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			81 lines
		
	
	
	
		
			1.8 KiB
		
	
	
	
		
			Go
		
	
	
	
	
	
		
		
			
		
	
	
			81 lines
		
	
	
	
		
			1.8 KiB
		
	
	
	
		
			Go
		
	
	
	
	
	
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								// Copyright (c) 2016 The mathutil Authors. All rights reserved.
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								// Use of this source code is governed by a BSD-style
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								// license that can be found in the LICENSE file.
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								package mathutil // import "modernc.org/mathutil"
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								import (
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									"math/big"
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								)
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								type float struct {
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									n           *big.Int
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									fracBits    int
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									maxFracBits int
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								}
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								func newFloat(n *big.Int, fracBits, maxFracBits int) float {
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									f := float{n: n, fracBits: fracBits, maxFracBits: maxFracBits}
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									f.normalize()
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									return f
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								}
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								func (f *float) normalize() {
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									n := f.n.BitLen()
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									if n == 0 {
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										return
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									}
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									if n := f.fracBits - f.maxFracBits; n > 0 {
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										bit := f.n.Bit(n - 1)
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										f.n.Rsh(f.n, uint(n))
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										if bit != 0 {
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											f.n.Add(f.n, _1)
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										}
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										f.fracBits -= n
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									}
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									var i int
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									for ; f.fracBits > 0 && i <= f.fracBits && f.n.Bit(i) == 0; i++ {
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										f.fracBits--
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									}
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									if i != 0 {
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										f.n.Rsh(f.n, uint(i))
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									}
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								}
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								func (f *float) eq1() bool { return f.fracBits == 0 && f.n.BitLen() == 1 }
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								func (f *float) ge2() bool { return f.n.BitLen() > f.fracBits+1 }
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								func (f *float) div2() {
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									f.fracBits++
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									f.normalize()
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								}
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								// BinaryLog computes the binary logarithm of n. The result consists of a
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								// characteristic and a mantissa having precision mantissaBits. The value of
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								// the binary logarithm is
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								//
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								//	characteristic + mantissa*(2^-mantissaBits)
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								//
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								// BinaryLog panics for n <= 0 or mantissaBits < 0.
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								func BinaryLog(n *big.Int, mantissaBits int) (characteristic int, mantissa *big.Int) {
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									if n.Sign() <= 0 || mantissaBits < 0 {
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										panic("invalid argument of BinaryLog")
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									}
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									characteristic = n.BitLen() - 1
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									mantissa = big.NewInt(0)
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									x := newFloat(n, characteristic, mantissaBits)
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									for ; mantissaBits != 0 && !x.eq1(); mantissaBits-- {
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										x.sqr()
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										mantissa.Lsh(mantissa, 1)
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										if x.ge2() {
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											mantissa.SetBit(mantissa, 0, 1)
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											x.div2()
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										}
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									}
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									return characteristic, mantissa
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								}
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