1 files changed, 0 insertions, 84 deletions
diff --git a/numpy/random/examples/numba/extending.py b/numpy/random/examples/numba/extending.py
deleted file mode 100644
index 0d240596b..000000000
--- a/numpy/random/examples/numba/extending.py
+++ /dev/null
@@ -1,84 +0,0 @@
-import numpy as np
-import numba as nb
-
-from numpy.random import PCG64
-from timeit import timeit
-
-bit_gen = PCG64()
-next_d = bit_gen.cffi.next_double
-state_addr = bit_gen.cffi.state_address
-
-def normals(n, state):
-    out = np.empty(n)
-    for i in range((n + 1) // 2):
-        x1 = 2.0 * next_d(state) - 1.0
-        x2 = 2.0 * next_d(state) - 1.0
-        r2 = x1 * x1 + x2 * x2
-        while r2 >= 1.0 or r2 == 0.0:
-            x1 = 2.0 * next_d(state) - 1.0
-            x2 = 2.0 * next_d(state) - 1.0
-            r2 = x1 * x1 + x2 * x2
-        f = np.sqrt(-2.0 * np.log(r2) / r2)
-        out[2 * i] = f * x1
-        if 2 * i + 1 < n:
-            out[2 * i + 1] = f * x2
-    return out
-
-# Compile using Numba
-normalsj = nb.jit(normals, nopython=True)
-# Must use state address not state with numba
-n = 10000
-
-def numbacall():
-    return normalsj(n, state_addr)
-
-rg = np.random.Generator(PCG64())
-
-def numpycall():
-    return rg.normal(size=n)
-
-# Check that the functions work
-r1 = numbacall()
-r2 = numpycall()
-assert r1.shape == (n,)
-assert r1.shape == r2.shape
-
-t1 = timeit(numbacall, number=1000)
-print('{:.2f} secs for {} PCG64 (Numba/PCG64) gaussian randoms'.format(t1, n))
-t2 = timeit(numpycall, number=1000)
-print('{:.2f} secs for {} PCG64 (NumPy/PCG64) gaussian randoms'.format(t2, n))
-
-# example 2
-
-next_u32 = bit_gen.ctypes.next_uint32
-ctypes_state = bit_gen.ctypes.state
-
-@nb.jit(nopython=True)
-def bounded_uint(lb, ub, state):
-    mask = delta = ub - lb
-    mask |= mask >> 1
-    mask |= mask >> 2
-    mask |= mask >> 4
-    mask |= mask >> 8
-    mask |= mask >> 16
-
-    val = next_u32(state) & mask
-    while val > delta:
-        val = next_u32(state) & mask
-
-    return lb + val
-
-
-print(bounded_uint(323, 2394691, ctypes_state.value))
-
-
-@nb.jit(nopython=True)
-def bounded_uints(lb, ub, n, state):
-    out = np.empty(n, dtype=np.uint32)
-    for i in range(n):
-        out[i] = bounded_uint(lb, ub, state)
-
-
-bounded_uints(323, 2394691, 10000000, ctypes_state.value)
-
-