def inverse_function():
print("Testing -- inverse_mod function--")
print("Since this function will raise ValueError easily from random\n"
"generating numbers, we will use three differen pair of numbers\n"
"to test its functionality.")
a = 57
b = 61
tf1 = nmtf.inverse_mod(tf.constant(a), tf.constant(b))
nm1 = nm.inverse_mod(a, b)
print("nmtf.inverse_mod({0}, {1}) = ({2}, {3})".format(
a, b, tf1[0].eval(), tf1[1].eval()))
print(" nm.inverse_mod({0}, {1}) = {2}".format(a, b, nm1))
a = 23
b = 58
tf1 = nmtf.inverse_mod(tf.constant(a), tf.constant(b))
nm1 = nm.inverse_mod(a, b)
print("nmtf.inverse_mod({0}, {1}) = ({2}, {3})".format(
a, b, tf1[0].eval(), tf1[1].eval()))
print(" nm.inverse_mod({0}, {1}) = {2}".format(a, b, nm1))
print("")
print(
"The last pair of numbers will make the normal inverse_mod function\n"
"raise an ValueError. For the tensorflow version, the second parameter\n"
"is 0")
a = 10
b = 34
tf1 = nmtf.inverse_mod(tf.constant(a), tf.constant(b))
#nm1 = nm.inverse_mod(a, b)
print("nmtf.inverse_mod({0}, {1}) = ({2}, {3})".format(
a, b, tf1[0].eval(), tf1[1].eval()))
def reducemat(submat): pivotrow=0 for rj in range(thedegree): # Find the pivot element in this column for ri in range(pivotrow,len(submat)): if (submat[ri][rj] != 0): # Swap rows temp = submat[pivotrow]; submat[pivotrow] = submat[ri]; submat[ri] = temp break else: continue # No pivot in this column - move to next column (for rj) # Subtract multiples of pivot row from lower rows (zeroing out column elts) invpivot = numbthy.inverse_mod(submat[pivotrow][rj],themod) for ri in range(pivotrow+1,len(submat)): rowmult = mod(invpivot*submat[ri][rj],themod) for rjj in range(rj,numcols): submat[ri][rjj] = mod(submat[ri][rjj]-rowmult*submat[pivotrow][rjj],themod) #if not any(themat[i][:thedegree]): return themat[i][thedegree:] pivotrow += 1 # Move down to next row
def reducemat(submat):
pivotrow = 0
for rj in range(thedegree):
# Find the pivot element in this column
for ri in range(pivotrow, len(submat)):
if (submat[ri][rj] != 0):
# Swap rows
temp = submat[pivotrow]
submat[pivotrow] = submat[ri]
submat[ri] = temp
break
else:
continue # No pivot in this column - move to next column (for rj)
# Subtract multiples of pivot row from lower rows (zeroing out column elts)
invpivot = numbthy.inverse_mod(submat[pivotrow][rj], themod)
for ri in range(pivotrow + 1, len(submat)):
rowmult = mod(invpivot * submat[ri][rj], themod)
for rjj in range(rj, numcols):
submat[ri][rjj] = mod(
submat[ri][rjj] - rowmult * submat[pivotrow][rjj],
themod)
#if not any(themat[i][:thedegree]): return themat[i][thedegree:]
pivotrow += 1 # Move down to next row
#5 base 2 in Z13 = 9
#x0 = 2
#x1 = 1
#p=1073676287
#g=1010343267
#h=857348958
#B=pow(2, 10)
#1026831 (*this is the solution*)
#x0 = 1002;
#x1 = 783;
print datetime.datetime.now()
gi = numbthy.inverse_mod(g, p)
gPowB = numbthy.power_mod(g, B, p)
print "p", p
print "g", g
print "h", h
print "B", B
print "inverse g", gi
print "gPowB", gPowB
left = {}
powX1 = h % p
left[powX1] = 0
x1 = 1
def f2(p, g, h, x1):
denom = power_mod(g, x1, p)
return (h * inverse_mod(denom, p)) % p
def DecryptCipher(CipherVal, EncExp, p1, q1):
DecExp = inverse_mod(EncExp, (p1 - 1) * (q1 - 1))
MsgVal = power_mod(CipherVal, DecExp, p1 * q1)
return MsgVal
from numbthy import inverse_mod, power_mod
p = 13407807929942597099574024998205846127479365820592393377723561443721764030073546976801874298166903427690031858186486050853753882811946569946433649006084171
g = 11717829880366207009516117596335367088558084999998952205599979459063929499736583746670572176471460312928594829675428279466566527115212748467589894601965568
h = 3239475104050450443565264378728065788649097520952449527834792452971981976143292558073856937958553180532878928001494706097394108577585732452307673444020333
table = []
B = 2**20
for x1 in range(B + 1):
denominator = inverse_mod(power_mod(g, x1, p), p)
table.append((h * denominator) % p)
for x0 in range(B + 1):
power = B * x0
trial = power_mod(g, power, p)
print 'Try ' + str(x0)
try:
x1 = table.index(trial)
print x0, x1
print x0 * B + x1
break
except ValueError:
continue