- pyproject towards PEP621

- catch errors reading metadata in tifread
- read dimension order from ome

ndbioimage/readers/tifread.py

@@ -6,9 +6,10 @@ from pathlib import Path
 import numpy as np
 import tifffile
 import yaml
-from ome_types import model
+import warnings
+from ome_types import model, from_xml
 
-from .. import AbstractReader
+from .. import AbstractReader, try_default
 
 
 class Reader(AbstractReader, ABC):
@@ -25,61 +26,75 @@ class Reader(AbstractReader, ABC):
 
     @cached_property
     def metadata(self):
-        return {key: yaml.safe_load(value) if isinstance(value, str) else value
+        return {key: try_default(yaml.safe_load, value, value) if isinstance(value, str) else value
                 for key, value in self.reader.imagej_metadata.items()}
 
     def get_ome(self):
-        page = self.reader.pages[0]
+        if self.reader.is_ome:
-        size_y = page.imagelength
+            with warnings.catch_warnings():
-        size_x = page.imagewidth
+                warnings.simplefilter('ignore', category=UserWarning)
-        if self.p_ndim == 3:
+                return from_xml(self.reader.ome_metadata)
-            size_c = page.samplesperpixel
-            size_t = self.metadata.get('frames', 1)  # // C
         else:
-            size_c = self.metadata.get('channels', 1)
+            page = self.reader.pages[0]
-            size_t = self.metadata.get('frames', 1)
+            size_y = page.imagelength
-        size_z = self.metadata.get('slices', 1)
+            size_x = page.imagewidth
-        if 282 in page.tags and 296 in page.tags and page.tags[296].value == 1:
+            if self.p_ndim == 3:
-            f = page.tags[282].value
+                size_c = page.samplesperpixel
-            pxsize = f[1] / f[0]
+                size_t = self.metadata.get('frames', 1)  # // C
-        else:
+            else:
-            pxsize = None
+                size_c = self.metadata.get('channels', 1)
+                size_t = self.metadata.get('frames', 1)
+            size_z = self.metadata.get('slices', 1)
+            if 282 in page.tags and 296 in page.tags and page.tags[296].value == 1:
+                f = page.tags[282].value
+                pxsize = f[1] / f[0]
+            else:
+                pxsize = None
 
-        dtype = page.dtype.name
+            dtype = page.dtype.name
-        if dtype not in ('int8', 'int16', 'int32', 'uint8', 'uint16', 'uint32',
+            if dtype not in ('int8', 'int16', 'int32', 'uint8', 'uint16', 'uint32',
-                         'float', 'double', 'complex', 'double-complex', 'bit'):
+                             'float', 'double', 'complex', 'double-complex', 'bit'):
-            dtype = 'float'
+                dtype = 'float'
 
-        interval_t = self.metadata.get('interval', 0)
+            interval_t = self.metadata.get('interval', 0)
 
-        ome = model.OME()
+            ome = model.OME()
-        ome.instruments.append(model.Instrument(id='Instrument:0'))
+            ome.instruments.append(model.Instrument(id='Instrument:0'))
-        ome.instruments[0].objectives.append(model.Objective(id='Objective:0'))
+            ome.instruments[0].objectives.append(model.Objective(id='Objective:0'))
-        ome.images.append(
+            ome.images.append(
-            model.Image(
+                model.Image(
-                id='Image:0',
+                    id='Image:0',
-                pixels=model.Pixels(
+                    pixels=model.Pixels(
-                    id='Pixels:0',
+                        id='Pixels:0',
-                    size_c=size_c, size_z=size_z, size_t=size_t, size_x=size_x, size_y=size_y,
+                        size_c=size_c, size_z=size_z, size_t=size_t, size_x=size_x, size_y=size_y,
-                    dimension_order='XYCZT', type=dtype,  # type: ignore
+                        dimension_order='XYCZT', type=dtype,  # type: ignore
-                    physical_size_x=pxsize, physical_size_y=pxsize),
+                        physical_size_x=pxsize, physical_size_y=pxsize),
-                objective_settings=model.ObjectiveSettings(id='Objective:0')))
+                    objective_settings=model.ObjectiveSettings(id='Objective:0')))
-        for c, z, t in product(range(size_c), range(size_z), range(size_t)):
+            for c, z, t in product(range(size_c), range(size_z), range(size_t)):
-            ome.images[0].pixels.planes.append(model.Plane(the_c=c, the_z=z, the_t=t, delta_t=interval_t * t))
+                ome.images[0].pixels.planes.append(model.Plane(the_c=c, the_z=z, the_t=t, delta_t=interval_t * t))
-        return ome
+            return ome
 
     def open(self):
         self.reader = tifffile.TiffFile(self.path)
-        page = self.reader.pages[0]
+        page = self.reader.pages.first
         self.p_ndim = page.ndim  # noqa
         if self.p_ndim == 3:
             self.p_transpose = [i for i in [page.axes.find(j) for j in 'SYX'] if i >= 0]  # noqa
+        else:
+            self.p_transpose = [i for i in [page.axes.find(j) for j in 'YX'] if i >= 0]  # noqa
 
     def close(self):
         self.reader.close()
 
-    def __frame__(self, c, z, t):
+    def __frame__(self, c: int, z: int, t: int):
+        dimension_order = self.ome.images[0].pixels.dimension_order.value
         if self.p_ndim == 3:
-            return np.transpose(self.reader.asarray(z + t * self.base_shape['z']), self.p_transpose)[c]
+            axes = ''.join([ax.lower() for ax in dimension_order if ax.lower() in 'zt'])
+            ct = {'z': z, 't': t}
+            n = sum([ct[ax] * np.prod(self.base_shape[axes[:i]]) for i, ax in enumerate(axes)])
+            return np.transpose(self.reader.asarray(int(n)), self.p_transpose)[int(c)]
         else:
-            return self.reader.asarray(c + z * self.base_shape['c'] + t * self.base_shape['c'] * self.base_shape['z'])
+            axes = ''.join([ax.lower() for ax in dimension_order if ax.lower() in 'czt'])
+            czt = {'c': c, 'z': z, 't': t}
+            n = sum([czt[ax] * np.prod(self.base_shape[axes[:i]]) for i, ax in enumerate(axes)])
+        return np.transpose(self.reader.asarray(int(n)), self.p_transpose)

ndbioimage/transform.txt

@@ -1,6 +1,4 @@
 #Insight Transform File V1.0
-#Transform 0
-Transform: CompositeTransform_double_2_2
 #Transform 1
 Transform: AffineTransform_double_2_2
 Parameters: 1 0 0 1 0 0

ndbioimage/transforms.py

@@ -299,7 +299,7 @@ class Transform:
             new.shape = [float(t) for t in transform['Size']]
             new.origin = [(t - 1) / 2 for t in new.shape]
         else:
-            raise NotImplementedError(f'{kind} tranforms not implemented (yet)')
+            raise NotImplementedError(f'{kind} transforms not implemented (yet)')
         new.dparameters = 6 * [np.nan]
         return new
 

pyproject.toml

@@ -1,46 +1,43 @@
-[tool.poetry]
+[project]
 name = "ndbioimage"
-version = "2025.2.1"
+version = "2025.3.0"
 description = "Bio image reading, metadata and some affine registration."
-authors = ["W. Pomp <w.pomp@nki.nl>"]
+authors = [
-license = "GPLv3"
+    { name = "W. Pomp", email = "w.pomp@nki.nl" }
+]
+license = { text = "GPL-3.0-or-later"}
 readme = "README.md"
 keywords = ["bioformats", "imread", "numpy", "metadata"]
 include = ["transform.txt"]
-repository = "https://github.com/wimpomp/ndbioimage"
+requires-python = ">=3.10"
 exclude = ["ndbioimage/jars"]
 
-[tool.poetry.dependencies]
+dependencies = [
-python = "^3.10"
+    "czifile == 2019.7.2",
-numpy = ">=1.20.0"
+    "imagecodecs",
-pandas = "*"
+    "JPype1",
-tifffile = "*"
+    "lxml",
-czifile = "2019.7.2"
+    "numpy >= 1.20",
-tiffwrite = ">=2024.12.1"
+    "ome-types",
-ome-types = ">=0.4.0"
+    "pandas",
-pint = "*"
+    "parfor >= 2025.1.0",
-tqdm = "*"
+    "pint",
-lxml = "*"
+    "pyyaml",
-pyyaml = "*"
+    "SimpleITK-SimpleElastix; sys_platform != 'darwin'",
-parfor = ">=2025.1.0"
+    "scikit-image",
-JPype1 = "*"
+    "tifffile <= 2025.1.10",
-SimpleITK-SimpleElastix = [
+    "tiffwrite >= 2024.12.1",
-    { version = "*", python = "<3.12" },
+    "tqdm",
-    { version = "*", python = ">=3.12", markers = "sys_platform != 'darwin'" },
-    { version = "*", python = ">=3.12", markers = "platform_machine == 'aarch64'" },
 ]
-scikit-image = "*"
-imagecodecs = "*"
-xsdata = "^23"  # until pydantic is up-to-date
-matplotlib = { version = "*", optional = true }
-scikit-video = { version = "*", optional = true }
-pytest = { version = "*", optional = true }
 
-[tool.poetry.extras]
+[project.optional-dependencies]
 test = ["pytest"]
 write = ["matplotlib", "scikit-video"]
 
-[tool.poetry.scripts]
+[project.urls]
+repository = "https://github.com/wimpomp/ndbioimage"
+
+[project.scripts]
 ndbioimage = "ndbioimage:main"
 
 [tool.pytest.ini_options]