本文整理汇总了Python中streamhist.StreamHist类的典型用法代码示例。如果您正苦于以下问题：Python StreamHist类的具体用法？Python StreamHist怎么用？Python StreamHist使用的例子？那么, 这里精选的类代码示例或许可以为您提供帮助。
在下文中一共展示了StreamHist类的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_len
def test_len():
h = StreamHist(maxbins=5)
assert len(h) == 0
h.update(range(5))
assert len(h) == len(h.bins) == 5
h.update(range(5))
assert len(h) == len(h.bins) == 5示例2: test_iterable
def test_iterable():
h = StreamHist().update([p for p in range(4)])
assert h.total == 4
nested = [[1, 2, 3], 4, [5, 6], 7, 8, [9], [10, 11, 12], 13, 14, 15]
h = StreamHist().update(nested)
assert h.total == 15
assert h.mean() == 8示例3: test_counts
def test_counts():
data = [605, 760, 610, 615, 605, 780, 605, 905]
h = StreamHist(maxbins=4, weighted=False)
for p in data:
h.update(p)
counts = [b[1] for b in h.bins]
assert len(data) == reduce(operator.add, counts) == h.total示例4: test_missing
def test_missing():
data = [1, None, 1, 4, 6]
h = StreamHist(maxbins=2)
for p in data:
h.update(p)
assert h.missing_count == 1
assert len(h.bins) == 2
assert h.bins[0][0] == 1 and h.bins[1][0] == 5示例5: test_string
def test_string():
h = StreamHist(maxbins=5)
assert str(h) == "Empty histogram"
h.update(range(5))
string = "Mean\tCount\n----\t-----\n"
string += "0\t1\n1\t1\n2\t1\n3\t1\n4\t1"
string += "\n----\t-----\nMissing values: 0\nTotal count: 5"
assert str(h) == string示例6: test_missing_merge
def test_missing_merge():
h1 = StreamHist(maxbins=8).update(None)
h2 = StreamHist(maxbins=8)
assert h1.merge(h2) is not None
h1 = StreamHist().update(None)
h2 = StreamHist().update(None)
merged = StreamHist().merge(h1.merge(h2))
assert merged.missing_count == 2示例7: test_compute_breaks
def test_compute_breaks():
points = 10000
bins = 25
from numpy import histogram, allclose
data = make_normal(points)
h1 = StreamHist().update(data)
h2, es2 = histogram(data, bins=bins)
h3, es3 = h1.compute_breaks(bins)
assert allclose(es2, es3)
assert allclose(h2, h3, rtol=1, atol=points/(bins**2))示例8: test_describe
def test_describe():
points = 10000
data = make_uniform(points)
h = StreamHist().update(data)
d = h.describe(quantiles=[0.5])
print(d)
assert about(d["50%"], 0.5, 0.05)
assert about(d["min"], 0.0, 0.05)
assert about(d["max"], 1.0, 0.05)
assert about(d["mean"], 0.5, 0.05)
assert about(d["var"], 0.08, 0.05)
assert d["count"] == points示例9: test_multi_merge
def test_multi_merge():
points = 100000
data = make_uniform(points)
samples = [data[x:x+100] for x in range(0, len(data), 100)]
hists = [StreamHist().update(s) for s in samples]
h1 = sum(hists)
h2 = StreamHist().update(data)
q1 = h1.quantiles(.1, .2, .3, .4, .5, .6, .7, .8, .9)
q2 = h2.quantiles(.1, .2, .3, .4, .5, .6, .7, .8, .9)
from numpy import allclose
assert allclose(q1, q2, rtol=1, atol=0.025)示例10: test_median_mean
def test_median_mean():
points = 10000
h = StreamHist()
for p in make_uniform(points):
h.update(p)
assert about(h.median(), 0.5, 0.05)
h = StreamHist()
for p in make_normal(points):
h.update(p)
assert about(h.median(), 0, 0.05)
assert about(h.mean(), 0, 0.05)示例11: test_exact_median
def test_exact_median():
points = range(15) # Odd number of points
h = StreamHist(maxbins=17)
h.update(points)
assert h.median() == 7
points = range(16) # Even number of points
h = StreamHist(maxbins=17)
h.update(points)
assert h.median() == 7.5示例12: test_var
def test_var():
assert StreamHist().update(1).var() is None
h = StreamHist()
for p in [1, 1, 2, 3, 4, 5, 6, 6]:
h.update(p)
assert h.var() == 3.75
h = StreamHist()
for p in make_normal(10000):
h.update(p)
assert about(h.var(), 1, 0.05)示例13: test_copy
def test_copy():
h1 = StreamHist()
h2 = h1.copy()
assert h1.bins == h2.bins
h1.update(make_normal(1000))
assert h1.bins != h2.bins
h2 = h1.copy()
assert h1.bins == h2.bins
h1 = StreamHist().update([p for p in range(4)])
h2 = h1.copy()
assert h1.to_dict() == h2.to_dict()示例14: test_trim
def test_trim():
points = 1000
h = StreamHist(maxbins=10)
for _ in range(points):
h.update(rand_int(10))
assert len(h.bins) == 10 and h.total == points
h = StreamHist(maxbins=10)
for _ in range(points):
h.insert(rand_int(10), 1)
h.trim()
assert len(h.bins) == 10 and h.total == points示例15: test_freeze
def test_freeze():
points = 100000
h = StreamHist(freeze=500)
for p in make_normal(points):
h.update(p)
assert about(h.sum(0), points/2.0, points/50.0)
assert about(h.median(), 0, 0.05)
assert about(h.mean(), 0, 0.05)
assert about(h.var(), 1, 0.05)