Installation¶

ISF is available for Linux, macOS and Windows.

For installation and environment management, ISF uses pixi. Please follow the installation instructions on the pixi documentation

To install ISF with pixi, simply:

git clone https://github.com/mpinb/in_silico_framework.git --depth 1 &&
cd in_silico_framework &&
pixi run setup

Windows

Windows support is still experimental. If you are using ISF with Dask parallellization on Windows, please monitor your dask dashboard closely. In case you encounter any issues, feel free to open an issue and include relevant logs. Note that many of the core ISF workflows (network mapping, neuron model generation etc.) require extensive resources, which often implies a (Linux-based) High Performance Computing environment.

Configuration¶

ISF works best with a dask server for parallel computing. We provide default scripts to launch a dask server and workers that should work on most systems.

pixi run launch_dask_server

pixi run launch_dask_workers

For High-Performance Computing (HPC), you may want to launch the dask server with custom configuration instead of these default scripts. The underlying commands for these shortcuts are configured in the pyproject.toml file.

Usage¶

We recommend to use ISF within a JupyterLab server for interactive use:

pixi run launch_jupyter_lab_server

pixi also supports a conda-style shell activation:

pixi shell

This can be useful for executing shell scripts within the ISF environment, or configuring HPC job submissions. To get started with ISF, feel free to consult the Tutorials.

Test ISF¶

To test if all components of ISF are working as intended, you can run the test suite locally.

pixi run test