Use AICS metadata even when GUI isn't involved

core/lls_core/models/deskew.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 # class for initializing lattice data and setting metadata
 # TODO: handle scenes
-from pydantic import Field, NonNegativeFloat, validator
+from pydantic import Field, NonNegativeFloat, validator, root_validator
 
 from typing import Any, Tuple
 from typing_extensions import Self, TYPE_CHECKING
@@ -12,7 +12,7 @@
 from xarray import DataArray
 
 from lls_core.models.utils import FieldAccessModel, enum_choices
-from lls_core.types import image_like_to_image
+from lls_core.types import image_like_to_image, is_arraylike, is_pathlike
 from lls_core.utils import get_deskewed_shape
 
 if TYPE_CHECKING:
@@ -164,11 +164,37 @@ def convert_pixels(cls, v: Any):
             return DefinedPixelSizes(Z=v[0], Y=v[1], X=v[2])
         return v
 
+    @root_validator(pre=True)
+    def read_image(cls, values: dict):
+        from aicsimageio import AICSImage
+        from os import fspath
+
+        img = values["input_image"]
+
+        aics: AICSImage | None = None
+        if is_pathlike(img):
+            aics = AICSImage(fspath(img))
+        elif isinstance(img, AICSImage):
+            aics = img
+        elif is_arraylike(img):
+            values["input_image"] = DataArray(img)
+        else:
+            raise ValueError("Value of input_image was neither a path, an AICSImage, or array-like.")
+
+        # If the image was convertible to AICSImage, we should use the metadata from there
+        if aics:
+            values["input_image"] = aics.xarray_dask_data
+            values["physical_pixel_sizes"] = aics.physical_pixel_sizes
+
+        # In all cases, input_image will be a DataArray (XArray) at this point
+
+        return values
+
     @validator("input_image", pre=True)
-    def reshaping(cls, v: Any):
+    def reshaping(cls, v: DataArray):
         # This allows a user to pass in any array-like object and have it
         # converted and reshaped appropriately
-        array = image_like_to_image(v)
+        array = v
         if not set(array.dims).issuperset({"X", "Y", "Z"}):
             raise ValueError("The input array must at least have XYZ coordinates")
         if "T" not in array.dims:

core/lls_core/types.py

@@ -1,38 +1,38 @@
-from typing import Union
-from typing_extensions import TypeGuard, Any, TypeAlias
-from dask.array.core import Array as DaskArray
-# from numpy.typing import NDArray
-from pyopencl.array import Array as OCLArray
-import numpy as np
-from numpy.typing import NDArray
-from xarray import DataArray
-from aicsimageio import AICSImage
-from os import fspath, PathLike as OriginalPathLike
-
-# This is a superset of os.PathLike
-PathLike: TypeAlias = Union[str, bytes, OriginalPathLike]
-def is_pathlike(x: Any) -> TypeGuard[PathLike]:
-    return isinstance(x, (str, bytes, OriginalPathLike))
-
-ArrayLike: TypeAlias = Union[DaskArray, NDArray, OCLArray, DataArray]
-
-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!")
-        return DataArray(img)
+from typing import Union
+from typing_extensions import TypeGuard, Any, TypeAlias
+from dask.array.core import Array as DaskArray
+# from numpy.typing import NDArray
+from pyopencl.array import Array as OCLArray
+import numpy as np
+from numpy.typing import NDArray
+from xarray import DataArray
+from aicsimageio import AICSImage
+from os import fspath, PathLike as OriginalPathLike
+
+# This is a superset of os.PathLike
+PathLike: TypeAlias = Union[str, bytes, OriginalPathLike]
+def is_pathlike(x: Any) -> TypeGuard[PathLike]:
+    return isinstance(x, (str, bytes, OriginalPathLike))
+
+ArrayLike: TypeAlias = Union[DaskArray, NDArray, OCLArray, DataArray]
+
+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!")
+        return DataArray(img)

core/tests/test_validation.py

@@ -2,8 +2,11 @@
 from lls_core.models.crop import CropParams
 from lls_core.models.lattice_data import LatticeData
 from lls_core.models.deskew import DeskewParams
+from lls_core.models.output import OutputParams
 import pytest
 from pydantic import ValidationError
+import tempfile
+from unittest.mock import patch, PropertyMock
 
 def test_default_save_dir(rbc_tiny: Path):
     # Test that the save dir is inferred to be the input dir
@@ -35,3 +38,17 @@ def test_pixel_tuple_order(rbc_tiny: Path):
     assert deskew.physical_pixel_sizes.X == 3.
     assert deskew.physical_pixel_sizes.Y == 2.
     assert deskew.physical_pixel_sizes.Z == 1.
+
+def test_allow_trailing_slash():
+    with tempfile.TemporaryDirectory() as tmpdir:
+        output = OutputParams(
+            save_dir=f"{tmpdir}/"
+        )
+        assert str(output.save_dir) == tmpdir
+
+def test_infer_czi_pixel_sizes(rbc_tiny: Path):
+    mock = PropertyMock()
+    with patch("aicsimageio.AICSImage.physical_pixel_sizes", new=mock):
+        DeskewParams(input_image=rbc_tiny)
+        # The AICSImage should be queried for the pixel sizes
+        assert mock.called