Hugging Face's logo

Spaces:
aagoluoglu
/
AI-Midterm-IDNN
Build error

App Files Community
AI-Midterm-IDNN
File size: 2,158 Bytes 
96283ff
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
 
import numpy as np
num = 1
def KL(a, b):
    """Calculate the Kullback Leibler divergence between a and b """
    D_KL = np.nansum(np.multiply(a, np.log(np.divide(a, b+np.spacing(1)))), axis=1)
    return D_KL


def calc_information(probTgivenXs, PYgivenTs, PXs, PYs):
    """Calculate the MI - I(X;T) and I(Y;T)"""
    PTs = np.nansum(probTgivenXs*PXs, axis=1)
    Ht = np.nansum(-np.dot(PTs, np.log2(PTs)))
    Htx = - np.nansum((np.dot(np.multiply(probTgivenXs, np.log2(probTgivenXs)), PXs)))
    Hyt = - np.nansum(np.dot(PYgivenTs*np.log2(PYgivenTs+np.spacing(1)), PTs))
    Hy = np.nansum(-PYs * np.log2(PYs+np.spacing(1)))
    IYT = Hy - Hyt
    ITX = Ht - Htx
    return ITX, IYT

def calc_information_1(probTgivenXs, PYgivenTs, PXs, PYs, PTs):
    """Calculate the MI - I(X;T) and I(Y;T)"""
    #PTs = np.nansum(probTgivenXs*PXs, axis=1)
    Ht = np.nansum(-np.dot(PTs, np.log2(PTs+np.spacing(1))))
    Htx = - np.nansum((np.dot(np.multiply(probTgivenXs, np.log2(probTgivenXs+np.spacing(1))), PXs)))
    Hyt = - np.nansum(np.dot(PYgivenTs*np.log2(PYgivenTs+np.spacing(1)), PTs))
    Hy = np.nansum(-PYs * np.log2(PYs+np.spacing(1)))
    IYT = Hy - Hyt
    ITX = Ht - Htx
    return ITX, IYT

def calc_information(probTgivenXs, PYgivenTs, PXs, PYs, PTs):
    """Calculate the MI - I(X;T) and I(Y;T)"""
    #PTs = np.nansum(probTgivenXs*PXs, axis=1)
    t_indeces = np.nonzero(PTs)
    Ht = np.nansum(-np.dot(PTs, np.log2(PTs+np.spacing(1))))
    Htx = - np.nansum((np.dot(np.multiply(probTgivenXs, np.log2(probTgivenXs)), PXs)))
    Hyt = - np.nansum(np.dot(PYgivenTs*np.log2(PYgivenTs+np.spacing(1)), PTs))
    Hy = np.nansum(-PYs * np.log2(PYs+np.spacing(1)))

    IYT = Hy - Hyt
    ITX = Ht - Htx

    return ITX, IYT


def t_calc_information(p_x_given_t, PYgivenTs, PXs, PYs):
    """Calculate the MI - I(X;T) and I(Y;T)"""
    Hx = np.nansum(-np.dot(PXs, np.log2(PXs)))
    Hxt = - np.nansum((np.dot(np.multiply(p_x_given_t, np.log2(p_x_given_t)), PXs)))
    Hyt = - np.nansum(np.dot(PYgivenTs*np.log2(PYgivenTs+np.spacing(1)), PTs))
    Hy = np.nansum(-PYs * np.log2(PYs+np.spacing(1)))
    IYT = Hy - Hyt
    ITX = Hx - Hxt
    return ITX, IYT