Fix Returns in docstrings (I think entered in #357) (#373)

glass-dev · Oct 18, 2024 · 0c39930 · 0c39930
1 parent c020f18
commit 0c39930
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Showing 3 changed files with 25 additions and 61 deletions.
diff --git a/glass/observations.py b/glass/observations.py
@@ -50,6 +50,8 @@ def vmap_galactic_ecliptic(
     the galactic and ecliptic planes. The location of the stripes is set with
     optional parameters.
 
+    Returns a HEALPix :term:`visibility map`.
+
     Parameters
     ----------
     nside:
@@ -59,11 +61,6 @@ def vmap_galactic_ecliptic(
     ecliptic:
         The location of the ecliptic plane in the respective coordinate system.
 
-    Returns
-    -------
-    vis:
-        A HEALPix :term:`visibility map`.
-
     Raises
     ------
     TypeError
@@ -100,6 +97,8 @@ def gaussian_nz(
     If ``mean`` or ``sigma`` are array_like, their axes will be the leading
     axes of the redshift distribution.
 
+    Returns the redshift distribution at the given ``z`` values.
+
     Parameters
     ----------
     z:
@@ -111,11 +110,6 @@ def gaussian_nz(
     norm:
         If given, the normalisation of the distribution.
 
-    Returns
-    -------
-    nz:
-        Redshift distribution at the given ``z`` values.
-
     """
     mean = np.reshape(mean, np.shape(mean) + (1,) * np.ndim(z))
     sigma = np.reshape(sigma, np.shape(sigma) + (1,) * np.ndim(z))
@@ -142,6 +136,8 @@ def smail_nz(
 
     The redshift follows the Smail et al. [1] redshift distribution.
 
+    Returns the redshift distribution at the given ``z`` values.
+
     Parameters
     ----------
     z:
@@ -155,11 +151,6 @@ def smail_nz(
     norm:
         If given, the normalisation of the distribution.
 
-    Returns
-    -------
-    pz:
-        Redshift distribution at the given ``z`` values.
-
     Notes
     -----
     The probability distribution function :math:`p(z)` for redshift :math:`z`
@@ -204,6 +195,8 @@ def fixed_zbins(
     This function creates contiguous tomographic redshift bins of fixed size.
     It takes either the number or size of the bins.
 
+    Returns a list of redshift bin edges.
+
     Parameters
     ----------
     zmin:
@@ -215,11 +208,6 @@ def fixed_zbins(
     dz:
         Size of redshift bin. Only one of ``nbins`` and ``dz`` can be given.
 
-    Returns
-    -------
-    zbins:
-        List of redshift bin edges.
-
     """
     if nbins is not None and dz is None:
         zbinedges = np.linspace(zmin, zmax, nbins + 1)
@@ -243,6 +231,8 @@ def equal_dens_zbins(
     This function subdivides a source redshift distribution into ``nbins``
     tomographic redshift bins with equal density.
 
+    Returns a list of redshift bin edges.
+
     Parameters
     ----------
     z:
@@ -252,11 +242,6 @@ def equal_dens_zbins(
     nbins:
         Number of redshift bins.
 
-    Returns
-    -------
-    zbins:
-        List of redshift bin edges.
-
     """
     # compute the normalised cumulative distribution function
     # first compute the cumulative integral (by trapezoidal rule)
@@ -285,6 +270,9 @@ def tomo_nz_gausserr(
     standard deviation of the Gaussian depends on redshift and is given by
     ``sigma(z) = sigma_0*(1 + z)``.
 
+    Returns the tomographic redshift bins convolved with a gaussian error.
+    Array has a shape (nbins, len(z))
+
     Parameters
     ----------
     z:
@@ -296,12 +284,6 @@ def tomo_nz_gausserr(
     zbins:
         List of redshift bin edges.
 
-    Returns
-    -------
-    binned_nz:
-        Tomographic redshift bins convolved with a gaussian error.
-        Array has a shape (nbins, len(z))
-
     See Also
     --------
     equal_dens_zbins:

diff --git a/glass/points.py b/glass/points.py
@@ -45,6 +45,8 @@ def effective_bias(z, bz, w):  # type: ignore[no-untyped-def]
     and computes an effective bias parameter :math:`\bar{b}` for a
     given window function :math:`w(z)`.
 
+    Returns the effective bias parameter for the window.
+
     Parameters
     ----------
     z:
@@ -54,11 +56,6 @@ def effective_bias(z, bz, w):  # type: ignore[no-untyped-def]
     w:
         The radial window function :math:`w(z)`.
 
-    Returns
-    -------
-    beff:
-        Effective bias parameter for the window.
-
     Notes
     -----
     The effective bias parameter :math:`\bar{b}` is computed using the
@@ -313,6 +310,8 @@ def position_weights(densities, bias=None):  # type: ignore[no-untyped-def]
     redshift distribution and bias factor :math:`n(z) \, b(z)` for the
     discretised shells.
 
+    Returns the relative weight of each shell for angular clustering.
+
     Parameters
     ----------
     densities:
@@ -321,11 +320,6 @@ def position_weights(densities, bias=None):  # type: ignore[no-untyped-def]
     bias:
         Value or values of the linear bias parameter for each shell.
 
-    Returns
-    -------
-    weights:
-        Relative weight of each shell for angular clustering.
-
     """
     # bring densities and bias into the same shape
     if bias is not None:

diff --git a/glass/shapes.py b/glass/shapes.py
@@ -37,6 +37,8 @@ def triaxial_axis_ratio(zeta, xi, size=None, *, rng=None):  # type: ignore[no-un
     Given the two axis ratios `1 >= zeta >= xi` of a randomly oriented triaxial
     ellipsoid, computes the axis ratio `q` of the projection.
 
+    Returns the axis ratio of the randomly projected ellipsoid.
+
     Parameters
     ----------
     zeta:
@@ -49,11 +51,6 @@ def triaxial_axis_ratio(zeta, xi, size=None, *, rng=None):  # type: ignore[no-un
     rng:
         Random number generator. If not given, a default RNG will be used.
 
-    Returns
-    -------
-    q:
-        Axis ratio of the randomly projected ellipsoid.
-
     Notes
     -----
     See equations (11) and (12) in [1] for details.
@@ -106,6 +103,8 @@ def ellipticity_ryden04(mu, sigma, gamma, sigma_gamma, size=None, *, rng=None):
     standard deviation :math:`\sigma_\gamma` [2]. Both distributions are
     truncated to produce ratios in the range 0 to 1 using rejection sampling.
 
+    Returns an array of :term:`ellipticity` from projected axis ratios.
+
     Parameters
     ----------
     mu:
@@ -121,11 +120,6 @@ def ellipticity_ryden04(mu, sigma, gamma, sigma_gamma, size=None, *, rng=None):
     rng:
         Random number generator. If not given, a default RNG will be used.
 
-    Returns
-    -------
-    eps:
-        Array of :term:`ellipticity` from projected axis ratios.
-
     References
     ----------
     * [1] Ryden B. S., 2004, ApJ, 601, 214.
@@ -186,6 +180,8 @@ def ellipticity_gaussian(
     this function with too large values of ``sigma``, or the sampling
     will become inefficient.
 
+    Returns an array of galaxy :term:`ellipticity`.
+
     Parameters
     ----------
     count:
@@ -195,11 +191,6 @@ def ellipticity_gaussian(
     rng:
         Random number generator. If not given, a default RNG is used.
 
-    Returns
-    -------
-    eps:
-        Array of galaxy :term:`ellipticity`.
-
     """
     # default RNG if not provided
     if rng is None:
@@ -240,6 +231,8 @@ def ellipticity_intnorm(
     The ellipticities are sampled from an intrinsic normal distribution
     with standard deviation ``sigma`` for each component.
 
+    Returns an array of galaxy :term:`ellipticity`.
+
     Parameters
     ----------
     count:
@@ -249,11 +242,6 @@ def ellipticity_intnorm(
     rng:
         Random number generator. If not given, a default RNG is used.
 
-    Returns
-    -------
-    eps:
-        Array of galaxy :term:`ellipticity`.
-
     """
     # default RNG if not provided
     if rng is None: