addressing PR comments

crates/re_types/definitions/rerun/components/color.fbs

@@ -10,6 +10,10 @@ namespace rerun.components;
 // ---
 
 /// An RGBA color tuple with unmultiplied/separate alpha, in sRGB gamma space with linear alpha.
+///
+/// \py Float colors are assumed to be in 0-1 gamma sRGB space.
+/// \py All other colors are assumed to be in 0-255 gamma sRGB space.
+/// \py If there is an alpha, we assume it is in linear space, and separate (NOT pre-multiplied).
 struct Color (
   "attr.arrow.transparent",
   "attr.python.aliases": "int, npt.NDArray[np.uint8], npt.NDArray[np.uint32], npt.NDArray[np.float32], npt.NDArray[np.float64]",

rerun_py/rerun_sdk/rerun2/components/class_id_ext.py

@@ -2,18 +2,18 @@
 
 __all__ = ["ClassIdArrayExt"]
 
-from typing import Any, Sequence, Type
+from typing import Any, Sequence
 
 import numpy as np
 import pyarrow as pa
 
 
 class ClassIdArrayExt:
     @staticmethod
-    def _from_similar(data: Any | None, *, mono: type, mono_aliases: Type, many: type, many_aliases: Type, arrow: type):
+    def _from_similar(data: Any | None, *, mono: type, mono_aliases: type, many: type, many_aliases: type, arrow: type):
         if isinstance(data, Sequence) and (len(data) > 0 and isinstance(data[0], mono)):
             array = np.asarray([class_id.id for class_id in data], np.uint16)
         else:
-            array = np.require(np.asarray(data), np.uint16).flatten()
+            array = np.asarray(data, dtype=np.uint16).flatten()
 
         return arrow().wrap_array(pa.array(array, type=arrow().storage_type))

rerun_py/rerun_sdk/rerun2/components/color.py

@@ -14,7 +14,13 @@
 
 @dataclass
 class Color:
-    """An RGBA color tuple with unmultiplied/separate alpha, in sRGB gamma space with linear alpha."""
+    """
+    An RGBA color tuple with unmultiplied/separate alpha, in sRGB gamma space with linear alpha.
+
+    Float colors are assumed to be in 0-1 gamma sRGB space.
+    All other colors are assumed to be in 0-255 gamma sRGB space.
+    If there is an alpha, we assume it is in linear space, and separate (NOT pre-multiplied).
+    """
 
     rgba: int
 

rerun_py/rerun_sdk/rerun2/components/color_ext.py

@@ -2,17 +2,16 @@
 
 __all__ = ["ColorArrayExt"]
 
-from typing import Any, Sequence, Type
+from typing import Any, Sequence
 
 import numpy as np
 import pyarrow as pa
-
 from rerun.color_conversion import u8_array_to_rgba
 
 
 class ColorArrayExt:
     @staticmethod
-    def _from_similar(data: Any | None, *, mono: type, mono_aliases: Type, many: type, many_aliases: Type, arrow: type):
+    def _from_similar(data: Any | None, *, mono: type, mono_aliases: type, many: type, many_aliases: type, arrow: type):
         """
         Normalize flexible colors arrays.
 
@@ -33,7 +32,7 @@ def _from_similar(data: Any | None, *, mono: type, mono_aliases: Type, many: typ
             if array.dtype.type in [np.float32, np.float64]:
                 # Assume gamma-space colors
                 array = np.asarray(data).reshape((-1, 4))
-                array = u8_array_to_rgba(np.require(np.round(array * 255.0), np.uint8))
+                array = u8_array_to_rgba(np.asarray(np.round(array * 255.0), np.uint8))
             elif array.dtype.type == np.uint32:
                 array = np.asarray(data).flatten()
             else:

rerun_py/rerun_sdk/rerun2/components/draw_order_ext.py

@@ -2,15 +2,15 @@
 
 __all__ = ["DrawOrderArrayExt"]
 
-from typing import Any, Sequence, Type
+from typing import Any, Sequence
 
 import numpy as np
 import pyarrow as pa
 
 
 class DrawOrderArrayExt:
     @staticmethod
-    def _from_similar(data: Any | None, *, mono: type, mono_aliases: Type, many: type, many_aliases: Type, arrow: type):
+    def _from_similar(data: Any | None, *, mono: type, mono_aliases: type, many: type, many_aliases: type, arrow: type):
         if isinstance(data, Sequence) and (len(data) > 0 and isinstance(data[0], mono)):
             array = np.asarray([draw_order.value for draw_order in data], np.float32)
         else:

rerun_py/rerun_sdk/rerun2/components/instance_key_ext.py

@@ -2,18 +2,18 @@
 
 __all__ = ["InstanceKeyArrayExt"]
 
-from typing import Any, Sequence, Type
+from typing import Any, Sequence
 
 import numpy as np
 import pyarrow as pa
 
 
 class InstanceKeyArrayExt:
     @staticmethod
-    def _from_similar(data: Any | None, *, mono: type, mono_aliases: Type, many: type, many_aliases: Type, arrow: type):
+    def _from_similar(data: Any | None, *, mono: type, mono_aliases: type, many: type, many_aliases: type, arrow: type):
         if isinstance(data, Sequence) and (len(data) > 0 and isinstance(data[0], mono)):
             array = np.asarray([datum.value for datum in data], np.uint64)
         else:
-            array = np.require(np.asarray(data), np.uint64).flatten()
+            array = np.asarray(data, dtype=np.uint64).flatten()
 
         return arrow().wrap_array(pa.array(array, type=arrow().storage_type))

rerun_py/rerun_sdk/rerun2/components/keypoint_id_ext.py

@@ -2,18 +2,18 @@
 
 __all__ = ["KeypointIdArrayExt"]
 
-from typing import Any, Sequence, Type
+from typing import Any, Sequence
 
 import numpy as np
 import pyarrow as pa
 
 
 class KeypointIdArrayExt:
     @staticmethod
-    def _from_similar(data: Any | None, *, mono: type, mono_aliases: Type, many: type, many_aliases: Type, arrow: type):
+    def _from_similar(data: Any | None, *, mono: type, mono_aliases: type, many: type, many_aliases: type, arrow: type):
         if isinstance(data, Sequence) and (len(data) > 0 and isinstance(data[0], mono)):
             array = np.asarray([class_id.id for class_id in data], np.uint16)
         else:
-            array = np.require(np.asarray(data), np.uint16).flatten()
+            array = np.asarray(data, dtype=np.uint16).flatten()
 
         return arrow().wrap_array(pa.array(array, type=arrow().storage_type))

rerun_py/rerun_sdk/rerun2/components/label_ext.py

@@ -2,14 +2,14 @@
 
 __all__ = ["LabelArrayExt"]
 
-from typing import Any, Sequence, Type
+from typing import Any, Sequence
 
 import pyarrow as pa
 
 
 class LabelArrayExt:
     @staticmethod
-    def _from_similar(data: Any | None, *, mono: type, mono_aliases: Type, many: type, many_aliases: Type, arrow: type):
+    def _from_similar(data: Any | None, *, mono: type, mono_aliases: type, many: type, many_aliases: type, arrow: type):
         if isinstance(data, Sequence):
             array = [str(datum) for datum in data]
         else:

rerun_py/rerun_sdk/rerun2/components/point2d_ext.py

@@ -2,18 +2,20 @@
 
 __all__ = ["Point2DArrayExt"]
 
-from typing import Any, Sequence, Type
+from typing import Any, Sequence
 
 import numpy as np
 import pyarrow as pa
 
 
 class Point2DArrayExt:
     @staticmethod
-    def _from_similar(data: Any | None, *, mono: type, mono_aliases: Type, many: type, many_aliases: Type, arrow: type):
+    def _from_similar(data: Any | None, *, mono: type, mono_aliases: type, many: type, many_aliases: type, arrow: type):
         if isinstance(data, Sequence) and (len(data) > 0 and isinstance(data[0], mono)):
-            arrays = [np.asarray(datum) for datum in data]
+            points = np.concatenate([np.asarray(datum.position, dtype=np.float32) for datum in data])
         else:
-            arrays = np.require(np.asarray(data), np.float32).reshape((-1, 2)).tolist()
+            points = np.asarray(data, dtype=np.float32)
 
-        return arrow().wrap_array(pa.array(arrays, type=arrow().storage_type))
+        points = points.reshape((-1,))
+
+        return arrow().wrap_array(pa.FixedSizeListArray.from_arrays(points, type=arrow().storage_type))

rerun_py/rerun_sdk/rerun2/components/radius_ext.py

@@ -2,18 +2,18 @@
 
 __all__ = ["RadiusArrayExt"]
 
-from typing import Any, Sequence, Type
+from typing import Any, Sequence
 
 import numpy as np
 import pyarrow as pa
 
 
 class RadiusArrayExt:
     @staticmethod
-    def _from_similar(data: Any | None, *, mono: type, mono_aliases: Type, many: type, many_aliases: Type, arrow: type):
+    def _from_similar(data: Any | None, *, mono: type, mono_aliases: type, many: type, many_aliases: type, arrow: type):
         if isinstance(data, Sequence) and (len(data) > 0 and isinstance(data[0], mono)):
             array = np.asarray([radius.value for radius in data], np.float32)
         else:
-            array = np.require(np.asarray(data), np.float32).flatten()
+            array = np.asarray(data, dtype=np.float32).flatten()
 
         return arrow().wrap_array(pa.array(array, type=arrow().storage_type))

rerun_py/rerun_sdk/rerun2/datatypes/vec2d_ext.py

@@ -2,18 +2,20 @@
 
 __all__ = ["Vec2DArrayExt"]
 
-from typing import Any, Sequence, Type
+from typing import Any, Sequence
 
 import numpy as np
 import pyarrow as pa
 
 
 class Vec2DArrayExt:
     @staticmethod
-    def _from_similar(data: Any | None, *, mono: type, mono_aliases: Type, many: type, many_aliases: Type, arrow: type):
+    def _from_similar(data: Any | None, *, mono: type, mono_aliases: type, many: type, many_aliases: type, arrow: type):
         if isinstance(data, Sequence) and (len(data) > 0 and isinstance(data[0], mono)):
-            arrays = [np.asarray(datum) for datum in data]
+            points = np.concatenate([np.asarray(datum.position, dtype=np.float32) for datum in data])
         else:
-            arrays = np.require(np.asarray(data), np.float32).reshape((-1, 2)).tolist()
+            points = np.asarray(data, dtype=np.float32)
 
-        return arrow().wrap_array(pa.array(arrays, type=arrow().storage_type))
+        points = points.reshape((-1,))
+
+        return arrow().wrap_array(pa.FixedSizeListArray.from_arrays(points, type=arrow().storage_type))

rerun_py/tests/unit/test_points2d.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import itertools
+from typing import Any, Sequence
 
 import numpy as np
 import rerun2 as rr
@@ -18,6 +19,8 @@
 
 def test_points2d() -> None:
     points_arrays = [
+        [],
+        np.array([]),
         # Point2DArrayLike: Sequence[Point2DLike]: Point2D
         [
             rrc.Point2D([1, 2]),
@@ -29,7 +32,7 @@ def test_points2d() -> None:
             np.array([3, 4], dtype=np.float32),
         ],
         # Point2DArrayLike: Sequence[Point2DLike]: Tuple[float, float]
-        [[1, 2], [3, 4]],
+        [(1, 2), (3, 4)],
         # Point2DArrayLike: Sequence[Point2DLike]: Sequence[float]
         [1, 2, 3, 4],
         # Point2DArrayLike: npt.NDArray[np.float32]
@@ -45,6 +48,8 @@ def test_points2d() -> None:
 
     radii_arrays = [
         None,
+        [],
+        np.array([]),
         # RadiusArrayLike: Sequence[RadiusLike]: float
         [42, 43],
         # RadiusArrayLike: Sequence[RadiusLike]: Radius
@@ -58,6 +63,8 @@ def test_points2d() -> None:
 
     colors_arrays = [
         None,
+        [],
+        np.array([]),
         # ColorArrayLike: Sequence[ColorLike]: int
         [
             0xAA0000CC,
@@ -154,6 +161,7 @@ def test_points2d() -> None:
 
     labels_arrays = [
         None,
+        [],
         # LabelArrayLike: Sequence[LabelLike]: str
         ["hello", "friend"],
         # LabelArrayLike: Sequence[LabelLike]: Label
@@ -172,6 +180,8 @@ def test_points2d() -> None:
     ]
 
     class_id_arrays = [
+        [],
+        np.array([]),
         # ClassIdArrayLike: Sequence[ClassIdLike]: int
         [126, 127],
         # ClassIdArrayLike: Sequence[ClassIdLike]: ClassId
@@ -187,6 +197,8 @@ def test_points2d() -> None:
     ]
 
     keypoint_id_arrays = [
+        [],
+        np.array([]),
         # KeypointIdArrayLike: Sequence[KeypointIdLike]: int
         [2, 3],
         # KeypointIdArrayLike: Sequence[KeypointIdLike]: KeypointId
@@ -202,6 +214,8 @@ def test_points2d() -> None:
     ]
 
     instance_key_arrays = [
+        [],
+        np.array([]),
         # InstanceKeyArrayLike: Sequence[InstanceKeyLike]: int
         [U64_MAX_MINUS_1, U64_MAX],
         # InstanceKeyArrayLike: Sequence[InstanceKeyLike]: InstanceKey
@@ -247,17 +261,21 @@ def test_points2d() -> None:
         )
         print(f"{arch}\n")
 
-        assert arch.points == rrc.Point2DArray.from_similar([[1.0, 2.0], [3.0, 4.0]])
-        assert arch.radii == rrc.RadiusArray.from_similar([42, 43] if radii is not None else [])
-        assert arch.colors == rrc.ColorArray.from_similar([0xAA0000CC, 0x00BB00DD] if colors is not None else [])
-        assert arch.labels == rrc.LabelArray.from_similar(["hello", "friend"] if labels is not None else [])
+        assert arch.points == rrc.Point2DArray.from_similar([[1.0, 2.0], [3.0, 4.0]] if non_empty(points) else [])
+        assert arch.radii == rrc.RadiusArray.from_similar([42, 43] if non_empty(radii) else [])
+        assert arch.colors == rrc.ColorArray.from_similar([0xAA0000CC, 0x00BB00DD] if non_empty(colors) else [])
+        assert arch.labels == rrc.LabelArray.from_similar(["hello", "friend"] if non_empty(labels) else [])
         assert arch.draw_order == rrc.DrawOrderArray.from_similar([300] if draw_order is not None else [])
-        assert arch.class_ids == rrc.ClassIdArray.from_similar([126, 127] if class_ids is not None else [])
-        assert arch.keypoint_ids == rrc.KeypointIdArray.from_similar([2, 3] if keypoint_ids is not None else [])
+        assert arch.class_ids == rrc.ClassIdArray.from_similar([126, 127] if non_empty(class_ids) else [])
+        assert arch.keypoint_ids == rrc.KeypointIdArray.from_similar([2, 3] if non_empty(keypoint_ids) else [])
         assert arch.instance_keys == rrc.InstanceKeyArray.from_similar(
-            [U64_MAX_MINUS_1, U64_MAX] if instance_keys is not None else []
+            [U64_MAX_MINUS_1, U64_MAX] if non_empty(instance_keys) else []
         )
 
 
+def non_empty(v: Sequence[Any] | None) -> bool:
+    return v is not None and len(v) > 0
+
+
 if __name__ == "__main__":
     test_points2d()