Skip to main content

spm-runtime

Compiled Statistical Parametric Mapping (SPM) package that can be called from Python.

This package contains the compiled SPM runtime used by spm-python.

Installation

# Version built against the latest available MATLAB runtime
$ pip install spm-runtime
$ pip install spm-runtime==25.01
# Version built against a specific version of the MATLAB runtime
$ pip install spm-runtime-R2024b
$ pip install spm-runtime-R2024b==25.01

[!WARNING] The repository does not contain the compiled CTF file, but wheels released on pypi or as part of our GitHub releases do. It is not advised to install spm-runtime directly from the repository, as it assumes that the matlab compiler is available. Installation from our releases wheels and distributions is preferred.

Supported Python versions

Different versions of the MATLAB runtime are compatible with a different range of python versions. To use the runtime with a python version that is not supported by the latest MATLAB runtime, you can choose to install a package specifically compiled against another MATLAB runtime. The python versions supported by each MATLAB runtime is provided in the table below:

MATLAB Python
R2025b 3.10 - 3.13
R2025a 3.9 - 3.12
R2024b 3.9 - 3.12
R2024a 3.9 - 3.11
R2023b 3.9 - 3.11
R2023a 3.8 - 3.10
R2022b 3.8 - 3.10
R2022a 3.8 - 3.9
R2021b 3.7 - 3.9
R2021a 3.7 - 3.8
R2020b 3.6 - 3.8
R2020a 3.6 - 3.7

SPM standalone

On installation, spm-runtime exposes the SPM standalone, which can be executed in a terminal by calling spm.

$ spm --help

SPM - Statistical Parametric Mapping
https://www.fil.ion.ucl.ac.uk/spm/

Usage: spm [ fmri | eeg | pet ]
       spm COMMAND [arg...]
       spm [ -h | --help | -v | --version ]

Commands:
    batch          Run a batch job
    script         Execute a script
    function       Execute a function
    eval           Evaluate a MATLAB expression
    [NODE]         Run a specified batch node

Options:
    -h, --help     Print usage statement
    -v, --version  Print version information

Run 'spm [NODE] help' for more information on a command.

Python runtime

This package ships a compiled version of SPM that can be called from Python:

import spm_runtime

spm_runtime.endpoint("spm_standalone", nargout=0)

All MATLAB functions from the SPM package can be called. However, the inputs and outputs of these bindings are not very user-friendly. For pythonic bindings, use the spm-python package (which uses spm-runtime under the hood).

Release files for spm-runtime-R2025b 25.1.2.post2

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

Source distribution (sdist)

Source distribution for spm-runtime-R2025b 25.1.2.post2
File Size Uploaded
spm_runtime_r2025b-25.1.2.post2.tar.gz 81.8 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for spm-runtime-R2025b 25.1.2.post2
File Interpreter ABI Platform
spm_runtime_r2025b-25.1.2.post2-py3-none-any.whl Python 3 none any Details

Total release size: 163.5 MB

Release files / spm_runtime_r2025b-25.1.2.post2.tar.gz

Download URL spm_runtime_r2025b-25.1.2.post2.tar.gz
Size 81.8 MB
Tags Source
SHA-256 checksum
How to use checksums
c55326c53d3b76f8c25adf407dee8d305d5d63d237b38c9403357475699cd445
BLAKE2b-256 checksum
How to use checksums
774514a6f703460d599d17cf291b8a5bce4e92e417ce7455042f3e9b723ce25b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Jan 6, 2026.

Transparency log

Release files / spm_runtime_r2025b-25.1.2.post2-py3-none-any.whl

Download URL spm_runtime_r2025b-25.1.2.post2-py3-none-any.whl
Size 81.8 MB
Tags Python 3
SHA-256 checksum
How to use checksums
1a3c41d79680d38c7fdd86c50f6139b982b96735e069e91c83da886139085a46
BLAKE2b-256 checksum
How to use checksums
c40255d9e33920d831fc473e7bcab2be4cdedb94693ebb9eae0d0486ab04688a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Jan 6, 2026.

Transparency log

Release history Release notifications | RSS feed

This release

25.1.2.post2 This release

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page