dipy_fetch#

Synopsis#

Download files to folder and check their md5 checksums.

To see all available datasets, please type “list” in data_names.

Usage#

dipy_fetch [OPTIONS] data_names

Input Parameters#

  • data_names

    Any number of Nifti1, bvals or bvecs files.

General Options#

  • --subjects

    Identifiers of the subjects to download. Used only by the HBN & HCP dataset. For example with HBN dataset: –subject NDARAA948VFH NDAREK918EC2 (default: None)

  • --include_optional

    Include optional datasets. (default: False)

  • --include_afq

    Whether to include pyAFQ derivatives. Used only by the HBN dataset. (default: False)

  • --hcp_bucket

    The name of the HCP S3 bucket. (default: hcp-openaccess)

  • --hcp_profile_name

    The name of the AWS profile used for access. (default: hcp)

  • --hcp_study

    Which HCP study to grab. (default: HCP_1200)

  • --hcp_aws_access_key_id

    AWS credentials to HCP AWS S3. Will only be used if profile_name is set to False. (default: None)

  • --hcp_aws_secret_access_key

    AWS credentials to HCP AWS S3. Will only be used if profile_name is set to False. (default: None)

Output Options#

  • --out_dir

    Output directory. (default: current directory)

References#

Garyfallidis, E., M. Brett, B. Amirbekian, A. Rokem, S. Van Der Walt, M. Descoteaux, and I. Nimmo-Smith. Dipy, a library for the analysis of diffusion MRI data. Frontiers in Neuroinformatics, 1-18, 2014.

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