Set of tools for downloading and accessing open-license neuroimaging data in a consistent format.
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nidata
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README.md

nidata - neuroimaging dataset download and formatting

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Goals

The goal of this tool is to offer a simple interface for downloading, storing, and getting access to neuroimaging datasets. We want to:

  • Decrease the amount of time spent by data scientists in accessing new datasets
  • Decrease the difficulty of scientists in sharing their data with the world
  • Increase the visibility of available data

Data types

The types of data we wish to expose include:

  • MRI / tMRI / rsMRI / dMRI

Known data sources

Not all data sources have been implemented. Our list of known data sources can be found here: https://github.com/nidata/nidata/wiki/Data-sources

Current data sources will be available via the website, when implemented: http://nidata.github.io/

Dependencies

nidata is tested in Python 2.7, and 3.5. The only package-level dependencies are pip, numpy, and nibabel .

Individual datasets may have package dependencies for downloads or examples. If so, nidata attempts to install them via pip. These packages include:

  • nilearn - Machine learning for neuroimaging, contains generic download tools and logic for accessing fMRI datasets

Installation

sudo pip install git+https://github.com/nidata/nidata

Usage

To run an example, python nidata/multimodal/hcp/example1.py

To download data,

from nidata.multimodal import HcpDataset
HcpDataset(username=#####, passwd=######).fetch(n_subjects=1, data_types=['anat'])