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komamripy

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Pulseq-compatible, high-performance MRI simulations in Python.

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- - ci.yml
  - publish.yml
  - tag_release.yml
  - update_deps.yml
- dependabot.yml
- basic_simulation.py
- custom_phantom_creation.py
- gpu_backend_selection.py
- motion_artifact.py
- pypulseq_composability.py
- update_deps.py
- - __init__.py
  - _backends.py
  - _session.py
  - juliapkg.json
- smoke_test.py
- test_integration_examples.py
.gitignore
.mailmap
LICENSE
pyproject.toml
README.md

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// repository documentation

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**Pulseq-compatible, high-performance MRI simulation in Python.**

`komamripy` is a thin Python interface to
[KomaMRI.jl](https://github.com/JuliaHealth/KomaMRI.jl), a high-performance
Julia framework for MRI simulation. It exposes KomaMRI to Python through
[juliacall](https://juliapy.github.io/PythonCall.jl/stable/juliacall/), so
Python users can run fast CPU/GPU MRI simulations without writing any Julia.

## Installation

Install from PyPI with [uv](https://docs.astral.sh/uv/) (recommended):

```bash
uv init project-folder && cd project-folder
uv add komamripy
```

or with pip:

```bash
pip install komamripy
```

## Quick start

The first import downloads Julia and precompiles KomaMRI, which can take a few
minutes. Subsequent runs are fast.

```python
import komamripy as km
import numpy as np

km.load_cuda()  # GPU backend selection, optional

sys = km.Scanner()  # scanner hardware
obj = km.brain_phantom2D()  # 2D brain phantom
seq = km.PulseDesigner.EPI_example()  # example EPI sequence

sim_params = {"return_type": "mat"}  # return the raw signal matrix
raw = km.simulate(obj, seq, sys, sim_params=sim_params)

print(np.shape(raw))
```

You do **not** need to install Julia yourself: `juliacall` provisions a suitable
Julia automatically, and KomaMRI is installed on first import.

## How it works

`komamripy` mirrors the KomaMRI Julia namespace: any function or type that
KomaMRI exposes is available as an attribute of `komamripy`. Julia code
therefore translates to Python almost line for line.

Simulation results are returned as Julia objects; convert array-like results to
NumPy with `numpy.asarray`.

## Status

`komamripy` is under active development as a Google Summer of Code project.

Project status and roadmap are tracked in
[JuliaHealth/komamripy#9](https://github.com/JuliaHealth/komamripy/issues/9).