implemented gbis for the moment

backend/Funding.py

@@ -66,9 +66,7 @@ class Funding:
 
         self.recommendations = property_recommendations
 
-        self.measure_types = []
-        for recs in self.recommendations:
-            self.measure_types.extend([r["measure_type"] for r in recs])
+        self.measure_types = list({r["measure_type"] for r in property_recommendations if r["default"]})
 
         # Load in the eco4 project scores matrix
         # Filter the matrix on scores relevant to this property
@@ -129,12 +127,12 @@ class Funding:
         :return:
         """
         measure_table = pd.DataFrame([
-            m[0] for m in self.recommendations if m[0]["measure_type"] in measures
+            m for m in self.recommendations if m in measures and m["default"]
         ])
 
         measure_table["post_install_sap"] = measure_table["sap_points"] + self.starting_sap
         # We classify the movement
-        measure_table["Finishing Band"] = measure_table["sap_points"].apply(
+        measure_table["Finishing Band"] = np.floor(measure_table["post_install_sap"]).apply(
             lambda points: self.sap_to_eco_band(points)
         )
         # Remove any measures that generate zero SAP movement
@@ -223,7 +221,7 @@ class Funding:
         # General Eligibility
         if (
             (self.starting_epc in ["G", "D", "E", "F"]) and
-            len(
+            any(
                 [measure in valid_measures for measure in self.measure_types
                  if measure not in ["cavity_wall_insulation", "loft_insulation"]]
             ) and
@@ -246,7 +244,7 @@ class Funding:
         # Low income/flex
         if (
             (self.starting_sap in ["G", "D", "E", "F"]) and
-            len([measure in valid_measures for measure in self.measure_types])
+            any([measure in valid_measures for measure in self.measure_types])
         ):
             # Find the best measure, and can also include CWI/LI but requires the tenant to be
             # low inome or on benefits
@@ -293,5 +291,5 @@ class Funding:
         """
 
         self.gbis()
-        self.eco4()
-        self.whlg()
+        # self.eco4()
+        # self.whlg()

backend/app/plan/router.py

@@ -380,6 +380,7 @@ def get_eco_project_scores_matrix():
     )
     df = pd.DataFrame(data)
     df.columns = ['Floor Area Segment', 'Starting Band', 'Finishing Band', 'Cost Savings']
+    df["Cost Savings"] = df["Cost Savings"].astype(float)
     return df