Load a BIDS Dataset

Load a BIDS Dataset#

Before you can query or modify your data, you need to make your dataset available to ancpBIDS. This involves two steps: fetching the dataset and creating a layout to represent its structure.

Fetch an existing BIDS dataset#

ancpBIDS is able to find and load specific files from your PC. With ´fetch_dataset()´,ancpBIDS will be able to fetch it even if you haven’t unzip your dataset. The output, ´dataset_path´, will contain the local path to it and within your PC folder ‘~/.ancp-bids/datasets’ you will find the zip file (f.e. ds005-testdata.zip) and the content extracted. If you run the code again, it won’t create unnecessary copies.

from ancpbids import utils
dataset_path = utils.fetch_dataset('ds005')

from ancpbids import utils
dataset_path = utils.fetch_dataset('ds003483')

Creating a Layout#

Once you fetch the path to our dataset folder, we can use ´BIDSLayout()´ to create the in-memory graph of your dataset, from where you can easily retrieve information. Both the dataset and the schema are accessible through the layout object.

from ancpbids.pybids_compat import BIDSLayout
layout = BIDSLayout(dataset_path)

In-memory graph?

If you want to learn more how ancpBIDS uses the BIDS specification to build the in-memory graph representation (and what exactly is a in-memory graph representation), follow this link.

Load a dataset#

Thanks to BIDSLayout your dataset it’s already loaded within the layout variable. But you may also use the function ´load_dataset()´ along with the dataset_path you queried before to load the dataset.

Warning

If you load your dataset with load_dataset(), you won’t have access to the BIDS Schema. Therefore, we suggest you to use BIDSLayout instead.

from ancpbids import load_dataset
dataset = load_dataset(dataset_path)
#print(dataset)
#{'name': 'ds003483'}

from ancpbids import load_dataset, DatasetOptins
dataset = load_dataset(dataset_path, DatasetOptions(ignore=False, infer_artifact_datatype=True))
#print(dataset)
#{'name': 'ds003483'}

Next section#

Now that your dataset is loaded and mapped into a layout, you’re ready to start extracting useful information from it. In the next sections, we’ll show how to:

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