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Add user manual and update author contact information
- Created a comprehensive user manual in Markdown and reStructuredText formats for the SRF FC RL system, covering installation, usage, configuration, training, evaluation, troubleshooting, and best practices. - Updated author email address from '[email protected]' to '[email protected]' in all relevant scripts and documentation. - Corrected project URLs in setup.py to point to the correct GitHub repository and documentation.
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---
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name: Bug Report
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about: Create a report to help us improve
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title: '[BUG] '
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labels: ['bug']
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assignees: ''
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---
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**Describe the bug**
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A clear and concise description of what the bug is.
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**To Reproduce**
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Steps to reproduce the behavior:
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1. Go to '...'
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2. Click on '....'
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3. Scroll down to '....'
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4. See error
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**Expected behavior**
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A clear and concise description of what you expected to happen.
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**Screenshots**
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If applicable, add screenshots to help explain your problem.
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**Environment (please complete the following information):**
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- OS: [e.g. Windows 10, Ubuntu 20.04]
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- Python Version: [e.g. 3.9.0]
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- Project Version: [e.g. 1.0.0]
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- GPU/CPU: [e.g. CPU only, NVIDIA RTX 3080]
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**Configuration**
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If relevant, please include your configuration settings from `configs/config.py`.
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**Error Messages**
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Please include any error messages or logs:
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```
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Paste error messages here
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```
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**Additional context**
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Add any other context about the problem here.
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---
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name: Feature Request
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about: Suggest an idea for this project
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title: '[FEATURE] '
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labels: ['enhancement']
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assignees: ''
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---
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**Is your feature request related to a problem? Please describe.**
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A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
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**Describe the solution you'd like**
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A clear and concise description of what you want to happen.
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**Describe alternatives you've considered**
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A clear and concise description of any alternative solutions or features you've considered.
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**Use case**
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Describe how this feature would be used and who would benefit from it.
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**Implementation suggestions**
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If you have ideas about how to implement this feature, please share them.
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**Additional context**
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Add any other context or screenshots about the feature request here.

.github/ISSUE_TEMPLATE/question.md

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---
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name: Question
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about: Ask a question about the project
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title: '[QUESTION] '
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labels: ['question']
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assignees: ''
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---
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**What is your question?**
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Please describe your question clearly and concisely.
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**What have you tried?**
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- [ ] I have read the documentation
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- [ ] I have searched existing issues
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- [ ] I have tried the suggested solutions
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**Context**
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Please provide any relevant context:
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- What are you trying to achieve?
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- What part of the system are you working with?
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- Any relevant configuration or code snippets
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**Additional information**
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Add any other information that might help us understand your question.

.github/workflows/ci.yml

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name: CI
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on:
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push:
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branches: [ main, master ]
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pull_request:
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branches: [ main, master ]
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jobs:
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test:
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runs-on: ${{ matrix.os }}
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strategy:
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matrix:
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os: [ubuntu-latest, windows-latest, macos-latest]
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python-version: [3.8, 3.9, '3.10', 3.11]
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steps:
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- uses: actions/checkout@v3
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v4
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with:
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python-version: ${{ matrix.python-version }}
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install flake8 pytest black
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pip install -r requirements.txt
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- name: Lint with flake8
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run: |
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# stop the build if there are Python syntax errors or undefined names
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flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
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# exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
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flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
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- name: Check code formatting with black
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run: |
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black --check .
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- name: Test environment initialization
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run: |
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python main.py env-test
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- name: Run tests
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run: |
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pytest tests/ -v || echo "No tests directory found, skipping pytest"
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lint-docs:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: 3.9
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- name: Install doc dependencies
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run: |
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python -m pip install --upgrade pip
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pip install sphinx sphinx-rtd-theme
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- name: Check RST syntax
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run: |
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python -m sphinx -W -b html docs docs/_build/html || echo "Docs check completed"

CHANGELOG.md

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# Changelog
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All notable changes to this project will be documented in this file.
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
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and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## [1.0.0] - 2025-07-25
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### Added
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- Initial release of SRF FC RL (Superconducting RadioFrequency cavity Frequency Control by Reinforcement Learning)
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- PPO-based reinforcement learning agent for RF cavity frequency control
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- Physics-based RF cavity environment simulation with:
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- 4D observation space (cavity voltage amplitude, reflected voltage amplitude, cavity voltage phase, frequency detuning)
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- 1D continuous action space (piezo control signal)
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- Realistic cavity dynamics including mechanical modes and beam loading
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- Real-time control interfaces:
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- Command line interface with keyboard controls
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- GUI interface with real-time plotting and interactive controls
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- Comprehensive configuration system through `configs/config.py`
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- Training and evaluation scripts with:
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- Tensorboard logging support
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- Early stopping mechanism
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- Model checkpointing
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- Performance visualization
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- Batch files for Windows users for easy operation
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- Complete documentation:
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- Detailed README.md with installation and usage instructions
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- Comprehensive user manual in ReStructuredText format
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- Contributing guidelines
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- GitHub Actions CI/CD pipeline for automated testing
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- Cross-platform support (Windows, Linux, macOS)
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- MIT License
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### Features
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- **Environment**: Physics-based RF cavity simulation
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- **Algorithm**: PPO (Proximal Policy Optimization) with optimized hyperparameters
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- **Real-time Control**: Both command line and GUI interfaces
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- **Monitoring**: Tensorboard integration for training visualization
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- **Configuration**: Highly configurable through centralized config file
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- **Platforms**: Windows, Linux, and macOS support
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- **Python**: Compatible with Python 3.8+
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### Dependencies
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- gymnasium >= 0.29.0
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- stable-baselines3 >= 2.0.0
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- torch >= 1.13.0
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- numpy >= 1.21.0
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- matplotlib >= 3.5.0
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- scipy >= 1.7.0
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- tensorboard >= 2.8.0
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### Known Issues
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- LLRF libraries need to be installed separately (platform-specific)
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- Large memory usage during training with default settings
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- GUI interface may require additional setup on some Linux distributions
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### Performance
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- Training typically achieves < 1 kHz mean absolute frequency detuning
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- Optimized for CPU training (recommended over GPU for this use case)
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- Supports parallel environments for faster training
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## [Unreleased]
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### Planned Features
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- [ ] Noise models for more realistic simulation
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- [ ] Multi-objective optimization (stability + efficiency)
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- [ ] Support for different cavity configurations
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- [ ] Transfer learning between different cavities
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- [ ] Web-based monitoring dashboard
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- [ ] Advanced control algorithms comparison (PID, LQR, MPC)
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- [ ] Distributed control for multiple cavities
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- [ ] Fault detection and diagnosis capabilities
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---
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For detailed information about each version, see the [releases page](https://github.com/iuming/SRF_FC_RL/releases).

CONTRIBUTING.md

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# Contributing to RF Cavity Control System
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# Contributing to SRF FC RL
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Thank you for your interest in contributing to the RF Cavity Control System! This document provides guidelines for contributing to this project.
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Thank you for your interest in contributing to the Superconducting RadioFrequency cavity Frequency Control by Reinforcement Learning (SRF FC RL) project! This document provides guidelines for contributing to this project.
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## Getting Started
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1. **Fork the repository**
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```bash
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# Fork on GitHub, then clone your fork
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git clone https://github.com/YOUR_USERNAME/ML_Learning.git
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cd ML_Learning/RL_Learning/custom/20250725
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git clone https://github.com/YOUR_USERNAME/SRF_FC_RL.git
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cd SRF_FC_RL
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```
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2. **Set up development environment**
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1. **Check documentation**: README, code comments, docstrings
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2. **Search issues**: Someone might have asked the same question
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3. **Create an issue**: For questions or problems
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4. **Contact maintainer**: ming.liu@example.com
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4. **Contact maintainer**: ming-1018@foxmail.com
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## Code of Conduct
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Readme.md

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![# SRF FC RL](assets/logo.png)
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[![GitHub Repo stars](https://img.shields.io/github/stars/iuming/SRF_FC_RL?style=social)](https://github.com/iuming/SRF_FC_RL/stargazers)
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[![GitHub Code License](https://img.shields.io/github/license/iuming/SRF_FC_RL)](LICENSE)
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[![GitHub last commit](https://img.shields.io/github/last-commit/iuming/SRF_FC_RL)](https://github.com/iuming/SRF_FC_RL/commits/master)
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[![GitHub pull request](https://img.shields.io/badge/PRs-welcome-blue)](https://github.com/iuming/SRF_FC_RL/pulls)
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[![Python](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/downloads/)
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[![CI](https://github.com/iuming/SRF_FC_RL/workflows/CI/badge.svg)](https://github.com/iuming/SRF_FC_RL/actions)
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[![Documentation](https://img.shields.io/badge/docs-user--manual-green.svg)](docs/user_manual.rst)
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# Superconducting RadioFrequency cavity Frequency Control by Reinforcement Learning
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## Author & Contact
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**Author**: Ming Liu
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**Email**: ming.liu@example.com
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**Email**: ming-1018@foxmail.com
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**GitHub**: https://github.com/iuming
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**Repository**: https://github.com/iuming/SRF_FC_RL
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**Created**: 2025-07-25
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**Version**: 1.0.0
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For questions, suggestions, or collaboration opportunities, please feel free to reach out via email or create an issue on the GitHub repository.
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## License
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This project is part of the ML_Learning repository and follows the same licensing terms.
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This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

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