""" Fitting perspective """ ################################################################################ #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 import sys import os import wx import logging import numpy import time from copy import deepcopy import models from sans.dataloader.loader import Loader from sans.guiframe.dataFitting import Data2D from sans.guiframe.dataFitting import Data1D from sans.guiframe.dataFitting import check_data_validity from sans.guiframe.events import NewPlotEvent from sans.guiframe.events import StatusEvent from sans.guiframe.events import EVT_SLICER_PANEL from sans.guiframe.events import EVT_SLICER_PARS_UPDATE from sans.guiframe.gui_style import GUIFRAME_ID from sans.guiframe.plugin_base import PluginBase from sans.guiframe.data_processor import BatchCell from sans.fit.Fitting import Fit from .console import ConsoleUpdate from .fitproblem import FitProblemDictionary from .fitpanel import FitPanel from .fit_thread import FitThread from .pagestate import Reader from .fitpage import Chi2UpdateEvent from sans.perspectives.calculator.model_editor import TextDialog from sans.perspectives.calculator.model_editor import EditorWindow MAX_NBR_DATA = 4 SANS_F_TOL = 5e-05 (PageInfoEvent, EVT_PAGE_INFO) = wx.lib.newevent.NewEvent() if sys.platform.count("darwin") == 0: ON_MAC = False else: ON_MAC = True class Plugin(PluginBase): """ Fitting plugin is used to perform fit """ def __init__(self, standalone=False): PluginBase.__init__(self, name="Fitting", standalone=standalone) #list of panel to send to guiframe self.mypanels = [] # reference to the current running thread self.calc_2D = None self.calc_1D = None self.color_dict = {} self.fit_thread_list = {} self.residuals = None self.weight = None self.fit_panel = None # Start with a good default self.elapsed = 0.022 # the type of optimizer selected, park or scipy self.fitter = None self.fit_panel = None #let fit ready self.fitproblem_count = 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' self._gui_engine = None ## Relative error desired in the sum of squares (float); scipy only self.ftol = SANS_F_TOL self.batch_reset_flag = True #List of selected data self.selected_data_list = [] ## list of slicer panel created to display slicer parameters and results self.slicer_panels = [] # model 2D view self.model2D_id = None #keep reference of the simultaneous fit page self.sim_page = None self.sim_menu = None self.batch_page = None self.batch_menu = None self.index_model = 0 self.test_model_color = None #Create a reader for fit page's state self.state_reader = None self._extensions = '.fitv' self.scipy_id = wx.NewId() self.park_id = wx.NewId() self.menu1 = None self.new_model_frame = None self.temp_state = [] self.state_index = 0 self.sfile_ext = None # take care of saving data, model and page associated with each other self.page_finder = {} # Log startup logging.info("Fitting plug-in started") self.batch_capable = self.get_batch_capable() def get_batch_capable(self): """ Check if the plugin has a batch capability """ return True def create_fit_problem(self, page_id): """ Given an ID create a fitproblem container """ self.page_finder[page_id] = FitProblemDictionary() def delete_fit_problem(self, page_id): """ Given an ID create a fitproblem container """ if page_id in self.page_finder.iterkeys(): del self.page_finder[page_id] def add_color(self, color, id): """ adds a color as a key with a plot id as its value to a dictionary """ self.color_dict[id] = color def on_batch_selection(self, flag): """ switch the the notebook of batch mode or not """ self.batch_on = flag if self.fit_panel is not None: self.fit_panel.batch_on = self.batch_on def populate_menu(self, 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() id1 = wx.NewId() simul_help = "Add new fit panel" self.menu1.Append(id1, '&New Fit Page', simul_help) wx.EVT_MENU(owner, id1, self.on_add_new_page) self.menu1.AppendSeparator() self.id_simfit = wx.NewId() simul_help = "Simultaneous Fit" self.menu1.Append(self.id_simfit, '&Simultaneous Fit', simul_help) wx.EVT_MENU(owner, self.id_simfit, self.on_add_sim_page) self.sim_menu = self.menu1.FindItemById(self.id_simfit) self.sim_menu.Enable(False) #combined Batch self.id_batchfit = wx.NewId() batch_help = "Combined Batch" self.menu1.Append(self.id_batchfit, '&Combine Batch Fit', batch_help) wx.EVT_MENU(owner, self.id_batchfit, self.on_add_sim_page) self.batch_menu = self.menu1.FindItemById(self.id_batchfit) self.batch_menu.Enable(False) self.menu1.AppendSeparator() #Set park engine scipy_help = "Scipy Engine: Perform Simple fit. More in Help window...." self.menu1.AppendCheckItem(self.scipy_id, "Simple FitEngine [LeastSq]", scipy_help) wx.EVT_MENU(owner, self.scipy_id, self._onset_engine_scipy) park_help = "Park Engine: Perform Complex fit. More in Help window...." self.menu1.AppendCheckItem(self.park_id, "Complex FitEngine [ParkMC]", park_help) wx.EVT_MENU(owner, self.park_id, self._onset_engine_park) self.menu1.FindItemById(self.scipy_id).Check(True) self.menu1.FindItemById(self.park_id).Check(False) self.menu1.AppendSeparator() self.id_tol = wx.NewId() ftol_help = "Change the current FTolerance (=%s) " % str(self.ftol) ftol_help += "of Simple FitEngine..." self.menu1.Append(self.id_tol, "Change FTolerance", ftol_help) wx.EVT_MENU(owner, self.id_tol, self.show_ftol_dialog) self.menu1.AppendSeparator() self.id_reset_flag = wx.NewId() resetf_help = "BatchFit: If checked, the initial param values will be " resetf_help += "propagated from the previous results. " resetf_help += "Otherwise, the same initial param values will be used " resetf_help += "for all fittings." self.menu1.AppendCheckItem(self.id_reset_flag, "Chain Fitting [BatchFit Only]", resetf_help) wx.EVT_MENU(owner, self.id_reset_flag, self.on_reset_batch_flag) chain_menu = self.menu1.FindItemById(self.id_reset_flag) chain_menu.Check(not self.batch_reset_flag) chain_menu.Enable(self.batch_on) self.menu1.AppendSeparator() self.edit_model_menu = wx.Menu() # Find and put files name in menu try: self.set_edit_menu(owner=owner) except: raise self.id_edit = wx.NewId() editmodel_help = "Edit customized model sample file" self.menu1.AppendMenu(self.id_edit, "Edit Custom Model", self.edit_model_menu, editmodel_help) #create menubar items return [(self.menu1, self.sub_menu)] def edit_custom_model(self, event): """ Get the python editor panel """ id = event.GetId() label = self.edit_menu.GetLabel(id) from sans.perspectives.calculator.pyconsole import PyConsole filename = os.path.join(models.find_plugins_dir(), label) frame = PyConsole(parent=self.parent, manager=self, panel=self.fit_panel, title='Advanced Custom Model Editor', filename=filename) self.put_icon(frame) frame.Show(True) def delete_custom_model(self, event): """ Delete custom model file """ id = event.GetId() label = self.delete_menu.GetLabel(id) toks = os.path.splitext(label) path = os.path.join(models.find_plugins_dir(), toks[0]) try: for ext in ['.py', '.pyc']: p_path = path + ext os.remove(p_path) self.update_custom_combo() self.delete_menu.Delete(id) for item in self.edit_menu.GetMenuItems(): if item.GetLabel() == label: self.edit_menu.DeleteItem(item) break except: msg ='Delete Error: \nCould not delete the file; Check if in use.' wx.MessageBox(msg) def make_sum_model(self, event): """ Edit summodel template and make one """ id = event.GetId() model_manager = models.ModelManager() model_list = model_manager.get_model_name_list() plug_dir = models.find_plugins_dir() textdial = TextDialog(None, self, -1, 'Easy Sum(p1, p2)', model_list, plug_dir) self.put_icon(textdial) textdial.ShowModal() textdial.Destroy() def make_new_model(self, event): """ Make new model """ if self.new_model_frame != None and self.new_model_frame.IsShown(): self.new_model_frame.Show(False) else: id = event.GetId() dir_path = models.find_plugins_dir() title = "New Custom Model Function" self.new_model_frame = EditorWindow(parent=self, base=self, path=dir_path, title=title) self.put_icon(self.new_model_frame) self.new_model_frame.Show(True) def update_custom_combo(self): """ Update custom model list in the fitpage combo box """ try: # Update edit menus self.set_edit_menu_helper(self.parent, self.edit_custom_model) self.set_edit_menu_helper(self.parent, self.delete_custom_model) temp = self.fit_panel.reset_pmodel_list() if temp: # Set the new custom model list for all fit pages for uid, page in self.fit_panel.opened_pages.iteritems(): if hasattr(page, "formfactorbox"): page.model_list_box = temp current_val = page.formfactorbox.GetValue() pos = page.formfactorbox.GetSelection() page._show_combox_helper() new_val = page.formfactorbox.GetValue() if current_val != new_val and new_val != '': page.formfactorbox.SetValue(new_val) else: page.formfactorbox.SetValue(current_val) except: pass def set_edit_menu(self, owner): """ Set list of the edit model menu labels """ id = wx.NewId() #new_model_menu = wx.Menu() self.edit_model_menu.Append(id, 'New', 'Add a new model function') wx.EVT_MENU(owner, id, self.make_new_model) id = wx.NewId() self.edit_model_menu.Append(id, 'Sum(p1, p2)', 'Sum of two model functions') wx.EVT_MENU(owner, id, self.make_sum_model) e_id = wx.NewId() self.edit_menu = wx.Menu() self.edit_model_menu.AppendMenu(e_id, 'Advanced', self.edit_menu) self.set_edit_menu_helper(owner, self.edit_custom_model) d_id = wx.NewId() self.delete_menu = wx.Menu() self.edit_model_menu.AppendMenu(d_id, 'Delete', self.delete_menu) self.set_edit_menu_helper(owner, self.delete_custom_model) def set_edit_menu_helper(self, owner=None, menu=None): """ help for setting list of the edit model menu labels """ if menu == None: menu = self.edit_custom_model list_fnames = os.listdir(models.find_plugins_dir()) list_fnames.sort() for f_item in list_fnames: name = os.path.basename(f_item) toks = os.path.splitext(name) if toks[-1] == '.py' and not toks[0] == '__init__': if menu == self.edit_custom_model: if toks[0] == 'easy_sum_of_p1_p2': continue submenu = self.edit_menu else: submenu = self.delete_menu has_file = False for item in submenu.GetMenuItems(): if name == submenu.GetLabel(item.GetId()): has_file = True if not has_file: id = wx.NewId() submenu.Append(id, name) wx.EVT_MENU(owner, id, menu) has_file = False def put_icon(self, frame): """ Put icon in the frame title bar """ if hasattr(frame, "IsIconized"): if not frame.IsIconized(): try: icon = self.parent.GetIcon() frame.SetIcon(icon) except: pass def on_add_sim_page(self, event): """ Create a page to access simultaneous fit option """ id = event.GetId() caption = "Simultaneous Fit" page = self.sim_page if id == self.id_batchfit: caption = "Combined Batch" page = self.batch_page def set_focus_page(page): page.Show(True) page.Refresh() page.SetFocus() self.parent._mgr.Update() msg = "%s already opened\n" % str(page.window_caption) wx.PostEvent(self.parent, StatusEvent(status=msg)) if page != None: return set_focus_page(page) if caption == "Simultaneous Fit": self.sim_page = self.fit_panel.add_sim_page(caption=caption) else: self.batch_page = self.fit_panel.add_sim_page(caption=caption) def help(self, evt): """ Show a general help dialog. """ from help_panel import HelpWindow frame = HelpWindow(None, -1, 'HelpWindow') if hasattr(frame, "IsIconized"): if not frame.IsIconized(): try: icon = self.parent.GetIcon() frame.SetIcon(icon) except: pass frame.Show(True) def get_context_menu(self, plotpanel=None): """ Get the context menu items available for P(r).them allow fitting option for Data2D and Data1D only. :param graph: the Graph object to which we attach the context menu :return: a list of menu items with call-back function :note: if Data1D was generated from Theory1D the fitting option is not allowed """ graph = plotpanel.graph fit_option = "Select data for fitting" fit_hint = "Dialog with fitting parameters " if graph.selected_plottable not in plotpanel.plots: return [] item = plotpanel.plots[graph.selected_plottable] if item.__class__.__name__ is "Data2D": if hasattr(item, "is_data"): if item.is_data: return [[fit_option, fit_hint, self._onSelect]] else: return [] return [[fit_option, fit_hint, self._onSelect]] else: # if is_data is true , this in an actual data loaded #else it is a data created from a theory model if hasattr(item, "is_data"): if item.is_data: return [[fit_option, fit_hint, self._onSelect]] else: return [] return [] def get_panels(self, parent): """ Create and return a list of panel objects """ self.parent = parent #self.parent.Bind(EVT_FITSTATE_UPDATE, self.on_set_state_helper) # Creation of the fit panel self.fit_panel = FitPanel(parent=self.parent, manager=self) self.on_add_new_page(event=None) #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) #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(EVT_SLICER_PARS_UPDATE, self._onEVT_SLICER_PANEL) self.parent._mgr.Bind(wx.aui.EVT_AUI_PANE_CLOSE,self._onclearslicer) #Create reader when fitting panel are created self.state_reader = Reader(self.set_state) #append that reader to list of available reader loader = Loader() loader.associate_file_reader(".fitv", self.state_reader) #Send the fitting panel to guiframe self.mypanels.append(self.fit_panel) return self.mypanels def clear_panel(self): """ """ self.fit_panel.clear_panel() def set_default_perspective(self): """ Call back method that True to notify the parent that the current plug-in can be set as default perspective. when returning False, the plug-in is not candidate for an automatic default perspective setting """ return True def delete_data(self, data): """ delete the given data from panel """ self.fit_panel.delete_data(data) def set_data(self, data_list=None): """ receive a list of data to fit """ if data_list is None: data_list = [] selected_data_list = [] if self.batch_on: page = self.add_fit_page(data=data_list) else: if len(data_list) > MAX_NBR_DATA: from fitting_widgets import DataDialog dlg = DataDialog(data_list=data_list, nb_data=MAX_NBR_DATA) if dlg.ShowModal() == wx.ID_OK: selected_data_list = dlg.get_data() dlg.Destroy() else: selected_data_list = data_list try: group_id = wx.NewId() for data in selected_data_list: if data is not None: # 2D has no same group_id if data.__class__.__name__ == 'Data2D': group_id = wx.NewId() data.group_id = group_id if group_id not in data.list_group_id: data.list_group_id.append(group_id) page = self.add_fit_page(data=[data]) except: msg = "Fitting Set_data: " + str(sys.exc_value) wx.PostEvent(self.parent, StatusEvent(status=msg, info="error")) def set_top_panel(self): """ Close default (welcome) panel """ if 'default' in self.parent.panels: self.parent.on_close_welcome_panel() def set_theory(self, theory_list=None): """ """ #set the model state for a given theory_state: for item in theory_list: try: _, theory_state = item self.fit_panel.set_model_state(theory_state) except: msg = "Fitting: cannot deal with the theory received" logging.error("set_theory " + msg + "\n" + str(sys.exc_value)) wx.PostEvent(self.parent, StatusEvent(status=msg, info="error")) def set_state(self, state=None, datainfo=None, format=None): """ Call-back method for the fit page state reader. This method is called when a .fitv/.svs file is loaded. : param state: PageState object : param datainfo: data """ #state = self.state_reader.get_state() if state != None: state = state.clone() # store fitting state in temp_state self.temp_state.append(state) else: self.temp_state = [] # index to start with for a new set_state self.state_index = 0 # state file format self.sfile_ext = format self.on_set_state_helper(event=None) def on_set_state_helper(self, event=None): """ Set_state_helper. This actually sets state after plotting data from state file. : event: FitStateUpdateEvent called by dataloader.plot_data from guiframe """ if len(self.temp_state) == 0: if self.state_index == 0 and len(self.mypanels) <= 0 \ and self.sfile_ext == '.svs': #TODO: Why was the following line left in the code # if add_default_pages doesn't exist? try: self.fit_panel.add_default_pages() except: print sys.exc_value self.temp_state = [] self.state_index = 0 return try: # Load fitting state state = self.temp_state[self.state_index] #panel state should have model selection to set_state if state.formfactorcombobox != None: #set state data = self.parent.create_gui_data(state.data) data.group_id = state.data.group_id self.parent.add_data(data_list={data.id: data}) wx.PostEvent(self.parent, NewPlotEvent(plot=data, title=data.title)) #need to be fix later make sure we are sendind guiframe.data #to panel state.data = data page = self.fit_panel.set_state(state) else: #just set data because set_state won't work data = self.parent.create_gui_data(state.data) data.group_id = state.data.group_id self.parent.add_data(data_list={data.id: data}) wx.PostEvent(self.parent, NewPlotEvent(plot=data, title=data.title)) page = self.add_fit_page([data]) caption = page.window_caption self.store_data(uid=page.uid, data_list=page.get_data_list(), caption=caption) self.mypanels.append(page) # get ready for the next set_state self.state_index += 1 #reset state variables to default when all set_state is finished. if len(self.temp_state) == self.state_index: self.temp_state = [] #self.state_index = 0 # Make sure the user sees the fitting panel after loading #self.parent.set_perspective(self.perspective) self.on_perspective(event=None) except: self.state_index = 0 self.temp_state = [] raise def set_param2fit(self, uid, param2fit): """ Set the list of param names to fit for fitprobelm """ self.page_finder[uid].set_param2fit(param2fit) def set_graph_id(self, uid, graph_id): """ Set graph_id for fitprobelm """ self.page_finder[uid].set_graph_id(graph_id) def get_graph_id(self, uid): """ Set graph_id for fitprobelm """ return self.page_finder[uid].get_graph_id() def save_fit_state(self, filepath, fitstate): """ save fit page state into file """ self.state_reader.write(filename=filepath, fitstate=fitstate) def set_fit_weight(self, uid, flag, is2d=False, fid=None): """ Set the fit weights of a given page for all its data by default. If fid is provide then set the range only for the data with fid as id :param uid: id corresponding to a fit page :param fid: id corresponding to a fit problem (data, model) :param weight: current dy data """ if uid in self.page_finder.keys(): self.page_finder[uid].set_weight(flag=flag, is2d=is2d) def set_fit_range(self, uid, qmin, qmax, fid=None): """ Set the fitting range of a given page for all its data by default. If fid is provide then set the range only for the data with fid as id :param uid: id corresponding to a fit page :param fid: id corresponding to a fit problem (data, model) :param qmin: minimum value of the fit range :param qmax: maximum value of the fit range """ if uid in self.page_finder.keys(): self.page_finder[uid].set_range(qmin=qmin, qmax=qmax, fid=fid) def schedule_for_fit(self, value=0, uid=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 uid: the id related to a page contaning fitting information """ if uid in self.page_finder.keys(): self.page_finder[uid].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_id = self.sim_page.uid for uid, value in self.page_finder.iteritems(): if uid != sim_page_id and uid != self.batch_page.uid: 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 Will return model_name = M1 , parameter name = A """ if item.find(".") >= 0: param_names = re.split("\.", item) model_name = param_names[0] ##Assume max len is 3; eg., M0.radius.width if len(param_names) == 3: param_name = param_names[1] + "." + param_names[2] else: param_name = param_names[1] return model_name, param_name def set_ftol(self, ftol=None): """ Set ftol: Relative error desired in the sum of chi squares. """ # check if it is flaot try: f_tol = float(ftol) except: # default f_tol = SANS_F_TOL self.ftol = f_tol # update ftol menu help strings ftol_help = "Change the current FTolerance (=%s) " % str(self.ftol) ftol_help += "of Simple FitEngine..." if self.menu1 != None: self.menu1.SetHelpString(self.id_tol, ftol_help) def show_ftol_dialog(self, event=None): """ Dialog to select ftol for Scipy """ #if event != None: # event.Skip() from ftol_dialog import ChangeFtol panel = ChangeFtol(self.parent, self) panel.ShowModal() def stop_fit(self, uid): """ Stop the fit engine """ if uid in self.fit_thread_list.keys(): calc_fit = self.fit_thread_list[uid] if calc_fit is not None and calc_fit.isrunning(): calc_fit.stop() msg = "Fit stop!" wx.PostEvent(self.parent, StatusEvent(status=msg, type="stop")) del self.fit_thread_list[uid] #set the fit button label of page when fit stop is trigger from #simultaneous fit pane sim_flag = self.sim_page is not None and uid == self.sim_page.uid batch_flag = self.batch_page is not None and uid == self.batch_page.uid if sim_flag or batch_flag: for uid, value in self.page_finder.iteritems(): if value.get_scheduled() == 1: if uid in self.fit_panel.opened_pages.keys(): panel = self.fit_panel.opened_pages[uid] panel._on_fit_complete() def set_smearer(self, uid, smearer, fid, qmin=None, qmax=None, draw=True, enable_smearer=False): """ Get a smear object and store it to a fit problem of fid as id. If proper flag is enable , will plot the theory with smearing information. :param smearer: smear object to allow smearing data of id fid :param enable_smearer: Define whether or not all (data, model) contained in the structure of id uid will be smeared before fitting. :param qmin: the maximum value of the theory plotting range :param qmax: the maximum value of the theory plotting range :param draw: Determine if the theory needs to be plot """ if uid not in self.page_finder.keys(): return self.page_finder[uid].enable_smearing(flag=enable_smearer) self.page_finder[uid].set_smearer(smearer, fid=fid) if draw: ## draw model 1D with smeared data data = self.page_finder[uid].get_fit_data(fid=fid) if data is None: msg = "set_mearer requires at least data.\n" msg += "Got data = %s .\n" % str(data) return #raise ValueError, msg model = self.page_finder[uid].get_model(fid=fid) if model is None: return enable1D = issubclass(data.__class__, Data1D) enable2D = issubclass(data.__class__, Data2D) ## if user has already selected a model to plot ## redraw the model with data smeared smear = self.page_finder[uid].get_smearer(fid=fid) # compute weight for the current data weight = self.page_finder[uid].get_weight(fid=fid) self.draw_model(model=model, data=data, page_id=uid, smearer=smear, enable1D=enable1D, enable2D=enable2D, qmin=qmin, qmax=qmax, weight=weight) self._mac_sleep(0.2) def _mac_sleep(self, sec=0.2): """ Give sleep to MAC """ if ON_MAC: time.sleep(sec) def draw_model(self, model, page_id, data=None, smearer=None, enable1D=True, enable2D=False, state=None, fid=None, toggle_mode_on=False, qmin=None, qmax=None, update_chisqr=True, weight=None, source='model'): """ 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 :param update_chisqr: update chisqr [bool] """ #self.weight = weight if issubclass(data.__class__, Data1D) or not enable2D: ## draw model 1D with no loaded data self._draw_model1D(model=model, data=data, page_id=page_id, enable1D=enable1D, smearer=smearer, qmin=qmin, qmax=qmax, fid=fid, weight=weight, toggle_mode_on=toggle_mode_on, state=state, update_chisqr=update_chisqr, source=source) else: ## draw model 2D with no initial data self._draw_model2D(model=model, page_id=page_id, data=data, enable2D=enable2D, smearer=smearer, qmin=qmin, qmax=qmax, fid=fid, weight=weight, state=state, toggle_mode_on=toggle_mode_on, update_chisqr=update_chisqr, source=source) def onFit(self, uid): """ Get series of data, model, associates parameters and range and send then to series of fit engines. Fit data and model, display result to corresponding panels. :param uid: id related to the panel currently calling this fit function. """ flag = True ## count the number of fitproblem schedule to fit fitproblem_count = 0 for value in self.page_finder.values(): if value.get_scheduled() == 1: fitproblem_count += 1 self._gui_engine = self._return_engine_type() self.fitproblem_count = fitproblem_count if self._fit_engine == "park": engineType = "Simultaneous Fit" else: engineType = "Single Fit" fitter_list = [] sim_fitter = None is_single_fit = True batch_on = False if self.sim_page is not None and self.sim_page.uid == uid: #simulatanous fit only one engine need to be created ## if simultaneous fit change automatically the engine to park self._on_change_engine(engine='park') sim_fitter = Fit(self._fit_engine) sim_fitter.fitter_id = self.sim_page.uid fitter_list.append(sim_fitter) is_single_fit = False batch_on = self.sim_page.batch_on self.fitproblem_count = fitproblem_count if self._fit_engine == "park": engineType = "Simultaneous Fit" else: engineType = "Single Fit" self.current_pg = None list_page_id = [] fit_id = 0 batch_inputs = {} batch_outputs = {} for page_id, value in self.page_finder.iteritems(): # For simulfit (uid give with None), do for-loop # if uid is specified (singlefit), do it only on the page. if engineType == "Single Fit": #combine more than 1 batch page on single mode if self.batch_page is None or self.batch_page.uid != uid: if page_id != uid: continue try: if value.get_scheduled() == 1: value.nbr_residuals_computed = 0 #Get list of parameters name to fit pars = [] templist = [] page = self.fit_panel.get_page_by_id(page_id) self.set_fit_weight(uid=page.uid, flag=page.get_weight_flag(), is2d=page._is_2D()) templist = page.get_param_list() flag = page._update_paramv_on_fit() if not flag: msg = "Fitting range or parameter values are" msg += " invalid in %s" % \ page.window_caption wx.PostEvent(page.parent.parent, StatusEvent(status=msg, info="error", type="stop")) return flag for element in templist: name = str(element[1]) pars.append(name) fitproblem_list = value.values() for fitproblem in fitproblem_list: if sim_fitter is None: fitter = Fit(self._fit_engine) fitter.fitter_id = page_id self._fit_helper(fitproblem=fitproblem, pars=pars, fitter=fitter, fit_id=fit_id, batch_inputs=batch_inputs, batch_outputs=batch_outputs) fitter_list.append(fitter) else: fitter = sim_fitter self._fit_helper(fitproblem=fitproblem, pars=pars, fitter=fitter, fit_id=fit_id, batch_inputs=batch_inputs, batch_outputs=batch_outputs) fit_id += 1 list_page_id.append(page_id) current_page_id = page_id value.clear_model_param() except: flag = False msg = "%s error: %s" % (engineType, sys.exc_value) wx.PostEvent(self.parent, StatusEvent(status=msg, info="error", type="stop")) return flag ## If a thread is already started, stop it #if self.calc_fit!= None and self.calc_fit.isrunning(): # self.calc_fit.stop() msg = "Fitting is in progress..." wx.PostEvent(self.parent, StatusEvent(status=msg, type="progress")) #Handler used for park engine displayed message handler = ConsoleUpdate(parent=self.parent, manager=self, improvement_delta=0.1) self._mac_sleep(0.2) ## perform single fit try: page = self.fit_panel.get_page_by_id(uid) batch_on = page.batch_on except: try: #if the id cannot be found then we deal with a self.sim_page #or a self.batch_page if self.sim_page is not None and uid == self.sim_page.uid: batch_on = self.sim_page.batch_on if self.batch_page is not None and uid == self.batch_page.uid: batch_on = self.batch_page.batch_on except: batch_on = False # batch fit if batch_on: calc_fit = FitThread(handler=handler, fn=fitter_list, pars=pars, batch_inputs=batch_inputs, batch_outputs=batch_outputs, page_id=list_page_id, completefn=self._batch_fit_complete, ftol=self.ftol, reset_flag=self.batch_reset_flag) else: # single fit: not batch and not simul fit if not is_single_fit: current_page_id = self.sim_page.uid ## Perform more than 1 fit at the time calc_fit = FitThread(handler=handler, fn=fitter_list, batch_inputs=batch_inputs, batch_outputs=batch_outputs, page_id=list_page_id, updatefn=handler.update_fit, completefn=self._fit_completed, ftol=self.ftol) self.fit_thread_list[current_page_id] = calc_fit calc_fit.queue() msg = "Fitting is in progress..." wx.PostEvent(self.parent, StatusEvent(status=msg, type="progress")) self.ready_fit(calc_fit=calc_fit) return flag def ready_fit(self, calc_fit): """ Ready for another fit """ if self.fitproblem_count != None and self.fitproblem_count > 1: calc_fit.ready(2.5) else: time.sleep(0.4) def remove_plot(self, uid, fid=None, theory=False): """ remove model plot when a fit page is closed :param uid: the id related to the fitpage to close :param fid: the id of the fitproblem(data, model, range,etc) """ if uid not in self.page_finder.keys(): return fitproblemList = self.page_finder[uid].get_fit_problem(fid) for fitproblem in fitproblemList: data = fitproblem.get_fit_data() model = fitproblem.get_model() plot_id = None if model is not None: plot_id = data.id + model.name if theory: plot_id = data.id + model.name group_id = data.group_id wx.PostEvent(self.parent, NewPlotEvent(id=plot_id, group_id=group_id, action='remove')) def store_data(self, uid, data_list=None, caption=None): """ Recieve a list of data and store them ans well as a caption of the fit page where they come from. :param uid: if related to a fit page :param data_list: list of data to fit :param caption: caption of the window related to these data """ if data_list is None: data_list = [] self.page_finder[uid].set_fit_data(data=data_list) if caption is not None: self.page_finder[uid].set_fit_tab_caption(caption=caption) def on_add_new_page(self, event=None): """ ask fit panel to create a new empty page """ try: page = self.fit_panel.add_empty_page() # add data associated to the page created if page != None: wx.PostEvent(self.parent, StatusEvent(status="Page Created", info="info")) else: msg = "Page was already Created" wx.PostEvent(self.parent, StatusEvent(status=msg, info="warning")) self.set_top_panel() except: msg = "Creating Fit page: %s"%sys.exc_value wx.PostEvent(self.parent, StatusEvent(status=msg, info="error")) def add_fit_page(self, data): """ given a data, ask to the fitting panel to create a new fitting page, get this page and store it into the page_finder of this plug-in :param data: is a list of data """ page = self.fit_panel.set_data(data) # page could be None when loading state files if page == None: return page #append Data1D to the panel containing its theory #if theory already plotted if page.uid in self.page_finder: data = page.get_data() theory_data = self.page_finder[page.uid].get_theory_data(data.id) if issubclass(data.__class__, Data2D): data.group_id = wx.NewId() if theory_data is not None: group_id = str(page.uid) + " Model1D" wx.PostEvent(self.parent, NewPlotEvent(group_id=group_id, action="delete")) self.parent.update_data(prev_data=theory_data, new_data=data) else: if theory_data is not None: group_id = str(page.uid) + " Model2D" data.group_id = theory_data.group_id wx.PostEvent(self.parent, NewPlotEvent(group_id=group_id, action="delete")) self.parent.update_data(prev_data=theory_data, new_data=data) self.store_data(uid=page.uid, data_list=page.get_data_list(), caption=page.window_caption) if self.sim_page is not None and not self.batch_on: self.sim_page.draw_page() if self.batch_page is not None and self.batch_on: self.batch_page.draw_page() return page 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: name = event.panel_name if self.parent.panels[item].window_caption.startswith(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. close fitpage only when the a loaded data is removed """ if event is None or event.data is None: return if hasattr(event.data, "is_data"): if not event.data.is_data or \ event.data.__class__.__name__ == "Data1D": self.fit_panel.close_page_with_data(event.data) def _reset_schedule_problem(self, value=0, uid=None): """ unschedule or schedule all fitproblem to be fit """ # case that uid is not specified if uid == None: for page_id in self.page_finder.keys(): self.page_finder[page_id].schedule_tofit(value) # when uid is given else: if uid in self.page_finder.keys(): self.page_finder[uid].schedule_tofit(value) def _fit_helper(self, fitproblem, pars, fitter, fit_id, batch_inputs, batch_outputs): """ Create and set fit engine with series of data and model :param pars: list of fittable parameters :param fitter_list: list of fit engine :param value: structure storing data mapped to their model, range etc. """ data = fitproblem.get_fit_data() model = fitproblem.get_model() smearer = fitproblem.get_smearer() qmin, qmax = fitproblem.get_range() #Extra list of parameters and their constraints listOfConstraint = [] param = fitproblem.get_model_param() if len(param) > 0: for item in param: ## check if constraint if item[0] != None and item[1] != None: listOfConstraint.append((item[0], item[1])) new_model = model fitter.set_model(new_model, fit_id, pars, data=data, constraints=listOfConstraint) fitter.set_data(data=data, id=fit_id, smearer=smearer, qmin=qmin, qmax=qmax) fitter.select_problem_for_fit(id=fit_id, value=1) 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) self.select_data(self.panel) def select_data(self, panel): """ """ self.panel = panel for plottable in self.panel.graph.plottables: if plottable.__class__.__name__ in ["Data1D", "Theory1D"]: data_id = self.panel.graph.selected_plottable if plottable == self.panel.plots[data_id]: data = plottable self.add_fit_page(data=[data]) return else: data = plottable self.add_fit_page(data=[data]) self.set_top_panel() def update_fit(self, result=None, msg=""): """ """ print "update_fit result", result def _batch_fit_complete(self, result, pars, page_id, batch_outputs, batch_inputs, elapsed=None): """ Display fit result in batch :param result: list of objects received fromt fit engines :param pars: list of fitted parameters names :param page_id: list of page ids which called fit function :param elapsed: time spent at the fitting level """ self._mac_sleep(0.2) uid = page_id[0] if uid in self.fit_thread_list.keys(): del self.fit_thread_list[uid] self._update_fit_button(page_id) t1 = time.time() str_time = time.strftime("%a, %d %b %Y %H:%M:%S ", time.localtime(t1)) msg = "Fit completed on %s \n" % str_time msg += "Duration time: %s s.\n" % str(elapsed) wx.PostEvent(self.parent, StatusEvent(status=msg, info="info", type="stop")) if batch_outputs is None: batch_outputs = {} # format batch_outputs batch_outputs["Chi2"] = [] #Don't like these loops # Need to create dictionary of all fitted parameters # since the number of parameters can differ between each fit result for list_res in result: for res in list_res: model, data = res.inputs[0] if model is not None and hasattr(model, "model"): model = model.model #get all fittable parameters of the current model for param in model.getParamList(): if param not in batch_outputs.keys(): batch_outputs[param] = [] for param in model.getDispParamList(): if not model.is_fittable(param) and \ param in batch_outputs.keys(): del batch_outputs[param] # Add fitted parameters and their error for param in res.param_list: if param not in batch_outputs.keys(): batch_outputs[param] = [] err_param = "error on %s" % str(param) if err_param not in batch_inputs.keys(): batch_inputs[err_param] = [] msg = "" for list_res in result: for res in list_res: pid = res.fitter_id model, data = res.inputs[0] correct_result = False if model is not None and hasattr(model, "model"): model = model.model if data is not None and hasattr(data, "sans_data"): data = data.sans_data is_data2d = issubclass(data.__class__, Data2D) #check consistency of arrays if not is_data2d: if len(res.theory) == len(res.index[res.index]) and \ len(res.index) == len(data.y): correct_result = True else: copy_data = deepcopy(data) new_theory = copy_data.data new_theory[res.index] = res.theory new_theory[res.index == False] = numpy.nan correct_result = True #get all fittable parameters of the current model param_list = model.getParamList() for param in model.getDispParamList(): if not model.is_fittable(param) and \ param in param_list: param_list.remove(param) if not correct_result or res.fitness is None or \ not numpy.isfinite(res.fitness) or \ numpy.any(res.pvec == None) or not \ numpy.all(numpy.isfinite(res.pvec)): data_name = str(None) if data is not None: data_name = str(data.name) model_name = str(None) if model is not None: model_name = str(model.name) msg += "Data %s and Model %s did not fit.\n" % (data_name, model_name) ERROR = numpy.NAN cell = BatchCell() cell.label = res.fitness cell.value = res.fitness batch_outputs["Chi2"].append(ERROR) for param in param_list: # save value of fixed parameters if param not in res.param_list: batch_outputs[str(param)].append(ERROR) else: #save only fitted values batch_outputs[param].append(ERROR) batch_inputs["error on %s" % str(param)].append(ERROR) else: # ToDo: Why sometimes res.pvec comes with numpy.float64? # Need to fix it within ScipyEngine if res.pvec.__class__ == numpy.float64: res.pvec = [res.pvec] cell = BatchCell() cell.label = res.fitness cell.value = res.fitness batch_outputs["Chi2"].append(cell) # add parameters to batch_results for param in param_list: # save value of fixed parameters if param not in res.param_list: batch_outputs[str(param)].append(model.getParam(param)) else: index = res.param_list.index(param) #save only fitted values batch_outputs[param].append(res.pvec[index]) if res.stderr is not None and \ len(res.stderr) == len(res.param_list): item = res.stderr[index] batch_inputs["error on %s" % param].append(item) else: batch_inputs["error on %s" % param].append('-') model.setParam(param, res.pvec[index]) #fill the batch result with emtpy value if not in the current #model EMPTY = "-" for key in batch_outputs.keys(): if key not in param_list and key not in ["Chi2", "Data"]: batch_outputs[key].append(EMPTY) self.page_finder[pid].set_batch_result(batch_inputs=batch_inputs, batch_outputs=batch_outputs) cpage = self.fit_panel.get_page_by_id(pid) cpage._on_fit_complete() self.page_finder[pid][data.id].set_result(res) fitproblem = self.page_finder[pid][data.id] qmin, qmax = fitproblem.get_range() plot_result = False if correct_result: if not is_data2d: self._complete1D(x=data.x, y=res.theory, page_id=pid, elapsed=None, index=res.index, model=model, weight=None, fid=data.id, toggle_mode_on=False, state=None, data=data, update_chisqr=False, source='fit', plot_result=plot_result) else: self._complete2D(image=new_theory, data=data, model=model, page_id=pid, elapsed=None, index=res.index, qmin=qmin, qmax=qmax, fid=data.id, weight=None, toggle_mode_on=False, state=None, update_chisqr=False, source='fit', plot_result=plot_result) self.on_set_batch_result(page_id=pid, fid=data.id, batch_outputs=batch_outputs, batch_inputs=batch_inputs) wx.PostEvent(self.parent, StatusEvent(status=msg, error="error", type="stop")) # Remove parameters that are not shown cpage = self.fit_panel.get_page_by_id(uid) tbatch_outputs = {} shownkeystr = cpage.get_copy_params() for key in batch_outputs.keys(): if key in ["Chi2", "Data"] or shownkeystr.count(key) > 0: tbatch_outputs[key] = batch_outputs[key] wx.CallAfter(self.parent.on_set_batch_result, tbatch_outputs, batch_inputs, self.sub_menu) def on_set_batch_result(self, page_id, fid, batch_outputs, batch_inputs): """ """ pid = page_id if fid not in self.page_finder[pid]: return fitproblem = self.page_finder[pid][fid] index = self.page_finder[pid].nbr_residuals_computed - 1 residuals = fitproblem.get_residuals() theory_data = fitproblem.get_theory_data() data = fitproblem.get_fit_data() model = fitproblem.get_model() #fill batch result information if "Data" not in batch_outputs.keys(): batch_outputs["Data"] = [] from sans.guiframe.data_processor import BatchCell cell = BatchCell() cell.label = data.name cell.value = index if theory_data != None: #Suucessful fit theory_data.id = wx.NewId() theory_data.name = model.name + "[%s]" % str(data.name) if issubclass(theory_data.__class__, Data2D): group_id = wx.NewId() theory_data.group_id = group_id if group_id not in theory_data.list_group_id: theory_data.list_group_id.append(group_id) try: # associate residuals plot if issubclass(residuals.__class__, Data2D): group_id = wx.NewId() residuals.group_id = group_id if group_id not in residuals.list_group_id: residuals.list_group_id.append(group_id) batch_outputs["Chi2"][index].object = [residuals] except: pass cell.object = [data, theory_data] batch_outputs["Data"].append(cell) for key, value in data.meta_data.iteritems(): if key not in batch_inputs.keys(): batch_inputs[key] = [] #if key.lower().strip() != "loader": batch_inputs[key].append(value) param = "temperature" if hasattr(data.sample, param): if param not in batch_inputs.keys(): batch_inputs[param] = [] batch_inputs[param].append(data.sample.temperature) def _fit_completed(self, result, page_id, batch_outputs, batch_inputs=None, pars=None, elapsed=None): """ Display result of the fit on related panel(s). :param result: list of object generated when fit ends :param pars: list of names of parameters fitted :param page_id: list of page ids which called fit function :param elapsed: time spent at the fitting level """ t1 = time.time() str_time = time.strftime("%a, %d %b %Y %H:%M:%S ", time.localtime(t1)) msg = "Fit completed on %s \n" % str_time msg += "Duration time: %s s.\n" % str(elapsed) wx.PostEvent(self.parent, StatusEvent(status=msg, info="info", type="stop")) # reset fit_engine if changed by simul_fit if self._fit_engine != self._gui_engine: self._on_change_engine(self._gui_engine) self._update_fit_button(page_id) result = result[0] self.fit_thread_list = {} if page_id is None: page_id = [] ## fit more than 1 model at the same time self._mac_sleep(0.2) try: index = 0 for uid in page_id: res = result[index] if res.fitness is None or \ not numpy.isfinite(res.fitness) or \ numpy.any(res.pvec == None) or \ not numpy.all(numpy.isfinite(res.pvec)): msg = "Fitting did not converge!!!" wx.PostEvent(self.parent, StatusEvent(status=msg, info="warning", type="stop")) self._update_fit_button(page_id) else: #set the panel when fit result are float not list if res.pvec.__class__ == numpy.float64: pvec = [res.pvec] else: pvec = res.pvec if res.stderr.__class__ == numpy.float64: stderr = [res.stderr] else: stderr = res.stderr cpage = self.fit_panel.get_page_by_id(uid) # Make sure we got all results #(CallAfter is important to MAC) try: #if res != None: wx.CallAfter(cpage.onsetValues, res.fitness, res.param_list, pvec, stderr) index += 1 wx.CallAfter(cpage._on_fit_complete) except: msg = "Singular point: Fitting Error occurred." wx.PostEvent(self.parent, StatusEvent(status=msg, info="error", type="stop")) except: msg = "Fit completed but Following" msg += " error occurred:%s" % sys.exc_value wx.PostEvent(self.parent, StatusEvent(status=msg, info="error", type="stop")) def _update_fit_button(self, page_id): """ Update Fit button when fit stopped : parameter page_id: fitpage where the button is """ if page_id.__class__.__name__ != 'list': page_id = [page_id] for uid in page_id: page = self.fit_panel.get_page_by_id(uid) page._on_fit_complete() def _on_show_panel(self, event): """ """ pass def on_reset_batch_flag(self, event): """ Set batch_reset_flag """ event.Skip() if self.menu1 == None: return menu_item = self.menu1.FindItemById(self.id_reset_flag) flag = menu_item.IsChecked() if not flag: menu_item.Check(False) self.batch_reset_flag = True else: menu_item.Check(True) self.batch_reset_flag = False ## post a message to status bar msg = "Set Chain Fitting: %s" % str(not self.batch_reset_flag) wx.PostEvent(self.parent, StatusEvent(status=msg)) 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 is not None: new_panel = event.panel self.slicer_panels.append(event.panel) # Set group ID if available event_id = self.parent.popup_panel(new_panel) new_panel.uid = event_id self.mypanels.append(new_panel) 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.FindItemById(self.park_id).Check(True) self.menu1.FindItemById(self.scipy_id).Check(False) else: self.menu1.FindItemById(self.park_id).Check(False) self.menu1.FindItemById(self.scipy_id).Check(True) ## post a message to status bar msg = "Engine set to: %s" % self._fit_engine wx.PostEvent(self.parent, StatusEvent(status=msg)) ## send the current engine type to fitpanel self.fit_panel._on_engine_change(name=self._fit_engine) 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 uid = evt.uid qmin = evt.qmin qmax = evt.qmax caption = evt.caption enable_smearer = evt.enable_smearer if model == None: return if uid not in self.page_finder.keys(): return # save the name containing the data name with the appropriate model self.page_finder[uid].set_model(model) self.page_finder[uid].enable_smearing(enable_smearer) self.page_finder[uid].set_range(qmin=qmin, qmax=qmax) self.page_finder[uid].set_fit_tab_caption(caption=caption) if self.sim_page is not None and not self.batch_on: self.sim_page.draw_page() if self.batch_page is not None and self.batch_on: self.batch_page.draw_page() def _update1D(self, x, output): """ Update the output of plotting model 1D """ msg = "Plot updating ... " wx.PostEvent(self.parent, StatusEvent(status=msg, type="update")) def _complete1D(self, x, y, page_id, elapsed, index, model, weight=None, fid=None, toggle_mode_on=False, state=None, data=None, update_chisqr=True, source='model', plot_result=True): """ Complete plotting 1D data """ try: numpy.nan_to_num(y) new_plot = Data1D(x=x, y=y) new_plot.is_data = False new_plot.dy = numpy.zeros(len(y)) new_plot.symbol = GUIFRAME_ID.CURVE_SYMBOL_NUM _yaxis, _yunit = data.get_yaxis() _xaxis, _xunit = data.get_xaxis() new_plot.title = data.name new_plot.group_id = data.group_id if new_plot.group_id == None: new_plot.group_id = data.group_id new_plot.id = str(page_id) + "model-" + data.name #if new_plot.id in self.color_dict: # new_plot.custom_color = self.color_dict[new_plot.id] #find if this theory was already plotted and replace that plot given #the same id theory_data = self.page_finder[page_id].get_theory_data(fid=data.id) if data.is_data: data_name = str(data.name) else: data_name = str(model.__class__.__name__) new_plot.name = model.name + " [" + data_name +"]" new_plot.xaxis(_xaxis, _xunit) new_plot.yaxis(_yaxis, _yunit) self.page_finder[page_id].set_theory_data(data=new_plot, fid=data.id) self.parent.update_theory(data_id=data.id, theory=new_plot, state=state) current_pg = self.fit_panel.get_page_by_id(page_id) title = new_plot.title batch_on = self.fit_panel.get_page_by_id(page_id).batch_on if not batch_on: wx.PostEvent(self.parent, NewPlotEvent(plot=new_plot, title=str(title))) elif plot_result: top_data_id = self.fit_panel.get_page_by_id(page_id).data.id if data.id == top_data_id: wx.PostEvent(self.parent, NewPlotEvent(plot=new_plot, title=str(title))) caption = current_pg.window_caption self.page_finder[page_id].set_fit_tab_caption(caption=caption) self.page_finder[page_id].set_theory_data(data=new_plot, fid=data.id) if toggle_mode_on: wx.PostEvent(self.parent, NewPlotEvent(group_id=str(page_id) + " Model2D", action="Hide")) else: if update_chisqr: wx.PostEvent(current_pg, Chi2UpdateEvent(output=self._cal_chisqr( data=data, fid=fid, weight=weight, page_id=page_id, index=index))) else: self._plot_residuals(page_id=page_id, data=data, fid=fid, index=index, weight=weight) msg = "Computation completed!" wx.PostEvent(self.parent, StatusEvent(status=msg, type="stop")) except: raise def _update2D(self, output, time=None): """ Update the output of plotting model """ wx.PostEvent(self.parent, StatusEvent(status="Plot \ #updating ... ", type="update")) #self.ready_fit() def _complete2D(self, image, data, model, page_id, elapsed, index, qmin, qmax, fid=None, weight=None, toggle_mode_on=False, state=None, update_chisqr=True, source='model', plot_result=True): """ Complete get the result of modelthread and create model 2D that can be plot. """ numpy.nan_to_num(image) new_plot = Data2D(image=image, err_image=data.err_data) new_plot.name = model.name new_plot.title = "Analytical model 2D " new_plot.id = str(page_id) + "model-" + data.name new_plot.group_id = str(page_id) + " Model2D" new_plot.detector = data.detector new_plot.source = data.source new_plot.is_data = False new_plot.qx_data = data.qx_data new_plot.qy_data = data.qy_data new_plot.q_data = data.q_data new_plot.mask = data.mask ## plot boundaries new_plot.ymin = data.ymin new_plot.ymax = data.ymax new_plot.xmin = data.xmin new_plot.xmax = data.xmax title = data.title new_plot.is_data = False if data.is_data: data_name = str(data.name) else: data_name = str(model.__class__.__name__) if len(title) > 1: new_plot.title = "Model2D for " + data_name new_plot.name = model.name + " [" + \ data_name + "-2D]" theory_data = deepcopy(new_plot) theory_data.name = "Unknown" self.page_finder[page_id].set_theory_data(data=theory_data, fid=data.id) self.parent.update_theory(data_id=data.id, theory=new_plot, state=state) current_pg = self.fit_panel.get_page_by_id(page_id) title = new_plot.title if not source == 'fit' and plot_result: wx.PostEvent(self.parent, NewPlotEvent(plot=new_plot, title=title)) if toggle_mode_on: wx.PostEvent(self.parent, NewPlotEvent(group_id=str(page_id) + " Model1D", action="Hide")) else: # Chisqr in fitpage if update_chisqr: wx.PostEvent(current_pg, Chi2UpdateEvent(output=self._cal_chisqr(data=data, weight=weight, fid=fid, page_id=page_id, index=index))) else: self._plot_residuals(page_id=page_id, data=data, fid=fid, index=index, weight=weight) msg = "Computation completed!" wx.PostEvent(self.parent, StatusEvent(status=msg, type="stop")) def _draw_model2D(self, model, page_id, qmin, qmax, data=None, smearer=None, description=None, enable2D=False, state=None, fid=None, weight=None, toggle_mode_on=False, update_chisqr=True, source='model'): """ 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 """ if not enable2D: return None try: from model_thread import Calc2D ## If a thread is already started, stop it if (self.calc_2D is not None) and self.calc_2D.isrunning(): self.calc_2D.stop() self.calc_2D = Calc2D(model=model, data=data, page_id=page_id, smearer=smearer, qmin=qmin, qmax=qmax, weight=weight, fid=fid, toggle_mode_on=toggle_mode_on, state=state, completefn=self._complete2D, update_chisqr=update_chisqr, source=source) self.calc_2D.queue() except: raise def _draw_model1D(self, model, page_id, data, qmin, qmax, smearer=None, state=None, weight=None, fid=None, toggle_mode_on=False, update_chisqr=True, source='model', enable1D=True): """ Draw model 1D from loaded data1D :param data: loaded data :param model: the model to plot """ if not enable1D: return try: from model_thread import Calc1D ## If a thread is already started, stop it if (self.calc_1D is not None) and self.calc_1D.isrunning(): self.calc_1D.stop() self.calc_1D = Calc1D(data=data, model=model, page_id=page_id, qmin=qmin, qmax=qmax, smearer=smearer, state=state, weight=weight, fid=fid, toggle_mode_on=toggle_mode_on, completefn=self._complete1D, #updatefn = self._update1D, update_chisqr=update_chisqr, source=source) 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)) def _cal_chisqr(self, page_id, data, weight, fid=None, index=None): """ Get handy Chisqr using the output from draw1D and 2D, instead of calling expansive CalcChisqr in guithread """ data_copy = deepcopy(data) # default chisqr chisqr = None #to compute chisq make sure data has valid data # return None if data == None if not check_data_validity(data_copy) or data_copy == None: return chisqr # Get data: data I, theory I, and data dI in order if data_copy.__class__.__name__ == "Data2D": if index == None: index = numpy.ones(len(data_copy.data), ntype=bool) if weight != None: data_copy.err_data = weight # get rid of zero error points index = index & (data_copy.err_data != 0) index = index & (numpy.isfinite(data_copy.data)) fn = data_copy.data[index] theory_data = self.page_finder[page_id].get_theory_data(fid=data_copy.id) if theory_data == None: return chisqr gn = theory_data.data[index] en = data_copy.err_data[index] else: # 1 d theory from model_thread is only in the range of index if index == None: index = numpy.ones(len(data_copy.y), ntype=bool) if weight != None: data_copy.dy = weight if data_copy.dy == None or data_copy.dy == []: dy = numpy.ones(len(data_copy.y)) else: ## Set consitently w/AbstractFitengine: # But this should be corrected later. dy = deepcopy(data_copy.dy) dy[dy == 0] = 1 fn = data_copy.y[index] theory_data = self.page_finder[page_id].get_theory_data(fid=data_copy.id) if theory_data == None: return chisqr gn = theory_data.y en = dy[index] # residual res = (fn - gn) / en residuals = res[numpy.isfinite(res)] # get chisqr only w/finite chisqr = numpy.average(residuals * residuals) self._plot_residuals(page_id=page_id, data=data_copy, fid=fid, weight=weight, index=index) return chisqr def _plot_residuals(self, page_id, weight, fid=None, data=None, index=None): """ Plot the residuals :param data: data :param index: index array (bool) : Note: this is different from the residuals in cal_chisqr() """ data_copy = deepcopy(data) # Get data: data I, theory I, and data dI in order if data_copy.__class__.__name__ == "Data2D": # build residuals residuals = Data2D() #residuals.copy_from_datainfo(data) # Not for trunk the line below, instead use the line above data_copy.clone_without_data(len(data_copy.data), residuals) residuals.data = None fn = data_copy.data theory_data = self.page_finder[page_id].get_theory_data(fid=data_copy.id) gn = theory_data.data if weight == None: en = data_copy.err_data else: en = weight residuals.data = (fn - gn) / en residuals.qx_data = data_copy.qx_data residuals.qy_data = data_copy.qy_data residuals.q_data = data_copy.q_data residuals.err_data = numpy.ones(len(residuals.data)) residuals.xmin = min(residuals.qx_data) residuals.xmax = max(residuals.qx_data) residuals.ymin = min(residuals.qy_data) residuals.ymax = max(residuals.qy_data) residuals.q_data = data_copy.q_data residuals.mask = data_copy.mask residuals.scale = 'linear' # check the lengths if len(residuals.data) != len(residuals.q_data): return else: # 1 d theory from model_thread is only in the range of index if data_copy.dy == None or data_copy.dy == []: dy = numpy.ones(len(data_copy.y)) else: if weight == None: dy = numpy.ones(len(data_copy.y)) ## Set consitently w/AbstractFitengine: ## But this should be corrected later. else: dy = weight dy[dy == 0] = 1 fn = data_copy.y[index] theory_data = self.page_finder[page_id].get_theory_data(fid=data_copy.id) gn = theory_data.y en = dy[index] # build residuals residuals = Data1D() residuals.y = (fn - gn) / en residuals.x = data_copy.x[index] residuals.dy = numpy.ones(len(residuals.y)) residuals.dx = None residuals.dxl = None residuals.dxw = None residuals.ytransform = 'y' # For latter scale changes residuals.xaxis('\\rm{Q} ', 'A^{-1}') residuals.yaxis('\\rm{Residuals} ', 'normalized') new_plot = residuals new_plot.name = "Residuals for " + str(theory_data.name.split()[0]) + "[" + str(data.name) +"]" ## allow to highlight data when plotted new_plot.interactive = True ## when 2 data have the same id override the 1 st plotted new_plot.id = "res" + str(data_copy.id) ##group_id specify on which panel to plot this data group_id = self.page_finder[page_id].get_graph_id() if group_id == None: group_id = data.group_id new_plot.group_id = "res" + str(group_id) #new_plot.is_data = True ##post data to plot title = new_plot.name self.page_finder[page_id].set_residuals(residuals=new_plot, fid=data.id) self.parent.update_theory(data_id=data.id, theory=new_plot) batch_on = self.fit_panel.get_page_by_id(page_id).batch_on if not batch_on: wx.PostEvent(self.parent, NewPlotEvent(plot=new_plot, title=title))