| 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 danse.common.plottools.plottables import Data1D, Theory1D, Data2D |
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| 7 | |
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| 8 | from sans.guiframe.data_loader import MetaData1D, MetaTheory1D, MetaData2D |
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| 9 | from danse.common.plottools.PlotPanel import PlotPanel |
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| 10 | from sans.guicomm.events import NewPlotEvent, StatusEvent |
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| 11 | from sans.fit.AbstractFitEngine import Model,Data,FitData1D,FitData2D |
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| 12 | from fitproblem import FitProblem |
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| 13 | from fitpanel import FitPanel |
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| 14 | |
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| 15 | import models |
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| 16 | import fitpage1D,fitpage2D |
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| 17 | import park |
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| 18 | |
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| 19 | class Plugin: |
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| 20 | """ |
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| 21 | Fitting plugin is used to perform fit |
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| 22 | """ |
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| 23 | def __init__(self): |
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| 24 | ## Plug-in name |
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| 25 | self.sub_menu = "Fitting" |
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| 26 | |
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| 27 | ## Reference to the parent window |
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| 28 | self.parent = None |
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| 29 | self.menu_mng = models.ModelManager() |
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| 30 | ## List of panels for the simulation perspective (names) |
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| 31 | self.perspective = [] |
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| 32 | # Start with a good default |
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| 33 | self.elapsed = 0.022 |
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| 34 | self.fitter = None |
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| 35 | |
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| 36 | #Flag to let the plug-in know that it is running standalone |
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| 37 | self.standalone=True |
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| 38 | ## Fit engine |
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| 39 | self._fit_engine = 'scipy' |
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| 40 | # Log startup |
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| 41 | logging.info("Fitting plug-in started") |
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| 42 | |
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| 43 | def populate_menu(self, id, owner): |
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| 44 | """ |
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| 45 | Create a menu for the Fitting plug-in |
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| 46 | @param id: id to create a menu |
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| 47 | @param owner: owner of menu |
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| 48 | @ return : list of information to populate the main menu |
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| 49 | """ |
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| 50 | #Menu for fitting |
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| 51 | self.menu1 = wx.Menu() |
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| 52 | id1 = wx.NewId() |
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| 53 | self.menu1.Append(id1, '&Show fit panel') |
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| 54 | wx.EVT_MENU(owner, id1, self.on_perspective) |
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| 55 | id3 = wx.NewId() |
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| 56 | self.menu1.AppendCheckItem(id3, "park") |
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| 57 | wx.EVT_MENU(owner, id3, self._onset_engine) |
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| 58 | |
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| 59 | #menu for model |
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| 60 | menu2 = wx.Menu() |
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| 61 | self.menu_mng.populate_menu(menu2, owner) |
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| 62 | id2 = wx.NewId() |
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| 63 | owner.Bind(models.EVT_MODEL,self._on_model_menu) |
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| 64 | self.fit_panel.set_owner(owner) |
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| 65 | self.fit_panel.set_model_list(self.menu_mng.get_model_list()) |
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| 66 | owner.Bind(fitpage1D.EVT_MODEL_BOX,self._on_model_panel) |
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| 67 | owner.Bind(fitpage2D.EVT_MODEL_BOX,self._on_model_panel) |
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| 68 | #create menubar items |
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| 69 | return [(id, self.menu1, "Fitting"),(id2, menu2, "Model")] |
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| 70 | |
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| 71 | |
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| 72 | def help(self, evt): |
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| 73 | """ |
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| 74 | Show a general help dialog. |
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| 75 | TODO: replace the text with a nice image |
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| 76 | """ |
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| 77 | pass |
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| 78 | |
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| 79 | def get_context_menu(self, graph=None): |
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| 80 | """ |
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| 81 | Get the context menu items available for P(r) |
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| 82 | @param graph: the Graph object to which we attach the context menu |
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| 83 | @return: a list of menu items with call-back function |
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| 84 | """ |
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| 85 | self.graph=graph |
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| 86 | for item in graph.plottables: |
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| 87 | if item.__class__.__name__ is "MetaData2D": |
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| 88 | return [["Fit Data2D", "Dialog with fitting parameters ", self._onSelect]] |
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| 89 | else: |
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| 90 | if item.name==graph.selected_plottable and (item.__class__.__name__ is "MetaData1D"or \ |
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| 91 | item.__class__.__name__ is "Data1D" ): |
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| 92 | return [["Fit Data1D", "Dialog with fitting parameters ", self._onSelect]] |
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| 93 | return [] |
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| 94 | |
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| 95 | |
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| 96 | def get_panels(self, parent): |
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| 97 | """ |
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| 98 | Create and return a list of panel objects |
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| 99 | """ |
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| 100 | self.parent = parent |
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| 101 | # Creation of the fit panel |
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| 102 | self.fit_panel = FitPanel(self.parent, -1) |
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| 103 | #Set the manager forthe main panel |
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| 104 | self.fit_panel.set_manager(self) |
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| 105 | # List of windows used for the perspective |
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| 106 | self.perspective = [] |
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| 107 | self.perspective.append(self.fit_panel.window_name) |
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| 108 | # take care of saving data, model and page associated with each other |
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| 109 | self.page_finder = {} |
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| 110 | #index number to create random model name |
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| 111 | self.index_model = 0 |
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| 112 | #create the fitting panel |
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| 113 | return [self.fit_panel] |
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| 114 | |
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| 115 | |
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| 116 | def get_perspective(self): |
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| 117 | """ |
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| 118 | Get the list of panel names for this perspective |
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| 119 | """ |
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| 120 | return self.perspective |
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| 121 | |
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| 122 | |
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| 123 | def on_perspective(self, event): |
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| 124 | """ |
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| 125 | Call back function for the perspective menu item. |
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| 126 | We notify the parent window that the perspective |
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| 127 | has changed. |
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| 128 | """ |
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| 129 | self.parent.set_perspective(self.perspective) |
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| 130 | |
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| 131 | |
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| 132 | def post_init(self): |
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| 133 | """ |
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| 134 | Post initialization call back to close the loose ends |
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| 135 | [Somehow openGL needs this call] |
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| 136 | """ |
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| 137 | self.parent.set_perspective(self.perspective) |
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| 138 | |
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| 139 | |
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| 140 | def _onSelect(self,event): |
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| 141 | """ |
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| 142 | when Select data to fit a new page is created .Its reference is |
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| 143 | added to self.page_finder |
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| 144 | """ |
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| 145 | self.panel = event.GetEventObject() |
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| 146 | for item in self.panel.graph.plottables: |
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| 147 | if item.name == self.panel.graph.selected_plottable or item.__class__.__name__ is "MetaData2D": |
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| 148 | #find a name for the page created for notebook |
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| 149 | try: |
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| 150 | page = self.fit_panel.add_fit_page(item) |
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| 151 | # add data associated to the page created |
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| 152 | |
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| 153 | if page !=None: |
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| 154 | |
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| 155 | #create a fitproblem storing all link to data,model,page creation |
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| 156 | self.page_finder[page]= FitProblem() |
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| 157 | self.page_finder[page].add_data(item) |
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| 158 | except: |
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| 159 | wx.PostEvent(self.parent, StatusEvent(status="Creating Fit page: %s"\ |
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| 160 | %sys.exc_value)) |
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| 161 | def schedule_for_fit(self,value=0,fitproblem =None): |
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| 162 | """ |
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| 163 | |
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| 164 | """ |
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| 165 | if fitproblem !=None: |
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| 166 | fitproblem.schedule_tofit(value) |
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| 167 | else: |
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| 168 | current_pg=self.fit_panel.get_current_page() |
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| 169 | for page, val in self.page_finder.iteritems(): |
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| 170 | if page ==current_pg : |
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| 171 | val.schedule_tofit(value) |
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| 172 | break |
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| 173 | |
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| 174 | |
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| 175 | def get_page_finder(self): |
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| 176 | """ @return self.page_finder used also by simfitpage.py""" |
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| 177 | return self.page_finder |
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| 178 | |
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| 179 | |
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| 180 | def set_page_finder(self,modelname,names,values): |
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| 181 | """ |
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| 182 | Used by simfitpage.py to reset a parameter given the string constrainst. |
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| 183 | @param modelname: the name ot the model for with the parameter has to reset |
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| 184 | @param value: can be a string in this case. |
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| 185 | @param names: the paramter name |
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| 186 | @note: expecting park used for fit. |
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| 187 | """ |
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| 188 | sim_page=self.fit_panel.get_page(0) |
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| 189 | for page, value in self.page_finder.iteritems(): |
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| 190 | if page != sim_page: |
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| 191 | list=value.get_model() |
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| 192 | model=list[0] |
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| 193 | #print "fitting",model.name,modelname |
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| 194 | if model.name== modelname: |
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| 195 | value.set_model_param(names,values) |
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| 196 | break |
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| 197 | |
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| 198 | |
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| 199 | |
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| 200 | def split_string(self,item): |
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| 201 | """ |
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| 202 | receive a word containing dot and split it. used to split parameterset |
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| 203 | name into model name and parameter name example: |
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| 204 | paramaterset (item) = M1.A |
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| 205 | @return model_name =M1 , parameter name =A |
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| 206 | """ |
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| 207 | if string.find(item,".")!=-1: |
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| 208 | param_names= re.split("\.",item) |
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| 209 | model_name=param_names[0] |
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| 210 | param_name=param_names[1] |
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| 211 | return model_name,param_name |
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| 212 | |
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| 213 | |
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| 214 | def _single_fit_completed(self,result,pars,cpage,qmin,qmax): |
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| 215 | """ |
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| 216 | Display fit result on one page of the notebook. |
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| 217 | @param result: result of fit |
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| 218 | @param pars: list of names of parameters fitted |
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| 219 | @param current_pg: the page where information will be displayed |
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| 220 | @param qmin: the minimum value of x to replot the model |
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| 221 | @param qmax: the maximum value of x to replot model |
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| 222 | |
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| 223 | """ |
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| 224 | try: |
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| 225 | for page, value in self.page_finder.iteritems(): |
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| 226 | if page==cpage : |
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| 227 | #fitdata = value.get_data() |
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| 228 | list = value.get_model() |
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| 229 | model= list[0] |
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| 230 | break |
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| 231 | i = 0 |
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| 232 | # print "fitting: single fit pars ", pars |
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| 233 | for name in pars: |
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| 234 | if result.pvec.__class__==numpy.float64: |
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| 235 | model.setParam(name,result.pvec) |
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| 236 | else: |
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| 237 | model.setParam(name,result.pvec[i]) |
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| 238 | # print "fitting: single fit", name, result.pvec[i] |
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| 239 | i += 1 |
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| 240 | # print "fitting result : chisqr",result.fitness |
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| 241 | # print "fitting result : pvec",result.pvec |
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| 242 | # print "fitting result : stderr",result.stderr |
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| 243 | |
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| 244 | cpage.onsetValues(result.fitness, result.pvec,result.stderr) |
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| 245 | self.plot_helper(currpage=cpage,qmin=qmin,qmax=qmax) |
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| 246 | except: |
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| 247 | raise |
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| 248 | wx.PostEvent(self.parent, StatusEvent(status="Fitting error: %s" % sys.exc_value)) |
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| 249 | |
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| 250 | |
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| 251 | def _simul_fit_completed(self,result,qmin,qmax): |
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| 252 | """ |
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| 253 | Parameter estimation completed, |
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| 254 | display the results to the user |
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| 255 | @param alpha: estimated best alpha |
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| 256 | @param elapsed: computation time |
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| 257 | """ |
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| 258 | try: |
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| 259 | for page, value in self.page_finder.iteritems(): |
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| 260 | if value.get_scheduled()==1: |
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| 261 | #fitdata = value.get_data() |
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| 262 | list = value.get_model() |
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| 263 | model= list[0] |
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| 264 | |
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| 265 | small_out = [] |
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| 266 | small_cov = [] |
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| 267 | i = 0 |
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| 268 | #Separate result in to data corresponding to each page |
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| 269 | for p in result.parameters: |
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| 270 | model_name,param_name = self.split_string(p.name) |
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| 271 | if model.name == model_name: |
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| 272 | small_out.append(p.value ) |
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| 273 | small_cov.append(p.stderr) |
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| 274 | model.setParam(param_name,p.value) |
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| 275 | # Display result on each page |
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| 276 | page.onsetValues(result.fitness, small_out,small_cov) |
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| 277 | #Replot model |
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| 278 | self.plot_helper(currpage= page,qmin= qmin,qmax= qmax) |
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| 279 | except: |
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| 280 | wx.PostEvent(self.parent, StatusEvent(status="Fitting error: %s" % sys.exc_value)) |
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| 281 | |
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| 282 | |
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| 283 | def _on_single_fit(self,id=None,qmin=None,qmax=None): |
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| 284 | """ |
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| 285 | perform fit for the current page and return chisqr,out and cov |
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| 286 | @param engineName: type of fit to be performed |
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| 287 | @param id: unique id corresponding to a fit problem(model, set of data) |
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| 288 | @param model: model to fit |
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| 289 | |
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| 290 | """ |
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| 291 | #print "in single fitting" |
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| 292 | #set an engine to perform fit |
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| 293 | from sans.fit.Fitting import Fit |
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| 294 | self.fitter= Fit(self._fit_engine) |
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| 295 | #Setting an id to store model and data in fit engine |
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| 296 | if id==None: |
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| 297 | id=0 |
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| 298 | self.id = id |
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| 299 | page_fitted=None |
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| 300 | fit_problem=None |
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| 301 | #Get information (model , data) related to the page on |
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| 302 | #with the fit will be perform |
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| 303 | #current_pg=self.fit_panel.get_current_page() |
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| 304 | #simul_pg=self.fit_panel.get_page(0) |
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| 305 | |
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| 306 | for page, value in self.page_finder.iteritems(): |
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| 307 | if value.get_scheduled() ==1 : |
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| 308 | fitdata = value.get_data() |
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| 309 | list=value.get_model() |
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| 310 | model=list[0] |
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| 311 | #Create list of parameters for fitting used |
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| 312 | pars=[] |
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| 313 | templist=[] |
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| 314 | try: |
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| 315 | #templist=current_pg.get_param_list() |
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| 316 | templist=page.get_param_list() |
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| 317 | for element in templist: |
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| 318 | pars.append(str(element[0].GetLabelText())) |
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| 319 | pars.sort() |
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| 320 | #Do the single fit |
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| 321 | self.fitter.set_model(Model(model), self.id, pars) |
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| 322 | self.fitter.set_data(fitdata,self.id,qmin,qmax) |
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| 323 | self.fitter.select_problem_for_fit(Uid=self.id,value=value.get_scheduled()) |
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| 324 | page_fitted=page |
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| 325 | self.id+=1 |
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| 326 | self.schedule_for_fit( 0,value) |
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| 327 | except: |
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| 328 | wx.PostEvent(self.parent, StatusEvent(status="Fitting error: %s" % sys.exc_value)) |
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| 329 | return |
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| 330 | # make sure to keep an alphabetic order |
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| 331 | #of parameter names in the list |
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| 332 | try: |
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| 333 | result=self.fitter.fit() |
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| 334 | #self._single_fit_completed(result,pars,current_pg,qmin,qmax) |
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| 335 | print "single_fit: result",result.fitness,result.pvec,result.stderr |
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| 336 | #self._single_fit_completed(result,pars,page,qmin,qmax) |
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| 337 | self._single_fit_completed(result,pars,page_fitted,qmin,qmax) |
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| 338 | except: |
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| 339 | raise |
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| 340 | wx.PostEvent(self.parent, StatusEvent(status="Single Fit error: %s" % sys.exc_value)) |
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| 341 | return |
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| 342 | |
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| 343 | def _on_simul_fit(self, id=None,qmin=None,qmax=None): |
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| 344 | """ |
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| 345 | perform fit for all the pages selected on simpage and return chisqr,out and cov |
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| 346 | @param engineName: type of fit to be performed |
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| 347 | @param id: unique id corresponding to a fit problem(model, set of data) |
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| 348 | in park_integration |
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| 349 | @param model: model to fit |
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| 350 | |
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| 351 | """ |
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| 352 | #set an engine to perform fit |
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| 353 | from sans.fit.Fitting import Fit |
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| 354 | self.fitter= Fit(self._fit_engine) |
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| 355 | |
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| 356 | #Setting an id to store model and data |
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| 357 | if id==None: |
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| 358 | id = 0 |
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| 359 | self.id = id |
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| 360 | |
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| 361 | for page, value in self.page_finder.iteritems(): |
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| 362 | try: |
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| 363 | if value.get_scheduled()==1: |
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| 364 | fitdata = value.get_data() |
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| 365 | list = value.get_model() |
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| 366 | model= list[0] |
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| 367 | #Create dictionary of parameters for fitting used |
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| 368 | pars = [] |
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| 369 | templist = [] |
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| 370 | templist = page.get_param_list() |
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| 371 | for element in templist: |
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| 372 | try: |
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| 373 | name = str(element[0].GetLabelText()) |
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| 374 | pars.append(name) |
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| 375 | except: |
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| 376 | wx.PostEvent(self.parent, StatusEvent(status="Fitting error: %s" % sys.exc_value)) |
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| 377 | return |
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| 378 | new_model=Model(model) |
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| 379 | param=value.get_model_param() |
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| 380 | |
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| 381 | if len(param)>0: |
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| 382 | for item in param: |
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| 383 | param_value = item[1] |
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| 384 | param_name = item[0] |
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| 385 | #print "fitting ", param,param_name, param_value |
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| 386 | |
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| 387 | #new_model.set( model.getParam(param_name[0])= param_value) |
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| 388 | #new_model.set( exec"%s=%s"%(param_name[0], param_value)) |
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| 389 | #new_model.set( exec "%s"%(param_nam) = param_value) |
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| 390 | new_model.parameterset[ param_name].set( param_value ) |
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| 391 | |
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| 392 | self.fitter.set_model(new_model, self.id, pars) |
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| 393 | self.fitter.set_data(fitdata,self.id,qmin,qmax) |
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| 394 | self.fitter.select_problem_for_fit(Uid=self.id,value=value.get_scheduled()) |
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| 395 | self.id += 1 |
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| 396 | except: |
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| 397 | wx.PostEvent(self.parent, StatusEvent(status="Fitting error: %s" % sys.exc_value)) |
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| 398 | return |
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| 399 | #Do the simultaneous fit |
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| 400 | try: |
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| 401 | result=self.fitter.fit() |
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| 402 | self._simul_fit_completed(result,qmin,qmax) |
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| 403 | except: |
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| 404 | wx.PostEvent(self.parent, StatusEvent(status="Simultaneous Fitting error: %s" % sys.exc_value)) |
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| 405 | return |
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| 406 | |
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| 407 | |
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| 408 | def _onset_engine(self,event): |
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| 409 | """ set engine to scipy""" |
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| 410 | if self._fit_engine== 'park': |
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| 411 | self._on_change_engine('scipy') |
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| 412 | else: |
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| 413 | self._on_change_engine('park') |
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| 414 | wx.PostEvent(self.parent, StatusEvent(status="Engine set to: %s" % self._fit_engine)) |
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| 415 | |
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| 416 | |
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| 417 | def _on_change_engine(self, engine='park'): |
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| 418 | """ |
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| 419 | Allow to select the type of engine to perform fit |
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| 420 | @param engine: the key work of the engine |
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| 421 | """ |
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| 422 | self._fit_engine = engine |
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| 423 | |
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| 424 | |
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| 425 | def _on_model_panel(self, evt): |
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| 426 | """ |
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| 427 | react to model selection on any combo box or model menu.plot the model |
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| 428 | """ |
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| 429 | |
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| 430 | model = evt.model |
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| 431 | name = evt.name |
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| 432 | sim_page=self.fit_panel.get_page(0) |
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| 433 | current_pg = self.fit_panel.get_current_page() |
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| 434 | if current_pg != sim_page: |
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| 435 | current_pg.set_model_name(name) |
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| 436 | current_pg.set_panel(model) |
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| 437 | |
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| 438 | try: |
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| 439 | metadata=self.page_finder[current_pg].get_data() |
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| 440 | M_name="M"+str(self.index_model)+"= "+name+"("+metadata.group_id+")" |
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| 441 | except: |
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| 442 | M_name="M"+str(self.index_model)+"= "+name |
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| 443 | model.name="M"+str(self.index_model) |
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| 444 | self.index_model += 1 |
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| 445 | |
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| 446 | self.page_finder[current_pg].set_model(model,M_name) |
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| 447 | self.plot_helper(currpage= current_pg,qmin= None,qmax= None) |
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| 448 | sim_page.add_model(self.page_finder) |
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| 449 | |
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| 450 | |
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| 451 | def redraw_model(self,qmin= None,qmax= None): |
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| 452 | """ |
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| 453 | Draw a theory according to model changes or data range. |
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| 454 | @param qmin: the minimum value plotted for theory |
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| 455 | @param qmax: the maximum value plotted for theory |
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| 456 | """ |
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| 457 | current_pg=self.fit_panel.get_current_page() |
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| 458 | for page, value in self.page_finder.iteritems(): |
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| 459 | if page ==current_pg : |
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| 460 | break |
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| 461 | self.plot_helper(currpage=page,qmin= qmin,qmax= qmax) |
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| 462 | |
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| 463 | def plot_helper(self,currpage,qmin=None,qmax=None): |
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| 464 | """ |
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| 465 | Plot a theory given a model and data |
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| 466 | @param model: the model from where the theory is derived |
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| 467 | @param currpage: page in a dictionary referring to some data |
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| 468 | """ |
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| 469 | if self.fit_panel.get_page_count() >1: |
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| 470 | for page in self.page_finder.iterkeys(): |
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| 471 | if page==currpage : |
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| 472 | data=self.page_finder[page].get_data() |
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| 473 | list=self.page_finder[page].get_model() |
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| 474 | model=list[0] |
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| 475 | break |
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| 476 | |
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| 477 | if data!=None and data.__class__.__name__ != 'MetaData2D': |
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| 478 | theory = Theory1D(x=[], y=[]) |
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| 479 | theory.name = "Model" |
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| 480 | theory.group_id = data.group_id |
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| 481 | |
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| 482 | x_name, x_units = data.get_xaxis() |
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| 483 | y_name, y_units = data.get_yaxis() |
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| 484 | theory.xaxis(x_name, x_units) |
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| 485 | theory.yaxis(y_name, y_units) |
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| 486 | if qmin == None : |
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| 487 | qmin = min(data.x) |
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| 488 | if qmax == None : |
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| 489 | qmax = max(data.x) |
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| 490 | try: |
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| 491 | tempx = qmin |
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| 492 | tempy = model.run(qmin) |
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| 493 | theory.x.append(tempx) |
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| 494 | theory.y.append(tempy) |
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| 495 | except : |
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| 496 | wx.PostEvent(self.parent, StatusEvent(status="fitting \ |
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| 497 | skipping point x %g %s" %(qmin, sys.exc_value))) |
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| 498 | |
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| 499 | for i in range(len(data.x)): |
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| 500 | try: |
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| 501 | if data.x[i]> qmin and data.x[i]< qmax: |
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| 502 | tempx = data.x[i] |
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| 503 | tempy = model.run(tempx) |
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| 504 | theory.x.append(tempx) |
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| 505 | theory.y.append(tempy) |
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| 506 | except: |
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| 507 | wx.PostEvent(self.parent, StatusEvent(status="fitting \ |
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| 508 | skipping point x %g %s" %(data.x[i], sys.exc_value))) |
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| 509 | try: |
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| 510 | tempx = qmax |
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| 511 | tempy = model.run(qmax) |
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| 512 | theory.x.append(tempx) |
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| 513 | theory.y.append(tempy) |
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| 514 | |
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| 515 | except: |
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| 516 | wx.PostEvent(self.parent, StatusEvent(status="fitting \ |
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| 517 | skipping point x %g %s" %(qmax, sys.exc_value))) |
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| 518 | else: |
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| 519 | theory=Data2D(data.image, data.err_image) |
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| 520 | theory.x_bins= data.x_bins |
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| 521 | theory.y_bins= data.y_bins |
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| 522 | tempy=[] |
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| 523 | for i in range(len(data.x_bins)): |
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| 524 | theory.image= model.runXY([data.x_bins[i],data.y_bins[i]]) |
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| 525 | #print "fitting : plot_helper:", theory.image |
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| 526 | #print data.image |
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| 527 | #theory.image=model.runXY(data.image) |
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| 528 | theory.image=model.run(data.image) |
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| 529 | print "fitting : plot_helper:",theory.image |
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| 530 | theory.zmin= data.zmin |
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| 531 | theory.zmax= data.zmax |
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| 532 | theory.xmin= data.xmin |
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| 533 | theory.xmax= data.xmax |
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| 534 | theory.ymin= data.ymin |
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| 535 | theory.ymax= data.ymax |
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| 536 | |
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| 537 | wx.PostEvent(self.parent, NewPlotEvent(plot=theory, title="Analytical model")) |
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| 538 | |
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| 539 | |
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| 540 | def _on_model_menu(self, evt): |
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| 541 | """ |
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| 542 | Plot a theory from a model selected from the menu |
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| 543 | """ |
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| 544 | name="Model View" |
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| 545 | model=evt.modelinfo.model() |
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| 546 | description=evt.modelinfo.description |
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| 547 | self.fit_panel.add_model_page(model,description,name) |
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| 548 | self.draw_model(model) |
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| 549 | |
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| 550 | def draw_model(self,model): |
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| 551 | """ |
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| 552 | draw model with default data value |
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| 553 | """ |
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| 554 | x = pylab.arange(0.001, 0.1, 0.001) |
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| 555 | xlen = len(x) |
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| 556 | dy = numpy.zeros(xlen) |
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| 557 | y = numpy.zeros(xlen) |
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| 558 | |
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| 559 | for i in range(xlen): |
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| 560 | y[i] = model.run(x[i]) |
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| 561 | dy[i] = math.sqrt(math.fabs(y[i])) |
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| 562 | try: |
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| 563 | |
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| 564 | new_plot = Theory1D(x, y) |
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| 565 | new_plot.name = "Model" |
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| 566 | new_plot.xaxis("\\rm{Q}", 'A^{-1}') |
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| 567 | new_plot.yaxis("\\rm{Intensity} ","cm^{-1}") |
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| 568 | new_plot.group_id ="Fitness" |
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| 569 | wx.PostEvent(self.parent, NewPlotEvent(plot=new_plot, title="Analytical model")) |
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| 570 | except: |
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| 571 | wx.PostEvent(self.parent, StatusEvent(status="fitting \ |
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| 572 | skipping point x %g %s" %(qmax, sys.exc_value))) |
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| 573 | |
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| 574 | if __name__ == "__main__": |
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| 575 | i = Plugin() |
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| 576 | |
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| 577 | |
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| 578 | |
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| 579 | |
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