Updated test_engine to use JSON inputs

rules-engine/src/rules_engine/engine.py

@@ -124,8 +124,7 @@ def get_outputs_normalized(
         maximum_heat_load=maximum_heat_load,
     )
 
-    # TODO: fill out balance point graph
-    balance_point_graph = BalancePointGraph(records=[])
+    balance_point_graph = home.balance_point_graph
     return (summary_output, balance_point_graph)
 
 
@@ -314,9 +313,9 @@ def _initialize_billing_periods(self, billing_periods: List[BillingPeriod]) -> N
             if billing_period.analysis_type == AnalysisType.INCLUDE:
                 self.bills_winter.append(billing_period)
             elif billing_period.analysis_type == AnalysisType.DO_NOT_INCLUDE:
-                self.bills_summer.append(billing_period)
-            else:
                 self.bills_shoulder.append(billing_period)
+            else:
+                self.bills_summer.append(billing_period)
 
         self._calculate_avg_summer_usage()
         self._calculate_avg_non_heating_usage()
@@ -374,9 +373,23 @@ def _calculate_balance_point_and_ua(
         the home, removing UA outliers based on a normalized standard
         deviation threshold.
         """
-        self.uas = [bp.ua for bp in self.bills_winter]
+
+        self.balance_point_graph = BalancePointGraph(records=[])
+
+        self.uas = [billing_period.ua for billing_period in self.bills_winter]
         self.avg_ua = sts.mean(self.uas)
         self.stdev_pct = sts.pstdev(self.uas) / self.avg_ua
+
+        balance_point_graph_row = BalancePointGraphRow(
+            balance_point=self.balance_point,
+            heat_loss_rate=self.avg_ua,
+            change_in_heat_loss_rate=0,
+            percent_change_in_heat_loss_rate=0,
+            standard_deviation=self.stdev_pct,
+        )
+
+        self.balance_point_graph.records.append(balance_point_graph_row)
+
         self._refine_balance_point(initial_balance_point_sensitivity)
 
         while self.stdev_pct > stdev_pct_max:
@@ -386,7 +399,7 @@ def _calculate_balance_point_and_ua(
             outlier = self.bills_winter.pop(
                 biggest_outlier_idx
             )  # removes the biggest outlier
-            uas_i = [bp.ua for bp in self.bills_winter]
+            uas_i = [billing_period.ua for billing_period in self.bills_winter]
             avg_ua_i = sts.mean(uas_i)
             stdev_pct_i = sts.pstdev(uas_i) / avg_ua_i
             if (
@@ -433,12 +446,26 @@ def _refine_balance_point(self, balance_point_sensitivity: float) -> None:
                 # TODO: For balance point graph, store the old balance
                 # point in a list to keep track of all intermediate balance
                 # point temperatures?
+
+                change_in_heat_loss_rate = avg_ua_i - self.avg_ua
+                percent_change_in_heat_loss_rate = (
+                    100 * change_in_heat_loss_rate / avg_ua_i
+                )
                 self.balance_point, self.avg_ua, self.stdev_pct = (
                     bp_i,
                     avg_ua_i,
                     stdev_pct_i,
                 )
 
+                balance_point_graph_row = BalancePointGraphRow(
+                    balance_point=self.balance_point,
+                    heat_loss_rate=self.avg_ua,
+                    change_in_heat_loss_rate=change_in_heat_loss_rate,
+                    percent_change_in_heat_loss_rate=percent_change_in_heat_loss_rate,
+                    standard_deviation=self.stdev_pct,
+                )
+                self.balance_point_graph.records.append(balance_point_graph_row)
+
                 for n, bill in enumerate(self.bills_winter):
                     bill.total_hdd = period_hdds_i[n]
                     bill.ua = uas_i[n]
@@ -483,10 +510,12 @@ def calculate_partial_ua(self, billing_period: BillingPeriod) -> float:
         """
         return (
             billing_period.days
-            * billing_period.avg_heating_usage
-            * self.fuel_type.value
-            * self.heat_sys_efficiency
+            * billing_period.avg_heating_usage  # gallons or therms
+            * self.fuel_type.value  # therm or gallon to BTU
+            * self.heat_sys_efficiency  # unitless
             / 24
+            # days * gallons/day * (BTU/gallon)/1 day (24 hours)
+            # BTUs/hour
         )
 
 

rules-engine/src/rules_engine/pydantic_models.py

@@ -113,8 +113,10 @@ class SummaryOutput(BaseModel):
     design_temperature: float = Field(description="Summary!B26")
     whole_home_heat_loss_rate: float = Field(
         description="Summary!B27"
-    )  # UA = heat loss rate
-    standard_deviation_of_heat_loss_rate: float = Field(description="Summary!B28")
+    )  # Whole Home UA. UA = heat loss rate
+    standard_deviation_of_heat_loss_rate: float = Field(
+        description="Summary!B28"
+    )  # Standard deviation of UA
     average_heat_load: float = Field(description="Summary!B29")
     maximum_heat_load: float = Field(description="Summary!B30")
 
@@ -123,10 +125,12 @@ class BalancePointGraphRow(BaseModel):
     """From Summary page"""
 
     balance_point: float = Field(description="Summary!G33:35")  # degree F
-    heat_loss_rate: float = Field(description="Summary!H33:35")  # BTU / (hr-deg. F)
+    heat_loss_rate: float = Field(
+        description="Summary!H33:35"
+    )  # BTU / (hr-deg. F) (UA)
     change_in_heat_loss_rate: float = Field(
         description="Summary!I33:35"
-    )  # BTU / (hr-deg. F)
+    )  # BTU / (hr-deg. F) (change in UA)
     percent_change_in_heat_loss_rate: float = Field(description="Summary!J33:35")
     standard_deviation: float = Field(description="Summary!K33:35")