update development dependencies

lmo/__init__.py

@@ -47,7 +47,7 @@
     import numpy as np
 
     if np.__version__.startswith("2."):
-        np.set_printoptions(legacy="1.25")  # pyright: ignore[reportArgumentType]
+        np.set_printoptions(legacy="1.25")
 
     del np
 

lmo/_lm.py

@@ -76,13 +76,13 @@ def __call__(self, x: onp.ToFloatND, /) -> _FloatND: ...
 
 
 def _l_weights_pwm(
-    r: _OrderT,
-    n: _SizeT,
+    r: int,
+    n: int,
     /,
     trim: tuple[int, int],
     *,
     dtype: _ToDType[_FloatT],
-) -> onp.Array[tuple[_OrderT, _SizeT], _FloatT]:
+) -> onp.Array2D[_FloatT]:
     s, t = trim
     r0 = r + s + t
     dtype = np.dtype(dtype)
@@ -106,13 +106,13 @@ def _l_weights_pwm(
 
 
 def _l_weights_ostat(
-    r: _OrderT,
-    n: _SizeT,
+    r: int,
+    n: int,
     /,
     trim: tuple[int, int] | tuple[float, float],
     *,
     dtype: _ToDType[_FloatT],
-) -> onp.Array[tuple[_OrderT, _SizeT], _FloatT]:
+) -> onp.Array2D[_FloatT]:
     assert r >= 1, r
 
     s, t = trim
@@ -344,18 +344,15 @@ def l_moment(
     dtype: _ToDType[_FloatT],
     **kwds: Unpack[lmt.LMomentOptions],
 ) -> onp.ArrayND[_FloatT]: ...
-def l_moment(
+def l_moment(  # pyright
     a: onp.ToFloatND,
     r: lmt.ToOrder,
     /,
     trim: lmt.ToTrim = 0,
     *,
     axis: int | None = None,
     dtype: _ToDType[npc.floating] = np.float64,
-    fweights: lmt.ToFWeights | None = None,
-    aweights: lmt.ToAWeights | None = None,
-    sort: lmt.SortKind | bool = True,
-    cache: bool | None = None,
+    **kwds: Unpack[lmt.LMomentOptions],
 ) -> float | _FloatND:
     r"""
     Estimates the generalized trimmed L-moment $\lambda^{(s, t)}_r$ from
@@ -460,9 +457,9 @@ def l_moment(
         a,
         axis=axis,
         dtype=dtype,
-        fweights=fweights,
-        aweights=aweights,
-        sort=sort,
+        fweights=kwds.pop("fweights", None),
+        aweights=kwds.pop("aweights", None),
+        sort=kwds.pop("sort", True),
     )
     x_k = ensure_axis_at(x_k, axis, -1)
     n = x_k.shape[-1]
@@ -482,7 +479,10 @@ def l_moment(
         if t:
             x_k[..., -t:] = np.nan_to_num(x_k[..., -t:], nan=np.nan)
 
-    l_r = np.inner(l_weights(r_max, n, st, dtype=dtype, cache=cache), x_k)
+    l_r = np.inner(
+        l_weights(r_max, n, st, dtype=dtype, cache=kwds.pop("cache", None)),
+        x_k,
+    )
 
     out: npc.floating | _FloatND
     if r_min > 0:

lmo/distributions/_wakeby.py

@@ -218,7 +218,7 @@ def _fitstart(
     @override
     def _pdf(self, /, x: _XT, b: float, d: float, f: float) -> _XT:
         # application of the inverse function theorem
-        return 1 / self._qdf(self._cdf(x, b, d, f), b, d, f)  # pyright: ignore[reportReturnType]
+        return 1 / self._qdf(self._cdf(x, b, d, f), b, d, f)
 
     @override
     def _cdf(self, /, x: _XT, b: float, d: float, f: float) -> _XT:

pyproject.toml

@@ -52,36 +52,35 @@ Funding = "https://github.com/sponsors/jorenham"
 
 [dependency-groups]
 debug = [
-    "ipython>=8.31.0",
+    "ipython>=9.0.2",
     "ipykernel>=6.29.5",
     "line_profiler>=4.2.0",
-    "matplotlib>=3.10.0",
+    "matplotlib>=3.10.1",
     "typing-extensions>=4.12.2",
 ]
 docs = [
     "mkdocs>=1.6.1",
-    "mkdocs-bibtex>=2.16.2",
-    "mkdocs-git-revision-date-localized-plugin>=1.3.0",
-    "mkdocs-include-markdown-plugin>=7.1.2",
+    "mkdocs-bibtex>=4.2.3",
+    "mkdocs-git-revision-date-localized-plugin>=1.4.5",
+    "mkdocs-include-markdown-plugin>=7.1.5",
     "mkdocs-jupyter>=0.25.1",
-    "mkdocs-material>=9.5.49",
+    "mkdocs-material>=9.6.9",
     "mkdocs-minify-plugin>=0.8.0",
-    "mkdocstrings[python]>=0.27.0",
+    "mkdocstrings[python]>=0.29.0",
 ]
 pandas = [
     "pandas>=2.2.3",
-    "pandas-stubs>=2.2.3.241126",
+    "pandas-stubs>=2.2.3.250308",
 ]
 dev = [
     "blacken-docs>=1.19.1",
-    "codespell>=2.3.0",
-    "hypothesis[numpy]>=6.123.17",
-    "basedpyright>=1.24.0",
-    "pytest>=8.3.4",
-    "pytest-doctestplus>=1.3.0",
-    "ruff>=0.9.1",
-    "sp-repo-review[cli]>=2024.8.19",
-    "tox>=4.23.2",
+    "codespell>=2.4.1",
+    "hypothesis[numpy]>=6.129.3",
+    "basedpyright>=1.28.1",
+    "pytest>=8.3.5",
+    "pytest-doctestplus>=1.4.0",
+    "ruff>=0.11.0",
+    "sp-repo-review[cli]>=2025.1.22",
 ]
 
 [tool.uv]

tests/test_multivariate.py

@@ -33,38 +33,50 @@
 
 
 @given(r=st_r, n=st_n, trim=st_trim)
-def test_l_comoment_empty(r: int, n: int, trim: tuple[int, int]):
+def test_l_comoment_empty(r: int, n: int, trim: tuple[int, int]) -> None:
     l_00 = lmo.l_comoment(np.empty((0, n)), r, trim)
 
     assert l_00.shape == (0, 0)
 
 
 @given(a=st_a, trim=st_trim)
-def test_l_comoment_zero(a: npt.NDArray[np.float64], trim: tuple[int, int]):
+def test_l_comoment_zero(a: npt.NDArray[np.float64], trim: tuple[int, int]) -> None:
     l_aa = lmo.l_comoment(a, 0, trim)
 
     assert l_aa.shape == (len(a), len(a))
     assert np.array_equal(l_aa, np.eye(len(a)))
 
 
 @given(a=st_a, r=st_r, trim=st_trim)
-def test_tl_comoment_rowvar(a: npt.NDArray[np.float64], r: int, trim: tuple[int, int]):
+def test_tl_comoment_rowvar(
+    a: npt.NDArray[np.float64],
+    r: int,
+    trim: tuple[int, int],
+) -> None:
     l_aa = lmo.l_comoment(a, r, trim)
     l_aa_t = lmo.l_comoment(a.T, r, trim, rowvar=False)
 
     assert np.array_equal(l_aa, l_aa_t)
 
 
 @given(a=st_a, r=st_r, trim=st_trim)
-def test_tl_comoment_diag(a: npt.NDArray[np.float64], r: int, trim: tuple[int, int]):
+def test_tl_comoment_diag(
+    a: npt.NDArray[np.float64],
+    r: int,
+    trim: tuple[int, int],
+) -> None:
     l_a = lmo.l_moment(a, r, trim, axis=1)
     L_aa = lmo.l_comoment(a, r, trim)
 
     assert np.allclose(L_aa.diagonal(), l_a)
 
 
 @given(a=st_a, r=st_r, trim=st_trim)
-def test_l_comoment_rowwise(a: npt.NDArray[np.float64], r: int, trim: tuple[int, int]):
+def test_l_comoment_rowwise(
+    a: npt.NDArray[np.float64],
+    r: int,
+    trim: tuple[int, int],
+) -> None:
     l_a = lmo.l_moment(a, r, trim, axis=1)
 
     def func(a_m: npt.NDArray[np.float64]):
@@ -77,17 +89,17 @@ def func(a_m: npt.NDArray[np.float64]):
 
 
 @given(a=st_a)
-def test_l_coloc_mean(a: npt.NDArray[np.float64]):
+def test_l_coloc_mean(a: npt.NDArray[np.float64]) -> None:
     m_a = a.mean(1)
     l_aa = lmo.l_coloc(a)
     l_a0 = l_aa[:, 0]
 
     assert np.allclose(l_a0, m_a, atol=1e-3, rtol=1e-3)
 
 
-@settings(deadline=timedelta(seconds=1))
+@settings(deadline=timedelta(seconds=1))  # pyright: ignore[reportArgumentType]
 @given(a=st_a_unique)
-def test_l_corr_standard(a: npt.NDArray[np.float64]):
+def test_l_corr_standard(a: npt.NDArray[np.float64]) -> None:
     r_aa = lmo.l_corr(a)
 
     assert np.all(r_aa.diagonal() == 1)

tests/test_theoretical.py

@@ -99,7 +99,7 @@ def uniform_qdf(p: float) -> float:
 
 # @given(a=st.floats(0.1, 10))
 @pytest.mark.parametrize("a", [0.1, 10])
-def test_lm_expon(a: float):
+def test_lm_expon(a: float) -> None:
     l_stats = np.array([a, a / 2, 1 / 3, 1 / 6])
     r = np.arange(5)
 
@@ -117,7 +117,7 @@ def test_lm_expon(a: float):
     assert_allclose(l_stats_cdf, l_stats, rtol=5e-7)
 
 
-def test_lm_normal():
+def test_lm_normal() -> None:
     from statistics import NormalDist
 
     mu, sigma = 100, 15
@@ -139,7 +139,7 @@ def test_lm_normal():
     assert_allclose(l_qdf, lr[1:])
 
 
-def test_tlm_normal():
+def test_tlm_normal() -> None:
     from statistics import NormalDist
 
     mu, sigma = 100, 15
@@ -165,7 +165,7 @@ def test_tlm_normal():
     assert_allclose(tl_qdf, tl[1:])
 
 
-def test_tlm_cauchy():
+def test_tlm_cauchy() -> None:
     r = [1, 2, 3, 4]
 
     z3 = zeta(3)
@@ -183,7 +183,7 @@ def test_tlm_cauchy():
 
 
 @given(a=st.floats(0.1, 10))
-def test_llm_expon(a: float):
+def test_llm_expon(a: float) -> None:
     r = [1, 2, 3, 4]
     lr = a * np.array([1, 1 / 2, 1 / 9, 1 / 24]) / 2
 
@@ -201,7 +201,7 @@ def test_llm_expon(a: float):
     assert_allclose(l_qdf, lr[1:])
 
 
-def test_lm_cov_uniform():
+def test_lm_cov_uniform() -> None:
     k4 = (
         np.array([
             [1 / 2, 0, -1 / 10, 0],
@@ -216,7 +216,7 @@ def test_lm_cov_uniform():
     assert_allclose(k4, k4_hat)
 
 
-def test_lm_cov_expon():
+def test_lm_cov_expon() -> None:
     k3 = np.array([
         [1, 1 / 2, 1 / 6],
         [1 / 2, 1 / 3, 1 / 6],
@@ -227,7 +227,7 @@ def test_lm_cov_expon():
     assert_allclose(k3, k3_hat)
 
 
-def test_llm_cov_expon():
+def test_llm_cov_expon() -> None:
     k3 = np.array([
         [1 / 3, 1 / 8, 0],
         [1 / 8, 3 / 40, 1 / 60],
@@ -239,7 +239,7 @@ def test_llm_cov_expon():
 
 
 @np.errstate(over="ignore", under="ignore")
-def test_lm_cov_loc_scale_invariant():
+def test_lm_cov_loc_scale_invariant() -> None:
     k4_hat = l_moment_cov_from_cdf(gumbel_cdf, 4, trim=(0, 1))
     k4_hat_r = l_moment_cov_from_cdf(
         functools.partial(gumbel_cdf, loc=5, scale=3),
@@ -249,7 +249,7 @@ def test_lm_cov_loc_scale_invariant():
     assert_allclose(k4_hat, k4_hat_r / 9)
 
 
-def test_ls_cov_uniform():
+def test_ls_cov_uniform() -> None:
     k4 = np.array([
         [1 / 12, 0, -1 / 10, 0],
         [0, 1 / 180, 0, -1 / 70],
@@ -261,7 +261,7 @@ def test_ls_cov_uniform():
     assert_allclose(k4, k4_hat)
 
 
-@settings(deadline=1_000)
+@settings(deadline=1_000)  # pyright: ignore[reportArgumentType]
 @given(
     ppf=st.one_of(
         *map(st.just, [uniform_ppf, norm_ppf, gumbel_ppf, rayleigh_ppf, expon_ppf])
@@ -271,7 +271,7 @@ def test_ls_cov_uniform():
 def test_ppf_from_l_moments_identity(
     ppf: "Callable[[float], float]",
     trim: tuple[int, int] | int,
-):
+) -> None:
     rmax = 8
     r = np.mgrid[1 : rmax + 1]
     l_r = l_moment_from_ppf(ppf, r, trim)
@@ -285,7 +285,7 @@ def test_ppf_from_l_moments_identity(
     assert_allclose(l_0_hat, l_0)
 
 
-@settings(deadline=1_000)
+@settings(deadline=1_000)  # pyright: ignore[reportArgumentType]
 @given(
     qdf=st.one_of(
         *map(st.just, [uniform_qdf, norm_qdf, gumbel_qdf, rayleigh_qdf, expon_qdf])
@@ -295,7 +295,7 @@ def test_ppf_from_l_moments_identity(
 def test_qdf_from_l_moments_identity(
     qdf: "Callable[[float], float]",
     trim: tuple[int, int] | int,
-):
+) -> None:
     rmax = 8
     r = np.mgrid[2 : rmax + 1]
     l_r = l_moment_from_qdf(qdf, r, trim)