def __init__(
self,
curvemodel,
prime,
formula,
style,
exponent,
tuned,
multievaluation,
uninitialized,
verbose,
):
self.curvemodel = curvemodel
self.prime = prime
self.style = style
self._exponent = exponent
self.tuned = tuned
self.uninitialized = uninitialized
self.multievaluation = multievaluation
self.params = attrdict(parameters['csidh'][prime])
self.params.update(self.params[style])
self.p_bytes = (self.params.p_bits + 8 - (self.params.p_bits % 8)) // 8
if self.curvemodel == 'montgomery':
self.isogeny = MontgomeryIsogeny(formula,
uninitialized=self.uninitialized)
self.curve = MontgomeryCurve(prime)
self.field = self.curve.field
else:
self.curve = None
raise NotImplemented
self.formula = self.isogeny(self.curve, self.tuned,
self.multievaluation)
if self.style == 'df':
self.gae = Gae_df(prime, self.tuned, self.curve, self.formula)
elif self.style == 'wd1':
self.gae = Gae_wd1(prime, self.tuned, self.curve, self.formula)
elif self.style == 'wd2':
self.gae = Gae_wd2(prime, self.tuned, self.curve, self.formula)
else:
self.gae = NotImplemented
def __init__(
self,
curvemodel,
prime,
formula,
tuned,
multievaluation,
uninitialized,
verbose
):
self.params = attrdict(parameters['bsidh'][prime])
self.p_bytes = (self.params.p_bits + (self.params.p_bits % 8)) // 8
self.prime = prime
self.tuned = tuned
self.uninitialized = uninitialized
self.multievaluation = multievaluation
self.verbose = verbose
random = SystemRandom()
if curvemodel == 'montgomery':
self.isogeny = MontgomeryIsogeny(formula, uninitialized = self.uninitialized)
self.curve = MontgomeryCurve(prime)
self.field = self.curve.field
self.basefield = self.curve.field.basefield
else:
self.curve = None
raise NotImplemented
self.formula = self.isogeny(self.curve, self.tuned, self.multievaluation)
if self.formula is not None and self.curve is not None:
self.strategy = Strategy(prime, self.tuned, self.curve, self.formula)
else:
self.strategy = None
raise NotImplemented