Merge pull request #109 from v0lta/add-pytyped

pyptoject.toml

Author: v0lta

.github/workflows/tests.yml

@@ -13,7 +13,7 @@ jobs:
     strategy:
       matrix:
         os: [ ubuntu-latest ]
-        python-version: [3.9, 3.12]
+        python-version: [3.11, 3.12]
     steps:
       - uses: actions/checkout@v2
       - name: Set up Python ${{ matrix.python-version }}
@@ -30,7 +30,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: [3.9, 3.12]
+        python-version: [3.11, 3.12]
     steps:
       - uses: actions/checkout@v2
       - name: Set up Python ${{ matrix.python-version }}
@@ -46,7 +46,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: [3.9, 3.12]
+        python-version: [3.11, 3.12]
     steps:
       - uses: actions/checkout@v2
       - name: Set up Python ${{ matrix.python-version }}

.gitignore

@@ -4,6 +4,7 @@ coverage_html_report/
 htmlcov
 .noseids
 log/
+.virtual_python
 examples/deepfake_analysis/ffhq_style_gan/
 
 

noxfile.py

@@ -78,8 +78,8 @@ def format(session):
     """Fix common convention problems automatically."""
     session.install("black")
     session.install("isort")
-    session.run("isort", ".")
-    session.run("black", ".")
+    session.run("isort", "src", "tests", "noxfile.py")
+    session.run("black", "src", "tests", "noxfile.py")
 
 
 @nox.session(name="coverage")
@@ -100,27 +100,6 @@ def clean_coverage(session):
     session.run("rm", "-r", "htmlcov", external=True)
 
 
-@nox.session(name="build")
-def build(session):
-    """Build a pip package."""
-    session.install("wheel")
-    session.install("setuptools")
-    session.run("python", "setup.py", "-q", "sdist", "bdist_wheel")
-
-
-@nox.session(name="finish")
-def finish(session):
-    """Finish this version increase the version number and upload to pypi."""
-    session.install("bump2version")
-    session.install("twine")
-    session.run("bumpversion", "release", external=True)
-    build(session)
-    session.run("twine", "upload", "--skip-existing", "dist/*", external=True)
-    session.run("git", "push", external=True)
-    session.run("bumpversion", "patch", external=True)
-    session.run("git", "push", external=True)
-
-
 @nox.session(name="check-package")
 def pyroma(session):
     """Run pyroma to check if the package is ok."""

pyproject.toml

@@ -0,0 +1,58 @@
+[tool.pdm]
+package-dir = "src"
+
+[project]
+name = "ptwt"
+description = "Differentiable and gpu enabled fast wavelet transforms in PyTorch"
+version = "0.1.10-dev"
+keywords = ["Wavelets", "Wavelet Transform", "Fast Wavelet Transform", "Boundary Wavelets", "PyTorch"]
+readme = "README.rst"
+authors = [
+    {name = "Moritz Wolter and Felix Blanke", email = "[email protected]"},
+]
+maintainers = [
+    {name = "Moritz Wolter and Felix Blanke", email = "[email protected]"},
+]
+classifiers = [
+    "Development Status :: 4 - Beta",
+    "Environment :: Console",
+    "Intended Audience :: Science/Research",
+    "License :: OSI Approved :: European Union Public Licence 1.2 (EUPL 1.2)",
+    "Operating System :: OS Independent",
+    "Programming Language :: Python",
+    "Programming Language :: Python :: 3 :: Only",
+    "Programming Language :: Python :: 3.12",
+    "Programming Language :: Python :: 3.11",
+    "Topic :: Scientific/Engineering :: Artificial Intelligence",
+]
+requires-python = ">=3.11"
+dependencies = [
+    "PyWavelets",
+    "numpy",
+    "torch",
+]
+license = {text = "EUPL-1.2"}
+
+[project.urls]
+Homepage = "https://github.com/v0lta/PyTorch-Wavelet-Toolbox"
+Downloads = "https://github.com/v0lta/PyTorch-Wavelet-Toolbox/releases"
+"Bug Tracker" = "https://github.com/v0lta/PyTorch-Wavelet-Toolbox/issues"
+"Source Code" = "https://github.com/v0lta/PyTorch-Wavelet-Toolbox"
+
+[project.optional-dependencies]
+tests = [
+    "pooch",
+    "pytest",
+    "scipy>=1.10",
+]
+typing = [
+    "mypy>=1.11",
+    "pytest",
+]
+examples = [
+    "matplotlib",
+]
+
+[build-system]
+requires = ["pdm-backend"]
+build-backend = "pdm.backend"

setup.cfg

@@ -758,7 +758,11 @@ def rename_kwargs(
         kwargs: Param.kwargs,  # type: ignore
         aliases: dict[str, str],
     ) -> None:
-        """Rename deprecated kwarg."""
+        """Rename deprecated kwarg.
+
+        Raises:
+            TypeError: If both arguments are present.
+        """
         for alias, new in aliases.items():
             if alias in kwargs:
                 if new in kwargs:

setup.py

@@ -11,6 +11,8 @@
 from pywt._functions import scale2frequency
 from torch.fft import fft, ifft
 
+__all__ = ["cwt"]
+
 
 def _next_fast_len(n: int) -> int:
     """Round up size to the nearest power of two.
@@ -24,10 +26,10 @@ def _next_fast_len(n: int) -> int:
 
 def cwt(
     data: torch.Tensor,
-    scales: Union[np.ndarray, torch.Tensor],  # type: ignore
+    scales: Union[np.ndarray, torch.Tensor],
     wavelet: Union[ContinuousWavelet, str],
     sampling_period: float = 1.0,
-) -> tuple[torch.Tensor, np.ndarray]:  # type: ignore
+) -> tuple[torch.Tensor, np.ndarray]:
     """Compute the single-dimensional continuous wavelet transform.
 
     This function is a PyTorch port of pywt.cwt as found at:
@@ -185,11 +187,11 @@ def _integrate_wavelet(
     """
 
     def _integrate(
-        arr: Union[np.ndarray, torch.Tensor],  # type: ignore
-        step: Union[np.ndarray, torch.Tensor],  # type: ignore
-    ) -> Union[np.ndarray, torch.Tensor]:  # type: ignore
+        arr: Union[np.ndarray, torch.Tensor],
+        step: Union[np.ndarray, torch.Tensor],
+    ) -> Union[np.ndarray, torch.Tensor]:
         if type(arr) is np.ndarray:
-            integral = np.cumsum(arr)
+            integral: Any = np.cumsum(arr)
         elif type(arr) is torch.Tensor:
             integral = torch.cumsum(arr, -1)
         else:
@@ -212,12 +214,12 @@ def _integrate(
         return _integrate(psi, step), x
 
     elif len(functions_approximations) == 3:  # orthogonal wavelet
-        _, psi, x = functions_approximations
+        _, psi, x = functions_approximations  # type: ignore
         step = x[1] - x[0]
         return _integrate(psi, step), x
 
     else:  # biorthogonal wavelet
-        _, psi_d, _, psi_r, x = functions_approximations
+        _, psi_d, _, psi_r, x = functions_approximations  # type: ignore
         step = x[1] - x[0]
         return _integrate(psi_d, step), _integrate(psi_r, step), x
 
@@ -248,7 +250,11 @@ def __init__(self, name: str):
         )
 
     def __call__(self, grid_values: torch.Tensor) -> torch.Tensor:
-        """Return numerical values for the wavelet on a grid."""
+        """Return numerical values for the wavelet on a grid.
+
+        Raises:
+            NotImplementedError: If this call is not overwritten by a child.
+        """
         raise NotImplementedError
 
     @property

src/ptwt/_util.py

@@ -26,6 +26,8 @@
 )
 from .constants import BoundaryMode, Wavelet, WaveletCoeff1d
 
+__all__ = ["wavedec", "waverec"]
+
 
 def _fwt_pad(
     data: torch.Tensor,

src/ptwt/continuous_transform.py

@@ -27,6 +27,8 @@
 )
 from .constants import BoundaryMode, Wavelet, WaveletCoeff2d, WaveletDetailTuple2d
 
+__all__ = ["wavedec2", "waverec2"]
+
 
 def _construct_2d_filt(lo: torch.Tensor, hi: torch.Tensor) -> torch.Tensor:
     """Construct two-dimensional filters using outer products.