fix ome metadata reading

This code was merged into iohub, so until a new release is made and we can pin the version we have helper functions stored in ome_tmp

Author: pattonw

funlib/persistence/arrays/ome_datasets.py

@@ -1,16 +1,15 @@
 import logging
-from itertools import chain
 from pathlib import Path
 from typing import Sequence
 
-import numpy as np
 from iohub.ngff import AxisMeta, TransformationMeta, open_ome_zarr
 from numpy.typing import DTypeLike
 
 from funlib.geometry import Coordinate
 
 from .array import Array
 from .metadata import MetaData, OME_MetaDataFormat
+from .ome_tmp import get_effective_scale, get_effective_translation
 
 logger = logging.getLogger(__name__)
 
@@ -57,45 +56,15 @@ def open_ome_ds(
     units = [axis.unit for axis in axes if axis.unit is not None]
     types = [axis.type for axis in axes if axis.type is not None]
 
-    base_transform = ome_zarr.metadata.multiscales[0].coordinate_transformations
-    img_transforms = [
-        ome_zarr.metadata.multiscales[0].datasets[i].coordinate_transformations
-        for i, dataset_meta in enumerate(ome_zarr.metadata.multiscales[0].datasets)
-        if dataset_meta.path == name
-    ][0]
-
-    scales = [
-        t.scale for t in chain(base_transform, img_transforms) if t.type == "scale"
-    ]
-    translations = [
-        t.translation
-        for t in chain(base_transform, img_transforms)
-        if t.type == "translation"
-    ]
-    assert all(
-        all(np.isclose(scale, Coordinate(scale))) for scale in scales
-    ), f"funlib.persistence only supports integer scales: {scales}"
-    assert all(
-        all(np.isclose(translation, Coordinate(translation)))
-        for translation in translations
-    ), f"funlib.persistence only supports integer translations: {translations}"
-    scales = [Coordinate(s) for s in scales]
-
-    # apply translations in order to get final scale/transform for this array
-    base_scale = scales[0] * 0 + 1
-    base_translation = scales[0] * 0
-    for t in chain(base_transform, img_transforms):
-        if t.type == "translation":
-            base_translation += base_scale * Coordinate(t.translation)
-        elif t.type == "scale":
-            base_scale *= Coordinate(t.scale)
+    scale = get_effective_scale(ome_zarr, name)
+    offset = get_effective_translation(ome_zarr, name)
 
     dataset = ome_zarr[name]
 
     metadata = OME_MetaDataFormat().parse(
         dataset.shape,
-        offset=list(base_translation),
-        voxel_size=list(base_scale),
+        offset=list(offset),
+        voxel_size=list(scale),
         axis_names=axis_names,
         units=units,
         types=types,

funlib/persistence/arrays/ome_tmp.py

@@ -0,0 +1,92 @@
+from typing import Literal
+
+import numpy as np
+from iohub.ngff import TransformationMeta
+
+
+def _get_all_transforms(node, image: str | Literal["*"]) -> list[TransformationMeta]:
+    """Get all transforms metadata
+    for one image array or the whole FOV.
+
+    Parameters
+    ----------
+    image : str | Literal["*"]
+        Name of one image array (e.g. "0") to query,
+        or "*" for the whole FOV
+
+    Returns
+    -------
+    list[TransformationMeta]
+        All transforms applicable to this image or FOV.
+    """
+    transforms: list[TransformationMeta] = (
+        [t for t in node.metadata.multiscales[0].coordinate_transformations]
+        if node.metadata.multiscales[0].coordinate_transformations is not None
+        else []
+    )
+    if image != "*" and image in node:
+        for i, dataset_meta in enumerate(node.metadata.multiscales[0].datasets):
+            if dataset_meta.path == image:
+                transforms.extend(
+                    node.metadata.multiscales[0].datasets[i].coordinate_transformations
+                )
+    elif image != "*":
+        raise ValueError(f"Key {image} not recognized.")
+    return transforms
+
+
+def get_effective_scale(
+    node,
+    image: str | Literal["*"],
+) -> list[float]:
+    """Get the effective coordinate scale metadata
+    for one image array or the whole FOV.
+
+    Parameters
+    ----------
+    image : str | Literal["*"]
+        Name of one image array (e.g. "0") to query,
+        or "*" for the whole FOV
+
+    Returns
+    -------
+    list[float]
+        A list of floats representing the total scale
+        for the image or FOV for each axis.
+    """
+    transforms = node._get_all_transforms(image)
+
+    full_scale = np.ones(len(node.axes), dtype=float)
+    for transform in transforms:
+        if transform.type == "scale":
+            full_scale *= np.array(transform.scale)
+
+    return [float(x) for x in full_scale]
+
+
+def get_effective_translation(
+    node,
+    image: str | Literal["*"],
+) -> TransformationMeta:
+    """Get the effective coordinate translation metadata
+    for one image array or the whole FOV.
+
+    Parameters
+    ----------
+    image : str | Literal["*"]
+        Name of one image array (e.g. "0") to query,
+        or "*" for the whole FOV
+
+    Returns
+    -------
+    list[float]
+        A list of floats representing the total translation
+        for the image or FOV for each axis.
+    """
+    transforms = node._get_all_transforms(image)
+    full_translation = np.zeros(len(node.axes), dtype=float)
+    for transform in transforms:
+        if transform.type == "translation":
+            full_translation += np.array(transform.translation)
+
+    return [float(x) for x in full_translation]