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from scalene import runningstats
import hypothesis.strategies as st
import math
import statistics
from hypothesis import given
from typing import List
TOLERANCE = 0.5
@given(
st.lists(
st.floats(
allow_infinity=False, allow_nan=False, min_value=0.5, max_value=1e9
),
min_size=2,
)
)
def test_running_stats(values: List[float]) -> None:
rstats = runningstats.RunningStats()
for value in values:
rstats.push(value)
assert len(values) == rstats.size()
assert max(values) == rstats.peak()
assert math.isclose(sum(values) / len(values), rstats.mean(), rel_tol=TOLERANCE)
assert math.isclose(
statistics.variance(values, xbar=rstats.mean()),
rstats.var(),
rel_tol=TOLERANCE,
)
assert math.isclose(
statistics.stdev(values, xbar=rstats.mean()),
rstats.std(),
rel_tol=TOLERANCE,
)
assert math.isclose(
statistics.stdev(values, xbar=rstats.mean())
/ math.sqrt(rstats.size()),
rstats.sem(),
rel_tol=TOLERANCE,
)
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