completed todo list and unit test updated

mbs_results/utilities/constrains.py

@@ -141,18 +141,11 @@ def constrain(
         Original dataframe with constrains.
     """
 
-    # TODO: Concat of derived and constains df needs to moved up prior to constains
-    # Currently we are not constaining any derived questions ... Move and refactor
-    #
-    # elif statement changed to if (might already be done on main branch - merge main)
-    # Add a pre-derived column and a post-derived-pre-constain column (again half done
-    # on main )
-    # Make unit tests pass and then work on validation function
-
     derive_map = create_derive_map(df, spp_form_id)
 
-    df["unadjusted_target"] = df[target]
+    df[f"pre_derived_{target}"] = df[target]
 
+
     # pre_derive_df has dimenesions as index, columns the values to be used when derived
     # Hard coded columns are from finalsel files,
     pre_derive_df = df.set_index(
@@ -178,29 +171,25 @@ def constrain(
             for form_type, derives in derive_map.items()
         ]
     )
-    unique_q_numbers = df[question_no].unique()
-    df.set_index([question_no, period, reference], inplace=True)
+
+    pre_constrained = pd.concat([df, derived_values])
+    pre_constrained[f"pre_constrained_{target}"] = pre_constrained[target]
 
-    pre_con_col_name = f"pre_con_{target}"
-    pre_con_vari = {}
+    unique_q_numbers = pre_constrained[question_no].unique()
+    pre_constrained.set_index([question_no, period, reference], inplace=True)
+
 
     if 49 in unique_q_numbers:
-        if unique_q_numbers > 40:
-            pre_con_vari[pre_con_col_name] = target.copy()
-        replace_values_index_based(df, target, 49, ">", 40)
-<<<<<<< HEAD
+        replace_values_index_based(pre_constrained, target, 49, ">", 40)
 
-    elif 90 in unique_q_numbers:
-=======
     if 90 in unique_q_numbers:
->>>>>>> 32e5aca974763866c27b30694bad38415f68e093
-        replace_values_index_based(df, target, 90, ">=", 40)
+        replace_values_index_based(pre_constrained, target, 90, ">=", 40)
 
-    df.reset_index(inplace=True)
 
-    final_constrained = pd.concat([df, derived_values, pre_con_vari])
+    post_constrained = pre_constrained.copy().reset_index()
 
-    return final_constrained
+
+    return post_constrained
 
 
 def derive_questions(

tests/data/utilities/constrains/test_constrain.csv

@@ -1,4 +1,4 @@
-period,reference,spp_form_id,question_no,target,unadjusted_target,expected_target,constrain_marker
+period,reference,spp_form_id,question_no,target,pre_derived_target,expected_target,constrain_marker
 202001,100,15,40,99,99,99,
 202001,100,15,49,100,100,99,49 > 40
 202001,100,15,90,100,100,99,90 >= 40

tests/utilities/test_constrains.py

@@ -81,16 +81,16 @@ def test_constrain_functionality(filepath):
             df[(df["question_no"] == 40) & (df["spp_form_id"].isin([13, 14]))].index
         )
         .drop(df[(df["question_no"] == 46) & (df["spp_form_id"].isin([15]))].index)
-        .drop(columns=["unadjusted_target"])
+        .drop(columns=["pre_derived_target"])
     )
 
     df_expected_output = df.drop(
         columns=["cell_no", "frotover", "froempment", "frosic2007", "target"]
     ).rename(columns={"expected_target": "target"})
     df_expected_output["target"] = df_expected_output["target"].astype(float)
 
-    df_expected_output["unadjusted_target"] = df_expected_output[
-        "unadjusted_target"
+    df_expected_output["pre_derived_target"] = df_expected_output[
+        "pre_derived_target"
     ].fillna("filled_na")
 
     df_output = constrain(
@@ -109,20 +109,20 @@ def test_constrain_functionality(filepath):
         "spp_form_id",
         "question_no",
         "target",
-        "unadjusted_target",
+        "pre_derived_target",
         "constrain_marker",
     ]
 
     df_output.drop(
         columns=["cell_no", "frotover", "froempment", "frosic2007"], inplace=True
     )
     df_output = df_output[order].sort_values(by=order).reset_index(drop=True)
-    df_output["unadjusted_target"] = df_output["unadjusted_target"].fillna("filled_na")
+    df_output["pre_derived_target"] = df_output["pre_derived_target"].fillna("filled_na")
 
     df_expected_output = (
         df_expected_output[order].sort_values(by=order).reset_index(drop=True)
     )
-
+    df_expected_output['spp_form_id'] = df_expected_output['spp_form_id'].astype('int64')
     assert_frame_equal(df_output, df_expected_output)