Java程序
|
1628行
|
62.74 KB
/*
* Copyright (C) 2015 The Android Open Source Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/*
* The above license covers additions and changes by AOSP authors.
* The original code is licensed as follows:
*/
//
// Copyright (c) 1999, Silicon Graphics, Inc. -- ALL RIGHTS RESERVED
//
// Permission is granted free of charge to copy, modify, use and distribute
// this software provided you include the entirety of this notice in all
// copies made.
//
// THIS SOFTWARE IS PROVIDED ON AN AS IS BASIS, WITHOUT WARRANTY OF ANY
// KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, WITHOUT LIMITATION,
// WARRANTIES THAT THE SUBJECT SOFTWARE IS FREE OF DEFECTS, MERCHANTABLE, FIT
// FOR A PARTICULAR PURPOSE OR NON-INFRINGING. SGI ASSUMES NO RISK AS TO THE
// QUALITY AND PERFORMANCE OF THE SOFTWARE. SHOULD THE SOFTWARE PROVE
// DEFECTIVE IN ANY RESPECT, SGI ASSUMES NO COST OR LIABILITY FOR ANY
// SERVICING, REPAIR OR CORRECTION. THIS DISCLAIMER OF WARRANTY CONSTITUTES
// AN ESSENTIAL PART OF THIS LICENSE. NO USE OF ANY SUBJECT SOFTWARE IS
// AUTHORIZED HEREUNDER EXCEPT UNDER THIS DISCLAIMER.
//
// UNDER NO CIRCUMSTANCES AND UNDER NO LEGAL THEORY, WHETHER TORT (INCLUDING,
// WITHOUT LIMITATION, NEGLIGENCE OR STRICT LIABILITY), CONTRACT, OR
// OTHERWISE, SHALL SGI BE LIABLE FOR ANY DIRECT, INDIRECT, SPECIAL,
// INCIDENTAL, OR CONSEQUENTIAL DAMAGES OF ANY CHARACTER WITH RESPECT TO THE
// SOFTWARE INCLUDING, WITHOUT LIMITATION, DAMAGES FOR LOSS OF GOODWILL, WORK
// STOPPAGE, LOSS OF DATA, COMPUTER FAILURE OR MALFUNCTION, OR ANY AND ALL
// OTHER COMMERCIAL DAMAGES OR LOSSES, EVEN IF SGI SHALL HAVE BEEN INFORMED OF
// THE POSSIBILITY OF SUCH DAMAGES. THIS LIMITATION OF LIABILITY SHALL NOT
// APPLY TO LIABILITY RESULTING FROM SGI's NEGLIGENCE TO THE EXTENT APPLICABLE
// LAW PROHIBITS SUCH LIMITATION. SOME JURISDICTIONS DO NOT ALLOW THE
// EXCLUSION OR LIMITATION OF INCIDENTAL OR CONSEQUENTIAL DAMAGES, SO THAT
// EXCLUSION AND LIMITATION MAY NOT APPLY TO YOU.
//
// These license terms shall be governed by and construed in accordance with
// the laws of the United States and the State of California as applied to
// agreements entered into and to be performed entirely within California
// between California residents. Any litigation relating to these license
// terms shall be subject to the exclusive jurisdiction of the Federal Courts
// of the Northern District of California (or, absent subject matter
// jurisdiction in such courts, the courts of the State of California), with
// venue lying exclusively in Santa Clara County, California.
// Copyright (c) 2001-2004, Hewlett-Packard Development Company, L.P.
//
// Permission is granted free of charge to copy, modify, use and distribute
// this software provided you include the entirety of this notice in all
// copies made.
//
// THIS SOFTWARE IS PROVIDED ON AN AS IS BASIS, WITHOUT WARRANTY OF ANY
// KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, WITHOUT LIMITATION,
// WARRANTIES THAT THE SUBJECT SOFTWARE IS FREE OF DEFECTS, MERCHANTABLE, FIT
// FOR A PARTICULAR PURPOSE OR NON-INFRINGING. HEWLETT-PACKARD ASSUMES
// NO RISK AS TO THE QUALITY AND PERFORMANCE OF THE SOFTWARE.
// SHOULD THE SOFTWARE PROVE DEFECTIVE IN ANY RESPECT,
// HEWLETT-PACKARD ASSUMES NO COST OR LIABILITY FOR ANY
// SERVICING, REPAIR OR CORRECTION. THIS DISCLAIMER OF WARRANTY CONSTITUTES
// AN ESSENTIAL PART OF THIS LICENSE. NO USE OF ANY SUBJECT SOFTWARE IS
// AUTHORIZED HEREUNDER EXCEPT UNDER THIS DISCLAIMER.
//
// UNDER NO CIRCUMSTANCES AND UNDER NO LEGAL THEORY, WHETHER TORT (INCLUDING,
// WITHOUT LIMITATION, NEGLIGENCE OR STRICT LIABILITY), CONTRACT, OR
// OTHERWISE, SHALL HEWLETT-PACKARD BE LIABLE FOR ANY DIRECT, INDIRECT, SPECIAL,
// INCIDENTAL, OR CONSEQUENTIAL DAMAGES OF ANY CHARACTER WITH RESPECT TO THE
// SOFTWARE INCLUDING, WITHOUT LIMITATION, DAMAGES FOR LOSS OF GOODWILL, WORK
// STOPPAGE, LOSS OF DATA, COMPUTER FAILURE OR MALFUNCTION, OR ANY AND ALL
// OTHER COMMERCIAL DAMAGES OR LOSSES, EVEN IF HEWLETT-PACKARD SHALL
// HAVE BEEN INFORMED OF THE POSSIBILITY OF SUCH DAMAGES.
// THIS LIMITATION OF LIABILITY SHALL NOT APPLY TO LIABILITY RESULTING
// FROM HEWLETT-PACKARD's NEGLIGENCE TO THE EXTENT APPLICABLE
// LAW PROHIBITS SUCH LIMITATION. SOME JURISDICTIONS DO NOT ALLOW THE
// EXCLUSION OR LIMITATION OF INCIDENTAL OR CONSEQUENTIAL DAMAGES, SO THAT
// EXCLUSION AND LIMITATION MAY NOT APPLY TO YOU.
//
// Added valueOf(string, radix), fixed some documentation comments.
// Hans_Boehm@hp.com 1/12/2001
// Fixed a serious typo in inv_CR(): For negative arguments it produced
// the wrong sign. This affected the sign of divisions.
// Added byteValue and fixed some comments. Hans.Boehm@hp.com 12/17/2002
// Added toStringFloatRep. Hans.Boehm@hp.com 4/1/2004
// Added get_appr() synchronization to allow access from multiple threads
// hboehm@google.com 4/25/2014
// Changed cos() prescaling to avoid logarithmic depth tree.
// hboehm@google.com 6/30/2014
// Added explicit asin() implementation. Remove one. Add ZERO and ONE and
// make them public. hboehm@google.com 5/21/2015
// Added Gauss-Legendre PI implementation. Removed two.
// hboehm@google.com 4/12/2016
// Fix shift operation in doubleValue. That produced incorrect values for
// large negative exponents.
// Don't negate argument and compute inverse for exp(). That causes severe
// performance problems for (-huge).exp()
// hboehm@google.com 8/21/2017
// Have comparison check for interruption. hboehm@google.com 10/31/2017
package com.hp.creals;
import java.math.BigInteger;
import java.util.ArrayList;
/**
* Constructive real numbers, also known as recursive, or computable reals.
* Each recursive real number is represented as an object that provides an
* approximation function for the real number.
* The approximation function guarantees that the generated approximation
* is accurate to the specified precision.
* Arithmetic operations on constructive reals produce new such objects;
* they typically do not perform any real computation.
* In this sense, arithmetic computations are exact: They produce
* a description which describes the exact answer, and can be used to
* later approximate it to arbitrary precision.
* <P>
* When approximations are generated, <I>e.g.</i> for output, they are
* accurate to the requested precision; no cumulative rounding errors
* are visible.
* In order to achieve this precision, the approximation function will often
* need to approximate subexpressions to greater precision than was originally
* demanded. Thus the approximation of a constructive real number
* generated through a complex sequence of operations may eventually require
* evaluation to very high precision. This usually makes such computations
* prohibitively expensive for large numerical problems.
* But it is perfectly appropriate for use in a desk calculator,
* for small numerical problems, for the evaluation of expressions
* computated by a symbolic algebra system, for testing of accuracy claims
* for floating point code on small inputs, or the like.
* <P>
* We expect that the vast majority of uses will ignore the particular
* implementation, and the member functons <TT>approximate</tt>
* and <TT>get_appr</tt>. Such applications will treat <TT>CR</tt> as
* a conventional numerical type, with an interface modelled on
* <TT>java.math.BigInteger</tt>. No subclasses of <TT>CR</tt>
* will be explicitly mentioned by such a program.
* <P>
* All standard arithmetic operations, as well as a few algebraic
* and transcendal functions are provided. Constructive reals are
* immutable; thus all of these operations return a new constructive real.
* <P>
* A few uses will require explicit construction of approximation functions.
* The requires the construction of a subclass of <TT>CR</tt> with
* an overridden <TT>approximate</tt> function. Note that <TT>approximate</tt>
* should only be defined, but never called. <TT>get_appr</tt>
* provides the same functionality, but adds the caching necessary to obtain
* reasonable performance.
* <P>
* Any operation may throw <TT>com.hp.creals.AbortedException</tt> if the thread
* in which it is executing is interrupted. (<TT>InterruptedException</tt>
* cannot be used for this purpose, since CR inherits from <TT>Number</tt>.)
* <P>
* Any operation may also throw <TT>com.hp.creals.PrecisionOverflowException</tt>
* If the precision request generated during any subcalculation overflows
* a 28-bit integer. (This should be extremely unlikely, except as an
* outcome of a division by zero, or other erroneous computation.)
*
*/
public abstract class CR extends Number {
// CR is the basic representation of a number.
// Abstractly this is a function for computing an approximation
// plus the current best approximation.
// We could do without the latter, but that would
// be atrociously slow.
/**
* Indicates a constructive real operation was interrupted.
* Most constructive real operations may throw such an exception.
* This is unchecked, since Number methods may not raise checked
* exceptions.
*/
public static class AbortedException extends RuntimeException {
public AbortedException() { super(); }
public AbortedException(String s) { super(s); }
}
/**
* Indicates that the number of bits of precision requested by
* a computation on constructive reals required more than 28 bits,
* and was thus in danger of overflowing an int.
* This is likely to be a symptom of a diverging computation,
* <I>e.g.</i> division by zero.
*/
public static class PrecisionOverflowException extends RuntimeException {
public PrecisionOverflowException() { super(); }
public PrecisionOverflowException(String s) { super(s); }
}
// First some frequently used constants, so we don't have to
// recompute these all over the place.
static final BigInteger big0 = BigInteger.ZERO;
static final BigInteger big1 = BigInteger.ONE;
static final BigInteger bigm1 = BigInteger.valueOf(-1);
static final BigInteger big2 = BigInteger.valueOf(2);
static final BigInteger bigm2 = BigInteger.valueOf(-2);
static final BigInteger big3 = BigInteger.valueOf(3);
static final BigInteger big6 = BigInteger.valueOf(6);
static final BigInteger big8 = BigInteger.valueOf(8);
static final BigInteger big10 = BigInteger.TEN;
static final BigInteger big750 = BigInteger.valueOf(750);
static final BigInteger bigm750 = BigInteger.valueOf(-750);
/**
* Setting this to true requests that all computations be aborted by
* throwing AbortedException. Must be rest to false before any further
* computation. Ideally Thread.interrupt() should be used instead, but
* that doesn't appear to be consistently supported by browser VMs.
*/
public volatile static boolean please_stop = false;
/**
* Must be defined in subclasses of <TT>CR</tt>.
* Most users can ignore the existence of this method, and will
* not ever need to define a <TT>CR</tt> subclass.
* Returns value / 2 ** precision rounded to an integer.
* The error in the result is strictly < 1.
* Informally, approximate(n) gives a scaled approximation
* accurate to 2**n.
* Implementations may safely assume that precision is
* at least a factor of 8 away from overflow.
* Called only with the lock on the <TT>CR</tt> object
* already held.
*/
protected abstract BigInteger approximate(int precision);
transient int min_prec;
// The smallest precision value with which the above
// has been called.
transient BigInteger max_appr;
// The scaled approximation corresponding to min_prec.
transient boolean appr_valid = false;
// min_prec and max_val are valid.
// Helper functions
static int bound_log2(int n) {
int abs_n = Math.abs(n);
return (int)Math.ceil(Math.log((double)(abs_n + 1))/Math.log(2.0));
}
// Check that a precision is at least a factor of 8 away from
// overflowng the integer used to hold a precision spec.
// We generally perform this check early on, and then convince
// ourselves that none of the operations performed on precisions
// inside a function can generate an overflow.
static void check_prec(int n) {
int high = n >> 28;
// if n is not in danger of overflowing, then the 4 high order
// bits should be identical. Thus high is either 0 or -1.
// The rest of this is to test for either of those in a way
// that should be as cheap as possible.
int high_shifted = n >> 29;
if (0 != (high ^ high_shifted)) {
throw new PrecisionOverflowException();
}
}
/**
* The constructive real number corresponding to a
* <TT>BigInteger</tt>.
*/
public static CR valueOf(BigInteger n) {
return new int_CR(n);
}
/**
* The constructive real number corresponding to a
* Java <TT>int</tt>.
*/
public static CR valueOf(int n) {
return valueOf(BigInteger.valueOf(n));
}
/**
* The constructive real number corresponding to a
* Java <TT>long</tt>.
*/
public static CR valueOf(long n) {
return valueOf(BigInteger.valueOf(n));
}
/**
* The constructive real number corresponding to a
* Java <TT>double</tt>.
* The result is undefined if argument is infinite or NaN.
*/
public static CR valueOf(double n) {
if (Double.isNaN(n)) throw new ArithmeticException("Nan argument");
if (Double.isInfinite(n)) {
throw new ArithmeticException("Infinite argument");
}
boolean negative = (n < 0.0);
long bits = Double.doubleToLongBits(Math.abs(n));
long mantissa = (bits & 0xfffffffffffffL);
int biased_exp = (int)(bits >> 52);
int exp = biased_exp - 1075;
if (biased_exp != 0) {
mantissa += (1L << 52);
} else {
mantissa <<= 1;
}
CR result = valueOf(mantissa).shiftLeft(exp);
if (negative) result = result.negate();
return result;
}
/**
* The constructive real number corresponding to a
* Java <TT>float</tt>.
* The result is undefined if argument is infinite or NaN.
*/
public static CR valueOf(float n) {
return valueOf((double) n);
}
public static CR ZERO = valueOf(0);
public static CR ONE = valueOf(1);
// Multiply k by 2**n.
static BigInteger shift(BigInteger k, int n) {
if (n == 0) return k;
if (n < 0) return k.shiftRight(-n);
return k.shiftLeft(n);
}
// Multiply by 2**n, rounding result
static BigInteger scale(BigInteger k, int n) {
if (n >= 0) {
return k.shiftLeft(n);
} else {
BigInteger adj_k = shift(k, n+1).add(big1);
return adj_k.shiftRight(1);
}
}
// Identical to approximate(), but maintain and update cache.
/**
* Returns value / 2 ** prec rounded to an integer.
* The error in the result is strictly < 1.
* Produces the same answer as <TT>approximate</tt>, but uses and
* maintains a cached approximation.
* Normally not overridden, and called only from <TT>approximate</tt>
* methods in subclasses. Not needed if the provided operations
* on constructive reals suffice.
*/
public synchronized BigInteger get_appr(int precision) {
check_prec(precision);
if (appr_valid && precision >= min_prec) {
return scale(max_appr, min_prec - precision);
} else {
BigInteger result = approximate(precision);
min_prec = precision;
max_appr = result;
appr_valid = true;
return result;
}
}
// Return the position of the msd.
// If x.msd() == n then
// 2**(n-1) < abs(x) < 2**(n+1)
// This initial version assumes that max_appr is valid
// and sufficiently removed from zero
// that the msd is determined.
int known_msd() {
int first_digit;
int length;
if (max_appr.signum() >= 0) {
length = max_appr.bitLength();
} else {
length = max_appr.negate().bitLength();
}
first_digit = min_prec + length - 1;
return first_digit;
}
// This version may return Integer.MIN_VALUE if the correct
// answer is < n.
int msd(int n) {
if (!appr_valid ||
max_appr.compareTo(big1) <= 0
&& max_appr.compareTo(bigm1) >= 0) {
get_appr(n - 1);
if (max_appr.abs().compareTo(big1) <= 0) {
// msd could still be arbitrarily far to the right.
return Integer.MIN_VALUE;
}
}
return known_msd();
}
// Functionally equivalent, but iteratively evaluates to higher
// precision.
int iter_msd(int n)
{
int prec = 0;
for (;prec > n + 30; prec = (prec * 3)/2 - 16) {
int msd = msd(prec);
if (msd != Integer.MIN_VALUE) return msd;
check_prec(prec);
if (Thread.interrupted() || please_stop) {
throw new AbortedException();
}
}
return msd(n);
}
// This version returns a correct answer eventually, except
// that it loops forever (or throws an exception when the
// requested precision overflows) if this constructive real is zero.
int msd() {
return iter_msd(Integer.MIN_VALUE);
}
// A helper function for toString.
// Generate a String containing n zeroes.
private static String zeroes(int n) {
char[] a = new char[n];
for (int i = 0; i < n; ++i) {
a[i] = '0';
}
return new String(a);
}
// Natural log of 2. Needed for some prescaling below.
// ln(2) = 7ln(10/9) - 2ln(25/24) + 3ln(81/80)
CR simple_ln() {
return new prescaled_ln_CR(this.subtract(ONE));
}
static CR ten_ninths = valueOf(10).divide(valueOf(9));
static CR twentyfive_twentyfourths = valueOf(25).divide(valueOf(24));
static CR eightyone_eightyeths = valueOf(81).divide(valueOf(80));
static CR ln2_1 = valueOf(7).multiply(ten_ninths.simple_ln());
static CR ln2_2 =
valueOf(2).multiply(twentyfive_twentyfourths.simple_ln());
static CR ln2_3 = valueOf(3).multiply(eightyone_eightyeths.simple_ln());
static CR ln2 = ln2_1.subtract(ln2_2).add(ln2_3);
// Atan of integer reciprocal. Used for atan_PI. Could perhaps be made
// public.
static CR atan_reciprocal(int n) {
return new integral_atan_CR(n);
}
// Other constants used for PI computation.
static CR four = valueOf(4);
// Public operations.
/**
* Return 0 if x = y to within the indicated tolerance,
* -1 if x < y, and +1 if x > y. If x and y are indeed
* equal, it is guaranteed that 0 will be returned. If
* they differ by less than the tolerance, anything
* may happen. The tolerance allowed is
* the maximum of (abs(this)+abs(x))*(2**r) and 2**a
* @param x The other constructive real
* @param r Relative tolerance in bits
* @param a Absolute tolerance in bits
*/
public int compareTo(CR x, int r, int a) {
int this_msd = iter_msd(a);
int x_msd = x.iter_msd(this_msd > a? this_msd : a);
int max_msd = (x_msd > this_msd? x_msd : this_msd);
int rel = max_msd + r;
// This can't approach overflow, since r and a are
// effectively divided by 2, and msds are checked.
int abs_prec = (rel > a? rel : a);
return compareTo(x, abs_prec);
}
/**
* Approximate comparison with only an absolute tolerance.
* Identical to the three argument version, but without a relative
* tolerance.
* Result is 0 if both constructive reals are equal, indeterminate
* if they differ by less than 2**a.
*
* @param x The other constructive real
* @param a Absolute tolerance in bits
*/
public int compareTo(CR x, int a) {
int needed_prec = a - 1;
BigInteger this_appr = get_appr(needed_prec);
BigInteger x_appr = x.get_appr(needed_prec);
int comp1 = this_appr.compareTo(x_appr.add(big1));
if (comp1 > 0) return 1;
int comp2 = this_appr.compareTo(x_appr.subtract(big1));
if (comp2 < 0) return -1;
return 0;
}
/**
* Return -1 if <TT>this < x</tt>, or +1 if <TT>this > x</tt>.
* Should be called only if <TT>this != x</tt>.
* If <TT>this == x</tt>, this will not terminate correctly; typically it
* will run until it exhausts memory.
* If the two constructive reals may be equal, the two or 3 argument
* version of compareTo should be used.
*/
public int compareTo(CR x) {
for (int a = -20; ; a *= 2) {
check_prec(a);
int result = compareTo(x, a);
if (0 != result) return result;
if (Thread.interrupted() || please_stop) {
throw new AbortedException();
}
}
}
/**
* Equivalent to <TT>compareTo(CR.valueOf(0), a)</tt>
*/
public int signum(int a) {
if (appr_valid) {
int quick_try = max_appr.signum();
if (0 != quick_try) return quick_try;
}
int needed_prec = a - 1;
BigInteger this_appr = get_appr(needed_prec);
return this_appr.signum();
}
/**
* Return -1 if negative, +1 if positive.
* Should be called only if <TT>this != 0</tt>.
* In the 0 case, this will not terminate correctly; typically it
* will run until it exhausts memory.
* If the two constructive reals may be equal, the one or two argument
* version of signum should be used.
*/
public int signum() {
for (int a = -20; ; a *= 2) {
check_prec(a);
int result = signum(a);
if (0 != result) return result;
if (Thread.interrupted() || please_stop) {
throw new AbortedException();
}
}
}
/**
* Return the constructive real number corresponding to the given
* textual representation and radix.
*
* @param s [-] digit* [. digit*]
* @param radix
*/
public static CR valueOf(String s, int radix)
throws NumberFormatException {
int len = s.length();
int start_pos = 0, point_pos;
String fraction;
while (s.charAt(start_pos) == ' ') ++start_pos;
while (s.charAt(len - 1) == ' ') --len;
point_pos = s.indexOf('.', start_pos);
if (point_pos == -1) {
point_pos = len;
fraction = "0";
} else {
fraction = s.substring(point_pos + 1, len);
}
String whole = s.substring(start_pos, point_pos);
BigInteger scaled_result = new BigInteger(whole + fraction, radix);
BigInteger divisor = BigInteger.valueOf(radix).pow(fraction.length());
return CR.valueOf(scaled_result).divide(CR.valueOf(divisor));
}
/**
* Return a textual representation accurate to <TT>n</tt> places
* to the right of the decimal point. <TT>n</tt> must be nonnegative.
*
* @param n Number of digits (>= 0) included to the right of decimal point
* @param radix Base ( >= 2, <= 16) for the resulting representation.
*/
public String toString(int n, int radix) {
CR scaled_CR;
if (16 == radix) {
scaled_CR = shiftLeft(4*n);
} else {
BigInteger scale_factor = BigInteger.valueOf(radix).pow(n);
scaled_CR = multiply(new int_CR(scale_factor));
}
BigInteger scaled_int = scaled_CR.get_appr(0);
String scaled_string = scaled_int.abs().toString(radix);
String result;
if (0 == n) {
result = scaled_string;
} else {
int len = scaled_string.length();
if (len <= n) {
// Add sufficient leading zeroes
String z = zeroes(n + 1 - len);
scaled_string = z + scaled_string;
len = n + 1;
}
String whole = scaled_string.substring(0, len - n);
String fraction = scaled_string.substring(len - n);
result = whole + "." + fraction;
}
if (scaled_int.signum() < 0) {
result = "-" + result;
}
return result;
}
/**
* Equivalent to <TT>toString(n,10)</tt>
*
* @param n Number of digits included to the right of decimal point
*/
public String toString(int n) {
return toString(n, 10);
}
/**
* Equivalent to <TT>toString(10, 10)</tt>
*/
public String toString() {
return toString(10);
}
static double doubleLog2 = Math.log(2.0);
/**
* Return a textual scientific notation representation accurate
* to <TT>n</tt> places to the right of the decimal point.
* <TT>n</tt> must be nonnegative. A value smaller than
* <TT>radix</tt>**-<TT>m</tt> may be displayed as 0.
* The <TT>mantissa</tt> component of the result is either "0"
* or exactly <TT>n</tt> digits long. The <TT>sign</tt>
* component is zero exactly when the mantissa is "0".
*
* @param n Number of digits (> 0) included to the right of decimal point.
* @param radix Base ( ≥ 2, ≤ 16) for the resulting representation.
* @param m Precision used to distinguish number from zero.
* Expressed as a power of m.
*/
public StringFloatRep toStringFloatRep(int n, int radix, int m) {
if (n <= 0) throw new ArithmeticException("Bad precision argument");
double log2_radix = Math.log((double)radix)/doubleLog2;
BigInteger big_radix = BigInteger.valueOf(radix);
long long_msd_prec = (long)(log2_radix * (double)m);
if (long_msd_prec > (long)Integer.MAX_VALUE
|| long_msd_prec < (long)Integer.MIN_VALUE)
throw new PrecisionOverflowException();
int msd_prec = (int)long_msd_prec;
check_prec(msd_prec);
int msd = iter_msd(msd_prec - 2);
if (msd == Integer.MIN_VALUE)
return new StringFloatRep(0, "0", radix, 0);
int exponent = (int)Math.ceil((double)msd / log2_radix);
// Guess for the exponent. Try to get it usually right.
int scale_exp = exponent - n;
CR scale;
if (scale_exp > 0) {
scale = CR.valueOf(big_radix.pow(scale_exp)).inverse();
} else {
scale = CR.valueOf(big_radix.pow(-scale_exp));
}
CR scaled_res = multiply(scale);
BigInteger scaled_int = scaled_res.get_appr(0);
int sign = scaled_int.signum();
String scaled_string = scaled_int.abs().toString(radix);
while (scaled_string.length() < n) {
// exponent was too large. Adjust.
scaled_res = scaled_res.multiply(CR.valueOf(big_radix));
exponent -= 1;
scaled_int = scaled_res.get_appr(0);
sign = scaled_int.signum();
scaled_string = scaled_int.abs().toString(radix);
}
if (scaled_string.length() > n) {
// exponent was too small. Adjust by truncating.
exponent += (scaled_string.length() - n);
scaled_string = scaled_string.substring(0, n);
}
return new StringFloatRep(sign, scaled_string, radix, exponent);
}
/**
* Return a BigInteger which differs by less than one from the
* constructive real.
*/
public BigInteger BigIntegerValue() {
return get_appr(0);
}
/**
* Return an int which differs by less than one from the
* constructive real. Behavior on overflow is undefined.
*/
public int intValue() {
return BigIntegerValue().intValue();
}
/**
* Return an int which differs by less than one from the
* constructive real. Behavior on overflow is undefined.
*/
public byte byteValue() {
return BigIntegerValue().byteValue();
}
/**
* Return a long which differs by less than one from the
* constructive real. Behavior on overflow is undefined.
*/
public long longValue() {
return BigIntegerValue().longValue();
}
/**
* Return a double which differs by less than one in the least
* represented bit from the constructive real.
* (We're in fact closer to round-to-nearest than that, but we can't and
* don't promise correct rounding.)
*/
public double doubleValue() {
int my_msd = iter_msd(-1080 /* slightly > exp. range */);
if (Integer.MIN_VALUE == my_msd) return 0.0;
int needed_prec = my_msd - 60;
double scaled_int = get_appr(needed_prec).doubleValue();
boolean may_underflow = (needed_prec < -1000);
long scaled_int_rep = Double.doubleToLongBits(scaled_int);
long exp_adj = may_underflow? needed_prec + 96 : needed_prec;
long orig_exp = (scaled_int_rep >> 52) & 0x7ff;
if (((orig_exp + exp_adj) & ~0x7ff) != 0) {
// Original unbiased exponent is > 50. Exp_adj > -1050.
// Thus this can overflow the 11 bit exponent only if the result
// itself overflows.
if (scaled_int < 0.0) {
return Double.NEGATIVE_INFINITY;
} else {
return Double.POSITIVE_INFINITY;
}
}
scaled_int_rep += exp_adj << 52;
double result = Double.longBitsToDouble(scaled_int_rep);
if (may_underflow) {
double two48 = (double)(1L << 48);
return result/two48/two48;
} else {
return result;
}
}
/**
* Return a float which differs by less than one in the least
* represented bit from the constructive real.
*/
public float floatValue() {
return (float)doubleValue();
// Note that double-rounding is not a problem here, since we
// cannot, and do not, guarantee correct rounding.
}
/**
* Add two constructive reals.
*/
public CR add(CR x) {
return new add_CR(this, x);
}
/**
* Multiply a constructive real by 2**n.
* @param n shift count, may be negative
*/
public CR shiftLeft(int n) {
check_prec(n);
return new shifted_CR(this, n);
}
/**
* Multiply a constructive real by 2**(-n).
* @param n shift count, may be negative
*/
public CR shiftRight(int n) {
check_prec(n);
return new shifted_CR(this, -n);
}
/**
* Produce a constructive real equivalent to the original, assuming
* the original was an integer. Undefined results if the original
* was not an integer. Prevents evaluation of digits to the right
* of the decimal point, and may thus improve performance.
*/
public CR assumeInt() {
return new assumed_int_CR(this);
}
/**
* The additive inverse of a constructive real
*/
public CR negate() {
return new neg_CR(this);
}
/**
* The difference between two constructive reals
*/
public CR subtract(CR x) {
return new add_CR(this, x.negate());
}
/**
* The product of two constructive reals
*/
public CR multiply(CR x) {
return new mult_CR(this, x);
}
/**
* The multiplicative inverse of a constructive real.
* <TT>x.inverse()</tt> is equivalent to <TT>CR.valueOf(1).divide(x)</tt>.
*/
public CR inverse() {
return new inv_CR(this);
}
/**
* The quotient of two constructive reals.
*/
public CR divide(CR x) {
return new mult_CR(this, x.inverse());
}
/**
* The real number <TT>x</tt> if <TT>this</tt> < 0, or <TT>y</tt> otherwise.
* Requires <TT>x</tt> = <TT>y</tt> if <TT>this</tt> = 0.
* Since comparisons may diverge, this is often
* a useful alternative to conditionals.
*/
public CR select(CR x, CR y) {
return new select_CR(this, x, y);
}
/**
* The maximum of two constructive reals.
*/
public CR max(CR x) {
return subtract(x).select(x, this);
}
/**
* The minimum of two constructive reals.
*/
public CR min(CR x) {
return subtract(x).select(this, x);
}
/**
* The absolute value of a constructive reals.
* Note that this cannot be written as a conditional.
*/
public CR abs() {
return select(negate(), this);
}
/**
* The exponential function, that is e**<TT>this</tt>.
*/
public CR exp() {
final int low_prec = -10;
BigInteger rough_appr = get_appr(low_prec);
// Handle negative arguments directly; negating and computing inverse
// can be very expensive.
if (rough_appr.compareTo(big2) > 0 || rough_appr.compareTo(bigm2) < 0) {
CR square_root = shiftRight(1).exp();
return square_root.multiply(square_root);
} else {
return new prescaled_exp_CR(this);
}
}
/**
* The ratio of a circle's circumference to its diameter.
*/
public static CR PI = new gl_pi_CR();
// Our old PI implementation. Keep this around for now to allow checking.
// This implementation may also be faster for BigInteger implementations
// that support only quadratic multiplication, but exhibit high performance
// for small computations. (The standard Android 6 implementation supports
// subquadratic multiplication, but has high constant overhead.) Many other
// atan-based formulas are possible, but based on superficial
// experimentation, this is roughly as good as the more complex formulas.
public static CR atan_PI = four.multiply(four.multiply(atan_reciprocal(5))
.subtract(atan_reciprocal(239)));
// pi/4 = 4*atan(1/5) - atan(1/239)
static CR half_pi = PI.shiftRight(1);
/**
* The trigonometric cosine function.
*/
public CR cos() {
BigInteger halfpi_multiples = divide(PI).get_appr(-1);
BigInteger abs_halfpi_multiples = halfpi_multiples.abs();
if (abs_halfpi_multiples.compareTo(big2) >= 0) {
// Subtract multiples of PI
BigInteger pi_multiples = scale(halfpi_multiples, -1);
CR adjustment = PI.multiply(CR.valueOf(pi_multiples));
if (pi_multiples.and(big1).signum() != 0) {
return subtract(adjustment).cos().negate();
} else {
return subtract(adjustment).cos();
}
} else if (get_appr(-1).abs().compareTo(big2) >= 0) {
// Scale further with double angle formula
CR cos_half = shiftRight(1).cos();
return cos_half.multiply(cos_half).shiftLeft(1).subtract(ONE);
} else {
return new prescaled_cos_CR(this);
}
}
/**
* The trigonometric sine function.
*/
public CR sin() {
return half_pi.subtract(this).cos();
}
/**
* The trignonometric arc (inverse) sine function.
*/
public CR asin() {
BigInteger rough_appr = get_appr(-10);
if (rough_appr.compareTo(big750) /* 1/sqrt(2) + a bit */ > 0){
CR new_arg = ONE.subtract(multiply(this)).sqrt();
return new_arg.acos();
} else if (rough_appr.compareTo(bigm750) < 0) {
return negate().asin().negate();
} else {
return new prescaled_asin_CR(this);
}
}
/**
* The trignonometric arc (inverse) cosine function.
*/
public CR acos() {
return half_pi.subtract(asin());
}
static final BigInteger low_ln_limit = big8; /* sixteenths, i.e. 1/2 */
static final BigInteger high_ln_limit =
BigInteger.valueOf(16 + 8 /* 1.5 */);
static final BigInteger scaled_4 =
BigInteger.valueOf(4*16);
/**
* The natural (base e) logarithm.
*/
public CR ln() {
final int low_prec = -4;
BigInteger rough_appr = get_appr(low_prec); /* In sixteenths */
if (rough_appr.compareTo(big0) < 0) {
throw new ArithmeticException("ln(negative)");
}
if (rough_appr.compareTo(low_ln_limit) <= 0) {
return inverse().ln().negate();
}
if (rough_appr.compareTo(high_ln_limit) >= 0) {
if (rough_appr.compareTo(scaled_4) <= 0) {
CR quarter = sqrt().sqrt().ln();
return quarter.shiftLeft(2);
} else {
int extra_bits = rough_appr.bitLength() - 3;
CR scaled_result = shiftRight(extra_bits).ln();
return scaled_result.add(CR.valueOf(extra_bits).multiply(ln2));
}
}
return simple_ln();
}
/**
* The square root of a constructive real.
*/
public CR sqrt() {
return new sqrt_CR(this);
}
} // end of CR
//
// A specialization of CR for cases in which approximate() calls
// to increase evaluation precision are somewhat expensive.
// If we need to (re)evaluate, we speculatively evaluate to slightly
// higher precision, miminimizing reevaluations.
// Note that this requires any arguments to be evaluated to higher
// precision than absolutely necessary. It can thus potentially
// result in lots of wasted effort, and should be used judiciously.
// This assumes that the order of magnitude of the number is roughly one.
//
abstract class slow_CR extends CR {
static int max_prec = -64;
static int prec_incr = 32;
public synchronized BigInteger get_appr(int precision) {
check_prec(precision);
if (appr_valid && precision >= min_prec) {
return scale(max_appr, min_prec - precision);
} else {
int eval_prec = (precision >= max_prec? max_prec :
(precision - prec_incr + 1) & ~(prec_incr - 1));
BigInteger result = approximate(eval_prec);
min_prec = eval_prec;
max_appr = result;
appr_valid = true;
return scale(result, eval_prec - precision);
}
}
}
// Representation of an integer constant. Private.
class int_CR extends CR {
BigInteger value;
int_CR(BigInteger n) {
value = n;
}
protected BigInteger approximate(int p) {
return scale(value, -p) ;
}
}
// Representation of a number that may not have been completely
// evaluated, but is assumed to be an integer. Hence we never
// evaluate beyond the decimal point.
class assumed_int_CR extends CR {
CR value;
assumed_int_CR(CR x) {
value = x;
}
protected BigInteger approximate(int p) {
if (p >= 0) {
return value.get_appr(p);
} else {
return scale(value.get_appr(0), -p) ;
}
}
}
// Representation of the sum of 2 constructive reals. Private.
class add_CR extends CR {
CR op1;
CR op2;
add_CR(CR x, CR y) {
op1 = x;
op2 = y;
}
protected BigInteger approximate(int p) {
// Args need to be evaluated so that each error is < 1/4 ulp.
// Rounding error from the cale call is <= 1/2 ulp, so that
// final error is < 1 ulp.
return scale(op1.get_appr(p-2).add(op2.get_appr(p-2)), -2);
}
}
// Representation of a CR multiplied by 2**n
class shifted_CR extends CR {
CR op;
int count;
shifted_CR(CR x, int n) {
op = x;
count = n;
}
protected BigInteger approximate(int p) {
return op.get_appr(p - count);
}
}
// Representation of the negation of a constructive real. Private.
class neg_CR extends CR {
CR op;
neg_CR(CR x) {
op = x;
}
protected BigInteger approximate(int p) {
return op.get_appr(p).negate();
}
}
// Representation of:
// op1 if selector < 0
// op2 if selector >= 0
// Assumes x = y if s = 0
class select_CR extends CR {
CR selector;
int selector_sign;
CR op1;
CR op2;
select_CR(CR s, CR x, CR y) {
selector = s;
int selector_sign = selector.get_appr(-20).signum();
op1 = x;
op2 = y;
}
protected BigInteger approximate(int p) {
if (selector_sign < 0) return op1.get_appr(p);
if (selector_sign > 0) return op2.get_appr(p);
BigInteger op1_appr = op1.get_appr(p-1);
BigInteger op2_appr = op2.get_appr(p-1);
BigInteger diff = op1_appr.subtract(op2_appr).abs();
if (diff.compareTo(big1) <= 0) {
// close enough; use either
return scale(op1_appr, -1);
}
// op1 and op2 are different; selector != 0;
// safe to get sign of selector.
if (selector.signum() < 0) {
selector_sign = -1;
return scale(op1_appr, -1);
} else {
selector_sign = 1;
return scale(op2_appr, -1);
}
}
}
// Representation of the product of 2 constructive reals. Private.
class mult_CR extends CR {
CR op1;
CR op2;
mult_CR(CR x, CR y) {
op1 = x;
op2 = y;
}
protected BigInteger approximate(int p) {
int half_prec = (p >> 1) - 1;
int msd_op1 = op1.msd(half_prec);
int msd_op2;
if (msd_op1 == Integer.MIN_VALUE) {
msd_op2 = op2.msd(half_prec);
if (msd_op2 == Integer.MIN_VALUE) {
// Product is small enough that zero will do as an
// approximation.
return big0;
} else {
// Swap them, so the larger operand (in absolute value)
// is first.
CR tmp;
tmp = op1;
op1 = op2;
op2 = tmp;
msd_op1 = msd_op2;
}
}
// msd_op1 is valid at this point.
int prec2 = p - msd_op1 - 3; // Precision needed for op2.
// The appr. error is multiplied by at most
// 2 ** (msd_op1 + 1)
// Thus each approximation contributes 1/4 ulp
// to the rounding error, and the final rounding adds
// another 1/2 ulp.
BigInteger appr2 = op2.get_appr(prec2);
if (appr2.signum() == 0) return big0;
msd_op2 = op2.known_msd();
int prec1 = p - msd_op2 - 3; // Precision needed for op1.
BigInteger appr1 = op1.get_appr(prec1);
int scale_digits = prec1 + prec2 - p;
return scale(appr1.multiply(appr2), scale_digits);
}
}
// Representation of the multiplicative inverse of a constructive
// real. Private. Should use Newton iteration to refine estimates.
class inv_CR extends CR {
CR op;
inv_CR(CR x) { op = x; }
protected BigInteger approximate(int p) {
int msd = op.msd();
int inv_msd = 1 - msd;
int digits_needed = inv_msd - p + 3;
// Number of SIGNIFICANT digits needed for
// argument, excl. msd position, which may
// be fictitious, since msd routine can be
// off by 1. Roughly 1 extra digit is
// needed since the relative error is the
// same in the argument and result, but
// this isn't quite the same as the number
// of significant digits. Another digit
// is needed to compensate for slop in the
// calculation.
// One further bit is required, since the
// final rounding introduces a 0.5 ulp
// error.
int prec_needed = msd - digits_needed;
int log_scale_factor = -p - prec_needed;
if (log_scale_factor < 0) return big0;
BigInteger dividend = big1.shiftLeft(log_scale_factor);
BigInteger scaled_divisor = op.get_appr(prec_needed);
BigInteger abs_scaled_divisor = scaled_divisor.abs();
BigInteger adj_dividend = dividend.add(
abs_scaled_divisor.shiftRight(1));
// Adjustment so that final result is rounded.
BigInteger result = adj_dividend.divide(abs_scaled_divisor);
if (scaled_divisor.signum() < 0) {
return result.negate();
} else {
return result;
}
}
}
// Representation of the exponential of a constructive real. Private.
// Uses a Taylor series expansion. Assumes |x| < 1/2.
// Note: this is known to be a bad algorithm for
// floating point. Unfortunately, other alternatives
// appear to require precomputed information.
class prescaled_exp_CR extends CR {
CR op;
prescaled_exp_CR(CR x) { op = x; }
protected BigInteger approximate(int p) {
if (p >= 1) return big0;
int iterations_needed = -p/2 + 2; // conservative estimate > 0.
// Claim: each intermediate term is accurate
// to 2*2^calc_precision.
// Total rounding error in series computation is
// 2*iterations_needed*2^calc_precision,
// exclusive of error in op.
int calc_precision = p - bound_log2(2*iterations_needed)
- 4; // for error in op, truncation.
int op_prec = p - 3;
BigInteger op_appr = op.get_appr(op_prec);
// Error in argument results in error of < 3/8 ulp.
// Sum of term eval. rounding error is < 1/16 ulp.
// Series truncation error < 1/16 ulp.
// Final rounding error is <= 1/2 ulp.
// Thus final error is < 1 ulp.
BigInteger scaled_1 = big1.shiftLeft(-calc_precision);
BigInteger current_term = scaled_1;
BigInteger current_sum = scaled_1;
int n = 0;
BigInteger max_trunc_error =
big1.shiftLeft(p - 4 - calc_precision);
while (current_term.abs().compareTo(max_trunc_error) >= 0) {
if (Thread.interrupted() || please_stop) throw new AbortedException();
n += 1;
/* current_term = current_term * op / n */
current_term = scale(current_term.multiply(op_appr), op_prec);
current_term = current_term.divide(BigInteger.valueOf(n));
current_sum = current_sum.add(current_term);
}
return scale(current_sum, calc_precision - p);
}
}
// Representation of the cosine of a constructive real. Private.
// Uses a Taylor series expansion. Assumes |x| < 1.
class prescaled_cos_CR extends slow_CR {
CR op;
prescaled_cos_CR(CR x) {
op = x;
}
protected BigInteger approximate(int p) {
if (p >= 1) return big0;
int iterations_needed = -p/2 + 4; // conservative estimate > 0.
// Claim: each intermediate term is accurate
// to 2*2^calc_precision.
// Total rounding error in series computation is
// 2*iterations_needed*2^calc_precision,
// exclusive of error in op.
int calc_precision = p - bound_log2(2*iterations_needed)
- 4; // for error in op, truncation.
int op_prec = p - 2;
BigInteger op_appr = op.get_appr(op_prec);
// Error in argument results in error of < 1/4 ulp.
// Cumulative arithmetic rounding error is < 1/16 ulp.
// Series truncation error < 1/16 ulp.
// Final rounding error is <= 1/2 ulp.
// Thus final error is < 1 ulp.
BigInteger current_term;
int n;
BigInteger max_trunc_error =
big1.shiftLeft(p - 4 - calc_precision);
n = 0;
current_term = big1.shiftLeft(-calc_precision);
BigInteger current_sum = current_term;
while (current_term.abs().compareTo(max_trunc_error) >= 0) {
if (Thread.interrupted() || please_stop) throw new AbortedException();
n += 2;
/* current_term = - current_term * op * op / n * (n - 1) */
current_term = scale(current_term.multiply(op_appr), op_prec);
current_term = scale(current_term.multiply(op_appr), op_prec);
BigInteger divisor = BigInteger.valueOf(-n)
.multiply(BigInteger.valueOf(n-1));
current_term = current_term.divide(divisor);
current_sum = current_sum.add(current_term);
}
return scale(current_sum, calc_precision - p);
}
}
// The constructive real atan(1/n), where n is a small integer
// > base.
// This gives a simple and moderately fast way to compute PI.
class integral_atan_CR extends slow_CR {
int op;
integral_atan_CR(int x) { op = x; }
protected BigInteger approximate(int p) {
if (p >= 1) return big0;
int iterations_needed = -p/2 + 2; // conservative estimate > 0.
// Claim: each intermediate term is accurate
// to 2*base^calc_precision.
// Total rounding error in series computation is
// 2*iterations_needed*base^calc_precision,
// exclusive of error in op.
int calc_precision = p - bound_log2(2*iterations_needed)
- 2; // for error in op, truncation.
// Error in argument results in error of < 3/8 ulp.
// Cumulative arithmetic rounding error is < 1/4 ulp.
// Series truncation error < 1/4 ulp.
// Final rounding error is <= 1/2 ulp.
// Thus final error is < 1 ulp.
BigInteger scaled_1 = big1.shiftLeft(-calc_precision);
BigInteger big_op = BigInteger.valueOf(op);
BigInteger big_op_squared = BigInteger.valueOf(op*op);
BigInteger op_inverse = scaled_1.divide(big_op);
BigInteger current_power = op_inverse;
BigInteger current_term = op_inverse;
BigInteger current_sum = op_inverse;
int current_sign = 1;
int n = 1;
BigInteger max_trunc_error =
big1.shiftLeft(p - 2 - calc_precision);
while (current_term.abs().compareTo(max_trunc_error) >= 0) {
if (Thread.interrupted() || please_stop) throw new AbortedException();
n += 2;
current_power = current_power.divide(big_op_squared);
current_sign = -current_sign;
current_term =
current_power.divide(BigInteger.valueOf(current_sign*n));
current_sum = current_sum.add(current_term);
}
return scale(current_sum, calc_precision - p);
}
}
// Representation for ln(1 + op)
class prescaled_ln_CR extends slow_CR {
CR op;
prescaled_ln_CR(CR x) { op = x; }
// Compute an approximation of ln(1+x) to precision
// prec. This assumes |x| < 1/2.
// It uses a Taylor series expansion.
// Unfortunately there appears to be no way to take
// advantage of old information.
// Note: this is known to be a bad algorithm for
// floating point. Unfortunately, other alternatives
// appear to require precomputed tabular information.
protected BigInteger approximate(int p) {
if (p >= 0) return big0;
int iterations_needed = -p; // conservative estimate > 0.
// Claim: each intermediate term is accurate
// to 2*2^calc_precision. Total error is
// 2*iterations_needed*2^calc_precision
// exclusive of error in op.
int calc_precision = p - bound_log2(2*iterations_needed)
- 4; // for error in op, truncation.
int op_prec = p - 3;
BigInteger op_appr = op.get_appr(op_prec);
// Error analysis as for exponential.
BigInteger scaled_1 = big1.shiftLeft(-calc_precision);
BigInteger x_nth = scale(op_appr, op_prec - calc_precision);
BigInteger current_term = x_nth; // x**n
BigInteger current_sum = current_term;
int n = 1;
int current_sign = 1; // (-1)^(n-1)
BigInteger max_trunc_error =
big1.shiftLeft(p - 4 - calc_precision);
while (current_term.abs().compareTo(max_trunc_error) >= 0) {
if (Thread.interrupted() || please_stop) throw new AbortedException();
n += 1;
current_sign = -current_sign;
x_nth = scale(x_nth.multiply(op_appr), op_prec);
current_term = x_nth.divide(BigInteger.valueOf(n * current_sign));
// x**n / (n * (-1)**(n-1))
current_sum = current_sum.add(current_term);
}
return scale(current_sum, calc_precision - p);
}
}
// Representation of the arcsine of a constructive real. Private.
// Uses a Taylor series expansion. Assumes |x| < (1/2)^(1/3).
class prescaled_asin_CR extends slow_CR {
CR op;
prescaled_asin_CR(CR x) {
op = x;
}
protected BigInteger approximate(int p) {
// The Taylor series is the sum of x^(2n+1) * (2n)!/(4^n n!^2 (2n+1))
// Note that (2n)!/(4^n n!^2) is always less than one.
// (The denominator is effectively 2n*2n*(2n-2)*(2n-2)*...*2*2
// which is clearly > (2n)!)
// Thus all terms are bounded by x^(2n+1).
// Unfortunately, there's no easy way to prescale the argument
// to less than 1/sqrt(2), and we can only approximate that.
// Thus the worst case iteration count is fairly high.
// But it doesn't make much difference.
if (p >= 2) return big0; // Never bigger than 4.
int iterations_needed = -3 * p / 2 + 4;
// conservative estimate > 0.
// Follows from assumed bound on x and
// the fact that only every other Taylor
// Series term is present.
// Claim: each intermediate term is accurate
// to 2*2^calc_precision.
// Total rounding error in series computation is
// 2*iterations_needed*2^calc_precision,
// exclusive of error in op.
int calc_precision = p - bound_log2(2*iterations_needed)
- 4; // for error in op, truncation.
int op_prec = p - 3; // always <= -2
BigInteger op_appr = op.get_appr(op_prec);
// Error in argument results in error of < 1/4 ulp.
// (Derivative is bounded by 2 in the specified range and we use
// 3 extra digits.)
// Ignoring the argument error, each term has an error of
// < 3ulps relative to calc_precision, which is more precise than p.
// Cumulative arithmetic rounding error is < 3/16 ulp (relative to p).
// Series truncation error < 2/16 ulp. (Each computed term
// is at most 2/3 of last one, so some of remaining series <
// 3/2 * current term.)
// Final rounding error is <= 1/2 ulp.
// Thus final error is < 1 ulp (relative to p).
BigInteger max_last_term =
big1.shiftLeft(p - 4 - calc_precision);
int exp = 1; // Current exponent, = 2n+1 in above expression
BigInteger current_term = op_appr.shiftLeft(op_prec - calc_precision);
BigInteger current_sum = current_term;
BigInteger current_factor = current_term;
// Current scaled Taylor series term
// before division by the exponent.
// Accurate to 3 ulp at calc_precision.
while (current_term.abs().compareTo(max_last_term) >= 0) {
if (Thread.interrupted() || please_stop) throw new AbortedException();
exp += 2;
// current_factor = current_factor * op * op * (exp-1) * (exp-2) /
// (exp-1) * (exp-1), with the two exp-1 factors cancelling,
// giving
// current_factor = current_factor * op * op * (exp-2) / (exp-1)
// Thus the error any in the previous term is multiplied by
// op^2, adding an error of < (1/2)^(2/3) < 2/3 the original
// error.
current_factor = current_factor.multiply(BigInteger.valueOf(exp - 2));
current_factor = scale(current_factor.multiply(op_appr), op_prec + 2);
// Carry 2 extra bits of precision forward; thus
// this effectively introduces 1/8 ulp error.
current_factor = current_factor.multiply(op_appr);
BigInteger divisor = BigInteger.valueOf(exp - 1);
current_factor = current_factor.divide(divisor);
// Another 1/4 ulp error here.
current_factor = scale(current_factor, op_prec - 2);
// Remove extra 2 bits. 1/2 ulp rounding error.
// Current_factor has original 3 ulp rounding error, which we
// reduced by 1, plus < 1 ulp new rounding error.
current_term = current_factor.divide(BigInteger.valueOf(exp));
// Contributes 1 ulp error to sum plus at most 3 ulp
// from current_factor.
current_sum = current_sum.add(current_term);
}
return scale(current_sum, calc_precision - p);
}
}
class sqrt_CR extends CR {
CR op;
sqrt_CR(CR x) { op = x; }
// Explicitly provide an initial approximation.
// Useful for arithmetic geometric mean algorithms, where we've previously
// computed a very similar square root.
sqrt_CR(CR x, int min_p, BigInteger max_a) {
op = x;
min_prec = min_p;
max_appr = max_a;
appr_valid = true;
}
final int fp_prec = 50; // Conservative estimate of number of
// significant bits in double precision
// computation.
final int fp_op_prec = 60;
protected BigInteger approximate(int p) {
int max_op_prec_needed = 2*p - 1;
int msd = op.iter_msd(max_op_prec_needed);
if (msd <= max_op_prec_needed) return big0;
int result_msd = msd/2; // +- 1
int result_digits = result_msd - p; // +- 2
if (result_digits > fp_prec) {
// Compute less precise approximation and use a Newton iter.
int appr_digits = result_digits/2 + 6;
// This should be conservative. Is fewer enough?
int appr_prec = result_msd - appr_digits;
int prod_prec = 2*appr_prec;
// First compute the argument to maximal precision, so we don't end up
// reevaluating it incrementally.
BigInteger op_appr = op.get_appr(prod_prec);
BigInteger last_appr = get_appr(appr_prec);
// Compute (last_appr * last_appr + op_appr) / last_appr / 2
// while adjusting the scaling to make everything work
BigInteger prod_prec_scaled_numerator =
last_appr.multiply(last_appr).add(op_appr);
BigInteger scaled_numerator =
scale(prod_prec_scaled_numerator, appr_prec - p);
BigInteger shifted_result = scaled_numerator.divide(last_appr);
return shifted_result.add(big1).shiftRight(1);
} else {
// Use a double precision floating point approximation.
// Make sure all precisions are even
int op_prec = (msd - fp_op_prec) & ~1;
int working_prec = op_prec - fp_op_prec;
BigInteger scaled_bi_appr = op.get_appr(op_prec)
.shiftLeft(fp_op_prec);
double scaled_appr = scaled_bi_appr.doubleValue();
if (scaled_appr < 0.0)
throw new ArithmeticException("sqrt(negative)");
double scaled_fp_sqrt = Math.sqrt(scaled_appr);
BigInteger scaled_sqrt = BigInteger.valueOf((long)scaled_fp_sqrt);
int shift_count = working_prec/2 - p;
return shift(scaled_sqrt, shift_count);
}
}
}
// The constant PI, computed using the Gauss-Legendre alternating
// arithmetic-geometric mean algorithm:
// a[0] = 1
// b[0] = 1/sqrt(2)
// t[0] = 1/4
// p[0] = 1
//
// a[n+1] = (a[n] + b[n])/2 (arithmetic mean, between 0.8 and 1)
// b[n+1] = sqrt(a[n] * b[n]) (geometric mean, between 0.7 and 1)
// t[n+1] = t[n] - (2^n)(a[n]-a[n+1])^2, (always between 0.2 and 0.25)
//
// pi is then approximated as (a[n+1]+b[n+1])^2 / 4*t[n+1].
//
class gl_pi_CR extends slow_CR {
// In addition to the best approximation kept by the CR base class, we keep
// the entire sequence b[n], to the extent we've needed it so far. Each
// reevaluation leads to slightly different sqrt arguments, but the
// previous result can be used to avoid repeating low precision Newton
// iterations for the sqrt approximation.
ArrayList<Integer> b_prec = new ArrayList<Integer>();
ArrayList<BigInteger> b_val = new ArrayList<BigInteger>();
gl_pi_CR() {
b_prec.add(null); // Zeroth entry unused.
b_val.add(null);
}
private static BigInteger TOLERANCE = BigInteger.valueOf(4);
// sqrt(1/2)
private static CR SQRT_HALF = new sqrt_CR(ONE.shiftRight(1));
protected BigInteger approximate(int p) {
// Rough approximations are easy.
if (p >= 0) return scale(BigInteger.valueOf(3), -p);
// We need roughly log2(p) iterations. Each iteration should
// contribute no more than 2 ulps to the error in the corresponding
// term (a[n], b[n], or t[n]). Thus 2log2(n) bits plus a few for the
// final calulation and rounding suffice.
final int extra_eval_prec =
(int)Math.ceil(Math.log(-p) / Math.log(2)) + 10;
// All our terms are implicitly scaled by eval_prec.
final int eval_prec = p - extra_eval_prec;
BigInteger a = BigInteger.ONE.shiftLeft(-eval_prec);
BigInteger b = SQRT_HALF.get_appr(eval_prec);
BigInteger t = BigInteger.ONE.shiftLeft(-eval_prec - 2);
int n = 0;
while (a.subtract(b).subtract(TOLERANCE).signum() > 0) {
// Current values correspond to n, next_ values to n + 1
// b_prec.size() == b_val.size() >= n + 1
final BigInteger next_a = a.add(b).shiftRight(1);
final BigInteger a_diff = a.subtract(next_a);
CR next_b_as_CR;
final BigInteger b_prod = a.multiply(b).shiftRight(-eval_prec);
// We the compute square root approximations using a nested
// temporary CR computation, to avoid implementing BigInteger
// square roots separately.
final CR b_prod_as_CR = CR.valueOf(b_prod).shiftRight(-eval_prec);
if (b_prec.size() == n + 1) {
// Need an n+1st slot.
b_prec.add(null);
b_val.add(null);
next_b_as_CR = b_prod_as_CR.sqrt();
} else {
// Reuse previous approximation to reduce sqrt iterations,
// hopefully to one.
next_b_as_CR = new sqrt_CR(b_prod_as_CR, b_prec.get(n + 1),
b_val.get(n + 1));
}
// b_prec.size() == b_val.size() >= n + 2
final BigInteger next_b = next_b_as_CR.get_appr(eval_prec);
b_prec.set(n + 1, Integer.valueOf(p));
b_val.set(n + 1, scale(next_b, -extra_eval_prec));
final BigInteger next_t =
t.subtract(a_diff.multiply(a_diff)
.shiftLeft(n + eval_prec)); // shift dist. usually neg.
a = next_a;
b = next_b;
t = next_t;
++n;
}
final BigInteger sum = a.add(b);
final BigInteger result = sum.multiply(sum).divide(t).shiftRight(2);
return scale(result, -extra_eval_prec);
}
}