BENCH: convert bencmarks to asv format

remove files that were part of the origal repo
rework randomgen docs to integrate with numpy and fix some links
remove convenience functions, require explicit call to gen.brng
move code out of numpy.random.randomgen into numpy.random

1 files changed, 77 insertions, 0 deletions

diff --git a/numpy/random/examples/numba/extending.py b/numpy/random/examples/numba/extending.py
new file mode 100644
index 000000000..72e903b1f
--- /dev/null
+++ b/numpy/random/examples/numba/extending.py
@@ -0,0 +1,77 @@
+import datetime as dt
+
+import numpy as np
+import numba as nb
+
+from randomgen import Xoroshiro128
+
+x = Xoroshiro128()
+f = x.ctypes.next_uint32
+s = x.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 = f(state) & mask
+    while val > delta:
+        val = f(state) & mask
+
+    return lb + val
+
+
+print(bounded_uint(323, 2394691, s.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, s.value)
+
+g = x.cffi.next_double
+cffi_state = x.cffi.state
+state_addr = x.cffi.state_address
+
+
+def normals(n, state):
+    out = np.empty(n)
+    for i in range((n + 1) // 2):
+        x1 = 2.0 * g(state) - 1.0
+        x2 = 2.0 * g(state) - 1.0
+        r2 = x1 * x1 + x2 * x2
+        while r2 >= 1.0 or r2 == 0.0:
+            x1 = 2.0 * g(state) - 1.0
+            x2 = 2.0 * g(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
+
+
+print(normals(10, cffi_state).var())
+# Warm up
+normalsj = nb.jit(normals, nopython=True)
+normalsj(1, state_addr)
+
+start = dt.datetime.now()
+normalsj(1000000, state_addr)
+ms = 1000 * (dt.datetime.now() - start).total_seconds()
+print('1,000,000 Polar-transform (numba/Xoroshiro128) randoms in '
+      '{ms:0.1f}ms'.format(ms=ms))
+
+start = dt.datetime.now()
+np.random.standard_normal(1000000)
+ms = 1000 * (dt.datetime.now() - start).total_seconds()
+print('1,000,000 Polar-transform (NumPy) randoms in {ms:0.1f}ms'.format(ms=ms))