In [3]:

    

##read array x and y
import tensorflow as tf
with tf.name_scope("array_x"):
    x = list()
    n = int(input("Enter input size:"))
    print("Enter x array elements:")
    for i in range(n):
        x.append(float(input()))
        
with tf.name_scope("array_y"):
    y = list()
    #n = int(input("Enter input size:"))
    print("Enter y array elemets:")
    for i in range(n):
        y.append(float(input()))        


    print(x)
    print(y)
    #print(mean_x)
    #print(sess.run(mean_x))
    #writer.close()


    

    




Enter input size:5
Enter x array elements:
3
2
1
3
2
Enter y array elemets:
4
3
2
3
4
[3.0, 2.0, 1.0, 3.0, 2.0]
[4.0, 3.0, 2.0, 3.0, 4.0]

In [4]:

    

##mean of x and y
with tf.name_scope("mean_x"):
    mean_x = tf.reduce_mean(x)
with tf.name_scope("mean_x"):
    mean_y = tf.reduce_mean(y)
sess = tf.Session()
    #writer = tf.summary.FileWriter("/tmp/tboard/output12345", sess.graph)
print(x)
print(y)
print("Mean of x:")
print(sess.run(mean_x))
print("Mean of y:")
print(sess.run(mean_y))
    #writer.close()


    

    




[3.0, 2.0, 1.0, 3.0, 2.0]
[4.0, 3.0, 2.0, 3.0, 4.0]
Mean of x:
2.2
Mean of y:
3.2

In [5]:

    

## variance of x
with tf.name_scope("Variance_x"):
    var_x = tf.constant(0.0)
    for i in range(n):
        a = tf.subtract(x[i],mean_x, name="x_minus_mean_of_x")
        b = tf.square(a, name="square_of_x_minus_mean_of_x")
        var_x = tf.add(var_x,b, name="variance_of_x")
    x_var = tf.realdiv(var_x,n,name="var_x")
#with tf.Session() as sess:

    #writer = tf.summary.FileWriter("/tmp/tboard/output12346", sess.graph)
print(sess.run(x_var))
    #writer.close()


    

    




0.56

In [6]:

    

##covariance of x,y
with tf.name_scope("Covariance"):
    covar_xy = tf.constant(0.0)
    for i in range(n):
        a = tf.subtract(x[i],mean_x)
        b = tf.subtract(y[i],mean_y)
        c = tf.multiply(a,b)
        covar_xy = tf.add(covar_xy,c)
    d = tf.subtract(float(n),1.0)
    covar_xy = tf.realdiv(covar_xy,d, name="cov_of_xy")
    
    print(sess.run(covar_xy))


    

    




0.45

In [8]:

    

## calculate slope:m
with tf.name_scope("m"):
    m = tf.realdiv(covar_xy,x_var)
    print(sess.run(m))


    

    




0.803571

In [9]:

    

## calculate c
with tf.name_scope("c"):
    mx = tf.multiply(m,mean_x)
    c = tf.subtract(mean_y,mx, name="constant_c")
print(sess.run(c))


    

    




1.43214

In [10]:

    

import matplotlib.pyplot as plt
#with tf.Session() as sess:
plt.plot(x,y,"ro")
plt.show()


    

In [11]:

    

plt.plot(x,y)
plt.show()


    

In [ ]: