Module: Flt::DecNum::AuxiliarFunctions

Included in:
Flt::DecNum
Defined in:
lib/flt/dec_num.rb

Overview

:nodoc:

Constant Summary

LOG10_LB_CORRECTION =

(1..9).map_hash{|i| 100 - (100*Math.log10(i)).floor}

{ # (1..9).map_hash{|i| 100 - (100*Math.log10(i)).floor}
'1'=> 100, '2'=> 70, '3'=> 53, '4'=> 40, '5'=> 31,
'6'=> 23, '7'=> 16, '8'=> 10, '9'=> 5}
NUMBER_OF_DIGITS_MAX_VALID_LOG =
10**(Float::DIG-1)

Class Attribute Summary (collapse)

Class Method Summary (collapse)

Class Attribute Details

+ (Object) log10_digits

Returns the value of attribute log10_digits



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# File 'lib/flt/dec_num.rb', line 1122

def log10_digits
  @log10_digits
end

Class Method Details

+ (Object) _dexp(c, e, p)

Compute an approximation to exp(c*10**e), with p decimal places of precision. Returns integers d, f such that:

10**(p-1) <= d <= 10**p, and
(d-1)*10**f < exp(c*10**e) < (d+1)*10**f

In other words, d*10**f is an approximation to exp(c*10**e) with p digits of precision, and with an error in d of at most 1. This is almost, but not quite, the same as the error being < 1ulp: when d

10**(p-1) the error could be up to 10 ulp.



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# File 'lib/flt/dec_num.rb', line 874

def _dexp(c, e, p)
    # we'll call iexp with M = 10**(p+2), giving p+3 digits of precision
    p += 2

    # compute log(10) with extra precision = adjusted exponent of c*10**e
    # TODO: without the .abs tests fail because c is negative: c should not be negative!!
    extra = [0, e + _number_of_digits(c.abs) - 1].max
    q = p + extra

    # compute quotient c*10**e/(log(10)) = c*10**(e+q)/(log(10)*10**q),
    # rounding down
    shift = e+q
    if shift >= 0
        cshift = c*10**shift
    else
        cshift = c/10**-shift
    end
    quot, rem = cshift.divmod(_log10_digits(q))

    # reduce remainder back to original precision
    rem = _div_nearest(rem, 10**extra)

    # error in result of _iexp < 120;  error after division < 0.62
    return _div_nearest(_iexp(rem, 10**p), 1000), quot - p + 3
end

+ (Object) _div_nearest(a, b)

Closest integer to a/b, a and b positive integers; rounds to even in the case of a tie.



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# File 'lib/flt/dec_num.rb', line 902

def _div_nearest(a, b)
  q, r = a.divmod(b)
  q + (((2*r + (q&1)) > b) ? 1 : 0)
end

+ (Object) _dlog(c, e, p)

Given integers c, e and p with c > 0, compute an integer approximation to 10**p * log(c*10**e), with an absolute error of at most 1. Assumes that c*10**e is not exactly 1.



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# File 'lib/flt/dec_num.rb', line 1033

def _dlog(c, e, p)

    # Increase precision by 2. The precision increase is compensated
    # for at the end with a division by 100.
    p += 2

    # rewrite c*10**e as d*10**f with either f >= 0 and 1 <= d <= 10,
    # or f <= 0 and 0.1 <= d <= 1.  Then we can compute 10**p * log(c*10**e)
    # as 10**p * log(d) + 10**p*f * log(10).
    l = _number_of_digits(c)
    f = e+l - ((e+l >= 1) ? 1 : 0)

    # compute approximation to 10**p*log(d), with error < 27
    if p > 0
        k = e+p-f
        if k >= 0
            c *= 10**k
        else
            c = _div_nearest(c, 10**-k)  # error of <= 0.5 in c
        end

        # _ilog magnifies existing error in c by a factor of at most 10
        log_d = _ilog(c, 10**p) # error < 5 + 22 = 27
    else
        # p <= 0: just approximate the whole thing by 0; error < 2.31
        log_d = 0
    end

    # compute approximation to f*10**p*log(10), with error < 11.
    if f
        extra = _number_of_digits(f.abs) - 1
        if p + extra >= 0
            # error in f * _log10_digits(p+extra) < |f| * 1 = |f|
            # after division, error < |f|/10**extra + 0.5 < 10 + 0.5 < 11
            f_log_ten = _div_nearest(f*_log10_digits(p+extra), 10**extra)
        else
            f_log_ten = 0
        end
    else
        f_log_ten = 0
    end

    # error in sum < 11+27 = 38; error after division < 0.38 + 0.5 < 1
    return _div_nearest(f_log_ten + log_d, 100)
end

+ (Object) _dlog10(c, e, p)

Given integers c, e and p with c > 0, p >= 0, compute an integer approximation to 10**p * log10(c*10**e), with an absolute error of at most 1. Assumes that c*10**e is not exactly 1.



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# File 'lib/flt/dec_num.rb', line 988

def _dlog10(c, e, p)
   # increase precision by 2; compensate for this by dividing
  # final result by 100
  p += 2

  # write c*10**e as d*10**f with either:
  #   f >= 0 and 1 <= d <= 10, or
  #   f <= 0 and 0.1 <= d <= 1.
  # Thus for c*10**e close to 1, f = 0
  l = _number_of_digits(c)
  f = e+l - ((e+l >= 1) ? 1 : 0)

  if p > 0
    m = 10**p
    k = e+p-f
    if k >= 0
      c *= 10**k
    else
      c = _div_nearest(c, 10**-k)
    end
    log_d = _ilog(c, m) # error < 5 + 22 = 27
    log_10 = _log10_digits(p) # error < 1
    log_d = _div_nearest(log_d*m, log_10)
    log_tenpower = f*m # exact
  else
    log_d = 0  # error < 2.31
    log_tenpower = _div_nearest(f, 10**-p) # error < 0.5
  end

  return _div_nearest(log_tenpower+log_d, 100)
end

+ (Object) _dpower(xc, xe, yc, ye, p)

Given integers xc, xe, yc and ye representing Decimals x = xc*10**xe and y = yc*10**ye, compute x**y. Returns a pair of integers (c, e) such that:

10**(p-1) <= c <= 10**p, and
(c-1)*10**e < x**y < (c+1)*10**e

in other words, c*10**e is an approximation to x**y with p digits of precision, and with an error in c of at most 1. (This is almost, but not quite, the same as the error being < 1ulp: when c

10**(p-1) we can only guarantee error < 10ulp.)

We assume that: x is positive and not equal to 1, and y is nonzero.



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# File 'lib/flt/dec_num.rb', line 832

def _dpower(xc, xe, yc, ye, p)
  # Find b such that 10**(b-1) <= |y| <= 10**b
  b = _number_of_digits(yc.abs) + ye

  # log(x) = lxc*10**(-p-b-1), to p+b+1 places after the decimal point
  lxc = _dlog(xc, xe, p+b+1)

  # compute product y*log(x) = yc*lxc*10**(-p-b-1+ye) = pc*10**(-p-1)
  shift = ye-b
  if shift >= 0
      pc = lxc*yc*10**shift
  else
      pc = _div_nearest(lxc*yc, 10**-shift)
  end

  if pc == 0
      # we prefer a result that isn't exactly 1; this makes it
      # easier to compute a correctly rounded result in __pow__
      if (_number_of_digits(xc) + xe >= 1) == (yc > 0) # if x**y > 1:
          coeff, exp = 10**(p-1)+1, 1-p
      else
          coeff, exp = 10**p-1, -p
      end
  else
      coeff, exp = _dexp(pc, -(p+1), p+1)
      coeff = _div_nearest(coeff, 10)
      exp += 1
  end

  return coeff, exp
end

+ (Object) _iexp(x, m, l = 8)

Given integers x and M, M > 0, such that x/M is small in absolute value, compute an integer approximation to M*exp(x/M). For 0 <= x/M <= 2.4, the absolute error in the result is bounded by 60 (and is usually much smaller).



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# File 'lib/flt/dec_num.rb', line 1083

def _iexp(x, m, l=8)

    # Algorithm: to compute exp(z) for a real number z, first divide z
    # by a suitable power R of 2 so that |z/2**R| < 2**-L.  Then
    # compute expm1(z/2**R) = exp(z/2**R) - 1 using the usual Taylor
    # series
    #
    #     expm1(x) = x + x**2/2! + x**3/3! + ...
    #
    # Now use the identity
    #
    #     expm1(2x) = expm1(x)*(expm1(x)+2)
    #
    # R times to compute the sequence expm1(z/2**R),
    # expm1(z/2**(R-1)), ... , exp(z/2), exp(z).

    # Find R such that x/2**R/M <= 2**-L
    r = _nbits((x<<l)/m)

    # Taylor series.  (2**L)**T > M
    t = -(-10*_number_of_digits(m)/(3*l)).to_i
    y = _div_nearest(x, t)
    mshift = m<<r
    (1...t).to_a.reverse.each do |i|
        y = _div_nearest(x*(mshift + y), mshift * i)
    end

    # Expansion
    (0...r).to_a.reverse.each do |k|
        mshift = m<<(k+2)
        y = _div_nearest(y*(y+mshift), mshift)
    end

    return m+y
end

+ (Object) _ilog(x, m, l = 8)

Integer approximation to M*log(x/M), with absolute error boundable in terms only of x/M.

Given positive integers x and M, return an integer approximation to M * log(x/M). For L = 8 and 0.1 <= x/M <= 10 the difference between the approximation and the exact result is at most 22. For L = 8 and 1.0 <= x/M <= 10.0 the difference is at most 15. In both cases these are upper bounds on the error; it will usually be much smaller.



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# File 'lib/flt/dec_num.rb', line 941

def _ilog(x, m, l = 8)
  # The basic algorithm is the following: let log1p be the function
  # log1p(x) = log(1+x).  Then log(x/M) = log1p((x-M)/M).  We use
  # the reduction
  #
  #    log1p(y) = 2*log1p(y/(1+sqrt(1+y)))
  #
  # repeatedly until the argument to log1p is small (< 2**-L in
  # absolute value).  For small y we can use the Taylor series
  # expansion
  #
  #    log1p(y) ~ y - y**2/2 + y**3/3 - ... - (-y)**T/T
  #
  # truncating at T such that y**T is small enough.  The whole
  # computation is carried out in a form of fixed-point arithmetic,
  # with a real number z being represented by an integer
  # approximation to z*M.  To avoid loss of precision, the y below
  # is actually an integer approximation to 2**R*y*M, where R is the
  # number of reductions performed so far.

  y = x-m
  # argument reduction; R = number of reductions performed
  r = 0
  # while (r <= l && y.abs << l-r >= m ||
  #        r > l and y.abs>> r-l >= m)
  while (((r <= l) && ((y.abs << (l-r)) >= m)) ||
         ((r > l) && ((y.abs>>(r-l)) >= m)))
      y = _div_nearest((m*y) << 1,
                       m + _sqrt_nearest(m*(m+_rshift_nearest(y, r)), m))
      r += 1
  end

  # Taylor series with T terms
  t = -(-10*_number_of_digits(m)/(3*l)).to_i
  yshift = _rshift_nearest(y, r)
  w = _div_nearest(m, t)
  # (1...t).reverse_each do |k| # Ruby 1.9
  (1...t).to_a.reverse.each do |k|
     w = _div_nearest(m, k) - _div_nearest(yshift*w, m)
  end

  return _div_nearest(w*y, m)
end

+ (Object) _log10_digits(p)

Given an integer p >= 0, return floor(10**p)*log(10).

Raises:

  • (ArgumentError)


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# File 'lib/flt/dec_num.rb', line 1126

def _log10_digits(p)
  # digits are stored as a string, for quick conversion to
  # integer in the case that we've already computed enough
  # digits; the stored digits should always be correct
  # (truncated, not rounded to nearest).
  raise ArgumentError, "p should be nonnegative" if p<0
  if p >= AuxiliarFunctions.log10_digits.length
      digits = nil
      # compute p+3, p+6, p+9, ... digits; continue until at
      # least one of the extra digits is nonzero
      extra = 3
      loop do
        # compute p+extra digits, correct to within 1ulp
        m = 10**(p+extra+2)
        digits = _div_nearest(_ilog(10*m, m), 100).to_s
        break if digits[-extra..-1] != '0'*extra
        extra += 3
      end
      # keep all reliable digits so far; remove trailing zeros
      # and next nonzero digit
      AuxiliarFunctions.log10_digits = digits.sub(/0*$/,'')[0...-1]
  end
  return (AuxiliarFunctions.log10_digits[0...p+1]).to_i
end

+ (Object) _log10_lb(c)

Compute a lower bound for 100*log10© for a positive integer c.

Raises:

  • (ArgumentError)


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# File 'lib/flt/dec_num.rb', line 1021

def _log10_lb(c)
    raise ArgumentError, "The argument to _log10_lb should be nonnegative." if c <= 0
    str_c = c.to_s
    return 100*str_c.length - LOG10_LB_CORRECTION[str_c[0,1]]
end

+ (Object) _number_of_digits(i)

number of bits in a nonnegative integer

Raises:

  • (TypeError)


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# File 'lib/flt/dec_num.rb', line 1189

def _number_of_digits(i)
  raise  TypeError, "The argument to _number_of_digits should be nonnegative." if i < 0
  if i.is_a?(Fixnum) || (i > NUMBER_OF_DIGITS_MAX_VALID_LOG)
    # for short integers this is faster
    # note that here we return 1 for 0
    i.to_s.length
  else
    (::Math.log10(i)+1).floor
  end
end

+ (Object) _rshift_nearest(x, shift)

Given an integer x and a nonnegative integer shift, return closest integer to x / 2**shift; use round-to-even in case of a tie.



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# File 'lib/flt/dec_num.rb', line 926

def _rshift_nearest(x, shift)
    b, q = (1 << shift), (x >> shift)
    return q + (((2*(x & (b-1)) + (q&1)) > b) ? 1 : 0)
    #return q + (2*(x & (b-1)) + (((q&1) > b) ? 1 : 0))
end

+ (Object) _sqrt_nearest(n, a)

Closest integer to the square root of the positive integer n. a is an initial approximation to the square root. Any positive integer will do for a, but the closer a is to the square root of n the faster convergence will be.



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# File 'lib/flt/dec_num.rb', line 911

def _sqrt_nearest(n, a)

    if n <= 0 or a <= 0
        raise ArgumentError, "Both arguments to _sqrt_nearest should be positive."
    end

    b=0
    while a != b
        b, a = a, a--n/a>>1 # ??
    end
    return a
end

+ (Object) dexp(c, e, p)

Compute an approximation to exp(c*10**e), with p decimal places of precision.

Returns integers d, f such that:

10**(p-1) <= d <= 10**p, and
(d-1)*10**f < exp(c*10**e) < (d+1)*10**f

In other words, d*10**f is an approximation to exp(c*10**e) with p digits of precision, and with an error in d of at most 1. This is almost, but not quite, the same as the error being < 1ulp: when d

10**(p-1) the error could be up to 10 ulp.



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# File 'lib/flt/dec_num.rb', line 1163

def dexp(c, e, p)
  # we'll call iexp with M = 10**(p+2), giving p+3 digits of precision
  p += 2

  # compute log(10) with extra precision = adjusted exponent of c*10**e
  extra = [0, e + _number_of_digits(c) - 1].max
  q = p + extra

  # compute quotient c*10**e/(log(10)) = c*10**(e+q)/(log(10)*10**q),
  # rounding down
  shift = e+q
  if shift >= 0
      cshift = c*10**shift
  else
      cshift = c/10**-shift
  end
  quot, rem = cshift.divmod(_log10_digits(q))

  # reduce remainder back to original precision
  rem = _div_nearest(rem, 10**extra)

  # error in result of _iexp < 1s20;  error after division < 0.62
  return _div_nearest(_iexp(rem, 10**p), 1000), quot - p + 3
end