Migrate from aicsimageio to bioio

core/lls_core/deconvolution.py

@@ -7,7 +7,7 @@
 import logging
 import importlib.util
 from typing import Collection, Iterable,Union,Literal, Optional, TYPE_CHECKING
-from aicsimageio.aics_image import AICSImage
+from bioio import BioImage
 from skimage.io import imread
 from aicspylibczi import CziFile
 from numpy.typing import NDArray
@@ -79,8 +79,8 @@ def read_psf(psf_paths: Collection[Path],
                    if len(psf_aics_data.shape) != 3:
                        raise ValueError(f"PSF should be a 3D image (shape of 3), but got {psf_aics.shape}")
                 else:
-                    #Use AICSImageIO
-                    psf_aics = AICSImage(str(psf))
+                    #Use BioIO
+                    psf_aics = BioImage(str(psf))
                     psf_aics_data = psf_aics.data[0][0]
                     psf_aics_data = pad_image_nearest_multiple(
                         img=psf_aics_data, nearest_multiple=16)           

core/lls_core/models/deskew.py

@@ -16,7 +16,7 @@
 import numpy as np
 
 if TYPE_CHECKING:
-    from aicsimageio.types import PhysicalPixelSizes
+    from bioio import PhysicalPixelSizes
 
 class DefinedPixelSizes(FieldAccessModel):
     """
@@ -161,7 +161,7 @@ def convert_skew(cls, v: Any):
 
     @validator("physical_pixel_sizes", pre=True, always=True)
     def convert_pixels(cls, v: Any, values: dict[Any, Any]):
-        from aicsimageio.types import PhysicalPixelSizes
+        from bioio import PhysicalPixelSizes
         if isinstance(v, PhysicalPixelSizes):
             v = DefinedPixelSizes.from_physical(v)
         elif isinstance(v, tuple) and len(v) == 3:
@@ -176,15 +176,15 @@ def convert_pixels(cls, v: Any, values: dict[Any, Any]):
 
     @root_validator(pre=True)
     def read_image(cls, values: dict):
-        from aicsimageio import AICSImage
+        from bioio import BioImage
         from os import fspath
 
         img = values["input_image"]
 
-        aics: AICSImage | None = None
+        aics: BioImage | None = None
         if is_pathlike(img):
-            aics = AICSImage(fspath(img))
-        elif isinstance(img, AICSImage):
+            aics = BioImage(fspath(img))
+        elif isinstance(img, BioImage):
             aics = img
         elif isinstance(img, DataArray):
             if set(img.dims) >= {"Z", "Y", "X"}:
@@ -198,9 +198,9 @@ def read_image(cls, values: dict):
             else:
                 raise ValueError("Only 3D numpy arrays are currently supported. If you have a different shape, please use a DataArray and name your dimensions C, T, Z, Y and/or Z.")
         else:
-            raise ValueError("Value of input_image was neither a path, an AICSImage, or array-like.")
+            raise ValueError("Value of input_image was neither a path, a BioImage, or array-like.")
 
-        # If the image was convertible to AICSImage, we should use the metadata from there
+        # If the image was convertible to BioImage, we should use the metadata from there
         if aics:
             values["input_image"] = aics.xarray_dask_data 
             # Take pixel sizes from the image metadata, but only if they're defined

core/lls_core/types.py

@@ -6,7 +6,7 @@
 import numpy as np
 from numpy.typing import NDArray
 from xarray import DataArray
-from aicsimageio import AICSImage
+from bioio import BioImage
 from os import fspath, PathLike as OriginalPathLike
 
 # This is a superset of os.PathLike
@@ -19,20 +19,20 @@ def is_pathlike(x: Any) -> TypeGuard[PathLike]:
 def is_arraylike(arr: Any) -> TypeGuard[ArrayLike]:
     return isinstance(arr, (DaskArray, np.ndarray, OCLArray, DataArray))
 
-ImageLike: TypeAlias = Union[PathLike, AICSImage, ArrayLike]
-def image_like_to_image(img: ImageLike) -> DataArray:
-    """
-    Converts an image in one of many formats to a DataArray
-    """
-    # First try treating it as a path
-    try:
-        img = AICSImage(fspath(img))
-    except TypeError:
-        pass
-    if isinstance(img, AICSImage):
-        return img.xarray_dask_data
-    else:
-        for required_key in ("shape", "dtype", "ndim", "__array__", "__array_ufunc__"):
-            if not hasattr(img, required_key):
-                raise ValueError(f"The provided object {img} is not array like!")
+ImageLike: TypeAlias = Union[PathLike, BioImage, ArrayLike]
+def image_like_to_image(img: ImageLike) -> DataArray:
+    """
+    Converts an image in one of many formats to a DataArray
+    """
+    # First try treating it as a path
+    try:
+        img = BioImage(fspath(img))
+    except TypeError:
+        pass
+    if isinstance(img, BioImage):
+        return img.xarray_dask_data
+    else:
+        for required_key in ("shape", "dtype", "ndim", "__array__", "__array_ufunc__"):
+            if not hasattr(img, required_key):
+                raise ValueError(f"The provided object {img} is not array like!")
         return DataArray(img)

core/pyproject.toml

@@ -35,8 +35,8 @@ classifiers = [
     "License :: OSI Approved :: GNU General Public License v3 (GPLv3)"
 ]
 requires-python = ">=3.8"
-dependencies = [
-    "aicsimageio>=4.6.3",
+dependencies = [
+    "bioio>=3.0.0",
     # Earlier versions don't have Python 3.11 binaries, and the sdist
     # is misconfigured: https://github.com/AllenCellModeling/aicspylibczi/issues/90
     "aicspylibczi>=3.1.1",

core/tests/test_cli.py

@@ -2,7 +2,7 @@
 
 from typing import Callable, List
 import pytest
-from aicsimageio.aics_image import AICSImage
+from bioio import BioImage
 from npy2bdv import BdvEditor
 import numpy as np
 from pathlib import Path
@@ -15,7 +15,7 @@ def create_image(path: Path):
     raw = np.zeros((5, 5, 5))
     raw[2, 4, 2] = 10
     # Save image as a tif filw in home directory
-    AICSImage(raw).save(path)
+    BioImage(raw).save(path)
     assert path.exists()
 
 
@@ -28,7 +28,7 @@ def create_data(dir: Path) -> Path:
     raw = np.zeros((5, 5, 5))
     raw[2, 4, 2] = 10
     # Save image as a tif filw in home directory
-    AICSImage(raw).save(input_file)
+    BioImage(raw).save(input_file)
     assert input_file.exists()
 
     config: dict[str, str] = {
@@ -47,7 +47,7 @@ def assert_tiff(output_dir: Path):
     results = list(output_dir.glob("*.tif"))
     assert len(results) > 0
     for result in results:
-        AICSImage(result).get_image_data()
+        BioImage(result).get_image_data()
 
 def assert_h5(output_dir: Path):
     """Checks that a valid H5 was generated"""

core/tests/utils.py

@@ -3,7 +3,7 @@
 from typer.testing import CliRunner
 from lls_core.cmds.__main__ import app
 import npy2bdv
-from aicsimageio import AICSImage
+from bioio import BioImage
 
 def invoke(args: Sequence[str]):
     CliRunner().invoke(app, args, catch_exceptions=False)
@@ -13,5 +13,5 @@ def valid_image_path(path: Path) -> bool:
         npy2bdv.npy2bdv.BdvEditor(str(path)).read_view()
         return True
     else:
-        AICSImage(path).get_image_data()
+        BioImage(path).get_image_data()
         return True

plugin/napari_lattice/fields.py

@@ -402,7 +402,7 @@ def _get_kwargs(self) -> DeskewKwargs:
         """
         Returns the LatticeData fields that the Deskew tab can provide
         """
-        from aicsimageio.types import PhysicalPixelSizes
+        from bioio import PhysicalPixelSizes
         DeskewParams.update_forward_refs()
         params = lattice_params_from_napari(
                 imgs=self.img_layer.value,

plugin/napari_lattice/reader.py

@@ -13,18 +13,18 @@
 import os 
 import numpy as np
 from napari.layers import Image
-from aicsimageio.aics_image import AICSImage
+from bioio import BioImage
 
 from typing import List, Optional, Tuple, Collection, TYPE_CHECKING, TypedDict
 
-from aicsimageio.types import PhysicalPixelSizes
+from bioio import PhysicalPixelSizes
 from lls_core.models.deskew import DefinedPixelSizes
 
 from logging import getLogger
 logger = getLogger(__name__)
 
 if TYPE_CHECKING:
-    from aicsimageio.types import ImageLike
+    from bioio import ImageLike
     from xarray import DataArray
 
 class NapariImageParams(TypedDict):
@@ -74,7 +74,7 @@ def lattice_params_from_napari(
         save_names.append(save_name)
 
         if 'aicsimage' in img.metadata.keys():
-            img_data_aics: AICSImage = img.metadata['aicsimage']
+            img_data_aics: BioImage = img.metadata['aicsimage']
             # If the user has not provided pixel sizes, we extract them fro the metadata
             # Only process pixel sizes that are not none
             if physical_pixel_sizes is None and all(img_data_aics.physical_pixel_sizes):
@@ -191,13 +191,13 @@ def bdv_h5_reader(path):
     layer_type = "image"  # optional, default is "image"
     return [(images, add_kwargs, layer_type)]
 
-def tiff_reader(path: ImageLike) -> List[Tuple[AICSImage, dict, str]]:
+def tiff_reader(path: ImageLike) -> List[Tuple[BioImage, dict, str]]:
     """Take path to tiff image and returns a list of LayerData tuples.
-    Specifying tiff_reader to have better control over tifffile related errors when using AICSImage
+    Specifying tiff_reader to have better control over tifffile related errors when using BioImage
     """
 
     try:
-        image = AICSImage(path)
+        image = BioImage(path)
     except Exception as e:
         raise Exception("Error reading TIFF. Try upgrading tifffile library: pip install tifffile --upgrade.") from e
 

plugin/pyproject.toml

@@ -35,8 +35,8 @@ classifiers = [
     "License :: OSI Approved :: GNU General Public License v3 (GPLv3)"
 ]
 requires-python = ">=3.8"
-dependencies = [
-    "aicsimageio>=4.6.3",
+dependencies = [
+    "bioio>=3.0.0",
     "dask[distributed]",
     # This isn't used directly, but we need to pin this version
     "fsspec>=2022.8.2",

plugin/tests/test_dock_widget.py

@@ -9,7 +9,7 @@
 from magicclass._gui._gui_modes import ErrorMode
 import pytest
 from lls_core.sample import resources
-from aicsimageio.aics_image import AICSImage
+from bioio import BioImage
 from napari_lattice.fields import PixelSizeSource
 from tempfile import TemporaryDirectory
 
@@ -35,7 +35,7 @@ def image_data(request: pytest.FixtureRequest):
     Fixture function that yields test images as file paths
     """
     with as_file(resources / request.param) as image_path:
-        yield AICSImage(image_path, )
+        yield BioImage(image_path, )
 
 def set_debug(cls: MagicTemplate):
     """
@@ -48,7 +48,7 @@ def _handler(e: Exception, parent: Widget):
     for child in cls.__magicclass_children__:
         set_debug(child)
 
-def test_dock_widget(make_napari_viewer: Callable[[], Viewer], image_data: AICSImage):
+def test_dock_widget(make_napari_viewer: Callable[[], Viewer], image_data: BioImage):
     # make viewer and add an image layer using our fixture
     viewer = make_napari_viewer()