MAINT: move numpy/random/examples -> numpy/random/_examples

2 files changed, 0 insertions, 145 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)
-
-
diff --git a/numpy/random/examples/numba/extending_distributions.py b/numpy/random/examples/numba/extending_distributions.py
deleted file mode 100644
index 9233ccced..000000000
--- a/numpy/random/examples/numba/extending_distributions.py
+++ /dev/null
@@ -1,61 +0,0 @@
-r"""
-On *nix, execute in randomgen/src/distributions
-
-export PYTHON_INCLUDE=#path to Python's include folder, usually \
-    ${PYTHON_HOME}/include/python${PYTHON_VERSION}m
-export NUMPY_INCLUDE=#path to numpy's include folder, usually \
-    ${PYTHON_HOME}/lib/python${PYTHON_VERSION}/site-packages/numpy/core/include
-gcc -shared -o libdistributions.so -fPIC distributions.c \
-    -I${NUMPY_INCLUDE} -I${PYTHON_INCLUDE}
-mv libdistributions.so ../../examples/numba/
-
-On Windows
-
-rem PYTHON_HOME is setup dependent, this is an example
-set PYTHON_HOME=c:\Anaconda
-cl.exe /LD .\distributions.c -DDLL_EXPORT \
-    -I%PYTHON_HOME%\lib\site-packages\numpy\core\include \
-    -I%PYTHON_HOME%\include %PYTHON_HOME%\libs\python36.lib
-move distributions.dll ../../examples/numba/
-"""
-import os
-
-import numba as nb
-import numpy as np
-from cffi import FFI
-
-from numpy.random import PCG64
-
-ffi = FFI()
-if os.path.exists('./distributions.dll'):
-    lib = ffi.dlopen('./distributions.dll')
-elif os.path.exists('./libdistributions.so'):
-    lib = ffi.dlopen('./libdistributions.so')
-else:
-    raise RuntimeError('Required DLL/so file was not found.')
-
-ffi.cdef("""
-double random_gauss_zig(void *bitgen_state);
-""")
-x = PCG64()
-xffi = x.cffi
-bit_generator = xffi.bit_generator
-
-random_gauss_zig = lib.random_gauss_zig
-
-
-def normals(n, bit_generator):
-    out = np.empty(n)
-    for i in range(n):
-        out[i] = random_gauss_zig(bit_generator)
-    return out
-
-
-normalsj = nb.jit(normals, nopython=True)
-
-# Numba requires a memory address for void *
-# Can also get address from x.ctypes.bit_generator.value
-bit_generator_address = int(ffi.cast('uintptr_t', bit_generator))
-
-norm = normalsj(1000, bit_generator_address)
-print(norm[:12])