7.Hafta.py

#!/usr/bin/env python
# coding: utf-8




import matplotlib.pyplot as plt
import numpy as np

x=[180,170,170,175,181,175,177,185,179,160]
y=[95,70,60,79,60,63,83,80,75,50]
x,y,len(x),len(y)

X = np.stack((x, y), axis=0)
X

sigma_1=np.cov(X)
sigma_1

X_test= np.stack((x, x), axis=0)
X_test

sigma_2=np.cov(X_test) #ortalamadan olan farkları carp (varyans)
sigma_2

def generate_data():
    x=[180,170,170,175,181,175,177,185,179,160]
    y=[95,70,60,79,60,63,83,80,75,50]
    X = np.stack((x, y), axis=0)
    return X
def get_cov_matrix(X):
    sigma_1=np.cov(X)
    return sigma_1

data_1=generate_data()
get_cov_matrix(data_1)

def multivariate_normal(x, d, mean, covariance):
    """pdf of the multivariate normal distribution."""
    x_m = x - mean
    return (1. / (np.sqrt((2 * np.pi)**d * np.linalg.det(covariance))) * 
            np.exp(-(np.linalg.solve(covariance, x_m).T.dot(x_m)) / 2))


x=generate_data()

np.mean(x[0,:]),np.mean(x[1,:])  #ortalma boy ve kilo

x=generate_data()
np.mean(x[0,:]),np.mean(x[1,:])

x_1=[175,72]
d_1=2

data=generate_data()
mean_1=np.array([np.mean(x[0,:]),np.mean(x[1,:])])
covariance_1=get_cov_matrix(data)
multivariate_normal(x_1,d_1,mean_1,covariance_1)


for i in range(10):
    v=167+i
    x_1=[v,72]
    s=multivariate_normal(x_1,d_1,mean_1,covariance_1)
    print(v,"      ",s)