From fae50aa0b67d806ed3b193e904429a988b4b1cdd Mon Sep 17 00:00:00 2001
From: Illviljan <14371165+Illviljan@users.noreply.github.com>
Date: Sun, 22 Sep 2024 00:38:38 +0200
Subject: [PATCH] add examples

---
 .../_array_api/_linear_algebra_functions.py   | 27 +++++++++++++++++++
 xarray/namedarray/_array_api/_utils.py        | 16 ++++++-----
 2 files changed, 36 insertions(+), 7 deletions(-)

diff --git a/xarray/namedarray/_array_api/_linear_algebra_functions.py b/xarray/namedarray/_array_api/_linear_algebra_functions.py
index f8b730907af..f5e2cc0f389 100644
--- a/xarray/namedarray/_array_api/_linear_algebra_functions.py
+++ b/xarray/namedarray/_array_api/_linear_algebra_functions.py
@@ -10,6 +10,33 @@
 def matmul(
     x1: NamedArray[Any, Any], x2: NamedArray[Any, Any], /
 ) -> NamedArray[Any, Any]:
+    """
+    Matrix product of two arrays.
+
+    Examples
+    --------
+    For 2-D arrays it is the matrix product:
+
+    >>> import numpy as np
+    >>> a = NamedArray(("y", "x"), np.array([[1, 0], [0, 1]]))
+    >>> b = NamedArray(("y", "x"), np.array([[4, 1], [2, 2]]))
+    >>> matmul(a, b)
+    <Namedarray, shape=(2, 2), dims=('y', 'x'), dtype=int64, data=[[4 1]
+     [2 2]]>
+
+    For 2-D mixed with 1-D, the result is the usual.
+
+    >>> a = NamedArray(("y", "x"), np.array([[1, 0], [0, 1]]))
+    >>> b = NamedArray(("x",), np.array([1, 2]))
+    >>> matmul(a, b)
+
+    Broadcasting is conventional for stacks of arrays
+
+    >>> a = NamedArray(("z", "y", "x"), np.arange(2 * 2 * 4).reshape((2, 2, 4)))
+    >>> b = NamedArray(("z", "y", "x"), np.arange(2 * 2 * 4).reshape((2, 4, 2)))
+    >>> axb = matmul(a,b)
+    >>> axb.dims, axb.shape
+    """
     xp = _get_data_namespace(x1)
     _data = xp.matmul(x1._data, x2._data)
     # TODO: Figure out a better way:
diff --git a/xarray/namedarray/_array_api/_utils.py b/xarray/namedarray/_array_api/_utils.py
index 30a125d5f6c..c0a6611427d 100644
--- a/xarray/namedarray/_array_api/_utils.py
+++ b/xarray/namedarray/_array_api/_utils.py
@@ -111,6 +111,8 @@ def _infer_dims(
     >>> _infer_dims((3, 1))
     ('dim_1', 'dim_0')
 
+    >>> _infer_dims((), ())
+    ()
     >>> _infer_dims((1,), "x")
     ('x',)
     >>> _infer_dims((1,), None)
@@ -406,19 +408,19 @@ def _dims_from_tuple_indexing(dims: _Dims, key: _IndexKeys) -> _Dims:
 
     Examples
     --------
-    >>> dims_from_tuple_indexing(("x", "y"), ())
+    >>> _dims_from_tuple_indexing(("x", "y"), ())
     ('x', 'y')
-    >>> dims_from_tuple_indexing(("x", "y"), (0,))
+    >>> _dims_from_tuple_indexing(("x", "y"), (0,))
     ('y',)
-    >>> dims_from_tuple_indexing(("x", "y"), (0, 0))
+    >>> _dims_from_tuple_indexing(("x", "y"), (0, 0))
     ()
-    >>> dims_from_tuple_indexing(("x", "y"), (0, ...))
+    >>> _dims_from_tuple_indexing(("x", "y"), (0, ...))
     ('y',)
-    >>> dims_from_tuple_indexing(("x", "y"), (0, slice(0)))
+    >>> _dims_from_tuple_indexing(("x", "y"), (0, slice(0)))
     ('y',)
-    >>> dims_from_tuple_indexing(("x", "y"), (None,))
+    >>> _dims_from_tuple_indexing(("x", "y"), (None,))
     ('dim_2', 'x', 'y')
-    >>> dims_from_tuple_indexing(("x", "y"), (0, None, None, 0))
+    >>> _dims_from_tuple_indexing(("x", "y"), (0, None, None, 0))
     ('dim_1', 'dim_2')
     """
     _dims = list(dims)