API: make mean private

Author: lucascolley

src/array_api_extra/_funcs.py

@@ -116,7 +116,7 @@ def cov(m: Array, /, *, xp: ModuleType) -> Array:
     m = atleast_nd(m, ndim=2, xp=xp)
     m = xp.astype(m, dtype)
 
-    avg = mean(m, axis=1, xp=xp)
+    avg = _mean(m, axis=1, xp=xp)
     fact = m.shape[1] - 1
 
     if fact <= 0:
@@ -133,7 +133,7 @@ def cov(m: Array, /, *, xp: ModuleType) -> Array:
     return xp.squeeze(c, axis=axes)
 
 
-def mean(
+def _mean(
     x: Array,
     /,
     *,
@@ -142,44 +142,7 @@ def mean(
     xp: ModuleType,
 ) -> Array:
     """
-    Calculates the arithmetic mean of the input array ``x``.
-
-    In addition to the standard ``mean``, this function supports complex-valued input.
-
-    Parameters
-    ----------
-    x: array
-        input array. Should have a floating-point data type.
-    axis: int or tuple of ints, optional
-        axis or axes along which arithmetic means must be computed.
-        By default, the mean must be computed over the entire array.
-        If a tuple of integers, arithmetic means must be computed over multiple axes.
-        Default: ``None``.
-    keepdims: bool, optional
-        if ``True``, the reduced axes (dimensions) must be included in the result as
-        singleton dimensions, and, accordingly, the result must be compatible with
-        the input array (see :ref:`broadcasting`).
-        Otherwise, if ``False``, the reduced axes (dimensions) must not be included
-        in the result. Default: ``False``.
-
-    Returns
-    -------
-    out: array
-        if the arithmetic mean was computed over the entire array,
-        a zero-dimensional array containing the arithmetic mean;
-        otherwise, a non-zero-dimensional array containing the arithmetic means.
-        The returned array must have the same data type as ``x``.
-
-    Notes
-    -----
-
-    **Special Cases**
-
-    Let ``N`` equal the number of elements over which to compute the arithmetic mean.
-
-    -   If ``N`` is ``0``, the arithmetic mean is ``NaN``.
-    -   If ``x_i`` is ``NaN``, the arithmetic mean is ``NaN``
-        (i.e., ``NaN`` values propagate).
+    Complex mean, https://github.com/data-apis/array-api/issues/846.
     """
     if xp.isdtype(x.dtype, "complex floating"):
         x_real = xp.real(x)