Scipy dependency removed

odya · Aug 25, 2024 · 46f2191 · 46f2191
1 parent 4875f15
commit 46f2191
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Showing 2 changed files with 13 additions and 19 deletions.
diff --git a/custom_components/ina219_ups_hat/manifest.json b/custom_components/ina219_ups_hat/manifest.json
@@ -7,6 +7,6 @@
   "integration_type": "device",
   "iot_class": "local_polling",
   "issue_tracker": "https://github.com/odya/hass-ina219-ups-hat/issues",
-  "requirements": ["smbus2>=0.4.2","numpy>=1.21.4","pandas","scipy"],
+  "requirements": ["smbus2>=0.4.2","numpy","pandas"],
   "version": "0.3.11"
 }
diff --git a/custom_components/ina219_ups_hat/soc/provider.py b/custom_components/ina219_ups_hat/soc/provider.py
@@ -1,6 +1,6 @@
 import numpy as np
 import pandas as pd
-from scipy.interpolate import interp1d
+
 from homeassistant import core
 
 
@@ -16,12 +16,8 @@ def __init__(self, hass: core.HomeAssistant, ocv_map) -> None:
         )
 
         # Create the cubic interpolation function
-        cubic_interp_func = interp1d(
-            soc_voltage_df["SOC"],
-            soc_voltage_df["Voltage"],
-            kind="cubic",
-            fill_value="extrapolate",
-        )
+        coefficients = np.polyfit(soc_voltage_df["SOC"], soc_voltage_df["Voltage"], 3)
+        cubic_interp_func = np.poly1d(coefficients)
         # Precalculate detailed SOC-Voltage data
         detailed_soc = np.linspace(0, 100, 100)
         detailed_voltage = cubic_interp_func(detailed_soc)
@@ -30,20 +26,18 @@ def __init__(self, hass: core.HomeAssistant, ocv_map) -> None:
             {"SOC": detailed_soc, "Voltage": detailed_voltage}
         )
 
-        # Interpolation function
-        self._linear_interp_func = interp1d(
-            self._detailed_soc_voltage_df["Voltage"],
-            self._detailed_soc_voltage_df["SOC"],
-            kind="linear",
-            fill_value="extrapolate",
-        )
-
     def get_soc_from_voltage(self, cell_voltage: float) -> float:
         # Ensure the voltage is within the measurable range
-        if cell_voltage > self._detailed_soc_voltage_df["Voltage"].max():
+        if cell_voltage >= self._detailed_soc_voltage_df["Voltage"].max():
             return 100
-        if cell_voltage < self._detailed_soc_voltage_df["Voltage"].min():
+        if cell_voltage <= self._detailed_soc_voltage_df["Voltage"].min():
             return 0
 
         # Interpolate the SOC based on the voltage
-        return float(self._linear_interp_func(cell_voltage))
+        return float(
+            np.interp(
+                cell_voltage,
+                self._detailed_soc_voltage_df["Voltage"],
+                self._detailed_soc_voltage_df["SOC"],
+            )
+        )