2. One line to (almost) run them all

Physprep is a Command Line Interface (CLI) that automatically (pre)processed and assessed the quality of peripheral physiological data. It takes in input a configuration file and a BIDS directory containing raw physiological data, and return cleaned timeseries, extracted features, quality assessment and summary quality report.

For this example, we will create a BIDS dataset with simulated data using a function in the physprep data submodule.

from physprep.data import data

# Let's see what parameters this function can take
help(data.create_bids_dataset)
# Let's create the dataset
data.create_bids_dataset('/path/to/save/those/data')

Once the dataset has been created, we can run the command in our terminal !

Warning

Make sure you have installed Physprep in your virtual environment before.

For this example, we will use the default configuration file provided in Physprep, i.e. the neuromod json file. You can also replace that first argument by your configuration file that you have created previously (see using configuration files). We will also specified the path where our raw physio data are, the subject id, the session id, the path where we want to save the derivatives, and the –save_report flag to save a summary descriptive report of our preprocessed signals.

Note

To run the pipeline on all subjects and sessions in your raw physio directory, do not use the –sub` and –ses arguments

physprep 'neuromod' '/path/where/the/simulated/data/have/been/saved' --sub '01' --ses '001' --derivatives_dir '/path/to/save/derivatives/' --save_report