gh-124: use cosmology.api over the cosmology package

glass/galaxies.py

@@ -33,7 +33,7 @@
 from glass.core.array import broadcast_leading_axes, cumtrapz
 
 if typing.TYPE_CHECKING:
-    from cosmology import Cosmology
+    from cosmology.api import StandardCosmology
 
     from glass.shells import RadialWindow
 
@@ -300,7 +300,7 @@ def kappa_ia_nla(  # noqa: PLR0913
     delta: npt.NDArray[np.float64],
     zeff: float,
     a_ia: float,
-    cosmo: Cosmology,
+    cosmo: StandardCosmology,
     *,
     z0: float = 0.0,
     eta: float = 0.0,

glass/lensing.py

@@ -40,7 +40,7 @@
 if typing.TYPE_CHECKING:
     import collections.abc
 
-    from cosmology import Cosmology
+    from cosmology.api import StandardCosmology
 
     from glass.shells import RadialWindow
 
@@ -269,7 +269,7 @@ def shear_from_convergence(
 class MultiPlaneConvergence:
     """Compute convergence fields iteratively from multiple matter planes."""
 
-    def __init__(self, cosmo: Cosmology) -> None:
+    def __init__(self, cosmo: StandardCosmology) -> None:
         """Create a new instance to iteratively compute the convergence."""
         self.cosmo = cosmo
 
@@ -333,9 +333,9 @@ def add_plane(
         t = r13 / r12
 
         # lensing weight of mass plane to be added
-        f = 3 * self.cosmo.omega_m / 2
+        f = 3 * self.cosmo.Omega_m0 / 2
         f *= x2 * self.r23
-        f *= (1 + self.z2) / self.cosmo.ef(self.z2)
+        f *= (1 + self.z2) / self.cosmo.H_over_H0(self.z2)
         f *= w2
 
         # create kappa planes on first iteration
@@ -377,7 +377,7 @@ def wlens(self) -> float:
 
 def multi_plane_matrix(
     shells: collections.abc.Sequence[RadialWindow],
-    cosmo: Cosmology,
+    cosmo: StandardCosmology,
 ) -> npt.NDArray[np.float64]:
     """Compute the matrix of lensing contributions from each shell."""
     mpc = MultiPlaneConvergence(cosmo)
@@ -391,7 +391,7 @@ def multi_plane_matrix(
 def multi_plane_weights(
     weights: npt.NDArray[np.float64],
     shells: collections.abc.Sequence[RadialWindow],
-    cosmo: Cosmology,
+    cosmo: StandardCosmology,
 ) -> npt.NDArray[np.float64]:
     """
     Compute effective weights for multi-plane convergence.

glass/shells.py

@@ -55,34 +55,34 @@
 from glass.core.array import ndinterp
 
 if typing.TYPE_CHECKING:
-    from cosmology import Cosmology
+    from cosmology.api import StandardCosmology
 
 ArrayLike1D = typing.Union[collections.abc.Sequence[float], npt.NDArray[np.float64]]
 WeightFunc = typing.Callable[[ArrayLike1D], npt.NDArray[np.float64]]
 
 
 def distance_weight(
     z: npt.NDArray[np.float64],
-    cosmo: Cosmology,
+    cosmo: StandardCosmology,
 ) -> npt.NDArray[np.float64]:
     """Uniform weight in comoving distance."""
-    return 1 / cosmo.ef(z)  # type: ignore[no-any-return]
+    return 1 / cosmo.H_over_H0(z)  # type: ignore[no-any-return]
 
 
 def volume_weight(
     z: npt.NDArray[np.float64],
-    cosmo: Cosmology,
+    cosmo: StandardCosmology,
 ) -> npt.NDArray[np.float64]:
     """Uniform weight in comoving volume."""
-    return cosmo.xm(z) ** 2 / cosmo.ef(z)  # type: ignore[no-any-return]
+    return cosmo.xm(z) ** 2 / cosmo.H_over_H0(z)  # type: ignore[no-any-return]
 
 
 def density_weight(
     z: npt.NDArray[np.float64],
-    cosmo: Cosmology,
+    cosmo: StandardCosmology,
 ) -> npt.NDArray[np.float64]:
     """Uniform weight in matter density."""
-    return cosmo.rho_m_z(z) * cosmo.xm(z) ** 2 / cosmo.ef(z)  # type: ignore[no-any-return]
+    return cosmo.rho_m_z(z) * cosmo.xm(z) ** 2 / cosmo.H_over_H0(z)  # type: ignore[no-any-return]
 
 
 class RadialWindow(typing.NamedTuple):
@@ -650,15 +650,15 @@ def redshift_grid(
 
 
 def distance_grid(
-    cosmo: Cosmology,
+    cosmo: StandardCosmology,
     zmin: float,
     zmax: float,
     *,
     dx: float | None = None,
     num: int | None = None,
 ) -> npt.NDArray[np.float64]:
     """Redshift grid with uniform spacing in comoving distance."""
-    xmin, xmax = cosmo.dc(zmin), cosmo.dc(zmax)
+    xmin, xmax = cosmo.comoving_distance(zmin), cosmo.comoving_distance(zmax)
     if dx is not None and num is None:
         x = np.arange(xmin, np.nextafter(xmax + dx, xmax), dx)
     elif dx is None and num is not None:

pyproject.toml

@@ -21,7 +21,7 @@ classifiers = [
     "Typing :: Typed",
 ]
 dependencies = [
-    "cosmology>=2022.10.9",
+    "cosmology.api>=0.1.0",
     "gaussiancl>=2022.10.21",
     "healpix>=2022.11.1",
     "healpy>=1.15.0",
@@ -50,6 +50,7 @@ docs = [
 ]
 examples = [
     "camb",
+    "cosmology",
     "glass.ext.camb",
     "jupyter",
     "matplotlib",
@@ -156,6 +157,7 @@ lint.isort = {known-first-party = [
 ], sections = {"cosmo" = [
     "camb",
     "cosmology",
+    "cosmology.api",
 ]}}
 lint.per-file-ignores = {"__init__.py" = [
     "F401", # unused-import

tests/test_lensing.py

@@ -16,7 +16,7 @@
 from glass.shells import RadialWindow
 
 if typing.TYPE_CHECKING:
-    from cosmology import Cosmology
+    from cosmology.api import StandardCosmology
 
 
 @pytest.fixture
@@ -31,14 +31,14 @@ def shells() -> list[RadialWindow]:
 
 
 @pytest.fixture
-def cosmo() -> Cosmology:
+def cosmo() -> StandardCosmology:
     class MockCosmology:
         @property
-        def omega_m(self) -> float:
+        def Omega_m0(self) -> float:  # noqa: N802
             return 0.3
 
-        def ef(self, z: npt.NDArray[np.float64]) -> npt.NDArray[np.float64]:
-            return (self.omega_m * (1 + z) ** 3 + 1 - self.omega_m) ** 0.5
+        def H_over_H0(self, z: npt.NDArray[np.float64]) -> npt.NDArray[np.float64]:  # noqa: N802
+            return (self.Omega_m0 * (1 + z) ** 3 + 1 - self.Omega_m0) ** 0.5
 
         def xm(
             self,
@@ -97,7 +97,7 @@ def test_deflect_many(rng: np.random.Generator) -> None:
 
 def test_multi_plane_matrix(
     shells: list[RadialWindow],
-    cosmo: Cosmology,
+    cosmo: StandardCosmology,
     rng: np.random.Generator,
 ) -> None:
     mat = multi_plane_matrix(shells, cosmo)
@@ -119,7 +119,7 @@ def test_multi_plane_matrix(
 
 def test_multi_plane_weights(
     shells: list[RadialWindow],
-    cosmo: Cosmology,
+    cosmo: StandardCosmology,
     rng: np.random.Generator,
 ) -> None:
     w_in = np.eye(len(shells))