PtyLab is an inverse modeling toolbox for Conventional (CP) and Fourier (FP) ptychography in a unified framework. For more information please check the paper.
- Classic reconstruction engines: ePIE, mPIE, mqNewton,
- Advanced corrections: multi-slice, multi-wavelength, position correction (pcPIE), defocus correction (zPIE), angle correction (aPIE), orthogonal probe relaxation (OPR), mixed-state object and probe.
- Multiple propagators: Fraunhofer, Fresnel, Angular Spectrum (ASP), scaled ASP, and polychromatic variants
- GPU acceleration: Same code runs on CPU and GPU.
The reconstructed output is a 6D array of shape (nlambda, nosm, npsm, nslice, No, No):
| Dim | Meaning |
|---|---|
nlambda |
wavelengths |
nosm |
object state mixture |
npsm |
probe state mixture |
nslice |
depth slices |
No |
output frame size |
The simplest way to get started is to check the below demo in Google Colab.
To explore more use cases of PtyLab, check the example_scripts and jupyter_tutorials directories. However, please install the package first as described in the below sections.
To install the package from source within your virtual environment:
pip install git+https://github.com/PtyLab/PtyLab.py.gitNote
Just as a tip, to install the package very fast, we recommend using uv and simply doing uv pip install git+https://github.com/PtyLab/PtyLab.py.git
This package uses cupy to utilize GPU for faster reconstruction. To enable GPU support, install the package with the appropriate CUDA extra:
# For CUDA 12.x
pip install "ptylab[cuda12] @ git+https://github.com/PtyLab/PtyLab.py.git"
# For CUDA 13.x
pip install "ptylab[cuda13] @ git+https://github.com/PtyLab/PtyLab.py.git"To check if GPU is being used, please do ptylab check gpu within your environment.
Clone this repository and navigate to the root folder:
git clone git@github.com:PtyLab/PtyLab.py.git
cd PtyLab.pyInstall uv if you have not already, then install ptylab and its development dependencies:
uv sync --extra devThis creates a .venv virtual environment in the project root. Select this environment from your IDE.
To use the GPU, install with the appropriate CUDA extra instead:
uv sync --extra dev,cuda12 # for CUDA 12.x
uv sync --extra dev,cuda13 # for CUDA 13.xand check if GPU is detected with uv run ptylab check gpu.
If any new changes are made, add a new test if necessary and run the test suite.
uv run pytest testsNote that CI will also do this at every PR. Please bump the package version when modifying dependencies.
If you use this package in your work, cite us as below.
@article{Loetgering:23,
author = {Lars Loetgering and Mengqi Du and Dirk Boonzajer Flaes and Tomas Aidukas and Felix Wechsler and Daniel S. Penagos Molina and Max Rose and Antonios Pelekanidis and Wilhelm Eschen and J\"{u}rgen Hess and Thomas Wilhein and Rainer Heintzmann and Jan Rothhardt and Stefan Witte},
journal = {Opt. Express},
number = {9},
pages = {13763--13797},
publisher = {Optica Publishing Group},
title = {PtyLab.m/py/jl: a cross-platform, open-source inverse modeling toolbox for conventional and Fourier ptychography},
volume = {31},
month = {Apr},
year = {2023},
doi = {10.1364/OE.485370},
}