Adjusting tiffile versioning (#487)

* Adjusting tiffile versioning * Adding pinned version of tifffile for bfio * new tiff.series logic to mmstack in tifffile 2023.3.15 * removing codecov from setup.py * applying reshape for mmstack tiff images * removing dim overwrite from tiff_reader * override mmstack parser with is_mmstack=False in Tifffile * set default parser for tiff_glob_reader to is_mmstack=False * reverting tifffile versioning for bfio * changing range of tifffile version * removing non-bfio readers from bfio reader tests * pillow 9.5.0 breaks tests * comment on mmstack reading * Adjusting tiffile versioning * Adding pinned version of tifffile for bfio * new tiff.series logic to mmstack in tifffile 2023.3.15 * applying reshape for mmstack tiff images * removing dim overwrite from tiff_reader * override mmstack parser with is_mmstack=False in Tifffile * set default parser for tiff_glob_reader to is_mmstack=False * reverting tifffile versioning for bfio * changing range of tifffile version * removing non-bfio readers from bfio reader tests * pillow 9.5.0 breaks tests * comment on mmstack reading * pinning tifffile verison 9.4.0 * unpinning pillow, pinning imageio to 2.27.0
AllenCellModeling · May 1, 2023 · 6d88e4a · 6d88e4a
1 parent d4ae290
commit 6d88e4a
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Showing 5 changed files with 29 additions and 47 deletions.
diff --git a/aicsimageio/readers/ome_tiff_reader.py b/aicsimageio/readers/ome_tiff_reader.py
@@ -38,7 +38,6 @@ class OmeTiffReader(TiffReader):
     """
     Wraps the tifffile and ome-types APIs to provide the same aicsimageio Reader
     API but for volumetric OME-TIFF images.
-
     Parameters
     ----------
     image: types.PathLike
@@ -56,12 +55,10 @@ class OmeTiffReader(TiffReader):
     fs_kwargs: Dict[str, Any]
         Any specific keyword arguments to pass down to the fsspec created filesystem.
         Default: {}
-
     Notes
     -----
     If the OME metadata in your file isn't OME schema compilant or does not validate
     this will fail to read your file and raise an exception.
-
     If the OME metadata in your file doesn't use the latest OME schema (2016-06),
     this reader will make a request to the referenced remote OME schema to validate.
     """
@@ -82,6 +79,8 @@ def _is_supported_image(
             with fs.open(path) as open_resource:
                 with TiffFile(open_resource) as tiff:
                     # Get first page description (aka the description tag in general)
+                    # after Tifffile version 2023.3.15 mmstack images read all scenes
+                    # into tiff.pages[0]
                     xml = tiff.pages[0].description
                     ome = OmeTiffReader._get_ome(xml, clean_metadata)
 
@@ -126,7 +125,6 @@ def _is_supported_image(
     def _guess_ome_dim_order(tiff: TiffFile, ome: OME, scene_index: int) -> List[str]:
         """
         Guess the dimension order based on OME metadata and actual TIFF data.
-
         Parameters
         -------
         tiff: TiffFile
@@ -135,7 +133,6 @@ def _guess_ome_dim_order(tiff: TiffFile, ome: OME, scene_index: int) -> List[str
             A constructed OME object to retrieve data from.
         scene_index: int
             The current operating scene index to pull metadata from.
-
         Returns
         -------
         dims: List[str]
@@ -188,7 +185,7 @@ def __init__(
 
         # Get ome-types object and warn of other behaviors
         with self._fs.open(self._path) as open_resource:
-            with TiffFile(open_resource) as tiff:
+            with TiffFile(open_resource, is_mmstack=False) as tiff:
                 # Get and store OME
                 self._ome = self._get_ome(
                     tiff.pages[0].description, self.clean_metadata
@@ -299,21 +296,19 @@ def _general_data_array_constructor(
     def _read_delayed(self) -> xr.DataArray:
         """
         Construct the delayed xarray DataArray object for the image.
-
         Returns
         -------
         image: xr.DataArray
             The fully constructed and fully delayed image as a DataArray object.
             Metadata is attached in some cases as coords, dims, and attrs contains
             unprocessed tags and processed OME object.
-
         Raises
         ------
         exceptions.UnsupportedFileFormatError
             The file could not be read or is not supported.
         """
         with self._fs.open(self._path) as open_resource:
-            with TiffFile(open_resource) as tiff:
+            with TiffFile(open_resource, is_mmstack=False) as tiff:
                 # Get unprocessed metadata from tags
                 tiff_tags = self._get_tiff_tags(tiff)
 
@@ -346,21 +341,19 @@ def _read_delayed(self) -> xr.DataArray:
     def _read_immediate(self) -> xr.DataArray:
         """
         Construct the in-memory xarray DataArray object for the image.
-
         Returns
         -------
         image: xr.DataArray
             The fully constructed and fully read into memory image as a DataArray
             object. Metadata is attached in some cases as coords, dims, and attrs
             contains unprocessed tags and processed OME object.
-
         Raises
         ------
         exceptions.UnsupportedFileFormatError
             The file could not be read or is not supported.
         """
         with self._fs.open(self._path) as open_resource:
-            with TiffFile(open_resource) as tiff:
+            with TiffFile(open_resource, is_mmstack=False) as tiff:
                 # Get unprocessed metadata from tags
                 tiff_tags = self._get_tiff_tags(tiff)
 
@@ -397,7 +390,6 @@ def physical_pixel_sizes(self) -> PhysicalPixelSizes:
         sizes: PhysicalPixelSizes
             Using available metadata, the floats representing physical pixel sizes for
             dimensions Z, Y, and X.
-
         Notes
         -----
         We currently do not handle unit attachment to these values. Please see the file

diff --git a/aicsimageio/readers/tiff_glob_reader.py b/aicsimageio/readers/tiff_glob_reader.py
@@ -117,7 +117,7 @@ def _is_supported_image(
     ) -> bool:
         try:
             with fs.open(path) as open_resource:
-                with TiffFile(open_resource):
+                with TiffFile(open_resource, is_mmstack=False):
                     return True
 
         except (TiffFileError, TypeError):
@@ -256,7 +256,7 @@ def indexer(x: str) -> pd.Series:
 
         if single_file_shape is None:
             with self._fs.open(self._path) as open_resource:
-                with TiffFile(open_resource) as tiff:
+                with TiffFile(open_resource, is_mmstack=False) as tiff:
                     self._single_file_shape = tiff.series[0].shape
 
         else:
@@ -299,7 +299,9 @@ def _read_delayed(self) -> xr.DataArray:
         scene_files = scene_files.drop(self.scene_glob_character, axis=1)
         scene_nunique = scene_files.nunique()
 
-        tiff_tags = self._get_tiff_tags(TiffFile(scene_files.filename.iloc[0]))
+        tiff_tags = self._get_tiff_tags(
+            TiffFile(scene_files.filename.iloc[0], is_mmstack=False)
+        )
 
         group_dims = [
             x for x in scene_files.columns if x not in ["filename", *self.chunk_dims]
@@ -364,7 +366,9 @@ def _read_delayed(self) -> xr.DataArray:
             dims = list(expanded_blocks_sizes.keys())
 
         else:  # assemble array in a single chunk
-            zarr_im = imread(scene_files.filename.tolist(), aszarr=True, level=0)
+            zarr_im = imread(
+                scene_files.filename.tolist(), aszarr=True, level=0, is_mmstack=False
+            )
             darr = da.from_zarr(zarr_im).rechunk(-1)
             darr = darr.reshape(reshape_sizes)
             darr = darr.transpose(axes_order)
@@ -403,7 +407,9 @@ def _read_immediate(self) -> xr.DataArray:
         scene_files = scene_files.drop(self.scene_glob_character, axis=1)
         scene_nunique = scene_files.nunique()
 
-        tiff_tags = self._get_tiff_tags(TiffFile(scene_files.filename.iloc[0]))
+        tiff_tags = self._get_tiff_tags(
+            TiffFile(scene_files.filename.iloc[0], is_mmstack=False)
+        )
 
         chunk_sizes = self._get_chunk_sizes(scene_nunique)
 

diff --git a/aicsimageio/readers/tiff_reader.py b/aicsimageio/readers/tiff_reader.py
@@ -33,7 +33,6 @@ class TiffReader(Reader):
     """
     Wraps the tifffile API to provide the same aicsimageio Reader API but for
     volumetric Tiff (and other tifffile supported) images.
-
     Parameters
     ----------
     image: types.PathLike
@@ -127,7 +126,7 @@ def __init__(
     def scenes(self) -> Tuple[str, ...]:
         if self._scenes is None:
             with self._fs.open(self._path) as open_resource:
-                with TiffFile(open_resource) as tiff:
+                with TiffFile(open_resource, is_mmstack=False) as tiff:
                     # This is non-metadata tiff, just use available series indices
                     self._scenes = tuple(
                         metadata_utils.generate_ome_image_id(i)
@@ -163,7 +162,6 @@ def _get_image_data(
         """
         Open a file for reading, construct a Zarr store, select data, and compute to
         numpy.
-
         Parameters
         ----------
         fs: AbstractFileSystem
@@ -176,15 +174,19 @@ def _get_image_data(
             The image indices to retrieve.
         transpose_indices: List[int]
             The indices to transpose to prior to requesting data.
-
         Returns
         -------
         chunk: np.ndarray
             The image chunk as a numpy array.
         """
         with fs.open(path) as open_resource:
             with imread(
-                open_resource, aszarr=True, series=scene, level=0, chunkmode="page"
+                open_resource,
+                aszarr=True,
+                series=scene,
+                level=0,
+                chunkmode="page",
+                is_mmstack=False,
             ) as store:
                 arr = da.from_zarr(store)
                 arr = arr.transpose(transpose_indices)
@@ -335,15 +337,13 @@ def _create_dask_array(
     ) -> da.Array:
         """
         Creates a delayed dask array for the file.
-
         Parameters
         ----------
         tiff: TiffFile
             An open TiffFile for processing.
         selected_scene_dims_list: List[str]
             The dimensions to use for constructing the array with.
             Required for managing chunked vs non-chunked dimensions.
-
         Returns
         -------
         image_data: da.Array
@@ -445,20 +445,18 @@ def _create_dask_array(
     def _read_delayed(self) -> xr.DataArray:
         """
         Construct the delayed xarray DataArray object for the image.
-
         Returns
         -------
         image: xr.DataArray
             The fully constructed and fully delayed image as a DataArray object.
             Metadata is attached in some cases as coords, dims, and attrs.
-
         Raises
         ------
         exceptions.UnsupportedFileFormatError
             The file could not be read or is not supported.
         """
         with self._fs.open(self._path) as open_resource:
-            with TiffFile(open_resource) as tiff:
+            with TiffFile(open_resource, is_mmstack=False) as tiff:
                 # Get dims from provided or guess
                 dims = self._get_dims_for_scene(tiff)
 
@@ -500,20 +498,18 @@ def _read_delayed(self) -> xr.DataArray:
     def _read_immediate(self) -> xr.DataArray:
         """
         Construct the in-memory xarray DataArray object for the image.
-
         Returns
         -------
         image: xr.DataArray
             The fully constructed and fully read into memory image as a DataArray
             object. Metadata is attached in some cases as coords, dims, and attrs.
-
         Raises
         ------
         exceptions.UnsupportedFileFormatError
             The file could not be read or is not supported.
         """
         with self._fs.open(self._path) as open_resource:
-            with TiffFile(open_resource) as tiff:
+            with TiffFile(open_resource, is_mmstack=False) as tiff:
                 # Get dims from provided or guess
                 dims = self._get_dims_for_scene(tiff)
 
@@ -581,7 +577,7 @@ def _get_pixel_size(
 ) -> Tuple[Optional[float], Optional[float], Optional[float]]:
     """Return the pixel size in microns (z,y,x) for the given series in a tiff path."""
 
-    with TiffFile(path_or_file) as tiff:
+    with TiffFile(path_or_file, is_mmstack=False) as tiff:
         tags = tiff.series[series_index].pages[0].tags
 
     if tiff.is_imagej:

diff --git a/aicsimageio/tests/readers/extra_readers/test_ome_tiled_tiff_reader.py b/aicsimageio/tests/readers/extra_readers/test_ome_tiled_tiff_reader.py
@@ -214,22 +214,10 @@ def test_ome_tiff_reader_large_files(
 @pytest.mark.parametrize(
     "filename, expected_reader",
     [
-        (
-            "s_1_t_1_c_1_z_1.tiff",
-            readers.TiffReader,
-        ),
-        (
-            "s_1_t_1_c_1_z_1.ome.tiff",
-            readers.OmeTiffReader,
-        ),
         (
             "s_1_t_1_c_1_z_1_ome_tiff_tiles.ome.tif",
             readers.OmeTiledTiffReader,
         ),
-        (  # Multiscene tiff
-            "variable_scene_shape_first_scene_pyramid.ome.tiff",
-            readers.OmeTiffReader,
-        ),
     ],
 )
 def test_selected_tiff_reader(

diff --git a/setup.py b/setup.py
@@ -31,8 +31,8 @@ def run(self):
 # "READER_TO_INSTALL" lookup table from aicsimageio/formats.py.
 format_libs: Dict[str, List[str]] = {
     "base-imageio": [
-        "imageio[ffmpeg]>=2.11.0",
-        "Pillow>=9.3",
+        "imageio[ffmpeg]>=2.11.0,<2.28.0",
+        "Pillow>=9.3.0",
     ],
     "nd2": ["nd2[legacy]>=0.2.0"],
     "dv": ["mrc>=0.2.0"],
@@ -108,7 +108,7 @@ def run(self):
     "ome-zarr>=0.6.1",
     "wrapt>=1.12",
     "resource-backed-dask-array>=0.1.0",
-    "tifffile>=2021.8.30,<2023.3.15",
+    "tifffile>=2021.8.30",
     "xarray>=0.16.1,<2023.02.0",
     "xmlschema",  # no pin because it's pulled in from OME types
     "zarr>=2.6,<3",