EIC code displayed by LXR master/​include/​boost/​charconv/​detail/​fast_float/​decimal_to_binary.hpp	Source navigation Diff markup Identifier search General search
	Version: master test Revert   Change

File indexing completed on 2025-04-19 08:19:37

 // Copyright 2020-2023 Daniel Lemire
 // Copyright 2023 Matt Borland
 // Distributed under the Boost Software License, Version 1.0.
 // https://www.boost.org/LICENSE_1_0.txt
 //
 // Derivative of: https://github.com/fastfloat/fast_float
 
 #ifndef BOOST_CHARCONV_DETAIL_FASTFLOAT_DECIMAL_TO_BINARY_HPP
 #define BOOST_CHARCONV_DETAIL_FASTFLOAT_DECIMAL_TO_BINARY_HPP
 
 #include <boost/charconv/detail/fast_float/float_common.hpp>
 #include <boost/charconv/detail/fast_float/fast_table.hpp>
 #include <cfloat>
 #include <cinttypes>
 #include <cmath>
 #include <cstdint>
 #include <cstdlib>
 #include <cstring>
 
 namespace boost { namespace charconv { namespace detail { namespace fast_float {
 
 // This will compute or rather approximate w * 5**q and return a pair of 64-bit words approximating
 // the result, with the "high" part corresponding to the most significant bits and the
 // low part corresponding to the least significant bits.
 //
 template <int bit_precision>
 BOOST_FORCEINLINE BOOST_CHARCONV_FASTFLOAT_CONSTEXPR20
 value128 compute_product_approximation(int64_t q, uint64_t w) {
   const int index = 2 * int(q - powers::smallest_power_of_five);
   // For small values of q, e.g., q in [0,27], the answer is always exact because
   // The line value128 firstproduct = full_multiplication(w, power_of_five_128[index]);
   // gives the exact answer.
   value128 firstproduct = full_multiplication(w, powers::power_of_five_128[index]);
   static_assert((bit_precision >= 0) && (bit_precision <= 64), " precision should  be in (0,64]");
   constexpr uint64_t precision_mask = (bit_precision < 64) ?
                (uint64_t(0xFFFFFFFFFFFFFFFF) >> bit_precision)
                : uint64_t(0xFFFFFFFFFFFFFFFF);
   if((firstproduct.high & precision_mask) == precision_mask) { // could further guard with  (lower + w < lower)
     // regarding the second product, we only need secondproduct.high, but our expectation is that the compiler will optimize this extra work away if needed.
     value128 secondproduct = full_multiplication(w, powers::power_of_five_128[index + 1]);
     firstproduct.low += secondproduct.high;
     if(secondproduct.high > firstproduct.low) {
       firstproduct.high++;
     }
   }
   return firstproduct;
 }
 
 namespace detail {
 /**
  * For q in (0,350), we have that
  *  f = (((152170 + 65536) * q ) >> 16);
  * is equal to
  *   floor(p) + q
  * where
  *   p = log(5**q)/log(2) = q * log(5)/log(2)
  *
  * For negative values of q in (-400,0), we have that
  *  f = (((152170 + 65536) * q ) >> 16);
  * is equal to
  *   -ceil(p) + q
  * where
  *   p = log(5**-q)/log(2) = -q * log(5)/log(2)
  */
   constexpr BOOST_FORCEINLINE int32_t power(int32_t q)  noexcept  {
     return (((152170 + 65536) * q) >> 16) + 63;
   }
 } // namespace detail
 
 // create an adjusted mantissa, biased by the invalid power2
 // for significant digits already multiplied by 10 ** q.
 template <typename binary>
 BOOST_FORCEINLINE BOOST_CHARCONV_FASTFLOAT_CONSTEXPR14
 adjusted_mantissa compute_error_scaled(int64_t q, uint64_t w, int lz) noexcept  {
   int hilz = int(w >> 63) ^ 1;
   adjusted_mantissa answer;
   answer.mantissa = w << hilz;
   int bias = binary::mantissa_explicit_bits() - binary::minimum_exponent();
   answer.power2 = int32_t(detail::power(int32_t(q)) + bias - hilz - lz - 62 + invalid_am_bias);
   return answer;
 }
 
 // w * 10 ** q, without rounding the representation up.
 // the power2 in the exponent will be adjusted by invalid_am_bias.
 template <typename binary>
 BOOST_FORCEINLINE BOOST_CHARCONV_FASTFLOAT_CONSTEXPR20
 adjusted_mantissa compute_error(int64_t q, uint64_t w)  noexcept  {
   int lz = leading_zeroes(w);
   w <<= lz;
   value128 product = compute_product_approximation<binary::mantissa_explicit_bits() + 3>(q, w);
   return compute_error_scaled<binary>(q, product.high, lz);
 }
 
 // w * 10 ** q
 // The returned value should be a valid ieee64 number that simply need to be packed.
 // However, in some very rare cases, the computation will fail. In such cases, we
 // return an adjusted_mantissa with a negative power of 2: the caller should recompute
 // in such cases.
 template <typename binary>
 BOOST_FORCEINLINE BOOST_CHARCONV_FASTFLOAT_CONSTEXPR20
 adjusted_mantissa compute_float(int64_t q, uint64_t w)  noexcept  {
   adjusted_mantissa answer;
   if ((w == 0) || (q < binary::smallest_power_of_ten())) {
     answer.power2 = 0;
     answer.mantissa = 0;
     // result should be zero
     return answer;
   }
   if (q > binary::largest_power_of_ten()) {
     // we want to get infinity:
     answer.power2 = binary::infinite_power();
     answer.mantissa = 0;
     return answer;
   }
   // At this point in time q is in [powers::smallest_power_of_five, powers::largest_power_of_five].
 
   // We want the most significant bit of i to be 1. Shift if needed.
   int lz = leading_zeroes(w);
   w <<= lz;
 
   // The required precision is binary::mantissa_explicit_bits() + 3 because
   // 1. We need the implicit bit
   // 2. We need an extra bit for rounding purposes
   // 3. We might lose a bit due to the "upperbit" routine (result too small, requiring a shift)
 
   value128 product = compute_product_approximation<binary::mantissa_explicit_bits() + 3>(q, w);
   // The computed 'product' is always sufficient.
   // Mathematical proof:
   // Noble Mushtak and Daniel Lemire, Fast Number Parsing Without Fallback (to appear)
   // See script/mushtak_lemire.py
 
   // The "compute_product_approximation" function can be slightly slower than a branchless approach:
   // value128 product = compute_product(q, w);
   // but in practice, we can win big with the compute_product_approximation if its additional branch
   // is easily predicted. Which is best is data specific.
   int upperbit = int(product.high >> 63);
 
   answer.mantissa = product.high >> (upperbit + 64 - binary::mantissa_explicit_bits() - 3);
 
   answer.power2 = int32_t(detail::power(int32_t(q)) + upperbit - lz - binary::minimum_exponent());
   if (answer.power2 <= 0) { // we have a subnormal?
     // Here have that answer.power2 <= 0 so -answer.power2 >= 0
     if(-answer.power2 + 1 >= 64) { // if we have more than 64 bits below the minimum exponent, you have a zero for sure.
       answer.power2 = 0;
       answer.mantissa = 0;
       // result should be zero
       return answer;
     }
     // next line is safe because -answer.power2 + 1 < 64
     answer.mantissa >>= -answer.power2 + 1;
     // Thankfully, we can't have both "round-to-even" and subnormals because
     // "round-to-even" only occurs for powers close to 0.
     answer.mantissa += (answer.mantissa & 1); // round up
     answer.mantissa >>= 1;
     // There is a weird scenario where we don't have a subnormal but just.
     // Suppose we start with 2.2250738585072013e-308, we end up
     // with 0x3fffffffffffff x 2^-1023-53 which is technically subnormal
     // whereas 0x40000000000000 x 2^-1023-53  is normal. Now, we need to round
     // up 0x3fffffffffffff x 2^-1023-53  and once we do, we are no longer
     // subnormal, but we can only know this after rounding.
     // So we only declare a subnormal if we are smaller than the threshold.
     answer.power2 = (answer.mantissa < (uint64_t(1) << binary::mantissa_explicit_bits())) ? 0 : 1;
     return answer;
   }
 
   // usually, we round *up*, but if we fall right in between and and we have an
   // even basis, we need to round down
   // We are only concerned with the cases where 5**q fits in single 64-bit word.
   if ((product.low <= 1) &&  (q >= binary::min_exponent_round_to_even()) && (q <= binary::max_exponent_round_to_even()) &&
       ((answer.mantissa & 3) == 1) ) { // we may fall between two floats!
     // To be in-between two floats we need that in doing
     //   answer.mantissa = product.high >> (upperbit + 64 - binary::mantissa_explicit_bits() - 3);
     // ... we dropped out only zeroes. But if this happened, then we can go back!!!
     if((answer.mantissa  << (upperbit + 64 - binary::mantissa_explicit_bits() - 3)) ==  product.high) {
       answer.mantissa &= ~uint64_t(1);          // flip it so that we do not round up
     }
   }
 
   answer.mantissa += (answer.mantissa & 1); // round up
   answer.mantissa >>= 1;
   if (answer.mantissa >= (uint64_t(2) << binary::mantissa_explicit_bits())) {
     answer.mantissa = (uint64_t(1) << binary::mantissa_explicit_bits());
     answer.power2++; // undo previous addition
   }
 
   answer.mantissa &= ~(uint64_t(1) << binary::mantissa_explicit_bits());
   if (answer.power2 >= binary::infinite_power()) { // infinity
     answer.power2 = binary::infinite_power();
     answer.mantissa = 0;
   }
   return answer;
 }
 
 }}}} // namespace fast_float
 
 #endif

This page was automatically generated by the 2.3.7 LXR engine. The LXR team