gh-384: rename all internal functions to trapezoid over trapz

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 cumtrapezoid(
     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, cumtrapezoid
 
 if typing.TYPE_CHECKING:
     from cosmology import Cosmology
@@ -129,7 +129,7 @@ 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 = cumtrapezoid(nz_out[k], z_out[k], dtype=float)
         cdf /= cdf[-1]
 
         # sample redshifts and store result

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 cumtrapezoid
 
 
 def vmap_galactic_ecliptic(
@@ -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 = cumtrapezoid(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(

tests/core/test_array.py

@@ -7,9 +7,9 @@
 from glass.core.array import (
     broadcast_first,
     broadcast_leading_axes,
-    cumtrapz,
+    cumtrapezoid,
     ndinterp,
-    trapz_product,
+    trapezoid_product,
 )
 
 # check if scipy is available for testing
@@ -144,20 +144,20 @@ def test_ndinterp() -> None:
     )
 
 
-def test_trapz_product() -> None:
+def test_trapezoid_product() -> None:
     x1 = np.linspace(0, 2, 100)
     f1 = np.full_like(x1, 2.0)
 
     x2 = np.linspace(1, 2, 10)
     f2 = np.full_like(x2, 0.5)
 
-    s = trapz_product((x1, f1), (x2, f2))
+    s = trapezoid_product((x1, f1), (x2, f2))
 
     np.testing.assert_allclose(s, 1.0)
 
 
 @pytest.mark.skipif(not HAVE_SCIPY, reason="test requires SciPy")
-def test_cumtrapz() -> None:
+def test_cumtrapezoid() -> None:
     from scipy.integrate import cumulative_trapezoid
 
     # 1D f and x
@@ -167,18 +167,18 @@ def test_cumtrapz() -> None:
 
     # default dtype (int - not supported by scipy)
 
-    glass_ct = cumtrapz(f, x)
+    glass_ct = cumtrapezoid(f, x)
     np.testing.assert_allclose(glass_ct, np.array([0, 1, 4, 7]))
 
     # explicit dtype (float)
 
-    glass_ct = cumtrapz(f, x, dtype=float)
+    glass_ct = cumtrapezoid(f, x, dtype=float)
     scipy_ct = cumulative_trapezoid(f, x, initial=0)
     np.testing.assert_allclose(glass_ct, scipy_ct)
 
     # explicit return array
 
-    result = cumtrapz(f, x, dtype=float, out=np.zeros((4,)))
+    result = cumtrapezoid(f, x, dtype=float, out=np.zeros((4,)))
     scipy_ct = cumulative_trapezoid(f, x, initial=0)
     np.testing.assert_allclose(result, scipy_ct)
 
@@ -189,17 +189,17 @@ def test_cumtrapz() -> None:
 
     # default dtype (int - not supported by scipy)
 
-    glass_ct = cumtrapz(f, x)
+    glass_ct = cumtrapezoid(f, x)
     np.testing.assert_allclose(glass_ct, np.array([[0, 2, 12, 31], [0, 2, 8, 17]]))
 
     # explicit dtype (float)
 
-    glass_ct = cumtrapz(f, x, dtype=float)
+    glass_ct = cumtrapezoid(f, x, dtype=float)
     scipy_ct = cumulative_trapezoid(f, x, initial=0)
     np.testing.assert_allclose(glass_ct, scipy_ct)
 
     # explicit return array
 
-    glass_ct = cumtrapz(f, x, dtype=float, out=np.zeros((2, 4)))
+    glass_ct = cumtrapezoid(f, x, dtype=float, out=np.zeros((2, 4)))
     scipy_ct = cumulative_trapezoid(f, x, initial=0)
     np.testing.assert_allclose(glass_ct, scipy_ct)