def mpfr_to_mpf(f):
ctx = gmpy2.get_context()
p = ctx.precision
# emax = ctx.emax - 1
# emax = (2 ** (w - 1)) - 1
# emax + 1 = 2 ** (w - 1)
# ln2(emax + 1) = w - 1
# w = ln(emax + 1) + 1
# w = ln(ctx.emax) + 1
w = log2(ctx.emax) + 1
assert w.is_integer()
w = int(w)
# w = k - p
# k = w + p
k = w + p
eb = k - p
sb = p
rv = MPF(eb, sb)
if gmpy2.is_nan(f):
rv.set_nan()
elif gmpy2.is_infinite(f):
if gmpy2.sign(f) > 0:
rv.set_infinite(0)
else:
rv.set_infinite(1)
elif gmpy2.is_zero(f):
if str(f) == "-0.0":
rv.set_zero(1)
elif str(f) == "0.0":
rv.set_zero(0)
else:
assert False
else:
a, b = f.as_integer_ratio()
rv.from_rational(RM_RNE, Rational(int(a), int(b)))
assert mpf_to_mpfr(rv) == f
return rv
def build_max_normal(eb, sb, _, sign):
rv = MPF(eb, sb)
rv.pack(sign, 2**rv.w - 2, 2**rv.t - 1)
return rv
def build_one(eb, sb, _, sign):
rv = MPF(eb, sb)
rv.from_rational(RM_RNE, Rational(1))
rv.set_sign_bit(sign)
return rv
def build_rnd_normal_large(eb, sb, rng, sign):
rv = MPF(eb, sb)
rv.pack(sign, rng.random_int(2**(rv.w - 1), 2**rv.w - 2),
rng.random_int(0, 2**rv.t - 1))
return rv
def build_rnd_normal_small(eb, sb, rng, sign):
rv = MPF(eb, sb)
rv.pack(sign, rng.random_int(1, 2**(rv.w - 1)),
rng.random_int(0, 2**rv.t - 1))
return rv
def build_min_normal(eb, sb, _, sign):
rv = MPF(eb, sb)
rv.pack(sign, 1, 0)
return rv
def build_rnd_subnormal(eb, sb, rng, sign):
rv = MPF(eb, sb)
rv.pack(sign, 0, rng.random_int(2, 2**rv.t - 2))
return rv
def build_min_subnormal(eb, sb, _, sign):
rv = MPF(eb, sb)
rv.pack(sign, 0, 1)
return rv
def build_zero(eb, sb, _, sign):
rv = MPF(eb, sb)
rv.set_zero(sign)
return rv
def build_nan(eb, sb, rng):
rv = MPF(eb, sb)
rv.pack(rng.random_int(0, 1), 2**rv.w - 1, rng.random_int(1, 2**rv.t - 1))
return rv
def build_inf(eb, sb, _, sign):
rv = MPF(eb, sb)
rv.pack(sign, 2**rv.w - 1, 0)
return rv