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Inputs of the App:
Files | Format | Datatype | Description | Optional |
|---|---|---|---|---|
MEG signal | .fif | meg/fif | first run | No |
MEG signal | .fif | meg/fif | second run | No |
… | … | … | … | Yes |
MEG signal | .fif | meg/fif | nth run | Yes |
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Output of the App:
Files | Format | Datatype | Description |
|---|---|---|---|
Raw file | .fif | meg/fif-override |
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Besides, in the output directory, there are the optional files we will use that can be used in a next App. This is mandatory, because the App that will be run after app-mean-transformation-matrix will can take as input all the files in app-mean-transformation-matrix’s matrix’s output directory corresponding to the datatype of the input of the next App (see How to run Apps one after another).
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The parameters of the App correspond to the parameters passed to the Python functions used in the App. They are listed in the Their default values proposed in Brainlife or in config.json.example when you test your App locally, then when you register you App on Brainlife, you enter them and a config.json is created by Brainlife.Here, we used the parameters set by default by mne correspond to the default values of MNE Python 0.23.
Next improvements
Rename it into “app-compute-realigment-matrix”?
Allow the user to compute a destination.fif that is not the mean of all the runs but a specific run ? (this option is available is
mne-bids-pipeline. To do so, it would be best not to save the entire .fif file (i.e. the MEG signalsignals) but to extract theraw.info[“dev_head_t"]["trans"]from this file run and put it in an empty fif file, like we do when we compute the mean of the runs (it would save space).Make sure that it is okay to run this app after of before
app-head-pos, the order must not matter.