chore: import upstream snapshot with attribution

bench/issue-36.py

@@ -0,0 +1,37 @@
+# Small benchmark to get the even point where the threading code
+# performs better than the serial code.  See issue #36 for details.
+
+from __future__ import print_function
+
+from time import time
+
+import numpy as np
+from numpy.testing import assert_array_equal
+
+import numexpr as ne
+
+
+def bench(N):
+    print("*** array length:", N)
+    a = np.arange(N)
+    t0 = time()
+    ntimes = (1000*2**15) // N
+    for i in range(ntimes):
+        ne.evaluate('a>1000')
+    print("numexpr--> %.3g" % ((time()-t0)/ntimes,))
+
+    t0 = time()
+    for i in range(ntimes):
+        eval('a>1000')
+    print("numpy--> %.3g" % ((time()-t0)/ntimes,))
+
+if __name__ == "__main__":
+    print("****** Testing with 1 thread...")
+    ne.set_num_threads(1)
+    for N in range(10, 20):
+        bench(2**N)
+
+    print("****** Testing with 2 threads...")
+    ne.set_num_threads(2)
+    for N in range(10, 20):
+        bench(2**N)