2021-08-23 00:35:28 +03:00
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module math
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pub fn log_n(x f64, b f64) f64 {
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y := log(x)
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z := log(b)
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return y / z
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}
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// log10 returns the decimal logarithm of x.
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// The special cases are the same as for log.
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pub fn log10(x f64) f64 {
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return log(x) * (1.0 / ln10)
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}
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// log2 returns the binary logarithm of x.
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// The special cases are the same as for log.
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pub fn log2(x f64) f64 {
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frac, exp := frexp(x)
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// Make sure exact powers of two give an exact answer.
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// Don't depend on log(0.5)*(1/ln2)+exp being exactly exp-1.
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if frac == 0.5 {
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return f64(exp - 1)
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}
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return log(frac) * (1.0 / ln2) + f64(exp)
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}
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pub fn log1p(x f64) f64 {
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y := 1.0 + x
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z := y - 1.0
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return log(y) - (z - x) / y // cancels errors with IEEE arithmetic
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}
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// log_b returns the binary exponent of x.
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//
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// special cases are:
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// log_b(±inf) = +inf
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// log_b(0) = -inf
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// log_b(nan) = nan
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pub fn log_b(x f64) f64 {
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if x == 0 {
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return inf(-1)
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}
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if is_inf(x, 0) {
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return inf(1)
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}
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if is_nan(x) {
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return x
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}
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return f64(ilog_b_(x))
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}
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// ilog_b returns the binary exponent of x as an integer.
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//
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// special cases are:
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// ilog_b(±inf) = max_i32
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// ilog_b(0) = min_i32
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// ilog_b(nan) = max_i32
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pub fn ilog_b(x f64) int {
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if x == 0 {
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return min_i32
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}
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if is_nan(x) {
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return max_i32
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}
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if is_inf(x, 0) {
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return max_i32
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}
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return ilog_b_(x)
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}
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// ilog_b returns the binary exponent of x. It assumes x is finite and
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// non-zero.
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fn ilog_b_(x_ f64) int {
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x, exp := normalize(x_)
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return int((f64_bits(x) >> shift) & mask) - bias + exp
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}
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2021-10-09 11:17:09 +03:00
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// log returns the logarithm of x
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//
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// Method :
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// 1. Argument Reduction: find k and f such that
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// x = 2^k * (1+f),
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// where sqrt(2)/2 < 1+f < sqrt(2) .
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//
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// 2. Approximation of log(1+f).
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// Let s = f/(2+f) ; based on log(1+f) = log(1+s) - log(1-s)
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// = 2s + 2/3 s**3 + 2/5 s**5 + .....,
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// = 2s + s*R
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// We use a special Remez algorithm on [0,0.1716] to generate
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// a polynomial of degree 14 to approximate R The maximum error
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// of this polynomial approximation is bounded by 2**-58.45. In
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// other words,
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// 2 4 6 8 10 12 14
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// R(z) ~ Lg1*s +Lg2*s +Lg3*s +Lg4*s +Lg5*s +Lg6*s +Lg7*s
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// (the values of Lg1 to Lg7 are listed in the program)
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// and
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// | 2 14 | -58.45
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// | Lg1*s +...+Lg7*s - R(z) | <= 2
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// | |
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// Note that 2s = f - s*f = f - hfsq + s*hfsq, where hfsq = f*f/2.
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// In order to guarantee error in log below 1ulp, we compute log
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// by
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// log(1+f) = f - s*(f - R) (if f is not too large)
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// log(1+f) = f - (hfsq - s*(hfsq+R)). (better accuracy)
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//
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// 3. Finally, log(x) = k*ln2 + log(1+f).
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// = k*ln2_hi+(f-(hfsq-(s*(hfsq+R)+k*ln2_lo)))
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// Here ln2 is split into two floating point number:
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// ln2_hi + ln2_lo,
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// where n*ln2_hi is always exact for |n| < 2000.
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//
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// Special cases:
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// log(x) is NaN with signal if x < 0 (including -inf) ;
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// log(+inf) is +inf; log(0) is -inf with signal;
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// log(NaN) is that NaN with no signal.
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//
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// Accuracy:
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// according to an error analysis, the error is always less than
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// 1 ulp (unit in the last place).
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pub fn log(a f64) f64 {
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ln2_hi := 6.93147180369123816490e-01 // 3fe62e42 fee00000
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ln2_lo := 1.90821492927058770002e-10 // 3dea39ef 35793c76
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l1 := 6.666666666666735130e-01 // 3FE55555 55555593
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l2 := 3.999999999940941908e-01 // 3FD99999 9997FA04
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l3 := 2.857142874366239149e-01 // 3FD24924 94229359
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l4 := 2.222219843214978396e-01 // 3FCC71C5 1D8E78AF
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l5 := 1.818357216161805012e-01 // 3FC74664 96CB03DE
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l6 := 1.531383769920937332e-01 // 3FC39A09 D078C69F
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l7 := 1.479819860511658591e-01 // 3FC2F112 DF3E5244
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x := a
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if is_nan(x) || is_inf(x, 1) {
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return x
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} else if x < 0 {
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return nan()
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} else if x == 0 {
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return inf(-1)
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}
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mut f1, mut ki := frexp(x)
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if f1 < sqrt2 / 2 {
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f1 *= 2
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ki--
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}
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f := f1 - 1
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k := f64(ki)
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// compute
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s := f / (2 + f)
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s2 := s * s
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s4 := s2 * s2
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t1 := s2 * (l1 + s4 * (l3 + s4 * (l5 + s4 * l7)))
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t2 := s4 * (l2 + s4 * (l4 + s4 * l6))
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r := t1 + t2
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hfsq := 0.5 * f * f
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return k * ln2_hi - ((hfsq - (s * (hfsq + r) + k * ln2_lo)) - f)
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}
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