def setup(self, n_components, coord_type):
self.data_dir = Path(
__file__).parent.parent / "gallery" / "neurolang_data"
self.resolution = 3
self.mask = load_mni_atlas(data_dir=self.data_dir,
resolution=self.resolution)
def load_voxels(nl, region_voxels, difumo_meta):
nl.add_tuple_set(region_voxels, name="RegionVoxel")
nl.add_tuple_set({("ContA",), ("ContB",)}, name="Network")
nl.add_tuple_set(
set(
(row["Yeo_networks17"], row["Difumo_names"])
for _, row in difumo_meta.iterrows()
if row["Yeo_networks17"] in ("ContA", "ContB")
),
name="NetworkRegion",
)
# %%
resolution = 3
mni_mask = data_utils.load_mni_atlas(data_dir=data_dir, resolution=resolution)
# %%
coord_type = "ijk"
peak_reported, study_ids = data_utils.fetch_neuroquery_peak_data(
mask=mni_mask, coord_type=coord_type, data_dir=data_dir
)
# %%
n_difumo_components = 128
region_voxels, difumo_meta = data_utils.fetch_difumo(
mask=mni_mask,
coord_type=coord_type,
n_components=n_difumo_components,
data_dir=data_dir,
def setup(self, tfidf_threshold, coord_type, convert_study_ids):
self.data_dir = Path(
__file__).parent.parent / "gallery" / "neurolang_data"
self.resolution = 3
self.mask = load_mni_atlas(data_dir=self.data_dir,
resolution=self.resolution)