Changeset 729198e in sasview for src/sas/sasgui/perspectives/fitting

Timestamp:

Sep 11, 2017 6:55:51 AM (7 years ago)

Author:

lewis

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:

ff65d02

Parents:

2d9526d (diff), e2b2473 (diff)
Note: this is a merge changeset, the changes displayed below correspond to the merge itself.
Use the (diff) links above to see all the changes relative to each parent.

Message:

Merge branch 'master' into FixingTicket741

Location:

src/sas/sasgui/perspectives/fitting

Files:

• fitting.py (modified) (2 diffs)
• model_thread.py (modified) (3 diffs)

src/sas/sasgui/perspectives/fitting/fitting.py

@@ -1742 +1742 @@
             @param unsmeared_error: data error, rescaled to unsmeared model
         """
-
         number_finite = np.count_nonzero(np.isfinite(y))
         np.nan_to_num(y)
@@ -1748 +1747 @@
                                          data_description=model.name,
                                          data_id=str(page_id) + " " + data.name)
+        plots_to_update = [] # List of plottables that have changed since last calculation
+        # Create the new theories
         if unsmeared_model is not None:
-            self.create_theory_1D(x, unsmeared_model, page_id, model, data, state,
+            unsmeared_model_plot = self.create_theory_1D(x, unsmeared_model, 
+                                  page_id, model, data, state,
                                   data_description=model.name + " unsmeared",
                                   data_id=str(page_id) + " " + data.name + " unsmeared")
+            plots_to_update.append(unsmeared_model_plot)
 
             if unsmeared_data is not None and unsmeared_error is not None:
-                self.create_theory_1D(x, unsmeared_data, page_id, model, data, state,
+                unsmeared_data_plot = self.create_theory_1D(x, unsmeared_data, 
+                                      page_id, model, data, state,
                                       data_description="Data unsmeared",
                                       data_id="Data  " + data.name + " unsmeared",
                                       dy=unsmeared_error)
-        # Comment this out until we can get P*S models with correctly populated parameters
-        #if sq_model is not None and pq_model is not None:
-        #    self.create_theory_1D(x, sq_model, page_id, model, data, state,
-        #                          data_description=model.name + " S(q)",
-        #                          data_id=str(page_id) + " " + data.name + " S(q)")
-        #    self.create_theory_1D(x, pq_model, page_id, model, data, state,
-        #                          data_description=model.name + " P(q)",
-        #                          data_id=str(page_id) + " " + data.name + " P(q)")
+                plots_to_update.append(unsmeared_data_plot)
+        if sq_model is not None and pq_model is not None:
+            sq_id = str(page_id) + " " + data.name + " S(q)"
+            sq_plot = self.create_theory_1D(x, sq_model, page_id, model, data, state,
+                                  data_description=model.name + " S(q)",
+                                  data_id=sq_id)
+            plots_to_update.append(sq_plot)
+            pq_id = str(page_id) + " " + data.name + " P(q)"
+            pq_plot = self.create_theory_1D(x, pq_model, page_id, model, data, state,
+                                  data_description=model.name + " P(q)",
+                                  data_id=pq_id)
+            plots_to_update.append(pq_plot)
+        # Update the P(Q), S(Q) and unsmeared theory plots if they exist
+        wx.PostEvent(self.parent, NewPlotEvent(plots=plots_to_update, 
+                                              action='update'))
 
         current_pg = self.fit_panel.get_page_by_id(page_id)

src/sas/sasgui/perspectives/fitting/model_thread.py

@@ -71 +71 @@
                     (self.data.qy_data * self.data.qy_data))
 
-        # For theory, qmax is based on 1d qmax 
+        # For theory, qmax is based on 1d qmax
         # so that must be mulitified by sqrt(2) to get actual max for 2d
         index_model = (self.qmin <= radius) & (radius <= self.qmax)
@@ -91 +91 @@
                 self.data.qy_data[index_model]
             ])
-        output = np.zeros(len(self.data.qx_data))
+        # Initialize output to NaN so masked elements do not get plotted.
+        output = np.empty_like(self.data.qx_data)
         # output default is None
         # This method is to distinguish between masked
         #point(nan) and data point = 0.
-        output = output / output
+        output[:] = np.NaN
         # set value for self.mask==True, else still None to Plottools
         output[index_model] = value
@@ -198 +199 @@
             output[index] = self.model.evalDistribution(self.data.x[index])
 
+        x=self.data.x[index]
+        y=output[index]
         sq_values = None
         pq_values = None
-        s_model = None
-        p_model = None
         if isinstance(self.model, MultiplicationModel):
             s_model = self.model.s_model
             p_model = self.model.p_model
-        elif hasattr(self.model, "get_composition_models"):
-            p_model, s_model = self.model.get_composition_models()
-
-        if p_model is not None and s_model is not None:
-            sq_values = np.zeros((len(self.data.x)))
-            pq_values = np.zeros((len(self.data.x)))
-            sq_values[index] = s_model.evalDistribution(self.data.x[index])
-            pq_values[index] = p_model.evalDistribution(self.data.x[index])
+            sq_values = s_model.evalDistribution(x)
+            pq_values = p_model.evalDistribution(x)
+        elif hasattr(self.model, "calc_composition_models"):
+            results = self.model.calc_composition_models(x)
+            if results is not None:
+                pq_values, sq_values = results
+
 
         elapsed = time.time() - self.starttime
 
-        self.complete(x=self.data.x[index], y=output[index],
+        self.complete(x=x, y=y,
                       page_id=self.page_id,
                       state=self.state,