import pandas as pd
import math
import scipy.stats as stats
import numpy as np
from scipy.stats import norm
path='D:\Study\Statistic\Exz\\'

sample = pd.read_csv(path+'ds5.6.0.csv', names = ['X','Y'],header = None)
sample_X = list(sample['X'])
sample_Y = list(filter(lambda x: not math.isnan(x),list(sample["Y"])))
sigmkv0 = 9.61
sigmkv1 = 302.76
x_mean = np.mean(sample_X)
y_mean = np.mean(sample_Y)
print(x_mean,y_mean)
len_X = len(sample_X)
len_Y = len(sample_Y)
z = (x_mean-y_mean)/(sigmkv0/len_X + sigmkv1/len_Y)**0.5
print('Статистика Z = ', z)

alpha = 0.04
z_alpha = norm().isf(alpha)
print('K0 = (-oo; ' + str(-z_alpha) + ')')

if z < -z_alpha:
    print('H0 Отвергается')
else:
    print('H0 Принимается')

print("P-value:",stats.norm.cdf(z))
if stats.norm.cdf(z) > alpha:
    print('H0 Принимается')
else:
    print('H0 отвергается')

x = symbols('x')
Laplace = 1/sqrt(2*pi)*integrate(exp(-x**2/2),(x,0,x))
delta = 1.5
beta = float(1/2 + Laplace.subs({x:z_alpha + math.sqrt(len_X*len_Y)/math.sqrt(len_Y*sigmkv0 + len_X*sigmkv1) * delta }))
print("Ошибка второго рода:",beta)
print("Мощность критерия:",1-beta)