Merge pull request #510 from FZJ-INM1-BDA/increase_intensity_profile_…

…compounding_speed

Increase intensity profile compounding speed

siibra/features/anchor.py

@@ -26,7 +26,7 @@
 
 from ..vocabularies import REGION_ALIASES
 
-from typing import Union, List, Dict
+from typing import Union, List, Dict, Iterable
 
 
 class AnatomicalAnchor:
@@ -46,7 +46,7 @@ def __init__(
 
         if isinstance(species, (str, Species)):
             self.species = {Species.decode(species)}
-        elif isinstance(species, list):
+        elif isinstance(species, Iterable):
             assert all(isinstance(_, Species) for _ in species)
             self.species = set(species)
         else:

siibra/features/feature.py

@@ -672,6 +672,10 @@ def _element_index(self) -> Any:
         assert hash(index), "`_element_index` of a compoundable must be hashable."
         return index
 
+    @classmethod
+    def _merge_anchors(cls, anchors: List[_anchor.AnatomicalAnchor]):
+        return sum(anchors)
+
 
 class CompoundFeature(Feature):
     """
@@ -716,7 +720,7 @@ def __init__(
             self,
             modality=modality,
             description="\n".join({f.description for f in elements}),
-            anchor=sum([f.anchor for f in elements]),
+            anchor=self._feature_type._merge_anchors([f.anchor for f in elements]),
             datasets=list(dict.fromkeys([ds for f in elements for ds in f.datasets]))
         )
         self._queryconcept = queryconcept

siibra/features/tabular/bigbrain_intensity_profile.py

@@ -15,7 +15,9 @@
 
 from . import cortical_profile
 
-from ...locations import point
+from typing import List, TYPE_CHECKING
+if TYPE_CHECKING:
+    from ...features.anchor import AnatomicalAnchor
 
 
 class BigBrainIntensityProfile(
@@ -38,18 +40,11 @@ class BigBrainIntensityProfile(
 
     def __init__(
         self,
-        regionname: str,
+        anchor: "AnatomicalAnchor",
         depths: list,
         values: list,
-        boundaries: list,
-        location: point.Point
+        boundaries: list
     ):
-        from ..anchor import AnatomicalAnchor
-        anchor = AnatomicalAnchor(
-            location=location,
-            region=regionname,
-            species='Homo sapiens'
-        )
         cortical_profile.CorticalProfile.__init__(
             self,
             description=self.DESCRIPTION,
@@ -67,3 +62,19 @@ def __init__(
     @property
     def location(self):
         return self.anchor.location
+
+    @classmethod
+    def _merge_anchors(cls, anchors: List['AnatomicalAnchor']):
+        from ...locations.pointset import PointSet
+        from ...features.anchor import AnatomicalAnchor
+
+        location = PointSet(
+            [anchor.location for anchor in anchors],
+            space="BigBrain"
+        )
+        regions = {anchor._regionspec for anchor in anchors}
+        return AnatomicalAnchor(
+            location=location,
+            region=", ".join(regions),
+            species='Homo sapiens'
+        )

siibra/features/tabular/layerwise_bigbrain_intensities.py

@@ -19,6 +19,10 @@
 import pandas as pd
 import numpy as np
 
+from typing import TYPE_CHECKING
+if TYPE_CHECKING:
+    from ...features.anchor import AnatomicalAnchor
+
 
 class LayerwiseBigBrainIntensities(
     tabular.Tabular,
@@ -39,16 +43,10 @@ class LayerwiseBigBrainIntensities(
 
     def __init__(
         self,
-        regionname: str,
+        anchor: "AnatomicalAnchor",
         means: list,
         stds: list,
     ):
-
-        from ..anchor import AnatomicalAnchor
-        anchor = AnatomicalAnchor(
-            region=regionname,
-            species='Homo sapiens',
-        )
         data = pd.DataFrame(
             np.array([means, stds]).T,
             columns=['mean', 'std'],

siibra/livequeries/bigbrain.py

@@ -94,12 +94,16 @@ def query(self, concept: structure.BrainStructure, **kwargs) -> List[bigbrain_in
         assert isinstance(matched, (point.Point, pointset.PointSet))
         assert matched.labels is not None
         for i in matched.labels:
+            anchor = _anchor.AnatomicalAnchor(
+                location=point.Point(loader._vertices[i], space='bigbrain'),
+                region=str(concept),
+                species='Homo sapiens'
+            )
             prof = bigbrain_intensity_profile.BigBrainIntensityProfile(
-                regionname=str(concept),
+                anchor=anchor,
                 depths=loader.profile_labels,
                 values=loader._profiles[i],
-                boundaries=loader._boundary_depths[i],
-                location=point.Point(loader._vertices[i], space='bigbrain')
+                boundaries=loader._boundary_depths[i]
             )
             prof.anchor._assignments[concept] = _anchor.AnatomicalAssignment(
                 query_structure=concept,
@@ -137,12 +141,16 @@ def query(self, concept: structure.BrainStructure, **kwargs) -> List[layerwise_b
             for b in boundary_depths
         ]).reshape((-1, 200))
 
+        anchor = _anchor.AnatomicalAnchor(
+            location=pointset.PointSet(loader._vertices[indices, :], space='bigbrain'),
+            region=str(concept),
+            species='Homo sapiens'
+        )
         result = layerwise_bigbrain_intensities.LayerwiseBigBrainIntensities(
-            regionname=str(concept),
+            anchor=anchor,
             means=[matched_profiles[layer_labels == layer].mean() for layer in range(1, 7)],
             stds=[matched_profiles[layer_labels == layer].std() for layer in range(1, 7)],
         )
-        result.anchor._location_cached = pointset.PointSet(loader._vertices[indices, :], space='bigbrain')
         result.anchor._assignments[concept] = _anchor.AnatomicalAssignment(
             query_structure=concept,
             assigned_structure=concept,