Merge branch 'Fairbotics' of https://github.com/Team-Optix-3749/Team-…

…3749-2024 into Fairbotics

.github/workflows/main.yml

@@ -0,0 +1,29 @@
+name: CI
+
+on:
+  push:
+    branches: [ main ]
+  pull_request:
+    branches: [ main ]
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    container: wpilib/roborio-cross-ubuntu:2024-22.04
+
+    steps:
+    - uses: actions/checkout@v4
+
+    # prevents Dubious Ownership err
+    - name: Add repository to git safe directories
+      run: git config --global --add safe.directory $GITHUB_WORKSPACE
+
+    # Grant execute permission for gradlew
+    - name: Grant execute permission for gradlew
+      run: chmod +777 ./gradlew
+      working-directory: ./Team-3749-2024
+
+    # Runs a single command using the runners shell
+    - name: Compile and run tests on robot code
+      run: ./gradlew build
+      working-directory: ./Team-3749-2024

Team-3749-2024/src/main/java/frc/robot/subsystems/arm/ArmConstants.java

@@ -108,6 +108,7 @@ public enum ArmStates {
                                                            // parameter
 
         // Field Parameters
+
         public static final double speakerHeight = Units.inchesToMeters(78.35);; // likely thing you'll need to tune
         public static final double minDistance = 0.9; // / NOTE: Not percise, please check
 

Team-3749-2024/wristRegressoin.py

@@ -12,10 +12,6 @@
 x2 = data["Arm Position Deg"].values/180.0 * math.pi
 y = data["Gravity Voltage"].values
 
-
-# if (x1.size != x2.size or x2.size!= y.size):c1
-#     throw Exception
-
 # Create design matrix
 X = np.column_stack((np.ones(x1.size),
                      x1,
@@ -40,7 +36,6 @@
 x1_str = 'x'
 x2_str = 'y'
 
-
 # Construct the equation string
 print(coefficients)
 
@@ -57,28 +52,11 @@
 equation += f'{coefficients[10]} * {x1_str+"^2"+x2_str+"^2"} '
 equation += f'{coefficients[11]} * {x1_str+"^3"+x2_str+"^2"} '
 
-
-# def predict(x1,x2):
-#     return coefficients[0] + coefficients[1] * x1 + coefficients[2] * x1**2 + coefficients[3] * x1**3 + coefficients[4] * x2**1 + coefficients[5] * x2**2
 rmse = mean_squared_error(y, predicted_y, squared=False)
 
 # Print or use the equation string
 print("Equation of the fitted quadratic regression model:")
 print(equation)
-# print(predicted_y)
-# print("Predicition: 15, 0")
-# print("0 " + str(predict(0,0)))
-# print(predict(15,0))
-# print(predict(30,0))
-# print("45 " + str(predict(45,0)))
-# print(predict(60,0))
-# print(predict(75,0))
-# print("90 "+ str(predict(90,0)))
-# print(predict(105,0))
-# print(predict(120,0))
-# print("135 " + str(predict(135,0)))
-# print(predict(150,0))
-
 
 print("R Squared")
 print(results.rsquared)