- add numpy flags

- all python objects pickleble
- transforms in python submodule
- fix tiffreader pxsize
- expose more of transforms to python
- loading transforms from yaml

Cargo.toml

@@ -19,7 +19,7 @@ name = "ndbioimage"
 crate-type = ["cdylib", "rlib"]
 
 [dependencies]
-bioformats = { version = "0.1", optional = true }
+bioformats = { version = "0.1", optional = true, default-features = false, features = ["zarr", "tissuefaxs"] }
 clap = { version = "4", features = ["derive"] }
 console = { version = "0.16", optional = true }
 downloader = { version = "0.2", optional = true, default-features = false, features = ["rustls-tls"] }
@@ -83,5 +83,8 @@ features = ["bioformats_java", "bioformats_rust", "czi", "movie", "tiffseq", "ti
 [profile.test]
 inherits = "release"
 
+[profile.release]
+debug = true
+
 [profile.dev.package.backtrace]
 opt-level = 3

py/ndbioimage/__init__.py

@@ -13,8 +13,14 @@ from numpy.typing import ArrayLike
 os.environ["RUST_BACKTRACE"] = "full"
 os.environ["COLORBT_SHOW_HIDDEN"] = "1"
 
-from . import ndbioimage_rs as rs
-from .ndbioimage_rs import Imread, Transform, Transforms
+from .ndbioimage_rs import Imread, generate_stub
+
+try:
+    from .ndbioimage_rs import transforms
+
+    sys.modules["ndbioimage.transforms"] = transforms
+except (ImportError, ModuleNotFoundError):
+    pass
 
 try:
     from .ndbioimage_rs import batch_to_tiff
@@ -23,8 +29,12 @@ except ImportError:
 
 try:
     import ome_metadata  # noqa
-except ModuleNotFoundError:
-    sys.modules["ome_metadata"] = rs.ome_metadata  # noqa
+except (ImportError, ModuleNotFoundError):
+    from .ndbioimage_rs import ome_metadata  # noqa
+
+    sys.modules["ome_metadata"] = ome_metadata
+    import ome_metadata  # noqa
+
 
 try:
     __version__ = version(Path(__file__).parent.name)
@@ -58,13 +68,26 @@ def ndbioimage_generate_stub():
         path = Path(sys.argv[1]).resolve()
     else:
         path = Path.cwd().resolve()
-    if (path / "py" / "ndbioimage" / "__init__.py").exists():
-        rs.generate_stub(str(path))  # noqa
+    nd = path / "py" / "ndbioimage"
+    if (nd / "__init__.pyi").exists():
+        (nd / "__init__.pyi").rename(nd / "ndbioimage.pyi")
+    try:
+        if (nd / "__init__.py").exists():
+            generate_stub(str(path))  # noqa
         else:
-        raise ModuleNotFoundError(str(path / "py" / "ndbioimage" / "__init__.py"))
-    (path / "py" / "ndbioimage" / "__init__.pyi").rename(
-        path / "py" / "ndbioimage" / "ndbioimage_rs.pyi"
-    )
+            raise ModuleNotFoundError(str(nd / "__init__.py"))
+        rs = nd / "ndbioimage_rs"
+        rs.mkdir(parents=True, exist_ok=True)
+        (nd / "__init__.pyi").rename(rs / "__init__.pyi")
+        for stub in nd.glob("**/__init__.pyi"):
+            if stub.parent != rs:
+                stub.rename((rs / stub.parent.name).with_suffix(".pyi"))
+                stub.parent.rmdir()
+    except Exception as e:
+        raise e
+    finally:
+        if (nd / "ndbioimage.pyi").exists():
+            (nd / "ndbioimage.pyi").rename(nd / "__init__.pyi")
 
 
 R = TypeVar("R")

py/ndbioimage/__init__.pyi

@@ -0,0 +1,3 @@
+from .ndbioimage_rs import Imread, Shape
+
+__all__ = ["Imread", "Shape"]

py/ndbioimage/ndbioimage_rs/__init__.pyi

@@ -9,15 +9,50 @@ import typing
 import numpy
 import numpy.typing
 
+from . import transforms
+
 __all__ = [
+    "Flags",
     "Imread",
     "Shape",
-    "Transform",
-    "Transforms",
     "batch_to_tiff",
+    "generate_stub",
     "main",
+    "transforms",
 ]
 
+class Flags:
+    r"""
+    https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flags.html
+    """
+    @property
+    def c_contiguous(self) -> builtins.bool: ...
+    @property
+    def f_contiguous(self) -> builtins.bool: ...
+    @property
+    def owndata(self) -> builtins.bool: ...
+    @property
+    def writable(self) -> builtins.bool: ...
+    @property
+    def aligned(self) -> builtins.bool: ...
+    @property
+    def writebackifcopy(self) -> builtins.bool: ...
+    @property
+    def fnc(self) -> builtins.bool: ...
+    @property
+    def forc(self) -> builtins.bool: ...
+    @property
+    def behaved(self) -> builtins.bool: ...
+    @property
+    def carray(self) -> builtins.bool: ...
+    @property
+    def farray(self) -> builtins.bool: ...
+    def __eq__(self, other: builtins.object, /) -> builtins.bool: ...
+    def __hash__(self) -> builtins.int: ...
+    def __new__(cls) -> Flags: ...
+    def __getnewargs__(self) -> None: ...
+    def __getitem__(self, item: builtins.str) -> builtins.bool: ...
+
 class Imread:
     r"""
     class to read image files, while taking good care of important metadata,
@@ -48,16 +83,28 @@ class Imread:
 
             TODO: argmax, argmin, nanmax, nanmin, nanmean, nansum, nanstd, nanvar, std, var
     """
+
+    available_readers: builtins.list[builtins.str]
+    @property
+    def flags(self) -> Flags:
+        r"""
+        https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flags.html
+        """
     @property
     def reader_name(self) -> builtins.str:
         r"""
         the name of the reader used to open the file
         """
     @property
-    def transform(self) -> Transforms:
+    def transforms(self) -> transforms.Transforms:
         r"""
         get the transformation
         """
+    @transforms.setter
+    def transforms(self, value: transforms.Transforms) -> None:
+        r"""
+        set the transformation
+        """
     @property
     def path(self) -> pathlib.Path:
         r"""
@@ -183,6 +230,15 @@ class Imread:
         r"""
         new view on a file at path, open series #, open as dtype: (u)int(8/16/32) or float(32/64)
         """
+    def set_flags(
+        self,
+        write: typing.Optional[builtins.bool] = None,
+        align: typing.Optional[builtins.bool] = None,
+        uic: typing.Optional[builtins.bool] = None,
+    ) -> None:
+        r"""
+        https://numpy.org/doc/stable/reference/generated/numpy.ndarray.setflags.html#numpy.ndarray.setflags
+        """
     @staticmethod
     def get_positions(
         path: str | pathlib.Path | Imread | bytes,
@@ -210,22 +266,31 @@ class Imread:
     ) -> Imread:
         r"""
         return a new view with transformations applied (channel alignment, drift correction)
+        backward compatibility
         """
-    def set_transform(self, transform: Transforms) -> None:
+    def with_transforms(
+        self,
+        channels: builtins.bool = True,
+        drift: builtins.bool = False,
+        file: typing.Optional[typing.Any] = None,
+        bead_files: typing.Optional[typing.Any] = None,
+        main_channel: typing.Optional[builtins.int] = None,
+        default_transform: typing.Optional[typing.Sequence[builtins.float]] = None,
+    ) -> Imread:
         r"""
-        set the transformation
+        return a new view with transformations applied (channel alignment, drift correction)
         """
-    def load_transform_from_yaml(
+    def load_transforms_from_yaml(
         self, path: builtins.str | os.PathLike | pathlib.Path
     ) -> None: ...
     def calculate_channel_transforms_2d(
         self, main_channel: builtins.int
-    ) -> builtins.list[Transform]: ...
+    ) -> builtins.dict[builtins.str, transforms.Transform]: ...
     def calculate_channel_transforms_3d(
         self, main_channel: builtins.int
-    ) -> builtins.list[Transform]: ...
-    def calculate_drift_transform_2d(self) -> builtins.list[Transform]: ...
-    def calculate_drift_transform_3d(self) -> builtins.list[Transform]: ...
+    ) -> builtins.dict[builtins.str, transforms.Transform]: ...
+    def calculate_drift_transforms_2d(self) -> builtins.list[transforms.Transform]: ...
+    def calculate_drift_transforms_3d(self) -> builtins.list[transforms.Transform]: ...
     def squeeze(self) -> numpy.ndarray | int | float: ...
     def close(self) -> None:
         r"""
@@ -678,7 +743,7 @@ class Shape:
         """
     def __getitem__(
         self, idx: str | int | None | Ellipsis | slice | list[int] | tuple[int]
-    ) -> typing.Optional[int | list[int]]:
+    ) -> typing.Optional[int | tuple[int]]:
         r"""
         get dimension size by index or axis name
         """
@@ -691,127 +756,6 @@ class Shape:
         convert shape to a list of dimension sizes in order
         """
 
-class Transform:
-    @property
-    def parameters(self) -> builtins.list[builtins.float]: ...
-    @parameters.setter
-    def parameters(self, value: typing.Sequence[builtins.float]) -> None: ...
-    @property
-    def dparameters(self) -> builtins.list[builtins.float]: ...
-    @dparameters.setter
-    def dparameters(self, value: typing.Sequence[builtins.float]) -> None: ...
-    @property
-    def center(self) -> builtins.list[builtins.float]: ...
-    @center.setter
-    def center(self, value: typing.Sequence[builtins.float]) -> None: ...
-    @property
-    def shape(self) -> builtins.list[builtins.int]: ...
-    @shape.setter
-    def shape(self, value: typing.Sequence[builtins.int]) -> None: ...
-    @property
-    def ndim(self) -> builtins.int: ...
-    @property
-    def matrix(self) -> numpy.typing.NDArray[numpy.float64]: ...
-    @matrix.setter
-    def matrix(self, value: numpy.typing.ArrayLike) -> None: ...
-    @property
-    def dmatrix(self) -> numpy.typing.NDArray[numpy.float64]: ...
-    @dmatrix.setter
-    def dmatrix(self, value: numpy.typing.ArrayLike) -> None: ...
-    @property
-    def inverse(self) -> Transform: ...
-    def __eq__(self, other: builtins.object, /) -> builtins.bool: ...
-    def __new__(
-        cls,
-        parameters: typing.Sequence[builtins.float],
-        shape: typing.Sequence[builtins.int],
-        center: typing.Optional[typing.Sequence[builtins.float]] = None,
-    ) -> Transform: ...
-    def __getnewargs__(
-        self,
-    ) -> tuple[
-        builtins.list[builtins.float],
-        builtins.list[builtins.int],
-        typing.Optional[builtins.list[builtins.float]],
-    ]: ...
-    def __getstate__(self) -> builtins.list[builtins.float]: ...
-    def __setstate__(self, state: typing.Sequence[builtins.float]) -> None: ...
-    def __add__(self, other: Transform) -> Transform: ...
-    def __radd__(self, other: Transform) -> Transform: ...
-    def __sub__(self, other: Transform) -> Transform: ...
-    def __rsub__(self, other: Transform) -> Transform: ...
-    def __mul__(self, other: Transform | float) -> Transform: ...
-    def __rmul__(self, other: Transform | float) -> Transform: ...
-    def __truediv__(self, other: builtins.float) -> Transform: ...
-    def adapt(
-        self,
-        center: typing.Sequence[builtins.float],
-        shape: typing.Sequence[builtins.int],
-    ) -> None: ...
-    @staticmethod
-    def from_scaling(scaling: typing.Sequence[builtins.float]) -> Transform: ...
-    @staticmethod
-    def from_translation(translation: typing.Sequence[builtins.float]) -> Transform: ...
-    @staticmethod
-    def from_rotation(
-        theta: builtins.float, center: typing.Sequence[builtins.float]
-    ) -> Transform: ...
-    def with_scaling(self, scaling: typing.Sequence[builtins.float]) -> Transform: ...
-    def with_translation(
-        self, translation: typing.Sequence[builtins.float]
-    ) -> Transform: ...
-    def with_rotation(
-        self, theta: builtins.float, center: typing.Sequence[builtins.float]
-    ) -> Transform: ...
-    def interpolate(
-        self, order: builtins.int, image: numpy.typing.ArrayLike
-    ) -> numpy.typing.NDArray[numpy.float64]: ...
-    def interpolate_par(
-        self, order: builtins.int, image: numpy.typing.ArrayLike
-    ) -> numpy.typing.NDArray[numpy.float64]: ...
-    def is_unity(self) -> builtins.bool: ...
-    def transform_point(
-        self, point: numpy.typing.ArrayLike
-    ) -> numpy.typing.NDArray[numpy.float64]: ...
-    def transform_points(
-        self, points: numpy.typing.ArrayLike
-    ) -> numpy.typing.NDArray[numpy.float64]: ...
-    @staticmethod
-    def register(
-        fixed: numpy.typing.ArrayLike,
-        moving: numpy.typing.ArrayLike,
-        fixed_mu: typing.Sequence[typing.Optional[builtins.float]],
-        initial_guess: typing.Optional[typing.Sequence[builtins.float]] = None,
-    ) -> Transform: ...
-    @staticmethod
-    def register_affine(
-        fixed: numpy.typing.ArrayLike, moving: numpy.typing.ArrayLike
-    ) -> Transform: ...
-    @staticmethod
-    def register_translation(
-        fixed: numpy.typing.ArrayLike, moving: numpy.typing.ArrayLike
-    ) -> Transform: ...
-
-class Transforms:
-    def __eq__(self, other: builtins.object, /) -> builtins.bool: ...
-    def __getstate__(self) -> builtins.list[builtins.int]: ...
-    def __setstate__(self, state: typing.Sequence[builtins.int]) -> None: ...
-    @staticmethod
-    def load(path: builtins.str | os.PathLike | pathlib.Path) -> Transforms: ...
-    def save(self, path: builtins.str | os.PathLike | pathlib.Path) -> None: ...
-    @staticmethod
-    def calculate_channel_transforms_2d(
-        bead_files: typing.Sequence[builtins.str | os.PathLike | pathlib.Path],
-        main_channel: builtins.int,
-        default_transform: typing.Optional[Transform],
-    ) -> builtins.list[Transform]: ...
-    @staticmethod
-    def calculate_channel_transforms_3d(
-        bead_files: typing.Sequence[builtins.str | os.PathLike | pathlib.Path],
-        main_channel: builtins.int,
-        default_transform: typing.Optional[Transform],
-    ) -> builtins.list[Transform]: ...
-
 def batch_to_tiff(
     files_in: typing.Sequence[builtins.str | os.PathLike | pathlib.Path],
     files_out: typing.Sequence[builtins.str | os.PathLike | pathlib.Path],
@@ -827,6 +771,11 @@ def batch_to_tiff(
     batch convert multiple image files to TIFF format
     """
 
+def generate_stub(dest_path: builtins.str) -> None:
+    r"""
+    generates ndbioimage/__init__.pyi
+    """
+
 def main() -> None:
     r"""
     main entry point for the command-line interface

py/ndbioimage/ndbioimage_rs/transforms.pyi

@@ -0,0 +1,244 @@
+# This file is automatically generated by pyo3_stub_gen
+# ruff: noqa: E501, F401, F403, F405
+
+import builtins
+import os
+import pathlib
+import typing
+
+import numpy
+import numpy.typing
+
+__all__ = [
+    "Optimizer",
+    "RegistrationStep",
+    "SamplingArg",
+    "Sigma",
+    "Transform",
+    "Transforms",
+]
+
+class Optimizer:
+    def __eq__(self, other: builtins.object, /) -> builtins.bool: ...
+    def __new__(cls, optimizer: builtins.str) -> Optimizer: ...
+    def __getnewargs__(self) -> tuple[builtins.str]: ...
+    @staticmethod
+    def lbfgs() -> Optimizer: ...
+    @staticmethod
+    def asgd() -> Optimizer: ...
+
+class RegistrationStep:
+    def __eq__(self, other: builtins.object, /) -> builtins.bool: ...
+    def __new__(
+        cls,
+        sigma: Sigma,
+        sample: SamplingArg,
+        n_bins: builtins.int,
+        tolerance: builtins.float,
+        edge: builtins.float,
+        max_iterations: builtins.int,
+        learning_rate: builtins.float,
+        optimizer: Optimizer,
+    ) -> RegistrationStep: ...
+    def __getnewargs__(
+        self,
+    ) -> tuple[
+        Sigma,
+        SamplingArg,
+        builtins.int,
+        builtins.float,
+        builtins.float,
+        builtins.int,
+        builtins.float,
+        Optimizer,
+    ]: ...
+    @staticmethod
+    def default_steps(
+        ndim: builtins.int, n: builtins.int
+    ) -> builtins.list[RegistrationStep]: ...
+
+class SamplingArg:
+    def __eq__(self, other: builtins.object, /) -> builtins.bool: ...
+    def __new__(
+        cls,
+        fixed: typing.Optional[builtins.int] = None,
+        fixed_at: typing.Optional[
+            typing.Sequence[typing.Sequence[builtins.float]]
+        ] = None,
+        random: typing.Optional[builtins.int] = None,
+    ) -> SamplingArg: ...
+    def __getnewargs__(
+        self,
+    ) -> tuple[
+        typing.Optional[builtins.int],
+        typing.Optional[builtins.list[builtins.list[builtins.float]]],
+        typing.Optional[builtins.int],
+    ]: ...
+    @staticmethod
+    def fixed(size: builtins.int) -> SamplingArg: ...
+    @staticmethod
+    def fixed_at(
+        f: typing.Sequence[typing.Sequence[builtins.float]],
+    ) -> SamplingArg: ...
+    @staticmethod
+    def random(size: builtins.int) -> SamplingArg: ...
+
+class Sigma:
+    def __eq__(self, other: builtins.object, /) -> builtins.bool: ...
+    def __new__(
+        cls,
+        absolute: typing.Optional[typing.Sequence[builtins.float]] = None,
+        relative: typing.Optional[typing.Sequence[builtins.float]] = None,
+    ) -> Sigma: ...
+    def __getnewargs__(
+        self,
+    ) -> tuple[builtins.str, typing.Optional[builtins.list[builtins.float]]]: ...
+    @staticmethod
+    def none() -> Sigma: ...
+    @staticmethod
+    def absolute(sigma: typing.Sequence[builtins.float]) -> Sigma: ...
+    @staticmethod
+    def relative(sigma: typing.Sequence[builtins.float]) -> Sigma: ...
+    def smooth(
+        self, array: numpy.typing.ArrayLike
+    ) -> numpy.typing.NDArray[numpy.float64]: ...
+    def sigma(
+        self, shape: typing.Sequence[builtins.int]
+    ) -> typing.Optional[builtins.list[builtins.float]]: ...
+
+class Transform:
+    @property
+    def parameters(self) -> builtins.list[builtins.float]: ...
+    @parameters.setter
+    def parameters(self, value: typing.Sequence[builtins.float]) -> None: ...
+    @property
+    def dparameters(self) -> builtins.list[builtins.float]: ...
+    @dparameters.setter
+    def dparameters(self, value: typing.Sequence[builtins.float]) -> None: ...
+    @property
+    def center(self) -> builtins.list[builtins.float]: ...
+    @center.setter
+    def center(self, value: typing.Sequence[builtins.float]) -> None: ...
+    @property
+    def shape(self) -> builtins.list[builtins.int]: ...
+    @shape.setter
+    def shape(self, value: typing.Sequence[builtins.int]) -> None: ...
+    @property
+    def ndim(self) -> builtins.int: ...
+    @property
+    def matrix(self) -> numpy.typing.NDArray[numpy.float64]: ...
+    @matrix.setter
+    def matrix(self, value: numpy.typing.ArrayLike) -> None: ...
+    @property
+    def dmatrix(self) -> numpy.typing.NDArray[numpy.float64]: ...
+    @dmatrix.setter
+    def dmatrix(self, value: numpy.typing.ArrayLike) -> None: ...
+    @property
+    def inverse(self) -> Transform: ...
+    def __eq__(self, other: builtins.object, /) -> builtins.bool: ...
+    def __new__(
+        cls,
+        parameters: typing.Optional[typing.Sequence[builtins.float]] = None,
+        shape: typing.Optional[typing.Sequence[builtins.int]] = None,
+        center: typing.Optional[typing.Sequence[builtins.float]] = None,
+    ) -> Transform: ...
+    def __getnewargs__(
+        self,
+    ) -> tuple[
+        builtins.list[builtins.float],
+        builtins.list[builtins.int],
+        typing.Optional[builtins.list[builtins.float]],
+    ]: ...
+    def __getstate__(self) -> builtins.list[builtins.float]: ...
+    def __setstate__(self, state: typing.Sequence[builtins.float]) -> None: ...
+    def __add__(self, other: Transform) -> Transform: ...
+    def __radd__(self, other: Transform) -> Transform: ...
+    def __sub__(self, other: Transform) -> Transform: ...
+    def __rsub__(self, other: Transform) -> Transform: ...
+    def __mul__(self, other: Transform | float) -> Transform: ...
+    def __rmul__(self, other: Transform | float) -> Transform: ...
+    def __truediv__(self, other: builtins.float) -> Transform: ...
+    def adapt(
+        self,
+        center: typing.Sequence[builtins.float],
+        shape: typing.Sequence[builtins.int],
+    ) -> None: ...
+    @staticmethod
+    def from_scaling(scaling: typing.Sequence[builtins.float]) -> Transform: ...
+    @staticmethod
+    def from_translation(translation: typing.Sequence[builtins.float]) -> Transform: ...
+    @staticmethod
+    def from_rotation(
+        theta: builtins.float, center: typing.Sequence[builtins.float]
+    ) -> Transform: ...
+    def with_scaling(self, scaling: typing.Sequence[builtins.float]) -> Transform: ...
+    def with_translation(
+        self, translation: typing.Sequence[builtins.float]
+    ) -> Transform: ...
+    def with_rotation(
+        self, theta: builtins.float, center: typing.Sequence[builtins.float]
+    ) -> Transform: ...
+    def interpolate(
+        self, order: builtins.int, image: numpy.typing.ArrayLike
+    ) -> numpy.typing.NDArray[numpy.float64]: ...
+    def interpolate_par(
+        self, order: builtins.int, image: numpy.typing.ArrayLike
+    ) -> numpy.typing.NDArray[numpy.float64]: ...
+    def is_unity(self) -> builtins.bool: ...
+    def transform_point(
+        self, point: numpy.typing.ArrayLike
+    ) -> numpy.typing.NDArray[numpy.float64]: ...
+    def transform_points(
+        self, points: numpy.typing.ArrayLike
+    ) -> numpy.typing.NDArray[numpy.float64]: ...
+    @staticmethod
+    def register(
+        fixed: numpy.typing.ArrayLike,
+        moving: numpy.typing.ArrayLike,
+        fixed_mu: typing.Sequence[typing.Optional[builtins.float]],
+        initial_guess: typing.Optional[typing.Sequence[builtins.float]] = None,
+    ) -> Transform: ...
+    @staticmethod
+    def register_affine(
+        fixed: numpy.typing.ArrayLike, moving: numpy.typing.ArrayLike
+    ) -> Transform: ...
+    @staticmethod
+    def register_translation(
+        fixed: numpy.typing.ArrayLike, moving: numpy.typing.ArrayLike
+    ) -> Transform: ...
+
+class Transforms:
+    @property
+    def channel_transforms(self) -> builtins.dict[builtins.str, Transform]: ...
+    @channel_transforms.setter
+    def channel_transforms(
+        self, value: typing.Mapping[builtins.str, Transform]
+    ) -> None: ...
+    @property
+    def drift_transforms(self) -> builtins.list[Transform]: ...
+    @drift_transforms.setter
+    def drift_transforms(self, value: typing.Sequence[Transform]) -> None: ...
+    def __eq__(self, other: builtins.object, /) -> builtins.bool: ...
+    def __new__(
+        cls,
+        channel: typing.Mapping[builtins.str, Transform] = {},
+        drift: typing.Sequence[Transform] = [],
+    ) -> Transforms: ...
+    def __getnewargs__(
+        self,
+    ) -> tuple[builtins.dict[builtins.str, Transform], builtins.list[Transform]]: ...
+    @staticmethod
+    def load(path: builtins.str | os.PathLike | pathlib.Path) -> Transforms: ...
+    def save(self, path: builtins.str | os.PathLike | pathlib.Path) -> None: ...
+    @staticmethod
+    def calculate_channel_transforms_2d(
+        bead_files: typing.Sequence[builtins.str | os.PathLike | pathlib.Path],
+        main_channel: builtins.int,
+        default_transform: typing.Optional[Transform],
+    ) -> builtins.dict[builtins.str, Transform]: ...
+    @staticmethod
+    def calculate_channel_transforms_3d(
+        bead_files: typing.Sequence[builtins.str | os.PathLike | pathlib.Path],
+        main_channel: builtins.int,
+        default_transform: typing.Optional[Transform],
+    ) -> builtins.dict[builtins.str, Transform]: ...

py/ndbioimage/transforms.pyi

@@ -0,0 +1,17 @@
+from .ndbioimage_rs.transforms import (
+    Optimizer,
+    RegistrationStep,
+    SamplingArg,
+    Sigma,
+    Transform,
+    Transforms,
+)
+
+__all__ = [
+    "Optimizer",
+    "RegistrationStep",
+    "SamplingArg",
+    "Sigma",
+    "Transform",
+    "Transforms",
+]

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "maturin"
 
 [project]
 name = "ndbioimage"
-version = "2027.0.4"
+version = "2027.0.5"
 requires-python = ">=3.10"
 classifiers = [
     "License :: OSI Approved :: MIT License",

src/py.rs

@@ -41,6 +41,7 @@ pub(crate) fn ndbioimage_file() -> PathBuf {
 }
 
 /// generates ndbioimage/__init__.pyi
+#[gen_stub_pyfunction]
 #[pyfunction]
 pub fn generate_stub(dest_path: String) -> PyResult<()> {
     Ok(StubInfo::from_project_root(
@@ -84,14 +85,31 @@ mod ndbioimage_rs {
     #[pymodule_export]
     use super::imread::PyShape;
 
+    #[pymodule_export]
+    use super::imread::PyFlags;
+
     #[pymodule_export]
     use ome_metadata::py::ome_metadata;
 
     #[cfg(feature = "transforms")]
+    #[pymodule]
+    mod transforms {
         #[pymodule_export]
-    use super::transforms::PyTransform;
+        use super::super::transforms::PyTransform;
 
-    #[cfg(feature = "transforms")]
         #[pymodule_export]
-    use super::transforms::PyTransforms;
+        use super::super::transforms::PyTransforms;
+
+        #[pymodule_export]
+        use super::super::transforms::PyRegistrationStep;
+
+        #[pymodule_export]
+        use super::super::transforms::PySigma;
+
+        #[pymodule_export]
+        use super::super::transforms::PySamplingArg;
+
+        #[pymodule_export]
+        use super::super::transforms::PyOptimizer;
+    }
 }

src/py/imread.rs

@@ -15,7 +15,9 @@ use numpy::{
 };
 use ome_metadata::Ome;
 use postcard::{from_bytes, to_stdvec};
-use pyo3::exceptions::{PyIndexError, PyNotImplementedError, PyTypeError, PyValueError};
+use pyo3::exceptions::{
+    PyIndexError, PyKeyError, PyNotImplementedError, PyTypeError, PyValueError,
+};
 use pyo3::prelude::*;
 use pyo3::types::{PyBytes, PyEllipsis, PyInt, PyList, PyNone, PySlice, PyString, PyTuple};
 pub(crate) use pyo3::{
@@ -25,7 +27,7 @@ pub(crate) use pyo3::{
 use pyo3_stub_gen::derive::*;
 use pyo3_stub_gen::inventory::submit;
 use serde::{Deserialize, Serialize};
-use std::collections::HashSet;
+use std::collections::{HashMap, HashSet};
 use std::path::PathBuf;
 
 /// class to read image files, while taking good care of important metadata,
@@ -204,6 +206,42 @@ impl PyView {
         }
     }
 
+    /// https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flags.html
+    #[getter]
+    fn flags(&self) -> PyFlags {
+        PyFlags::new()
+    }
+
+    /// https://numpy.org/doc/stable/reference/generated/numpy.ndarray.setflags.html#numpy.ndarray.setflags
+    #[pyo3(signature = (write = None, align = None, uic = None))]
+    fn set_flags(
+        &self,
+        write: Option<bool>,
+        align: Option<bool>,
+        uic: Option<bool>,
+    ) -> PyResult<()> {
+        if let Some(write) = write
+            && write
+        {
+            Err(PyValueError::new_err("write cannot be set True"))
+        } else if let Some(align) = align
+            && align
+        {
+            Err(PyValueError::new_err("align cannot be set True"))
+        } else if let Some(uic) = uic
+            && uic
+        {
+            Err(PyValueError::new_err("uic cannot be set True"))
+        } else {
+            Ok(())
+        }
+    }
+
+    #[classattr]
+    fn available_readers() -> Vec<String> {
+        DynReader::available_readers()
+    }
+
     /// get all available positions (series) in the file
     #[staticmethod]
     fn get_positions<'py>(
@@ -232,11 +270,34 @@ impl PyView {
         todo!()
     }
 
+    /// return a new view with transformations applied (channel alignment, drift correction)
+    /// backward compatibility
+    #[cfg(feature = "transforms")]
+    #[pyo3(signature = (channels = true, drift = false, file = None, bead_files = None, main_channel = None, default_transform = None))]
+    fn with_transform<'py>(
+        &self,
+        channels: bool,
+        drift: bool,
+        file: Option<Bound<'py, PyAny>>,
+        bead_files: Option<Bound<'py, PyAny>>,
+        main_channel: Option<usize>,
+        default_transform: Option<Vec<f64>>,
+    ) -> PyResult<PyView> {
+        self.with_transforms(
+            channels,
+            drift,
+            file,
+            bead_files,
+            main_channel,
+            default_transform,
+        )
+    }
+
     /// return a new view with transformations applied (channel alignment, drift correction)
     #[cfg(feature = "transforms")]
     #[expect(unused_variables)]
     #[pyo3(signature = (channels = true, drift = false, file = None, bead_files = None, main_channel = None, default_transform = None))]
-    fn with_transform<'py>(
+    fn with_transforms<'py>(
         &self,
         channels: bool,
         drift: bool,
@@ -251,21 +312,22 @@ impl PyView {
     /// get the transformation
     #[cfg(feature = "transforms")]
     #[getter]
-    fn get_transform(&self) -> PyResult<PyTransforms> {
+    fn get_transforms(&self) -> PyResult<PyTransforms> {
         Ok(PyTransforms {
-            inner: self.view.transforms.clone(),
+            inner: self.view.get_transforms().clone(),
         })
     }
 
     /// set the transformation
     #[cfg(feature = "transforms")]
-    fn set_transform(&mut self, transform: PyTransforms) {
-        self.view.transforms = transform.inner;
+    #[setter]
+    fn set_transforms(&mut self, transform: PyTransforms) {
+        self.view.set_transforms(transform.inner);
     }
 
     #[cfg(feature = "transforms")]
-    fn load_transform_from_yaml(&mut self, path: PathBuf) -> PyResult<()> {
-        self.view.load_transform_from_yaml(path.as_path())?;
+    fn load_transforms_from_yaml(&mut self, path: PathBuf) -> PyResult<()> {
+        self.view.load_transforms_from_yaml(path.as_path())?;
         Ok(())
     }
 
@@ -274,14 +336,19 @@ impl PyView {
         &self,
         py: Python,
         main_channel: usize,
-    ) -> PyResult<Vec<PyTransform>> {
+    ) -> PyResult<HashMap<String, PyTransform>> {
         py.detach(|| {
             Ok(self
                 .view
                 .calculate_channel_transforms_2d(main_channel)?
                 .into_iter()
-                .map(|t| PyTransform {
+                .map(|(n, t)| {
+                    (
+                        n,
+                        PyTransform {
                             inner: t.into_dyn(),
+                        },
+                    )
                 })
                 .collect())
         })
@@ -292,25 +359,30 @@ impl PyView {
         &self,
         py: Python,
         main_channel: usize,
-    ) -> PyResult<Vec<PyTransform>> {
+    ) -> PyResult<HashMap<String, PyTransform>> {
         py.detach(|| {
             Ok(self
                 .view
                 .calculate_channel_transforms_3d(main_channel)?
                 .into_iter()
-                .map(|t| PyTransform {
+                .map(|(n, t)| {
+                    (
+                        n,
+                        PyTransform {
                             inner: t.into_dyn(),
+                        },
+                    )
                 })
                 .collect())
         })
     }
 
     #[cfg(feature = "transforms")]
-    fn calculate_drift_transform_2d(&self, py: Python) -> PyResult<Vec<PyTransform>> {
+    fn calculate_drift_transforms_2d(&self, py: Python) -> PyResult<Vec<PyTransform>> {
         py.detach(|| {
             Ok(self
                 .view
-                .calculate_drift_transform_2d()?
+                .calculate_drift_transforms_2d()?
                 .into_iter()
                 .map(|t| PyTransform {
                     inner: t.into_dyn(),
@@ -320,11 +392,11 @@ impl PyView {
     }
 
     #[cfg(feature = "transforms")]
-    fn calculate_drift_transform_3d(&self, py: Python) -> PyResult<Vec<PyTransform>> {
+    fn calculate_drift_transforms_3d(&self, py: Python) -> PyResult<Vec<PyTransform>> {
         py.detach(|| {
             Ok(self
                 .view
-                .calculate_drift_transform_3d()?
+                .calculate_drift_transforms_3d()?
                 .into_iter()
                 .map(|t| PyTransform {
                     inner: t.into_dyn(),
@@ -2094,7 +2166,7 @@ impl PyShape {
     }
 
     /// get dimension size by index or axis name
-    #[gen_stub(override_return_type(type_repr="typing.Optional[int | list[int]]", imports=("typing")
+    #[gen_stub(override_return_type(type_repr="typing.Optional[int | tuple[int]]", imports=("typing")
     ))]
     fn __getitem__<'py>(
         &self,
@@ -2185,7 +2257,7 @@ impl PyShape {
         } else if shape.len() == 1 {
             Ok(shape[0].into_bound_py_any(py)?)
         } else {
-            Ok(shape.into_bound_py_any(py)?)
+            Ok(PyTuple::new(py, shape)?.into_bound_py_any(py)?)
         }
     }
 
@@ -2215,3 +2287,90 @@ impl PyShape {
             .collect::<String>()
     }
 }
+
+/// https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flags.html
+#[gen_stub_pyclass]
+#[pyclass(
+    subclass,
+    from_py_object,
+    frozen,
+    eq,
+    hash,
+    name = "Flags",
+    module = "ndbioimage"
+)]
+#[derive(Clone, Debug, Serialize, Deserialize, Hash, PartialEq, Eq)]
+pub(crate) struct PyFlags {
+    #[pyo3(get)]
+    c_contiguous: bool,
+    #[pyo3(get)]
+    f_contiguous: bool,
+    #[pyo3(get)]
+    owndata: bool,
+    #[pyo3(get)]
+    writable: bool,
+    #[pyo3(get)]
+    aligned: bool,
+    #[pyo3(get)]
+    writebackifcopy: bool,
+}
+
+#[gen_stub_pymethods]
+#[pymethods]
+impl PyFlags {
+    #[new]
+    fn new() -> Self {
+        Self {
+            c_contiguous: false,
+            f_contiguous: false,
+            owndata: false,
+            writable: false,
+            aligned: false,
+            writebackifcopy: false,
+        }
+    }
+
+    fn __getnewargs__(&self) {}
+
+    fn __getitem__(&self, item: String) -> PyResult<bool> {
+        match item.to_lowercase().as_str() {
+            "c_contiguous" | "c" => Ok(self.c_contiguous),
+            "f_contiguous" | "f" => Ok(self.f_contiguous),
+            "owndata" | "o" => Ok(self.owndata),
+            "writable" | "w" => Ok(self.writable),
+            "aligned" | "a" => Ok(self.aligned),
+            "writebackifcopy" | "x" => Ok(self.writebackifcopy),
+            "fnc" => Ok(self.fnc()),
+            "forc" => Ok(self.forc()),
+            "behaved" | "b" => Ok(self.behaved()),
+            "carray" | "ca" => Ok(self.carray()),
+            "farray" | "fa" => Ok(self.farray()),
+            _ => Err(PyKeyError::new_err(format!("no such key: {}", item))),
+        }
+    }
+
+    #[getter]
+    fn fnc(&self) -> bool {
+        self.c_contiguous && !self.f_contiguous
+    }
+
+    #[getter]
+    fn forc(&self) -> bool {
+        self.c_contiguous || self.f_contiguous
+    }
+
+    #[getter]
+    fn behaved(&self) -> bool {
+        self.aligned && self.writable
+    }
+
+    #[getter]
+    fn carray(&self) -> bool {
+        self.behaved() && self.c_contiguous
+    }
+
+    #[getter]
+    fn farray(&self) -> bool {
+        self.behaved() && self.f_contiguous && !self.c_contiguous
+    }
+}

src/py/transforms.rs

@@ -1,16 +1,18 @@
 use crate::error::Error;
 use crate::transforms::Transforms;
+use image_registration::metric::{SamplingArg, Sigma};
+use image_registration::register::{Optimizer, RegistrationStep};
 use image_registration::transform::Transform;
 use ndarray::{Ix0, Ix1, Ix2, Ix3, Ix4, Ix5, IxDyn};
 use numpy::{
     AllowTypeChange, IntoPyArray, PyArray, PyArray1, PyArray2, PyArrayDyn, PyArrayLike1,
     PyArrayLike2, PyArrayLikeDyn,
 };
-use postcard::{from_bytes, to_stdvec};
 use pyo3::exceptions::{PyNotImplementedError, PyValueError};
 use pyo3::prelude::*;
 use pyo3_stub_gen::derive::*;
 use serde::{Deserialize, Serialize};
+use std::collections::HashMap;
 use std::path::PathBuf;
 
 #[gen_stub_pyclass]
@@ -19,7 +21,7 @@ use std::path::PathBuf;
     from_py_object,
     eq,
     name = "Transform",
-    module = "ndbioimage"
+    module = "ndbioimage.transforms"
 )]
 #[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
 pub(crate) struct PyTransform {
@@ -30,8 +32,14 @@ pub(crate) struct PyTransform {
 #[pymethods]
 impl PyTransform {
     #[new]
-    #[pyo3(signature = (parameters, shape, center = None))]
-    fn new(parameters: Vec<f64>, shape: Vec<usize>, center: Option<Vec<f64>>) -> Self {
+    #[pyo3(signature = (parameters = None, shape = None, center = None))]
+    fn new(
+        parameters: Option<Vec<f64>>,
+        shape: Option<Vec<usize>>,
+        center: Option<Vec<f64>>,
+    ) -> Self {
+        let parameters = parameters.unwrap_or_else(|| vec![1.0, 0.0, 0.0, 1.0, 0.0, 0.0]);
+        let shape = shape.unwrap_or_else(|| vec![512, 512]);
         if let Some(center) = center {
             Self {
                 inner: Transform::new_with_center(parameters, center, shape),
@@ -598,7 +606,7 @@ impl PyTransform {
     from_py_object,
     eq,
     name = "Transforms",
-    module = "ndbioimage"
+    module = "ndbioimage.transforms"
 )]
 #[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
 pub(crate) struct PyTransforms {
@@ -608,12 +616,51 @@ pub(crate) struct PyTransforms {
 #[gen_stub_pymethods]
 #[pymethods]
 impl PyTransforms {
-    pub(crate) fn __getstate__(&self) -> PyResult<Vec<u8>> {
-        Ok(to_stdvec(self).map_err(Error::from)?)
+    #[new]
+    #[pyo3(signature = (channel = HashMap::new(), drift = Vec::new()))]
+    fn new(
+        channel: HashMap<String, PyTransform>,
+        drift: Vec<PyTransform>,
+    ) -> PyResult<PyTransforms> {
+        let channel = channel.into_iter().map(|(n, t)| (n, t.inner)).collect();
+        let drift = drift.into_iter().map(|t| t.inner).collect();
+        Ok(PyTransforms {
+            inner: Transforms { channel, drift },
+        })
     }
 
-    pub(crate) fn __setstate__(&mut self, state: Vec<u8>) -> PyResult<()> {
-        Ok(from_bytes(&state).map_err(Error::from)?)
+    #[getter]
+    fn get_channel_transforms(&self) -> HashMap<String, PyTransform> {
+        self.inner
+            .channel
+            .iter()
+            .map(|(n, t)| (n.clone(), PyTransform { inner: t.clone() }))
+            .collect()
+    }
+
+    #[setter]
+    fn set_channel_transforms(&mut self, transforms: HashMap<String, PyTransform>) -> PyResult<()> {
+        self.inner.channel = transforms.into_iter().map(|(n, t)| (n, t.inner)).collect();
+        Ok(())
+    }
+
+    #[getter]
+    fn get_drift_transforms(&self) -> Vec<PyTransform> {
+        self.inner
+            .drift
+            .iter()
+            .map(|t| PyTransform { inner: t.clone() })
+            .collect()
+    }
+
+    #[setter]
+    fn set_drift_transforms(&mut self, transforms: Vec<PyTransform>) -> PyResult<()> {
+        self.inner.drift = transforms.into_iter().map(|t| t.inner).collect();
+        Ok(())
+    }
+
+    fn __getnewargs__(&self) -> (HashMap<String, PyTransform>, Vec<PyTransform>) {
+        (self.get_channel_transforms(), self.get_drift_transforms())
     }
 
     #[staticmethod]
@@ -632,7 +679,7 @@ impl PyTransforms {
         bead_files: Vec<PathBuf>,
         main_channel: usize,
         default_transform: Option<PyTransform>,
-    ) -> PyResult<Vec<PyTransform>> {
+    ) -> PyResult<HashMap<String, PyTransform>> {
         Ok(Transforms::calculate_channel_transforms_2d(
             &bead_files
                 .iter()
@@ -644,8 +691,13 @@ impl PyTransforms {
                 .transpose()?,
         )?
         .into_iter()
-        .map(|t| PyTransform {
+        .map(|(n, t)| {
+            (
+                n,
+                PyTransform {
                     inner: t.into_dyn(),
+                },
+            )
         })
         .collect())
     }
@@ -655,7 +707,7 @@ impl PyTransforms {
         bead_files: Vec<PathBuf>,
         main_channel: usize,
         default_transform: Option<PyTransform>,
-    ) -> PyResult<Vec<PyTransform>> {
+    ) -> PyResult<HashMap<String, PyTransform>> {
         Ok(Transforms::calculate_channel_transforms_3d(
             &bead_files
                 .iter()
@@ -667,9 +719,298 @@ impl PyTransforms {
                 .transpose()?,
         )?
         .into_iter()
-        .map(|t| PyTransform {
+        .map(|(n, t)| {
+            (
+                n,
+                PyTransform {
                     inner: t.into_dyn(),
+                },
+            )
         })
         .collect())
     }
 }
+
+#[gen_stub_pyclass]
+#[pyclass(
+    subclass,
+    from_py_object,
+    eq,
+    name = "RegistrationStep",
+    module = "ndbioimage.transforms"
+)]
+#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
+pub(crate) struct PyRegistrationStep {
+    pub(crate) inner: RegistrationStep,
+}
+
+#[gen_stub_pymethods]
+#[pymethods]
+impl PyRegistrationStep {
+    #[new]
+    #[expect(clippy::too_many_arguments)]
+    fn new(
+        sigma: PySigma,
+        sample: PySamplingArg,
+        n_bins: usize,
+        tolerance: f64,
+        edge: f64,
+        max_iterations: usize,
+        learning_rate: f64,
+        optimizer: PyOptimizer,
+    ) -> PyResult<PyRegistrationStep> {
+        Ok(PyRegistrationStep {
+            inner: RegistrationStep::new(
+                sigma.inner,
+                sample.inner,
+                n_bins,
+                tolerance,
+                edge,
+                max_iterations,
+                learning_rate,
+                optimizer.inner,
+            ),
+        })
+    }
+
+    fn __getnewargs__(
+        &self,
+    ) -> (
+        PySigma,
+        PySamplingArg,
+        usize,
+        f64,
+        f64,
+        usize,
+        f64,
+        PyOptimizer,
+    ) {
+        (
+            PySigma {
+                inner: self.inner.sigma.clone(),
+            },
+            PySamplingArg {
+                inner: self.inner.samples.clone(),
+            },
+            self.inner.n_bins,
+            self.inner.tolerance,
+            self.inner.edge,
+            self.inner.max_iterations,
+            self.inner.learning_rate,
+            PyOptimizer {
+                inner: self.inner.optimizer.clone(),
+            },
+        )
+    }
+
+    #[staticmethod]
+    fn default_steps(ndim: usize, n: usize) -> Vec<PyRegistrationStep> {
+        RegistrationStep::default_steps(ndim, n)
+            .into_iter()
+            .map(|s| PyRegistrationStep { inner: s })
+            .collect()
+    }
+}
+
+#[gen_stub_pyclass]
+#[pyclass(
+    subclass,
+    from_py_object,
+    eq,
+    name = "Sigma",
+    module = "ndbioimage.transforms"
+)]
+#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
+pub(crate) struct PySigma {
+    pub(crate) inner: Sigma,
+}
+
+#[gen_stub_pymethods]
+#[pymethods]
+impl PySigma {
+    #[new]
+    #[pyo3(signature = (absolute = None, relative = None))]
+    fn new(absolute: Option<Vec<f64>>, relative: Option<Vec<f64>>) -> Self {
+        if let Some(absolute) = absolute {
+            Self {
+                inner: Sigma::Absolute(absolute),
+            }
+        } else if let Some(relative) = relative {
+            Self {
+                inner: Sigma::Relative(relative),
+            }
+        } else {
+            Self { inner: Sigma::None }
+        }
+    }
+
+    fn __getnewargs__(&self) -> (String, Option<Vec<f64>>) {
+        match &self.inner {
+            Sigma::None => ("none".to_string(), None),
+            Sigma::Absolute(sigma) => ("absolute".to_string(), Some(sigma.clone())),
+            Sigma::Relative(sigma) => ("relative".to_string(), Some(sigma.clone())),
+        }
+    }
+
+    #[staticmethod]
+    fn none() -> PySigma {
+        PySigma { inner: Sigma::None }
+    }
+
+    #[staticmethod]
+    fn absolute(sigma: Vec<f64>) -> PySigma {
+        PySigma {
+            inner: Sigma::Absolute(sigma),
+        }
+    }
+
+    #[staticmethod]
+    fn relative(sigma: Vec<f64>) -> PySigma {
+        PySigma {
+            inner: Sigma::Relative(sigma),
+        }
+    }
+
+    fn smooth<'py>(
+        &self,
+        py: Python<'py>,
+        #[gen_stub(override_type(type_repr="numpy.typing.ArrayLike", imports=("numpy.typing")))]
+        array: PyArrayLikeDyn<f64, AllowTypeChange>,
+    ) -> PyResult<Bound<'py, PyArrayDyn<f64>>> {
+        let array = array.as_array();
+        Ok(py
+            .detach(|| self.inner.smooth(array))
+            .map_err(Error::from)?
+            .into_pyarray(py))
+    }
+
+    fn sigma(&self, shape: Vec<usize>) -> Option<Vec<f64>> {
+        self.inner.sigma(shape.as_slice())
+    }
+}
+
+#[gen_stub_pyclass]
+#[pyclass(
+    subclass,
+    from_py_object,
+    eq,
+    name = "SamplingArg",
+    module = "ndbioimage.transforms"
+)]
+#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
+pub(crate) struct PySamplingArg {
+    pub(crate) inner: SamplingArg,
+}
+
+#[gen_stub_pymethods]
+#[pymethods]
+impl PySamplingArg {
+    #[new]
+    #[pyo3(signature = (fixed = None, fixed_at = None, random = None))]
+    fn new(
+        fixed: Option<usize>,
+        fixed_at: Option<Vec<Vec<f64>>>,
+        random: Option<usize>,
+    ) -> PyResult<Self> {
+        if let Some(fixed) = fixed {
+            Ok(Self {
+                inner: SamplingArg::Fixed(fixed),
+            })
+        } else if let Some(fixed_at) = fixed_at {
+            Ok(Self {
+                inner: SamplingArg::FixedAt(fixed_at),
+            })
+        } else if let Some(random) = random {
+            Ok(Self {
+                inner: SamplingArg::Random(random),
+            })
+        } else {
+            Err(PyValueError::new_err(
+                "missing argument 'fixed', 'fixed_at' or 'random'",
+            ))
+        }
+    }
+
+    fn __getnewargs__(&self) -> (Option<usize>, Option<Vec<Vec<f64>>>, Option<usize>) {
+        match &self.inner {
+            SamplingArg::Fixed(fixed) => (Some(*fixed), None, None),
+            SamplingArg::FixedAt(fixed_at) => (None, Some(fixed_at.clone()), None),
+            SamplingArg::Random(usize) => (None, None, Some(*usize)),
+        }
+    }
+
+    #[staticmethod]
+    fn fixed(size: usize) -> PySamplingArg {
+        PySamplingArg {
+            inner: SamplingArg::Fixed(size),
+        }
+    }
+
+    #[staticmethod]
+    fn fixed_at(f: Vec<Vec<f64>>) -> PySamplingArg {
+        PySamplingArg {
+            inner: SamplingArg::FixedAt(f),
+        }
+    }
+
+    #[staticmethod]
+    fn random(size: usize) -> PySamplingArg {
+        PySamplingArg {
+            inner: SamplingArg::Random(size),
+        }
+    }
+}
+
+#[gen_stub_pyclass]
+#[pyclass(
+    subclass,
+    from_py_object,
+    eq,
+    name = "Optimizer",
+    module = "ndbioimage.transforms"
+)]
+#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
+pub(crate) struct PyOptimizer {
+    pub(crate) inner: Optimizer,
+}
+
+#[gen_stub_pymethods]
+#[pymethods]
+impl PyOptimizer {
+    #[new]
+    fn new(optimizer: String) -> PyResult<Self> {
+        match optimizer.to_lowercase().as_str() {
+            "lbfgs" => Ok(Self {
+                inner: Optimizer::LBFGS,
+            }),
+            "asgd" => Ok(Self {
+                inner: Optimizer::ASGD,
+            }),
+            _ => Err(PyValueError::new_err(format!(
+                "invalid optimizer: {}",
+                optimizer
+            ))),
+        }
+    }
+
+    fn __getnewargs__(&self) -> (String,) {
+        (match &self.inner {
+            Optimizer::LBFGS => "lbfgs".to_string(),
+            Optimizer::ASGD => "asgd".to_string(),
+        },)
+    }
+
+    #[staticmethod]
+    fn lbfgs() -> PyOptimizer {
+        PyOptimizer {
+            inner: Optimizer::LBFGS,
+        }
+    }
+
+    #[staticmethod]
+    fn asgd() -> PyOptimizer {
+        PyOptimizer {
+            inner: Optimizer::ASGD,
+        }
+    }
+}

src/readers.rs

@@ -229,6 +229,7 @@ pub trait Reader: Clone + Sized + Debug + Send + Hash + Into<DynReader> {
         P: AsRef<Path>;
 }
 
+/// Bioformats numbering
 impl TryFrom<i32> for PixelType {
     type Error = Error;
 
@@ -257,6 +258,7 @@ impl FromStr for PixelType {
 
     fn from_str(s: &str) -> Result<Self, Self::Err> {
         match s.to_lowercase().as_str() {
+            "bool" | "bit" => Ok(PixelType::Bool),
             "int8" | "i8" => Ok(PixelType::I8),
             "uint8" | "u8" => Ok(PixelType::U8),
             "int16" | "i16" => Ok(PixelType::I16),
@@ -683,6 +685,22 @@ impl Reader for DynReader {
 }
 
 impl DynReader {
+    /// list of enabled readers
+    pub fn available_readers() -> Vec<String> {
+        vec![
+            #[cfg(feature = "tiff")]
+            "tiff".to_string(),
+            #[cfg(feature = "tiffseq")]
+            "tiffseq".to_string(),
+            #[cfg(feature = "czi")]
+            "czi".to_string(),
+            #[cfg(feature = "bioformats_rust")]
+            "bioformats_rust".to_string(),
+            #[cfg(feature = "bioformats_java")]
+            "bioformats_java".to_string(),
+        ]
+    }
+
     /// create a dynreader by selecting the reader type explicitly
     pub fn from_path_select_reader<P, R>(path: P, reader: R) -> Result<DynReader, Error>
     where
@@ -694,7 +712,7 @@ impl DynReader {
         let reader = reader.as_ref();
         let reader = match reader.to_lowercase().as_str() {
             #[cfg(feature = "tiff")]
-            "tif" => Ok(DynReader::Tiff(tiff::TiffReader::new(
+            "tiff" => Ok(DynReader::Tiff(tiff::TiffReader::new(
                 path,
                 dimensions.s.unwrap_or(0),
                 dimensions.p.unwrap_or(0),
@@ -746,7 +764,7 @@ impl DynReader {
             let reader = reader.as_ref();
             match reader.to_lowercase().as_str() {
                 #[cfg(feature = "tiff")]
-                "tif" => Ok(tiff::TiffReader::get_available_positions(path, series)?),
+                "tiff" => Ok(tiff::TiffReader::get_available_positions(path, series)?),
                 #[cfg(feature = "tiffseq")]
                 "tiffseq" => Ok(tiffseq::TiffSeqReader::get_available_positions(
                     path, series,
@@ -781,7 +799,7 @@ impl DynReader {
             let reader = reader.as_ref();
             match reader.to_lowercase().as_str() {
                 #[cfg(feature = "tiff")]
-                "tif" => Ok(tiff::TiffReader::get_available_series(path)?),
+                "tiff" => Ok(tiff::TiffReader::get_available_series(path)?),
                 #[cfg(feature = "tiffseq")]
                 "tiffseq" => Ok(tiffseq::TiffSeqReader::get_available_series(path)?),
                 #[cfg(feature = "czi")]

src/readers/tiff.rs

@@ -9,6 +9,7 @@ use std::fs::File;
 use std::hash::{Hash, Hasher};
 use std::path::{Path, PathBuf};
 use thread_local::ThreadLocal;
+use tiff::decoder::ifd::Value;
 use tiff::decoder::{Decoder, DecodingResult};
 use tiff::tags::Tag;
 
@@ -25,8 +26,6 @@ pub struct TiffReader {
     n_samples: usize,
     p_ndim: u8,
     planar: bool,
-    interval_t: f64,
-    pixel_size: Option<f64>,
 }
 
 impl From<TiffReader> for DynReader {
@@ -55,8 +54,6 @@ impl Clone for TiffReader {
             n_samples: self.n_samples,
             p_ndim: self.p_ndim,
             planar: self.planar,
-            interval_t: self.interval_t,
-            pixel_size: self.pixel_size,
         }
     }
 }
@@ -128,8 +125,6 @@ impl Reader for TiffReader {
             n_samples: 0,
             p_ndim: 0,
             planar: true,
-            interval_t: 0.0,
-            pixel_size: None,
         };
 
         let mut reader = new.get_reader()?;
@@ -157,7 +152,7 @@ impl Reader for TiffReader {
             .get_tag(Tag::Unknown(50839))
             .or_else(|_| reader.get_tag(Tag::ImageDescription))?;
         let imagej_bytes = match imagej_bytes {
-            tiff::decoder::ifd::Value::Ascii(s) => s.into_bytes(),
+            Value::Ascii(s) => s.into_bytes(),
             other => other.into_u8_vec()?,
         };
         let metadata_str = String::from_utf8_lossy(&imagej_bytes);
@@ -179,30 +174,6 @@ impl Reader for TiffReader {
             .get("frames")
             .and_then(|v| v.parse::<usize>().ok())
             .unwrap_or(1);
-        let interval_t = metadata_map
-            .get("interval")
-            .and_then(|v| v.parse::<f64>().ok())
-            .unwrap_or(0.0);
-        let ru = reader
-            .get_tag(Tag::ResolutionUnit)
-            .ok()
-            .and_then(|i| i.into_u16().ok())
-            .unwrap_or(2);
-        let pixel_size = reader
-            .get_tag(Tag::XResolution)
-            .ok()
-            .and_then(|i| i.into_f64().ok())
-            .and_then(|i| {
-                if i <= 0.0 {
-                    None
-                } else if ru == 3 {
-                    Some(1e4 / i)
-                } else if ru == 2 {
-                    Some(25400.0 / i)
-                } else {
-                    Some(1.0 / i)
-                }
-            });
 
         let mult = if p_ndim == 3 { n_samples } else { 1 };
         let expected = size_c * size_z * size_t / mult;
@@ -231,8 +202,6 @@ impl Reader for TiffReader {
         new.pixel_type = pixtype;
         new.n_samples = n_samples;
         new.p_ndim = p_ndim;
-        new.interval_t = interval_t;
-        new.pixel_size = pixel_size;
         new.planar = planar;
 
         // test reading first frame, if error another reader (bioformats) can take over
@@ -241,6 +210,48 @@ impl Reader for TiffReader {
     }
 
     fn metadata(&self) -> Result<Ome, Error> {
+        let mut reader = self.get_reader()?;
+        let imagej_bytes = reader
+            .get_tag(Tag::Unknown(50839))
+            .or_else(|_| reader.get_tag(Tag::ImageDescription))?;
+        let imagej_bytes = match imagej_bytes {
+            Value::Ascii(s) => s.into_bytes(),
+            other => other.into_u8_vec()?,
+        };
+        let metadata_str = String::from_utf8_lossy(&imagej_bytes);
+        let metadata_map = parse_imagej_metadata(&metadata_str);
+
+        let interval_t = metadata_map
+            .get("interval")
+            .and_then(|v| v.parse::<f64>().ok());
+        let ru = reader
+            .get_tag(Tag::ResolutionUnit)
+            .ok()
+            .and_then(|i| i.into_u16().ok())
+            .unwrap_or(2);
+        let pixel_size = reader
+            .get_tag(Tag::XResolution)
+            .ok()
+            .and_then(|i| i.into_u64_vec().ok())
+            .and_then(|i| {
+                i.first()
+                    .and_then(|&n| i.get(1).map(|&d| (n as f64) / (d as f64)))
+            })
+            .and_then(|i| {
+                if i <= 0.0 {
+                    None
+                } else if ru == 3 {
+                    Some(1e4 / i)
+                } else if ru == 2 {
+                    Some(25400.0 / i)
+                } else {
+                    Some(1.0 / i)
+                }
+            });
+        let interval_z = metadata_map
+            .get("spacing")
+            .and_then(|v| v.parse::<f64>().ok());
+
         let ome_pixel_type = match self.pixel_type {
             PixelType::I8 => ome::PixelType::Int8,
             PixelType::U8 => ome::PixelType::Uint8,
@@ -262,13 +273,13 @@ impl Reader for TiffReader {
             size_t: self.shape.t as i32,
             dimension_order: ome::PixelsDimensionOrderType::Xyczt,
             r#type: ome_pixel_type,
-            physical_size_x: self.pixel_size.map(|v| v as f32),
+            physical_size_x: pixel_size.map(|v| v as f32),
             physical_size_x_unit: ome::UnitsLength::um,
-            physical_size_y: self.pixel_size.map(|v| v as f32),
+            physical_size_y: pixel_size.map(|v| v as f32),
             physical_size_y_unit: ome::UnitsLength::um,
-            physical_size_z: None,
+            physical_size_z: interval_z.map(|v| v as f32),
             physical_size_z_unit: ome::UnitsLength::um,
-            time_increment: None,
+            time_increment: interval_t.map(|v| v as f32),
             time_increment_unit: ome::UnitsTime::s,
             significant_bits: None,
             interleaved: None,
@@ -295,11 +306,13 @@ impl Reader for TiffReader {
                         the_c: Some(c as i32),
                         the_z: Some(z as i32),
                         the_t: Some(t as i32),
-                        delta_t: if self.interval_t > 0.0 {
-                            Some(t as f32 * self.interval_t as f32)
+                        delta_t: interval_t.and_then(|v| {
+                            if v > 0.0 {
+                                Some((t as f64 * v) as f32)
                             } else {
                                 None
-                        },
+                            }
+                        }),
                         ..Default::default()
                     });
                 }
@@ -341,7 +354,7 @@ impl Reader for TiffReader {
         reader.seek_to_image(page_idx)?;
 
         let data: DecodingResult = if self.planar {
-            let mut result = DecodingResult::U16(vec![]);
+            let mut result = DecodingResult::U16(Vec::new());
             reader.read_image_to_buffer(&mut result)?;
             result
         } else {

src/transforms.rs

@@ -3,30 +3,73 @@ use crate::error::Error;
 use crate::readers::{DynReader, Reader};
 use crate::view::View;
 pub use image_registration::transform::Transform;
-use ndarray::{Dimension, Ix2, Ix3, s};
+use ndarray::{Array2, Dimension, Ix2, Ix3, IxDyn, s};
 use serde::{Deserialize, Serialize};
+use std::collections::{HashMap, HashSet};
+use std::io::Seek;
 use std::path::Path;
 
-#[expect(clippy::upper_case_acronyms)]
-#[derive(Clone, Debug, Eq, PartialEq, Serialize, Deserialize)]
-pub enum TransformD {
-    YX(Transform<Ix2>),
-    ZYX(Transform<Ix3>),
+#[derive(Clone, Debug, Default, PartialEq, Serialize, Deserialize)]
+struct TransformOld {
+    #[serde(alias = "CenterOfRotationPoint")]
+    center_of_rotation_point: Vec<f64>,
+    #[serde(alias = "Size")]
+    size: Vec<f64>,
+    #[serde(alias = "TransformParameters")]
+    transform_parameters: Vec<f64>,
+    #[serde(alias = "dTransformParameters")]
+    dtransform_parameters: Vec<f64>,
+}
+
+impl TryFrom<HashMap<String, TransformOld>> for Transforms {
+    type Error = Error;
+
+    fn try_from(t: HashMap<String, TransformOld>) -> Result<Self, Error> {
+        Ok(Self {
+            channel: t
+                .into_iter()
+                .map(|(n, i)| {
+                    Ok((
+                        n,
+                        Transform::new_with_center(
+                            i.transform_parameters,
+                            i.center_of_rotation_point,
+                            i.size.into_iter().map(|j| j as usize).collect(),
+                        )
+                        .with_dparameters(i.dtransform_parameters)
+                        .inverse()?,
+                    ))
+                })
+                .collect::<Result<_, Error>>()?,
+            drift: Vec::new(),
+        })
+    }
 }
 
 #[derive(Clone, Debug, Default, Eq, PartialEq, Serialize, Deserialize)]
 pub struct Transforms {
-    pub channel: Vec<TransformD>,
-    pub drift: Vec<TransformD>,
+    #[serde(skip_serializing_if = "HashMap::is_empty", default = "HashMap::new")]
+    pub channel: HashMap<String, Transform<IxDyn>>,
+    #[serde(skip_serializing_if = "Vec::is_empty", default = "Vec::new")]
+    pub drift: Vec<Transform<IxDyn>>,
 }
 
 impl Transforms {
-    pub fn load(path: &Path) -> Result<Self, Error> {
-        let file = std::fs::File::open(path)?;
-        Ok(yaml_serde::from_reader(file)?)
+    pub fn load<P: AsRef<Path>>(path: P) -> Result<Self, Error> {
+        let mut file = std::fs::File::open(&path)?;
+        Ok(
+            if let Ok(t) = yaml_serde::from_reader::<_, Self>(&file)
+                && !(t.channel.is_empty() && t.drift.is_empty())
+            {
+                t
+            } else {
+                file.seek(std::io::SeekFrom::Start(0))?;
+                yaml_serde::from_reader::<_, HashMap<String, TransformOld>>(&file)?.try_into()?
+            },
+        )
     }
 
-    pub fn save(&self, path: &Path) -> Result<(), Error> {
+    pub fn save<P: AsRef<Path>>(&self, path: P) -> Result<(), Error> {
         let file = std::fs::OpenOptions::new()
             .write(true)
             .create(true)
@@ -39,30 +82,43 @@ impl Transforms {
         bead_files: &[&Path],
         main_channel: usize,
         default_transform: Option<Transform<Ix2>>,
-    ) -> Result<Vec<Transform<Ix2>>, Error> {
+    ) -> Result<HashMap<String, Transform<Ix2>>, Error> {
         let mut transforms = Vec::new();
         let default_transform = default_transform.unwrap_or_default();
         for file in bead_files {
             let view = View::<_, DynReader>::from_path(file)?;
             transforms.push(view.calculate_channel_transforms_2d(main_channel)?)
         }
-        let n_channels = transforms.iter().map(|t| t.len()).max().unwrap();
-        let mut average_transforms = Vec::new();
-        for channel in 0..n_channels {
-            let matrix = transforms
+        let channels = transforms
             .iter()
-                .map(|t| (&t[channel] * &default_transform).matrix())
-                .reduce(|a, b| a + b)
-                .unwrap()
-                / n_channels as f64;
-            let dmatrix = transforms
+            .flat_map(|t| t.keys())
+            .collect::<HashSet<_>>();
+        let mut average_transforms = HashMap::new();
+        for channel in channels {
+            let (s, n) = transforms
                 .iter()
-                .map(|t| ((&t[channel] * &default_transform).matrix() - &matrix).powi(2))
-                .reduce(|a, b| a + b)
-                .unwrap()
-                .sqrt()
-                / (n_channels as f64).sqrt();
-            average_transforms.push(
+                .filter_map(|t| {
+                    if t.contains_key(channel) {
+                        Some((&t[channel] * &default_transform).matrix())
+                    } else {
+                        None
+                    }
+                })
+                .fold((Array2::zeros((3, 3)), 0), |(s, n), t| (s + t, n + 1));
+            let matrix = s / (n as f64);
+            let (s, n) = transforms
+                .iter()
+                .filter_map(|t| {
+                    if t.contains_key(channel) {
+                        Some(((&t[channel] * &default_transform).matrix() - &matrix).powi(2))
+                    } else {
+                        None
+                    }
+                })
+                .fold((Array2::zeros((3, 3)), 0), |(s, n), t| (s + t, n + 1));
+            let dmatrix = (s / n as f64).sqrt();
+            average_transforms.insert(
+                channel.clone(),
                 Transform::default()
                     .with_matrix(matrix.view())
                     .with_dmatrix(dmatrix.view()),
@@ -75,30 +131,43 @@ impl Transforms {
         bead_files: &[&Path],
         main_channel: usize,
         default_transform: Option<Transform<Ix3>>,
-    ) -> Result<Vec<Transform<Ix3>>, Error> {
+    ) -> Result<HashMap<String, Transform<Ix3>>, Error> {
         let mut transforms = Vec::new();
         let default_transform = default_transform.unwrap_or_default();
         for file in bead_files {
             let view = View::<_, DynReader>::from_path(file)?;
             transforms.push(view.calculate_channel_transforms_3d(main_channel)?)
         }
-        let n_channels = transforms.iter().map(|t| t.len()).max().unwrap();
-        let mut average_transforms = Vec::new();
-        for channel in 0..n_channels {
-            let matrix = transforms
+        let channels = transforms
             .iter()
-                .map(|t| (&t[channel] * &default_transform).matrix())
-                .reduce(|a, b| a + b)
-                .unwrap()
-                / n_channels as f64;
-            let dmatrix = transforms
+            .flat_map(|t| t.keys())
+            .collect::<HashSet<_>>();
+        let mut average_transforms = HashMap::new();
+        for channel in channels {
+            let (s, n) = transforms
                 .iter()
-                .map(|t| ((&t[channel] * &default_transform).matrix() - &matrix).powi(2))
-                .reduce(|a, b| a + b)
-                .unwrap()
-                .sqrt()
-                / (n_channels as f64).sqrt();
-            average_transforms.push(
+                .filter_map(|t| {
+                    if t.contains_key(channel) {
+                        Some((&t[channel] * &default_transform).matrix())
+                    } else {
+                        None
+                    }
+                })
+                .fold((Array2::zeros((4, 4)), 0), |(s, n), t| (s + t, n + 1));
+            let matrix = s / (n as f64);
+            let (s, n) = transforms
+                .iter()
+                .filter_map(|t| {
+                    if t.contains_key(channel) {
+                        Some(((&t[channel] * &default_transform).matrix() - &matrix).powi(2))
+                    } else {
+                        None
+                    }
+                })
+                .fold((Array2::zeros((4, 4)), 0), |(s, n), t| (s + t, n + 1));
+            let dmatrix = (s / n as f64).sqrt();
+            average_transforms.insert(
+                channel.clone(),
                 Transform::default()
                     .with_matrix(matrix.view())
                     .with_dmatrix(dmatrix.view()),
@@ -109,34 +178,61 @@ impl Transforms {
 }
 
 impl<D: Dimension, R: Reader> View<D, R> {
-    pub fn with_transform_from_yaml(mut self, path: &Path) -> Result<Self, Error> {
-        self.transforms = Transforms::load(path)?;
+    #[cfg(feature = "transforms")]
+    pub(crate) fn get_transforms(&self) -> &Transforms {
+        &self.transforms
+    }
+
+    #[cfg(feature = "transforms")]
+    pub(crate) fn set_transforms(&mut self, transforms: Transforms) {
+        self.transforms = transforms;
+    }
+
+    pub fn with_transforms_from_yaml(mut self, path: &Path) -> Result<Self, Error> {
+        self.set_transforms(Transforms::load(path)?);
         Ok(self)
     }
 
-    pub fn load_transform_from_yaml(&mut self, path: &Path) -> Result<(), Error> {
-        self.transforms = Transforms::load(path)?;
+    pub fn load_transforms_from_yaml(&mut self, path: &Path) -> Result<(), Error> {
+        self.set_transforms(Transforms::load(path)?);
         Ok(())
     }
 
     pub fn calculate_channel_transforms_2d(
         &self,
         main_channel: usize,
-    ) -> Result<Vec<Transform<Ix2>>, Error> {
+    ) -> Result<HashMap<String, Transform<Ix2>>, Error> {
         let main_max = self
             .slice_cztyx(s![main_channel, .., 0, .., ..])?
             .max_proj(Axis::Z)?
             .as_array::<f64>()?;
-        let mut transforms = Vec::new();
-        for channel in 0..self.shape().c {
+        let mut transforms = HashMap::new();
+        let shape = vec![self.shape().y, self.shape().x];
+        let center = shape
+            .iter()
+            .map(|&i| (i as f64 - 1.0) / 2.0)
+            .collect::<Vec<_>>();
+        for (channel, metadata) in self.metadata()?.image[0].pixels.channel.iter().enumerate() {
+            let name = metadata
+                .name
+                .clone()
+                .unwrap_or_else(|| format!("channel{}", channel));
             if channel == main_channel {
-                transforms.push(Transform::default());
+                transforms.insert(
+                    name,
+                    Transform::default()
+                        .with_shape(shape.clone())
+                        .with_center(center.clone()),
+                );
             } else {
                 let max = self
                     .slice_cztyx(s![channel, .., 0, .., ..])?
                     .max_proj(Axis::Z)?
                     .as_array::<f64>()?;
-                transforms.push(Transform::register_affine(main_max.view(), max.view())?);
+                transforms.insert(
+                    name,
+                    Transform::register_affine(main_max.view(), max.view())?,
+                );
             }
         }
         Ok(transforms)
@@ -145,29 +241,46 @@ impl<D: Dimension, R: Reader> View<D, R> {
     pub fn calculate_channel_transforms_3d(
         &self,
         main_channel: usize,
-    ) -> Result<Vec<Transform<Ix3>>, Error> {
+    ) -> Result<HashMap<String, Transform<Ix3>>, Error> {
         let main_max = self
             .slice_cztyx(s![main_channel, .., 0, .., ..])?
             .as_array::<f64>()?;
-        let mut transforms = Vec::new();
-        for channel in 0..self.shape().c {
+        let mut transforms = HashMap::new();
+        let shape = vec![self.shape().z, self.shape().y, self.shape().x];
+        let center = shape
+            .iter()
+            .map(|&i| (i as f64 - 1.0) / 2.0)
+            .collect::<Vec<_>>();
+        for (channel, metadata) in self.metadata()?.image[0].pixels.channel.iter().enumerate() {
+            let name = metadata
+                .name
+                .clone()
+                .unwrap_or_else(|| format!("channel{}", channel));
             if channel == main_channel {
-                transforms.push(Transform::default());
+                transforms.insert(
+                    name,
+                    Transform::default()
+                        .with_shape(shape.clone())
+                        .with_center(center.clone()),
+                );
             } else {
                 let max = self
                     .slice_cztyx(s![channel, .., 0, .., ..])?
                     .as_array::<f64>()?;
-                transforms.push(Transform::register_affine(main_max.view(), max.view())?);
+                transforms.insert(
+                    name,
+                    Transform::register_affine(main_max.view(), max.view())?,
+                );
             }
         }
         Ok(transforms)
     }
 
-    pub fn calculate_drift_transform_2d(&self) -> Result<Vec<Transform<Ix2>>, Error> {
+    pub fn calculate_drift_transforms_2d(&self) -> Result<Vec<Transform<Ix2>>, Error> {
         todo!()
     }
 
-    pub fn calculate_drift_transform_3d(&self) -> Result<Vec<Transform<Ix3>>, Error> {
+    pub fn calculate_drift_transforms_3d(&self) -> Result<Vec<Transform<Ix3>>, Error> {
         todo!()
     }
 }
@@ -182,4 +295,22 @@ mod tests {
 
         Ok(())
     }
+
+    #[test]
+    fn load_transforms() -> Result<(), Box<dyn std::error::Error>> {
+        let t = Transforms::load("tests/files/transforms.yml")?;
+        println!("t: {:?}", t);
+        assert_eq!(t.channel["TV1"].ndim(), 2);
+        assert_eq!(t.channel["TV2"].ndim(), 2);
+        Ok(())
+    }
+
+    #[test]
+    fn load_old_transforms() -> Result<(), Box<dyn std::error::Error>> {
+        let t = Transforms::load("tests/files/transform_red.yml")?;
+        println!("t: {:?}", t);
+        assert_eq!(t.channel["TV1"].ndim(), 2);
+        assert_eq!(t.channel["TV2"].ndim(), 2);
+        Ok(())
+    }
 }