#!/usr/bin/env python3
import os
import sys
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


def test_and_check(name, a, b, t_stat, p_value):
    client = ClickHouseClient()
    client.query("DROP TABLE IF EXISTS mann_whitney;")
    client.query("CREATE TABLE mann_whitney (left Float64, right UInt8) ENGINE = Memory;");
    client.query("INSERT INTO mann_whitney VALUES {};".format(", ".join(['({},{}), ({},{})'.format(i, 0, j, 1) for i,j in zip(a, 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) + 
        "FROM mann_whitney FORMAT TabSeparatedWithNames;")
    real_t_stat = real['t_stat'][0]
    real_p_value = real['p_value'][0]
    assert(abs(real_t_stat - np.float64(t_stat) < 1e-2)), "clickhouse_t_stat {}, scipy_t_stat {}".format(real_t_stat, t_stat)
    assert(abs(real_p_value - np.float64(p_value)) < 1e-2), "clickhouse_p_value {}, scipy_p_value {}".format(real_p_value, p_value)
    client.query("DROP TABLE IF EXISTS mann_whitney;")


def test_mann_whitney():
    rvs1 = np.round(stats.norm.rvs(loc=1, scale=5,size=500), 5)
    rvs2 = np.round(stats.expon.rvs(scale=0.2,size=500), 5)
    s, p = stats.mannwhitneyu(rvs1, rvs2, alternative='two-sided')
    test_and_check("mannWhitneyUTest", rvs1, rvs2, s, p)
    test_and_check("mannWhitneyUTest('two-sided')", rvs1, rvs2, s, p)

    equal = np.round(stats.cauchy.rvs(scale=5, size=500), 5)
    s, p = stats.mannwhitneyu(equal, equal, alternative='two-sided')
    test_and_check("mannWhitneyUTest('two-sided')", equal, equal, s, p)

    s, p = stats.mannwhitneyu(equal, equal, alternative='less', use_continuity=False)
    test_and_check("mannWhitneyUTest('less', 0)", equal, equal, s, p)


    rvs1 = np.round(stats.cauchy.rvs(scale=10,size=65536), 5)
    rvs2 = np.round(stats.norm.rvs(loc=0, scale=10,size=65536), 5)
    s, p = stats.mannwhitneyu(rvs1, rvs2, alternative='greater')
    test_and_check("mannWhitneyUTest('greater')", rvs1, rvs2, s, p)

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