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-rw-r--r--doc/source/reference/random/extending.rst6
1 files changed, 3 insertions, 3 deletions
diff --git a/doc/source/reference/random/extending.rst b/doc/source/reference/random/extending.rst
index c63fb1a1b..7b1168c45 100644
--- a/doc/source/reference/random/extending.rst
+++ b/doc/source/reference/random/extending.rst
@@ -16,7 +16,7 @@ This example shows how numba can be used to produce gaussian samples using
a pure Python implementation which is then compiled. The random numbers are
provided by ``ctypes.next_double``.
-.. literalinclude:: ../../../../numpy/random/examples/numba/extending.py
+.. literalinclude:: ../../../../numpy/random/_examples/numba/extending.py
:language: python
:end-before: example 2
@@ -35,14 +35,14 @@ This example uses `PCG64` and the example from above. The usual caveats
for writing high-performance code using Cython -- removing bounds checks and
wrap around, providing array alignment information -- still apply.
-.. literalinclude:: ../../../../numpy/random/examples/cython/extending_distributions.pyx
+.. literalinclude:: ../../../../numpy/random/_examples/cython/extending_distributions.pyx
:language: cython
:end-before: example 2
The BitGenerator can also be directly accessed using the members of the basic
RNG structure.
-.. literalinclude:: ../../../../numpy/random/examples/cython/extending_distributions.pyx
+.. literalinclude:: ../../../../numpy/random/_examples/cython/extending_distributions.pyx
:language: cython
:start-after: example 2