mvpa2.datasets.sources.native.load_tutorial_data(path=None, roi='brain', add_fa=None, flavor=None)

Loads the block-design demo dataset from PyMVPA dataset DB.


path : str, optional

Path to the directory with the extracted content of the tutorial data package. This is only necessary for accessing the full resolution data. The 1slice, and 25mm flavors are shipped with PyMVPA itself, and the path argument is ignored for them. This function also honors the MVPA_LOCATION_TUTORIAL_DATA environment variable, and the respective configuration setting.

roi : str or int or tuple or None, optional

Region Of Interest to be used for masking the dataset. If a string is given a corresponding mask image from the demo dataset will be used (mask_<str>.nii.gz). If an int value is given, the corresponding ROI is determined from the atlas image (mask_hoc.nii.gz). If a tuple is provided it may contain int values that a processed as explained before, but the union of a ROIs is taken to produce the final mask. If None, no masking is performed.

add_fa : dict, optional

Passed on to the dataset creator function (see fmri_dataset() for more information).

flavor: str, optional

Resolution flavor of the data to load. By default, the data is loaded in its original resolution. The PyMVPA source distribution contains a ‘25mm’ flavor that has been downsampled to a very coarse resolution and can be used for quick test execution. Likewise a 1slice flavor is available that contents a full-resultion single-slice subset of the dataset.