Math1

import math
def c(b, a):
    a1 = math.factorial(a)
    b1 = math.factorial(b)
    c1 = math.factorial(a-b)
    c = a1 / b1 / c1
    return c
def M(arX, ksi):
    M = []
    for i in range(0, len(arX)):
        M.append(arX[i]*ksi[i])
    return M
def Msum(arX, ksi):
    M = []
    for i in range(0, len(arX)):
        M.append(arX[i]*ksi[i])
    return sum(M)
def D(M_, arX, ksi):
    D = []
    for i in range(0, len(arX)):
        out = ((ksi[i])-M_)**2 * arX[i]
        D.append(out)
    return D
def Dsum(M_, arX, ksi):
    D = []
    for i in range(0, len(arX)):
        out = ((ksi[i])-M_)**2 * arX[i]
        D.append(out)
    return sum(D)
def sigma(Dx):
    return Dx**0.5
def MuXY(arX_,ksi_,ksiy, Dx, Dy):
    ar = []
    for item in ksiy:
        for i in range(len(arX_)):
            ar.append(arX_[i]*ksi_[i]*item)
            i +=1
    ar.append(-Dx*Dy)
    return sum(ar)
def rxy(MuXY,Sigx, Sigy):
    rx = MuXY/Sigx/Sigy
    return rx

# 1
# Дано

arX_ = [0.35,0.27,0.33,0.05] # Дано
ksi_ = [0,1,2,3]   # Дано

arY = [0.58,0.42] # Дано
ksiy = [22,18]   # Дано
pervoe = 1 # первое число равно ?


MuXY = MuXY(arX_,ksi_,ksiy, 0.8736, 3.897)
print("MuXY - ", MuXY)

# Формулы функции
M_ = Msum(arX_, ksi_)
print("Матожидан =", M_)
D_= Dsum(M_,arX_,ksi_) # массив
print("Дисперсия = ",D_)
Sig = sigma(D_)
print("Сигма = ",Sig)
rxy = rxy(MuXY,0.934, 1.97)
print("rx = ", rxy)




# 2
# импортируем модули
import numpy as np
import math
import matplotlib.pyplot as plt
from numpy import arange, exp
##a=0
##b=2
##def fx(x):
##    y = 1 - (b-x)**2/(b-a)**2
##    return y
##print(fx(0))
##print(fx(2))
##def fx2(x):
##    y = +1/2*x**2 - 1/12*x**3
##    return y
##print(fx2(0))
##print(fx2(2))
##x = np.linspace(0, 2,10)
#plt.plot(x, fx2(x))
#plt.show()


##
##
##def x025(x):
##    return 0.25*x**2
##x025(1.5) - x025(-0.5)
##
##
##
##
##
##def x025_(x):
##    return (1/6)*x**3
##x025_(1.5) - x025_(-0.5) -0.5**2
def graf(x,y):
    plt.plot(x, y)
a=6.4
k = -0.3125/6.4
b = 0.3125
def fx_(x):
    return k*x+b
def fxInt(x):
    return (k*x**2)/2+b*x
def fxMx(x):
    return (k*x**3)/3+b*x**2/2
def fxDx(x):
    return (k*x**4)/4 + b*x**3/3 - 2.13**2
def expP(x):
    return 1-exp(-x*3)
def expInt(x):
    return x+exp(-3*x)/3-1/3

x = np.linspace(-1, 100,1)
x_= arange(0,2.3333,0.01)
fx_(x)
graf(x_,expInt(x_))
graf(x_,expP(x_))

#S = fxInt(0) - fxInt(a)
#S = fxMx(0) - fxMx(a)
#S = fxDx(0) - fxDx(a)
S = expInt(0.81)

print(S)
#graf(x,fx_(x))
#graf(x,fxInt(x))
#graf(x,fxMx(x))
#graf(x,fxDx(x))
#plt.show()
#######################################4-5



def laplasX(Dsig, predel): ##потом по табличному значению https://math.semestr.ru/corel/table-laplas.php
    return predel / Dsig



plt.show()