nifti-mrs-plus

Efficient, backend-agnostic batching of NIfTI-MRS spectra

nifti-mrs-plus wraps a list of NIfTI-MRS objects into a single batch-aware tensor, keeping the header, dimension tags, and provenance intact. It materializes in whatever backend your pipeline needs (NumPy, PyTorch, JAX, TensorFlow, or Keras) with no code changes.

Install

pip install nifti-mrs-plus                   # core (numpy + nifti-mrs)
pip install "nifti-mrs-plus[torch]"          # + PyTorch
pip install "nifti-mrs-plus[viz]"            # + plotting (matplotlib + fsl-mrs)
pip install "nifti-mrs-plus[all]"            # everything

Extras: torch · jax · tensorflow · keras · viz · hdf5 · all · dev

Quick start

from nifti_mrs_plus import NIfTI_MRS_Plus, Backend

batch = NIfTI_MRS_Plus(nifti_list)

batch.shape                          # (8, 1, 1, 1, 2048)
batch.numpy()                        # np.ndarray, cached
batch.get_data(Backend.PYTORCH)      # torch.Tensor  (if torch installed)
batch[0]                             # NIFTI_MRS  (single subject)
batch[0:4]                           # NIfTI_MRS_Plus  (sub-batch)

Backends

Extra	Backend	Returns
(none)	`NIFTI_LIST`	`list[NIFTI_MRS]`
(none)	`NUMPY`	`numpy.ndarray`
`torch`	`PYTORCH`	`torch.Tensor`
`jax`	`JAX`	`jax.Array`
`tensorflow`	`TENSORFLOW`	`tf.Tensor`
`keras`	`KERAS`	`KerasTensor`

_{Built with ❤️ for the MRS community}

Metadata

Release files for nifti-mrs-plus 0.2.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for nifti-mrs-plus 0.2.0
File	Size	Uploaded
nifti_mrs_plus-0.2.0.tar.gz	47.3 kB	Sep 7, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for nifti-mrs-plus 0.2.0
File	Interpreter	ABI	Platform	Reset
nifti_mrs_plus-0.2.0-py3-none-any.whl 40.4 kB Sep 7, 2026	Python 3	none	any	Details

Total release size: 87.7 kB

Release files / nifti_mrs_plus-0.2.0.tar.gz

Download URL	nifti_mrs_plus-0.2.0.tar.gz
Size	47.3 kB
Tags	Source
SHA-256 checksum How to use checksums	`b850b5b4148ae9e40f2732adf1db95f4da1b20a4acead3a4b067b3af16fe38c7`
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Upload date	Sep 7, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.2.0 CPython/3.9.6`

Release files / nifti_mrs_plus-0.2.0-py3-none-any.whl

Download URL	nifti_mrs_plus-0.2.0-py3-none-any.whl
Size	40.4 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`e0377397819d1a7765e03b374a9444c5a2d7711343dec7e75894cc6dcaa2b730`
BLAKE2b-256 checksum How to use checksums	`37ca0179aac6a9a574b905ef8a577115ccaafea4dd83a1357849ebf69505bab1`
Upload date	Sep 7, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.2.0 CPython/3.9.6`