A high-performance Python library for material simulation and analysis
Project description
MaterForge - Materials Formulation Engine with Python
A high-performance Python library for materials modeling and simulation. MaterForge enables efficient definition of any material - metals, alloys, polymers, ceramics, composites, or hypothetical materials - through YAML configuration files, providing symbolic and numerical property evaluation as a function of any SymPy symbol.
Documentation: https://materforge.readthedocs.io
Table of Contents
- Key Features
- Installation
- Quick Start
- YAML Configuration Format
- Documentation
- Contributing
- Known Limitations
- License
- Citation
- Support
- Acknowledgments
🚀 Key Features
- Schema-Agnostic Material Definition: Any material kind, any property name - the YAML schema drives everything with no hardcoded material types or required fields
- Dependency-Driven Properties: Properties expressed as symbolic functions of any independent variable - temperature, pressure, composition, strain, or any SymPy symbol
- Modular Architecture: Clean separation with algorithms, parsing, and visualization modules
- Symbolic Mathematics: Built on SymPy for precise mathematical expressions
- Piecewise Functions: Advanced piecewise function support with regression capabilities
- Property Inversion: Create inverse functions for any piecewise-linear property
- Visualization: Automatic plotting of material properties with customizable options
- Multiple Property Types: Constants, step functions, file-based data, tabular data, piecewise equations, and computed properties
- Regression Analysis: Built-in piecewise linear fitting with configurable parameters
📦 Installation
Install from PyPI
pip install materforge
All required dependencies are installed automatically.
For contributors
Clone the repository and install in editable mode:
git clone https://i10git.cs.fau.de/rahil.doshi/materforge.git
cd materforge
pip install -e .
Note: The -e flag (--editable) installs the package by symlinking directly to the
source directory. Changes to source files take effect immediately without reinstalling -
intended for development only. Use pip install materforge for regular use.
🏃 Quick Start
Basic Material Creation
import sympy as sp
from materforge import create_material
# Any SymPy symbol works as the dependency variable
T = sp.Symbol('T')
# Load a material from YAML (see examples/myAlloy.yaml)
mat = create_material('examples/myAlloy.yaml', dependency=T, enable_plotting=True)
# Access symbolic property expressions directly
print(mat.heat_capacity) # SymPy Piecewise expression in T
print(mat.density) # 7000.0 (constant float)
# Evaluate all properties at a specific value (returns a new Material)
results = mat.evaluate(T, 500.0)
print(results.heat_capacity) # float
Bundled Example Materials
MaterForge is designed for you to write your own YAML configs. For convenience, a few reference materials ship with the package and can be loaded by name - handy for demos and quick experiments:
import sympy as sp
from materforge import list_materials, load_material
print(list_materials()) # ['1.4301', 'Al', 'Al2O3']
steel = load_material('1.4301', sp.Symbol('T'))
These are examples, not a curated database. See the bundled materials guide for details.
Command-Line Interface
Installing the package also provides a materforge command for working with YAML
files straight from a shell - no Python required:
materforge list # bundled example materials
materforge validate my_material.yaml # check a file is structurally valid
materforge info my_material.yaml # name, properties, and property types
materforge plot my_material.yaml # write a property figure
materforge evaluate my_material.yaml 500 # evaluate every property at T=500
Each subcommand wraps the same public API shown above. See the CLI guide for the full reference.
Fast Evaluation Over Many Values
evaluate() is convenient for a single value. To sweep a range, compile the
material once - each property is lambdified and cached, so an array is evaluated
in a single vectorised call:
import numpy as np
evaluate = mat.compile() # cache numeric callables once
evaluate(500.0) # scalar -> {'density': 7861.2, ...}
table = evaluate(np.linspace(300, 1800, 500)) # array -> dict of arrays
table['density'].shape # (500,)
See the fast evaluation guide for details.
Cached Builds
The slow part of create_material is the piecewise regression. MaterForge caches
the built result on disk (keyed by the YAML, its data files, the dependency, and
the library versions), so reloading an unchanged material skips the refit:
# First call builds and caches; later calls of the unchanged YAML are instant.
mat = create_material('steel.yaml', dependency=T, enable_plotting=False)
On by default for non-plotting builds; disable with MATERFORGE_DISABLE_CACHE=1,
relocate with MATERFORGE_CACHE_DIR, or empty it via clear_cache(). See the
cache guide.
Property Inversion
from materforge.algorithms.piecewise_inverter import PiecewiseInverter
import sympy as sp
from materforge import create_material
T = sp.Symbol('T')
mat = create_material('examples/myAlloy.yaml', dependency=T)
if hasattr(mat, 'energy_density'):
E = sp.Symbol('E')
inverse = PiecewiseInverter.create_inverse(mat.energy_density, 'T', 'E')
# Validate round-trip accuracy
test_val = 500.0
e = float(mat.energy_density.subs(T, test_val))
recovered = float(inverse.subs(E, e))
print(f"Round-trip: T={test_val} -> E={e:.2e} -> T={recovered:.2f}")
📋 YAML Configuration Format
Supported Property Types
- CONSTANT_VALUE: Single numeric value - not dependency-driven
- STEP_FUNCTION: Discontinuous transition at a scalar reference point
- FILE_IMPORT: Data loaded from CSV, Excel, or text files
- TABULAR_DATA: Explicit dependency-value pairs
- PIECEWISE_EQUATION: Symbolic equations over dependency variable ranges
- COMPUTED_PROPERTY: Properties derived from other defined properties
The symbol used in YAML equations (T) is a placeholder only - MaterForge substitutes
it with whatever symbol you pass to create_material(..., dependency=symbol) at runtime.
See the YAML schema documentation for full configuration options.
Example YAML files:
📚 Documentation
Full documentation is available at https://materforge.readthedocs.io
The documentation follows the Diátaxis framework:
| Type | Content |
|---|---|
| Tutorials | Getting Started · First Simulation |
| How-to Guides | Defining Material Properties · Property Inversion |
| Reference | API Reference · YAML Schema |
| Explanation | Design Philosophy · Material Properties |
🤝 Contributing
Contributions are welcome! Please see our Contributing Guide for details on how to get started.
🐛 Known Limitations
- Piecewise Inverter: Currently supports linear piecewise functions only (
degree: 1) - File Formats: Limited to CSV, Excel, and text files
- Memory Usage: Large datasets may require optimization for very high-resolution data
- Regression: Maximum 8 segments recommended for stability
📄 License
Core Library (BSD-3-Clause)
The MaterForge library itself (src/materforge/, examples/, tests/, docs/) is licensed
under the BSD 3-Clause License. See the
LICENSE file for full details.
Application Examples (GPL-3.0-or-later)
The apps/ directory contains two demonstration applications that integrate MaterForge with
waLBerla and
pystencils via code generation —
apps/HeatEquationKernel/ (a heat-equation solver with a temperature-dependent material) and
apps/CouetteFlow/ (a 3D thermal Couette flow LBM benchmark). Because these dependencies are
GPLv3-licensed, the apps directory is licensed under GPL-3.0-or-later. See
apps/README.md for the
overview and apps/LICENSE
for full details.
PyPI Distribution
pip install materforge includes only the BSD-3-Clause licensed core library. The
GPL-licensed apps are excluded from the PyPI distribution — they need a C++/CMake/MPI
toolchain plus waLBerla that pip cannot provide. To run the demo apps, get them from the
source repository:
git clone https://github.com/rahildoshi97/materforge.git
cd materforge
git submodule update --init --recursive # populates apps/walberla
See apps/README.md for build and run instructions.
| Component | Location | License | In PyPI |
|---|---|---|---|
| Core library | src/materforge/ |
BSD-3-Clause | ✅ |
| Example scripts | examples/ |
BSD-3-Clause | ❌ |
| Tests | tests/ |
BSD-3-Clause | ❌ |
| Documentation | docs/ |
BSD-3-Clause | ❌ |
| Apps | apps/ |
GPL-3.0-or-later | ❌ |
📖 Citation
If you use MaterForge in your research, please cite it using the information in our CITATION.cff file.
📞 Support
- Author: Rahil Doshi
- Email: rahil.doshi@fau.de
- Documentation: materforge.readthedocs.io
- Bug Tracker: GitHub Issues
- GitLab: i10git.cs.fau.de
🙏 Acknowledgments
- Built with SymPy for symbolic mathematics
- Data handling powered by pandas
- Uses pwlf for piecewise linear fitting
- Visualization powered by Matplotlib
- YAML parsing with ruamel.yaml
MaterForge - Empowering materials simulation with Python
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