DOC: Fix intersphinx inventory names

Since Sphinx 5.0.0, some intersphinx links need explicit inventory names or they won't be resolved correctly. See https://www.sphinx-doc.org/en/master/changes.html\#release-5-0-0-released-may-30-2022 and sphinx-doc/sphinx#2068.
numpy · Aug 15, 2022 · 9de446a · 9de446a
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diff --git a/doc/source/reference/arrays.interface.rst b/doc/source/reference/arrays.interface.rst
@@ -125,7 +125,7 @@ This approach to the interface consists of the object having an
        **Default**: ``[('', typestr)]``
 
    **data** (optional)
-       A 2-tuple whose first argument is a :doc:`Python integer <c-api/long>`
+       A 2-tuple whose first argument is a :doc:`Python integer <python:c-api/long>`
        that points to the data-area storing the array contents.
 
        .. note::
@@ -253,7 +253,7 @@ flag is present.
 .. note::
 
     :obj:`__array_struct__` is considered legacy and should not be used for new
-    code. Use the :py:doc:`buffer protocol <c-api/buffer>` or the DLPack protocol
+    code. Use the :doc:`buffer protocol <python:c-api/buffer>` or the DLPack protocol
     `numpy.from_dlpack` instead.
 
 

diff --git a/doc/source/user/basics.interoperability.rst b/doc/source/user/basics.interoperability.rst
@@ -44,7 +44,7 @@ objects to be treated as NumPy arrays whenever possible. When NumPy functions
 encounter a foreign object, they will try (in order):
 
 1. The buffer protocol, described :py:doc:`in the Python C-API documentation
-   <c-api/buffer>`.
+   <python:c-api/buffer>`.
 2. The ``__array_interface__`` protocol, described
    :ref:`in this page <arrays.interface>`. A precursor to Python's buffer
    protocol, it defines a way to access the contents of a NumPy array from other

diff --git a/doc/source/user/how-to-how-to.rst b/doc/source/user/how-to-how-to.rst
@@ -105,7 +105,7 @@ deep dives intended to give understanding rather than immediate assistance,
 and `References`, which give complete, authoritative data on some concrete
 part of NumPy (like its API) but aren't obligated to paint a broader picture.
 
-For more on tutorials, see :doc:`content/tutorial-style-guide`
+For more on tutorials, see :doc:`numpy-tutorials:content/tutorial-style-guide`
 
 ******************************************************************************
 Is this page an example of a how-to?

diff --git a/doc/source/user/quickstart.rst b/doc/source/user/quickstart.rst
@@ -1485,4 +1485,4 @@ Further reading
 -  `SciPy Tutorial <https://docs.scipy.org/doc/scipy/reference/tutorial/index.html>`__
 -  `SciPy Lecture Notes <https://scipy-lectures.org>`__
 -  A `matlab, R, IDL, NumPy/SciPy dictionary <http://mathesaurus.sf.net/>`__
--  :doc:`tutorial-svd <content/tutorial-svd>`
+-  :doc:`tutorial-svd <numpy-tutorials:content/tutorial-svd>`
diff --git a/numpy/core/_add_newdocs.py b/numpy/core/_add_newdocs.py
@@ -1756,9 +1756,9 @@
     In such cases, the use of `numpy.linspace` should be preferred.
 
     The built-in :py:class:`range` generates :std:doc:`Python built-in integers
-    that have arbitrary size <c-api/long>`, while `numpy.arange` produces
-    `numpy.int32` or `numpy.int64` numbers. This may result in incorrect
-    results for large integer values::
+    that have arbitrary size <python:c-api/long>`, while `numpy.arange`
+    produces `numpy.int32` or `numpy.int64` numbers. This may result in
+    incorrect results for large integer values::
 
       >>> power = 40
       >>> modulo = 10000