1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
|
from __future__ import annotations
import sys
import numpy as np
import pytest
from numpy.testing import assert_almost_equal, assert_array_equal
import boost_histogram as bh
if sys.platform.startswith("emscripten"):
pytest.skip(allow_module_level=True)
def fillit(hist, *args, **kwargs):
return hist.reset().fill(*args, **kwargs)
@pytest.mark.benchmark(group="threaded-fill-1d")
@pytest.mark.parametrize("threads", [1, 4], ids=lambda x: f"threads={x}")
# @pytest.mark.parametrize("atomic", [True, False], ids=["atomic", "double"])
@pytest.mark.parametrize(
"storage", [bh.storage.AtomicInt64, bh.storage.Double, bh.storage.Int64]
)
def test_threads(benchmark, threads, storage):
axes = [bh.axis.Regular(100, 0, 1)]
hist_linear = bh.Histogram(*axes, storage=storage())
hist_atomic = hist_linear.copy()
vals = np.random.rand(1000000)
hist_linear.fill(vals)
hist_result = benchmark(fillit, hist_atomic, vals, threads=threads)
assert_array_equal(hist_linear, hist_result)
@pytest.mark.parametrize("threads", [1, 4, 7], ids=lambda x: f"threads={x}")
@pytest.mark.parametrize(
"storage", [bh.storage.AtomicInt64, bh.storage.Double, bh.storage.Int64]
)
def test_threaded_builtin(threads, storage):
axes = [bh.axis.Regular(1000, 0, 1)]
hist_atomic1 = bh.Histogram(*axes, storage=storage())
hist_atomic2 = hist_atomic1.copy()
vals = np.random.rand(10003)
hist_atomic1.fill(vals)
hist_atomic2.fill(vals, threads=threads)
assert_array_equal(hist_atomic1, hist_atomic2)
@pytest.mark.parametrize("threads", [1, 4, 7], ids=lambda x: f"threads={x}")
def test_threaded_numpy(threads):
vals = np.random.rand(10003)
hist_1, _ = bh.numpy.histogram(vals)
hist_2, _ = bh.numpy.histogram(vals, threads=threads)
assert_array_equal(hist_1, hist_2)
@pytest.mark.parametrize("threads", [1, 4, 7], ids=lambda x: f"threads={x}")
def test_threaded_weights(threads):
x, y, weights = np.random.rand(3, 10003)
hist_1 = bh.Histogram(bh.axis.Regular(10, 0, 1), bh.axis.Regular(10, 0, 1))
hist_2 = hist_1.copy()
hist_1.fill(x, y, weight=weights)
hist_2.fill(x, y, weight=weights, threads=threads)
assert_almost_equal(hist_1.view(), hist_2.view())
@pytest.mark.parametrize("threads", [1, 4, 7], ids=lambda x: f"threads={x}")
def test_threaded_weight_storage(threads):
x, y, weights = np.random.rand(3, 10003)
hist_1 = bh.Histogram(
bh.axis.Regular(10, 0, 1),
bh.axis.Regular(10, 0, 1),
storage=bh.storage.Weight(),
)
hist_2 = hist_1.copy()
hist_1.fill(x, y, weight=weights)
hist_2.fill(x, y, weight=weights, threads=threads)
assert_almost_equal(hist_1.view().value, hist_2.view().value)
assert_almost_equal(hist_1.view().variance, hist_2.view().variance)
def test_no_profile():
hist = bh.Histogram(bh.axis.Regular(10, 0, 1), storage=bh.storage.Mean())
hist.fill([1, 1], sample=[1, 1])
with pytest.raises(RuntimeError):
hist.fill([1, 1], sample=[1, 1], threads=2)
def test_no_weighted_profile():
hist = bh.Histogram(bh.axis.Regular(10, 0, 1), storage=bh.storage.WeightedMean())
hist.fill([1, 1], sample=[1, 1])
with pytest.raises(RuntimeError):
hist.fill([1, 1], sample=[1, 1], threads=2)
# Filling then summing produces different results for means
# @pytest.mark.parametrize("threads", [2, 4, 7], ids=lambda x: "threads={0}".format(x))
# def test_threaded_samples(threads):
# x, y, weights = np.random.rand(3, 10003)
# samples = np.random.randint(1, 10, size=10003)
#
# hist_1 = bh.Histogram(
# bh.axis.Regular(10,0,1),
# bh.axis.Regular(10,0,1),
# storage=bh.storage.WeightedMean())
# hist_2 = hist_1.copy()
#
# hist_1.fill(x, y, sample=samples, weight=weights)
# hist_2.fill(x, y, sample=samples, weight=weights, threads=threads)
#
# assert_almost_equal(hist_1.view().value, hist_2.view().value)
# assert_almost_equal(hist_1.view().variance, hist_2.view().variance)
# assert_almost_equal(hist_1.view().sum_of_weights, hist_2.view().sum_of_weights)
|
