Changes in / [33d5956:30bed93] in sasview

Location:

src/sas/qtgui

Files:

• MainWindow/DataExplorer.py (modified) (1 diff)
• Perspectives/Fitting/FittingUtilities.py (modified) (1 diff)
• Perspectives/Fitting/FittingWidget.py (modified) (2 diffs)

src/sas/qtgui/MainWindow/DataExplorer.py

@@ -579 +579 @@
             # Don't plot intermediate results, e.g. P(Q), S(Q)
             match = GuiUtils.theory_plot_ID_pattern.match(plot.id)
-            # 2nd match group contains the identifier for the intermediate result, if present (e.g. "[P(Q)]")
+            # 2nd match group contains the identifier for the intermediate
+            # result, if present (e.g. "[P(Q)]")
             if match and match.groups()[1] != None:
                 continue
-            # Don't include plots from different fitpages, but always include the original data
-            if fitpage_name in plot.name or filename in plot.name or filename == plot.filename:
+            # Don't include plots from different fitpages,
+            # but always include the original data
+            if (fitpage_name in plot.name
+                    or filename in plot.name
+                    or filename == plot.filename):
                 # Residuals get their own plot
                 if plot.plot_role == Data1D.ROLE_RESIDUAL:

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

@@ -570 +570 @@
     return residuals
 
+def plotPolydispersities(model):
+    plots = []
+    if model is None:
+        return plots
+    # test for model being a sasmodels.sasview_model.SasviewModel?
+    for name in model.dispersion.keys():
+        xarr, yarr = model.get_weights(name)
+        if len(xarr) <= 1: # param name not found or no polydisp.
+            continue
+        # create Data1D as in residualsData1D() and fill x/y members
+        # similar to FittingLogic._create1DPlot() but different data/axes
+        data1d = Data1D(x=xarr, y=yarr)
+        xunit = model.details[name][0]
+        data1d.xaxis(r'\rm{{{}}}'.format(name.replace('_', '\_')), xunit)
+        data1d.yaxis(r'\rm{weight}', 'normalized')
+        data1d.scale = 'linear'
+        data1d.symbol = 'Line'
+        data1d.name = "{} polydispersity".format(name)
+        data1d.id = data1d.name # placeholder, has to be completed later
+        data1d.plot_role = Data1D.ROLE_RESIDUAL
+        plots.append(data1d)
+    return plots
+
 def binary_encode(i, digits):
     return [i >> d & 1 for d in range(digits)]

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

@@ -58 +58 @@
 DEFAULT_POLYDISP_FUNCTION = 'gaussian'
 
+# CRUFT: remove when new release of sasmodels is available
+# https://github.com/SasView/sasview/pull/181#discussion_r218135162
+from sasmodels.sasview_model import SasviewModel
+if not hasattr(SasviewModel, 'get_weights'):
+    def get_weights(self, name):
+        """
+        Returns the polydispersity distribution for parameter *name* as *value* and *weight* arrays.
+        """
+        # type: (str) -> Tuple(np.ndarray, np.ndarray)
+        _, x, w = self._get_weights(self._model_info.parameters[name])
+        return x, w
+
+    SasviewModel.get_weights = get_weights
 
 logger = logging.getLogger(__name__)
@@ -2488 +2501 @@
 
         if self.data_is_loaded:
-            # delete any plots associated with the data that were not updated (e.g. to remove beta(Q), S_eff(Q))
+            # delete any plots associated with the data that were not updated
+            # (e.g. to remove beta(Q), S_eff(Q))
             GuiUtils.deleteRedundantPlots(self.all_data[self.data_index], new_plots)
             pass
         else:
-            # delete theory items for the model, in order to get rid of any redundant items, e.g. beta(Q), S_eff(Q)
+            # delete theory items for the model, in order to get rid of any
+            # redundant items, e.g. beta(Q), S_eff(Q)
             self.communicate.deleteIntermediateTheoryPlotsSignal.emit(self.kernel_module.id)
+
+        # Create plots for parameters with enabled polydispersity
+        for plot in FittingUtilities.plotPolydispersities(return_data.get('model', None)):
+            data_id = fitted_data.id.split()
+            plot.id = "{} [{}] {}".format(data_id[0], plot.name, " ".join(data_id[1:]))
+            data_name = fitted_data.name.split()
+            plot.name = " ".join([data_name[0], plot.name] + data_name[1:])
+            self.createNewIndex(plot)
+            new_plots.append(plot)
 
         # Create plots for intermediate product data