mirror of https://github.com/mahmoud/boltons.git
34 lines
1.1 KiB
Python
34 lines
1.1 KiB
Python
|
# -*- 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()
|