public static DiyFp Normalize(ref DiyFp a)
{
DiyFp result = a;
result.Normalize();
return(result);
}
// Reads a DiyFp from the buffer.
// The returned DiyFp is not necessarily normalized.
// If remaining_decimals is zero then the returned DiyFp is accurate.
// Otherwise it has been rounded and has error of at most 1/2 ulp.
static void ReadDiyFp(Vector buffer,
out DiyFp result,
out int remaining_decimals)
{
int read_digits;
uint64_t significand = ReadUint64(buffer, out read_digits);
if (buffer.length() == read_digits)
{
result = new DiyFp(significand, 0);
remaining_decimals = 0;
}
else
{
// Round the significand.
if (buffer[read_digits] >= '5')
{
significand++;
}
// Compute the binary exponent.
int exponent = 0;
result = new DiyFp(significand, exponent);
remaining_decimals = buffer.length() - read_digits;
}
}
public static void GetCachedPowerForDecimalExponent(int requested_exponent,
out DiyFp power,
out int found_exponent)
{
int index = (requested_exponent + kCachedPowersOffset) / kDecimalExponentDistance;
CachedPower cached_power = kCachedPowers[index];
power = new DiyFp(cached_power.significand, cached_power.binary_exponent);
found_exponent = cached_power.decimal_exponent;
}
public static void GetCachedPowerForBinaryExponentRange(
int min_exponent,
int max_exponent,
out DiyFp power,
out int decimal_exponent)
{
int kQ = DiyFp.kSignificandSize;
double k = Math.Ceiling((min_exponent + kQ - 1) * kD_1_LOG2_10);
int foo = kCachedPowersOffset;
int index = (foo + (int)(k) - 1) / kDecimalExponentDistance + 1;
CachedPower cached_power = kCachedPowers[index];
// (void)max_exponent; // Mark variable as used.
decimal_exponent = cached_power.decimal_exponent;
power = new DiyFp(cached_power.significand, cached_power.binary_exponent);
}
// Computes the two boundaries of this.
// The bigger boundary (m_plus) is normalized. The lower boundary has the same
// exponent as m_plus.
// Precondition: the value encoded by this Single must be greater than 0.
public void NormalizedBoundaries(out DiyFp out_m_minus, out DiyFp out_m_plus)
{
DiyFp v = this.AsDiyFp();
var __ = new DiyFp((v.f << 1) + 1, v.e - 1);
DiyFp m_plus = DiyFp.Normalize(ref __);
DiyFp m_minus;
if (LowerBoundaryIsCloser())
{
m_minus = new DiyFp((v.f << 2) - 1, v.e - 2);
}
else
{
m_minus = new DiyFp((v.f << 1) - 1, v.e - 1);
}
m_minus.f = (m_minus.f << (m_minus.e - m_plus.e));
m_minus.e = (m_plus.e);
out_m_plus = m_plus;
out_m_minus = m_minus;
}
public static ulong DiyFpToUint64(DiyFp diy_fp)
{
ulong significand = diy_fp.f;
int exponent = diy_fp.e;
while (significand > kHiddenBit + kSignificandMask)
{
significand >>= 1;
exponent++;
}
if (exponent >= kMaxExponent)
{
return(kInfinity);
}
if (exponent < kDenormalExponent)
{
return(0);
}
while (exponent > kDenormalExponent && (significand & kHiddenBit) == 0)
{
significand <<= 1;
exponent--;
}
ulong biased_exponent;
if (exponent == kDenormalExponent && (significand & kHiddenBit) == 0)
{
biased_exponent = 0;
}
else
{
biased_exponent = (ulong)(exponent + kExponentBias);
}
return((significand & kSignificandMask) |
(biased_exponent << kPhysicalSignificandSize));
}
// this = this - other.
// The exponents of both numbers must be the same and the significand of this
// must be bigger than the significand of other.
// The result will not be normalized.
public void Subtract(ref DiyFp other)
{
f -= other.f;
}
public Double(DiyFp d)
{
d64_ = DiyFpToUint64(d);
}
// If the function returns true then the result is the correct double.
// Otherwise it is either the correct double or the double that is just below
// the correct double.
static bool DiyFpStrtod(Vector buffer,
int exponent,
out double result)
{
DiyFp input;
int remaining_decimals;
ReadDiyFp(buffer, out input, out remaining_decimals);
// Since we may have dropped some digits the input is not accurate.
// If remaining_decimals is different than 0 than the error is at most
// .5 ulp (unit in the last place).
// We don't want to deal with fractions and therefore keep a common
// denominator.
const int kDenominatorLog = 3;
const int kDenominator = 1 << kDenominatorLog;
// Move the remaining decimals into the exponent.
exponent += remaining_decimals;
uint64_t error = (ulong)(remaining_decimals == 0 ? 0 : kDenominator / 2);
int old_e = input.e;
input.Normalize();
error <<= old_e - input.e;
if (exponent < PowersOfTenCache.kMinDecimalExponent)
{
result = 0.0;
return(true);
}
DiyFp cached_power;
int cached_decimal_exponent;
PowersOfTenCache.GetCachedPowerForDecimalExponent(exponent,
out cached_power,
out cached_decimal_exponent);
if (cached_decimal_exponent != exponent)
{
int adjustment_exponent = exponent - cached_decimal_exponent;
DiyFp adjustment_power = AdjustmentPowerOfTen(adjustment_exponent);
input.Multiply(ref adjustment_power);
if (kMaxUint64DecimalDigits - buffer.length() >= adjustment_exponent)
{
// The product of input with the adjustment power fits into a 64 bit
// integer.
}
else
{
// The adjustment power is exact. There is hence only an error of 0.5.
error += kDenominator / 2;
}
}
input.Multiply(ref cached_power);
// The error introduced by a multiplication of a*b equals
// error_a + error_b + error_a*error_b/2^64 + 0.5
// Substituting a with 'input' and b with 'cached_power' we have
// error_b = 0.5 (all cached powers have an error of less than 0.5 ulp),
// error_ab = 0 or 1 / kDenominator > error_a*error_b/ 2^64
int error_b = kDenominator / 2;
int error_ab = (error == 0 ? 0 : 1); // We round up to 1.
int fixed_error = kDenominator / 2;
error += (ulong)(error_b + error_ab + fixed_error);
old_e = input.e;
input.Normalize();
error <<= old_e - input.e;
// See if the double's significand changes if we add/subtract the error.
int order_of_magnitude = DiyFp.kSignificandSize + input.e;
int effective_significand_size = Double.SignificandSizeForOrderOfMagnitude(order_of_magnitude);
int precision_digits_count = DiyFp.kSignificandSize - effective_significand_size;
if (precision_digits_count + kDenominatorLog >= DiyFp.kSignificandSize)
{
// This can only happen for very small denormals. In this case the
// half-way multiplied by the denominator exceeds the range of an uint64.
// Simply shift everything to the right.
int shift_amount = (precision_digits_count + kDenominatorLog) -
DiyFp.kSignificandSize + 1;
input.f = (input.f >> shift_amount);
input.e = (input.e + shift_amount);
// We add 1 for the lost precision of error, and kDenominator for
// the lost precision of input.f().
error = (error >> shift_amount) + 1 + kDenominator;
precision_digits_count -= shift_amount;
}
// We use uint64_ts now. This only works if the DiyFp uses uint64_ts too.
uint64_t one64 = 1;
uint64_t precision_bits_mask = (one64 << precision_digits_count) - 1;
uint64_t precision_bits = input.f & precision_bits_mask;
uint64_t half_way = one64 << (precision_digits_count - 1);
precision_bits *= kDenominator;
half_way *= kDenominator;
DiyFp rounded_input = new DiyFp(input.f >> precision_digits_count, input.e + precision_digits_count);
if (precision_bits >= half_way + error)
{
rounded_input.f = (rounded_input.f + 1);
}
// If the last_bits are too close to the half-way case than we are too
// inaccurate and round down. In this case we return false so that we can
// fall back to a more precise algorithm.
result = new Double(rounded_input).value();
if (half_way - error < precision_bits && precision_bits < half_way + error)
{
// Too imprecise. The caller will have to fall back to a slower version.
// However the returned number is guaranteed to be either the correct
// double, or the next-lower double.
return(false);
}
else
{
return(true);
}
}