mirror of
https://github.com/ClickHouse/ClickHouse.git
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127 lines
4.0 KiB
Python
127 lines
4.0 KiB
Python
#!/usr/bin/env python3
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import os
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import sys
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from statistics import variance
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from scipy import stats
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import pandas as pd
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import numpy as np
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CURDIR = os.path.dirname(os.path.realpath(__file__))
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sys.path.insert(0, os.path.join(CURDIR, "helpers"))
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from pure_http_client import ClickHouseClient
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# unpooled variance z-test for means of two samples
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def twosample_mean_ztest(rvs1, rvs2, alpha=0.05):
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mean_rvs1 = np.mean(rvs1)
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mean_rvs2 = np.mean(rvs2)
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var_pop_rvs1 = variance(rvs1)
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var_pop_rvs2 = variance(rvs2)
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se = np.sqrt(var_pop_rvs1 / len(rvs1) + var_pop_rvs2 / len(rvs2))
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z_stat = (mean_rvs1 - mean_rvs2) / se
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p_val = 2 * stats.norm.cdf(-1 * abs(z_stat))
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z_a = stats.norm.ppf(1 - alpha / 2)
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ci_low = (mean_rvs1 - mean_rvs2) - z_a * se
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ci_high = (mean_rvs1 - mean_rvs2) + z_a * se
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return z_stat, p_val, ci_low, ci_high
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def test_and_check(name, a, b, t_stat, p_value, ci_low, ci_high, precision=1e-2):
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client = ClickHouseClient()
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client.query("DROP TABLE IF EXISTS ztest;")
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client.query("CREATE TABLE ztest (left Float64, right UInt8) ENGINE = Memory;")
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client.query(
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"INSERT INTO ztest VALUES {};".format(
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", ".join(["({},{})".format(i, 0) for i in a])
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)
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)
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client.query(
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"INSERT INTO ztest VALUES {};".format(
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", ".join(["({},{})".format(j, 1) for j in b])
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)
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)
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real = client.query_return_df(
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"SELECT roundBankers({}(left, right).1, 16) as t_stat, ".format(name)
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+ "roundBankers({}(left, right).2, 16) as p_value, ".format(name)
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+ "roundBankers({}(left, right).3, 16) as ci_low, ".format(name)
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+ "roundBankers({}(left, right).4, 16) as ci_high ".format(name)
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+ "FROM ztest FORMAT TabSeparatedWithNames;"
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)
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real_t_stat = real["t_stat"][0]
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real_p_value = real["p_value"][0]
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real_ci_low = real["ci_low"][0]
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real_ci_high = real["ci_high"][0]
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assert (
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abs(real_t_stat - np.float64(t_stat)) < precision
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), "clickhouse_t_stat {}, py_t_stat {}".format(real_t_stat, t_stat)
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assert (
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abs(real_p_value - np.float64(p_value)) < precision
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), "clickhouse_p_value {}, py_p_value {}".format(real_p_value, p_value)
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assert (
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abs(real_ci_low - np.float64(ci_low)) < precision
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), "clickhouse_ci_low {}, py_ci_low {}".format(real_ci_low, ci_low)
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assert (
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abs(real_ci_high - np.float64(ci_high)) < precision
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), "clickhouse_ci_high {}, py_ci_high {}".format(real_ci_high, ci_high)
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client.query("DROP TABLE IF EXISTS ztest;")
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def test_mean_ztest():
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rvs1 = np.round(stats.norm.rvs(loc=1, scale=5, size=500), 2)
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rvs2 = np.round(stats.norm.rvs(loc=10, scale=5, size=500), 2)
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s, p, cl, ch = twosample_mean_ztest(rvs1, rvs2)
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test_and_check(
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"meanZTest(%f, %f, 0.95)" % (variance(rvs1), variance(rvs2)),
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rvs1,
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rvs2,
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s,
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p,
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cl,
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ch,
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)
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rvs1 = np.round(stats.norm.rvs(loc=0, scale=5, size=500), 2)
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rvs2 = np.round(stats.norm.rvs(loc=0, scale=5, size=500), 2)
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s, p, cl, ch = twosample_mean_ztest(rvs1, rvs2)
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test_and_check(
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"meanZTest(%f, %f, 0.95)" % (variance(rvs1), variance(rvs2)),
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rvs1,
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rvs2,
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s,
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p,
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cl,
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ch,
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)
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rvs1 = np.round(stats.norm.rvs(loc=2, scale=10, size=512), 2)
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rvs2 = np.round(stats.norm.rvs(loc=5, scale=20, size=1024), 2)
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s, p, cl, ch = twosample_mean_ztest(rvs1, rvs2)
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test_and_check(
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"meanZTest(%f, %f, 0.95)" % (variance(rvs1), variance(rvs2)),
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rvs1,
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rvs2,
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s,
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p,
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cl,
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ch,
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)
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rvs1 = np.round(stats.norm.rvs(loc=0, scale=10, size=1024), 2)
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rvs2 = np.round(stats.norm.rvs(loc=0, scale=10, size=512), 2)
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s, p, cl, ch = twosample_mean_ztest(rvs1, rvs2)
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test_and_check(
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"meanZTest(%f, %f, 0.95)" % (variance(rvs1), variance(rvs2)),
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rvs1,
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rvs2,
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s,
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p,
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cl,
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ch,
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)
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if __name__ == "__main__":
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test_mean_ztest()
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print("Ok.")
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