Function compile error now raised when the return type of ObjectiveCo…

…nstraint's exec is not a float

pymead/gui/gui_settings/defaults/genetic_algorithm_settings.json

@@ -12,7 +12,7 @@
         "label": "Objective Functions:",
         "widget_type": "QLineEdit",
         "setText": "$Cd",
-        "setToolTip": "Enter the objective functions to be minimized, separated by commas.\nVariables can be started with the dollar sign ($)."
+        "setToolTip": "Enter the objective functions to be minimized, separated by commas.\nVariables can be started with the dollar sign ($).\nNote: if multi-point optimization is active, each variable\nmust be indexed to ensure the return type is a float rather\nthat a list. For example, $Cd[0] must be used rather than\n$Cd if multi-point optimization is active. Here, $Cd[0]\ncorresponds to the drag coefficient of the airfoil (system) evaluated\nusing the first multi-point stencil point values."
     },
     "G": {
         "label": "Constraints:",

pymead/optimization/objectives_and_constraints.py

@@ -78,6 +78,10 @@ def update_function(self):
             if execute:
                 try:
                     exec(self.func, self.function_dict)
+                    return_val = self.function_dict["f"]()
+                    if not isinstance(return_val, float):
+                        raise FunctionCompileError(f"Error in function compilation output type. Required type is float,"
+                                                   f"found type {type(return_val)}")
                 except (SyntaxError, NameError, TypeError):
                     raise FunctionCompileError('Error in function compilation')
 
@@ -114,7 +118,6 @@ def parse_update_function_str(self):
         a ``Param`` name. For example, the string ``"A0.Base.R_le"`` corresponds to the leading edge radius of the base
         parameter set of airfoil ``"A0"``.
         """
-        # TODO: throw an error if an objective function is setup without indexing despite multipoint being active
         self.tag_matrix = []
         self.func = 'def f(): return '
         math_functions_to_include = []