Allow generic tabular and image features

siibra/configuration/factory.py

@@ -25,13 +25,14 @@
 from ..commons import logger, Species
 from ..features import anchor, connectivity
 from ..features.tabular import (
+    tabular,
     receptor_density_profile,
     receptor_density_fingerprint,
     cell_density_profile,
     layerwise_cell_density,
     regional_timeseries_activity,
 )
-from ..features.image import sections, volume_of_interest
+from ..features.image import image, sections, volume_of_interest
 from ..core import atlas, parcellation, space, region
 from ..locations import point, pointcloud, boundingbox
 from ..retrieval import datasets, repositories
@@ -391,6 +392,19 @@ def build_receptor_density_fingerprint(cls, spec):
             prerelease=spec.get("prerelease", False),
         )
 
+    @classmethod
+    @build_type("siibra/feature/tabular/v0.1")
+    def build_generic_tabular(cls, spec):
+        return tabular.Tabular(
+            file=spec["file"],
+            description=spec.get("description"),
+            modality=spec.get("modality"),
+            anchor=cls.extract_anchor(spec),
+            datasets=cls.extract_datasets(spec),
+            id=spec.get("@id", None),
+            prerelease=spec.get("prerelease", False),
+        )
+
     @classmethod
     @build_type("siibra/feature/fingerprint/celldensity/v0.1")
     def build_cell_density_fingerprint(cls, spec):
@@ -492,6 +506,22 @@ def build_volume_of_interest(cls, spec):
                 f"No method for building image section feature type {modality}."
             )
 
+    @classmethod
+    @build_type("siibra/feature/image/v0.1")
+    def build_generic_image_feature(cls, spec):
+        kwargs = {
+            "name": spec.get("name"),
+            "modality": spec.get("modality"),
+            "region": spec.get("region", None),
+            "space_spec": spec.get("space"),
+            "providers": cls.build_volumeproviders(spec.get("providers")),
+            "datasets": cls.extract_datasets(spec),
+            "bbox": cls.build_boundingbox(spec),
+            "id": spec.get("@id", None),
+            "prerelease": spec.get("prerelease", False),
+        }
+        return image.Image(**kwargs)
+
     @classmethod
     @build_type("siibra/feature/connectivitymatrix/v0.3")
     def build_connectivity_matrix(cls, spec):

siibra/features/image/image.py

@@ -53,7 +53,12 @@ def __str__(self):
         return f"Bounding box of image in {self.space.name}"
 
 
-class Image(feature.Feature, _volume.Volume):
+class Image(
+    feature.Feature,
+    _volume.Volume,
+    configuration_folder="features/images",
+    category="generic"
+):
 
     def __init__(
         self,

siibra/features/tabular/receptor_density_fingerprint.py

@@ -55,12 +55,12 @@ def __init__(
             description=self.DESCRIPTION,
             modality="Neurotransmitter receptor density",
             anchor=anchor,
+            file=tsvfile,
             data=None,  # lazy loading below
             datasets=datasets,
             id=id,
             prerelease=prerelease,
         )
-        self._loader = requests.HttpRequest(tsvfile)
 
     @property
     def unit(self) -> str:

siibra/features/tabular/tabular.py

@@ -22,9 +22,10 @@
 from .. import feature
 from .. import anchor as _anchor
 from ...commons import logger
+from ...retrieval import requests
 
 
-class Tabular(feature.Feature):
+class Tabular(feature.Feature, category="generic", configuration_folder="features/tabular"):
     """
     Represents a table of different measures anchored to a brain location.
 
@@ -42,7 +43,8 @@ def __init__(
         description: str,
         modality: str,
         anchor: _anchor.AnatomicalAnchor,
-        data: pd.DataFrame,  # sample x feature dimension
+        file: str = None,
+        data: pd.DataFrame = None,  # sample x feature dimension
         datasets: list = [],
         id: str = None,
         prerelease: bool = False,
@@ -56,10 +58,19 @@ def __init__(
             id=id,
             prerelease=prerelease
         )
-        self._data_cached = data
+        if data is None:
+            if file is not None:
+                self._loader = requests.HttpRequest(file)
+            else:
+                self._data_cached = data
+        else:
+            self._loader = None
+            self._data_cached = data
 
     @property
     def data(self):
+        if self._loader is not None:
+            self._data_cached = self._loader.get()
         return self._data_cached.copy()
 
     def _to_zip(self, fh: ZipFile):