Light microscopy simulation in python.
The goal of this library is to generate highly realistic simulated data such as the following:
(this data was generated using segmentations from cell jrc_hela-3 at OpenOrganelle as the ground truth)
out.mp4
Documentation
Start with the tutorial, and read about the
simulation stages, then see the
API Reference for details
on the Simulation object and options for all of the fields.
Installation
from PyPI
pip install "microsim[all]"Note
At the moment, this library is a bit more "application" than it
is "library". If you are following the docs or tutorials, its
probably best to install the full [all] extra, which brings in
io, visualization, and other data-fetching dependencies. However,
the bare minimal install is fully functional for generating data.
Local Development
gh repo clone tlambert03/microsim
cd microsim
uv syncFrom github
To get the bleeding edge version, which will change rapidly, you can install from github.
pip install "microsim[all] @ git+https://github.com/tlambert03/microsim"With GPU support
If available, microsim can use either Jax or Cupy to accelerate computations. These are not installed by default, see the jax or cupy installation instructions, paying attention to your GPU requirements. Support for torch is planned.
Usage
Construct and run a
microsim.Simulation
object.
from microsim import schema as ms from microsim.util import ortho_plot # define the parameters of the simulation sim = ms.Simulation( truth_space=ms.ShapeScaleSpace(shape=(128, 512, 512), scale=(0.02, 0.01, 0.01)), output_space={'downscale': 8}, sample=ms.Sample( labels=[ms.MatsLines(density=0.5, length=30, azimuth=5, max_r=1)] ), modality=ms.Confocal(pinhole_au=0.2), output_path="au02.tiff", ) # run it result = sim.run() # optionally plot the result ortho_plot(result)
