--- /dev/null
+// Licensed to the .NET Foundation under one or more agreements.
+// The .NET Foundation licenses this file to you under the MIT license.
+// See the LICENSE file in the project root for more information.
+
+using System.Runtime.InteropServices;
+using System.Runtime.CompilerServices;
+using Internal.Runtime.CompilerServices;
+
+namespace System
+{
+ internal static partial class Number
+ {
+ private static unsafe void Dragon4(double value, int precision, ref NumberBuffer number)
+ {
+ // ========================================================================================================================================
+ // This implementation is based on the paper: https://www.cs.indiana.edu/~dyb/pubs/FP-Printing-PLDI96.pdf
+ // Besides the paper, some of the code and ideas are modified from http://www.ryanjuckett.com/programming/printing-floating-point-numbers/
+ // You must read these two materials to fully understand the code.
+ //
+ // Note: we only support fixed format input.
+ // ========================================================================================================================================
+ //
+ // Overview:
+ //
+ // The input double number can be represented as:
+ // value = f * 2^e = r / s.
+ //
+ // f: the output mantissa. Note: f is not the 52 bits mantissa of the input double number.
+ // e: biased exponent.
+ // r: numerator.
+ // s: denominator.
+ // k: value = d0.d1d2 . . . dn * 10^k
+
+ // Step 1:
+ // Extract meta data from the input double value.
+ //
+ // Refer to IEEE double precision floating point format.
+ ulong f = (ulong)(ExtractFractionAndBiasedExponent(value, out int e));
+ int mantissaHighBitIndex = (e == -1074) ? (int)(BigInteger.LogBase2(f)) : 52;
+
+ // Step 2:
+ // Estimate k. We'll verify it and fix any error later.
+ //
+ // This is an improvement of the estimation in the original paper.
+ // Inspired by http://www.ryanjuckett.com/programming/printing-floating-point-numbers/
+ //
+ // LOG10V2 = 0.30102999566398119521373889472449
+ // DRIFT_FACTOR = 0.69 = 1 - log10V2 - epsilon (a small number account for drift of floating point multiplication)
+ int k = (int)(Math.Ceiling(((mantissaHighBitIndex + e) * Log10V2) - DriftFactor));
+
+ // Step 3:
+ // Store the input double value in BigInteger format.
+ //
+ // To keep the precision, we represent the double value as r/s.
+ // We have several optimization based on following table in the paper.
+ //
+ // ----------------------------------------------------------------------------------------------------------
+ // | e >= 0 | e < 0 |
+ // ----------------------------------------------------------------------------------------------------------
+ // | f != b^(P - 1) | f = b^(P - 1) | e = min exp or f != b^(P - 1) | e > min exp and f = b^(P - 1) |
+ // --------------------------------------------------------------------------------------------------------------
+ // | r | f * b^e * 2 | f * b^(e + 1) * 2 | f * 2 | f * b * 2 |
+ // --------------------------------------------------------------------------------------------------------------
+ // | s | 2 | b * 2 | b^(-e) * 2 | b^(-e + 1) * 2 |
+ // --------------------------------------------------------------------------------------------------------------
+ //
+ // Note, we do not need m+ and m- because we only support fixed format input here.
+ // m+ and m- are used for free format input, which need to determine the exact range of values
+ // that would round to value when input so that we can generate the shortest correct number.digits.
+ //
+ // In our case, we just output number.digits until reaching the expected precision.
+
+ var r = new BigInteger(f);
+ var s = new BigInteger(0);
+
+ if (e >= 0)
+ {
+ // When f != b^(P - 1):
+ // r = f * b^e * 2
+ // s = 2
+ // value = r / s = f * b^e * 2 / 2 = f * b^e / 1
+ //
+ // When f = b^(P - 1):
+ // r = f * b^(e + 1) * 2
+ // s = b * 2
+ // value = r / s = f * b^(e + 1) * 2 / b * 2 = f * b^e / 1
+ //
+ // Therefore, we can simply say that when e >= 0:
+ // r = f * b^e = f * 2^e
+ // s = 1
+
+ r.ShiftLeft((uint)(e));
+ s.SetUInt64(1);
+ }
+ else
+ {
+ // When e = min exp or f != b^(P - 1):
+ // r = f * 2
+ // s = b^(-e) * 2
+ // value = r / s = f * 2 / b^(-e) * 2 = f / b^(-e)
+ //
+ // When e > min exp and f = b^(P - 1):
+ // r = f * b * 2
+ // s = b^(-e + 1) * 2
+ // value = r / s = f * b * 2 / b^(-e + 1) * 2 = f / b^(-e)
+ //
+ // Therefore, we can simply say that when e < 0:
+ // r = f
+ // s = b^(-e) = 2^(-e)
+
+ BigInteger.ShiftLeft(1, (uint)(-e), ref s);
+ }
+
+ // According to the paper, we should use k >= 0 instead of k > 0 here.
+ // However, if k = 0, both r and s won't be changed, we don't need to do any operation.
+ //
+ // Following are the Scheme code from the paper:
+ // --------------------------------------------------------------------------------
+ // (if (>= est 0)
+ // (fixup r (* s (exptt B est)) m+ m− est B low-ok? high-ok? )
+ // (let ([scale (exptt B (− est))])
+ // (fixup (* r scale) s (* m+ scale) (* m− scale) est B low-ok? high-ok? ))))
+ // --------------------------------------------------------------------------------
+ //
+ // If est is 0, (* s (exptt B est)) = s, (* r scale) = (* r (exptt B (− est)))) = r.
+ //
+ // So we just skip when k = 0.
+
+ if (k > 0)
+ {
+ BigInteger poweredValue = new BigInteger(0);
+ BigInteger.Pow10((uint)(k), ref poweredValue);
+ s.Multiply(ref poweredValue);
+ }
+ else if (k < 0)
+ {
+ BigInteger poweredValue = new BigInteger(0);
+ BigInteger.Pow10((uint)(-k), ref poweredValue);
+ r.Multiply(ref poweredValue);
+ }
+
+ if (BigInteger.Compare(ref r, ref s) >= 0)
+ {
+ // The estimation was incorrect. Fix the error by increasing 1.
+ k += 1;
+ }
+ else
+ {
+ r.Multiply10();
+ }
+
+ number.scale = (k - 1);
+
+ // This the prerequisite of calling BigInteger.HeuristicDivide().
+ BigInteger.PrepareHeuristicDivide(ref r, ref s);
+
+ // Step 4:
+ // Calculate number.digits.
+ //
+ // Output number.digits until reaching the last but one precision or the numerator becomes zero.
+
+ int digitsNum = 0;
+ int currentDigit = 0;
+
+ while (true)
+ {
+ currentDigit = (int)(BigInteger.HeuristicDivide(ref r, ref s));
+
+ if (r.IsZero() || ((digitsNum + 1) == precision))
+ {
+ break;
+ }
+
+ number.digits[digitsNum] = (char)('0' + currentDigit);
+ digitsNum++;
+
+ r.Multiply10();
+ }
+
+ // Step 5:
+ // Set the last digit.
+ //
+ // We round to the closest digit by comparing value with 0.5:
+ // compare( value, 0.5 )
+ // = compare( r / s, 0.5 )
+ // = compare( r, 0.5 * s)
+ // = compare(2 * r, s)
+ // = compare(r << 1, s)
+
+ r.ShiftLeft(1);
+ int compareResult = BigInteger.Compare(ref r, ref s);
+ bool isRoundDown = compareResult < 0;
+
+ // We are in the middle, round towards the even digit (i.e. IEEE rouding rules)
+ if (compareResult == 0)
+ {
+ isRoundDown = (currentDigit & 1) == 0;
+ }
+
+ if (isRoundDown)
+ {
+ number.digits[digitsNum] = (char)('0' + currentDigit);
+ digitsNum++;
+ }
+ else
+ {
+ char* pCurrentDigit = (number.digits + digitsNum);
+
+ // Rounding up for 9 is special.
+ if (currentDigit == 9)
+ {
+ // find the first non-nine prior digit
+ while (true)
+ {
+ // If we are at the first digit
+ if (pCurrentDigit == number.digits)
+ {
+ // Output 1 at the next highest exponent
+ *pCurrentDigit = '1';
+ digitsNum++;
+ number.scale += 1;
+ break;
+ }
+
+ pCurrentDigit--;
+ digitsNum--;
+
+ if (*pCurrentDigit != '9')
+ {
+ // increment the digit
+ *pCurrentDigit += (char)(1);
+ digitsNum++;
+ break;
+ }
+ }
+ }
+ else
+ {
+ // It's simple if the digit is not 9.
+ *pCurrentDigit = (char)('0' + currentDigit + 1);
+ digitsNum++;
+ }
+ }
+
+ while (digitsNum < precision)
+ {
+ number.digits[digitsNum] = '0';
+ digitsNum++;
+ }
+
+ number.digits[precision] = '\0';
+
+ number.scale++;
+ number.sign = double.IsNegative(value);
+ }
+ }
+}
-// Licensed to the .NET Foundation under one or more agreements.
+// Licensed to the .NET Foundation under one or more agreements.
// The .NET Foundation licenses this file to you under the MIT license.
// See the LICENSE file in the project root for more information.
value /= 1000000000;
return rem;
}
+
+ private static unsafe void DoubleToNumber(double value, int precision, ref NumberBuffer number)
+ {
+ number.precision = precision;
+
+ if (double.GetExponent(value) == 0x7FF)
+ {
+ number.scale = double.IsNaN(value) ? ScaleNAN : ScaleINF;
+ number.sign = double.IsNegative(value);
+ number.digits[0] = '\0';
+ }
+ else if (value == 0.0)
+ {
+ number.scale = 0;
+ number.sign = double.IsNegative(value);
+ number.digits[0] = '\0';
+ }
+ else
+ {
+ Dragon4(value, precision, ref number);
+ }
+ }
+
+ private static long ExtractFractionAndBiasedExponent(double value, out int exponent)
+ {
+ long fraction = double.GetMantissa(value);
+ exponent = double.GetExponent(value);
+
+ if (exponent != 0)
+ {
+ // For normalized value, according to https://en.wikipedia.org/wiki/Double-precision_floating-point_format
+ // value = 1.fraction * 2^(exp - 1023)
+ // = (1 + mantissa / 2^52) * 2^(exp - 1023)
+ // = (2^52 + mantissa) * 2^(exp - 1023 - 52)
+ //
+ // So f = (2^52 + mantissa), e = exp - 1075;
+
+ fraction |= ((long)(1) << 52);
+ exponent -= 1075;
+ }
+ else
+ {
+ // For denormalized value, according to https://en.wikipedia.org/wiki/Double-precision_floating-point_format
+ // value = 0.fraction * 2^(1 - 1023)
+ // = (mantissa / 2^52) * 2^(-1022)
+ // = mantissa * 2^(-1022 - 52)
+ // = mantissa * 2^(-1074)
+ // So f = mantissa, e = -1074
+ exponent = -1074;
+ }
+
+ return fraction;
+ }
}
}
projects / platform / upstream / dotnet / runtime.git / commitdiff