Update packaging

.github/workflows/main.yaml

@@ -13,20 +13,20 @@ jobs:
       max-parallel: 8
       matrix:
         platform: [ "ubuntu-latest", "macos-latest", "windows-latest" ]
-        python-version: [ "3.8", "3.9", "3.10", "3.11", "3.12" ]
-        poetry-version: [ "1.7.1" ]
+        python-version: [ "3.9", "3.10", "3.11", "3.12" ]
+        poetry-version: [ "1.8.3" ]
 
     steps:
       - name: Checkout project
-        uses: actions/checkout@v3
+        uses: actions/checkout@v4
 
       - name: Setup Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python-version }}
 
       - name: Install Poetry ${{ matrix.poetry-version }}
-        uses: abatilo/actions-poetry@v2
+        uses: abatilo/actions-poetry@v3
         with:
           poetry-version: ${{ matrix.poetry-version }}
 
@@ -36,7 +36,7 @@ jobs:
           poetry config virtualenvs.in-project true --local
 
       - name: Define a cache for the virtual environment based on the dependencies lock file
-        uses: actions/cache@v3
+        uses: actions/cache@v4
         with:
           path: ./.venv
           key: venv-${{ hashFiles('poetry.lock') }}
@@ -47,7 +47,6 @@ jobs:
       - name: Run static analysis and linters
         run: |
           poetry run ruff check .
-          poetry run isort -c .
 
       - name: Run tests
         run: poetry run pytest -v --color=yes --cov=csaps --cov-report=term --cov-report=lcov:coverage.info

.pre-commit-config.yaml

@@ -0,0 +1,12 @@
+# See https://pre-commit.com for more information
+# See https://pre-commit.com/hooks.html for more hooks
+
+repos:
+  - repo: local
+    hooks:
+      - id: ruff
+        name: ruff
+        entry: poetry run ruff check
+        language: system
+        types: [python]
+        require_serial: true

README.md

@@ -22,7 +22,7 @@ Use pip for installing:
 pip install -U csaps
 ```
 
-The module depends only on NumPy and SciPy. Python 3.6 or above is supported.
+The module depends only on NumPy and SciPy. Python 3.9 or above is supported.
 
 ## Simple Examples
 

csaps/__init__.py

@@ -13,15 +13,13 @@
     # Shortcut
     'csaps',
     'AutoSmoothingResult',
-
     # Classes
     'ISplinePPForm',
     'ISmoothingSpline',
     'SplinePPForm',
     'NdGridSplinePPForm',
     'CubicSmoothingSpline',
     'NdGridCubicSmoothingSpline',
-
     # Type-hints
     'UnivariateDataType',
     'MultivariateDataType',

csaps/_base.py

@@ -11,8 +11,7 @@
 
 
 class ISplinePPForm(abc.ABC, Generic[TData, TProps]):
-    """The interface class for spline representation in PP-form
-    """
+    """The interface class for spline representation in PP-form"""
 
     __module__ = 'csaps'
 
@@ -84,24 +83,20 @@ def shape(self) -> Tuple[int, ...]:
 
 
 class ISmoothingSpline(abc.ABC, Generic[TSpline, TSmooth, TXi, TNu, TExtrapolate]):
-    """The interface class for smooting splines
-    """
+    """The interface class for smooting splines"""
 
     __module__ = 'csaps'
 
     @property
     @abc.abstractmethod
     def smooth(self) -> TSmooth:
-        """Returns smoothing factor(s)
-        """
+        """Returns smoothing factor(s)"""
 
     @property
     @abc.abstractmethod
     def spline(self) -> TSpline:
-        """Returns spline representation in PP-form
-        """
+        """Returns spline representation in PP-form"""
 
     @abc.abstractmethod
     def __call__(self, xi: TXi, nu: Optional[TNu] = None, extrapolate: Optional[TExtrapolate] = None) -> np.ndarray:
-        """Evaluates spline on the data sites
-        """
+        """Evaluates spline on the data sites"""

csaps/_reshape.py

@@ -150,7 +150,7 @@ def umv_coeffs_to_flatten(arr: np.ndarray):
         strides = arr.strides[:-3:-1]
         arr_view = as_strided(arr, shape=shape, strides=strides)
     else:  # pragma: no cover
-        raise ValueError(f"The array ndim must be 2 or 3, but given array has ndim={arr.ndim}.")
+        raise ValueError(f'The array ndim must be 2 or 3, but given array has ndim={arr.ndim}.')
 
     return arr_view
 

csaps/_sspndg.py

@@ -62,11 +62,11 @@ def coeffs(self) -> np.ndarray:
 
     @property
     def order(self) -> Tuple[int, ...]:
-        return self.c.shape[:self.c.ndim // 2]
+        return self.c.shape[: self.c.ndim // 2]
 
     @property
     def pieces(self) -> Tuple[int, ...]:
-        return self.c.shape[self.c.ndim // 2:]
+        return self.c.shape[self.c.ndim // 2 :]
 
     @property
     def ndim(self) -> int:
@@ -112,7 +112,7 @@ def __call__(
             raise ValueError(f"'x' sequence must have length {self.ndim} according to 'breaks'")
 
         if nu is None:
-            nu = (0, ) * len(x)
+            nu = (0,) * len(x)
 
         if extrapolate is None:
             extrapolate = True
@@ -210,7 +210,6 @@ def __init__(
         smooth: Optional[Union[float, Sequence[Optional[float]]]] = None,
         normalizedsmooth: bool = False,
     ) -> None:
-
         x, y, w, s = self._prepare_data(xdata, ydata, weights, smooth)
         coeffs, smooth = self._make_spline(x, y, w, s, normalizedsmooth)
 
@@ -306,8 +305,7 @@ def _prepare_data(cls, xdata, ydata, weights, smooth):
 
         if len(smooth) != data_ndim:
             raise ValueError(
-                'Number of smoothing parameter values must '
-                f'be equal number of dimensions ({data_ndim})'
+                'Number of smoothing parameter values must ' f'be equal number of dimensions ({data_ndim})'
             )
 
         return xdata, ydata, weights, smooth
@@ -324,7 +322,7 @@ def _make_spline(xdata, ydata, weights, smooth, normalizedsmooth):
                 smooth=smooth[0],
                 normalizedsmooth=normalizedsmooth,
             )
-            return s.spline.coeffs, (s.smooth, )
+            return s.spline.coeffs, (s.smooth,)
 
         shape = ydata.shape
         coeffs = ydata

csaps/_sspumv.py

@@ -58,8 +58,7 @@ def ndim(self) -> int:
 
     @property
     def shape(self) -> Tuple[int, ...]:
-        """Returns the source data shape
-        """
+        """Returns the source data shape"""
         shape: List[int] = list(self.c.shape[2:])
         shape.insert(self.axis, self.c.shape[1] + 1)
 
@@ -124,7 +123,6 @@ def __init__(
         axis: int = -1,
         normalizedsmooth: bool = False,
     ):
-
         x, y, w, shape, axis = self._prepare_data(xdata, ydata, weights, axis)
         coeffs, smooth = self._make_spline(x, y, w, smooth, shape, normalizedsmooth)
         spline = SplinePPForm.construct_fast(coeffs, x, axis=axis)
@@ -236,7 +234,7 @@ def _compute_smooth(a, b):
         def trace(m: sp.dia_matrix):
             return m.diagonal().sum()
 
-        return 1. / (1. + trace(a) / (6. * trace(b)))
+        return 1.0 / (1.0 + trace(a) / (6.0 * trace(b)))
 
     @staticmethod
     def _normalize_smooth(x: np.ndarray, w: np.ndarray, smooth: Optional[float]):
@@ -246,8 +244,8 @@ def _normalize_smooth(x: np.ndarray, w: np.ndarray, smooth: Optional[float]):
 
         span = np.ptp(x)
 
-        eff_x = 1 + (span**2) / np.sum(np.diff(x)**2)
-        eff_w = np.sum(w)**2 / np.sum(w**2)
+        eff_x = 1 + (span**2) / np.sum(np.diff(x) ** 2)
+        eff_w = np.sum(w) ** 2 / np.sum(w**2)
         k = 80 * (span**3) * (x.size**-2) * (eff_x**-0.5) * (eff_w**-0.5)
 
         s = 0.5 if smooth is None else smooth
@@ -281,11 +279,11 @@ def _make_spline(x, y, w, smooth, shape, normalizedsmooth):
         diags_r = np.vstack((dx[1:], 2 * (dx[1:] + dx[:-1]), dx[:-1]))
         r = sp.spdiags(diags_r, [-1, 0, 1], pcount - 2, pcount - 2)
 
-        dx_recip = 1. / dx
+        dx_recip = 1.0 / dx
         diags_qtw = np.vstack((dx_recip[:-1], -(dx_recip[1:] + dx_recip[:-1]), dx_recip[1:]))
-        diags_sqrw_recip = 1. / np.sqrt(w)
+        diags_sqrw_recip = 1.0 / np.sqrt(w)
 
-        qtw = (sp.diags(diags_qtw, [0, 1, 2], (pcount - 2, pcount)) @ sp.diags(diags_sqrw_recip, 0, (pcount, pcount)))
+        qtw = sp.diags(diags_qtw, [0, 1, 2], (pcount - 2, pcount)) @ sp.diags(diags_sqrw_recip, 0, (pcount, pcount))
         qtw = qtw @ qtw.T
 
         p = smooth
@@ -295,7 +293,7 @@ def _make_spline(x, y, w, smooth, shape, normalizedsmooth):
         elif smooth is None:
             p = CubicSmoothingSpline._compute_smooth(r, qtw)
 
-        pp = (6. * (1. - p))
+        pp = 6.0 * (1.0 - p)
 
         # Solve linear system for the 2nd derivatives
         a = pp * qtw + p * r
@@ -314,15 +312,15 @@ def _make_spline(x, y, w, smooth, shape, normalizedsmooth):
         d1 = np.diff(vpad(u), axis=0) / dx
         d2 = np.diff(vpad(d1), axis=0)
 
-        diags_w_recip = 1. / w
+        diags_w_recip = 1.0 / w
         w = sp.diags(diags_w_recip, 0, (pcount, pcount))
 
         yi = y.T - (pp * w) @ d2
         pu = vpad(p * u)
 
         c1 = np.diff(pu, axis=0) / dx
-        c2 = 3. * pu[:-1, :]
-        c3 = np.diff(yi, axis=0) / dx - dx * (2. * pu[:-1, :] + pu[1:, :])
+        c2 = 3.0 * pu[:-1, :]
+        c3 = np.diff(yi, axis=0) / dx - dx * (2.0 * pu[:-1, :] + pu[1:, :])
         c4 = yi[:-1, :]
 
         c_shape = (4, pcount - 1) + shape[1:]

docs/conf.py

@@ -25,6 +25,7 @@
 
 def _get_version():
     from csaps import __version__
+
     return __version__
 
 
@@ -54,10 +55,10 @@ def _get_version():
     'figure.autolayout': 'True',
     'figure.figsize': '5, 3.5',
     'savefig.bbox': 'tight',
-    'savefig.facecolor': "None",
+    'savefig.facecolor': 'None',
 }
 
-plot_formats = [("png", 90)]
+plot_formats = [('png', 90)]
 plot_include_source = True
 plot_html_show_source_link = False
 plot_html_show_formats = False