Changeset 32f87a5 in sasmodels

Timestamp:

Oct 18, 2017 12:08:54 AM (7 years ago)

Author:

Paul Kienzle <pkienzle@…>

Branches:

master, core_shell_microgels, magnetic_model, ticket-1257-vesicle-product, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests

Children:

fbb9397

Parents:

8698a0d

Message:

update sasview wrapper with new way of handling orientation dispersity

Location:

sasmodels

Files:

• direct_model.py (modified) (1 diff)
• sasview_model.py (modified) (1 diff)

sasmodels/direct_model.py

@@ -141 +141 @@
     npts = values.get(parameter.name+'_pd_n', 0)
     width = values.get(parameter.name+'_pd', 0.0)
+    relative = parameter.relative_pd
     if npts == 0 or width == 0 or not active:
         # Note: orientation parameters have the viewing angle as the parameter
         # value and the jitter in the distribution, so be sure to set the
         # empty pd for orientation parameters to 0.
-        pd = [value if parameter.type != 'orientation' else 0.0], [1.0]
-    else:
-        relative = parameter.relative_pd
+        pd = [value if relative else 0.0], [1.0]
+    else:
         limits = parameter.limits
         disperser = values.get(parameter.name+'_pd_type', 'gaussian')

sasmodels/sasview_model.py

@@ -759 +759 @@
         if par.name not in self.params:
             if par.name == self.multiplicity_info.control:
-                return [self.multiplicity], [1.0]
+                return self.multiplicity, [self.multiplicity], [1.0]
             else:
                 # For hidden parameters use the default value.
-                value = self._model_info.parameters.defaults.get(par.name, np.NaN)
-                return [value], [1.0]
+                default = self._model_info.parameters.defaults.get(par.name, np.NaN)
+                return [default], [1.0]
         elif par.polydisperse:
+            value = self.params[par.name]
             dis = self.dispersion[par.name]
             if dis['type'] == 'array':
-                value, weight = dis['values'], dis['weights']
+                dispersity, weight = dis['values'], dis['weights']
             else:
-                value, weight = weights.get_weights(
+                dispersity, weight = weights.get_weights(
                     dis['type'], dis['npts'], dis['width'], dis['nsigmas'],
-                    self.params[par.name], par.limits, par.relative_pd)
-            return value, weight / np.sum(weight)
-        else:
-            return [self.params[par.name]], [1.0]
+                    value, par.limits, par.relative_pd)
+            return value, dispersity, weight
+        else:
+            value = self.params[par.name]
+            return value, [value if par.relative_pd else 0.0], [1.0]
 
 def test_cylinder():