1 files changed, 15 insertions, 9 deletions
diff --git a/numpy/random/examples/cython/extending_distributions.pyx b/numpy/random/examples/cython/extending_distributions.pyx
index da584e941..89477eb6d 100644
--- a/numpy/random/examples/cython/extending_distributions.pyx
+++ b/numpy/random/examples/cython/extending_distributions.pyx
@@ -1,13 +1,16 @@
 #!/usr/bin/env python
 #cython: language_level=3
-
+"""
+This file shows how the distributions that are accessed through
+distributions.pxd can be used Cython code.
+"""
 import numpy as np
 cimport numpy as np
 cimport cython
 from cpython.pycapsule cimport PyCapsule_IsValid, PyCapsule_GetPointer
 from numpy.random.common cimport *
 from numpy.random.distributions cimport random_gauss_zig
-from numpy.random import Xoroshiro128
+from numpy.random import Xoshiro256
 
 
 @cython.boundscheck(False)
@@ -18,14 +21,16 @@ def normals_zig(Py_ssize_t n):
     cdef const char *capsule_name = "BitGenerator"
     cdef double[::1] random_values
 
-    x = Xoroshiro128()
+    x = Xoshiro256()
     capsule = x.capsule
     if not PyCapsule_IsValid(capsule, capsule_name):
         raise ValueError("Invalid pointer to anon_func_state")
     rng = <bitgen_t *> PyCapsule_GetPointer(capsule, capsule_name)
     random_values = np.empty(n)
-    for i in range(n):
-        random_values[i] = random_gauss_zig(rng)
+    # Best practice is to release GIL and acquire the lock
+    with x.lock, nogil:
+        for i in range(n):
+            random_values[i] = random_gauss_zig(rng)
     randoms = np.asarray(random_values)
     return randoms
 
@@ -38,7 +43,7 @@ def uniforms(Py_ssize_t n):
     cdef const char *capsule_name = "BitGenerator"
     cdef double[::1] random_values
 
-    x = Xoroshiro128()
+    x = Xoshiro256()
     capsule = x.capsule
     # Optional check that the capsule if from a BitGenerator
     if not PyCapsule_IsValid(capsule, capsule_name):
@@ -46,8 +51,9 @@ def uniforms(Py_ssize_t n):
     # Cast the pointer
     rng = <bitgen_t *> PyCapsule_GetPointer(capsule, capsule_name)
     random_values = np.empty(n)
-    for i in range(n):
-        # Call the function
-        random_values[i] = rng.next_double(rng.state)
+    with x.lock, nogil:
+        for i in range(n):
+            # Call the function
+            random_values[i] = rng.next_double(rng.state)
     randoms = np.asarray(random_values)
     return randoms