From 0c21a7303a5d6fbf6f1da2bc6e7c9a56826163ba Mon Sep 17 00:00:00 2001
From: William Patton <wllmpttn24@gmail.com>
Date: Mon, 9 Dec 2024 20:29:56 -0800
Subject: [PATCH 01/13] add support for getting the aggregated scale/transform
 for individual arrays

---
 iohub/ngff/nodes.py     | 164 +++++++++++++++++-----------------------
 tests/ngff/test_ngff.py | 132 +++++++++++++++++---------------
 2 files changed, 142 insertions(+), 154 deletions(-)

diff --git a/iohub/ngff/nodes.py b/iohub/ngff/nodes.py
index 32ec1e7f..fa6dec7b 100644
--- a/iohub/ngff/nodes.py
+++ b/iohub/ngff/nodes.py
@@ -58,9 +58,7 @@ def _open_store(
     synchronizer=None,
 ):
     if not os.path.isdir(store_path) and mode in ("r", "r+"):
-        raise FileNotFoundError(
-            f"Dataset directory not found at {store_path}."
-        )
+        raise FileNotFoundError(f"Dataset directory not found at {store_path}.")
     if version != "0.4":
         _logger.warning(
             "IOHub is only tested against OME-NGFF v0.4. "
@@ -70,14 +68,10 @@ def _open_store(
     else:
         dimension_separator = "/"
     try:
-        store = zarr.DirectoryStore(
-            store_path, dimension_separator=dimension_separator
-        )
+        store = zarr.DirectoryStore(store_path, dimension_separator=dimension_separator)
         root = zarr.open_group(store, mode=mode, synchronizer=synchronizer)
     except Exception as e:
-        raise RuntimeError(
-            f"Cannot open Zarr root group at {store_path}"
-        ) from e
+        raise RuntimeError(f"Cannot open Zarr root group at {store_path}") from e
     return root
 
 
@@ -108,9 +102,7 @@ def __init__(
         if channel_names:
             self._channel_names = channel_names
         elif not parse_meta:
-            raise ValueError(
-                "Channel names need to be provided or in metadata."
-            )
+            raise ValueError("Channel names need to be provided or in metadata.")
         if axes:
             self.axes = axes
         self._group = group
@@ -541,12 +533,8 @@ def _parse_meta(self):
         omero = self.zattrs.get("omero")
         if multiscales and omero:
             try:
-                self.metadata = ImagesMeta(
-                    multiscales=multiscales, omero=omero
-                )
-                self._channel_names = [
-                    c.label for c in self.metadata.omero.channels
-                ]
+                self.metadata = ImagesMeta(multiscales=multiscales, omero=omero)
+                self._channel_names = [c.label for c in self.metadata.omero.channels]
                 self.axes = self.metadata.multiscales[0].axes
             except ValidationError:
                 self._warn_invalid_meta()
@@ -560,9 +548,7 @@ def dump_meta(self):
     @property
     def _storage_options(self):
         return {
-            "compressor": Blosc(
-                cname="zstd", clevel=1, shuffle=Blosc.BITSHUFFLE
-            ),
+            "compressor": Blosc(cname="zstd", clevel=1, shuffle=Blosc.BITSHUFFLE),
             "overwrite": self._overwrite,
         }
 
@@ -599,8 +585,7 @@ def data(self):
             return self["0"]
         except KeyError:
             raise KeyError(
-                "There is no array named '0' "
-                f"in the group of: {self.array_keys()}"
+                "There is no array named '0' " f"in the group of: {self.array_keys()}"
             )
 
     def __getitem__(self, key: int | str) -> ImageArray:
@@ -624,9 +609,7 @@ def __setitem__(self, key, value: NDArray):
         """Write an up-to-5D image with default settings."""
         key = normalize_storage_path(key)
         if not isinstance(value, np.ndarray):
-            raise TypeError(
-                f"Value must be a NumPy array. Got type {type(value)}."
-            )
+            raise TypeError(f"Value must be a NumPy array. Got type {type(value)}.")
         self.create_image(key, value)
 
     def images(self) -> Generator[tuple[str, ImageArray]]:
@@ -676,9 +659,7 @@ def create_image(
         if check_shape:
             self._check_shape(data.shape)
         img_arr = ImageArray(
-            self._group.array(
-                name, data, chunks=chunks, **self._storage_options
-            )
+            self._group.array(name, data, chunks=chunks, **self._storage_options)
         )
         self._create_image_meta(img_arr.basename, transform=transform)
         return img_arr
@@ -761,8 +742,7 @@ def _check_shape(self, data_shape: tuple[int]):
                 _logger.warning(msg)
         else:
             _logger.info(
-                "Dataset channel axis is not set. "
-                "Skipping channel shape check."
+                "Dataset channel axis is not set. " "Skipping channel shape check."
             )
 
     def _create_image_meta(
@@ -773,9 +753,7 @@ def _create_image_meta(
     ):
         if not transform:
             transform = [TransformationMeta(type="identity")]
-        dataset_meta = DatasetMeta(
-            path=name, coordinate_transformations=transform
-        )
+        dataset_meta = DatasetMeta(path=name, coordinate_transformations=transform)
         if not hasattr(self, "metadata"):
             self.metadata = ImagesMeta(
                 multiscales=[
@@ -784,18 +762,13 @@ def _create_image_meta(
                         axes=self.axes,
                         datasets=[dataset_meta],
                         name=name,
-                        coordinateTransformations=[
-                            TransformationMeta(type="identity")
-                        ],
+                        coordinateTransformations=[TransformationMeta(type="identity")],
                         metadata=extra_meta,
                     )
                 ],
                 omero=self._omero_meta(id=0, name=self._group.basename),
             )
-        elif (
-            dataset_meta.path
-            not in self.metadata.multiscales[0].get_dataset_paths()
-        ):
+        elif dataset_meta.path not in self.metadata.multiscales[0].get_dataset_paths():
             self.metadata.multiscales[0].datasets.append(dataset_meta)
         self.dump_meta()
 
@@ -808,15 +781,11 @@ def _omero_meta(
         if not clims:
             clims = [None] * len(self.channel_names)
         channels = []
-        for i, (channel_name, clim) in enumerate(
-            zip(self.channel_names, clims)
-        ):
+        for i, (channel_name, clim) in enumerate(zip(self.channel_names, clims)):
             if i == 0:
                 first_chan = True
             channels.append(
-                channel_display_settings(
-                    channel_name, clim=clim, first_chan=first_chan
-                )
+                channel_display_settings(channel_name, clim=clim, first_chan=first_chan)
             )
         omero_meta = OMEROMeta(
             version=self.version,
@@ -836,8 +805,7 @@ def _find_axis(self, axis_type):
     def _get_channel_axis(self):
         if (ch_ax := self._find_axis("channel")) is None:
             raise KeyError(
-                "Axis 'channel' does not exist. "
-                "Please update `self.axes` first."
+                "Axis 'channel' does not exist. " "Please update `self.axes` first."
             )
         else:
             return ch_ax
@@ -866,14 +834,10 @@ def append_channel(self, chan_name: str, resize_arrays: bool = True):
                 elif ch_ax == len(shape):
                     shape = _pad_shape(tuple(shape), target=len(shape) + 1)
                 else:
-                    raise IndexError(
-                        f"Cannot infer channel axis for shape {shape}."
-                    )
+                    raise IndexError(f"Cannot infer channel axis for shape {shape}.")
                 img.resize(shape)
         if "omero" in self.metadata.model_dump().keys():
-            self.metadata.omero.channels.append(
-                channel_display_settings(chan_name)
-            )
+            self.metadata.omero.channels.append(channel_display_settings(chan_name))
             self.dump_meta()
 
     def rename_channel(self, old: str, new: str):
@@ -937,18 +901,12 @@ def initialize_pyramid(self, levels: int) -> None:
         for level in range(1, levels):
             factor = 2**level
 
-            shape = array.shape[:-3] + _scale_integers(
-                array.shape[-3:], factor
-            )
+            shape = array.shape[:-3] + _scale_integers(array.shape[-3:], factor)
 
-            chunks = _pad_shape(
-                _scale_integers(array.chunks, factor), len(shape)
-            )
+            chunks = _pad_shape(_scale_integers(array.chunks, factor), len(shape))
 
             transforms = deepcopy(
-                self.metadata.multiscales[0]
-                .datasets[0]
-                .coordinate_transformations
+                self.metadata.multiscales[0].datasets[0].coordinate_transformations
             )
             for tr in transforms:
                 if tr.type == "scale":
@@ -970,9 +928,7 @@ def scale(self) -> list[float]:
         highest resolution scale.
         """
         scale = [1] * self.data.ndim
-        transforms = (
-            self.metadata.multiscales[0].datasets[0].coordinate_transformations
-        )
+        transforms = self.metadata.multiscales[0].datasets[0].coordinate_transformations
         for trans in transforms:
             if trans.type == "scale":
                 if len(trans.scale) != len(scale):
@@ -990,9 +946,7 @@ def axis_names(self) -> list[str]:
 
         Returns lowercase axis names.
         """
-        return [
-            axis.name.lower() for axis in self.metadata.multiscales[0].axes
-        ]
+        return [axis.name.lower() for axis in self.metadata.multiscales[0].axes]
 
     def get_axis_index(self, axis_name: str) -> int:
         """
@@ -1010,6 +964,43 @@ def get_axis_index(self, axis_name: str) -> int:
         """
         return self.axis_names.index(axis_name.lower())
 
+    def get_transforms(
+        self,
+        image: str | Literal["*"],
+    ) -> tuple[TransformationMeta, TransformationMeta]:
+        """Get the total coordinate scale and translation metadata
+        for one image array or the whole FOV.
+
+        Parameters
+        ----------
+        image : str | Literal["*"]
+            Name of one image array (e.g. "0") to transform,
+            or "*" for the whole FOV
+        """
+        transforms: list[TransformationMeta] = self.metadata.multiscales[0].coordinate_transformations
+        if image != "*" and image in self:
+            for i, dataset_meta in enumerate(self.metadata.multiscales[0].datasets):
+                if dataset_meta.path == image:
+                    transforms.extend(
+                        self.metadata.multiscales[0]
+                        .datasets[i]
+                        .coordinate_transformations
+                    )
+        elif image != "*":
+            raise ValueError(f"Key {image} not recognized.")
+
+        full_scale = np.array([1]*len(self.axes), dtype=float)
+        full_translation = np.array([0]*len(self.axes), dtype=float)
+        for transform in transforms:
+            if transform.type == "scale":
+                full_scale *= np.array(transform.scale)
+            elif transform.type == "translation":
+                full_translation += full_scale * np.array(transform.translation)
+
+        return TransformationMeta(
+            type="scale", scale=tuple(full_scale)
+        ), TransformationMeta(type="translation", translation=tuple(full_translation))
+
     def set_transform(
         self,
         image: str | Literal["*"],
@@ -1030,9 +1021,7 @@ def set_transform(
         if image == "*":
             self.metadata.multiscales[0].coordinate_transformations = transform
         elif image in self:
-            for i, dataset_meta in enumerate(
-                self.metadata.multiscales[0].datasets
-            ):
+            for i, dataset_meta in enumerate(self.metadata.multiscales[0].datasets):
                 if dataset_meta.path == image:
                     self.metadata.multiscales[0].datasets[i] = DatasetMeta(
                         path=image, coordinate_transformations=transform
@@ -1061,9 +1050,7 @@ def set_scale(
             Value of the new scale.
         """
         if len(self.metadata.multiscales) > 1:
-            raise NotImplementedError(
-                "Cannot set scale for multi-resolution images."
-            )
+            raise NotImplementedError("Cannot set scale for multi-resolution images.")
 
         if new_scale <= 0:
             raise ValueError("New scale must be positive.")
@@ -1078,9 +1065,7 @@ def set_scale(
         self.zattrs["iohub"] = iohub_dict
 
         # Update scale while preserving existing transforms
-        transforms = (
-            self.metadata.multiscales[0].datasets[0].coordinate_transformations
-        )
+        transforms = self.metadata.multiscales[0].datasets[0].coordinate_transformations
         # Replace default identity transform with scale
         if len(transforms) == 1 and transforms[0].type == "identity":
             transforms = [TransformationMeta(type="scale", scale=[1] * 5)]
@@ -1206,9 +1191,7 @@ def _parse_meta(self):
 
     def dump_meta(self):
         """Dumps metadata JSON to the `.zattrs` file."""
-        self.zattrs.update(
-            {"well": self.metadata.model_dump(**TO_DICT_SETTINGS)}
-        )
+        self.zattrs.update({"well": self.metadata.model_dump(**TO_DICT_SETTINGS)})
 
     def __getitem__(self, key: str):
         """Get a position member of the well.
@@ -1389,8 +1372,7 @@ def from_positions(
         for name, src_pos in positions.items():
             if not isinstance(src_pos, Position):
                 raise TypeError(
-                    f"Expected item type {type(Position)}, "
-                    f"got {type(src_pos)}"
+                    f"Expected item type {type(Position)}, " f"got {type(src_pos)}"
                 )
             name = normalize_storage_path(name)
             if name in plate.zgroup:
@@ -1473,9 +1455,7 @@ def dump_meta(self, field_count: bool = False):
         """
         if field_count:
             self.metadata.field_count = len(list(self.positions()))
-        self.zattrs.update(
-            {"plate": self.metadata.model_dump(**TO_DICT_SETTINGS)}
-        )
+        self.zattrs.update({"plate": self.metadata.model_dump(**TO_DICT_SETTINGS)})
 
     def _auto_idx(
         self,
@@ -1563,9 +1543,7 @@ def create_well(
             self.metadata.wells.append(well_index_meta)
         # create new row if needed
         if row_name not in self:
-            row_grp = self.zgroup.create_group(
-                row_meta.name, overwrite=self._overwrite
-            )
+            row_grp = self.zgroup.create_group(row_meta.name, overwrite=self._overwrite)
             if row_meta not in self.metadata.rows:
                 self.metadata.rows.append(row_meta)
         else:
@@ -1688,9 +1666,9 @@ def rename_well(
         self.zgroup.move(old, new)
 
         # update well metadata
-        old_well_index = [
-            well_name.path for well_name in self.metadata.wells
-        ].index(old)
+        old_well_index = [well_name.path for well_name in self.metadata.wells].index(
+            old
+        )
         self.metadata.wells[old_well_index].path = new
         new_well_names = [well.path for well in self.metadata.wells]
 
diff --git a/tests/ngff/test_ngff.py b/tests/ngff/test_ngff.py
index cf0ce4f0..9d5801ce 100644
--- a/tests/ngff/test_ngff.py
+++ b/tests/ngff/test_ngff.py
@@ -37,16 +37,10 @@
 y_dim_st = st.integers(1, 32)
 x_dim_st = st.integers(1, 32)
 channel_names_st = c_dim_st.flatmap(
-    (
-        lambda c_dim: st.lists(
-            short_text_st, min_size=c_dim, max_size=c_dim, unique=True
-        )
-    )
+    (lambda c_dim: st.lists(short_text_st, min_size=c_dim, max_size=c_dim, unique=True))
 )
 short_alpha_numeric = st.text(
-    alphabet=list(
-        string.ascii_lowercase + string.ascii_uppercase + string.digits
-    ),
+    alphabet=list(string.ascii_lowercase + string.ascii_uppercase + string.digits),
     min_size=1,
     max_size=16,
 )
@@ -90,9 +84,7 @@ def _channels_and_random_5d_shape_and_dtype(draw):
 
 @st.composite
 def _channels_and_random_5d(draw):
-    channel_names, shape, dtype = draw(
-        _channels_and_random_5d_shape_and_dtype()
-    )
+    channel_names, shape, dtype = draw(_channels_and_random_5d_shape_and_dtype())
     random_5d = draw(npst.arrays(dtype, shape=shape))
     return channel_names, random_5d
 
@@ -213,9 +205,7 @@ def _temp_ome_zarr_plate(
             channel_names=channel_names,
         )
         for position in position_list:
-            pos = dataset.create_position(
-                position[0], position[1], position[2]
-            )
+            pos = dataset.create_position(position[0], position[1], position[2])
             pos.create_image(arr_name, image_5d, **kwargs)
         yield dataset
     finally:
@@ -282,13 +272,9 @@ def test_ome_zarr_to_dask(channels_and_random_5d, arr_name):
     """Test `iohub.ngff.Position.data` to dask"""
     channel_names, random_5d = channels_and_random_5d
     with _temp_ome_zarr(random_5d, channel_names, "0") as dataset:
-        assert_array_almost_equal(
-            dataset.data.dask_array().compute(), random_5d
-        )
+        assert_array_almost_equal(dataset.data.dask_array().compute(), random_5d)
     with _temp_ome_zarr(random_5d, channel_names, arr_name) as dataset:
-        assert_array_almost_equal(
-            dataset[arr_name].dask_array().compute(), random_5d
-        )
+        assert_array_almost_equal(dataset[arr_name].dask_array().compute(), random_5d)
 
 
 @given(
@@ -324,9 +310,7 @@ def test_append_channel(channels_and_random_5d, arr_name):
     """Test `iohub.ngff.Position.append_channel()`"""
     channel_names, random_5d = channels_and_random_5d
     assume(len(channel_names) > 1)
-    with _temp_ome_zarr(
-        random_5d[:, :-1], channel_names[:-1], arr_name
-    ) as dataset:
+    with _temp_ome_zarr(random_5d[:, :-1], channel_names[:-1], arr_name) as dataset:
         dataset.append_channel(channel_names[-1], resize_arrays=True)
         dataset[arr_name][:, -1] = random_5d[:, -1]
         assert_array_almost_equal(dataset[arr_name][:], random_5d)
@@ -419,16 +403,10 @@ def test_update_channel(channels_and_random_5d, arr_name):
     """Test `iohub.ngff.Position.update_channel()`"""
     channel_names, random_5d = channels_and_random_5d
     assume(len(channel_names) > 1)
-    with _temp_ome_zarr(
-        random_5d[:, :-1], channel_names[:-1], arr_name
-    ) as dataset:
+    with _temp_ome_zarr(random_5d[:, :-1], channel_names[:-1], arr_name) as dataset:
         for i, ch in enumerate(dataset.channel_names):
-            dataset.update_channel(
-                chan_name=ch, target=arr_name, data=random_5d[:, -1]
-            )
-            assert_array_almost_equal(
-                dataset[arr_name][:, i], random_5d[:, -1]
-            )
+            dataset.update_channel(chan_name=ch, target=arr_name, data=random_5d[:, -1])
+            assert_array_almost_equal(dataset[arr_name][:, i], random_5d[:, -1])
 
 
 @given(
@@ -467,14 +445,10 @@ def test_set_transform_image(ch_shape_dtype, arr_name):
             dataset.create_zeros(name=arr_name, shape=shape, dtype=dtype)
             assert dataset.metadata.multiscales[0].datasets[
                 0
-            ].coordinate_transformations == [
-                TransformationMeta(type="identity")
-            ]
+            ].coordinate_transformations == [TransformationMeta(type="identity")]
             dataset.set_transform(image=arr_name, transform=transform)
             assert (
-                dataset.metadata.multiscales[0]
-                .datasets[0]
-                .coordinate_transformations
+                dataset.metadata.multiscales[0].datasets[0].coordinate_transformations
                 == transform
             )
         # read data with an external reader
@@ -485,6 +459,57 @@ def test_set_transform_image(ch_shape_dtype, arr_name):
         ]
 
 
+@pytest.mark.parametrize(
+    "transforms",
+    [
+        (
+            [TransformationMeta(type="identity")],
+            TransformationMeta(type="scale", scale=(1.0, 1.0, 1.0, 1.0, 1.0)),
+            TransformationMeta(type="translation", translation=(0.0, 0.0, 0.0, 0.0, 0.0)),
+        ),
+        (
+            [TransformationMeta(type="scale", scale=(1.0, 2.0, 3.0, 4.0, 5.0))],
+            TransformationMeta(type="scale", scale=(1.0, 2.0, 3.0, 4.0, 5.0)),
+            TransformationMeta(type="translation", translation=(0.0, 0.0, 0.0, 0.0, 0.0)),
+        ),
+        (
+            [TransformationMeta(type="translation", translation=(1.0, 2.0, 3.0, 4.0, 5.0))],
+            TransformationMeta(type="scale", scale=(1.0, 1.0, 1.0, 1.0, 1.0)),
+            TransformationMeta(type="translation", translation=(1.0, 2.0, 3.0, 4.0, 5.0)),
+        ),
+        (
+            [
+                TransformationMeta(type="scale", scale=(2.0, 2.0, 2.0, 2.0, 2.0)),
+                TransformationMeta(type="translation", translation=(1.0, 1.0, 1.0, 1.0, 1.0)),
+            ],
+            TransformationMeta(type="scale", scale=(2.0, 2.0, 2.0, 2.0, 2.0)),
+            TransformationMeta(type="translation", translation=(2.0, 2.0, 2.0, 2.0, 2.0)),
+        ),
+    ],
+)
+@given(
+    ch_shape_dtype=_channels_and_random_5d_shape_and_dtype(),
+    arr_name=short_alpha_numeric,
+)
+def test_get_transform_image(transforms, ch_shape_dtype, arr_name):
+    """Test `iohub.ngff.Position.set_transform()`"""
+    transform, expected_scale, expected_translate = transforms
+    channel_names, shape, dtype = ch_shape_dtype
+    with TemporaryDirectory() as temp_dir:
+        store_path = os.path.join(temp_dir, "ome.zarr")
+        with open_ome_zarr(
+            store_path, layout="fov", mode="w-", channel_names=channel_names
+        ) as dataset:
+            dataset.create_zeros(name=arr_name, shape=shape, dtype=dtype)
+            assert dataset.metadata.multiscales[0].datasets[
+                0
+            ].coordinate_transformations == [TransformationMeta(type="identity")]
+            dataset.set_transform(image=arr_name, transform=transform)
+            scale, translate = dataset.get_transforms(image=arr_name)
+            assert scale == expected_scale
+            assert translate == expected_translate
+
+
 @given(
     ch_shape_dtype=_channels_and_random_5d_shape_and_dtype(),
     arr_name=short_alpha_numeric,
@@ -501,15 +526,12 @@ def test_set_transform_fov(ch_shape_dtype, arr_name):
             store_path, layout="fov", mode="w-", channel_names=channel_names
         ) as dataset:
             dataset.create_zeros(name=arr_name, shape=shape, dtype=dtype)
-            assert dataset.metadata.multiscales[
-                0
-            ].coordinate_transformations == [
+            assert dataset.metadata.multiscales[0].coordinate_transformations == [
                 TransformationMeta(type="identity")
             ]
             dataset.set_transform(image="*", transform=transform)
             assert (
-                dataset.metadata.multiscales[0].coordinate_transformations
-                == transform
+                dataset.metadata.multiscales[0].coordinate_transformations == transform
             )
         # read data with plain zarr
         group = zarr.open(store_path)
@@ -593,9 +615,7 @@ def test_make_tiles(channels_and_random_5d, grid_shape, arr_name):
                 grid_shape[-2] * random_5d.shape[-2],
                 grid_shape[-1] * random_5d.shape[-1],
             )
-            assert tiles.tile_shape == _pad_shape(
-                random_5d.shape[-2:], target=5
-            )
+            assert tiles.tile_shape == _pad_shape(random_5d.shape[-2:], target=5)
             assert tiles.dtype == random_5d.dtype
             for args in ((1.01, 1), (0, 0, 0)):
                 with pytest.raises(TypeError):
@@ -724,9 +744,7 @@ def test_get_axis_index():
             _ = position.get_axis_index("DOG")
 
 
-@given(
-    row=short_alpha_numeric, col=short_alpha_numeric, pos=short_alpha_numeric
-)
+@given(row=short_alpha_numeric, col=short_alpha_numeric, pos=short_alpha_numeric)
 @settings(max_examples=16, deadline=2000)
 def test_modify_hcs_ref(row: str, col: str, pos: str):
     """Test `iohub.ngff.open_ome_zarr()`"""
@@ -759,17 +777,11 @@ def test_create_well(row_names: list[str], col_names: list[str]):
         for row_name in row_names:
             for col_name in col_names:
                 dataset.create_well(row_name, col_name)
-        assert [
-            c["name"] for c in dataset.zattrs["plate"]["columns"]
-        ] == col_names
-        assert [
-            r["name"] for r in dataset.zattrs["plate"]["rows"]
-        ] == row_names
+        assert [c["name"] for c in dataset.zattrs["plate"]["columns"]] == col_names
+        assert [r["name"] for r in dataset.zattrs["plate"]["rows"]] == row_names
 
 
-@given(
-    row=short_alpha_numeric, col=short_alpha_numeric, pos=short_alpha_numeric
-)
+@given(row=short_alpha_numeric, col=short_alpha_numeric, pos=short_alpha_numeric)
 def test_create_position(row, col, pos):
     """Test `iohub.ngff.Plate.create_position()`"""
     with TemporaryDirectory() as temp_dir:
@@ -790,9 +802,7 @@ def test_position_scale(channels_and_random_5d):
     channel_names, random_5d = channels_and_random_5d
     scale = list(range(1, 6))
     transform = [TransformationMeta(type="scale", scale=scale)]
-    with _temp_ome_zarr(
-        random_5d, channel_names, "0", transform=transform
-    ) as dataset:
+    with _temp_ome_zarr(random_5d, channel_names, "0", transform=transform) as dataset:
         # round-trip test with the offical reader implementation
         assert dataset.scale == scale
 

From bd77cd9c05359a5f494c23dfdb433e2538efa90e Mon Sep 17 00:00:00 2001
From: William Patton <wllmpttn24@gmail.com>
Date: Mon, 9 Dec 2024 20:35:32 -0800
Subject: [PATCH 02/13] Revert "formatting changes"

This reverts the formatting changes that were accidentally included with commit  0c21a7303a5d6fbf6f1da2bc6e7c9a56826163ba.
---
 iohub/ngff/nodes.py     | 127 +++++++++++++++++++++++++++++-----------
 tests/ngff/test_ngff.py |  81 ++++++++++++++++++-------
 2 files changed, 154 insertions(+), 54 deletions(-)

diff --git a/iohub/ngff/nodes.py b/iohub/ngff/nodes.py
index fa6dec7b..6352f846 100644
--- a/iohub/ngff/nodes.py
+++ b/iohub/ngff/nodes.py
@@ -58,7 +58,9 @@ def _open_store(
     synchronizer=None,
 ):
     if not os.path.isdir(store_path) and mode in ("r", "r+"):
-        raise FileNotFoundError(f"Dataset directory not found at {store_path}.")
+        raise FileNotFoundError(
+            f"Dataset directory not found at {store_path}."
+        )
     if version != "0.4":
         _logger.warning(
             "IOHub is only tested against OME-NGFF v0.4. "
@@ -68,10 +70,14 @@ def _open_store(
     else:
         dimension_separator = "/"
     try:
-        store = zarr.DirectoryStore(store_path, dimension_separator=dimension_separator)
+        store = zarr.DirectoryStore(
+            store_path, dimension_separator=dimension_separator
+        )
         root = zarr.open_group(store, mode=mode, synchronizer=synchronizer)
     except Exception as e:
-        raise RuntimeError(f"Cannot open Zarr root group at {store_path}") from e
+        raise RuntimeError(
+            f"Cannot open Zarr root group at {store_path}"
+        ) from e
     return root
 
 
@@ -102,7 +108,9 @@ def __init__(
         if channel_names:
             self._channel_names = channel_names
         elif not parse_meta:
-            raise ValueError("Channel names need to be provided or in metadata.")
+            raise ValueError(
+                "Channel names need to be provided or in metadata."
+            )
         if axes:
             self.axes = axes
         self._group = group
@@ -533,8 +541,12 @@ def _parse_meta(self):
         omero = self.zattrs.get("omero")
         if multiscales and omero:
             try:
-                self.metadata = ImagesMeta(multiscales=multiscales, omero=omero)
-                self._channel_names = [c.label for c in self.metadata.omero.channels]
+                self.metadata = ImagesMeta(
+                    multiscales=multiscales, omero=omero
+                )
+                self._channel_names = [
+                    c.label for c in self.metadata.omero.channels
+                ]
                 self.axes = self.metadata.multiscales[0].axes
             except ValidationError:
                 self._warn_invalid_meta()
@@ -548,7 +560,9 @@ def dump_meta(self):
     @property
     def _storage_options(self):
         return {
-            "compressor": Blosc(cname="zstd", clevel=1, shuffle=Blosc.BITSHUFFLE),
+            "compressor": Blosc(
+                cname="zstd", clevel=1, shuffle=Blosc.BITSHUFFLE
+            ),
             "overwrite": self._overwrite,
         }
 
@@ -585,7 +599,8 @@ def data(self):
             return self["0"]
         except KeyError:
             raise KeyError(
-                "There is no array named '0' " f"in the group of: {self.array_keys()}"
+                "There is no array named '0' "
+                f"in the group of: {self.array_keys()}"
             )
 
     def __getitem__(self, key: int | str) -> ImageArray:
@@ -609,7 +624,9 @@ def __setitem__(self, key, value: NDArray):
         """Write an up-to-5D image with default settings."""
         key = normalize_storage_path(key)
         if not isinstance(value, np.ndarray):
-            raise TypeError(f"Value must be a NumPy array. Got type {type(value)}.")
+            raise TypeError(
+                f"Value must be a NumPy array. Got type {type(value)}."
+            )
         self.create_image(key, value)
 
     def images(self) -> Generator[tuple[str, ImageArray]]:
@@ -659,7 +676,9 @@ def create_image(
         if check_shape:
             self._check_shape(data.shape)
         img_arr = ImageArray(
-            self._group.array(name, data, chunks=chunks, **self._storage_options)
+            self._group.array(
+                name, data, chunks=chunks, **self._storage_options
+            )
         )
         self._create_image_meta(img_arr.basename, transform=transform)
         return img_arr
@@ -742,7 +761,8 @@ def _check_shape(self, data_shape: tuple[int]):
                 _logger.warning(msg)
         else:
             _logger.info(
-                "Dataset channel axis is not set. " "Skipping channel shape check."
+                "Dataset channel axis is not set. "
+                "Skipping channel shape check."
             )
 
     def _create_image_meta(
@@ -753,7 +773,9 @@ def _create_image_meta(
     ):
         if not transform:
             transform = [TransformationMeta(type="identity")]
-        dataset_meta = DatasetMeta(path=name, coordinate_transformations=transform)
+        dataset_meta = DatasetMeta(
+            path=name, coordinate_transformations=transform
+        )
         if not hasattr(self, "metadata"):
             self.metadata = ImagesMeta(
                 multiscales=[
@@ -762,13 +784,18 @@ def _create_image_meta(
                         axes=self.axes,
                         datasets=[dataset_meta],
                         name=name,
-                        coordinateTransformations=[TransformationMeta(type="identity")],
+                        coordinateTransformations=[
+                            TransformationMeta(type="identity")
+                        ],
                         metadata=extra_meta,
                     )
                 ],
                 omero=self._omero_meta(id=0, name=self._group.basename),
             )
-        elif dataset_meta.path not in self.metadata.multiscales[0].get_dataset_paths():
+        elif (
+            dataset_meta.path
+            not in self.metadata.multiscales[0].get_dataset_paths()
+        ):
             self.metadata.multiscales[0].datasets.append(dataset_meta)
         self.dump_meta()
 
@@ -781,11 +808,15 @@ def _omero_meta(
         if not clims:
             clims = [None] * len(self.channel_names)
         channels = []
-        for i, (channel_name, clim) in enumerate(zip(self.channel_names, clims)):
+        for i, (channel_name, clim) in enumerate(
+            zip(self.channel_names, clims)
+        ):
             if i == 0:
                 first_chan = True
             channels.append(
-                channel_display_settings(channel_name, clim=clim, first_chan=first_chan)
+                channel_display_settings(
+                    channel_name, clim=clim, first_chan=first_chan
+                )
             )
         omero_meta = OMEROMeta(
             version=self.version,
@@ -805,7 +836,8 @@ def _find_axis(self, axis_type):
     def _get_channel_axis(self):
         if (ch_ax := self._find_axis("channel")) is None:
             raise KeyError(
-                "Axis 'channel' does not exist. " "Please update `self.axes` first."
+                "Axis 'channel' does not exist. "
+                "Please update `self.axes` first."
             )
         else:
             return ch_ax
@@ -834,10 +866,14 @@ def append_channel(self, chan_name: str, resize_arrays: bool = True):
                 elif ch_ax == len(shape):
                     shape = _pad_shape(tuple(shape), target=len(shape) + 1)
                 else:
-                    raise IndexError(f"Cannot infer channel axis for shape {shape}.")
+                    raise IndexError(
+                        f"Cannot infer channel axis for shape {shape}."
+                    )
                 img.resize(shape)
         if "omero" in self.metadata.model_dump().keys():
-            self.metadata.omero.channels.append(channel_display_settings(chan_name))
+            self.metadata.omero.channels.append(
+                channel_display_settings(chan_name)
+            )
             self.dump_meta()
 
     def rename_channel(self, old: str, new: str):
@@ -901,12 +937,18 @@ def initialize_pyramid(self, levels: int) -> None:
         for level in range(1, levels):
             factor = 2**level
 
-            shape = array.shape[:-3] + _scale_integers(array.shape[-3:], factor)
+            shape = array.shape[:-3] + _scale_integers(
+                array.shape[-3:], factor
+            )
 
-            chunks = _pad_shape(_scale_integers(array.chunks, factor), len(shape))
+            chunks = _pad_shape(
+                _scale_integers(array.chunks, factor), len(shape)
+            )
 
             transforms = deepcopy(
-                self.metadata.multiscales[0].datasets[0].coordinate_transformations
+                self.metadata.multiscales[0]
+                .datasets[0]
+                .coordinate_transformations
             )
             for tr in transforms:
                 if tr.type == "scale":
@@ -928,7 +970,9 @@ def scale(self) -> list[float]:
         highest resolution scale.
         """
         scale = [1] * self.data.ndim
-        transforms = self.metadata.multiscales[0].datasets[0].coordinate_transformations
+        transforms = (
+            self.metadata.multiscales[0].datasets[0].coordinate_transformations
+        )
         for trans in transforms:
             if trans.type == "scale":
                 if len(trans.scale) != len(scale):
@@ -946,7 +990,9 @@ def axis_names(self) -> list[str]:
 
         Returns lowercase axis names.
         """
-        return [axis.name.lower() for axis in self.metadata.multiscales[0].axes]
+        return [
+            axis.name.lower() for axis in self.metadata.multiscales[0].axes
+        ]
 
     def get_axis_index(self, axis_name: str) -> int:
         """
@@ -1021,7 +1067,9 @@ def set_transform(
         if image == "*":
             self.metadata.multiscales[0].coordinate_transformations = transform
         elif image in self:
-            for i, dataset_meta in enumerate(self.metadata.multiscales[0].datasets):
+            for i, dataset_meta in enumerate(
+                self.metadata.multiscales[0].datasets
+            ):
                 if dataset_meta.path == image:
                     self.metadata.multiscales[0].datasets[i] = DatasetMeta(
                         path=image, coordinate_transformations=transform
@@ -1050,7 +1098,9 @@ def set_scale(
             Value of the new scale.
         """
         if len(self.metadata.multiscales) > 1:
-            raise NotImplementedError("Cannot set scale for multi-resolution images.")
+            raise NotImplementedError(
+                "Cannot set scale for multi-resolution images."
+            )
 
         if new_scale <= 0:
             raise ValueError("New scale must be positive.")
@@ -1065,7 +1115,9 @@ def set_scale(
         self.zattrs["iohub"] = iohub_dict
 
         # Update scale while preserving existing transforms
-        transforms = self.metadata.multiscales[0].datasets[0].coordinate_transformations
+        transforms = (
+            self.metadata.multiscales[0].datasets[0].coordinate_transformations
+        )
         # Replace default identity transform with scale
         if len(transforms) == 1 and transforms[0].type == "identity":
             transforms = [TransformationMeta(type="scale", scale=[1] * 5)]
@@ -1191,7 +1243,9 @@ def _parse_meta(self):
 
     def dump_meta(self):
         """Dumps metadata JSON to the `.zattrs` file."""
-        self.zattrs.update({"well": self.metadata.model_dump(**TO_DICT_SETTINGS)})
+        self.zattrs.update(
+            {"well": self.metadata.model_dump(**TO_DICT_SETTINGS)}
+        )
 
     def __getitem__(self, key: str):
         """Get a position member of the well.
@@ -1372,7 +1426,8 @@ def from_positions(
         for name, src_pos in positions.items():
             if not isinstance(src_pos, Position):
                 raise TypeError(
-                    f"Expected item type {type(Position)}, " f"got {type(src_pos)}"
+                    f"Expected item type {type(Position)}, "
+                    f"got {type(src_pos)}"
                 )
             name = normalize_storage_path(name)
             if name in plate.zgroup:
@@ -1455,7 +1510,9 @@ def dump_meta(self, field_count: bool = False):
         """
         if field_count:
             self.metadata.field_count = len(list(self.positions()))
-        self.zattrs.update({"plate": self.metadata.model_dump(**TO_DICT_SETTINGS)})
+        self.zattrs.update(
+            {"plate": self.metadata.model_dump(**TO_DICT_SETTINGS)}
+        )
 
     def _auto_idx(
         self,
@@ -1543,7 +1600,9 @@ def create_well(
             self.metadata.wells.append(well_index_meta)
         # create new row if needed
         if row_name not in self:
-            row_grp = self.zgroup.create_group(row_meta.name, overwrite=self._overwrite)
+            row_grp = self.zgroup.create_group(
+                row_meta.name, overwrite=self._overwrite
+            )
             if row_meta not in self.metadata.rows:
                 self.metadata.rows.append(row_meta)
         else:
@@ -1666,9 +1725,9 @@ def rename_well(
         self.zgroup.move(old, new)
 
         # update well metadata
-        old_well_index = [well_name.path for well_name in self.metadata.wells].index(
-            old
-        )
+        old_well_index = [
+            well_name.path for well_name in self.metadata.wells
+        ].index(old)
         self.metadata.wells[old_well_index].path = new
         new_well_names = [well.path for well in self.metadata.wells]
 
diff --git a/tests/ngff/test_ngff.py b/tests/ngff/test_ngff.py
index 9d5801ce..48cfddfb 100644
--- a/tests/ngff/test_ngff.py
+++ b/tests/ngff/test_ngff.py
@@ -37,10 +37,16 @@
 y_dim_st = st.integers(1, 32)
 x_dim_st = st.integers(1, 32)
 channel_names_st = c_dim_st.flatmap(
-    (lambda c_dim: st.lists(short_text_st, min_size=c_dim, max_size=c_dim, unique=True))
+    (
+        lambda c_dim: st.lists(
+            short_text_st, min_size=c_dim, max_size=c_dim, unique=True
+        )
+    )
 )
 short_alpha_numeric = st.text(
-    alphabet=list(string.ascii_lowercase + string.ascii_uppercase + string.digits),
+    alphabet=list(
+        string.ascii_lowercase + string.ascii_uppercase + string.digits
+    ),
     min_size=1,
     max_size=16,
 )
@@ -84,7 +90,9 @@ def _channels_and_random_5d_shape_and_dtype(draw):
 
 @st.composite
 def _channels_and_random_5d(draw):
-    channel_names, shape, dtype = draw(_channels_and_random_5d_shape_and_dtype())
+    channel_names, shape, dtype = draw(
+        _channels_and_random_5d_shape_and_dtype()
+    )
     random_5d = draw(npst.arrays(dtype, shape=shape))
     return channel_names, random_5d
 
@@ -205,7 +213,9 @@ def _temp_ome_zarr_plate(
             channel_names=channel_names,
         )
         for position in position_list:
-            pos = dataset.create_position(position[0], position[1], position[2])
+            pos = dataset.create_position(
+                position[0], position[1], position[2]
+            )
             pos.create_image(arr_name, image_5d, **kwargs)
         yield dataset
     finally:
@@ -272,9 +282,13 @@ def test_ome_zarr_to_dask(channels_and_random_5d, arr_name):
     """Test `iohub.ngff.Position.data` to dask"""
     channel_names, random_5d = channels_and_random_5d
     with _temp_ome_zarr(random_5d, channel_names, "0") as dataset:
-        assert_array_almost_equal(dataset.data.dask_array().compute(), random_5d)
+        assert_array_almost_equal(
+            dataset.data.dask_array().compute(), random_5d
+        )
     with _temp_ome_zarr(random_5d, channel_names, arr_name) as dataset:
-        assert_array_almost_equal(dataset[arr_name].dask_array().compute(), random_5d)
+        assert_array_almost_equal(
+            dataset[arr_name].dask_array().compute(), random_5d
+        )
 
 
 @given(
@@ -310,7 +324,9 @@ def test_append_channel(channels_and_random_5d, arr_name):
     """Test `iohub.ngff.Position.append_channel()`"""
     channel_names, random_5d = channels_and_random_5d
     assume(len(channel_names) > 1)
-    with _temp_ome_zarr(random_5d[:, :-1], channel_names[:-1], arr_name) as dataset:
+    with _temp_ome_zarr(
+        random_5d[:, :-1], channel_names[:-1], arr_name
+    ) as dataset:
         dataset.append_channel(channel_names[-1], resize_arrays=True)
         dataset[arr_name][:, -1] = random_5d[:, -1]
         assert_array_almost_equal(dataset[arr_name][:], random_5d)
@@ -403,10 +419,16 @@ def test_update_channel(channels_and_random_5d, arr_name):
     """Test `iohub.ngff.Position.update_channel()`"""
     channel_names, random_5d = channels_and_random_5d
     assume(len(channel_names) > 1)
-    with _temp_ome_zarr(random_5d[:, :-1], channel_names[:-1], arr_name) as dataset:
+    with _temp_ome_zarr(
+        random_5d[:, :-1], channel_names[:-1], arr_name
+    ) as dataset:
         for i, ch in enumerate(dataset.channel_names):
-            dataset.update_channel(chan_name=ch, target=arr_name, data=random_5d[:, -1])
-            assert_array_almost_equal(dataset[arr_name][:, i], random_5d[:, -1])
+            dataset.update_channel(
+                chan_name=ch, target=arr_name, data=random_5d[:, -1]
+            )
+            assert_array_almost_equal(
+                dataset[arr_name][:, i], random_5d[:, -1]
+            )
 
 
 @given(
@@ -445,10 +467,14 @@ def test_set_transform_image(ch_shape_dtype, arr_name):
             dataset.create_zeros(name=arr_name, shape=shape, dtype=dtype)
             assert dataset.metadata.multiscales[0].datasets[
                 0
-            ].coordinate_transformations == [TransformationMeta(type="identity")]
+            ].coordinate_transformations == [
+                TransformationMeta(type="identity")
+            ]
             dataset.set_transform(image=arr_name, transform=transform)
             assert (
-                dataset.metadata.multiscales[0].datasets[0].coordinate_transformations
+                dataset.metadata.multiscales[0]
+                .datasets[0]
+                .coordinate_transformations
                 == transform
             )
         # read data with an external reader
@@ -526,12 +552,15 @@ def test_set_transform_fov(ch_shape_dtype, arr_name):
             store_path, layout="fov", mode="w-", channel_names=channel_names
         ) as dataset:
             dataset.create_zeros(name=arr_name, shape=shape, dtype=dtype)
-            assert dataset.metadata.multiscales[0].coordinate_transformations == [
+            assert dataset.metadata.multiscales[
+                0
+            ].coordinate_transformations == [
                 TransformationMeta(type="identity")
             ]
             dataset.set_transform(image="*", transform=transform)
             assert (
-                dataset.metadata.multiscales[0].coordinate_transformations == transform
+                dataset.metadata.multiscales[0].coordinate_transformations
+                == transform
             )
         # read data with plain zarr
         group = zarr.open(store_path)
@@ -615,7 +644,9 @@ def test_make_tiles(channels_and_random_5d, grid_shape, arr_name):
                 grid_shape[-2] * random_5d.shape[-2],
                 grid_shape[-1] * random_5d.shape[-1],
             )
-            assert tiles.tile_shape == _pad_shape(random_5d.shape[-2:], target=5)
+            assert tiles.tile_shape == _pad_shape(
+                random_5d.shape[-2:], target=5
+            )
             assert tiles.dtype == random_5d.dtype
             for args in ((1.01, 1), (0, 0, 0)):
                 with pytest.raises(TypeError):
@@ -744,7 +775,9 @@ def test_get_axis_index():
             _ = position.get_axis_index("DOG")
 
 
-@given(row=short_alpha_numeric, col=short_alpha_numeric, pos=short_alpha_numeric)
+@given(
+    row=short_alpha_numeric, col=short_alpha_numeric, pos=short_alpha_numeric
+)
 @settings(max_examples=16, deadline=2000)
 def test_modify_hcs_ref(row: str, col: str, pos: str):
     """Test `iohub.ngff.open_ome_zarr()`"""
@@ -777,11 +810,17 @@ def test_create_well(row_names: list[str], col_names: list[str]):
         for row_name in row_names:
             for col_name in col_names:
                 dataset.create_well(row_name, col_name)
-        assert [c["name"] for c in dataset.zattrs["plate"]["columns"]] == col_names
-        assert [r["name"] for r in dataset.zattrs["plate"]["rows"]] == row_names
+        assert [
+            c["name"] for c in dataset.zattrs["plate"]["columns"]
+        ] == col_names
+        assert [
+            r["name"] for r in dataset.zattrs["plate"]["rows"]
+        ] == row_names
 
 
-@given(row=short_alpha_numeric, col=short_alpha_numeric, pos=short_alpha_numeric)
+@given(
+    row=short_alpha_numeric, col=short_alpha_numeric, pos=short_alpha_numeric
+)
 def test_create_position(row, col, pos):
     """Test `iohub.ngff.Plate.create_position()`"""
     with TemporaryDirectory() as temp_dir:
@@ -802,7 +841,9 @@ def test_position_scale(channels_and_random_5d):
     channel_names, random_5d = channels_and_random_5d
     scale = list(range(1, 6))
     transform = [TransformationMeta(type="scale", scale=scale)]
-    with _temp_ome_zarr(random_5d, channel_names, "0", transform=transform) as dataset:
+    with _temp_ome_zarr(
+        random_5d, channel_names, "0", transform=transform
+    ) as dataset:
         # round-trip test with the offical reader implementation
         assert dataset.scale == scale
 

From 6a490ff98e0f3d02ff4c798fe27e6c9646ac8da5 Mon Sep 17 00:00:00 2001
From: William Patton <wllmpttn24@gmail.com>
Date: Tue, 10 Dec 2024 12:29:42 -0800
Subject: [PATCH 03/13] address ziwen's comments

---
 iohub/ngff/nodes.py     | 55 ++++++++++++++++++++++++++++++++---------
 tests/ngff/test_ngff.py | 31 +++++++++++++++++------
 2 files changed, 68 insertions(+), 18 deletions(-)

diff --git a/iohub/ngff/nodes.py b/iohub/ngff/nodes.py
index 6352f846..c161fbf9 100644
--- a/iohub/ngff/nodes.py
+++ b/iohub/ngff/nodes.py
@@ -1010,20 +1010,22 @@ def get_axis_index(self, axis_name: str) -> int:
         """
         return self.axis_names.index(axis_name.lower())
 
-    def get_transforms(
+    def get_effective_scale(
         self,
         image: str | Literal["*"],
-    ) -> tuple[TransformationMeta, TransformationMeta]:
-        """Get the total coordinate scale and translation metadata
+    ) -> TransformationMeta:
+        """Get the total coordinate scale metadata
         for one image array or the whole FOV.
 
         Parameters
         ----------
         image : str | Literal["*"]
-            Name of one image array (e.g. "0") to transform,
+            Name of one image array (e.g. "0") to query,
             or "*" for the whole FOV
         """
-        transforms: list[TransformationMeta] = self.metadata.multiscales[0].coordinate_transformations
+        transforms: list[TransformationMeta] = [t for t in self.metadata.multiscales[
+            0
+        ].coordinate_transformations]
         if image != "*" and image in self:
             for i, dataset_meta in enumerate(self.metadata.multiscales[0].datasets):
                 if dataset_meta.path == image:
@@ -1035,17 +1037,48 @@ def get_transforms(
         elif image != "*":
             raise ValueError(f"Key {image} not recognized.")
 
-        full_scale = np.array([1]*len(self.axes), dtype=float)
-        full_translation = np.array([0]*len(self.axes), dtype=float)
+        full_scale = np.ones(len(self.axes), dtype=float)
         for transform in transforms:
             if transform.type == "scale":
                 full_scale *= np.array(transform.scale)
-            elif transform.type == "translation":
-                full_translation += full_scale * np.array(transform.translation)
+
+        return TransformationMeta(type="scale", scale=tuple(full_scale))
+
+    def get_effective_translation(
+        self,
+        image: str | Literal["*"],
+    ) -> TransformationMeta:
+        """Get the total 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
+        """
+        transforms: list[TransformationMeta] = [
+            t for t in self.metadata.multiscales[0].coordinate_transformations
+        ]
+        if image != "*" and image in self:
+            for i, dataset_meta in enumerate(self.metadata.multiscales[0].datasets):
+                if dataset_meta.path == image:
+                    transforms.extend(
+                        self.metadata.multiscales[0]
+                        .datasets[i]
+                        .coordinate_transformations
+                    )
+        elif image != "*":
+            raise ValueError(f"Key {image} not recognized.")
+
+        full_translation = np.zeros(len(self.axes), dtype=float)
+        for transform in transforms:
+            if transform.type == "translation":
+                full_translation += np.array(transform.translation)
 
         return TransformationMeta(
-            type="scale", scale=tuple(full_scale)
-        ), TransformationMeta(type="translation", translation=tuple(full_translation))
+            type="translation", translation=tuple(full_translation)
+        )
 
     def set_transform(
         self,
diff --git a/tests/ngff/test_ngff.py b/tests/ngff/test_ngff.py
index 48cfddfb..7ef20b7a 100644
--- a/tests/ngff/test_ngff.py
+++ b/tests/ngff/test_ngff.py
@@ -491,25 +491,39 @@ def test_set_transform_image(ch_shape_dtype, arr_name):
         (
             [TransformationMeta(type="identity")],
             TransformationMeta(type="scale", scale=(1.0, 1.0, 1.0, 1.0, 1.0)),
-            TransformationMeta(type="translation", translation=(0.0, 0.0, 0.0, 0.0, 0.0)),
+            TransformationMeta(
+                type="translation", translation=(0.0, 0.0, 0.0, 0.0, 0.0)
+            ),
         ),
         (
             [TransformationMeta(type="scale", scale=(1.0, 2.0, 3.0, 4.0, 5.0))],
             TransformationMeta(type="scale", scale=(1.0, 2.0, 3.0, 4.0, 5.0)),
-            TransformationMeta(type="translation", translation=(0.0, 0.0, 0.0, 0.0, 0.0)),
+            TransformationMeta(
+                type="translation", translation=(0.0, 0.0, 0.0, 0.0, 0.0)
+            ),
         ),
         (
-            [TransformationMeta(type="translation", translation=(1.0, 2.0, 3.0, 4.0, 5.0))],
+            [
+                TransformationMeta(
+                    type="translation", translation=(1.0, 2.0, 3.0, 4.0, 5.0)
+                )
+            ],
             TransformationMeta(type="scale", scale=(1.0, 1.0, 1.0, 1.0, 1.0)),
-            TransformationMeta(type="translation", translation=(1.0, 2.0, 3.0, 4.0, 5.0)),
+            TransformationMeta(
+                type="translation", translation=(1.0, 2.0, 3.0, 4.0, 5.0)
+            ),
         ),
         (
             [
                 TransformationMeta(type="scale", scale=(2.0, 2.0, 2.0, 2.0, 2.0)),
-                TransformationMeta(type="translation", translation=(1.0, 1.0, 1.0, 1.0, 1.0)),
+                TransformationMeta(
+                    type="translation", translation=(1.0, 1.0, 1.0, 1.0, 1.0)
+                ),
             ],
             TransformationMeta(type="scale", scale=(2.0, 2.0, 2.0, 2.0, 2.0)),
-            TransformationMeta(type="translation", translation=(2.0, 2.0, 2.0, 2.0, 2.0)),
+            TransformationMeta(
+                type="translation", translation=(1.0, 1.0, 1.0, 1.0, 1.0)
+            ),
         ),
     ],
 )
@@ -531,7 +545,10 @@ def test_get_transform_image(transforms, ch_shape_dtype, arr_name):
                 0
             ].coordinate_transformations == [TransformationMeta(type="identity")]
             dataset.set_transform(image=arr_name, transform=transform)
-            scale, translate = dataset.get_transforms(image=arr_name)
+            scale, translate = (
+                dataset.get_effective_scale(image=arr_name),
+                dataset.get_effective_translation(image=arr_name),
+            )
             assert scale == expected_scale
             assert translate == expected_translate
 

From fc31a1098cfcb6f0b97153e91266ce7326189079 Mon Sep 17 00:00:00 2001
From: William Patton <wllmpttn24@gmail.com>
Date: Tue, 10 Dec 2024 12:31:32 -0800
Subject: [PATCH 04/13] black formatting changes

---
 iohub/ngff/nodes.py     | 14 +++++++++-----
 tests/ngff/test_ngff.py | 14 +++++++++++---
 2 files changed, 20 insertions(+), 8 deletions(-)

diff --git a/iohub/ngff/nodes.py b/iohub/ngff/nodes.py
index c161fbf9..359ee262 100644
--- a/iohub/ngff/nodes.py
+++ b/iohub/ngff/nodes.py
@@ -1023,11 +1023,13 @@ def get_effective_scale(
             Name of one image array (e.g. "0") to query,
             or "*" for the whole FOV
         """
-        transforms: list[TransformationMeta] = [t for t in self.metadata.multiscales[
-            0
-        ].coordinate_transformations]
+        transforms: list[TransformationMeta] = [
+            t for t in self.metadata.multiscales[0].coordinate_transformations
+        ]
         if image != "*" and image in self:
-            for i, dataset_meta in enumerate(self.metadata.multiscales[0].datasets):
+            for i, dataset_meta in enumerate(
+                self.metadata.multiscales[0].datasets
+            ):
                 if dataset_meta.path == image:
                     transforms.extend(
                         self.metadata.multiscales[0]
@@ -1061,7 +1063,9 @@ def get_effective_translation(
             t for t in self.metadata.multiscales[0].coordinate_transformations
         ]
         if image != "*" and image in self:
-            for i, dataset_meta in enumerate(self.metadata.multiscales[0].datasets):
+            for i, dataset_meta in enumerate(
+                self.metadata.multiscales[0].datasets
+            ):
                 if dataset_meta.path == image:
                     transforms.extend(
                         self.metadata.multiscales[0]
diff --git a/tests/ngff/test_ngff.py b/tests/ngff/test_ngff.py
index 7ef20b7a..293c37ac 100644
--- a/tests/ngff/test_ngff.py
+++ b/tests/ngff/test_ngff.py
@@ -496,7 +496,11 @@ def test_set_transform_image(ch_shape_dtype, arr_name):
             ),
         ),
         (
-            [TransformationMeta(type="scale", scale=(1.0, 2.0, 3.0, 4.0, 5.0))],
+            [
+                TransformationMeta(
+                    type="scale", scale=(1.0, 2.0, 3.0, 4.0, 5.0)
+                )
+            ],
             TransformationMeta(type="scale", scale=(1.0, 2.0, 3.0, 4.0, 5.0)),
             TransformationMeta(
                 type="translation", translation=(0.0, 0.0, 0.0, 0.0, 0.0)
@@ -515,7 +519,9 @@ def test_set_transform_image(ch_shape_dtype, arr_name):
         ),
         (
             [
-                TransformationMeta(type="scale", scale=(2.0, 2.0, 2.0, 2.0, 2.0)),
+                TransformationMeta(
+                    type="scale", scale=(2.0, 2.0, 2.0, 2.0, 2.0)
+                ),
                 TransformationMeta(
                     type="translation", translation=(1.0, 1.0, 1.0, 1.0, 1.0)
                 ),
@@ -543,7 +549,9 @@ def test_get_transform_image(transforms, ch_shape_dtype, arr_name):
             dataset.create_zeros(name=arr_name, shape=shape, dtype=dtype)
             assert dataset.metadata.multiscales[0].datasets[
                 0
-            ].coordinate_transformations == [TransformationMeta(type="identity")]
+            ].coordinate_transformations == [
+                TransformationMeta(type="identity")
+            ]
             dataset.set_transform(image=arr_name, transform=transform)
             scale, translate = (
                 dataset.get_effective_scale(image=arr_name),

From d13942ca67a2306baf9c1b6e418c749caf485ba4 Mon Sep 17 00:00:00 2001
From: William Patton <wllmpttn24@gmail.com>
Date: Wed, 11 Dec 2024 10:47:40 -0800
Subject: [PATCH 05/13] update test_get_transform_image test name

---
 tests/ngff/test_ngff.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/ngff/test_ngff.py b/tests/ngff/test_ngff.py
index 293c37ac..3b3ba1eb 100644
--- a/tests/ngff/test_ngff.py
+++ b/tests/ngff/test_ngff.py
@@ -537,7 +537,7 @@ def test_set_transform_image(ch_shape_dtype, arr_name):
     ch_shape_dtype=_channels_and_random_5d_shape_and_dtype(),
     arr_name=short_alpha_numeric,
 )
-def test_get_transform_image(transforms, ch_shape_dtype, arr_name):
+def test_get_effective_transforms_image(transforms, ch_shape_dtype, arr_name):
     """Test `iohub.ngff.Position.set_transform()`"""
     transform, expected_scale, expected_translate = transforms
     channel_names, shape, dtype = ch_shape_dtype

From 67848bc196a9ba822e618d7c239b01e82ab8d562 Mon Sep 17 00:00:00 2001
From: William Patton <wllmpttn24@gmail.com>
Date: Wed, 11 Dec 2024 10:53:08 -0800
Subject: [PATCH 06/13] factor out retrieving the list of all applicable
 transforms and improve docs

---
 iohub/ngff/nodes.py | 61 +++++++++++++++++++++++++++++----------------
 1 file changed, 39 insertions(+), 22 deletions(-)

diff --git a/iohub/ngff/nodes.py b/iohub/ngff/nodes.py
index 359ee262..effee389 100644
--- a/iohub/ngff/nodes.py
+++ b/iohub/ngff/nodes.py
@@ -1010,11 +1010,10 @@ def get_axis_index(self, axis_name: str) -> int:
         """
         return self.axis_names.index(axis_name.lower())
 
-    def get_effective_scale(
-        self,
-        image: str | Literal["*"],
-    ) -> TransformationMeta:
-        """Get the total coordinate scale metadata
+    def _get_all_transforms(
+        self, image: str | Literal["*"]
+    ) -> list[TransformationMeta]:
+        """Get all transforms metadata
         for one image array or the whole FOV.
 
         Parameters
@@ -1022,6 +1021,11 @@ def get_effective_scale(
         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 self.metadata.multiscales[0].coordinate_transformations
@@ -1038,6 +1042,28 @@ def get_effective_scale(
                     )
         elif image != "*":
             raise ValueError(f"Key {image} not recognized.")
+        return transforms
+
+    def get_effective_scale(
+        self,
+        image: str | Literal["*"],
+    ) -> TransformationMeta:
+        """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
+        -------
+        TransformationMeta
+            A single TransformationMeta object with the total
+            scale factor for the image or FOV.
+        """
+        transforms = self._get_all_transforms(image)
 
         full_scale = np.ones(len(self.axes), dtype=float)
         for transform in transforms:
@@ -1050,7 +1076,7 @@ def get_effective_translation(
         self,
         image: str | Literal["*"],
     ) -> TransformationMeta:
-        """Get the total coordinate translation metadata
+        """Get the effective coordinate translation metadata
         for one image array or the whole FOV.
 
         Parameters
@@ -1058,23 +1084,14 @@ def get_effective_translation(
         image : str | Literal["*"]
             Name of one image array (e.g. "0") to query,
             or "*" for the whole FOV
-        """
-        transforms: list[TransformationMeta] = [
-            t for t in self.metadata.multiscales[0].coordinate_transformations
-        ]
-        if image != "*" and image in self:
-            for i, dataset_meta in enumerate(
-                self.metadata.multiscales[0].datasets
-            ):
-                if dataset_meta.path == image:
-                    transforms.extend(
-                        self.metadata.multiscales[0]
-                        .datasets[i]
-                        .coordinate_transformations
-                    )
-        elif image != "*":
-            raise ValueError(f"Key {image} not recognized.")
 
+        Returns
+        -------
+        TransformationMeta
+            A single TransformationMeta object with the total
+            translation vector for the image or FOV.
+        """
+        transforms = self._get_all_transforms(image)
         full_translation = np.zeros(len(self.axes), dtype=float)
         for transform in transforms:
             if transform.type == "translation":

From 6fc5ad6616eeccc49d14dd84c60d616429abc9e3 Mon Sep 17 00:00:00 2001
From: William Patton <wllmpttn24@gmail.com>
Date: Wed, 11 Dec 2024 10:54:52 -0800
Subject: [PATCH 07/13] use get_effective_scale to simplify the scale property

---
 iohub/ngff/nodes.py | 14 +-------------
 1 file changed, 1 insertion(+), 13 deletions(-)

diff --git a/iohub/ngff/nodes.py b/iohub/ngff/nodes.py
index effee389..6452170c 100644
--- a/iohub/ngff/nodes.py
+++ b/iohub/ngff/nodes.py
@@ -969,19 +969,7 @@ def scale(self) -> list[float]:
         Helper function for scale transform metadata of
         highest resolution scale.
         """
-        scale = [1] * self.data.ndim
-        transforms = (
-            self.metadata.multiscales[0].datasets[0].coordinate_transformations
-        )
-        for trans in transforms:
-            if trans.type == "scale":
-                if len(trans.scale) != len(scale):
-                    raise RuntimeError(
-                        f"Length of scale transformation {len(trans.scale)} "
-                        f"does not match data dimension {len(scale)}."
-                    )
-                scale = [s1 * s2 for s1, s2 in zip(scale, trans.scale)]
-        return scale
+        return self.get_effective_scale("*").scale
 
     @property
     def axis_names(self) -> list[str]:

From d3a8b43ab4bb501bc655f856ae67af322bcd0420 Mon Sep 17 00:00:00 2001
From: William Patton <wllmpttn24@gmail.com>
Date: Wed, 11 Dec 2024 12:03:31 -0800
Subject: [PATCH 08/13] use the first array's path in `scale` property to get
 the highest resolution image metadata

---
 iohub/ngff/nodes.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/iohub/ngff/nodes.py b/iohub/ngff/nodes.py
index 6452170c..49778c31 100644
--- a/iohub/ngff/nodes.py
+++ b/iohub/ngff/nodes.py
@@ -969,7 +969,9 @@ def scale(self) -> list[float]:
         Helper function for scale transform metadata of
         highest resolution scale.
         """
-        return self.get_effective_scale("*").scale
+        return self.get_effective_scale(
+            self.metadata.multiscales[0].datasets[0].path
+        ).scale
 
     @property
     def axis_names(self) -> list[str]:

From e3f6ea188cedcf9498a8f9a96c1d2f46f1e217d4 Mon Sep 17 00:00:00 2001
From: William Patton <wllmpttn24@gmail.com>
Date: Wed, 11 Dec 2024 12:25:04 -0800
Subject: [PATCH 09/13] Separate test into 2, and cover cases where both the
 fov and image have scale and translation transforms

---
 tests/ngff/test_ngff.py | 130 ++++++++++++++++++++++++----------------
 1 file changed, 78 insertions(+), 52 deletions(-)

diff --git a/tests/ngff/test_ngff.py b/tests/ngff/test_ngff.py
index 3b3ba1eb..9eb0a634 100644
--- a/tests/ngff/test_ngff.py
+++ b/tests/ngff/test_ngff.py
@@ -485,61 +485,68 @@ def test_set_transform_image(ch_shape_dtype, arr_name):
         ]
 
 
-@pytest.mark.parametrize(
-    "transforms",
-    [
-        (
-            [TransformationMeta(type="identity")],
-            TransformationMeta(type="scale", scale=(1.0, 1.0, 1.0, 1.0, 1.0)),
-            TransformationMeta(
-                type="translation", translation=(0.0, 0.0, 0.0, 0.0, 0.0)
-            ),
-        ),
-        (
-            [
-                TransformationMeta(
-                    type="scale", scale=(1.0, 2.0, 3.0, 4.0, 5.0)
-                )
-            ],
-            TransformationMeta(type="scale", scale=(1.0, 2.0, 3.0, 4.0, 5.0)),
-            TransformationMeta(
-                type="translation", translation=(0.0, 0.0, 0.0, 0.0, 0.0)
-            ),
-        ),
-        (
-            [
-                TransformationMeta(
-                    type="translation", translation=(1.0, 2.0, 3.0, 4.0, 5.0)
-                )
-            ],
-            TransformationMeta(type="scale", scale=(1.0, 1.0, 1.0, 1.0, 1.0)),
+input_transformations = [
+    ([TransformationMeta(type="identity")], []),
+    ([TransformationMeta(type="scale", scale=(1.0, 2.0, 3.0, 4.0, 5.0))], []),
+    (
+        [
             TransformationMeta(
                 type="translation", translation=(1.0, 2.0, 3.0, 4.0, 5.0)
+            )
+        ],
+        [],
+    ),
+    (
+        [
+            TransformationMeta(type="scale", scale=(2.0, 2.0, 2.0, 2.0, 2.0)),
+            TransformationMeta(
+                type="translation", translation=(1.0, 1.0, 1.0, 1.0, 1.0)
             ),
-        ),
-        (
-            [
-                TransformationMeta(
-                    type="scale", scale=(2.0, 2.0, 2.0, 2.0, 2.0)
-                ),
-                TransformationMeta(
-                    type="translation", translation=(1.0, 1.0, 1.0, 1.0, 1.0)
-                ),
-            ],
+        ],
+        [
             TransformationMeta(type="scale", scale=(2.0, 2.0, 2.0, 2.0, 2.0)),
             TransformationMeta(
                 type="translation", translation=(1.0, 1.0, 1.0, 1.0, 1.0)
             ),
-        ),
+        ],
+    ),
+]
+target_scales = [
+    TransformationMeta(type="scale", scale=(1.0, 1.0, 1.0, 1.0, 1.0)),
+    TransformationMeta(type="scale", scale=(1.0, 2.0, 3.0, 4.0, 5.0)),
+    TransformationMeta(type="scale", scale=(1.0, 1.0, 1.0, 1.0, 1.0)),
+    TransformationMeta(type="scale", scale=(4.0, 4.0, 4.0, 4.0, 4.0)),
+]
+target_translations = [
+    TransformationMeta(
+        type="translation", translation=(0.0, 0.0, 0.0, 0.0, 0.0)
+    ),
+    TransformationMeta(
+        type="translation", translation=(0.0, 0.0, 0.0, 0.0, 0.0)
+    ),
+    TransformationMeta(
+        type="translation", translation=(1.0, 2.0, 3.0, 4.0, 5.0)
+    ),
+    TransformationMeta(
+        type="translation", translation=(2.0, 2.0, 2.0, 2.0, 2.0)
+    ),
+]
+
+
+@pytest.mark.parametrize(
+    "transforms",
+    [
+        (saved, target)
+        for saved, target in zip(input_transformations, target_scales)
     ],
 )
 @given(
     ch_shape_dtype=_channels_and_random_5d_shape_and_dtype(),
     arr_name=short_alpha_numeric,
 )
-def test_get_effective_transforms_image(transforms, ch_shape_dtype, arr_name):
+def test_get_effective_scale_image(transforms, ch_shape_dtype, arr_name):
     """Test `iohub.ngff.Position.set_transform()`"""
-    transform, expected_scale, expected_translate = transforms
+    (fov_transform, img_transform), expected_scale = transforms
     channel_names, shape, dtype = ch_shape_dtype
     with TemporaryDirectory() as temp_dir:
         store_path = os.path.join(temp_dir, "ome.zarr")
@@ -547,18 +554,37 @@ def test_get_effective_transforms_image(transforms, ch_shape_dtype, arr_name):
             store_path, layout="fov", mode="w-", channel_names=channel_names
         ) as dataset:
             dataset.create_zeros(name=arr_name, shape=shape, dtype=dtype)
-            assert dataset.metadata.multiscales[0].datasets[
-                0
-            ].coordinate_transformations == [
-                TransformationMeta(type="identity")
-            ]
-            dataset.set_transform(image=arr_name, transform=transform)
-            scale, translate = (
-                dataset.get_effective_scale(image=arr_name),
-                dataset.get_effective_translation(image=arr_name),
-            )
+            dataset.set_transform(image="*", transform=fov_transform)
+            dataset.set_transform(image=arr_name, transform=img_transform)
+            scale = dataset.get_effective_scale(image=arr_name)
             assert scale == expected_scale
-            assert translate == expected_translate
+
+
+@pytest.mark.parametrize(
+    "transforms",
+    [
+        (saved, target)
+        for saved, target in zip(input_transformations, target_translations)
+    ],
+)
+@given(
+    ch_shape_dtype=_channels_and_random_5d_shape_and_dtype(),
+    arr_name=short_alpha_numeric,
+)
+def test_get_effective_translation_image(transforms, ch_shape_dtype, arr_name):
+    """Test `iohub.ngff.Position.set_transform()`"""
+    (fov_transform, img_transform), expected_translation = transforms
+    channel_names, shape, dtype = ch_shape_dtype
+    with TemporaryDirectory() as temp_dir:
+        store_path = os.path.join(temp_dir, "ome.zarr")
+        with open_ome_zarr(
+            store_path, layout="fov", mode="w-", channel_names=channel_names
+        ) as dataset:
+            dataset.create_zeros(name=arr_name, shape=shape, dtype=dtype)
+            dataset.set_transform(image="*", transform=fov_transform)
+            dataset.set_transform(image=arr_name, transform=img_transform)
+            translation = dataset.get_effective_translation(image=arr_name)
+            assert translation == expected_translation
 
 
 @given(

From c96a0ccbce7442b18ca28a6fd27ef82206f922ca Mon Sep 17 00:00:00 2001
From: William Patton <wllmpttn24@gmail.com>
Date: Wed, 11 Dec 2024 12:27:24 -0800
Subject: [PATCH 10/13] Return effective scale and transform as simple lists of
 floats instead of TransformationMeta

---
 iohub/ngff/nodes.py     | 22 ++++++++++------------
 tests/ngff/test_ngff.py | 24 ++++++++----------------
 2 files changed, 18 insertions(+), 28 deletions(-)

diff --git a/iohub/ngff/nodes.py b/iohub/ngff/nodes.py
index 49778c31..8089a211 100644
--- a/iohub/ngff/nodes.py
+++ b/iohub/ngff/nodes.py
@@ -971,7 +971,7 @@ def scale(self) -> list[float]:
         """
         return self.get_effective_scale(
             self.metadata.multiscales[0].datasets[0].path
-        ).scale
+        )
 
     @property
     def axis_names(self) -> list[str]:
@@ -1037,7 +1037,7 @@ def _get_all_transforms(
     def get_effective_scale(
         self,
         image: str | Literal["*"],
-    ) -> TransformationMeta:
+    ) -> list[float]:
         """Get the effective coordinate scale metadata
         for one image array or the whole FOV.
 
@@ -1049,9 +1049,9 @@ def get_effective_scale(
 
         Returns
         -------
-        TransformationMeta
-            A single TransformationMeta object with the total
-            scale factor for the image or FOV.
+        list[float]
+            A list of floats representing the total scale
+            for the image or FOV for each axis.
         """
         transforms = self._get_all_transforms(image)
 
@@ -1060,7 +1060,7 @@ def get_effective_scale(
             if transform.type == "scale":
                 full_scale *= np.array(transform.scale)
 
-        return TransformationMeta(type="scale", scale=tuple(full_scale))
+        return list(full_scale)
 
     def get_effective_translation(
         self,
@@ -1077,9 +1077,9 @@ def get_effective_translation(
 
         Returns
         -------
-        TransformationMeta
-            A single TransformationMeta object with the total
-            translation vector for the image or FOV.
+        list[float]
+            A list of floats representing the total translation
+            for the image or FOV for each axis.
         """
         transforms = self._get_all_transforms(image)
         full_translation = np.zeros(len(self.axes), dtype=float)
@@ -1087,9 +1087,7 @@ def get_effective_translation(
             if transform.type == "translation":
                 full_translation += np.array(transform.translation)
 
-        return TransformationMeta(
-            type="translation", translation=tuple(full_translation)
-        )
+        return list(full_translation)
 
     def set_transform(
         self,
diff --git a/tests/ngff/test_ngff.py b/tests/ngff/test_ngff.py
index 9eb0a634..a9705f09 100644
--- a/tests/ngff/test_ngff.py
+++ b/tests/ngff/test_ngff.py
@@ -512,24 +512,16 @@ def test_set_transform_image(ch_shape_dtype, arr_name):
     ),
 ]
 target_scales = [
-    TransformationMeta(type="scale", scale=(1.0, 1.0, 1.0, 1.0, 1.0)),
-    TransformationMeta(type="scale", scale=(1.0, 2.0, 3.0, 4.0, 5.0)),
-    TransformationMeta(type="scale", scale=(1.0, 1.0, 1.0, 1.0, 1.0)),
-    TransformationMeta(type="scale", scale=(4.0, 4.0, 4.0, 4.0, 4.0)),
+    (1.0, 1.0, 1.0, 1.0, 1.0),
+    (1.0, 2.0, 3.0, 4.0, 5.0),
+    (1.0, 1.0, 1.0, 1.0, 1.0),
+    (4.0, 4.0, 4.0, 4.0, 4.0),
 ]
 target_translations = [
-    TransformationMeta(
-        type="translation", translation=(0.0, 0.0, 0.0, 0.0, 0.0)
-    ),
-    TransformationMeta(
-        type="translation", translation=(0.0, 0.0, 0.0, 0.0, 0.0)
-    ),
-    TransformationMeta(
-        type="translation", translation=(1.0, 2.0, 3.0, 4.0, 5.0)
-    ),
-    TransformationMeta(
-        type="translation", translation=(2.0, 2.0, 2.0, 2.0, 2.0)
-    ),
+    (0.0, 0.0, 0.0, 0.0, 0.0),
+    (0.0, 0.0, 0.0, 0.0, 0.0),
+    (1.0, 2.0, 3.0, 4.0, 5.0),
+    (2.0, 2.0, 2.0, 2.0, 2.0),
 ]
 
 

From a50240755020d6ee1988112edd0719aabfac8e7a Mon Sep 17 00:00:00 2001
From: William Patton <wllmpttn24@gmail.com>
Date: Wed, 11 Dec 2024 12:31:57 -0800
Subject: [PATCH 11/13] Return plain floats instead of numpy floats

---
 iohub/ngff/nodes.py     |  4 ++--
 tests/ngff/test_ngff.py | 16 ++++++++--------
 2 files changed, 10 insertions(+), 10 deletions(-)

diff --git a/iohub/ngff/nodes.py b/iohub/ngff/nodes.py
index 8089a211..f05adbcf 100644
--- a/iohub/ngff/nodes.py
+++ b/iohub/ngff/nodes.py
@@ -1060,7 +1060,7 @@ def get_effective_scale(
             if transform.type == "scale":
                 full_scale *= np.array(transform.scale)
 
-        return list(full_scale)
+        return [float(x) for x in full_scale]
 
     def get_effective_translation(
         self,
@@ -1087,7 +1087,7 @@ def get_effective_translation(
             if transform.type == "translation":
                 full_translation += np.array(transform.translation)
 
-        return list(full_translation)
+        return [float(x) for x in full_translation]
 
     def set_transform(
         self,
diff --git a/tests/ngff/test_ngff.py b/tests/ngff/test_ngff.py
index a9705f09..837c4ddb 100644
--- a/tests/ngff/test_ngff.py
+++ b/tests/ngff/test_ngff.py
@@ -512,16 +512,16 @@ def test_set_transform_image(ch_shape_dtype, arr_name):
     ),
 ]
 target_scales = [
-    (1.0, 1.0, 1.0, 1.0, 1.0),
-    (1.0, 2.0, 3.0, 4.0, 5.0),
-    (1.0, 1.0, 1.0, 1.0, 1.0),
-    (4.0, 4.0, 4.0, 4.0, 4.0),
+    [1.0, 1.0, 1.0, 1.0, 1.0],
+    [1.0, 2.0, 3.0, 4.0, 5.0],
+    [1.0, 1.0, 1.0, 1.0, 1.0],
+    [4.0, 4.0, 4.0, 4.0, 4.0],
 ]
 target_translations = [
-    (0.0, 0.0, 0.0, 0.0, 0.0),
-    (0.0, 0.0, 0.0, 0.0, 0.0),
-    (1.0, 2.0, 3.0, 4.0, 5.0),
-    (2.0, 2.0, 2.0, 2.0, 2.0),
+    [0.0, 0.0, 0.0, 0.0, 0.0],
+    [0.0, 0.0, 0.0, 0.0, 0.0],
+    [1.0, 2.0, 3.0, 4.0, 5.0],
+    [2.0, 2.0, 2.0, 2.0, 2.0],
 ]
 
 

From 49fe3ae6fd928b6f161166fa0caac9b398142c18 Mon Sep 17 00:00:00 2001
From: William Patton <wllmpttn24@gmail.com>
Date: Thu, 19 Dec 2024 09:18:36 -0500
Subject: [PATCH 12/13] fix test docstring

---
 tests/ngff/test_ngff.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/tests/ngff/test_ngff.py b/tests/ngff/test_ngff.py
index 837c4ddb..1e3ff9e5 100644
--- a/tests/ngff/test_ngff.py
+++ b/tests/ngff/test_ngff.py
@@ -537,7 +537,7 @@ def test_set_transform_image(ch_shape_dtype, arr_name):
     arr_name=short_alpha_numeric,
 )
 def test_get_effective_scale_image(transforms, ch_shape_dtype, arr_name):
-    """Test `iohub.ngff.Position.set_transform()`"""
+    """Test `iohub.ngff.Position.get_effective_scale()`"""
     (fov_transform, img_transform), expected_scale = transforms
     channel_names, shape, dtype = ch_shape_dtype
     with TemporaryDirectory() as temp_dir:
@@ -564,7 +564,7 @@ def test_get_effective_scale_image(transforms, ch_shape_dtype, arr_name):
     arr_name=short_alpha_numeric,
 )
 def test_get_effective_translation_image(transforms, ch_shape_dtype, arr_name):
-    """Test `iohub.ngff.Position.set_transform()`"""
+    """Test `iohub.ngff.Position.get_effective_translation()`"""
     (fov_transform, img_transform), expected_translation = transforms
     channel_names, shape, dtype = ch_shape_dtype
     with TemporaryDirectory() as temp_dir:

From c3b258b8b6aaf635797dc91f70e581671acea301 Mon Sep 17 00:00:00 2001
From: William Patton <wllmpttn24@gmail.com>
Date: Thu, 19 Dec 2024 09:26:03 -0500
Subject: [PATCH 13/13] Handle case where
 `self.metadata.multiscales[0].coordinate_transformations` is `None`

---
 iohub/ngff/nodes.py | 14 +++++++++++---
 1 file changed, 11 insertions(+), 3 deletions(-)

diff --git a/iohub/ngff/nodes.py b/iohub/ngff/nodes.py
index f05adbcf..e96a1276 100644
--- a/iohub/ngff/nodes.py
+++ b/iohub/ngff/nodes.py
@@ -1017,9 +1017,17 @@ def _get_all_transforms(
         list[TransformationMeta]
             All transforms applicable to this image or FOV.
         """
-        transforms: list[TransformationMeta] = [
-            t for t in self.metadata.multiscales[0].coordinate_transformations
-        ]
+        transforms: list[TransformationMeta] = (
+            [
+                t
+                for t in self.metadata.multiscales[
+                    0
+                ].coordinate_transformations
+            ]
+            if self.metadata.multiscales[0].coordinate_transformations
+            is not None
+            else []
+        )
         if image != "*" and image in self:
             for i, dataset_meta in enumerate(
                 self.metadata.multiscales[0].datasets