From b2a2cc123dc0737acff24d3638d70f4e7319dea9 Mon Sep 17 00:00:00 2001
From: Hans Dembinski <hans.dembinski@gmail.com>
Date: Fri, 3 Nov 2017 16:26:33 +0100
Subject: [PATCH] fix

---
 test/speed_numpy.py | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/test/speed_numpy.py b/test/speed_numpy.py
index 99e33dee..02b91049 100755
--- a/test/speed_numpy.py
+++ b/test/speed_numpy.py
@@ -40,20 +40,20 @@ def compare_2d(n, distrib):
         r = np.random.rand(n)
     else:
         r = 0.5 + 0.3 * np.random.randn(n)
-    r = r.reshape(n/2, 2)
+    r = r.reshape(2, n/2)
 
     best_numpy = float("infinity")
     best_boost = float("infinity")
     for k in xrange(50):
         t = timer()
-        w, xe, ye = np.histogram2d(r[:,0], r[:,1], bins=(100, 100),
+        w, xe, ye = np.histogram2d(r[0], r[1], bins=(100, 100),
                                    range=((0.0, 1.0), (0.0, 1.0)))
         t = timer() - t
         best_numpy = min(t, best_numpy)
 
         h = histogram(regular(100, 0, 1), regular(100, 0, 1))
         t = timer()
-        h.fill(r[:,0], r[:,1])
+        h.fill(r[0], r[1])
         t = timer() - t
         best_boost = min(t, best_boost)
     assert(np.all(w == np.array(h)[:-2,:-2]))
@@ -66,13 +66,13 @@ def compare_3d(n, distrib):
         r = np.random.rand(n)
     else:
         r = 0.3 * np.random.randn(n)
-    r = r.reshape(n/3, 3)
+    r = r.reshape(3, n/3)
 
     best_numpy = float("infinity")
     best_boost = float("infinity")
     for k in xrange(50):
         t = timer()
-        w, xe = np.histogramdd(r, bins=(100, 100, 100),
+        w, xe = np.histogramdd(r.T, bins=(100, 100, 100),
                                range=((0.0, 1.0),
                                       (0.0, 1.0),
                                       (0.0, 1.0)))
@@ -83,7 +83,7 @@ def compare_3d(n, distrib):
                       regular(100, 0, 1),
                       regular(100, 0, 1))
         t = timer()
-        h.fill(r[:,0], r[:,1], r[:,2])
+        h.fill(r[0], r[1], r[2])
         t = timer() - t
         best_boost = min(t, best_boost)
     assert(np.all(w == np.array(h)[:-2,:-2,:-2]))
@@ -96,13 +96,13 @@ def compare_6d(n, distrib):
         r = np.random.rand(n)
     else:
         r = 0.3 * np.random.randn(n)
-    r = r.reshape(n/6, 6)
+    r = r.reshape(6, n/6)
 
     best_numpy = float("infinity")
     best_boost = float("infinity")
     for k in xrange(50):
         t = timer()
-        w, xe = np.histogramdd(r, bins=(10, 10, 10,
+        w, xe = np.histogramdd(r.T, bins=(10, 10, 10,
                                         10, 10, 10),
                                range=((0.0, 1.0),
                                       (0.0, 1.0),
@@ -120,7 +120,7 @@ def compare_6d(n, distrib):
                       regular(10, 0, 1),
                       regular(10, 0, 1))
         t = timer()
-        h.fill(r[:,0], r[:,1], r[:,2], r[:,3], r[:,4], r[:,5])
+        h.fill(r[0], r[1], r[2], r[3], r[4], r[5])
         t = timer() - t
         best_boost = min(t, best_boost)
     assert(np.all(w == np.array(h)[:-2,:-2,:-2,:-2,:-2,:-2]))