gh-163: drop Python 3.9 & NumPy < 2.1.1 support (#391)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: paddyroddy

.github/workflows/test.yml

@@ -25,7 +25,6 @@ jobs:
     strategy:
       matrix:
         python-version:
-          - "3.9"
           - "3.10"
           - "3.11"
           - "3.12"
@@ -79,7 +78,7 @@ jobs:
       - name: Coveralls finished
         uses: coverallsapp/github-action@v2
         with:
-          carryforward: run-3.9,run-3.10,run-3.11,run-3.12,run-3.13
+          carryforward: run-3.10,run-3.11,run-3.12,run-3.13
           parallel-finished: true
 
   build:

examples/1-basic/photoz.ipynb

@@ -165,7 +165,7 @@
     "tomo_nz = glass.tomo_nz_gausserr(z, dndz, phz_sigma_0, zbins)\n",
     "tomo_nz *= ARCMIN2_SPHERE * (z[-1] - z[0]) / 40\n",
     "\n",
-    "for (z1, z2), nz in zip(zbins, tomo_nz):\n",
+    "for (z1, z2), nz in zip(zbins, tomo_nz, strict=False):\n",
     "    plt.hist(\n",
     "        ztrue[(z1 <= zphot) & (zphot < z2)],\n",
     "        bins=40,\n",

glass/core/array.py

@@ -81,7 +81,9 @@ def broadcast_leading_axes(
         shapes.append(s[:i])
         trails.append(s[i:])
     dims = np.broadcast_shapes(*shapes)
-    arrs = (np.broadcast_to(a, dims + t) for (a, _), t in zip(args, trails))
+    arrs = (
+        np.broadcast_to(a, dims + t) for (a, _), t in zip(args, trails, strict=False)
+    )
     return (dims, *arrs)
 
 
@@ -164,11 +166,7 @@ def trapz_product(
     y = np.interp(x, *f)
     for f_ in ff:
         y *= np.interp(x, *f_)
-    return np.trapz(  # type: ignore[attr-defined, no-any-return]
-        y,
-        x,
-        axis=axis,
-    )
+    return np.trapezoid(y, x, axis=axis)  # type: ignore[no-any-return]
 
 
 def cumtrapz(

glass/fields.py

@@ -37,7 +37,7 @@
 from gaussiancl import gaussiancl
 
 Cls = collections.abc.Sequence[
-    typing.Union[npt.NDArray[np.float64], collections.abc.Sequence[float]]
+    npt.NDArray[np.float64] | collections.abc.Sequence[float]
 ]
 
 

glass/lensing.py

@@ -324,17 +324,7 @@ def add_window(self, delta: npt.NDArray[np.float64], w: RadialWindow) -> None:
 
         """
         zsrc = w.zeff
-        lens_weight = float(
-            np.trapz(  # type: ignore[attr-defined]
-                w.wa,
-                w.za,
-            )
-            / np.interp(
-                zsrc,
-                w.za,
-                w.wa,
-            )
-        )
+        lens_weight = float(np.trapezoid(w.wa, w.za) / np.interp(zsrc, w.za, w.wa))
 
         self.add_plane(delta, zsrc, lens_weight)
 

glass/observations.py

@@ -27,6 +27,7 @@
 
 from __future__ import annotations
 
+import itertools
 import math
 
 import healpy as hp
@@ -119,11 +120,7 @@ def gaussian_nz(
     sigma = np.reshape(sigma, np.shape(sigma) + (1,) * np.ndim(z))
 
     nz = np.exp(-(((z - mean) / sigma) ** 2) / 2)
-    nz /= np.trapz(  # type: ignore[attr-defined]
-        nz,
-        z,
-        axis=-1,
-    )[..., np.newaxis]
+    nz /= np.trapezoid(nz, z, axis=-1)[..., np.newaxis]
 
     if norm is not None:
         nz *= norm
@@ -184,11 +181,7 @@ def smail_nz(
     beta = np.asanyarray(beta)[..., np.newaxis]
 
     pz = z**alpha * np.exp(-alpha / beta * (z / z_mode) ** beta)
-    pz /= np.trapz(  # type: ignore[attr-defined]
-        pz,
-        z,
-        axis=-1,
-    )[..., np.newaxis]
+    pz /= np.trapezoid(pz, z, axis=-1)[..., np.newaxis]
 
     if norm is not None:
         pz *= norm
@@ -238,7 +231,7 @@ def fixed_zbins(
         msg = "exactly one of nbins and dz must be given"
         raise ValueError(msg)
 
-    return list(zip(zbinedges, zbinedges[1:]))
+    return list(itertools.pairwise(zbinedges))
 
 
 def equal_dens_zbins(
@@ -274,7 +267,7 @@ def equal_dens_zbins(
     cuml_nz /= cuml_nz[[-1]]
     zbinedges = np.interp(np.linspace(0, 1, nbins + 1), cuml_nz, z)
 
-    return list(zip(zbinedges, zbinedges[1:]))
+    return list(itertools.pairwise(zbinedges))
 
 
 def tomo_nz_gausserr(

glass/points.py

@@ -84,11 +84,8 @@ def effective_bias(
         \;.
 
     """
-    norm = np.trapz(  # type: ignore[attr-defined]
-        w.wa,
-        w.za,
-    )
-    return trapz_product((z, bz), (w.za, w.wa)) / norm  # type: ignore[no-any-return]
+    norm = np.trapezoid(w.wa, w.za)
+    return trapz_product((z, bz), (w.za, w.wa)) / norm
 
 
 def linear_bias(

glass/shells.py

@@ -46,6 +46,7 @@
 from __future__ import annotations
 
 import collections.abc
+import itertools
 import typing
 import warnings
 
@@ -58,7 +59,7 @@
 if typing.TYPE_CHECKING:
     from cosmology import Cosmology
 
-ArrayLike1D = typing.Union[collections.abc.Sequence[float], npt.NDArray[np.float64]]
+ArrayLike1D = collections.abc.Sequence[float] | npt.NDArray[np.float64]
 WeightFunc = typing.Callable[[ArrayLike1D], npt.NDArray[np.float64]]
 
 
@@ -232,17 +233,11 @@ def tophat_windows(
     wht: WeightFunc
     wht = weight if weight is not None else np.ones_like
     ws = []
-    for zmin, zmax in zip(zbins, zbins[1:]):
+    for zmin, zmax in itertools.pairwise(zbins):
         n = max(round((zmax - zmin) / dz), 2)
         z = np.linspace(zmin, zmax, n)
         w = wht(z)
-        zeff = np.trapz(  # type: ignore[attr-defined]
-            w * z,
-            z,
-        ) / np.trapz(  # type: ignore[attr-defined]
-            w,
-            z,
-        )
+        zeff = np.trapezoid(w * z, z) / np.trapezoid(w, z)
         ws.append(RadialWindow(z, w, zeff))
     return ws
 
@@ -296,7 +291,7 @@ def linear_windows(
         warnings.warn("first triangular window does not start at z=0", stacklevel=2)
 
     ws = []
-    for zmin, zmid, zmax in zip(zgrid, zgrid[1:], zgrid[2:]):
+    for zmin, zmid, zmax in zip(zgrid, zgrid[1:], zgrid[2:], strict=False):
         n = max(round((zmid - zmin) / dz), 2) - 1
         m = max(round((zmax - zmid) / dz), 2)
         z = np.concatenate(
@@ -361,7 +356,7 @@ def cubic_windows(
         warnings.warn("first cubic spline window does not start at z=0", stacklevel=2)
 
     ws = []
-    for zmin, zmid, zmax in zip(zgrid, zgrid[1:], zgrid[2:]):
+    for zmin, zmid, zmax in zip(zgrid, zgrid[1:], zgrid[2:], strict=False):
         n = max(round((zmid - zmin) / dz), 2) - 1
         m = max(round((zmax - zmid) / dz), 2)
         z = np.concatenate(
@@ -580,11 +575,7 @@ def partition_lstsq(
 
     # create the window function matrix
     a = np.array([np.interp(zp, za, wa, left=0.0, right=0.0) for za, wa, _ in shells])
-    a /= np.trapz(  # type: ignore[attr-defined]
-        a,
-        zp,
-        axis=-1,
-    )[..., None]
+    a /= np.trapezoid(a, zp, axis=-1)[..., None]
     a = a * dz
 
     # create the target vector of distribution values
@@ -594,20 +585,7 @@ def partition_lstsq(
     # append a constraint for the integral
     mult = 1 / sumtol
     a = np.concatenate([a, mult * np.ones((len(shells), 1))], axis=-1)
-    b = np.concatenate(
-        [
-            b,
-            mult
-            * np.reshape(
-                np.trapz(  # type: ignore[attr-defined]
-                    fz,
-                    z,
-                ),
-                (*dims, 1),
-            ),
-        ],
-        axis=-1,
-    )
+    b = np.concatenate([b, mult * np.reshape(np.trapezoid(fz, z), (*dims, 1))], axis=-1)
 
     # now a is a matrix of shape (len(shells), len(zp) + 1)
     # and b is a matrix of shape (*dims, len(zp) + 1)
@@ -672,11 +650,7 @@ def partition_nnls(
             for za, wa, _ in shells
         ],
     )
-    a /= np.trapz(  # type: ignore[attr-defined]
-        a,
-        zp,
-        axis=-1,
-    )[..., None]
+    a /= np.trapezoid(a, zp, axis=-1)[..., None]
     a = a * dz
 
     # create the target vector of distribution values
@@ -686,20 +660,7 @@ def partition_nnls(
     # append a constraint for the integral
     mult = 1 / sumtol
     a = np.concatenate([a, mult * np.ones((len(shells), 1))], axis=-1)
-    b = np.concatenate(
-        [
-            b,
-            mult
-            * np.reshape(
-                np.trapz(  # type: ignore[attr-defined]
-                    fz,
-                    z,
-                ),
-                (*dims, 1),
-            ),
-        ],
-        axis=-1,
-    )
+    b = np.concatenate([b, mult * np.reshape(np.trapezoid(fz, z), (*dims, 1))], axis=-1)
 
     # now a is a matrix of shape (len(shells), len(zp) + 1)
     # and b is a matrix of shape (*dims, len(zp) + 1)
@@ -743,11 +704,7 @@ def partition_restrict(
     part = np.empty((len(shells),) + np.shape(fz)[:-1])
     for i, w in enumerate(shells):
         zr, fr = restrict(z, fz, w)
-        part[i] = np.trapz(  # type: ignore[attr-defined]
-            fr,
-            zr,
-            axis=-1,
-        )
+        part[i] = np.trapezoid(fr, zr, axis=-1)
     return part
 
 
@@ -879,15 +836,11 @@ def combine(
             * np.interp(
                 z,
                 shell.za,
-                shell.wa
-                / np.trapz(  # type: ignore[attr-defined]
-                    shell.wa,
-                    shell.za,
-                ),
+                shell.wa / np.trapezoid(shell.wa, shell.za),
                 left=0.0,
                 right=0.0,
             )
-            for shell, weight in zip(shells, weights)
+            for shell, weight in zip(shells, weights, strict=False)
         ],
         axis=0,
     )

noxfile.py

@@ -10,7 +10,12 @@
 nox.options.reuse_existing_virtualenvs = True
 nox.options.sessions = ["lint", "tests"]
 
-ALL_PYTHON = ["3.9", "3.10", "3.11", "3.12", "3.13"]
+ALL_PYTHON = [
+    "3.10",
+    "3.11",
+    "3.12",
+    "3.13",
+]
 
 
 @nox.session

pyproject.toml

@@ -11,7 +11,6 @@ classifiers = [
     "Operating System :: OS Independent",
     "Programming Language :: Python :: 3",
     "Programming Language :: Python :: 3 :: Only",
-    "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
@@ -25,7 +24,7 @@ dependencies = [
     "gaussiancl>=2022.10.21",
     "healpix>=2022.11.1",
     "healpy>=1.15.0",
-    "numpy>=1.22.0",
+    "numpy>=2.1.1",
 ]
 description = "Generator for Large Scale Structure"
 dynamic = [
@@ -36,7 +35,7 @@ maintainers = [
 ]
 name = "glass"
 readme = "README.md"
-requires-python = ">=3.9"
+requires-python = ">=3.10"
 license.file = "LICENSE"
 
 [project.optional-dependencies]
@@ -142,7 +141,6 @@ lint.ignore = [
     "D203", # one-blank-line-before-class
     "D212", # blank-line-before-class
     "ISC001", # single-line-implicit-string-concatenation (ruff-format recommended)
-    "NPY201", # TODO: numpy2-deprecation
     "RUF003", # ambiguous-unicode-character-comment
 ]
 lint.isort = {known-first-party = [

tests/test_lensing.py

@@ -109,7 +109,7 @@ def test_multi_plane_matrix(
 
     deltas = rng.random((len(shells), 10))
     kappas = []
-    for shell, delta in zip(shells, deltas):
+    for shell, delta in zip(shells, deltas, strict=False):
         convergence.add_window(delta, shell)
         if convergence.kappa is not None:
             kappas.append(convergence.kappa.copy())
@@ -133,7 +133,7 @@ def test_multi_plane_weights(
     deltas = rng.random((len(shells), 10))
     weights = rng.random((len(shells), 3))
     kappa = 0
-    for shell, delta, weight in zip(shells, deltas, weights):
+    for shell, delta, weight in zip(shells, deltas, weights, strict=False):
         convergence.add_window(delta, shell)
         kappa = kappa + weight[..., None] * convergence.kappa
     kappa /= weights.sum(axis=0)[..., None]