| 1 | import os,os.path, re |
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| 2 | import sys, wx, logging |
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| 3 | import string, numpy, pylab, math |
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| 4 | |
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| 5 | from copy import deepcopy |
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| 6 | from sans.guitools.plottables import Data1D, Theory1D |
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| 7 | from sans.guitools.PlotPanel import PlotPanel |
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| 8 | from sans.guicomm.events import NewPlotEvent, StatusEvent |
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| 9 | from sans.fit.AbstractFitEngine import Model,Data |
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| 10 | from fitproblem import FitProblem |
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| 11 | from fitpanel import FitPanel |
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| 12 | |
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| 13 | import models |
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| 14 | import fitpage |
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| 15 | import park |
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| 16 | |
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| 17 | class Plugin: |
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| 18 | """ |
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| 19 | Fitting plugin is used to perform fit |
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| 20 | """ |
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| 21 | def __init__(self): |
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| 22 | ## Plug-in name |
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| 23 | self.sub_menu = "Fitting" |
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| 24 | |
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| 25 | ## Reference to the parent window |
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| 26 | self.parent = None |
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| 27 | self.menu_mng = models.ModelManager() |
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| 28 | ## List of panels for the simulation perspective (names) |
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| 29 | self.perspective = [] |
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| 30 | # Start with a good default |
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| 31 | self.elapsed = 0.022 |
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| 32 | self.fitter = None |
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| 33 | |
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| 34 | #Flag to let the plug-in know that it is running standalone |
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| 35 | self.standalone=True |
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| 36 | ## Fit engine |
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| 37 | self._fit_engine = 'scipy' |
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| 38 | # Log startup |
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| 39 | logging.info("Fitting plug-in started") |
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| 40 | |
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| 41 | def populate_menu(self, id, owner): |
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| 42 | """ |
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| 43 | Create a menu for the Fitting plug-in |
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| 44 | @param id: id to create a menu |
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| 45 | @param owner: owner of menu |
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| 46 | @ return : list of information to populate the main menu |
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| 47 | """ |
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| 48 | #Menu for fitting |
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| 49 | self.menu1 = wx.Menu() |
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| 50 | id1 = wx.NewId() |
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| 51 | self.menu1.Append(id1, '&Show fit panel') |
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| 52 | wx.EVT_MENU(owner, id1, self.on_perspective) |
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| 53 | id3 = wx.NewId() |
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| 54 | self.menu1.AppendCheckItem(id3, "park") |
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| 55 | wx.EVT_MENU(owner, id3, self._onset_engine) |
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| 56 | |
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| 57 | #menu for model |
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| 58 | menu2 = wx.Menu() |
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| 59 | self.menu_mng.populate_menu(menu2, owner) |
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| 60 | id2 = wx.NewId() |
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| 61 | owner.Bind(models.EVT_MODEL,self._on_model_menu) |
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| 62 | self.fit_panel.set_owner(owner) |
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| 63 | self.fit_panel.set_model_list(self.menu_mng.get_model_list()) |
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| 64 | owner.Bind(fitpage.EVT_MODEL_BOX,self._on_model_panel) |
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| 65 | #create menubar items |
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| 66 | return [(id, self.menu1, "Fitting"),(id2, menu2, "Model")] |
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| 67 | |
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| 68 | |
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| 69 | def help(self, evt): |
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| 70 | """ |
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| 71 | Show a general help dialog. |
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| 72 | TODO: replace the text with a nice image |
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| 73 | """ |
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| 74 | pass |
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| 75 | |
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| 76 | def get_context_menu(self, graph=None): |
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| 77 | """ |
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| 78 | Get the context menu items available for P(r) |
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| 79 | @param graph: the Graph object to which we attach the context menu |
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| 80 | @return: a list of menu items with call-back function |
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| 81 | """ |
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| 82 | self.graph=graph |
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| 83 | for item in graph.plottables: |
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| 84 | if item.name==graph.selected_plottable and item.__class__.__name__ is not "Theory1D": |
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| 85 | return [["Select Data", "Dialog with fitting parameters ", self._onSelect]] |
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| 86 | return [] |
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| 87 | |
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| 88 | |
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| 89 | def get_panels(self, parent): |
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| 90 | """ |
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| 91 | Create and return a list of panel objects |
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| 92 | """ |
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| 93 | self.parent = parent |
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| 94 | # Creation of the fit panel |
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| 95 | self.fit_panel = FitPanel(self.parent, -1) |
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| 96 | #Set the manager forthe main panel |
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| 97 | self.fit_panel.set_manager(self) |
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| 98 | # List of windows used for the perspective |
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| 99 | self.perspective = [] |
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| 100 | self.perspective.append(self.fit_panel.window_name) |
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| 101 | # take care of saving data, model and page associated with each other |
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| 102 | self.page_finder = {} |
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| 103 | #index number to create random model name |
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| 104 | self.index_model = 0 |
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| 105 | #create the fitting panel |
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| 106 | return [self.fit_panel] |
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| 107 | |
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| 108 | |
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| 109 | def get_perspective(self): |
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| 110 | """ |
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| 111 | Get the list of panel names for this perspective |
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| 112 | """ |
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| 113 | return self.perspective |
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| 114 | |
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| 115 | |
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| 116 | def on_perspective(self, event): |
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| 117 | """ |
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| 118 | Call back function for the perspective menu item. |
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| 119 | We notify the parent window that the perspective |
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| 120 | has changed. |
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| 121 | """ |
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| 122 | self.parent.set_perspective(self.perspective) |
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| 123 | |
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| 124 | |
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| 125 | def post_init(self): |
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| 126 | """ |
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| 127 | Post initialization call back to close the loose ends |
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| 128 | [Somehow openGL needs this call] |
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| 129 | """ |
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| 130 | self.parent.set_perspective(self.perspective) |
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| 131 | |
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| 132 | |
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| 133 | def _onSelect(self,event): |
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| 134 | """ |
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| 135 | when Select data to fit a new page is created .Its reference is |
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| 136 | added to self.page_finder |
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| 137 | """ |
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| 138 | self.panel = event.GetEventObject() |
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| 139 | for item in self.panel.graph.plottables: |
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| 140 | if item.name == self.panel.graph.selected_plottable: |
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| 141 | #find a name for the page created for notebook |
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| 142 | try: |
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| 143 | name = item.group_id # item in Data1D |
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| 144 | except: |
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| 145 | name = 'Fit' |
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| 146 | try: |
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| 147 | page = self.fit_panel.add_fit_page(name) |
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| 148 | # add data associated to the page created |
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| 149 | page.set_data_name(item) |
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| 150 | #create a fitproblem storing all link to data,model,page creation |
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| 151 | self.page_finder[page]= FitProblem() |
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| 152 | #data_for_park= Data(sans_data=item) |
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| 153 | #datap = PlottableData(data=data_for_park,data1d=item) |
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| 154 | #self.page_finder[page].add_data(datap) |
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| 155 | self.page_finder[page].add_data(item) |
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| 156 | except: |
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| 157 | #raise |
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| 158 | wx.PostEvent(self.parent, StatusEvent(status="Fitting error: \ |
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| 159 | data already Selected ")) |
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| 160 | |
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| 161 | |
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| 162 | def get_page_finder(self): |
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| 163 | """ @return self.page_finder used also by simfitpage.py""" |
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| 164 | return self.page_finder |
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| 165 | |
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| 166 | |
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| 167 | def set_page_finder(self,modelname,names,values): |
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| 168 | """ |
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| 169 | Used by simfitpage.py to reset a parameter given the string constrainst. |
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| 170 | @param modelname: the name ot the model for with the parameter has to reset |
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| 171 | @param value: can be a string in this case. |
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| 172 | @param names: the paramter name |
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| 173 | @note: expecting park used for fit. |
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| 174 | """ |
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| 175 | sim_page=self.fit_panel.get_page(0) |
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| 176 | for page, value in self.page_finder.iteritems(): |
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| 177 | if page != sim_page: |
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| 178 | list=value.get_model() |
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| 179 | model=list[0] |
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| 180 | print "fitting",model.name,modelname |
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| 181 | if model.name== modelname: |
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| 182 | value.set_model_param(names,values) |
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| 183 | break |
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| 184 | |
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| 185 | |
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| 186 | |
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| 187 | def split_string(self,item): |
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| 188 | """ |
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| 189 | receive a word containing dot and split it. used to split parameterset |
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| 190 | name into model name and parameter name example: |
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| 191 | paramaterset (item) = M1.A |
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| 192 | @return model_name =M1 , parameter name =A |
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| 193 | """ |
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| 194 | if string.find(item,".")!=-1: |
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| 195 | param_names= re.split("\.",item) |
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| 196 | model_name=param_names[0] |
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| 197 | param_name=param_names[1] |
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| 198 | return model_name,param_name |
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| 199 | |
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| 200 | |
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| 201 | def _single_fit_completed(self,result,pars,current_pg,qmin,qmax): |
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| 202 | """ |
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| 203 | Display fit result on one page of the notebook. |
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| 204 | @param result: result of fit |
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| 205 | @param pars: list of names of parameters fitted |
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| 206 | @param current_pg: the page where information will be displayed |
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| 207 | @param qmin: the minimum value of x to replot the model |
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| 208 | @param qmax: the maximum value of x to replot model |
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| 209 | |
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| 210 | """ |
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| 211 | try: |
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| 212 | for page, value in self.page_finder.iteritems(): |
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| 213 | if page== current_pg: |
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| 214 | data = value.get_data() |
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| 215 | list = value.get_model() |
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| 216 | model= list[0] |
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| 217 | break |
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| 218 | i = 0 |
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| 219 | # print "fitting: single fit pars ", pars |
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| 220 | for name in pars: |
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| 221 | if result.pvec.__class__==numpy.float64: |
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| 222 | model.setParam(name,result.pvec) |
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| 223 | else: |
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| 224 | model.setParam(name,result.pvec[i]) |
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| 225 | # print "fitting: single fit", name, result.pvec[i] |
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| 226 | i += 1 |
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| 227 | # print "fitting result : chisqr",result.fitness |
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| 228 | # print "fitting result : pvec",result.pvec |
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| 229 | # print "fitting result : stderr",result.stderr |
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| 230 | |
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| 231 | current_pg.onsetValues(result.fitness, result.pvec,result.stderr) |
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| 232 | self.plot_helper(currpage=current_pg,qmin=qmin,qmax=qmax) |
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| 233 | except: |
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| 234 | raise |
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| 235 | wx.PostEvent(self.parent, StatusEvent(status="Fitting error: %s" % sys.exc_value)) |
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| 236 | |
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| 237 | |
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| 238 | def _simul_fit_completed(self,result,qmin,qmax): |
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| 239 | """ |
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| 240 | Parameter estimation completed, |
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| 241 | display the results to the user |
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| 242 | @param alpha: estimated best alpha |
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| 243 | @param elapsed: computation time |
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| 244 | """ |
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| 245 | try: |
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| 246 | for page, value in self.page_finder.iteritems(): |
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| 247 | if value.get_scheduled()=='True': |
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| 248 | data = value.get_data() |
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| 249 | list = value.get_model() |
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| 250 | model= list[0] |
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| 251 | |
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| 252 | small_out = [] |
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| 253 | small_cov = [] |
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| 254 | i = 0 |
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| 255 | #Separate result in to data corresponding to each page |
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| 256 | for p in result.parameters: |
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| 257 | model_name,param_name = self.split_string(p.name) |
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| 258 | if model.name == model_name: |
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| 259 | small_out.append(p.value ) |
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| 260 | small_cov.append(p.stderr) |
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| 261 | model.setParam(param_name,p.value) |
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| 262 | # Display result on each page |
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| 263 | page.onsetValues(result.fitness, small_out,small_cov) |
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| 264 | #Replot model |
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| 265 | self.plot_helper(currpage= page,qmin= qmin,qmax= qmax) |
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| 266 | except: |
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| 267 | wx.PostEvent(self.parent, StatusEvent(status="Fitting error: %s" % sys.exc_value)) |
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| 268 | |
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| 269 | |
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| 270 | def _on_single_fit(self,id=None,qmin=None,qmax=None): |
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| 271 | """ |
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| 272 | perform fit for the current page and return chisqr,out and cov |
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| 273 | @param engineName: type of fit to be performed |
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| 274 | @param id: unique id corresponding to a fit problem(model, set of data) |
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| 275 | @param model: model to fit |
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| 276 | |
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| 277 | """ |
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| 278 | #set an engine to perform fit |
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| 279 | from sans.fit.Fitting import Fit |
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| 280 | self.fitter= Fit(self._fit_engine) |
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| 281 | #Setting an id to store model and data in fit engine |
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| 282 | if id==None: |
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| 283 | id=0 |
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| 284 | self.id = id |
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| 285 | #Get information (model , data) related to the page on |
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| 286 | #with the fit will be perform |
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| 287 | current_pg=self.fit_panel.get_current_page() |
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| 288 | for page, value in self.page_finder.iteritems(): |
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| 289 | if page ==current_pg : |
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| 290 | data = value.get_data() |
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| 291 | list=value.get_model() |
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| 292 | model=list[0] |
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| 293 | |
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| 294 | #Create list of parameters for fitting used |
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| 295 | pars=[] |
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| 296 | templist=[] |
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| 297 | try: |
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| 298 | templist=current_pg.get_param_list() |
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| 299 | except: |
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| 300 | wx.PostEvent(self.parent, StatusEvent(status="Fitting error: %s" % sys.exc_value)) |
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| 301 | return |
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| 302 | |
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| 303 | for element in templist: |
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| 304 | try: |
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| 305 | pars.append(str(element[0].GetLabelText())) |
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| 306 | except: |
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| 307 | wx.PostEvent(self.parent, StatusEvent(status="Fitting error: %s" % sys.exc_value)) |
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| 308 | return |
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| 309 | # make sure to keep an alphabetic order |
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| 310 | #of parameter names in the list |
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| 311 | pars.sort() |
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| 312 | #Do the single fit |
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| 313 | try: |
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| 314 | self.fitter.set_model(Model(model), self.id, pars) |
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| 315 | #print "fitting: data .x",data.x |
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| 316 | #print "fitting: data .y",data.y |
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| 317 | #print "fitting: data .dy",data.dy |
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| 318 | self.fitter.set_data(Data(sans_data=data),self.id,qmin,qmax) |
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| 319 | |
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| 320 | result=self.fitter.fit() |
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| 321 | self._single_fit_completed(result,pars,current_pg,qmin,qmax) |
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| 322 | |
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| 323 | except: |
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| 324 | raise |
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| 325 | wx.PostEvent(self.parent, StatusEvent(status="Single Fit error: %s" % sys.exc_value)) |
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| 326 | return |
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| 327 | |
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| 328 | def _on_simul_fit(self, id=None,qmin=None,qmax=None): |
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| 329 | """ |
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| 330 | perform fit for all the pages selected on simpage and return chisqr,out and cov |
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| 331 | @param engineName: type of fit to be performed |
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| 332 | @param id: unique id corresponding to a fit problem(model, set of data) |
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| 333 | in park_integration |
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| 334 | @param model: model to fit |
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| 335 | |
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| 336 | """ |
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| 337 | #set an engine to perform fit |
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| 338 | from sans.fit.Fitting import Fit |
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| 339 | self.fitter= Fit(self._fit_engine) |
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| 340 | |
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| 341 | #Setting an id to store model and data |
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| 342 | if id==None: |
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| 343 | id = 0 |
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| 344 | self.id = id |
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| 345 | |
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| 346 | for page, value in self.page_finder.iteritems(): |
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| 347 | try: |
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| 348 | if value.get_scheduled()=='True': |
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| 349 | data = value.get_data() |
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| 350 | list = value.get_model() |
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| 351 | model= list[0] |
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| 352 | #Create dictionary of parameters for fitting used |
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| 353 | pars = [] |
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| 354 | templist = [] |
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| 355 | templist = page.get_param_list() |
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| 356 | for element in templist: |
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| 357 | try: |
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| 358 | name = str(element[0].GetLabelText()) |
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| 359 | pars.append(name) |
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| 360 | except: |
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| 361 | wx.PostEvent(self.parent, StatusEvent(status="Fitting error: %s" % sys.exc_value)) |
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| 362 | return |
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| 363 | new_model=Model(model) |
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| 364 | param_name,param_value=value.get_model_param() |
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| 365 | print "fitting ",param_name |
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| 366 | new_model.set( param_name =str(param_value)) |
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| 367 | #self.fitter.set_model(new_model, self.id, pars) |
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| 368 | self.fitter.set_data(Data(sans_data=data),self.id,qmin,qmax) |
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| 369 | |
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| 370 | self.id += 1 |
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| 371 | except: |
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| 372 | wx.PostEvent(self.parent, StatusEvent(status="Fitting error: %s" % sys.exc_value)) |
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| 373 | return |
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| 374 | #Do the simultaneous fit |
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| 375 | try: |
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| 376 | result=self.fitter.fit() |
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| 377 | self._simul_fit_completed(result,qmin,qmax) |
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| 378 | except: |
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| 379 | wx.PostEvent(self.parent, StatusEvent(status="Simultaneous Fitting error: %s" % sys.exc_value)) |
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| 380 | return |
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| 381 | |
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| 382 | |
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| 383 | def _onset_engine(self,event): |
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| 384 | """ set engine to scipy""" |
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| 385 | if self._fit_engine== 'park': |
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| 386 | self._on_change_engine('scipy') |
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| 387 | else: |
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| 388 | self._on_change_engine('park') |
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| 389 | wx.PostEvent(self.parent, StatusEvent(status="Engine set to: %s" % self._fit_engine)) |
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| 390 | |
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| 391 | |
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| 392 | def _on_change_engine(self, engine='park'): |
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| 393 | """ |
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| 394 | Allow to select the type of engine to perform fit |
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| 395 | @param engine: the key work of the engine |
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| 396 | """ |
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| 397 | self._fit_engine = engine |
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| 398 | |
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| 399 | |
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| 400 | def _on_model_panel(self, evt): |
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| 401 | """ |
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| 402 | react to model selection on any combo box or model menu.plot the model |
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| 403 | """ |
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| 404 | model = evt.model |
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| 405 | name = evt.name |
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| 406 | sim_page=self.fit_panel.get_page(0) |
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| 407 | current_pg = self.fit_panel.get_current_page() |
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| 408 | if current_pg != sim_page: |
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| 409 | current_pg.set_model_name(name) |
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| 410 | current_pg.set_panel(model) |
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| 411 | try: |
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| 412 | data=self.page_finder[current_pg].get_data() |
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| 413 | M_name="M"+str(self.index_model)+"= "+name+"("+data.group_id+")" |
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| 414 | except: |
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| 415 | raise |
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| 416 | M_name="M"+str(self.index_model)+"= "+name |
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| 417 | model.name="M"+str(self.index_model) |
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| 418 | self.index_model += 1 |
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| 419 | |
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| 420 | self.page_finder[current_pg].set_model(model,M_name) |
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| 421 | self.plot_helper(currpage= current_pg,qmin= None,qmax= None) |
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| 422 | sim_page.add_model(self.page_finder) |
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| 423 | |
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| 424 | |
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| 425 | def redraw_model(self,qmin= None,qmax= None): |
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| 426 | """ |
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| 427 | Draw a theory according to model changes or data range. |
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| 428 | @param qmin: the minimum value plotted for theory |
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| 429 | @param qmax: the maximum value plotted for theory |
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| 430 | """ |
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| 431 | current_pg=self.fit_panel.get_current_page() |
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| 432 | for page, value in self.page_finder.iteritems(): |
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| 433 | if page ==current_pg : |
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| 434 | break |
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| 435 | self.plot_helper(currpage=page,qmin= qmin,qmax= qmax) |
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| 436 | |
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| 437 | def plot_helper(self,currpage,qmin=None,qmax=None): |
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| 438 | """ |
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| 439 | Plot a theory given a model and data |
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| 440 | @param model: the model from where the theory is derived |
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| 441 | @param currpage: page in a dictionary referring to some data |
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| 442 | """ |
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| 443 | if self.fit_panel.get_page_count() >1: |
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| 444 | for page in self.page_finder.iterkeys(): |
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| 445 | if page==currpage : |
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| 446 | break |
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| 447 | data=self.page_finder[page].get_data() |
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| 448 | list=self.page_finder[page].get_model() |
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| 449 | model=list[0] |
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| 450 | if data!=None: |
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| 451 | theory = Theory1D(x=[], y=[]) |
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| 452 | theory.name = "Model" |
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| 453 | theory.group_id = data.group_id |
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| 454 | |
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| 455 | x_name, x_units = data.get_xaxis() |
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| 456 | y_name, y_units = data.get_yaxis() |
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| 457 | theory.xaxis(x_name, x_units) |
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| 458 | theory.yaxis(y_name, y_units) |
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| 459 | if qmin == None : |
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| 460 | qmin = min(data.x) |
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| 461 | if qmax == None : |
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| 462 | qmax = max(data.x) |
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| 463 | try: |
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| 464 | tempx = qmin |
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| 465 | tempy = model.run(qmin) |
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| 466 | theory.x.append(tempx) |
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| 467 | theory.y.append(tempy) |
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| 468 | except : |
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| 469 | wx.PostEvent(self.parent, StatusEvent(status="fitting \ |
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| 470 | skipping point x %g %s" %(qmin, sys.exc_value))) |
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| 471 | |
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| 472 | for i in range(len(data.x)): |
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| 473 | try: |
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| 474 | if data.x[i]> qmin and data.x[i]< qmax: |
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| 475 | tempx = data.x[i] |
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| 476 | tempy = model.run(tempx) |
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| 477 | |
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| 478 | theory.x.append(tempx) |
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| 479 | theory.y.append(tempy) |
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| 480 | except: |
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| 481 | wx.PostEvent(self.parent, StatusEvent(status="fitting \ |
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| 482 | skipping point x %g %s" %(data.x[i], sys.exc_value))) |
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| 483 | try: |
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| 484 | tempx = qmax |
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| 485 | tempy = model.run(qmax) |
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| 486 | theory.x.append(tempx) |
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| 487 | theory.y.append(tempy) |
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| 488 | wx.PostEvent(self.parent, NewPlotEvent(plot=theory, title="Analytical model")) |
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| 489 | except: |
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| 490 | wx.PostEvent(self.parent, StatusEvent(status="fitting \ |
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| 491 | skipping point x %g %s" %(qmax, sys.exc_value))) |
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| 492 | |
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| 493 | |
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| 494 | def _on_model_menu(self, evt): |
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| 495 | """ |
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| 496 | Plot a theory from a model selected from the menu |
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| 497 | """ |
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| 498 | name="Model View" |
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| 499 | model=evt.modelinfo.model() |
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| 500 | description=evt.modelinfo.description |
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| 501 | self.fit_panel.add_model_page(model,description,name) |
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| 502 | self.draw_model(model) |
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| 503 | |
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| 504 | def draw_model(self,model): |
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| 505 | """ |
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| 506 | draw model with default data value |
|---|
| 507 | """ |
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| 508 | x = pylab.arange(0.001, 0.1, 0.001) |
|---|
| 509 | xlen = len(x) |
|---|
| 510 | dy = numpy.zeros(xlen) |
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| 511 | y = numpy.zeros(xlen) |
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| 512 | |
|---|
| 513 | for i in range(xlen): |
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| 514 | y[i] = model.run(x[i]) |
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| 515 | dy[i] = math.sqrt(math.fabs(y[i])) |
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| 516 | try: |
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| 517 | |
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| 518 | new_plot = Theory1D(x, y) |
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| 519 | new_plot.name = "Model" |
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| 520 | new_plot.xaxis("\\rm{Q}", 'A^{-1}') |
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| 521 | new_plot.yaxis("\\rm{Intensity} ","cm^{-1}") |
|---|
| 522 | new_plot.group_id ="Fitness" |
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| 523 | wx.PostEvent(self.parent, NewPlotEvent(plot=new_plot, title="Analytical model")) |
|---|
| 524 | except: |
|---|
| 525 | wx.PostEvent(self.parent, StatusEvent(status="fitting \ |
|---|
| 526 | skipping point x %g %s" %(qmax, sys.exc_value))) |
|---|
| 527 | |
|---|
| 528 | if __name__ == "__main__": |
|---|
| 529 | i = Plugin() |
|---|
| 530 | |
|---|
| 531 | |
|---|
| 532 | |
|---|
| 533 | |
|---|
