A modern, N-dimensional, xarray-based toolbox for Magnetic Resonance Imaging and Spectroscopy.
Documentation, tutorials, and API reference can be found here.
xmris bridges the gap between modern data structures and magnetic resonance research. By building on top of xarray, it provides a robust environment for handling multi-dimensional MRI and MRS data with labeled coordinates, powerful broadcasting, and seamless integration with the scientific Python ecosystem.
Key Features:
- N-Dimensional Data: Native handling of complex MRI/MRS datasets using
xarray. - MRS Integration: Direct compatibility with tools like
pyAMARESandnmrglue. - Modern Tooling: Built for speed and reliability, developed using
uvand strictly typed for modern Python environments.
You can install the package directly from PyPI using standard package managers:
# Using pip
pip install xmris
# Using uv (recommended)
uv add xmris
import numpy as np
import xarray as xr
import xmris # Registers the .xmr accessor!
# 1. Create a dummy N-dimensional FID (e.g., 5 Voxels x 1024 Time points)
time = np.linspace(0, 1, 1024)
data = np.random.randn(5, 1024) + 1j * np.random.randn(5, 1024)
mrsi_data = xr.DataArray(
data,
dims=["voxel", "time"],
coords={"voxel": np.arange(5), "time": time},
attrs={"MHz": 120.0, "sw": 10000.0}
)
# 2. Process all voxels simultaneously using the .xmr accessor!
results = (
mrsi_data
.xmr.zero_fill(target_points=2048)
.xmr.apodize_exp(lb=5.0)
.xmr.to_spectrum()
.xmr.autophase()
)We use uv for lightning-fast dependency management and Ruff for linting/formatting. To set up a local development environment:
-
Fork this repository and then clone your version of this repository.
-
Sync the environment and install dependencies:
uv sync
- Run tests via
pytest(which includes notebook testing vianbmake):
uv run test
- Build the MyST based documentation :
uv run docs
More information can be found in the documentation here
xmris is licensed under the GNU Affero General Public License v3.0 (AGPLv3).