Pulseq-compatible, high-performance MRI simulation in Python.
komamripy is a thin Python interface to
KomaMRI.jl, a high-performance
Julia framework for MRI simulation. It exposes KomaMRI to Python through
juliacall, so
Python users can run fast CPU/GPU MRI simulations without writing any Julia.
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.
komamripyis in early development and is not yet on PyPI. Install it from source.
You do not need to install Julia yourself: juliacall provisions a suitable
Julia automatically, and KomaMRI is installed on first import.
Install by using uv (recommended) or pip (remove uv):
uv pip install git+https://github.com/JuliaHealth/komamripyThe first import downloads Julia and precompiles KomaMRI, which can take a few minutes. Subsequent runs are fast.
import komamripy as km
import numpy as np
sys = km.Scanner() # scanner hardware
obj = km.brain_phantom2D() # 2D brain phantom
seq = km.PulseDesigner.EPI_example() # example EPI sequence
sim_params = km.KomaMRICore.default_sim_params()
sim_params["return_type"] = "mat" # return the raw signal matrix
raw = km.simulate(obj, seq, sys, sim_params=sim_params)
signal = np.asarray(raw)
print(signal.shape)A runnable version lives in examples/.
KomaMRI reads Pulseq .seq files, so komamripy can
simulate sequences produced by any Pulseq tool, including
pypulseq:
seq = km.read_seq("sequence.seq")
raw = km.simulate(obj, seq, sys)komamripy is under active development as a Google Summer of Code project.
Currently supported: the core simulation pipeline and reading Pulseq files.
Planned: PyPI releases, GPU backend selection, tighter pypulseq integration, and differentiable workflows.