___ ____ __ __
/ __)( _ \( \/ )
\__ \ )___/ ) ( Statistical Parametric Mapping
(___/(__) (_/\/\_) SPM - https://www.fil.ion.ucl.ac.uk/spm/
Copyright (C) 1991,1994-2024 Wellcome Centre for Human Neuroimaging
Warning
This project is currently under construction and might contain bugs. If you experience any issues, please let us know!
- Install Python and Pip. Python installation made from Microsoft Store on Windows will not work (raises DeclarativeService.dll not found), intall it from Python website.
- Install Matlab Runtime 2024b
- Install SPM:
pip install spm-python
- That's all!
Here is a minimal set of examples showcasing changes to do to use existing Matlab code in Python (taken from the OPM tutorial).
In Matlab:
spm('defaults', 'eeg');
In Python:
from spm import *
spm('defaults', 'eeg');
In Matlab:
S = [];
S.data = 'OPM_meg_001.cMEG';
S.positions = 'OPM_HelmConfig.tsv';
D = spm_opm_create(S);
In Python, create a Struct()
instead of a struct
:
S = Struct()
S.data='OPM_meg_001.cMEG'
S.positions='OPM_HelmConfig.tsv'
D = spm_opm_create(S)
Here, D
will be a meeg
object which contains a virtual representation of the Matlab object. Class methods should work as expected, e.g.:
D.fullfile()
>>> './OPM_meg_001.mat'
Note that the alternative call that exist in Matlab (i.e., fullfile(D)
) will not work.
In Matlab:
S = [];
S.triallength = 3000;
S.plot = 1;
S.D = D;
S.channels = 'MEG';
spm_opm_psd(S);
ylim([1,1e5])
In Python:
S = Struct()
S.triallength = 3000
S.plot = 1
S.D = D
S.channels = 'MEG'
spm_opm_psd(S)
This opens a Matlab figure, but we do not have the possibility of manipulating it yet (e.g., calling ylim
). As of now, we can view the figures, have GUI interactions, but cannot manipulate figures with Python code.
In Matlab:
S = [];
S.triallength = 3000;
S.plot = 1;
S.D = mD;
[~,freq] = spm_opm_psd(S);
In Python, the number of output arguments must be specified by the nargout
keyword argument:
S = Struct()
S.triallength = 3000
S.plot=1
S.D=mD
[_,freq] = spm_opm_psd(S, nargout=2)
In Matlab:
S=[];
S.D=D;
S.freq=[10];
S.band = 'high';
fD = spm_eeg_ffilter(S);
S = [];
S.D = fD;
S.freq = [70];
S.band = 'low';
fD = spm_eeg_ffilter(S);
In Python:
S = Struct()
S.D = D
S.freq = 10
S.band = 'high'
fD = spm_eeg_ffilter(S)
S = Struct()
S.D = fD
S.freq = 70
S.band = 'low'
fD = spm_eeg_ffilter(S)