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app-temporal-filtering
app under development Private app on bl
This App aims at apply to MEG signals temporal filtering (lowpass, highpass, or bandpass) on epoched or continuous data. To do so, the MNE Python functions raw.filter and Epoch.filter are used.
The filter function is the same for epoched and raw data but the value of the pad parameter is not the same if the data is continuous or epoched.
GitHub repository
GitHub - brainlife/app-temporal-filtering: Filter MEG signals using MNE Python
Brainlife datatype used:
For input: neuro/meg/fif
For outputs: neuro/meg/fif and report/html
Inputs of the App
Files | Format | Datatype | Description | Optional |
---|---|---|---|---|
MEG signals | .fif | meg/fif | The data can be continuous or epoched. Notch filtering and resampling can have been applied beforehand. | No |
Outputs of the App:
Files | Format | Datatype | Description |
---|---|---|---|
MEG signals | .fif | meg/fif | Data after filtering |
Report | .html | html | Visualization in time and frequency domains |
Besides, in the output directory, there are the optional files that can be used in a next App (see How to run Apps one after another).
Parameters of the App
The parameters of the App correspond to the parameters passed to the Python functions used in the App. Their default values proposed in Brainlife or in config.json.example
correspond to the default values of MNE Python 0.23.
The parameter iir_params
can’t be used on BL (it’s set to “READ ONLY”) because it is a dictionary and BL doesn’t handle Python dictionaries as parameter values and no conversion script has been written in the python file of this app (see Parameters conversion to make an App run on BL).
Next improvements
Be able to use the
iir_params
: register this parameter as aSTRING
in BL and convert it into a Python dict intemporal_filtering.py
Allow user to change the plot parameters for the plots in the HTML report?