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# contructor function
tensor <- function(x) {
  # check that it's numeric
  if (!is.numeric(x)) stop("X must be numeric")
  
  # create the array and change the class
  y <- structure(array(x), class = "tensor")
  
  # add attributes
  attributes(y)$creators <- list()

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import numpy as np
import sys

def gen_poly(n,q):
    global xN_1
    l = 0 #Gamma Distribution Location (Mean "center" of dist.)
    poly = np.floor(np.random.normal(l,size=(n)))
    while (len(poly) != n):
        poly = np.floor(np.random.normal(l,size=(n)))
        poly = np.floor(p.polydiv(poly,xN_1)[1]%q)

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# adapted from: https://asecuritysite.com/encryption/lwe4

import sys
import numpy as np
import random
import math

nvals=20
B=[]
e=[]

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# define some functions

# modular exponentiation
# source: https://gist.github.com/ttezel/4635562
function result = modexp (x, y, n)
    %anything raised to 0th power = 1 so return 1
    if (y == 0)
        result = 1;
        return;
    end

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# Author: Bill Buchanan
# source: https://asecuritysite.com/encryption/pal_ex

from random import randint
import sys

def gcd(a,b):
    """Compute the greatest common divisor of a and b"""
    while b > 0:
        a, b = b, a % b

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# Paillier cryptosystem in R
# Bastiaan Quast

# install and load the GNU Multiple Percision Arithmetic R package 
install.packages('gmp')
library(gmp)

# define parameters
# p and q are private to the Inspector
Inspector = list()

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# RSA example 
# 
# Bastiaan Quast
# International Telecommunication Union
# bastiaan.quast@itu.int

# Two people - Alice and Bob - want to communicate privately
# A third person Eve wants to read the private communication
Alice = list()
Bob   = list()

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## sigmoid function
sigmoid <- function(x, k=1, x0=0)
  1 / (1+exp( -k*(x-x0) ))

## tanh^2 function
tanhsq <- function(x)
  ((exp(2*x)-1)^2)/((exp(2*x)+1)^2)

# define weights
Wa = matrix( c(0.45, 0.25), nrow=1 ); Ua = matrix(0.15); ba = matrix(0.20)

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# sigmoid function
sigmoid <- function(x)
  1 / (1 + exp(-x) )

# sigmoid derivative
sigmoid_output_to_derivative <- function(x)
  x*(1-x)

# hidden layer size
hidden_dim = 4

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# define some functions

## convert integer to binary
i2b <- function(integer, length=8)
  as.numeric(intToBits(integer))[1:length]

## apply 
int2bin <- function(integer, length=8)
  t(sapply(integer, i2b, length=length))