""" This software was developed by the University of Tennessee as part of the Distributed Data Analysis of Neutron Scattering Experiments (DANSE) project funded by the US National Science Foundation. See the license text in license.txt copyright 2009, University of Tennessee """ import re,copy import sys, wx, logging import string, numpy, math import time import thread #from danse.common.plottools.plottables import Theory1D from danse.common.plottools.PlotPanel import PlotPanel from sans.guiframe.dataFitting import Data2D from sans.guiframe.dataFitting import Data1D from sans.guiframe.dataFitting import Theory1D from sans.guiframe import dataFitting from sans.guicomm.events import NewPlotEvent, StatusEvent from sans.guicomm.events import EVT_SLICER_PANEL,ERR_DATA,EVT_REMOVE_DATA from sans.guicomm.events import EVT_SLICER_PARS_UPDATE from sans.fit.AbstractFitEngine import Model from sans.fit.AbstractFitEngine import FitAbort from fitproblem import FitProblem from fitpanel import FitPanel from fit_thread import FitThread import models import fitpage DEFAULT_BEAM = 0.005 DEFAULT_QMIN = 0.001 DEFAULT_QMAX = 0.13 DEFAULT_NPTS = 50 (PageInfoEvent, EVT_PAGE_INFO) = wx.lib.newevent.NewEvent() class PlotInfo: """ store some plotting field """ _xunit = 'A^{-1}' _xaxis= "\\rm{Q}" _yunit = "cm^{-1}" _yaxis= "\\rm{Intensity} " id = "Model" group_id = "Model" title= None info= None class Plugin: """ Fitting plugin is used to perform fit """ def __init__(self): ## Plug-in name self.sub_menu = "Fitting" ## Reference to the parent window self.parent = None #Provide list of models existing in the application self.menu_mng = models.ModelManager() ## List of panels for the simulation perspective (names) self.perspective = [] #list of panel to send to guiframe self.mypanels=[] # reference to the current running thread self.calc_2D= None self.calc_1D= None self.calc_fit= None # Start with a good default self.elapsed = 0.022 # the type of optimizer selected, park or scipy self.fitter = None #Flag to let the plug-in know that it is running stand alone self.standalone=True ## dictionary of page closed and id self.closed_page_dict ={} ## Fit engine self._fit_engine = 'scipy' #List of selected data self.selected_data_list=[] ## list of slicer panel created to display slicer parameters and results self.slicer_panels=[] # Log startup logging.info("Fitting plug-in started") # model 2D view self.model2D_id=None #keep reference of the simultaneous fit page self.sim_page=None #dictionary containing data name and error on dy of that data self.err_dy={} def populate_menu(self, id, owner): """ Create a menu for the Fitting plug-in @param id: id to create a menu @param owner: owner of menu @ return : list of information to populate the main menu """ #Menu for fitting self.menu1 = wx.Menu() #Set park engine id3 = wx.NewId() scipy_help= "Scipy Engine: Perform Simple fit. More in Help window...." self.menu1.AppendCheckItem(id3, "Simple Fit [Scipy]",scipy_help) wx.EVT_MENU(owner, id3, self._onset_engine_scipy) id3 = wx.NewId() park_help = "Park Engine: Perform Complex fit. More in Help window...." self.menu1.AppendCheckItem(id3, "Complex Fit [Park]",park_help) wx.EVT_MENU(owner, id3, self._onset_engine_park) self.menu1.FindItemByPosition(0).Check(True) self.menu1.FindItemByPosition(1).Check(False) self.menu1.AppendSeparator() id1 = wx.NewId() simul_help = "Allow to edit fit engine with multiple model and data" self.menu1.Append(id1, '&Simultaneous Page',simul_help) wx.EVT_MENU(owner, id1, self.on_add_sim_page) #menu for SLD Calculator #self.tool_menu = wx.Menu() #id_tool_menu = wx.NewId() #sld_id = wx.NewId() #sld_help= "Compute the scattering length density of molecules" #self.tool_menu.Append(sld_id, "SLD Calculator",sld_help) #wx.EVT_MENU(owner,sld_id, self.onCalculateSld) #menu for model menu2 = wx.Menu() self.menu_mng.populate_menu(menu2, owner) id2 = wx.NewId() owner.Bind(models.EVT_MODEL,self._on_model_menu) self.fit_panel.set_owner(owner) self.fit_panel.set_model_list(self.menu_mng.get_model_list()) owner.Bind(fitpage.EVT_MODEL_BOX,self._on_model_panel) #create menubar items return [(id, self.menu1, "Fitting"), (id2, menu2, "Model")] def on_add_sim_page(self, event): """ Create a page to access simultaneous fit option """ Plugin.on_perspective(self,event=event) if self.sim_page !=None: msg= "Simultaneous Fit page already opened" wx.PostEvent(self.parent, StatusEvent(status= msg)) return self.sim_page= self.fit_panel.add_sim_page() def help(self, evt): """ Show a general help dialog. TODO: replace the text with a nice image """ from helpPanel import HelpWindow frame = HelpWindow(None, -1, 'HelpWindow') frame.Show(True) def get_context_menu(self, graph=None): """ Get the context menu items available for P(r) @param graph: the Graph object to which we attach the context menu @return: a list of menu items with call-back function """ #TODO: clean this up so that the string are not copied # multiple times. self.graph=graph for item in graph.plottables: if item.__class__.__name__ is "Data2D": if hasattr(item,"is_data"): if item.is_data: return [["Select data for fitting", \ "Dialog with fitting parameters ", self._onSelect]] else: return [] return [["Select data for fitting",\ "Dialog with fitting parameters ", self._onSelect]] else: if item.name==graph.selected_plottable : if item.name !="$I_{obs}(q)$" and item.name !="$P_{fit}(r)$": if hasattr(item, "group_id"): if hasattr(item,"is_data"): if item.is_data: return [["Select data for fitting", \ "Dialog with fitting parameters ", self._onSelect]] else: return [] else: return [["Select data for fitting", \ "Dialog with fitting parameters ", self._onSelect]] return [] def get_panels(self, parent): """ Create and return a list of panel objects """ self.parent = parent # Creation of the fit panel self.fit_panel = FitPanel(self.parent, -1) #Set the manager for the main panel self.fit_panel.set_manager(self) # List of windows used for the perspective self.perspective = [] self.perspective.append(self.fit_panel.window_name) # take care of saving data, model and page associated with each other self.page_finder = {} #index number to create random model name self.index_model = 0 self.index_theory= 0 self.parent.Bind(EVT_SLICER_PANEL, self._on_slicer_event) self.parent.Bind( ERR_DATA, self._on_data_error) self.parent.Bind(EVT_REMOVE_DATA, self._closed_fitpage) self.parent.Bind(EVT_SLICER_PARS_UPDATE, self._onEVT_SLICER_PANEL) self.parent._mgr.Bind(wx.aui.EVT_AUI_PANE_CLOSE,self._onclearslicer) #Send the fitting panel to guiframe self.mypanels.append(self.fit_panel) return self.mypanels def get_perspective(self): """ Get the list of panel names for this perspective """ return self.perspective def on_perspective(self, event): """ Call back function for the perspective menu item. We notify the parent window that the perspective has changed. """ self.parent.set_perspective(self.perspective) def post_init(self): """ Post initialization call back to close the loose ends """ # Do not show the fitting perspective immediately and # let the application show the Welcome Page. #self.parent.set_perspective(self.perspective) pass def copy_data(self, item, dy=None): """ receive a data 1D and the list of errors on dy and create a new data1D data @param return """ id=None if hasattr(item,"id"): id = copy.deepcopy(item.id) data= Data1D(x=item.x, y=item.y,dx=None, dy=None) data.copy_from_datainfo(item) item.clone_without_data(clone=data) data.dy=dy data.name = item.name ## allow to highlight data when plotted data.interactive = copy.deepcopy(item.interactive) ## when 2 data have the same id override the 1 st plotted data.id = id data.group_id = item.group_id return data def set_fit_range(self, page, qmin, qmax): """ Set the fitting range of a given page """ if page in self.page_finder.iterkeys(): fitproblem= self.page_finder[page] fitproblem.set_range(qmin= qmin, qmax= qmax) def schedule_for_fit(self,value=0,page=None,fitproblem =None): """ Set the fit problem field to 0 or 1 to schedule that problem to fit. Schedule the specified fitproblem or get the fit problem related to the current page and set value. @param value : integer 0 or 1 @param fitproblem: fitproblem to schedule or not to fit """ if fitproblem !=None: fitproblem.schedule_tofit(value) else: if page in self.page_finder.iterkeys(): fitproblem= self.page_finder[page] fitproblem.schedule_tofit(value) def get_page_finder(self): """ @return self.page_finder used also by simfitpage.py""" return self.page_finder def set_page_finder(self,modelname,names,values): """ Used by simfitpage.py to reset a parameter given the string constrainst. @param modelname: the name ot the model for with the parameter has to reset @param value: can be a string in this case. @param names: the paramter name @note: expecting park used for fit. """ sim_page= self.sim_page for page, value in self.page_finder.iteritems(): if page != sim_page: list=value.get_model() model = list[0] if model.name== modelname: value.set_model_param(names,values) break def split_string(self,item): """ receive a word containing dot and split it. used to split parameterset name into model name and parameter name example: paramaterset (item) = M1.A @return model_name =M1 , parameter name =A """ if string.find(item,".")!=-1: param_names= re.split("\.",item) model_name=param_names[0] param_name=param_names[1] return model_name,param_name def stop_fit(self): """ Stop the fit engine """ if self.calc_fit!= None and self.calc_fit.isrunning(): self.calc_fit.stop() wx.PostEvent(self.parent, StatusEvent(status="Fitting \ is cancelled" , type="stop")) def set_smearer(self,smearer, qmin=None, qmax=None): """ Get a smear object and store it to a fit problem @param smearer: smear object to allow smearing data """ current_pg=self.fit_panel.get_current_page() self.page_finder[current_pg].set_smearer(smearer) ## draw model 1D with smeared data data = self.page_finder[current_pg].get_plotted_data() model = self.page_finder[current_pg].get_model() ## if user has already selected a model to plot ## redraw the model with data smeared smear =self.page_finder[current_pg].get_smearer() if model!= None: self.draw_model( model=model, data= data, smearer= smear, qmin= qmin, qmax= qmax) def draw_model(self, model, data= None,smearer= None, enable1D= True, enable2D= False, qmin= DEFAULT_QMIN, qmax= DEFAULT_QMAX, qstep= DEFAULT_NPTS): """ Draw model. @param model: the model to draw @param name: the name of the model to draw @param data: the data on which the model is based to be drawn @param description: model's description @param enable1D: if true enable drawing model 1D @param enable2D: if true enable drawing model 2D @param qmin: Range's minimum value to draw model @param qmax: Range's maximum value to draw model @param qstep: number of step to divide the x and y-axis """ ## draw model 1D with no loaded data self._draw_model1D( model= model, data= data,enable1D=enable1D, smearer= smearer, qmin= qmin, qmax= qmax, qstep= qstep ) ## draw model 2D with no initial data self._draw_model2D(model=model, data = data, enable2D= enable2D, qmin=qmin, qmax=qmax, qstep=qstep) def onFit(self): """ perform fit """ ## count the number of fitproblem schedule to fit fitproblem_count= 0 for value in self.page_finder.itervalues(): if value.get_scheduled()==1: fitproblem_count += 1 ## if simultaneous fit change automatically the engine to park if fitproblem_count >1: self._on_change_engine(engine='park') from sans.fit.Fitting import Fit self.fitter= Fit(self._fit_engine) if self._fit_engine=="park": engineType="Simultaneous Fit" else: engineType="Single Fit" fproblemId = 0 current_pg=None for page, value in self.page_finder.iteritems(): try: if value.get_scheduled()==1: #Get list of parameters name to fit pars = [] templist = [] templist = page.get_param_list() for element in templist: name = str(element[1]) pars.append(name) #Set Engine (model , data) related to the page on self._fit_helper( current_pg=page, value=value,pars=pars, id=fproblemId, title= engineType ) fproblemId += 1 current_pg= page except: msg= "%s error: %s" % (engineType,sys.exc_value) wx.PostEvent(self.parent, StatusEvent(status= msg )) return #Do the simultaneous fit try: ## If a thread is already started, stop it if self.calc_fit!= None and self.calc_fit.isrunning(): self.calc_fit.stop() wx.PostEvent(self.parent, StatusEvent(status="Start the computation", curr_thread=self.calc_fit,type="start")) wx.PostEvent(self.parent, StatusEvent(status="Computing...", curr_thread=self.calc_fit,type="progress")) ## perform single fit if self._fit_engine=="scipy": qmin, qmax= current_pg.get_range() self.calc_fit=FitThread(parent =self.parent, fn= self.fitter, cpage=current_pg, pars= pars, completefn= self._single_fit_completed, updatefn=self._updateFit) else: ## Perform more than 1 fit at the time self.calc_fit=FitThread(parent =self.parent, fn= self.fitter, completefn= self._simul_fit_completed, updatefn=self._updateFit) self.calc_fit.queue() self.calc_fit.ready(2.5) except FitAbort: print "in pluging" except: msg= "%s error: %s" % (engineType,sys.exc_value) wx.PostEvent(self.parent, StatusEvent(status= msg ,type="stop")) return def onCalculateSld(self, event): """ Compute the scattering length density of molecula """ from sldPanel import SldWindow frame = SldWindow(base=self.parent) frame.Show(True) def _onEVT_SLICER_PANEL(self, event): """ receive and event telling to update a panel with a name starting with event.panel_name. this method update slicer panel for a given interactor. @param event: contains type of slicer , paramaters for updating the panel and panel_name to find the slicer 's panel concerned. """ for item in self.parent.panels: if self.parent.panels[item].window_caption.startswith(event.panel_name): self.parent.panels[item].set_slicer(event.type, event.params) self.parent._mgr.Update() def _closed_fitpage(self, event): """ request fitpanel to close a given page when its unique data is removed from the plot """ self.fit_panel._close_fitpage(event.data) def _add_page_onmenu(self, name,fitproblem=None): """ Add name of a closed page of fitpanel in a menu """ list = self.menu1.GetMenuItems() for item in list: if name == item.GetItemLabel(): self.closed_page_dict[name][1] = fitproblem if not name in self.closed_page_dict.keys(): # Post paramters event_id = wx.NewId() self.menu1.Append(event_id, name, "Show %s fit panel" % name) self.closed_page_dict[name]= [event_id, fitproblem] wx.EVT_MENU(self.parent,event_id, self._open_closed_page) def _open_closed_page(self, event): """ reopen a closed page """ for name, value in self.closed_page_dict.iteritems(): if event.GetId() in value: id,fitproblem = value if name !="Model": data= fitproblem.get_fit_data() page = self.fit_panel.add_fit_page(data= data,reset=True) if fitproblem != None: self.page_finder[page]=fitproblem if self.sim_page != None: self.sim_page.draw_page() else: model = fitproblem self.fit_panel.add_model_page(model=model, topmenu=True, reset= True) break def _reset_schedule_problem(self, value=0): """ unschedule or schedule all fitproblem to be fit """ for page, fitproblem in self.page_finder.iteritems(): fitproblem.schedule_tofit(value) def _fit_helper(self,current_pg,pars,value, id, title="Single Fit " ): """ helper for fitting """ metadata = value.get_fit_data() model = value.get_model() smearer = value.get_smearer() qmin , qmax = value.get_range() self.fit_id =id #Create list of parameters for fitting used templist=[] pars=pars try: ## create a park model and reset parameter value if constraint ## is given new_model = Model(model) param = value.get_model_param() if len(param)>0: for item in param: param_value = item[1] param_name = item[0] ## check if constraint if param_value !=None and param_name != None: new_model.parameterset[ param_name].set( param_value ) #Do the single fit self.fitter.set_model(new_model, self.fit_id, pars) self.fitter.set_data(data=metadata,Uid=self.fit_id, smearer=smearer,qmin= qmin,qmax=qmax ) self.fitter.select_problem_for_fit(Uid= self.fit_id, value= value.get_scheduled()) value.clear_model_param() except: msg= title +" error: %s" % sys.exc_value wx.PostEvent(self.parent, StatusEvent(status= msg, type="stop")) return def _onSelect(self,event): """ when Select data to fit a new page is created .Its reference is added to self.page_finder """ self.panel = event.GetEventObject() Plugin.on_perspective(self,event=event) for plottable in self.panel.graph.plottables: if plottable.name == self.panel.graph.selected_plottable: #if not hasattr(plottable, "is_data"): if plottable.__class__.__name__=="Theory1D": dy=numpy.zeros(len(plottable.y)) if hasattr(plottable, "dy"): dy= copy.deepcopy(plottable.dy) item= self.copy_data(plottable, dy) item.group_id += "data1D" item.id +="data1D" item.is_data= False title = item.name wx.PostEvent(self.parent, NewPlotEvent(plot=item, title=str(title))) else: item= self.copy_data(plottable, plottable.dy) item.is_data=True ## put the errors values back to the model if the errors were hiden ## before sending them to the fit engine if len(self.err_dy)>0: if item.name in self.err_dy.iterkeys(): dy= self.err_dy[item.name] data= self.copy_data(item, dy) data.is_data= item.is_data else: data= self.copy_data(item, item.dy) data.is_data= item.is_data else: if item.dy==None: dy= numpy.zeros(len(item.y)) data= self.copy_data(item, dy) data.is_data=item.is_data else: data= self.copy_data(item,item.dy) data.is_data=item.is_data else: if plottable.__class__.__name__ !="Data2D": return ## Data2D case if not hasattr(plottable, "is_data"): item= copy.deepcopy(plottable) item.group_id += "data2D" item.id +="data2D" item.is_data= False title = item.name title += " Fit" data = item wx.PostEvent(self.parent, NewPlotEvent(plot=item, title=str(title))) else: item= copy.deepcopy(plottable ) data= copy.deepcopy(plottable ) item.is_data=True data.is_data=True ## create anew page if item.name == self.panel.graph.selected_plottable or\ item.__class__.__name__ is "Data2D": try: page = self.fit_panel.add_fit_page(data) # add data associated to the page created if page !=None: #create a fitproblem storing all link to data,model,page creation if not page in self.page_finder.keys(): self.page_finder[page]= FitProblem() ## item is almost the same as data but contains ## axis info for plotting self.page_finder[page].add_plotted_data(item) self.page_finder[page].add_fit_data(data) wx.PostEvent(self.parent, StatusEvent(status="Page Created")) else: wx.PostEvent(self.parent, StatusEvent(status="Page was already Created")) except: wx.PostEvent(self.parent, StatusEvent(status="Creating Fit page: %s"\ %sys.exc_value)) return def _updateFit(self): """ Is called when values of result are available """ ##Sending a progess message to the status bar wx.PostEvent(self.parent, StatusEvent(status="Computing...")) def _single_fit_completed(self,result,pars,cpage, elapsed=None): """ Display fit result on one page of the notebook. @param result: result of fit @param pars: list of names of parameters fitted @param current_pg: the page where information will be displayed @param qmin: the minimum value of x to replot the model @param qmax: the maximum value of x to replot model """ wx.PostEvent(self.parent, StatusEvent(status="Single fit \ complete! " )) try: if result ==None: msg= "Simple Fitting Stop !!!" wx.PostEvent(self.parent, StatusEvent(status=msg,type="stop")) return if numpy.any(result.pvec ==None )or not numpy.all(numpy.isfinite(result.pvec) ): msg= "Single Fitting did not converge!!!" wx.PostEvent(self.parent, StatusEvent(status=msg,type="stop")) return for page, value in self.page_finder.iteritems(): if page==cpage : model= value.get_model() break i = 0 for name in pars: if result.pvec.__class__==numpy.float64: model.setParam(name,result.pvec) else: model.setParam(name,result.pvec[i]) i += 1 ## Reset values of the current page to fit result cpage.onsetValues(result.fitness, result.pvec,result.stderr) ## plot the current model with new param metadata = self.page_finder[cpage].get_fit_data() model = self.page_finder[cpage].get_model() qmin, qmax= self.page_finder[cpage].get_range() smearer =self.page_finder[cpage].get_smearer() #Replot models msg= "Single Fit completed. plotting... %s:"%model.name wx.PostEvent(self.parent, StatusEvent(status="%s " % msg)) self.draw_model( model=model, data= metadata, smearer= smearer, qmin= qmin, qmax= qmax) wx.PostEvent(self.parent, StatusEvent(status=" " , type="stop")) except: msg= "Single Fit completed but Following error occurred:%s"% sys.exc_value wx.PostEvent(self.parent, StatusEvent(status=msg,type="stop")) return def _simul_fit_completed(self,result,pars=None,cpage=None, elapsed=None): """ Parameter estimation completed, display the results to the user @param alpha: estimated best alpha @param elapsed: computation time """ wx.PostEvent(self.parent, StatusEvent(status="Simultaneous fit complete ")) ## fit more than 1 model at the same time try: if result ==None: msg= "Complex Fitting Stop !!!" wx.PostEvent(self.parent, StatusEvent(status=msg,type="stop")) return if numpy.any(result.pvec ==None )or not numpy.all(numpy.isfinite(result.pvec) ): msg= "Single Fitting did not converge!!!" wx.PostEvent(self.parent, StatusEvent(status=msg,type="stop")) return for page, value in self.page_finder.iteritems(): if value.get_scheduled()==1: model = value.get_model() metadata = value.get_plotted_data() small_out = [] small_cov = [] i = 0 #Separate result in to data corresponding to each page for p in result.parameters: model_name,param_name = self.split_string(p.name) if model.name == model_name: p_name= model.name+"."+param_name if p.name == p_name: small_out.append(p.value ) model.setParam(param_name,p.value) small_cov.append(p.stderr) else: value= model.getParam(param_name) small_out.append(value ) small_cov.append(None) # Display result on each page page.onsetValues(result.fitness, small_out,small_cov) #Replot models msg= "Simultaneous Fit completed. plotting... %s:"%model.name wx.PostEvent(self.parent, StatusEvent(status="%s " % msg)) qmin, qmax= page.get_range() smearer =self.page_finder[page].get_smearer() self.draw_model( model=model, data= metadata, smearer=smearer, qmin= qmin, qmax= qmax) wx.PostEvent(self.parent, StatusEvent(status="", type="stop")) except: msg= "Simultaneous Fit completed" msg +=" but Following error occurred:%s"%sys.exc_value wx.PostEvent(self.parent, StatusEvent(status=msg,type="stop")) return def _on_show_panel(self, event): print "_on_show_panel: fitting" def _onset_engine_park(self,event): """ set engine to park """ self._on_change_engine('park') def _onset_engine_scipy(self,event): """ set engine to scipy """ self._on_change_engine('scipy') def _on_slicer_event(self, event): """ Receive a panel as event and send it to guiframe @param event: event containing a panel """ if event.panel!=None: new_panel = event.panel self.slicer_panels.append(event.panel) # Set group ID if available event_id = self.parent.popup_panel(new_panel) #self.menu3.Append(event_id, new_panel.window_caption, # "Show %s plot panel" % new_panel.window_caption) # Set UID to allow us to reference the panel later new_panel.uid = event_id self.mypanels.append(new_panel) return def _onclearslicer(self, event): """ Clear the boxslicer when close the panel associate with this slicer """ name =event.GetPane().caption for panel in self.slicer_panels: if panel.window_caption==name: for item in self.parent.panels: if hasattr(self.parent.panels[item],"uid"): if self.parent.panels[item].uid ==panel.base.uid: self.parent.panels[item].onClearSlicer(event) self.parent._mgr.Update() break break def _return_engine_type(self): """ return the current type of engine """ return self._fit_engine def _on_change_engine(self, engine='park'): """ Allow to select the type of engine to perform fit @param engine: the key work of the engine """ ## saving fit engine name self._fit_engine = engine ## change menu item state if engine=="park": self.menu1.FindItemByPosition(0).Check(False) self.menu1.FindItemByPosition(1).Check(True) else: self.menu1.FindItemByPosition(0).Check(True) self.menu1.FindItemByPosition(1).Check(False) ## post a message to status bar wx.PostEvent(self.parent, StatusEvent(status="Engine set to: %s" % self._fit_engine)) ## Bind every open fit page with a newevent to know the current fitting engine import fitpage event= fitpage.FitterTypeEvent() event.type = self._fit_engine for key in self.page_finder.keys(): wx.PostEvent(key, event) def _on_model_panel(self, evt): """ react to model selection on any combo box or model menu.plot the model @param evt: wx.combobox event """ model = evt.model if model ==None: return model.origin_name = model.name current_pg = self.fit_panel.get_current_page() ## make sure nothing is done on self.sim_page ## example trying to call set_panel on self.sim_page if current_pg != self.sim_page : if self.page_finder[current_pg].get_model()== None : model.name="M"+str(self.index_model) self.index_model += 1 else: model.name= self.page_finder[current_pg].get_model().name metadata = self.page_finder[current_pg].get_plotted_data() # save the name containing the data name with the appropriate model self.page_finder[current_pg].set_model(model) qmin, qmax= current_pg.get_range() self.page_finder[current_pg].set_range(qmin=qmin, qmax=qmax) smearer= self.page_finder[current_pg].get_smearer() # save model name self.draw_model( model=model,smearer=smearer, data= metadata, qmin=qmin, qmax=qmax) if self.sim_page!=None: self.sim_page.draw_page() def _on_model_menu(self, evt): """ Plot a theory from a model selected from the menu @param evt: wx.menu event """ model = evt.model Plugin.on_perspective(self,event=evt) # Create a model page. If a new page is created, the model # will be plotted automatically. If a page already exists, # the content will be updated and the plot refreshed self.fit_panel.add_model_page(model,topmenu=True) def _update1D(self,x, output): """ Update the output of plotting model 1D """ wx.PostEvent(self.parent, StatusEvent(status="Plot \ #updating ... ",type="update")) self.calc_thread.ready(0.01) def _fill_default_model2D(self, theory, qmax,qstep, qmin=None): """ fill Data2D with default value @param theory: Data2D to fill """ from DataLoader.data_info import Detector, Source detector = Detector() theory.detector.append(detector) theory.detector[0].distance=1e+32 theory.source= Source() theory.source.wavelength=2*math.pi/1e+32 ## Create detector for Model 2D xmax=2*theory.detector[0].distance*math.atan(\ qmax/(4*math.pi/theory.source.wavelength)) theory.detector[0].pixel_size.x= xmax/(qstep/2-0.5) theory.detector[0].pixel_size.y= xmax/(qstep/2-0.5) theory.detector[0].beam_center.x= qmax theory.detector[0].beam_center.y= qmax ## create x_bins and y_bins of the model 2D distance = theory.detector[0].distance pixel = qstep/2-1 theta = pixel / distance / qstep#100.0 wavelength = theory.source.wavelength pixel_width_x = theory.detector[0].pixel_size.x pixel_width_y = theory.detector[0].pixel_size.y center_x = theory.detector[0].beam_center.x/pixel_width_x center_y = theory.detector[0].beam_center.y/pixel_width_y size_x, size_y= numpy.shape(theory.data) for i_x in range(size_x): theta = (i_x-center_x)*pixel_width_x / distance qx = 4.0*math.pi/wavelength * math.tan(theta/2.0) theory.x_bins.append(qx) for i_y in range(size_y): theta = (i_y-center_y)*pixel_width_y / distance qy =4.0*math.pi/wavelength * math.tan(theta/2.0) theory.y_bins.append(qy) theory.group_id ="Model" theory.id ="Model" ## determine plot boundaries theory.xmin= -qmax theory.xmax= qmax theory.ymin= -qmax theory.ymax= qmax def _get_plotting_info(self, data=None): """ get plotting info from data if data !=None else use some default """ my_info = PlotInfo() if data !=None: if hasattr(data,"info"): x_name, x_units = data.get_xaxis() y_name, y_units = data.get_yaxis() my_info._xunit = x_units my_info._xaxis = x_name my_info._yunit = y_units my_info._yaxis = y_name my_info.title= data.name if hasattr(data, "info"): my_info.info= data.info if hasattr(data, "group_id"): my_info.group_id= data.group_id return my_info def _complete1D(self, x,y, elapsed,model,data=None): """ Complete plotting 1D data """ try: new_plot = Theory1D(x=x, y=y) my_info = self._get_plotting_info( data) new_plot.name = model.name new_plot.id = my_info.id new_plot.group_id = my_info.group_id new_plot.xaxis( my_info._xaxis, my_info._xunit) new_plot.yaxis( my_info._yaxis, my_info._yunit) if data!=None: if new_plot.id == data.id: new_plot.id += "Model" new_plot.is_data =False title= new_plot.name # Pass the reset flag to let the plotting event handler # know that we are replacing the whole plot if title== None: title = "Analytical model 1D " if data ==None: wx.PostEvent(self.parent, NewPlotEvent(plot=new_plot, title= str(title), reset=True )) else: wx.PostEvent(self.parent, NewPlotEvent(plot=new_plot, title= str(title))) msg = "Plot 1D complete !" wx.PostEvent( self.parent, StatusEvent( status= msg , type="stop" )) except: msg= " Error occurred when drawing %s Model 1D: "%new_plot.name msg+= " %s"%sys.exc_value wx.PostEvent( self.parent, StatusEvent(status= msg, type="stop" )) return def _update2D(self, output,time=None): """ Update the output of plotting model """ wx.PostEvent(self.parent, StatusEvent(status="Plot \ #updating ... ",type="update")) self.calc_thread.ready(0.01) def _complete2D(self, image,data, model, elapsed,qmin, qmax,qstep=DEFAULT_NPTS): """ Complete get the result of modelthread and create model 2D that can be plot. """ err_image = numpy.zeros(numpy.shape(image)) theory= Data2D(image= image , err_image= err_image) theory.name= model.name if data ==None: self._fill_default_model2D(theory= theory, qmax=qmax,qstep=qstep, qmin= qmin) else: theory.id= data.id+"Model" theory.group_id= data.name+"Model" theory.x_bins= data.x_bins theory.y_bins= data.y_bins theory.detector= data.detector theory.source= data.source theory.is_data =False ## plot boundaries theory.ymin= data.ymin theory.ymax= data.ymax theory.xmin= data.xmin theory.xmax= data.xmax ## plot wx.PostEvent(self.parent, NewPlotEvent(plot=theory, title="Analytical model 2D ", reset=True )) msg = "Plot 2D complete !" wx.PostEvent( self.parent, StatusEvent( status= msg , type="stop" )) def _on_data_error(self, event): """ receives and event from plotting plu-gins to store the data name and their errors of y coordinates for 1Data hide and show error """ self.err_dy= event.err_dy def _draw_model2D(self,model,data=None,description=None, enable2D=False, qmin=DEFAULT_QMIN, qmax=DEFAULT_QMAX, qstep=DEFAULT_NPTS): """ draw model in 2D @param model: instance of the model to draw @param description: the description of the model @param enable2D: when True allows to draw model 2D @param qmin: the minimum value to draw model 2D @param qmax: the maximum value to draw model 2D @param qstep: the number of division of Qx and Qy of the model to draw """ x= numpy.linspace(start= -1*qmax, stop= qmax, num= qstep, endpoint=True ) y = numpy.linspace(start= -1*qmax, stop= qmax, num= qstep, endpoint=True ) ## use data info instead if data !=None: ## check if data2D to plot if hasattr(data, "x_bins"): enable2D = True x= data.x_bins y= data.y_bins if not enable2D: return try: from model_thread import Calc2D ## If a thread is already started, stop it if self.calc_2D != None and self.calc_2D.isrunning(): self.calc_2D.stop() self.calc_2D = Calc2D( x= x, y= y, model= model, data = data, qmin= qmin, qmax= qmax, qstep= qstep, completefn= self._complete2D, updatefn= self._update2D ) self.calc_2D.queue() except: raise #msg= " Error occurred when drawing %s Model 2D: "%model.name #msg+= " %s"%sys.exc_value #wx.PostEvent( self.parent, StatusEvent(status= msg )) #return def _draw_model1D(self, model, data=None, smearer= None, qmin=DEFAULT_QMIN, qmax=DEFAULT_QMAX, qstep= DEFAULT_NPTS,enable1D= True): """ Draw model 1D from loaded data1D @param data: loaded data @param model: the model to plot """ x= numpy.linspace(start= qmin, stop= qmax, num= qstep, endpoint=True ) if data!=None: ## check for data2D if hasattr(data,"x_bins"): return x = data.x if qmin == DEFAULT_QMIN : qmin = min(data.x) if qmax == DEFAULT_QMAX: qmax = max(data.x) if not enable1D: return try: from model_thread import Calc1D ## If a thread is already started, stop it if self.calc_1D!= None and self.calc_1D.isrunning(): self.calc_1D.stop() self.calc_1D= Calc1D( x= x, data = data, model= model, qmin = qmin, qmax = qmax, smearer = smearer, completefn = self._complete1D, updatefn = self._update1D ) self.calc_1D.queue() except: msg= " Error occurred when drawing %s Model 1D: "%model.name msg+= " %s"%sys.exc_value wx.PostEvent( self.parent, StatusEvent(status= msg )) return def profile(fn, *args, **kw): import cProfile, pstats, os global call_result def call(): global call_result call_result = fn(*args, **kw) cProfile.runctx('call()', dict(call=call), {}, 'profile.out') stats = pstats.Stats('profile.out') stats.sort_stats('time') #stats.sort_stats('calls') stats.print_stats() os.unlink('profile.out') return call_result if __name__ == "__main__": i = Plugin()