YA_Colab Code

BidsConvert module:

Create, manipulate, validate and present a BIDS compliant directory.

Class BidsGenerator

contains several functions aimed at generating the main sub directories for the BIDS compliant dataset. (i.e, converting the raw dicom files to BIDS-sorted niftis)

Initialize a class that creates/validates/presents a BIDS compliant directory.

• Arguments:
  • raw {str} -- Path to a directory that contains the raw dicom files. (sourcedata)
  • bids_dir {str} -- Path to the directory to initialize as a BIDS compliant one.

Usage:

>>> from Code import BidsConvert
>>> gen_bids = BidsConvert.BidsGenerator(
bids_dir = '/path/to/your/bids_dir',
raw = '/path/to/your/raw_data')

• Note that the raw directory should contain subdirectories with name such as "sub-XX"

>>> gen_bids.run()

Output:

A BIDS compliant directory, containing the niftis converted from the raw dicom directory.

• bids_dataset/
  • sub-01/
    • dwi/
      • sub-01_acq-AP_dwi.bvec
      • sub-01_acq-AP_dwi.nii
      • sub-01_acq-AP_dwi.bval
      • sub-01_acq-AP_dwi.json
    • fmap/
      • sub-01_acq-PA_dwi.nii
      • sub-01_acq-PA_dwi.json
    • anat/
      • sub-01_acq-T1w.nii
      • sub-01_acq-T2w.json
      • sub-01_acq-T2w.nii
      • sub-01_acq-T1w.json
    • func/
      • sub-01_task-rest_bold.nii
      • sub-01_task-rest_sbref.nii
      • sub-01_task-rest_sbref.json
      • sub-01_task-rest_bold.json
  • sub-02/
  • .
  • .
  • .

Class FilesGenerator

Contains several functions aimed at generating BIDS compliant dataset descriptive files. (i.e, dataset_description.json and participants.tsv)

• Note that this class does not create the recommended README file, as it should be manually created by the researcher.

Generate BIDS compliant dataset description file and participants file (based on a template and CRF file)

• Arguments:
  • bids_dir {str} -- Path to the directory to initialize as a BIDS compliant one. subj_temp {str} -- Participant template file as can be obtained here.
  • crf {str} -- A CRF files containing data regarding the participants in the dataset.
  • ds_temp (str) -- Path to a dataset description template as can also be obtained here

Usage:

>>> from Code import BidsConvert
>>> gen_files = BidsConvert.Generate_Files(
bids_dir = '/path/to/your/bids_dir',
subj_temp = '/path/to/paticipants_template.tsv',
crf = '/path/to/CRF.xlsx',
ds_temp = '/path/to/dataset_description.json)
>>> gen_files.run()

Output:

The dataset descriptive files, as demended by the BIDS specifications.

• bids_dataset/
  • dataset_description.json
  • participants.tsv

dataset_description.json:

{
"Name": "[Name of your bids dataset directory]",
"BIDSVersion": "1.0.2",
"License": "",
"Authors": [
"",
"",
""
],
"Acknowledgements": "",
"HowToAcknowledge": "",
"Funding": [
"",
"",
""
],
"ReferencesAndLinks": [
"",
"",
""
],
"DatasetDOI": ""
}

participants.tsv:

participant_id	age	handedness	sex
sub-01	18	r	m
sub-02	.	.	.
.
.
.