
| 638 | """ |
|---|
| 639 | return self.original_data |
|---|
| 640 | |
|---|
| 641 | def set_weight(self, is2d, flag=None): |
|---|
| 642 | """ |
|---|
| 643 | Received flag and compute error on data. |
|---|
| 644 | :param flag: flag to transform error of data. |
|---|
| 645 | :param is2d: flag to distinguish 1D to 2D Data |
|---|
| 646 | """ |
|---|
| 647 | from .utils import get_weight |
|---|
| 648 | # send original data for weighting |
|---|
| 649 | self.weight = get_weight(data=self.original_data, is2d=is2d, flag=flag) |
|---|
| 650 | if is2d: |
|---|
| 651 | self.fit_data.err_data = self.weight |
|---|
| 652 | else: |
|---|
| 653 | self.fit_data.dy = self.weight |
|---|
| 654 | |
|---|
| 655 | def get_weight(self): |
|---|
| 656 | """ |
|---|
| 657 | returns weight array |
|---|
| 658 | """ |
|---|
| 659 | return self.weight |
|---|
| 660 | |
|---|
| 661 | def set_param2fit(self, list): |
|---|
| 662 | """ |
|---|
| 663 | Store param names to fit (checked) |
|---|
| 664 | :param list: list of the param names |
|---|
| 665 | """ |
|---|
| 666 | self.list_param2fit = list |
|---|
| 667 | |
|---|
| 668 | def get_param2fit(self): |
|---|
| 669 | """ |
|---|
| 670 | return the list param names to fit |
|---|
| 671 | """ |
|---|
| 672 | return self.list_param2fit |
|---|
| 673 | |
|---|
| 674 | def set_model_param(self, name, value=None): |
|---|
| 675 | """ |
|---|
| 676 | Store the name and value of a parameter of this fitproblem's model |
|---|
| 677 | :param name: name of the given parameter |
|---|
| 678 | :param value: value of that parameter |
|---|
| 679 | """ |
|---|
| 680 | self.list_param.append([name, value]) |
|---|
| 681 | |
|---|
| 682 | def get_model_param(self): |
|---|
| 683 | """ |
|---|
| 684 | return list of couple of parameter name and value |
|---|
| 685 | """ |
|---|
| 686 | return self.list_param |
|---|
| 687 | |
|---|
| 688 | def schedule_tofit(self, schedule=0): |
|---|
| 689 | """ |
|---|
| 690 | set schedule to true to decide if this fit must be performed |
|---|
| 691 | """ |
|---|
| 692 | self.schedule = schedule |
|---|
| 693 | |
|---|
| 694 | def get_scheduled(self): |
|---|
| 695 | """ |
|---|
| 696 | return true or false if a problem as being schedule for fitting |
|---|
| 697 | """ |
|---|
| 698 | return self.schedule |
|---|
| 699 | |
|---|
| 700 | def set_range(self, qmin=None, qmax=None): |
|---|
| 701 | """ |
|---|
| 702 | set fitting range |
|---|
| 703 | :param qmin: minimum value to consider for the fit range |
|---|
| 704 | :param qmax: maximum value to consider for the fit range |
|---|
| 705 | """ |
|---|
| 706 | self.qmin = qmin |
|---|
| 707 | self.qmax = qmax |
|---|
| 708 | |
|---|
| 709 | def get_range(self): |
|---|
| 710 | """ |
|---|
| 711 | :return: fitting range |
|---|
| 712 | |
|---|
| 713 | """ |
|---|
| 714 | return self.qmin, self.qmax |
|---|
| 715 | |
|---|
| 716 | def clear_model_param(self): |
|---|
| 717 | """ |
|---|
| 718 | clear constraint info |
|---|
| 719 | """ |
|---|
| 720 | self.list_param = [] |
|---|
| 721 | |
|---|
| 722 | def set_fit_tab_caption(self, caption): |
|---|
| 723 | """ |
|---|
| 724 | """ |
|---|
| 725 | self.fit_tab_caption = str(caption) |
|---|
| 726 | |
|---|
| 727 | def get_fit_tab_caption(self): |
|---|
| 728 | """ |
|---|
| 729 | """ |
|---|
| 730 | return self.fit_tab_caption |
|---|
| 731 | |
|---|
| 732 | def set_graph_id(self, id): |
|---|
| 733 | """ |
|---|
| 734 | Set graph id (from data_group_id at the time the graph produced) |
|---|
| 735 | """ |
|---|
| 736 | self.graph_id = id |
|---|
| 737 | |
|---|
| 738 | def get_graph_id(self): |
|---|
| 739 | """ |
|---|
| 740 | Get graph_id |
|---|
| 741 | """ |
|---|
| 742 | return self.graph_id |
|---|
| 743 | |
|---|
| 744 | def set_result(self, result): |
|---|
| 745 | """ |
|---|
| 746 | """ |
|---|
| 747 | self.result = result |
|---|
| 748 | |
|---|
| 749 | def get_result(self): |
|---|
| 750 | """ |
|---|
| 751 | get result |
|---|
| 752 | """ |
|---|
| 753 | return self.result |
|---|
