🌈 pyTMat

pyTMat is a blazing-fast, user-friendly Python package for simulating optical multilayer stacks using the Transfer Matrix Method (TMM). Powered by a Rust core for maximum performance, pyTMat makes it easy to compute reflection and transmission spectra for complex photonic structures — perfect for research, engineering, and education.

🚀 Features

  • Ultra-fast: Rust-powered core for high-performance calculations
  • Easy-to-use: Simple Python API, no need to write Rust
  • Parallelized: Automatically uses all your CPU cores for large wavelength arrays
  • Polarization Support: TE, TM, and arbitrary polarization angles
  • Complex Refractive Indices: Supports lossy materials with complex indices
  • Flexible Layer Configurations: Any number of layers with arbitrary thicknesses
  • Incident Angles: Specify any angle of incidence
  • Wavelength Range: Define custom wavelength ranges for your simulations
  • Numpy Integration: Works seamlessly with NumPy arrays
  • Perfect for DBRs, filters, sensors, and more!

📦 Installation

Install the latest release directly from PyPI:

pip install pytmat

🧑‍💻 Quick Start

import numpy as np
import pytmat

# Define layer thicknesses (nm)
d = np.array([100, 200, 100])  # Example: 3 layers

# Define complex refractive indices for each layer at each wavelength
# Shape: (num_layers, num_wavelengths)
n = np.array([
    [1.0+0j, 1.0+0j, 1.0+0j],   # Layer 1
    [2.0+0j, 2.0+0j, 2.0+0j],   # Layer 2
    [1.5+0j, 1.5+0j, 1.5+0j],   # Layer 3
])

# Wavelengths (nm)
wl = np.linspace(400, 700, 3)

# Angle of incidence (radians) and polarization angle (radians)
theta = 0.0  # normal incidence
phi = 0.0    # TE polarization

# Create the TMM data object
data = pytmat.Data(d, n, wl, theta, phi)

# Compute reflection and transmission spectra
R = data.get_r_power_vec()
T = data.get_t_power_vec()

print("Reflection:", R)
print("Transmission:", T)

📚 API Overview

  • Data(d, n, wl, theta, phi): Main class for defining your multilayer stack.
    • d: 1D array of layer thicknesses (float, nm or μm)
    • n: 2D array of complex refractive indices (layers × wavelengths)
    • wl: 1D array of wavelengths
    • theta: Angle of incidence (radians)
    • phi: Polarization angle (radians, 0=TE, π/2=TM)
  • get_r_power_vec(): Returns reflection spectrum (array)
  • get_t_power_vec(): Returns transmission spectrum (array)

🛠️ Advanced Usage

  • Arbitrary polarization: Set phi between 0 (TE) and π/2 (TM) for mixed polarization.
  • Large arrays: For >100 wavelengths, pyTMat automatically parallelizes computations.
  • Complex indices: Supports lossy materials (complex n).

🏗️ Project Structure

pytmat/
├── tmatrix/         # Rust core library
├── pytmat/          # Python bindings (PyO3/maturin)
├── tests/           # Python tests
├── README.md
└── ...

🤝 Contributing

Contributions, bug reports, and feature requests are welcome!
Please open an issue or submit a pull request.

📄 License

This project is licensed under the MIT License.

🌟 Acknowledgements

🔗 Links

pyTMat — Fast, flexible, and fun multilayer optics for Python

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Latest release

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for gbeane66 from gravatar.com gbeane66

Requires

Python >=3.8

Classifiers

Report project as malware

Release files for pytmat 0.2.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pytmat 0.2.0
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pytmat-0.2.0.tar.gz 15.6 kB Details

Built distributions (wheels)

Table of built distributions (wheels) for pytmat 0.2.0
File
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pytmat-0.2.0-cp39-cp39-musllinux_1_2_aarch64.whl 464.4 kB CPython 3.9 CPython 3.9 Linux musl 1.2+ ARM64 Details
pytmat-0.2.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 305.0 kB CPython 3.9 CPython 3.9 Linux glibc 2.17+ x86-64 Details
pytmat-0.2.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl 327.5 kB CPython 3.9 CPython 3.9 Linux glibc 2.17+ IBM System/390x Details
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pytmat-0.2.0-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl 288.6 kB CPython 3.9 CPython 3.9 Linux glibc 2.17+ ARMv7l Details
pytmat-0.2.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 285.1 kB CPython 3.9 CPython 3.9 Linux glibc 2.17+ ARM64 Details
pytmat-0.2.0-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl 295.6 kB CPython 3.9 CPython 3.9 Linux glibc 2.12+ x86-32 Details
pytmat-0.2.0-cp38-cp38-musllinux_1_2_x86_64.whl 476.3 kB CPython 3.8 CPython 3.8 Linux musl 1.2+ x86-64 Details
pytmat-0.2.0-cp38-cp38-musllinux_1_2_i686.whl 505.0 kB CPython 3.8 CPython 3.8 Linux musl 1.2+ x86-32 Details
pytmat-0.2.0-cp38-cp38-musllinux_1_2_armv7l.whl 552.4 kB CPython 3.8 CPython 3.8 Linux musl 1.2+ ARMv7l Details
pytmat-0.2.0-cp38-cp38-musllinux_1_2_aarch64.whl 464.1 kB CPython 3.8 CPython 3.8 Linux musl 1.2+ ARM64 Details
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pytmat-0.2.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl 327.0 kB CPython 3.8 CPython 3.8 Linux glibc 2.17+ IBM System/390x Details
pytmat-0.2.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl 430.4 kB CPython 3.8 CPython 3.8 Linux glibc 2.17+ PowerPC 64-le Details
pytmat-0.2.0-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl 327.9 kB CPython 3.8 CPython 3.8 Linux glibc 2.17+ x86-32 Details
pytmat-0.2.0-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl 288.2 kB CPython 3.8 CPython 3.8 Linux glibc 2.17+ ARMv7l Details
pytmat-0.2.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 284.8 kB CPython 3.8 CPython 3.8 Linux glibc 2.17+ ARM64 Details
pytmat-0.2.0-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.whl 295.2 kB CPython 3.8 CPython 3.8 Linux glibc 2.12+ x86-32 Details

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