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- # -*- coding: utf-8 -*-
- from boltons.statsutils import Stats
- def test_stats_basic():
- da = Stats(range(20))
- assert da.mean == 9.5
- assert round(da.std_dev, 2) == 5.77
- assert da.variance == 33.25
- assert da.skewness == 0
- assert round(da.kurtosis, 1) == 1.9
- assert da.median == 9.5
- def _test_pearson():
- import random
- from statsutils import pearson_type
- def get_pt(dist):
- vals = [dist() for x in range(10000)]
- pt = pearson_type(vals)
- return pt
- for x in range(3):
- # pt = get_pt(dist=lambda: random.normalvariate(15, 5)) # expect 0, normal
- # pt = get_pt(dist=lambda: random.weibullvariate(2, 3)) # gets 1, beta, weibull not specifically supported
- # pt = get_pt(dist=lambda: random.gammavariate(2, 3)) # expect 3, gamma
- # pt = get_pt(dist=lambda: random.betavariate(2, 3)) # expect 1, beta
- # pt = get_pt(dist=lambda: random.expovariate(0.2)) # expect 3, beta
- pt = get_pt(dist=lambda: random.uniform(0.0, 10.0)) # gets 2
- print('pearson type:', pt)
- # import pdb;pdb.set_trace()
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