target variance for each solver run. authored by Yosh

app/models/form.py

@@ -1,13 +1,15 @@
 from pydantic import BaseModel
-from typing import List
+from typing import List, TypeVar, Type
 
 from helpers import irt_helper
 
+from models.solver_run import SolverRun
 from models.item import Item
 from models.target import Target
 
 from lib.irt.test_response_function import TestResponseFunction
 
+_T = TypeVar("_T")
 
 class Form(BaseModel):
     items: List[Item]
@@ -15,13 +17,15 @@ class Form(BaseModel):
     tif_results: List[Target]
     tcc_results: List[Target]
     status: str = 'Not Optimized'
+    solver_variables: List[str]
 
     @classmethod
-    def create(cls, items, solver_run, status):
+    def create(cls: Type[_T], items: list, solver_run: SolverRun, status: str, solver_variables: list) -> _T:
         return cls(
             items=items,
             cut_score=TestResponseFunction(solver_run.irt_model).calculate(
                 items, theta=solver_run.theta_cut_score),
             tif_results=irt_helper.generate_tif_results(items, solver_run),
             tcc_results=irt_helper.generate_tcc_results(items, solver_run),
-            status=status)
+            status=status,
+            solver_variables=solver_variables)

app/models/objective_function.py

@@ -10,6 +10,7 @@ class ObjectiveFunction(BaseModel):
     # likely with models representing each objective function type
     tif_targets: List[Target]
     tcc_targets: List[Target]
+    target_variance_percentage: int = 10
     objective: AnyStr = "minimize"
     weight: Dict = {'tif': 1, 'tcc': 1}