Merge pull request #81 from rmarkello/von_economo

[ENH] Adds von Economo-Koskinas atlas fetcher

Author: rmarkello

docs/api.rst

@@ -153,6 +153,7 @@ Functions to download atlases and templates
     fetch_pauli2018
     fetch_schaefer2018
     fetch_hcp_standards
+    fetch_voneconomo
 
 Functions to download real-world datasets
 

netneurotools/data/osf.json

@@ -351,5 +351,12 @@
             ],
             "md5": "d8378f33107ed5d98c27e8070ebb5aa2"
         }
+    },
+    "atl-voneconomo_koskinas": {
+        "url": [
+            "mb37e",
+            "5ed80005fabc45000d639900"
+        ],
+        "md5": "28fb2bb04fbb2a1d65428364b48cf6ac"
     }
 }

netneurotools/datasets/__init__.py

@@ -6,12 +6,12 @@
     'fetch_cammoun2012', 'fetch_pauli2018', 'fetch_fsaverage', 'fetch_conte69',
     'fetch_connectome', 'available_connectomes', 'fetch_vazquez_rodriguez2019',
     'fetch_mirchi2018', 'make_correlated_xy', 'fetch_schaefer2018',
-    'fetch_hcp_standards'
+    'fetch_hcp_standards', 'fetch_voneconomo'
 ]
 
 from .fetchers import (fetch_cammoun2012, fetch_pauli2018, fetch_fsaverage,
                        fetch_conte69, fetch_connectome, available_connectomes,
                        fetch_vazquez_rodriguez2019, fetch_schaefer2018,
-                       fetch_hcp_standards)
+                       fetch_hcp_standards, fetch_voneconomo)
 from .generators import (make_correlated_xy)
 from .mirchi import (fetch_mirchi2018)

netneurotools/datasets/fetchers.py

@@ -608,3 +608,62 @@ def fetch_hcp_standards(data_dir=None, url=None, resume=True, verbose=1):
     _fetch_files(data_dir, files=files, resume=resume, verbose=verbose)
 
     return op.join(data_dir, dataset_name)
+
+
+def fetch_voneconomo(data_dir=None, url=None, resume=True, verbose=1):
+    """
+    Fetches von-Economo Koskinas probabilistic FreeSurfer atlas
+
+    Parameters
+    ----------
+    data_dir : str, optional
+        Path to use as data directory. If not specified, will check for
+        environmental variable 'NNT_DATA'; if that is not set, will use
+        `~/nnt-data` instead. Default: None
+    url : str, optional
+        URL from which to download data. Default: None
+    resume : bool, optional
+        Whether to attempt to resume partial download, if possible. Default:
+        True
+    verbose : int, optional
+        Modifies verbosity of download, where higher numbers mean more updates.
+        Default: 1
+
+    Returns
+    -------
+    filenames : :class:`sklearn.utils.Bunch`
+        Dictionary-like object with keys of format '{}Parcels{}Networks' where
+        corresponding values are the left/right hemisphere annotation files
+
+    References
+    ----------
+    Scholtens, L. H., de Reus, M. A., de Lange, S. C., Schmidt, R., & van den
+    Heuvel, M. P. (2018). An MRI von Economo–Koskinas atlas. NeuroImage, 170,
+    249-256.
+
+    Notes
+    -----
+    License: CC-BY-NC-SA 4.0
+    """
+
+    dataset_name = 'atl-voneconomo_koskinas'
+    keys = ['gcs', 'ctab']
+
+    data_dir = _get_data_dir(data_dir=data_dir)
+    info = _get_dataset_info(dataset_name)
+    if url is None:
+        url = info['url']
+    opts = {
+        'uncompress': True,
+        'md5sum': info['md5'],
+        'move': '{}.tar.gz'.format(dataset_name)
+    }
+    filenames = [
+        'atl-vonEconomoKoskinas_hemi-{}_probabilistic.{}'.format(hemi, suff)
+        for hemi in ['L', 'R'] for suff in ['gcs', 'ctab']
+    ]
+    files = [(op.join(dataset_name, f), url, opts) for f in filenames]
+    data = _fetch_files(data_dir, files=files, resume=resume, verbose=verbose)
+    data = [ANNOT(*data[n::2]) for n in range(len(keys))]
+
+    return Bunch(**dict(zip(keys, data)))

netneurotools/freesurfer.py

@@ -109,7 +109,7 @@ def _decode_list(vals):
     """ List decoder
     """
 
-    return [l.decode() if hasattr(l, 'decode') else l for l in vals]
+    return [val.decode() if hasattr(val, 'decode') else val for val in vals]
 
 
 def find_parcel_centroids(*, lhannot, rhannot, method='surface',

netneurotools/tests/test_datasets.py

@@ -148,6 +148,11 @@ def test_fetch_hcp_standards(tmpdir):
     assert os.path.isdir(hcp)
 
 
+def test_fetch_voneconomo(tmpdir):
+    vek = datasets.fetch_voneconomo(data_dir=tmpdir, verbose=0)
+    assert all(hasattr(vek, k) and len(vek[k]) == 2 for k in ['gcs', 'ctab'])
+
+
 @pytest.mark.parametrize('dset, expected', [
     ('atl-cammoun2012', ['fsaverage', 'fsaverage5', 'fsaverage6', 'fslr32k',
                          'MNI152NLin2009aSym', 'gcs']),