Modernize type annotations

src/tophu/io.py

@@ -1,9 +1,11 @@
+from __future__ import annotations
+
 import mmap
 import os
 import textwrap
 from dataclasses import dataclass
 from pathlib import Path
-from typing import Optional, Protocol, Tuple, Union, overload, runtime_checkable
+from typing import Protocol, overload, runtime_checkable
 
 import h5py
 import numpy as np
@@ -39,13 +41,13 @@ class DatasetReader(Protocol):
     dtype: np.dtype
     """numpy.dtype : Data-type of the array's elements."""
 
-    shape: Tuple[int, ...]
+    shape: tuple[int, ...]
     """tuple of int : Tuple of array dimensions."""
 
     ndim: int
     """int : Number of array dimensions."""
 
-    def __getitem__(self, key: Tuple[slice, ...], /) -> ArrayLike:
+    def __getitem__(self, key: tuple[slice, ...], /) -> ArrayLike:
         """Read a block of data."""
         ...
 
@@ -68,18 +70,18 @@ class DatasetWriter(Protocol):
     dtype: np.dtype
     """numpy.dtype : Data-type of the array's elements."""
 
-    shape: Tuple[int, ...]
+    shape: tuple[int, ...]
     """tuple of int : Tuple of array dimensions."""
 
     ndim: int
     """int : Number of array dimensions."""
 
-    def __setitem__(self, key: Tuple[slice, ...], value: np.ndarray, /) -> None:
+    def __setitem__(self, key: tuple[slice, ...], value: np.ndarray, /) -> None:
         """Write a block of data."""
         ...
 
 
-def _create_or_extend_file(filepath: Union[str, os.PathLike], size: int) -> None:
+def _create_or_extend_file(filepath: str | os.PathLike, size: int) -> None:
     """
     Create a file with the specified size or extend an existing file to the same size.
 
@@ -126,13 +128,13 @@ class BinaryFile(DatasetReader, DatasetWriter):
     filepath: Path
     """pathlib.Path : The file path."""
 
-    shape: Tuple[int, ...]
+    shape: tuple[int, ...]
     dtype: np.dtype
 
     def __init__(
         self,
-        filepath: Union[str, os.PathLike],
-        shape: Tuple[int, ...],
+        filepath: str | os.PathLike,
+        shape: tuple[int, ...],
         dtype: DTypeLike,
     ):
         """
@@ -175,7 +177,7 @@ def ndim(self) -> int:  # type: ignore[override]
     def __array__(self) -> np.ndarray:
         return self[:,]
 
-    def __getitem__(self, key: Tuple[slice, ...], /) -> np.ndarray:
+    def __getitem__(self, key: tuple[slice, ...], /) -> np.ndarray:
         with self.filepath.open("rb") as f:
             # Memory-map the entire file.
             with mmap.mmap(f.fileno(), 0, access=mmap.ACCESS_READ) as mm:
@@ -187,7 +189,7 @@ def __getitem__(self, key: Tuple[slice, ...], /) -> np.ndarray:
                 del arr
             return data
 
-    def __setitem__(self, key: Tuple[slice, ...], value: np.ndarray, /) -> None:
+    def __setitem__(self, key: tuple[slice, ...], value: np.ndarray, /) -> None:
         with self.filepath.open("r+b") as f:
             # Memory-map the entire file.
             with mmap.mmap(f.fileno(), 0, access=mmap.ACCESS_WRITE) as mm:
@@ -224,16 +226,16 @@ class HDF5Dataset(DatasetReader, DatasetWriter):
     datapath: str
     """str : The path to the dataset within the file."""
 
-    chunks: Optional[Tuple[int, ...]]
+    chunks: tuple[int, ...] | None
     """
     tuple of int : Tuple giving the chunk shape, or None if chunked storage is not used.
     """
 
-    shape: Tuple[int, ...]
+    shape: tuple[int, ...]
     dtype: np.dtype
 
     @overload
-    def __init__(self, filepath: Union[str, os.PathLike], datapath: str):  # noqa: D418
+    def __init__(self, filepath: str | os.PathLike, datapath: str):  # noqa: D418
         """
         Construct a new `HDF5Dataset` object from an existing dataset.
 
@@ -249,9 +251,9 @@ def __init__(self, filepath: Union[str, os.PathLike], datapath: str):  # noqa: D
     @overload
     def __init__(
         self,
-        filepath: Union[str, os.PathLike],
+        filepath: str | os.PathLike,
         datapath: str,
-        shape: Tuple[int, ...],
+        shape: tuple[int, ...],
         dtype: DTypeLike,
         **kwargs,
     ):  # noqa: D418
@@ -340,19 +342,19 @@ def ndim(self) -> int:  # type: ignore[override]
     def __array__(self) -> np.ndarray:
         return self[:,]
 
-    def __getitem__(self, key: Tuple[slice, ...], /) -> np.ndarray:
+    def __getitem__(self, key: tuple[slice, ...], /) -> np.ndarray:
         with h5py.File(self.filepath, "r") as f:
             dataset = f[self.datapath]
             return dataset[key]
 
-    def __setitem__(self, key: Tuple[slice, ...], value: np.ndarray, /) -> None:
+    def __setitem__(self, key: tuple[slice, ...], value: np.ndarray, /) -> None:
         with h5py.File(self.filepath, "r+") as f:
             dataset = f[self.datapath]
             dataset[key] = value
 
 
 def _check_contains_single_band(
-    dataset: Union[rasterio.io.DatasetReader, rasterio.io.DatasetWriter]
+    dataset: rasterio.io.DatasetReader | rasterio.io.DatasetWriter,
 ) -> None:
     """
     Validate that the supplied dataset contains a single raster band.
@@ -374,7 +376,7 @@ def _check_contains_single_band(
 
 
 def _check_valid_band(
-    dataset: Union[rasterio.io.DatasetReader, rasterio.io.DatasetWriter],
+    dataset: rasterio.io.DatasetReader | rasterio.io.DatasetWriter,
     band: int,
 ) -> None:
     """
@@ -438,18 +440,18 @@ class RasterBand(DatasetReader, DatasetWriter):
     coordinate reference system.
     """
 
-    shape: Tuple[int, int]
+    shape: tuple[int, int]
     dtype: np.dtype
 
     # TODO: `chunks` & `nodata` attributes
 
     @overload
     def __init__(
         self,
-        filepath: Union[str, os.PathLike],
+        filepath: str | os.PathLike,
         *,
-        band: Optional[int] = None,
-        driver: Optional[str] = None,
+        band: int | None = None,
+        driver: str | None = None,
     ):  # noqa: D418
         """
         Construct a new `RasterBand` object.
@@ -470,14 +472,14 @@ def __init__(
     @overload
     def __init__(
         self,
-        filepath: Union[str, os.PathLike],
+        filepath: str | os.PathLike,
         width: int,
         height: int,
         dtype: DTypeLike,
         *,
-        driver: Optional[str] = None,
-        crs: Optional[Union[str, dict, rasterio.crs.CRS]] = None,
-        transform: Optional[rasterio.transform.Affine] = None,
+        driver: str | None = None,
+        crs: str | dict | rasterio.crs.CRS | None = None,
+        transform: rasterio.transform.Affine | None = None,
     ):  # noqa: D418
         """
         Construct a new `RasterBand` object.
@@ -595,7 +597,7 @@ def ndim(self) -> int:  # type: ignore[override]
     def __array__(self) -> np.ndarray:
         return self[:, :]
 
-    def __getitem__(self, key: Tuple[slice, ...], /) -> np.ndarray:
+    def __getitem__(self, key: tuple[slice, ...], /) -> np.ndarray:
         with rasterio.io.DatasetReader(
             self.filepath,
             driver=self.driver,
@@ -607,7 +609,7 @@ def __getitem__(self, key: Tuple[slice, ...], /) -> np.ndarray:
             )
             return dataset.read(self.band, window=window)
 
-    def __setitem__(self, key: Tuple[slice, ...], value: np.ndarray, /) -> None:
+    def __setitem__(self, key: tuple[slice, ...], value: np.ndarray, /) -> None:
         with rasterio.io.DatasetWriter(
             self.filepath,
             "r+",

src/tophu/multilook.py

@@ -1,5 +1,8 @@
+from __future__ import annotations
+
 import warnings
-from typing import Iterable, SupportsInt, Tuple, Union, cast
+from collections.abc import Iterable
+from typing import Tuple, cast
 
 import dask.array as da
 import numpy as np
@@ -11,10 +14,7 @@
 ]
 
 
-IntOrInts = Union[SupportsInt, Iterable[SupportsInt]]
-
-
-def multilook(arr: da.Array, nlooks: IntOrInts) -> da.Array:
+def multilook(arr: da.Array, nlooks: int | Iterable[int]) -> da.Array:
     """
     Multilook an array by simple averaging.
 

src/tophu/multiscale.py

@@ -1,5 +1,6 @@
+from __future__ import annotations
+
 import warnings
-from typing import Optional, Tuple
 
 import dask.array as da
 import numpy as np
@@ -20,7 +21,7 @@
 
 def lowpass_filter_and_multilook(
     arr: da.Array,
-    downsample_factor: Tuple[int, int],
+    downsample_factor: tuple[int, int],
     *,
     shape_factor: float = 1.5,
     overhang: float = 0.5,
@@ -204,14 +205,14 @@ def coarse_unwrap(
     coherence: da.Array,
     nlooks: float,
     unwrap: UnwrapCallback,
-    downsample_factor: Tuple[int, int],
+    downsample_factor: tuple[int, int],
     *,
     do_lowpass_filter: bool = True,
     shape_factor: float = 1.5,
     overhang: float = 0.5,
     ripple: float = 0.01,
     attenuation: float = 40.0,
-) -> Tuple[da.Array, da.Array]:
+) -> tuple[da.Array, da.Array]:
     """
     Estimate coarse unwrapped phase by unwrapping a downsampled interferogram.
 
@@ -429,14 +430,14 @@ def _multiscale_unwrap(
     coherence: da.Array,
     nlooks: float,
     unwrap: UnwrapCallback,
-    downsample_factor: Tuple[int, int],
+    downsample_factor: tuple[int, int],
     *,
     do_lowpass_filter: bool = True,
     shape_factor: float = 1.5,
     overhang: float = 0.5,
     ripple: float = 0.01,
     attenuation: float = 40.0,
-) -> Tuple[da.Array, da.Array]:
+) -> tuple[da.Array, da.Array]:
     """
     Perform 2-D phase unwrapping using a multi-resolution approach.
 
@@ -557,10 +558,10 @@ def _multiscale_unwrap(
 
 
 def get_tile_dims(
-    shape: Tuple[int, ...],
-    ntiles: Tuple[int, ...],
-    snap_to: Optional[Tuple[int, ...]] = None,
-) -> Tuple[int, ...]:
+    shape: tuple[int, ...],
+    ntiles: tuple[int, ...],
+    snap_to: tuple[int, ...] | None = None,
+) -> tuple[int, ...]:
     """
     Get tile dimensions of an array partitioned into tiles.
 
@@ -622,8 +623,8 @@ def multiscale_unwrap(
     coherence: DatasetReader,
     nlooks: float,
     unwrap: UnwrapCallback,
-    downsample_factor: Tuple[int, int],
-    ntiles: Tuple[int, int],
+    downsample_factor: tuple[int, int],
+    ntiles: tuple[int, int],
     *,
     do_lowpass_filter: bool = True,
     shape_factor: float = 1.5,

src/tophu/tile.py

@@ -1,5 +1,7 @@
+from __future__ import annotations
+
 import itertools
-from typing import Iterable, Iterator, Optional, SupportsInt, Tuple, Union
+from collections.abc import Iterable, Iterator
 
 import numpy as np
 
@@ -10,10 +12,6 @@
 ]
 
 
-IntOrInts = Union[SupportsInt, Iterable[SupportsInt]]
-NDSlice = Tuple[slice, ...]
-
-
 class TiledPartition:
     """
     A partitioning of an N-dimensional array into tiles.
@@ -31,10 +29,10 @@ class TiledPartition:
 
     def __init__(
         self,
-        shape: IntOrInts,
-        ntiles: IntOrInts,
-        overlap: Optional[IntOrInts] = None,
-        snap_to: Optional[IntOrInts] = None,
+        shape: int | Iterable[int],
+        ntiles: int | Iterable[int],
+        overlap: int | Iterable[int] | None = None,
+        snap_to: int | Iterable[int] | None = None,
     ):
         """
         Construct a new `TiledPartition` object.
@@ -111,32 +109,32 @@ def __init__(
         self._tiledims = tiledims
 
     @property
-    def ntiles(self) -> Tuple[int, ...]:
+    def ntiles(self) -> tuple[int, ...]:
         """tuple of int : Number of tiles along each array axis."""
         return self._ntiles
 
     @property
-    def tiledims(self) -> Tuple[int, ...]:
+    def tiledims(self) -> tuple[int, ...]:
         """
         tuple of int : Shape of a typical tile. The last tile along each axis may be
         smaller.
         """
         return tuple(self._tiledims)
 
     @property
-    def strides(self) -> Tuple[int, ...]:
+    def strides(self) -> tuple[int, ...]:
         """
         tuple of int : Step size between the start of adjacent tiles along each
         axis.
         """
         return tuple(self._strides)
 
     @property
-    def overlap(self) -> Tuple[int, ...]:
+    def overlap(self) -> tuple[int, ...]:
         """tuple of int : Overlap between adjacent tiles along each axis."""
         return tuple(self._tiledims - self._strides)
 
-    def __getitem__(self, index: IntOrInts) -> NDSlice:
+    def __getitem__(self, index: int | Iterable[int]) -> tuple[slice, ...]:
         """
         Access a tile.
 
@@ -171,7 +169,7 @@ def wrap_index(i: int, n: int) -> int:
 
         return tuple([slice(a, b) for (a, b) in zip(start, stop)])
 
-    def __iter__(self) -> Iterator[NDSlice]:
+    def __iter__(self) -> Iterator[tuple[slice, ...]]:
         """
         Iterate over tiles in arbitrary order.