Changeset 24b3821 in sasview for src/sas/sasgui/perspectives


Ignore:
Timestamp:
Apr 11, 2017 9:02:04 AM (8 years ago)
Author:
butler
Branches:
master, ESS_GUI, ESS_GUI_Docs, ESS_GUI_batch_fitting, ESS_GUI_bumps_abstraction, ESS_GUI_iss1116, ESS_GUI_iss879, ESS_GUI_iss959, ESS_GUI_opencl, ESS_GUI_ordering, ESS_GUI_sync_sascalc, costrafo411, magnetic_scatt, release-4.2.2, ticket-1009, ticket-1094-headless, ticket-1242-2d-resolution, ticket-1243, ticket-1249, ticket885, unittest-saveload
Children:
426df2e
Parents:
d26f025
Message:

re-enable calculation/separation of P & S in SasView? (appearing under
the model they fit or in theory as appropriate) addresses #741

Location:
src/sas/sasgui/perspectives/fitting
Files:
2 edited

Legend:

Unmodified
Added
Removed
  • src/sas/sasgui/perspectives/fitting/fitting.py

    r7432acb r24b3821  
    359359                                   'Add a new model function') 
    360360        wx.EVT_MENU(owner, wx_id, self.make_new_model) 
    361          
     361 
    362362        wx_id = wx.NewId() 
    363363        self.edit_model_menu.Append(wx_id, 'Sum|Multi(p1, p2)', 
     
    381381          '(Re)Load all models present in user plugin_models folder') 
    382382        wx.EVT_MENU(owner, wx_id, self.load_plugin_models) 
    383                  
     383    
    384384    def set_edit_menu_helper(self, owner=None, menu=None): 
    385385        """ 
     
    17481748                                          dy=unsmeared_error) 
    17491749            # Comment this out until we can get P*S models with correctly populated parameters 
    1750             #if sq_model is not None and pq_model is not None: 
    1751             #    self.create_theory_1D(x, sq_model, page_id, model, data, state, 
    1752             #                          data_description=model.name + " S(q)", 
    1753             #                          data_id=str(page_id) + " " + data.name + " S(q)") 
    1754             #    self.create_theory_1D(x, pq_model, page_id, model, data, state, 
    1755             #                          data_description=model.name + " P(q)", 
    1756             #                          data_id=str(page_id) + " " + data.name + " P(q)") 
     1750            if sq_model is not None and pq_model is not None: 
     1751                self.create_theory_1D(x, sq_model, page_id, model, data, state, 
     1752                                      data_description=model.name + " S(q)", 
     1753                                      data_id=str(page_id) + " " + data.name + " S(q)") 
     1754                self.create_theory_1D(x, pq_model, page_id, model, data, state, 
     1755                                      data_description=model.name + " P(q)", 
     1756                                      data_id=str(page_id) + " " + data.name + " P(q)") 
    17571757 
    17581758            current_pg = self.fit_panel.get_page_by_id(page_id) 
     
    19101910                ## and may be the cause of other noted instabilities 
    19111911                ## 
    1912                 ##    -PDB August 12, 2014  
     1912                ##    -PDB August 12, 2014 
    19131913                while self.calc_2D.isrunning(): 
    19141914                    time.sleep(0.1) 
     
    19521952            if (self.calc_1D is not None) and self.calc_1D.isrunning(): 
    19531953                self.calc_1D.stop() 
    1954                 ## stop just raises the flag -- the thread is supposed to  
     1954                ## stop just raises the flag -- the thread is supposed to 
    19551955                ## then kill itself but cannot.  Paul Kienzle came up with 
    19561956                ## this fix to prevent threads from stepping on each other 
     
    19641964                ## a request to stop the computation. 
    19651965                ## It seems thus that the whole thread approach used here 
    1966                 ## May need rethinking   
     1966                ## May need rethinking 
    19671967                ## 
    19681968                ##    -PDB August 12, 2014 
     
    21292129            residuals.dxw = None 
    21302130            residuals.ytransform = 'y' 
    2131             # For latter scale changes  
     2131            # For latter scale changes 
    21322132            residuals.xaxis('\\rm{Q} ', 'A^{-1}') 
    21332133            residuals.yaxis('\\rm{Residuals} ', 'normalized') 
  • src/sas/sasgui/perspectives/fitting/model_thread.py

    r7432acb r24b3821  
    7171                    (self.data.qy_data * self.data.qy_data)) 
    7272 
    73         # For theory, qmax is based on 1d qmax  
     73        # For theory, qmax is based on 1d qmax 
    7474        # so that must be mulitified by sqrt(2) to get actual max for 2d 
    7575        index_model = (self.qmin <= radius) & (radius <= self.qmax) 
     
    9191                self.data.qy_data[index_model] 
    9292            ]) 
    93         output = np.zeros(len(self.data.qx_data)) 
     93        # Initialize output to NaN so masked elements do not get plotted. 
     94        output = np.empty_like(self.data.qx_data) 
    9495        # output default is None 
    9596        # This method is to distinguish between masked 
    9697        #point(nan) and data point = 0. 
    97         output = output / output 
     98        output[:] = np.NaN 
    9899        # set value for self.mask==True, else still None to Plottools 
    99100        output[index_model] = value 
     
    198199            output[index] = self.model.evalDistribution(self.data.x[index]) 
    199200 
     201        x=self.data.x[index] 
     202        y=output[index] 
    200203        sq_values = None 
    201204        pq_values = None 
    202         s_model = None 
    203         p_model = None 
    204205        if isinstance(self.model, MultiplicationModel): 
    205206            s_model = self.model.s_model 
    206207            p_model = self.model.p_model 
    207         elif hasattr(self.model, "get_composition_models"): 
    208             p_model, s_model = self.model.get_composition_models() 
    209  
    210         if p_model is not None and s_model is not None: 
    211             sq_values = np.zeros((len(self.data.x))) 
    212             pq_values = np.zeros((len(self.data.x))) 
    213             sq_values[index] = s_model.evalDistribution(self.data.x[index]) 
    214             pq_values[index] = p_model.evalDistribution(self.data.x[index]) 
     208            #sq_values = np.zeros((len(self.data.x))) 
     209            #pq_values = np.zeros((len(self.data.x))) 
     210            #sq_values[index] = s_model.evalDistribution(self.data.x[index]) 
     211            #pq_values[index] = p_model.evalDistribution(self.data.x[index]) 
     212            sq_values = s_model.evalDistribution(x) 
     213            pq_values = p_model.evalDistribution(x) 
     214        elif hasattr(self.model, "calc_composition_models"): 
     215            results = self.model.calc_composition_models(x) 
     216            if results is not None: 
     217                sq_values = results[0] 
     218                pq_values = results[1] 
     219 
    215220 
    216221        elapsed = time.time() - self.starttime 
    217222 
    218         self.complete(x=self.data.x[index], y=output[index], 
     223        self.complete(x=x, y=y, 
    219224                      page_id=self.page_id, 
    220225                      state=self.state, 
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