From 541006041bf2e213a7c273ec3212438df010dd50 Mon Sep 17 00:00:00 2001
From: Atharv Nagavarapu <30nagava@elmbrookstudents.org>
Date: Fri, 19 Dec 2025 22:40:48 +0000
Subject: [PATCH] Delete diagnostics/BatteryDiagnostics.py

---
 diagnostics/BatteryDiagnostics.py | 49 -------------------------------
 1 file changed, 49 deletions(-)
 delete mode 100644 diagnostics/BatteryDiagnostics.py

diff --git a/diagnostics/BatteryDiagnostics.py b/diagnostics/BatteryDiagnostics.py
deleted file mode 100644
index 682793f..0000000
--- a/diagnostics/BatteryDiagnostics.py
+++ /dev/null
@@ -1,49 +0,0 @@
-from pybricks.tools import wait
-import umath
-class BatteryDiagnostics:
-    def __init__(self, hub):
-        self.voltage = 0
-        self.current = 0
-        self.hub = hub
-    def printVoltage(self):
-        self.voltage = self.hub.battery.voltage()
-        if self.voltage > 7800:
-            print(f"Battery voltage is sufficient: {self.voltage}")
-        elif self.voltage < 7800 :
-            print(f"Charging needed: {self.voltage}")
-    def printCurrent(self):
-        self.current = self.hub.battery.current()
-        print("Battery current:", self.current)
-    def printAll(self):
-        timeelapsed = 0
-        voltageList = []
-        currentList = []
-        while True:
-            print("\n\n\n\n\n")
-            self.printVoltage()
-            voltageList.append(self.voltage)
-            self.printCurrent()
-            currentList.append(self.current)
-            wait(50)
-            timeelapsed += 50
-            
-            if(timeelapsed >= 3000):
-                break
-        print("--------------FINAL RESULTS OF BATTERY DIAGNOSTICS---------------")
-        print("Voltage deviation:", self.stdev(voltageList))
-        print("Current deviation:", self.stdev(currentList))
-    def stdev(self, vals):
-        DATA = vals
-        if len(DATA) < 2:
-            return 0
-        # Calculate the mean
-        MEAN = sum(DATA) / len(DATA)
-
-        # Calculate the variance (sum of squared differences from the mean, divided by n-1 for sample standard deviation)
-        VARIANCE = sum([(x - MEAN) ** 2 for x in DATA]) / float(len(DATA) - 1)
-        
-        # Calculate the standard deviation (square root of the variance)
-        STD_DEV_MANUAL = umath.sqrt(VARIANCE)
-        
-
-        return (STD_DEV_MANUAL)
\ No newline at end of file