#!/usr/bin/env python3
import os
import sys
from statistics import variance
from scipy import stats
import pandas as pd
import numpy as np

CURDIR = os.path.dirname(os.path.realpath(__file__))
sys.path.insert(0, os.path.join(CURDIR, "helpers"))

from pure_http_client import ClickHouseClient


# unpooled variance z-test for means of two samples
def twosample_mean_ztest(rvs1, rvs2, alpha=0.05):
    mean_rvs1 = np.mean(rvs1)
    mean_rvs2 = np.mean(rvs2)
    var_pop_rvs1 = variance(rvs1)
    var_pop_rvs2 = variance(rvs2)
    se = np.sqrt(var_pop_rvs1 / len(rvs1) + var_pop_rvs2 / len(rvs2))
    z_stat = (mean_rvs1 - mean_rvs2) / se
    p_val = 2 * stats.norm.cdf(-1 * abs(z_stat))
    z_a = stats.norm.ppf(1 - alpha / 2)
    ci_low = (mean_rvs1 - mean_rvs2) - z_a * se
    ci_high = (mean_rvs1 - mean_rvs2) + z_a * se
    return z_stat, p_val, ci_low, ci_high


def test_and_check(name, a, b, t_stat, p_value, ci_low, ci_high, precision=1e-2):
    client = ClickHouseClient()
    client.query("DROP TABLE IF EXISTS ztest;")
    client.query("CREATE TABLE ztest (left Float64, right UInt8) ENGINE = Memory;")
    client.query(
        "INSERT INTO ztest VALUES {};".format(
            ", ".join(["({},{})".format(i, 0) for i in a])
        )
    )
    client.query(
        "INSERT INTO ztest VALUES {};".format(
            ", ".join(["({},{})".format(j, 1) for j in b])
        )
    )
    real = client.query_return_df(
        "SELECT roundBankers({}(left, right).1, 16) as t_stat, ".format(name)
        + "roundBankers({}(left, right).2, 16) as p_value, ".format(name)
        + "roundBankers({}(left, right).3, 16) as ci_low, ".format(name)
        + "roundBankers({}(left, right).4, 16) as ci_high ".format(name)
        + "FROM ztest FORMAT TabSeparatedWithNames;"
    )
    real_t_stat = real["t_stat"][0]
    real_p_value = real["p_value"][0]
    real_ci_low = real["ci_low"][0]
    real_ci_high = real["ci_high"][0]
    assert (
        abs(real_t_stat - np.float64(t_stat)) < precision
    ), "clickhouse_t_stat {}, py_t_stat {}".format(real_t_stat, t_stat)
    assert (
        abs(real_p_value - np.float64(p_value)) < precision
    ), "clickhouse_p_value {}, py_p_value {}".format(real_p_value, p_value)
    assert (
        abs(real_ci_low - np.float64(ci_low)) < precision
    ), "clickhouse_ci_low {}, py_ci_low {}".format(real_ci_low, ci_low)
    assert (
        abs(real_ci_high - np.float64(ci_high)) < precision
    ), "clickhouse_ci_high {}, py_ci_high {}".format(real_ci_high, ci_high)
    client.query("DROP TABLE IF EXISTS ztest;")


def test_mean_ztest():
    rvs1 = np.round(stats.norm.rvs(loc=1, scale=5, size=500), 2)
    rvs2 = np.round(stats.norm.rvs(loc=10, scale=5, size=500), 2)
    s, p, cl, ch = twosample_mean_ztest(rvs1, rvs2)
    test_and_check(
        "meanZTest(%f, %f, 0.95)" % (variance(rvs1), variance(rvs2)),
        rvs1,
        rvs2,
        s,
        p,
        cl,
        ch,
    )

    rvs1 = np.round(stats.norm.rvs(loc=0, scale=5, size=500), 2)
    rvs2 = np.round(stats.norm.rvs(loc=0, scale=5, size=500), 2)
    s, p, cl, ch = twosample_mean_ztest(rvs1, rvs2)
    test_and_check(
        "meanZTest(%f, %f, 0.95)" % (variance(rvs1), variance(rvs2)),
        rvs1,
        rvs2,
        s,
        p,
        cl,
        ch,
    )

    rvs1 = np.round(stats.norm.rvs(loc=2, scale=10, size=512), 2)
    rvs2 = np.round(stats.norm.rvs(loc=5, scale=20, size=1024), 2)
    s, p, cl, ch = twosample_mean_ztest(rvs1, rvs2)
    test_and_check(
        "meanZTest(%f, %f, 0.95)" % (variance(rvs1), variance(rvs2)),
        rvs1,
        rvs2,
        s,
        p,
        cl,
        ch,
    )

    rvs1 = np.round(stats.norm.rvs(loc=0, scale=10, size=1024), 2)
    rvs2 = np.round(stats.norm.rvs(loc=0, scale=10, size=512), 2)
    s, p, cl, ch = twosample_mean_ztest(rvs1, rvs2)
    test_and_check(
        "meanZTest(%f, %f, 0.95)" % (variance(rvs1), variance(rvs2)),
        rvs1,
        rvs2,
        s,
        p,
        cl,
        ch,
    )


if __name__ == "__main__":
    test_mean_ztest()
    print("Ok.")