boost/histogram
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fix

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This commit is contained in:
Hans Dembinski
2017-11-03 16:26:33 +01:00
parent 730db79f5c
commit b2a2cc123d
1 changed files with 9 additions and 9 deletions
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18
test/speed_numpy.py
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@@ -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]))