Merge branch 'main' into paddy/issue-124

.github/workflows/pull_request.yml

@@ -12,11 +12,12 @@ on:
 
 jobs:
   check-pr-title:
-    if: github.actor != 'pre-commit-ci[bot]'
+    if:
+      github.actor != 'pre-commit-ci[bot]' && github.actor != 'dependabot[bot]'
     runs-on: ubuntu-latest
     steps:
       - name: Enfore PR title format
-        uses: thehanimo/[email protected].2
+        uses: thehanimo/[email protected].3
         with:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
           pass_on_octokit_error: false

.github/workflows/release.yml

@@ -2,14 +2,10 @@
 name: Release
 
 on:
-  workflow_dispatch:
-    inputs:
-      target:
-        default: testpypi
-        description: Deployment target. Can be pypi or testpypi.
   release:
     types:
       - published
+  workflow_dispatch:
 
 jobs:
   dist:
@@ -55,8 +51,16 @@ jobs:
     needs: dist
     runs-on: ubuntu-latest
     environment:
-      name: publish
-      url: https://pypi.org/p/glass
+      name: >-
+        ${{ (github.event_name == 'release' &&
+         github.event.action == 'published') &&
+         'publish' ||
+         'test-publish' }}
+      url: >-
+        ${{ (github.event_name == 'release' &&
+         github.event.action == 'published') &&
+         'https://pypi.org/project/glass' ||
+         'https://test.pypi.org/project/glass' }}
     permissions:
       id-token: write
     steps:
@@ -71,12 +75,11 @@ jobs:
 
       - name: Publish to PyPI
         if: >-
-          github.event.inputs.target == 'pypi' || (github.event_name ==
-          'release' && github.event.action == 'published')
+          github.event_name == 'release' && github.event.action == 'published'
         uses: pypa/gh-action-pypi-publish@release/v1
 
       - name: Publish to TestPyPI
-        if: github.event.inputs.target == 'testpypi'
+        if: github.event_name == 'workflow_dispatch'
         uses: pypa/gh-action-pypi-publish@release/v1
         with:
           repository-url: https://test.pypi.org/legacy/

.pre-commit-config.yaml

@@ -33,7 +33,7 @@ repos:
         args:
           - --strict
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.7.4
+    rev: v0.8.0
     hooks:
       - id: ruff
       - id: ruff-format
@@ -44,15 +44,15 @@ repos:
         additional_dependencies:
           - black
   - repo: https://github.com/pappasam/toml-sort
-    rev: v0.24.1
+    rev: v0.24.2
     hooks:
       - id: toml-sort-fix
   - repo: https://github.com/rbubley/mirrors-prettier
     rev: v3.3.3
     hooks:
       - id: prettier
   - repo: https://github.com/igorshubovych/markdownlint-cli
-    rev: v0.42.0
+    rev: v0.43.0
     hooks:
       - id: markdownlint-fix
         args:

glass/__init__.py

@@ -1,5 +1,60 @@
 """GLASS package."""
 
+__all__ = [
+    "MultiPlaneConvergence",
+    "RadialWindow",
+    "cls2cov",
+    "combine",
+    "cubic_windows",
+    "deflect",
+    "density_weight",
+    "discretized_cls",
+    "distance_grid",
+    "distance_weight",
+    "effective_bias",
+    "effective_cls",
+    "ellipticity_gaussian",
+    "ellipticity_intnorm",
+    "ellipticity_ryden04",
+    "equal_dens_zbins",
+    "fixed_zbins",
+    "from_convergence",
+    "galaxy_shear",
+    "gaussian_nz",
+    "gaussian_phz",
+    "generate_gaussian",
+    "generate_lognormal",
+    "getcl",
+    "iternorm",
+    "linear_bias",
+    "linear_windows",
+    "load_cls",
+    "loglinear_bias",
+    "lognormal_gls",
+    "multalm",
+    "multi_plane_matrix",
+    "multi_plane_weights",
+    "partition",
+    "position_weights",
+    "positions_from_delta",
+    "redshift_grid",
+    "redshifts",
+    "redshifts_from_nz",
+    "restrict",
+    "save_cls",
+    "shear_from_convergence",
+    "smail_nz",
+    "tomo_nz_gausserr",
+    "tophat_windows",
+    "transform_cls",
+    "triaxial_axis_ratio",
+    "uniform_positions",
+    "vmap_galactic_ecliptic",
+    "volume_weight",
+    "write_catalog",
+]
+
+
 import contextlib
 from importlib.metadata import PackageNotFoundError
 

glass/core/array.py

@@ -131,7 +131,7 @@ def ndinterp(  # noqa: PLR0913
     )
 
 
-def trapz_product(
+def trapezoid_product(
     f: tuple[npt.NDArray[np.float64], npt.NDArray[np.float64]],
     *ff: tuple[
         npt.NDArray[np.float64],
@@ -169,7 +169,7 @@ def trapz_product(
     return np.trapezoid(y, x, axis=axis)  # type: ignore[no-any-return]
 
 
-def cumtrapz(
+def cumulative_trapezoid(
     f: npt.NDArray[np.int_] | npt.NDArray[np.float64],
     x: npt.NDArray[np.int_] | npt.NDArray[np.float64],
     dtype: npt.DTypeLike | None = None,

glass/galaxies.py

@@ -26,7 +26,7 @@
 import numpy as np
 import numpy.typing as npt
 
-from glass.core.array import broadcast_leading_axes, cumtrapz
+from glass.core.array import broadcast_leading_axes, cumulative_trapezoid
 
 if typing.TYPE_CHECKING:
     from glass.shells import RadialWindow
@@ -127,7 +127,7 @@ def redshifts_from_nz(
     # go through extra dimensions; also works if dims is empty
     for k in np.ndindex(dims):
         # compute the CDF of each galaxy population
-        cdf = cumtrapz(nz_out[k], z_out[k], dtype=float)
+        cdf = cumulative_trapezoid(nz_out[k], z_out[k], dtype=float)
         cdf /= cdf[-1]
 
         # sample redshifts and store result

glass/lensing.py

@@ -45,6 +45,117 @@
     from glass.shells import RadialWindow
 
 
+@typing.overload
+def from_convergence(
+    kappa: npt.NDArray[np.float64],
+    lmax: int | None = None,
+    *,
+    potential: typing.Literal[True] = True,
+    deflection: typing.Literal[False] = False,
+    shear: typing.Literal[False] = False,
+    discretized: bool = True,
+) -> tuple[npt.NDArray[np.float64]]:
+    # returns psi
+    ...
+
+
+@typing.overload
+def from_convergence(
+    kappa: npt.NDArray[np.float64],
+    lmax: int | None = None,
+    *,
+    potential: typing.Literal[False] = False,
+    deflection: typing.Literal[True] = True,
+    shear: typing.Literal[False] = False,
+    discretized: bool = True,
+) -> tuple[npt.NDArray[np.complex128]]:
+    # returns alpha
+    ...
+
+
+@typing.overload
+def from_convergence(
+    kappa: npt.NDArray[np.float64],
+    lmax: int | None = None,
+    *,
+    potential: typing.Literal[False] = False,
+    deflection: typing.Literal[False] = False,
+    shear: typing.Literal[True] = True,
+    discretized: bool = True,
+) -> tuple[npt.NDArray[np.complex128]]:
+    # returns gamma
+    ...
+
+
+@typing.overload
+def from_convergence(
+    kappa: npt.NDArray[np.float64],
+    lmax: int | None = None,
+    *,
+    potential: typing.Literal[True] = True,
+    deflection: typing.Literal[True] = True,
+    shear: typing.Literal[False] = False,
+    discretized: bool = True,
+) -> tuple[
+    npt.NDArray[np.float64],
+    npt.NDArray[np.complex128],
+]:
+    # returns psi, alpha
+    ...
+
+
+@typing.overload
+def from_convergence(
+    kappa: npt.NDArray[np.float64],
+    lmax: int | None = None,
+    *,
+    potential: typing.Literal[True] = True,
+    deflection: typing.Literal[False] = False,
+    shear: typing.Literal[True] = True,
+    discretized: bool = True,
+) -> tuple[
+    npt.NDArray[np.float64],
+    npt.NDArray[np.complex128],
+]:
+    # returns psi, gamma
+    ...
+
+
+@typing.overload
+def from_convergence(
+    kappa: npt.NDArray[np.float64],
+    lmax: int | None = None,
+    *,
+    potential: typing.Literal[False] = False,
+    deflection: typing.Literal[True] = True,
+    shear: typing.Literal[True] = True,
+    discretized: bool = True,
+) -> tuple[
+    npt.NDArray[np.complex128],
+    npt.NDArray[np.complex128],
+]:
+    # returns alpha, gamma
+    ...
+
+
+@typing.overload
+def from_convergence(
+    kappa: npt.NDArray[np.float64],
+    lmax: int | None = None,
+    *,
+    potential: typing.Literal[True] = True,
+    deflection: typing.Literal[True] = True,
+    shear: typing.Literal[True] = True,
+    discretized: bool = True,
+) -> tuple[
+    npt.NDArray[np.float64],
+    npt.NDArray[np.complex128],
+    npt.NDArray[np.complex128],
+]:
+    # returns psi, alpha, gamma
+    ...
+
+
 def from_convergence(  # noqa: PLR0913
     kappa: npt.NDArray[np.float64],
     lmax: int | None = None,
@@ -53,7 +164,7 @@ def from_convergence(  # noqa: PLR0913
     deflection: bool = False,
     shear: bool = False,
     discretized: bool = True,
-) -> tuple[npt.NDArray[np.float64], ...]:
+) -> tuple[npt.NDArray[np.float64] | npt.NDArray[np.complex128], ...]:
     r"""
     Compute other weak lensing maps from the convergence.
 
@@ -175,7 +286,7 @@ def from_convergence(  # noqa: PLR0913
     ell = np.arange(lmax + 1)
 
     # this tuple will be returned
-    results: tuple[npt.NDArray[np.float64], ...] = ()
+    results: tuple[npt.NDArray[np.float64] | npt.NDArray[np.complex128], ...] = ()
 
     # convert convergence to potential
     fl = np.divide(-2, ell * (ell + 1), where=(ell > 0), out=np.zeros(lmax + 1))

glass/observations.py

@@ -34,7 +34,7 @@
 import numpy as np
 import numpy.typing as npt
 
-from glass.core.array import cumtrapz
+from glass.core.array import cumulative_trapezoid
 
 
 def vmap_galactic_ecliptic(
@@ -89,7 +89,7 @@ def gaussian_nz(
     mean: float | npt.NDArray[np.float64],
     sigma: float | npt.NDArray[np.float64],
     *,
-    norm: npt.NDArray[np.float64] | None = None,
+    norm: float | npt.NDArray[np.float64] | None = None,
 ) -> npt.NDArray[np.float64]:
     """
     Gaussian redshift distribution.
@@ -130,11 +130,11 @@ def gaussian_nz(
 
 def smail_nz(
     z: npt.NDArray[np.float64],
-    z_mode: npt.NDArray[np.float64],
-    alpha: npt.NDArray[np.float64],
-    beta: npt.NDArray[np.float64],
+    z_mode: float | npt.NDArray[np.float64],
+    alpha: float | npt.NDArray[np.float64],
+    beta: float | npt.NDArray[np.float64],
     *,
-    norm: npt.NDArray[np.float64] | None = None,
+    norm: float | npt.NDArray[np.float64] | None = None,
 ) -> npt.NDArray[np.float64]:
     r"""
     Redshift distribution following Smail et al. (1994).
@@ -225,8 +225,8 @@ def fixed_zbins(
     """
     if nbins is not None and dz is None:
         zbinedges = np.linspace(zmin, zmax, nbins + 1)
-    if nbins is None and dz is not None:
-        zbinedges = np.arange(zmin, zmax, dz)
+    elif nbins is None and dz is not None:
+        zbinedges = np.arange(zmin, np.nextafter(zmax + dz, zmax), dz)
     else:
         msg = "exactly one of nbins and dz must be given"
         raise ValueError(msg)
@@ -263,7 +263,7 @@ def equal_dens_zbins(
     # first compute the cumulative integral (by trapezoidal rule)
     # then normalise: the first z is at CDF = 0, the last z at CDF = 1
     # interpolate to find the z values at CDF = i/nbins for i = 0, ..., nbins
-    cuml_nz = cumtrapz(nz, z)
+    cuml_nz = cumulative_trapezoid(nz, z)
     cuml_nz /= cuml_nz[[-1]]
     zbinedges = np.interp(np.linspace(0, 1, nbins + 1), cuml_nz, z)
 

glass/points.py

@@ -37,7 +37,7 @@
 import numpy as np
 import numpy.typing as npt
 
-from glass.core.array import broadcast_first, broadcast_leading_axes, trapz_product
+from glass.core.array import broadcast_first, broadcast_leading_axes, trapezoid_product
 
 if typing.TYPE_CHECKING:
     import collections.abc
@@ -85,7 +85,7 @@ def effective_bias(
 
     """
     norm = np.trapezoid(w.wa, w.za)
-    return trapz_product((z, bz), (w.za, w.wa)) / norm
+    return trapezoid_product((z, bz), (w.za, w.wa)) / norm
 
 
 def linear_bias(