# Public domain.

import sys
import random
import signatures
import doublescalarmult

c = 5
# XXX: tune c for b

def multiscalarmult(scalars,points):
  multiples = [False,points]
  for i in range(2,2**c):
    multiples.append([P + Q for P,Q in zip(points,multiples[i - 1])])
  maxscalar = max(scalars)
  i = 0
  while 2**i <= maxscalar:
    i += c
  result = signatures.groupelt(0)
  while i >= c:
    for j in range(c):
      result = result + result
      i -= 1
    for j in range(len(scalars)):
      digit = (scalars[j] >> i) % (2**c)
      if digit > 0:
        result = result + multiples[digit][j]
  return result

def verifybatch(smvector):
  results = []
  randomizers = [random.randrange(2**signatures.b) for i in range(len(smvector))]

  points = [signatures.B]
  scalars = [0]
  for i in range(len(smvector)):
    sm = smvector[i]
    R,S,A,M = sm[0],sm[1],sm[2],sm[3]
    h = signatures.inthash(str(R) + str(A) + M)
    points.append(signatures.groupelt(R))
    scalars.append(randomizers[i])
    points.append(signatures.groupelt(A))
    scalars.append((h * randomizers[i]) % signatures.l)
    scalars[0] = (scalars[0] - S * randomizers[i]) % signatures.l

  if multiscalarmult(scalars,points).x == 0:
    return [True] * len(smvector)

  for sm in smvector:
    R,S,A,M = sm[0],sm[1],sm[2],sm[3]
    h = signatures.inthash(str(R) + str(A) + M)
    checkR = doublescalarmult.doublescalarmult(S,signatures.B,(-h) % signatures.l,signatures.groupelt(A))
    results.append(R == checkR.x)
  return results

signatures.benchmark(verifybatch,int(sys.argv[1]))