Changes in / [9ba91b7:fb560d2] in sasview

Location:

src/sas/qtgui/Perspectives/Fitting

Files:

• FittingLogic.py (modified) (2 diffs)
• FittingWidget.py (modified) (1 diff)
• ModelThread.py (modified) (2 diffs)
• UnitTesting/FittingLogicTest.py (modified) (1 diff)

src/sas/qtgui/Perspectives/Fitting/FittingLogic.py

@@ -161 +161 @@
         Create a new 1D data instance based on fitting results
         """
+
         return self._create1DPlot(tab_id, return_data['x'], return_data['y'],
                                   return_data['model'], return_data['data'])
@@ -211 +212 @@
         (pq_plot, sq_plot). If either are unavailable, the corresponding plot is None.
         """
-        plots = []
-        for name, result in return_data['intermediate_results'].items():
-            plots.append(self._create1DPlot(tab_id, return_data['x'], result,
-                         return_data['model'], return_data['data'],
-                         component=name))
-        return plots
+
+        pq_plot = None
+        sq_plot = None
+
+        if return_data.get('pq_values', None) is not None:
+            pq_plot = self._create1DPlot(tab_id, return_data['x'],
+                    return_data['pq_values'], return_data['model'],
+                    return_data['data'], component="P(Q)")
+        if return_data.get('sq_values', None) is not None:
+            sq_plot = self._create1DPlot(tab_id, return_data['x'],
+                    return_data['sq_values'], return_data['model'],
+                    return_data['data'], component="S(Q)")
+
+        return pq_plot, sq_plot
 
     def computeDataRange(self):

src/sas/qtgui/Perspectives/Fitting/FittingWidget.py

@@ -2417 +2417 @@
 
         # Create plots for intermediate product data
-        plots = self.logic.new1DProductPlots(return_data, self.tab_id)
-        for plot in plots:
-            plot.symbol = "Line"
-            self.createNewIndex(plot)
-            new_plots.append(plot)
+        pq_data, sq_data = self.logic.new1DProductPlots(return_data, self.tab_id)
+        if pq_data is not None:
+            pq_data.symbol = "Line"
+            self.createNewIndex(pq_data)
+            # self.communicate.plotUpdateSignal.emit([pq_data])
+            new_plots.append(pq_data)
+        if sq_data is not None:
+            sq_data.symbol = "Line"
+            self.createNewIndex(sq_data)
+            # self.communicate.plotUpdateSignal.emit([sq_data])
+            new_plots.append(sq_data)
 
         for plot in new_plots:

src/sas/qtgui/Perspectives/Fitting/ModelThread.py

@@ -195 +195 @@
             output[index] = self.model.evalDistribution(self.data.x[index])
 
-        results_eval = {}
-        intermediate_results = getattr(self.model, "_intermediate_results", None)
-        if callable(intermediate_results):
-            # support for future sasmodels (beta approx support) - it returns a dict of intermediate results, keyed by
-            # name
-            results_eval = intermediate_results()
-        else:
-            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, "calc_composition_models"):
-                results = self.model.calc_composition_models(self.data.x[index])
-                if results is not None:
-                    pq_values, sq_values = results
-
-            if pq_values is None or sq_values is None:
-                if p_model is not None and s_model is not None:
-                    sq_values = numpy.zeros((len(self.data.x)))
-                    pq_values = numpy.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])
-
-            if pq_values is not None and sq_values is not None:
-                results_eval = {
-                    "P(Q)": pq_values,
-                    "S(Q)": sq_values
-                }
+        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, "calc_composition_models"):
+            results = self.model.calc_composition_models(self.data.x[index])
+            if results is not None:
+                pq_values, sq_values = results
+
+        if pq_values is None or sq_values is None:
+            if p_model is not None and s_model is not None:
+                sq_values = numpy.zeros((len(self.data.x)))
+                pq_values = numpy.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])
 
         elapsed = time.time() - self.starttime
@@ -236 +223 @@
             source = self.source, unsmeared_output = unsmeared_output,
             unsmeared_data = unsmeared_data, unsmeared_error = unsmeared_error,
-            intermediate_results = results_eval)
+            pq_values = pq_values, sq_values = sq_values)
 
         if LocalConfig.USING_TWISTED:

src/sas/qtgui/Perspectives/Fitting/UnitTesting/FittingLogicTest.py

@@ -103 +103 @@
                        data, False, None,
                        None, None, None,
-                       None)
+                       None, None)
 
         new_plot = self.logic.new1DPlot(return_data=return_data, tab_id=0)