From ebe5439f0267c0927e4c417408b2f08364bf0db1 Mon Sep 17 00:00:00 2001
From: Peter Yefi <peteryefi@gmail.com>
Date: Wed, 10 Nov 2021 10:17:01 +0000
Subject: [PATCH] Fixed issue with coefficient computation

---
 imports/energy_systems/xlsx_heat_pump_parameters.py | 13 +++++++++----
 imports/energy_systems_factory.py                   |  2 +-
 2 files changed, 10 insertions(+), 5 deletions(-)

diff --git a/imports/energy_systems/xlsx_heat_pump_parameters.py b/imports/energy_systems/xlsx_heat_pump_parameters.py
index 5e6269d0..b1b96e70 100644
--- a/imports/energy_systems/xlsx_heat_pump_parameters.py
+++ b/imports/energy_systems/xlsx_heat_pump_parameters.py
@@ -86,7 +86,7 @@ class XlsxHeatPumpParameters:
       self._city.add_city_object(energy_system)
     return self._city
 
-  def _extract_heat_pump_data(self, heat_pump_capacity_data) -> [List, List]:
+  def _extract_heat_pump_data(self, heat_pump_capacity_data: Dict) -> [List, List]:
     """
     Fetches a list of metric based data for heat pump for various temperature,
     eg. cooling capacity data for 12 capacity heat pump
@@ -102,7 +102,7 @@ class XlsxHeatPumpParameters:
       compressor_power_data.append(metric_data[1])
     return [cooling_heating_capacity_data, compressor_power_data]
 
-  def _compute_coefficients(self, heat_pump_data, data_type="heat") -> List[float]:
+  def _compute_coefficients(self, heat_pump_data: List, data_type="heat") -> List[float]:
     """
     Compute heat output and electrical demand coefficients
     from heating and cooling performance data
@@ -111,10 +111,15 @@ class XlsxHeatPumpParameters:
     or heating performance data
     :return: Tuple[Dict, Dict]
     """
-    out_temp = [25, 30, 32, 35, 40, 45] * 6
+    # Determine the recurrence of temperature values. 6 repetitions for
+    # cooling performance and 5 repetition for heating performance
+    temp_multiplier = 5 if data_type == "heat" else 6
+    out_temp = [25, 30, 32, 35, 40, 45] * temp_multiplier
+
     heat_x_values = np.repeat([-5, 0, 7, 10, 15], 6)
     cool_x_values = np.repeat([6, 7, 8, 9, 10, 11], 6)
     x_values = heat_x_values if data_type == "heat" else cool_x_values
+    x_values = x_values.tolist()
     # convert list of lists to one list
     heat_pump_data = list(itertools.chain.from_iterable(heat_pump_data))
 
@@ -122,7 +127,7 @@ class XlsxHeatPumpParameters:
     popt, _ = curve_fit(self._objective_function, [x_values, out_temp], heat_pump_data)
     return popt.tolist()
 
-  def _objective_function(self, xdata, a1, a2, a3, a4, a5, a6) -> float:
+  def _objective_function(self, xdata: List, a1: float, a2: float, a3: float, a4: float, a5: float, a6: float) -> float:
     """
     Objective function for computing coefficients
     :param xdata:
diff --git a/imports/energy_systems_factory.py b/imports/energy_systems_factory.py
index 964353e7..18d65e86 100644
--- a/imports/energy_systems_factory.py
+++ b/imports/energy_systems_factory.py
@@ -19,7 +19,7 @@ class EnergySystemsFactory:
     self._city = city
     self._base_path = base_path
 
-  def _xlsx_heat_pump(self):
+  def _xlsx_heat_pump_parameters(self):
     """
     Enrich the city by using xlsx heat pump information
     """