# PhysiCell Settings
A powerful, modular Python package for generating PhysiCell_settings.xml configuration files with comprehensive parameter coverage, intuitive API design, and maintainable architecture.
[](https://www.python.org/downloads/)
[](https://pypi.org/project/physicell-settings/)
[](https://www.gnu.org/licenses/gpl-3.0)
## 🚀 Overview
The PhysiCell Settings package provides a powerful yet simple API for creating complex PhysiCell simulations. Built with a modern modular architecture, it handles all aspects of PhysiCell configuration with a focus on ease of use, maintainability, and compatibility with existing PhysiCell standards.
## 📦 Installation
Install from PyPI using pip:
```bash
pip install physicell-settings
```
**Requirements:**
- Python 3.8 or higher
- No external dependencies (uses only Python standard library)
## 🚀 Quick Start
```python
import physicell_config
from physicell_config import PhysiCellConfig
# Create a new configuration
config = PhysiCellConfig()
# Set up simulation domain
config.domain.set_bounds(x_min=-500, x_max=500, y_min=-500, y_max=500)
# Add substrates
config.substrates.add_substrate(
name="oxygen",
diffusion_coefficient=100000.0,
decay_rate=0.1
)
# Add cell type
config.cell_types.add_cell_type(
name="cancer_cell",
cycle_model="Ki67_basic"
)
# Save configuration
config.save("PhysiCell_settings.xml")
```
## 🔄 **NEW: Bidirectional XML Support**
**Load, modify, and save existing PhysiCell configurations!**
```python
# Load existing PhysiCell configuration
config = PhysiCellConfig()
config.load_xml("existing_simulation.xml")
# Modify as needed
config.domain.set_bounds(-600, 600, -400, 400)
config.substrates.add_substrate("my_drug", diffusion_coefficient=1000.0)
# Add cell rules
rules = config.cell_rules_csv
rules.add_rule("cancer_cell", "oxygen", "decreases", "necrosis", 0, 3.75, 8, 0)
# Save modified configuration
config.save_xml("modified_simulation.xml")
```
**Features:**
- ✅ **Complete XML Loading** - Load any existing PhysiCell configuration
- ✅ **Perfect Data Preservation** - Round-trip loading maintains all data
- ✅ **PhysiBOSS Support** - Full intracellular model loading and saving
- ✅ **Robust Validation** - Clear error messages for invalid XML files
- ✅ **Cell Rules Integration** - Preserve and modify existing rule configurations
[📖 **Full Documentation: BIDIRECTIONAL_XML_SUPPORT.md**](BIDIRECTIONAL_XML_SUPPORT.md)
## 🚧 Development Status
**Current Version:** 0.1.0 (Beta)
This package is currently in active development. While it's functional and available on PyPI, some features are still being refined and additional functionality is being added.
### ✅ **What's Working:**
- Core configuration generation
- All major PhysiCell modules (domain, substrates, cell types, etc.)
- PyPI installation and basic usage
- Modular architecture
### 🔄 **In Progress:**
- Additional validation and error handling
- Enhanced documentation and examples
- Extended API coverage for advanced features
- Performance optimizations
### 📋 **Planned Features:**
- Advanced parameter validation
- Configuration templates
- Migration tools from legacy formats
- Enhanced PhysiBoSS integration
**Note:** The repository is currently private as we finalize features and documentation. The package is stable for basic use cases.
## ✨ Key Features
- **🏗️ Modular Architecture** - Well-organized, maintainable codebase with focused modules
- **🎯 Simple & Intuitive** - Clean API with sensible defaults and method chaining
- **🔧 Comprehensive Coverage** - All PhysiCell features: domain, substrates, cells, rules, PhysiBoSS
- **✅ Built-in Validation** - Configuration validation with detailed error reporting
- **🔄 Full Compatibility** - Generates standard PhysiCell XML, reproduces existing configs
- **🧬 Advanced Features** - Cell rules, PhysiBoSS integration, initial conditions, enhanced visualization
- **📊 Cell Rules CSV** - Context-aware generation of rules.csv files with signal/behavior validation
- **📚 Well Documented** - Extensive examples and clear modular documentation
### 🎯 Perfect For
- **Researchers** building new PhysiCell models with complex requirements
- **Developers** programmatically generating parameter sweeps and batch simulations
- **Teams** collaborating on large simulation projects with maintainable code
- **Educators** teaching computational biology with clear, reproducible examples
## 🏗️ Modular Architecture
The configuration builder uses a modular composition pattern that provides:
- **Clean Separation**: Each module handles one aspect of configuration
- **Easy Maintenance**: Small, focused files instead of monolithic code
- **Team Development**: Multiple developers can work on different modules
- **Extensibility**: Easy to add new modules without affecting existing code
### Module Structure
```
├── config_builder_modular.py # Main configuration class
└── modules/
├── domain.py # Simulation domain and mesh
├── substrates.py # Microenvironment substrates
├── cell_types.py # Cell definitions and phenotypes
├── cell_rules.py # Cell behavior rules
├── cell_rules_csv.py # rules.csv generation with context awareness
├── physiboss.py # PhysiBoSS boolean networks
├── initial_conditions.py # Initial cell placement
├── save_options.py # Output and visualization
└── options.py # Simulation parameters
```
## 🚀 Quick Start
### Installation
The package is available on PyPI for easy installation:
```bash
pip install physicell-settings
```
### Basic Usage
```python
import physicell_config
from physicell_config import PhysiCellConfig
# Create configuration
config = PhysiCellConfig()
# Set up simulation domain
config.domain.set_bounds(x_min=-400, x_max=400, y_min=-400, y_max=400)
# Add substrates
config.substrates.add_substrate(
name="oxygen",
diffusion_coefficient=100000.0,
decay_rate=0.1
)
# Add cell type
config.cell_types.add_cell_type(
name="cancer_cell",
cycle_model="Ki67_basic"
)
```
### Advanced Modular Usage
```python
# Direct module access for advanced features
config.domain.set_bounds(-500, 500, -500, 500)
config.substrates.add_substrate("glucose", diffusion_coefficient=50000.0)
config.cell_types.add_cell_type("immune_cell")
config.cell_types.set_motility("immune_cell", speed=2.0, enabled=True)
config.cell_types.add_secretion("immune_cell", "oxygen", uptake_rate=5.0)
config.cell_rules.add_rule("oxygen", "proliferation", "cancer_cell")
config.physiboss.enable_physiboss("boolean_model.bnd")
config.initial_conditions.add_cell_cluster("cancer_cell", x=0, y=0, radius=100)
```
## 📖 Examples
### Complete Tumor-Immune Simulation
```python
from config_builder_modular import PhysiCellConfig
# Create configuration
config = PhysiCellConfig()
# Setup domain
config.domain.set_bounds(-600, 600, -600, 600)
config.domain.set_mesh(20.0, 20.0)
# Add substrates
config.substrates.add_substrate("oxygen",
diffusion_coefficient=100000.0,
decay_rate=0.1,
initial_condition=38.0)
config.substrates.add_substrate("glucose",
diffusion_coefficient=50000.0,
decay_rate=0.01,
initial_condition=10.0)
# Add cell types
config.cell_types.add_cell_type("cancer_cell")
config.cell_types.set_motility("cancer_cell", speed=0.5, enabled=True)
config.cell_types.add_secretion("cancer_cell", "oxygen", uptake_rate=10.0)
config.cell_types.add_cell_type("immune_cell")
config.cell_types.set_motility("immune_cell", speed=2.0, enabled=True)
# Add initial conditions
config.initial_conditions.add_cell_cluster("cancer_cell", x=0, y=0, radius=150, num_cells=100)
config.initial_conditions.add_cell_cluster("immune_cell", x=300, y=300, radius=50, num_cells=20)
# Add cell rules to XML
config.cell_rules.add_rule(
signal="oxygen",
behavior="proliferation",
cell_type="cancer_cell",
min_signal=0.0,
max_signal=38.0,
min_behavior=0.0,
max_behavior=0.05
)
# Configure visualization
config.save_options.set_svg_options(
interval=120.0,
plot_substrate=True,
substrate_to_plot="oxygen",
cell_color_by="cell_type"
)
# Save configuration
config.save_xml("tumor_immune_simulation.xml")
```
### Loading Cell Rules from CSV
```python
# Create rules CSV file
import csv
rules = [
{"signal": "oxygen", "behavior": "proliferation", "cell_type": "cancer_cell",
"min_signal": 0.0, "max_signal": 38.0, "min_behavior": 0.0, "max_behavior": 0.05},
{"signal": "pressure", "behavior": "apoptosis", "cell_type": "cancer_cell",
"min_signal": 0.0, "max_signal": 1.0, "min_behavior": 0.0, "max_behavior": 0.1}
]
with open("cell_rules.csv", "w", newline="") as f:
writer = csv.DictWriter(f, fieldnames=rules[0].keys())
writer.writeheader()
writer.writerows(rules)
# Load rules in configuration
config.cell_rules.load_rules_from_csv("cell_rules.csv")
```
## 🧪 Testing and Validation
### Run Demo
```bash
python demo_modular.py
```
### Configuration Validation
```python
# Built-in validation
issues = config.validate()
if issues:
for issue in issues:
print(f"⚠️ {issue}")
else:
print("✅ Configuration is valid!")
# Get configuration summary
summary = config.get_summary()
print(f"Substrates: {summary['substrates']}")
print(f"Cell types: {summary['cell_types']}")
```
## 📁 Project Structure
```
physicell_config/
├── README.md # This file
├── config_builder.py # Main configuration class
├── demo_modular.py # Demonstration script
├── modules/ # Modular components
│ ├── __init__.py
│ ├── base.py # Common utilities
│ ├── domain.py # Domain configuration
│ ├── substrates.py # Substrate management
│ ├── cell_types.py # Cell type definitions
│ ├── cell_rules.py # Cell behavior rules
│ ├── physiboss.py # PhysiBoSS integration
│ ├── initial_conditions.py # Initial cell placement
│ ├── save_options.py # Output configuration
│ └── options.py # Simulation options
├── examples/ # Example configurations
│ ├── PhysiCell_settings.xml # Reference PhysiCell config
│ ├── basic_tumor.py # Basic tumor example
│ ├── cancer_immune.py # Cancer-immune interaction
│ └── physiboss_integration.py # PhysiBoSS example
├── MODULAR_ARCHITECTURE.md # Detailed architecture docs
├── MODULARIZATION_COMPLETE.md # Project completion summary
└── setup.py # Package setup
```
## 🔧 Advanced Features
### PhysiBoSS Integration
```python
# Enable PhysiBoSS boolean networks
config.physiboss.enable_physiboss("boolean_model.bnd")
config.physiboss.add_mutation("mutant_cell", "p53", False)
config.physiboss.add_initial_value("EGFR", True)
```
### Complex Initial Conditions
```python
# Multiple initial condition types
config.initial_conditions.add_cell_cluster("cancer", 0, 0, radius=100)
config.initial_conditions.add_single_cell("stem_cell", 200, 200)
config.initial_conditions.add_rectangular_region("stromal", -300, 300, -300, 300, density=0.3)
```
### Enhanced Visualization
```python
# Advanced SVG options
config.save_options.set_svg_options(
plot_substrate=True,
substrate_to_plot="oxygen",
cell_color_by="cell_type",
interval=60.0
)
```
### Cell Rules CSV Generation
```python
# Create cell rules CSV with context awareness
rules = config.cell_rules_csv
# Explore available signals and behaviors
rules.print_available_signals(filter_by_type="contact")
rules.print_available_behaviors(filter_by_type="motility")
rules.print_context() # Shows current cell types and substrates
# Add rules following PhysiCell CSV format
rules.add_rule("tumor", "oxygen", "decreases", "necrosis", 0, 3.75, 8, 0)
rules.add_rule("tumor", "contact with immune_cell", "increases", "apoptosis", 0.1, 0.5, 4, 0)
# Generate PhysiCell-compatible CSV file
rules.generate_csv("config/differentiation/rules.csv")
```
### PhysiBoSS Integration
```python
# Add intracellular models to cell types
config.cell_types.add_intracellular_model("T_cell", "maboss")
config.cell_types.set_intracellular_settings("T_cell",
bnd_filename="tcell.bnd",
cfg_filename="tcell.cfg")
config.cell_types.add_intracellular_mutation("T_cell", "FOXP3", 0)
```
## 🤝 Contributing
We welcome contributions! The modular architecture makes it easy to:
- Add new modules for additional PhysiCell features
- Enhance existing modules with new functionality
- Improve documentation and examples
- Add comprehensive test suites
## 📧 Support & Contact
- **Author:** Marco Ruscone
- **Email:** ym.ruscone94@gmail.com
- **PyPI:** https://pypi.org/project/physicell-settings/
For questions, suggestions, or bug reports, please feel free to reach out via email.
## 📄 License
This project is licensed under the GNU General Public License v3.0 - see the [LICENSE](LICENSE) file for details.
## 🙏 Acknowledgments
- PhysiCell development team for creating the simulation framework
- The open-source community for inspiration and best practices
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"description": "# PhysiCell Settings\n\nA powerful, modular Python package for generating PhysiCell_settings.xml configuration files with comprehensive parameter coverage, intuitive API design, and maintainable architecture.\n\n[](https://www.python.org/downloads/)\n[](https://pypi.org/project/physicell-settings/)\n[](https://www.gnu.org/licenses/gpl-3.0)\n\n## \ud83d\ude80 Overview\n\nThe PhysiCell Settings package provides a powerful yet simple API for creating complex PhysiCell simulations. Built with a modern modular architecture, it handles all aspects of PhysiCell configuration with a focus on ease of use, maintainability, and compatibility with existing PhysiCell standards.\n\n## \ud83d\udce6 Installation\n\nInstall from PyPI using pip:\n\n```bash\npip install physicell-settings\n```\n\n**Requirements:**\n- Python 3.8 or higher\n- No external dependencies (uses only Python standard library)\n\n## \ud83d\ude80 Quick Start\n\n```python\nimport physicell_config\nfrom physicell_config import PhysiCellConfig\n\n# Create a new configuration\nconfig = PhysiCellConfig()\n\n# Set up simulation domain\nconfig.domain.set_bounds(x_min=-500, x_max=500, y_min=-500, y_max=500)\n\n# Add substrates\nconfig.substrates.add_substrate(\n name=\"oxygen\", \n diffusion_coefficient=100000.0,\n decay_rate=0.1\n)\n\n# Add cell type\nconfig.cell_types.add_cell_type(\n name=\"cancer_cell\",\n cycle_model=\"Ki67_basic\"\n)\n\n# Save configuration\nconfig.save(\"PhysiCell_settings.xml\")\n```\n\n## \ud83d\udd04 **NEW: Bidirectional XML Support**\n\n**Load, modify, and save existing PhysiCell configurations!**\n\n```python\n# Load existing PhysiCell configuration\nconfig = PhysiCellConfig()\nconfig.load_xml(\"existing_simulation.xml\")\n\n# Modify as needed\nconfig.domain.set_bounds(-600, 600, -400, 400)\nconfig.substrates.add_substrate(\"my_drug\", diffusion_coefficient=1000.0)\n\n# Add cell rules\nrules = config.cell_rules_csv\nrules.add_rule(\"cancer_cell\", \"oxygen\", \"decreases\", \"necrosis\", 0, 3.75, 8, 0)\n\n# Save modified configuration\nconfig.save_xml(\"modified_simulation.xml\")\n```\n\n**Features:**\n- \u2705 **Complete XML Loading** - Load any existing PhysiCell configuration\n- \u2705 **Perfect Data Preservation** - Round-trip loading maintains all data\n- \u2705 **PhysiBOSS Support** - Full intracellular model loading and saving\n- \u2705 **Robust Validation** - Clear error messages for invalid XML files\n- \u2705 **Cell Rules Integration** - Preserve and modify existing rule configurations\n\n[\ud83d\udcd6 **Full Documentation: BIDIRECTIONAL_XML_SUPPORT.md**](BIDIRECTIONAL_XML_SUPPORT.md)\n\n## \ud83d\udea7 Development Status\n\n**Current Version:** 0.1.0 (Beta)\n\nThis package is currently in active development. While it's functional and available on PyPI, some features are still being refined and additional functionality is being added.\n\n### \u2705 **What's Working:**\n- Core configuration generation\n- All major PhysiCell modules (domain, substrates, cell types, etc.)\n- PyPI installation and basic usage\n- Modular architecture\n\n### \ud83d\udd04 **In Progress:**\n- Additional validation and error handling\n- Enhanced documentation and examples\n- Extended API coverage for advanced features\n- Performance optimizations\n\n### \ud83d\udccb **Planned Features:**\n- Advanced parameter validation\n- Configuration templates\n- Migration tools from legacy formats\n- Enhanced PhysiBoSS integration\n\n**Note:** The repository is currently private as we finalize features and documentation. The package is stable for basic use cases.\n\n## \u2728 Key Features\n\n- **\ud83c\udfd7\ufe0f Modular Architecture** - Well-organized, maintainable codebase with focused modules\n- **\ud83c\udfaf Simple & Intuitive** - Clean API with sensible defaults and method chaining\n- **\ud83d\udd27 Comprehensive Coverage** - All PhysiCell features: domain, substrates, cells, rules, PhysiBoSS\n- **\u2705 Built-in Validation** - Configuration validation with detailed error reporting\n- **\ud83d\udd04 Full Compatibility** - Generates standard PhysiCell XML, reproduces existing configs\n- **\ud83e\uddec Advanced Features** - Cell rules, PhysiBoSS integration, initial conditions, enhanced visualization\n- **\ud83d\udcca Cell Rules CSV** - Context-aware generation of rules.csv files with signal/behavior validation\n- **\ud83d\udcda Well Documented** - Extensive examples and clear modular documentation\n\n### \ud83c\udfaf Perfect For\n\n- **Researchers** building new PhysiCell models with complex requirements\n- **Developers** programmatically generating parameter sweeps and batch simulations\n- **Teams** collaborating on large simulation projects with maintainable code\n- **Educators** teaching computational biology with clear, reproducible examples\n\n## \ud83c\udfd7\ufe0f Modular Architecture\n\nThe configuration builder uses a modular composition pattern that provides:\n\n- **Clean Separation**: Each module handles one aspect of configuration\n- **Easy Maintenance**: Small, focused files instead of monolithic code\n- **Team Development**: Multiple developers can work on different modules\n- **Extensibility**: Easy to add new modules without affecting existing code\n\n### Module Structure\n\n```\n\u251c\u2500\u2500 config_builder_modular.py # Main configuration class\n\u2514\u2500\u2500 modules/\n \u251c\u2500\u2500 domain.py # Simulation domain and mesh\n \u251c\u2500\u2500 substrates.py # Microenvironment substrates \n \u251c\u2500\u2500 cell_types.py # Cell definitions and phenotypes\n \u251c\u2500\u2500 cell_rules.py # Cell behavior rules\n \u251c\u2500\u2500 cell_rules_csv.py # rules.csv generation with context awareness\n \u251c\u2500\u2500 physiboss.py # PhysiBoSS boolean networks\n \u251c\u2500\u2500 initial_conditions.py # Initial cell placement\n \u251c\u2500\u2500 save_options.py # Output and visualization\n \u2514\u2500\u2500 options.py # Simulation parameters\n```\n\n## \ud83d\ude80 Quick Start\n\n### Installation\n\nThe package is available on PyPI for easy installation:\n\n```bash\npip install physicell-settings\n```\n\n### Basic Usage\n\n```python\nimport physicell_config\nfrom physicell_config import PhysiCellConfig\n\n# Create configuration\nconfig = PhysiCellConfig()\n\n# Set up simulation domain\nconfig.domain.set_bounds(x_min=-400, x_max=400, y_min=-400, y_max=400)\n\n# Add substrates\nconfig.substrates.add_substrate(\n name=\"oxygen\", \n diffusion_coefficient=100000.0,\n decay_rate=0.1\n)\n\n# Add cell type\nconfig.cell_types.add_cell_type(\n name=\"cancer_cell\",\n cycle_model=\"Ki67_basic\"\n)\n```\n\n### Advanced Modular Usage\n\n```python\n# Direct module access for advanced features\nconfig.domain.set_bounds(-500, 500, -500, 500)\nconfig.substrates.add_substrate(\"glucose\", diffusion_coefficient=50000.0)\n\nconfig.cell_types.add_cell_type(\"immune_cell\")\nconfig.cell_types.set_motility(\"immune_cell\", speed=2.0, enabled=True)\nconfig.cell_types.add_secretion(\"immune_cell\", \"oxygen\", uptake_rate=5.0)\n\nconfig.cell_rules.add_rule(\"oxygen\", \"proliferation\", \"cancer_cell\")\nconfig.physiboss.enable_physiboss(\"boolean_model.bnd\")\nconfig.initial_conditions.add_cell_cluster(\"cancer_cell\", x=0, y=0, radius=100)\n```\n\n## \ud83d\udcd6 Examples\n\n### Complete Tumor-Immune Simulation\n\n```python\nfrom config_builder_modular import PhysiCellConfig\n\n# Create configuration\nconfig = PhysiCellConfig()\n\n# Setup domain \nconfig.domain.set_bounds(-600, 600, -600, 600)\nconfig.domain.set_mesh(20.0, 20.0)\n\n# Add substrates\nconfig.substrates.add_substrate(\"oxygen\", \n diffusion_coefficient=100000.0,\n decay_rate=0.1, \n initial_condition=38.0)\n\nconfig.substrates.add_substrate(\"glucose\",\n diffusion_coefficient=50000.0,\n decay_rate=0.01,\n initial_condition=10.0)\n\n# Add cell types\nconfig.cell_types.add_cell_type(\"cancer_cell\")\nconfig.cell_types.set_motility(\"cancer_cell\", speed=0.5, enabled=True)\nconfig.cell_types.add_secretion(\"cancer_cell\", \"oxygen\", uptake_rate=10.0)\n\nconfig.cell_types.add_cell_type(\"immune_cell\") \nconfig.cell_types.set_motility(\"immune_cell\", speed=2.0, enabled=True)\n\n# Add initial conditions\nconfig.initial_conditions.add_cell_cluster(\"cancer_cell\", x=0, y=0, radius=150, num_cells=100)\nconfig.initial_conditions.add_cell_cluster(\"immune_cell\", x=300, y=300, radius=50, num_cells=20)\n\n# Add cell rules to XML\nconfig.cell_rules.add_rule(\n signal=\"oxygen\",\n behavior=\"proliferation\",\n cell_type=\"cancer_cell\",\n min_signal=0.0,\n max_signal=38.0,\n min_behavior=0.0,\n max_behavior=0.05\n)\n\n# Configure visualization\nconfig.save_options.set_svg_options(\n interval=120.0,\n plot_substrate=True,\n substrate_to_plot=\"oxygen\",\n cell_color_by=\"cell_type\"\n)\n\n# Save configuration\nconfig.save_xml(\"tumor_immune_simulation.xml\")\n```\n\n### Loading Cell Rules from CSV\n\n```python\n# Create rules CSV file\nimport csv\n\nrules = [\n {\"signal\": \"oxygen\", \"behavior\": \"proliferation\", \"cell_type\": \"cancer_cell\", \n \"min_signal\": 0.0, \"max_signal\": 38.0, \"min_behavior\": 0.0, \"max_behavior\": 0.05},\n {\"signal\": \"pressure\", \"behavior\": \"apoptosis\", \"cell_type\": \"cancer_cell\",\n \"min_signal\": 0.0, \"max_signal\": 1.0, \"min_behavior\": 0.0, \"max_behavior\": 0.1}\n]\n\nwith open(\"cell_rules.csv\", \"w\", newline=\"\") as f:\n writer = csv.DictWriter(f, fieldnames=rules[0].keys())\n writer.writeheader()\n writer.writerows(rules)\n\n# Load rules in configuration\nconfig.cell_rules.load_rules_from_csv(\"cell_rules.csv\")\n```\n\n## \ud83e\uddea Testing and Validation\n\n### Run Demo\n```bash\npython demo_modular.py\n```\n\n### Configuration Validation\n```python\n# Built-in validation\nissues = config.validate()\nif issues:\n for issue in issues:\n print(f\"\u26a0\ufe0f {issue}\")\nelse:\n print(\"\u2705 Configuration is valid!\")\n\n# Get configuration summary\nsummary = config.get_summary()\nprint(f\"Substrates: {summary['substrates']}\")\nprint(f\"Cell types: {summary['cell_types']}\")\n```\n\n## \ud83d\udcc1 Project Structure\n\n```\nphysicell_config/\n\u251c\u2500\u2500 README.md # This file\n\u251c\u2500\u2500 config_builder.py # Main configuration class\n\u251c\u2500\u2500 demo_modular.py # Demonstration script\n\u251c\u2500\u2500 modules/ # Modular components\n\u2502 \u251c\u2500\u2500 __init__.py\n\u2502 \u251c\u2500\u2500 base.py # Common utilities\n\u2502 \u251c\u2500\u2500 domain.py # Domain configuration\n\u2502 \u251c\u2500\u2500 substrates.py # Substrate management\n\u2502 \u251c\u2500\u2500 cell_types.py # Cell type definitions\n\u2502 \u251c\u2500\u2500 cell_rules.py # Cell behavior rules\n\u2502 \u251c\u2500\u2500 physiboss.py # PhysiBoSS integration\n\u2502 \u251c\u2500\u2500 initial_conditions.py # Initial cell placement\n\u2502 \u251c\u2500\u2500 save_options.py # Output configuration\n\u2502 \u2514\u2500\u2500 options.py # Simulation options\n\u251c\u2500\u2500 examples/ # Example configurations\n\u2502 \u251c\u2500\u2500 PhysiCell_settings.xml # Reference PhysiCell config\n\u2502 \u251c\u2500\u2500 basic_tumor.py # Basic tumor example\n\u2502 \u251c\u2500\u2500 cancer_immune.py # Cancer-immune interaction\n\u2502 \u2514\u2500\u2500 physiboss_integration.py # PhysiBoSS example\n\u251c\u2500\u2500 MODULAR_ARCHITECTURE.md # Detailed architecture docs\n\u251c\u2500\u2500 MODULARIZATION_COMPLETE.md # Project completion summary\n\u2514\u2500\u2500 setup.py # Package setup\n```\n\n## \ud83d\udd27 Advanced Features\n\n### PhysiBoSS Integration\n```python\n# Enable PhysiBoSS boolean networks\nconfig.physiboss.enable_physiboss(\"boolean_model.bnd\")\nconfig.physiboss.add_mutation(\"mutant_cell\", \"p53\", False)\nconfig.physiboss.add_initial_value(\"EGFR\", True)\n```\n\n### Complex Initial Conditions\n```python\n# Multiple initial condition types\nconfig.initial_conditions.add_cell_cluster(\"cancer\", 0, 0, radius=100)\nconfig.initial_conditions.add_single_cell(\"stem_cell\", 200, 200)\nconfig.initial_conditions.add_rectangular_region(\"stromal\", -300, 300, -300, 300, density=0.3)\n```\n\n### Enhanced Visualization\n```python\n# Advanced SVG options\nconfig.save_options.set_svg_options(\n plot_substrate=True,\n substrate_to_plot=\"oxygen\", \n cell_color_by=\"cell_type\",\n interval=60.0\n)\n```\n\n### Cell Rules CSV Generation\n```python\n# Create cell rules CSV with context awareness\nrules = config.cell_rules_csv\n\n# Explore available signals and behaviors\nrules.print_available_signals(filter_by_type=\"contact\")\nrules.print_available_behaviors(filter_by_type=\"motility\")\nrules.print_context() # Shows current cell types and substrates\n\n# Add rules following PhysiCell CSV format\nrules.add_rule(\"tumor\", \"oxygen\", \"decreases\", \"necrosis\", 0, 3.75, 8, 0)\nrules.add_rule(\"tumor\", \"contact with immune_cell\", \"increases\", \"apoptosis\", 0.1, 0.5, 4, 0)\n\n# Generate PhysiCell-compatible CSV file\nrules.generate_csv(\"config/differentiation/rules.csv\")\n```\n\n### PhysiBoSS Integration\n```python\n# Add intracellular models to cell types\nconfig.cell_types.add_intracellular_model(\"T_cell\", \"maboss\")\nconfig.cell_types.set_intracellular_settings(\"T_cell\", \n bnd_filename=\"tcell.bnd\",\n cfg_filename=\"tcell.cfg\")\nconfig.cell_types.add_intracellular_mutation(\"T_cell\", \"FOXP3\", 0)\n```\n\n## \ud83e\udd1d Contributing\n\nWe welcome contributions! The modular architecture makes it easy to:\n\n- Add new modules for additional PhysiCell features\n- Enhance existing modules with new functionality \n- Improve documentation and examples\n- Add comprehensive test suites\n\n## \ud83d\udce7 Support & Contact\n\n- **Author:** Marco Ruscone\n- **Email:** ym.ruscone94@gmail.com\n- **PyPI:** https://pypi.org/project/physicell-settings/\n\nFor questions, suggestions, or bug reports, please feel free to reach out via email.\n\n## \ud83d\udcc4 License\n\nThis project is licensed under the GNU General Public License v3.0 - see the [LICENSE](LICENSE) file for details.\n\n## \ud83d\ude4f Acknowledgments\n\n- PhysiCell development team for creating the simulation framework\n- The open-source community for inspiration and best practices\n",
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