Changeset 14fbdba in sasview

Timestamp:

Aug 30, 2017 10:32:35 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, magnetic_scatt, release-4.2.2, ticket-1009, ticket-1094-headless, ticket-1242-2d-resolution, ticket-1243, ticket-1249, ticket885, unittest-saveload

Children:

f1495ff

Parents:

9f703d0

Message:

Ensure sum/multiplication models behave correctly

File:

• src/sas/sasgui/perspectives/calculator/model_editor.py (modified) (11 diffs)

src/sas/sasgui/perspectives/calculator/model_editor.py

@@ -106 +106 @@
         self.model2_string = "cylinder"
         self.name = 'Sum' + M_NAME
-        self.factor = 'scale_factor'
         self._notes = ''
         self._operator = '+'
@@ -133 +132 @@
         self.model2_name = str(self.model2.GetValue())
         self.good_name = True
-        self.fill_oprator_combox()
+        self.fill_operator_combox()
 
     def _layout_name(self):
@@ -491 +490 @@
         a sum or multiply model then create the appropriate string
         """
-
         name = ''
-
         if operator == '*':
             name = 'Multi'
             factor = 'background'
-            f_oper = '+'
         else:
             name = 'Sum'
             factor = 'scale_factor'
-            f_oper = '*'
-
-        self.factor = factor
+
         self._operator = operator
-        self.explanation = "  Plugin Model = %s %s (model1 %s model2)\n" % \
-                           (self.factor, f_oper, self._operator)
+        self.explanation = ("  Plugin_model = scale_factor * (model_1 {} "
+            "model_2) + background").format(operator)
         self.explanationctr.SetLabel(self.explanation)
         self.name = name + M_NAME
 
 
-    def fill_oprator_combox(self):
+    def fill_operator_combox(self):
         """
         fill the current combobox with the operator
@@ -536 +530 @@
             description = name1 + self._operator + name2
         operator_text = self._operator_choice.GetValue()
-        if '+' in operator_text:
-            factor = 'scale_factor'
-            f_oper = '*'
-            default_val = '1.0'
-        else:
-            factor = 'background'
-            f_oper = '+'
-            default_val = '0.0'
+        f_oper = '*' if '+' in operator_text else '+'
         path = self.fname
-        try:
-            out_f = open(path, 'w')
-        except:
-            raise
         output = SUM_TEMPLATE.format(model1=name1, model2=name2, 
-            scale_factor_default=default_val, factor_operator=f_oper,
-            operator=self._operator, description=description)
-        output = output.replace("scale_factor", factor)
-        out_f.write(output + "\n")
-        out_f.close()
+            scale_factor_default=1.0, background_default=0.001,
+            factor_operator=f_oper, operator=self._operator,
+            description=description)
+        if self._operator == '*':
+            # Multiplication models only have 1 overall scale factor. Don't use
+            # sub-models' individual scales as fitting params
+            output = output.replace("if name == 'background'", 
+                "if name == 'background' or name == 'scale'")
+        with open(self.fname, 'w') as out_f:
+            out_f.write(output + "\n")
 
     def compile_file(self, path):
@@ -1280 +1268 @@
         ## New parameter:scaling_factor
         self.params['scale_factor'] = {scale_factor_default}
+        # Set each model's background to 0, and define our own background param
+        if 'background' in self.p_model1.params:
+            self.p_model1.setParam('background', 0.0)
+        if 'background' in self.p_model2.params:
+            self.p_model2.setParam('background', 0.0)
+        self.params['background'] = {background_default}
 
         ## Parameter details [units, min, max]
         self._set_details()
         self.details['scale_factor'] = ['', 0.0, numpy.inf]
-
+        self.details['background'] = ['1/cm', 0.0, numpy.inf]
 
         #list of parameter that can be fitted
@@ -1385 +1379 @@
     def _set_params(self):
         for name , value in self.p_model1.params.iteritems():
-            # No 2D-supported
-            #if name not in self.p_model1.orientation_params:
+            # Don't use the model's background param - we've defined our own
+            if name == 'background':
+                continue
             new_name = "p1_" + name
-            self.params[new_name]= value
+            self.params[new_name] = value
 
         for name , value in self.p_model2.params.iteritems():
-            # No 2D-supported
-            #if name not in self.p_model2.orientation_params:
+            # Don't use the model's background param - we've defined our own
+            if name == 'background':
+                continue
             new_name = "p2_" + name
-            self.params[new_name]= value
+            self.params[new_name] = value
 
         # Set "scale" as initializing
@@ -1402 +1398 @@
     def _set_details(self):
         for name ,detail in self.p_model1.details.iteritems():
+            if name == 'background':
+                continue
             new_name = "p1_" + name
             #if new_name not in self.orientation_params:
@@ -1407 +1405 @@
 
         for name ,detail in self.p_model2.details.iteritems():
+            if name == 'background':
+                continue
             new_name = "p2_" + name
             #if new_name not in self.orientation_params:
@@ -1432 +1432 @@
              if new_name in self.p_model2.getParamList():
                 self.p_model2.setParam(new_name, value)
-        elif name == 'scale_factor':
-            self.params['scale_factor'] = value
+        elif name == 'scale_factor' or name == 'background':
+            self.params[name] = value
         else:
             raise ValueError, "Model does not contain parameter %s" % name
@@ -1490 +1490 @@
         self._set_scale_factor()
         return self.params['scale_factor'] {factor_operator} \
-(self.p_model1.run(x) {operator} self.p_model2.run(x))
+(self.p_model1.run(x) {operator} self.p_model2.run(x)) + self.params['background']
 
     def runXY(self, x = 0.0):
         self._set_scale_factor()
         return self.params['scale_factor'] {factor_operator} \
-(self.p_model1.runXY(x) {operator} self.p_model2.runXY(x))
+(self.p_model1.runXY(x) {operator} self.p_model2.runXY(x)) + self.params['background']
 
     ## Now (May27,10) directly uses the model eval function
@@ -1503 +1503 @@
         return self.params['scale_factor'] {factor_operator} \
 (self.p_model1.evalDistribution(x) {operator} \
-self.p_model2.evalDistribution(x))
+self.p_model2.evalDistribution(x)) + self.params['background']
 
     def set_dispersion(self, parameter, dispersion):