Changeset 6fe5100 in sasview for src/sans/fit/AbstractFitEngine.py
- Timestamp:
- Apr 6, 2014 7:29:59 AM (10 years ago)
- Branches:
- master, ESS_GUI, ESS_GUI_Docs, ESS_GUI_batch_fitting, ESS_GUI_bumps_abstraction, ESS_GUI_iss1116, ESS_GUI_iss879, ESS_GUI_iss959, ESS_GUI_opencl, ESS_GUI_ordering, ESS_GUI_sync_sascalc, costrafo411, magnetic_scatt, release-4.1.1, release-4.1.2, release-4.2.2, release_4.0.1, ticket-1009, ticket-1094-headless, ticket-1242-2d-resolution, ticket-1243, ticket-1249, ticket885, unittest-saveload
- Children:
- 95d58d3
- Parents:
- 960fdbb
- File:
-
- 1 edited
Legend:
- Unmodified
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- Removed
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src/sans/fit/AbstractFitEngine.py
r6c00702 r6fe5100 3 3 #import logging 4 4 import sys 5 import math 5 6 import numpy 6 import math 7 import park 7 8 8 from sans.dataloader.data_info import Data1D 9 9 from sans.dataloader.data_info import Data2D 10 _SMALLVALUE = 1.0e-10 11 12 class SansParameter(park.Parameter): 13 """ 14 SANS model parameters for use in the PARK fitting service. 15 The parameter attribute value is redirected to the underlying 16 parameter value in the SANS model. 17 """ 18 def __init__(self, name, model, data): 19 """ 20 :param name: the name of the model parameter 21 :param model: the sans model to wrap as a park model 22 """ 23 park.Parameter.__init__(self, name) 24 self._model, self._name = model, name 25 self.data = data 26 self.model = model 27 #set the value for the parameter of the given name 28 self.set(model.getParam(name)) 29 30 def _getvalue(self): 31 """ 32 override the _getvalue of park parameter 33 34 :return value the parameter associates with self.name 35 36 """ 37 return self._model.getParam(self.name) 38 39 def _setvalue(self, value): 40 """ 41 override the _setvalue pf park parameter 42 43 :param value: the value to set on a given parameter 44 45 """ 46 self._model.setParam(self.name, value) 47 48 value = property(_getvalue, _setvalue) 49 50 def _getrange(self): 51 """ 52 Override _getrange of park parameter 53 return the range of parameter 54 """ 55 #if not self.name in self._model.getDispParamList(): 56 lo, hi = self._model.details[self.name][1:3] 57 if lo is None: lo = -numpy.inf 58 if hi is None: hi = numpy.inf 59 if lo > hi: 60 raise ValueError, "wrong fit range for parameters" 61 62 return lo, hi 63 64 def get_name(self): 65 """ 66 """ 67 return self._getname() 68 69 def _setrange(self, r): 70 """ 71 override _setrange of park parameter 72 73 :param r: the value of the range to set 74 75 """ 76 self._model.details[self.name][1:3] = r 77 range = property(_getrange, _setrange) 78 79 80 class Model(park.Model): 81 """ 82 PARK wrapper for SANS models. 10 _SMALLVALUE = 1.0e-10 11 12 # Note: duplicated from park 13 class FitHandler(object): 14 """ 15 Abstract interface for fit thread handler. 16 17 The methods in this class are called by the optimizer as the fit 18 progresses. 19 20 Note that it is up to the optimizer to call the fit handler correctly, 21 reporting all status changes and maintaining the 'done' flag. 22 """ 23 done = False 24 """True when the fit job is complete""" 25 result = None 26 """The current best result of the fit""" 27 28 def improvement(self): 29 """ 30 Called when a result is observed which is better than previous 31 results from the fit. 32 33 result is a FitResult object, with parameters, #calls and fitness. 34 """ 35 def error(self, msg): 36 """ 37 Model had an error; print traceback 38 """ 39 def progress(self, current, expected): 40 """ 41 Called each cycle of the fit, reporting the current and the 42 expected amount of work. The meaning of these values is 43 optimizer dependent, but they can be converted into a percent 44 complete using (100*current)//expected. 45 46 Progress is updated each iteration of the fit, whatever that 47 means for the particular optimization algorithm. It is called 48 after any calls to improvement for the iteration so that the 49 update handler can control I/O bandwidth by suppressing 50 intermediate improvements until the fit is complete. 51 """ 52 def finalize(self): 53 """ 54 Fit is complete; best results are reported 55 """ 56 def abort(self): 57 """ 58 Fit was aborted. 59 """ 60 61 class Model: 62 """ 63 Fit wrapper for SANS models. 83 64 """ 84 65 def __init__(self, sans_model, sans_data=None, **kw): 85 66 """ 86 67 :param sans_model: the sans model to wrap using park interface 87 88 """ 89 park.Model.__init__(self, **kw) 68 69 """ 90 70 self.model = sans_model 91 71 self.name = sans_model.name 92 72 self.data = sans_data 93 #list of parameters names 94 self.sansp = sans_model.getParamList() 95 #list of park parameter 96 self.parkp = [SansParameter(p, sans_model, sans_data) for p in self.sansp] 97 #list of parameter set 98 self.parameterset = park.ParameterSet(sans_model.name, pars=self.parkp) 99 self.pars = [] 100 73 101 74 def get_params(self, fitparams): 102 75 """ 103 76 return a list of value of paramter to fit 104 77 105 78 :param fitparams: list of paramaters name to fit 106 107 """ 108 list_params = [] 109 self.pars = [] 110 self.pars = fitparams 111 for item in fitparams: 112 for element in self.parkp: 113 if element.name == str(item): 114 list_params.append(element.value) 115 return list_params 116 79 80 """ 81 return [self.model.getParam(k) for k in fitparams] 82 117 83 def set_params(self, paramlist, params): 118 84 """ 119 85 Set value for parameters to fit 120 86 121 87 :param params: list of value for parameters to fit 122 123 """ 124 try: 125 for i in range(len(self.parkp)): 126 for j in range(len(paramlist)): 127 if self.parkp[i].name == paramlist[j]: 128 self.parkp[i].value = params[j] 129 self.model.setParam(self.parkp[i].name, params[j]) 130 except: 131 raise 132 88 89 """ 90 for k,v in zip(paramlist, params): 91 self.model.setParam(k,v) 92 93 def set(self, **kw): 94 self.set_params(*zip(*kw.items())) 95 133 96 def eval(self, x): 134 97 """ 135 98 Override eval method of park model. 136 99 137 100 :param x: the x value used to compute a function 138 101 """ … … 141 104 except: 142 105 raise 143 106 144 107 def eval_derivs(self, x, pars=[]): 145 108 """ … … 154 117 instead of calling eval. 155 118 """ 156 return [] 157 158 119 raise NotImplementedError('no derivatives available') 120 121 def __call__(self, x): 122 return self.eval(x) 123 159 124 class FitData1D(Data1D): 160 125 """ … … 185 150 """ 186 151 Data1D.__init__(self, x=x, y=y, dx=dx, dy=dy) 152 self.num_points = len(x) 187 153 self.sans_data = data 188 154 self.smearer = smearer … … 298 264 """ 299 265 self.res_err_image = [] 266 self.num_points = data.size 300 267 self.idx = [] 301 268 self.qmin = None … … 409 376 410 377 411 class SansAssembly: 412 """ 413 Sans Assembly class a class wrapper to be call in optimizer.leastsq method 414 """ 415 def __init__(self, paramlist, model=None, data=None, fitresult=None, 416 handler=None, curr_thread=None, msg_q=None): 417 """ 418 :param Model: the model wrapper fro sans -model 419 :param Data: the data wrapper for sans data 420 421 """ 422 self.model = model 423 self.data = data 424 self.paramlist = paramlist 425 self.msg_q = msg_q 426 self.curr_thread = curr_thread 427 self.handler = handler 428 self.fitresult = fitresult 429 self.res = [] 430 self.true_res = [] 431 self.func_name = "Functor" 432 self.theory = None 433 434 def chisq(self): 435 """ 436 Calculates chi^2 437 438 :param params: list of parameter values 439 440 :return: chi^2 441 442 """ 443 total = 0 444 for item in self.true_res: 445 total += item * item 446 if len(self.true_res) == 0: 447 return None 448 return total / len(self.true_res) 449 450 def __call__(self, params): 451 """ 452 Compute residuals 453 :param params: value of parameters to fit 454 """ 455 #import thread 456 self.model.set_params(self.paramlist, params) 457 #print "params", params 458 self.true_res, theory = self.data.residuals(self.model.eval) 459 self.theory = copy.deepcopy(theory) 460 # check parameters range 461 if self.check_param_range(): 462 # if the param value is outside of the bound 463 # just silent return res = inf 464 return self.res 465 self.res = self.true_res 466 467 if self.fitresult is not None: 468 self.fitresult.set_model(model=self.model) 469 self.fitresult.residuals = self.true_res 470 self.fitresult.iterations += 1 471 self.fitresult.theory = theory 472 473 #fitness = self.chisq(params=params) 474 fitness = self.chisq() 475 self.fitresult.pvec = params 476 self.fitresult.set_fitness(fitness=fitness) 477 if self.msg_q is not None: 478 self.msg_q.put(self.fitresult) 479 480 if self.handler is not None: 481 self.handler.set_result(result=self.fitresult) 482 self.handler.update_fit() 483 484 if self.curr_thread != None: 485 try: 486 self.curr_thread.isquit() 487 except: 488 #msg = "Fitting: Terminated... Note: Forcing to stop " 489 #msg += "fitting may cause a 'Functor error message' " 490 #msg += "being recorded in the log file....." 491 #self.handler.stop(msg) 492 raise 493 494 return self.res 495 496 def check_param_range(self): 497 """ 498 Check the lower and upper bound of the parameter value 499 and set res to the inf if the value is outside of the 500 range 501 :limitation: the initial values must be within range. 502 """ 503 504 #time.sleep(0.01) 505 is_outofbound = False 506 # loop through the fit parameters 507 for p in self.model.parameterset: 508 param_name = p.get_name() 509 if param_name in self.paramlist: 510 511 # if the range was defined, check the range 512 if numpy.isfinite(p.range[0]): 513 if p.value == 0: 514 # This value works on Scipy 515 # Do not change numbers below 516 value = _SMALLVALUE 517 else: 518 value = p.value 519 # For leastsq, it needs a bit step back from the boundary 520 val = p.range[0] - value * _SMALLVALUE 521 if p.value < val: 522 self.res *= 1e+6 523 524 is_outofbound = True 525 break 526 if numpy.isfinite(p.range[1]): 527 # This value works on Scipy 528 # Do not change numbers below 529 if p.value == 0: 530 value = _SMALLVALUE 531 else: 532 value = p.value 533 # For leastsq, it needs a bit step back from the boundary 534 val = p.range[1] + value * _SMALLVALUE 535 if p.value > val: 536 self.res *= 1e+6 537 is_outofbound = True 538 break 539 540 return is_outofbound 541 542 378 543 379 class FitEngine: 544 380 def __init__(self): … … 754 590 755 591 756 IS_MAC = True757 if sys.platform.count("win32") > 0:758 IS_MAC = False759 760 761 592 class FResult(object): 762 593 """ … … 777 608 self.index = [] 778 609 self.parameters = None 779 self.is_mac = IS_MAC780 610 self.model = model 781 611 self.data = data … … 803 633 if self.pvec == None and self.model is None and self.param_list is None: 804 634 return "No results" 805 n = len(self.model.parameterset) 806 807 result_param = zip(xrange(n), self.model.parameterset) 808 msg1 = ["[Iteration #: %s ]" % self.iterations] 809 msg3 = ["=== goodness of fit: %s ===" % (str(self.fitness))] 810 if not self.is_mac: 811 msg2 = ["P%-3d %s......|.....%s" % \ 812 (p[0], p[1], p[1].value)\ 813 for p in result_param if p[1].name in self.param_list] 814 msg = msg1 + msg3 + msg2 815 else: 816 msg = msg1 + msg3 817 msg = "\n".join(msg) 818 return msg 635 636 pars = enumerate(self.model.model.getParamList()) 637 msg1 = "[Iteration #: %s ]" % self.iterations 638 msg3 = "=== goodness of fit: %s ===" % (str(self.fitness)) 639 msg2 = ["P%-3d %s......|.....%s" % (i, v, self.model.model.getParam(v)) 640 for i,v in pars if v in self.param_list] 641 msg = [msg1, msg3] + msg2 642 return "\n".join(msg) 819 643 820 644 def print_summary(self):
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