def reconstruct_polynomial(alpha, poly_alpha, field_value=257):
temp_poly = Polynomial([0])
t = len(alpha)
for i in range(t):
poly = Polynomial([1])
temp_prod = 1
alpha_i = alpha[i]
for j in range(t):
if (i != j):
poly = poly.multiply(
Polynomial([1, (field_value - alpha[j]) % field_value]))
temp_prod = temp_prod * (
(alpha_i - alpha[j] + field_value) % field_value)
temp_prod %= field_value
poly = poly.divide_by_constant(temp_prod)
poly = poly.multiply(Polynomial([poly_alpha[i]]))
temp_poly = temp_poly.add(poly)
return temp_poly
def generate_shadow_images(self, store_shadows = True):
print ("Encryption begins!")
img_info = self.img_info
n, t, k = self.n, self.t, self.k
alpha = self.alpha
e = self.e
poly_q = self.poly_q
shadow_image_size = None
shadow_images = []
for i in range(n):
print ("Shadow Image no :- {}".format(i))
x_secrets = []
y_secrets = []
lagrange = get_Lagrange_Polynomials(e)
prod_fun = get_prod_funs(e)
temp_poly = Polynomial(poly_q)
temp_poly = temp_poly.multiply(prod_fun)
if self.debug == True:
#For debugging whether the first term of the generated polynomial is correct
for mmm in range(len(e)):
value = temp_poly.eval(e[mmm])
if value != 0:
raise ValueError("First term of the encrypting polynomial is wrong")
quit()
#For debugging whether the generated Lagrange Polynomial is correct
for nnn in range(len(e)):
for j in range(len(lagrange)):
if nnn != j:
if (lagrange[j].eval(e[nnn]) != 0):
raise ValueError("Lagrange Polynmial is wrong")
else:
if (lagrange[j].eval(e[nnn]) != 1):
raise ValueError("Lagrange Polynomial is wrong")
for x in img_info.keys():
for y in range(len(img_info[x][1])):
bar = img_info[x][1][y]
sum_polyx = Polynomial([0])
sum_polyy = Polynomial([0])
for u in range(k):
s_x = img_info[x][1][y][u][0]
s_y = img_info[x][1][y][u][1]
tempx = (lagrange[u]).multiply(Polynomial([s_x]))
tempy = (lagrange[u]).multiply(Polynomial([s_y]))
sum_polyx = sum_polyx.add(tempx)
sum_polyy = sum_polyy.add(tempy)
x_poly = temp_poly.add(sum_polyx)
y_poly = temp_poly.add(sum_polyy)
x_secrets += [x_poly.eval(alpha[i])]
y_secrets += [y_poly.eval(alpha[i])]
temp_shadow = x_secrets + y_secrets
if (shadow_image_size is None):
temp_size = len(temp_shadow)
while(1):
if (floor(sqrt(temp_size)) == ceil(sqrt(temp_size))):
break
else:
temp_size += 1
shadow_image_size = temp_size
temp_shadow = temp_shadow + [np.random.randint(0, 256) for u in range(len(x_secrets + y_secrets), shadow_image_size)]
temp_shadow = np.array(temp_shadow).astype(int)
temp_shadow = temp_shadow.reshape((int(sqrt(shadow_image_size)), int(sqrt(shadow_image_size))))
invalid_positions = []
for x in range(temp_shadow.shape[0]):
for y in range(temp_shadow.shape[1]):
if temp_shadow[x, y] == 256:
invalid_positions += [(x, y)]
temp_shadow[x, y] = 255
if store_shadows == True:
cv2.imwrite("Shadows/{}.jpg".format(i), temp_shadow)
shadow_images += [(temp_shadow, invalid_positions)]
print ("Encryption ends!")
return shadow_images
from Polynomial import Polynomial from Monomial import Monomial from LinearInterpolater import LinearInterpolator # polynomial mon0 = Monomial(1, 2) mon1 = Monomial(1, 1) mon2 = Monomial(-1, 0) pol0 = Polynomial([mon0, mon1]) pol0.add(mon2) pol1 = Polynomial([Monomial(1, 2), Monomial(1, 0)]) print(pol0.pretty_print()) print(pol0.print_eval(5)) print(pol0 - pol1) print(pol1 * pol0) #linear interpolation x = list(range(0, 10)) li = LinearInterpolator(x, [i**2 for i in x])
from itertools import zip_longest
from EducationEmployee import EducationEmployee
from Polynomial import Polynomial
from ScienceEmployee import ScienceEmployee
from Student import Student
if __name__ == '__main__':
p = Polynomial(1, -2, 2) # this is 1 - 2x + 2x^2
p2 = Polynomial(1, 0, 5) # this is 1 + 5x^2
print(p(3))
print(p + p2)
print(p.add(p2))
print(p - p2)
print(p * p2)
(p2 * p).print_polynomial() # more "mathematical" way of print
print(bool(p(3)))
print("###############################")
student = Student("Ania", "Urban", "*****@*****.**", "298005",
{'history': 4})
student2 = Student("Beata", "Kozidrak", "*****@*****.**", "298006")
scienceEmployee = ScienceEmployee("Jakub", "Nowak",
"*****@*****.**", 412,
["First publication"])
educationEmployee = EducationEmployee('Adam', 'Radosny',
'*****@*****.**', 523,
{'Friday': '14;00 - '
'15;00'})
scienceEmployee.add_publication("some publication")
educationEmployee.add_learning_subject("history")
