FiringSolutionSolver.java

.gitignore

@@ -184,4 +184,32 @@ ctre_sim/
 compile_commands.json
 
 # Version file
-src/main/java/frc/robot/generic/BuildConstants.java
+src/main/java/frc/robot/generic/BuildConstants.java
+
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+env/
+venv/
+ENV/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# Tuner logs
+tuner_logs/

bayesopt/config/COEFFICIENT_TUNING.py

@@ -0,0 +1,201 @@
+"""
+COEFFICIENT TUNING CONFIGURATION
+=================================
+This file controls WHAT gets tuned, HOW MUCH it can change, and IN WHAT ORDER.
+Edit this file to customize the optimization behavior.
+
+NO CODE CHANGES NEEDED - just modify the values below.
+"""
+
+# ============================================================
+# TUNING ORDER - What gets optimized and in what sequence
+# ============================================================
+# The optimizer tunes ONE coefficient at a time in this order.
+# Put most impactful coefficients first for fastest improvement.
+# Comment out (add # at start) any coefficient you DON'T want to tune.
+
+TUNING_ORDER = [
+    "kDragCoefficient",          # Air resistance (MOST IMPACT - tune this first!)
+    "kVelocityIterationCount",   # Solver accuracy vs CPU load
+    "kAngleIterationCount",      # Solver accuracy vs CPU load
+    "kVelocityTolerance",        # How precise velocity calculation needs to be
+    "kAngleTolerance",           # How precise angle calculation needs to be
+    "kLaunchHeight",             # Physical measurement (tune last - rarely changes)
+    # "kAirDensity",             # Commented out - air density is constant (1.225)
+]
+
+# ============================================================
+# COEFFICIENT DEFINITIONS
+# ============================================================
+# For each coefficient, you can control:
+#   - enabled: True = tune this, False = skip it
+#   - default_value: Starting value
+#   - min_value: Lowest allowed value (SAFETY LIMIT)
+#   - max_value: Highest allowed value (SAFETY LIMIT)
+#   - initial_step_size: How big the first changes are
+#   - step_decay_rate: How quickly to reduce step size (0.9 = shrink 10% per iteration)
+#   - is_integer: True = round to whole numbers, False = allow decimals
+#   - nt_key: NetworkTables path (don't change unless robot code changes)
+
+# TODO: Update tuning parameters before testing on robot
+
+COEFFICIENTS = {
+    "kDragCoefficient": {
+        "enabled": True,               # ← CHANGE THIS to enable/disable tuning
+        "default_value": 0.003,        # Starting guess
+        "min_value": 0.001,            # ← SAFETY: Can't go below this
+        "max_value": 0.006,            # ← SAFETY: Can't go above this
+        "initial_step_size": 0.001,    # ← HOW MUCH: Start with big changes
+        "step_decay_rate": 0.9,        # Gradually make smaller changes
+        "is_integer": False,           # Allow decimals like 0.0035
+        "nt_key": "/Tuning/FiringSolver/DragCoefficient",
+        "description": "Air resistance coefficient - affects trajectory curvature"
+    },
+
+    "kAirDensity": {
+        "enabled": False,              # ← DISABLED: Air density is constant in FiringSolutionSolver
+        "default_value": 1.225,
+        "min_value": 1.10,
+        "max_value": 1.30,
+        "initial_step_size": 0.05,
+        "step_decay_rate": 0.9,
+        "is_integer": False,
+        "nt_key": "/Tuning/FiringSolver/AirDensity",
+        "description": "Air density (kg/m³) - typically constant at 1.225"
+    },
+
+    "kVelocityIterationCount": {
+        "enabled": True,               # ← CHANGE THIS to enable/disable tuning
+        "default_value": 20,
+        "min_value": 10,
+        "max_value": 30,               # ← REDUCED from 50 to prevent RoboRIO CPU overload
+        "initial_step_size": 5,        # ← HOW MUCH: Try steps of 5 iterations
+        "step_decay_rate": 0.85,
+        "is_integer": True,            # Must be whole number (10, 11, 12, not 10.5)
+        "nt_key": "/Tuning/FiringSolver/VelocityIterations",
+        "description": "Solver iterations for velocity - more = accurate but slower"
+    },
+
+    "kAngleIterationCount": {
+        "enabled": True,               # ← CHANGE THIS to enable/disable tuning
+        "default_value": 20,
+        "min_value": 10,
+        "max_value": 30,               # ← REDUCED from 50 to prevent RoboRIO CPU overload
+        "initial_step_size": 5,        # ← HOW MUCH: Try steps of 5 iterations
+        "step_decay_rate": 0.85,
+        "is_integer": True,            # Must be whole number
+        "nt_key": "/Tuning/FiringSolver/AngleIterations",
+        "description": "Solver iterations for angle - more = accurate but slower"
+    },
+
+    "kVelocityTolerance": {
+        "enabled": True,               # ← CHANGE THIS to enable/disable tuning
+        "default_value": 0.01,
+        "min_value": 0.005,            # ← SAFETY: Too tight = solver struggles
+        "max_value": 0.05,             # ← SAFETY: Too loose = inaccurate
+        "initial_step_size": 0.005,    # ← HOW MUCH: Start with 0.005 m/s changes
+        "step_decay_rate": 0.9,
+        "is_integer": False,
+        "nt_key": "/Tuning/FiringSolver/VelocityTolerance",
+        "description": "Velocity convergence tolerance (m/s) - smaller = more precise"
+    },
+
+    "kAngleTolerance": {
+        "enabled": True,               # ← CHANGE THIS to enable/disable tuning
+        "default_value": 0.0001,
+        "min_value": 0.00001,          # ← SAFETY: Too tight = solver struggles
+        "max_value": 0.001,            # ← SAFETY: Too loose = inaccurate
+        "initial_step_size": 0.0001,   # ← HOW MUCH: Start with 0.0001 rad changes
+        "step_decay_rate": 0.9,
+        "is_integer": False,
+        "nt_key": "/Tuning/FiringSolver/AngleTolerance",
+        "description": "Angle convergence tolerance (rad) - smaller = more precise"
+    },
+
+    "kLaunchHeight": {
+        "enabled": True,               # ← CHANGE THIS to enable/disable tuning
+        "default_value": 0.8,
+        "min_value": 0.75,             # ← SAFETY: Physical robot constraint
+        "max_value": 0.85,             # ← SAFETY: Physical robot constraint
+        "initial_step_size": 0.02,     # ← HOW MUCH: Start with 2cm changes
+        "step_decay_rate": 0.9,
+        "is_integer": False,
+        "nt_key": "/Tuning/FiringSolver/LaunchHeight",
+        "description": "Launch height above ground (m) - physical measurement"
+    },
+}
+
+# ============================================================
+# OPTIMIZATION SETTINGS
+# ============================================================
+# How the Bayesian optimizer behaves
+
+# How many random points to try before starting intelligent optimization
+N_INITIAL_POINTS = 5  # More = better exploration, slower convergence
+
+# Maximum iterations per coefficient before moving to next one
+N_CALLS_PER_COEFFICIENT = 20  # More = more thorough, takes longer
+
+# ============================================================
+# ROBORIO PROTECTION SETTINGS
+# ============================================================
+# Prevent overloading the robot's onboard computer
+
+# Maximum coefficient updates per second (prevents NT spam)
+MAX_WRITE_RATE_HZ = 5.0  # SAFETY: Don't flood the RoboRIO with updates
+
+# Maximum shot data reads per second (prevents NT spam)
+MAX_READ_RATE_HZ = 20.0  # SAFETY: Don't overload NT with read requests
+
+# Batch multiple writes together (reduces NT traffic)
+BATCH_WRITES = True  # True = more efficient, False = immediate writes
+
+# ============================================================
+# PHYSICAL ROBOT LIMITS (SAFETY)
+# ============================================================
+# Hardcoded limits based on robot physical capabilities
+# Reject any shot data outside these bounds (likely sensor errors)
+
+PHYSICAL_MAX_VELOCITY_MPS = 30.0   # Maximum physically possible exit velocity
+PHYSICAL_MIN_VELOCITY_MPS = 5.0    # Minimum physically possible exit velocity
+PHYSICAL_MAX_ANGLE_RAD = 1.57      # ~90 degrees (straight up)
+PHYSICAL_MIN_ANGLE_RAD = 0.17      # ~10 degrees (very low angle)
+PHYSICAL_MAX_DISTANCE_M = 10.0     # Maximum field distance for shots
+PHYSICAL_MIN_DISTANCE_M = 1.0      # Minimum shot distance
+
+# ============================================================
+# HOW TO USE THIS FILE
+# ============================================================
+"""
+QUICK MODIFICATIONS:
+
+1. DISABLE A COEFFICIENT:
+   Set enabled = False in that coefficient's section
+
+2. CHANGE TUNING ORDER:
+   Rearrange or comment out items in TUNING_ORDER list
+
+3. ADJUST HOW MUCH IT CHANGES:
+   Modify initial_step_size (bigger = more aggressive)
+
+4. TIGHTEN SAFETY LIMITS:
+   Reduce the range between min_value and max_value
+
+5. PROTECT ROBORIO:
+   Lower MAX_WRITE_RATE_HZ or MAX_READ_RATE_HZ
+
+EXAMPLES:
+
+# Only tune drag coefficient:
+TUNING_ORDER = ["kDragCoefficient"]
+
+# Make drag tuning more aggressive:
+"initial_step_size": 0.002,  # Change from 0.001
+
+# Tighten drag safety range:
+"min_value": 0.002,  # Change from 0.001
+"max_value": 0.004,  # Change from 0.006
+
+# Reduce RoboRIO load:
+MAX_WRITE_RATE_HZ = 2.0  # Change from 5.0
+"""

bayesopt/config/TUNER_TOGGLES.ini

@@ -0,0 +1,38 @@
+# ============================================================
+# TUNER CONTROL - THREE MAIN TOGGLES
+# ============================================================
+# This file controls the THREE main tuner settings
+# NO DIGGING IN CODE REQUIRED - just edit these values
+# ============================================================
+
+[main_controls]
+# Toggle 1: Turn the entire tuner on or off
+# True = Tuner runs automatically in background
+# False = Tuner is completely disabled
+tuner_enabled = False
+
+# Toggle 2: Block shooting until shot is logged (hit or miss button pressed)
+# True = Robot cannot shoot again until driver logs previous shot result
+# False = Robot can shoot freely (may miss logging some shots)
+# RECOMMENDED: False for normal play, True for intensive tuning sessions
+require_shot_logged = False
+
+# Toggle 3: Block shooting until tuner finishes calculations and updates coefficients
+# True = Robot waits for optimizer before allowing next shot
+# False = Shooting and optimization happen independently
+# RECOMMENDED: False for normal play, True for sequential testing
+require_coefficients_updated = False
+
+# ============================================================
+# Team Configuration
+# ============================================================
+[team]
+# Your FRC team number (used to calculate robot IP address)
+team_number = 5892
+
+# ============================================================
+# THAT'S IT!
+# ============================================================
+# These are the only settings you need to change regularly.
+# For coefficient tuning configuration, see COEFFICIENT_TUNING.py
+# ============================================================

bayesopt/docs/CONTRIBUTIONS.md

@@ -0,0 +1,69 @@
+# Contributing — SideKick / bayesopt (short)
+
+Thanks for contributing. Be clear, small, and test your changes.
+
+Quick workflow
+1. Fork, clone, create a branch (e.g. feat/xxx or fix/yyy).
+2. Make focused commits, run tests/linters locally.
+3. Push branch and open a PR against main (link issue if present).
+4. Address reviews; rebase/squash if requested.
+
+Etiquette (short)
+- Be respectful and constructive.
+- Ask questions instead of assuming.
+- Explain why a change is needed and how you validated it.
+
+Commit message (required)
+Format:
+<type>(scope): short imperative summary
+
+Body:
+- State value change clearly: "from X → Y on Z" and why.
+- Add testing/compatibility notes as needed.
+
+Types: feat, fix, docs, style, refactor, perf, test, chore
+
+Example:
+- feat(optimizer): change default learning_rate from 0.01 → 0.001
+  Body: "Changed Adam default LR 0.01 → 0.001 to improve noisy-data stability. Added unit test."
+
+## Examples
+
+Good commit + PR example (clear, concrete)
+
+- Commit title:
+  feat(optimizer): reduce default Adam learning_rate 0.01 → 0.001
+
+- Commit body:
+  - What changed value-wise: changed Adam (adaptive motion estimate) default learning_rate in bayesopt/optimizer.py from 0.01 → 0.001.
+  - Why: reduced overshooting and improved stability on noisy datasets (see issue #42).
+  - Tests: updated tests/test_optimizer.py::test_default_lr to assert new default.
+  - Files changed: bayesopt/optimizer.py, tests/test_optimizer.py, docs/usage.md (if applicable).
+
+- PR description (short & required):
+  - Summary: Reduced Adam default LR 0.01 → 0.001 to improve noisy-data stability.
+  - Details:
+    - What changed: Adam.default_lr 0.01 → 0.001 in bayesopt/optimizer.py
+    - Why: training on noisy datasets showed unstable convergence; lowering LR reduced oscillation.
+    - How validated: ran unit tests and a small example run below.
+  - Validation steps (maintainers/reviewers):
+    1. Run unit test: pytest -k test_default_lr
+    2. Run a quick example: python examples/adam_demo.py --max-evals 10
+    3. Confirm no regression in CI and review updated test assertions.
+  - Related: Closes #42
+
+Bad commit/PR (what to avoid)
+- Title: "fix stuff"
+- Body: no before/after values, no tests, no explanation.
+
+PR checklist
+- Branch uses naming convention.
+- Tests added/updated where applicable.
+- Linter run.
+- Docs updated for public API changes.
+- PR description states: what changed, from what → to what, why, and how to validate.
+
+Issues
+Provide summary, steps to reproduce, environment, and logs or minimal examples.
+
+That's it — short, clear, and testable contributions are preferred.