/*
* Copyright (c) 2001, 2012, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*
*/
#include "precompiled.hpp"
#include "memory/allocation.inline.hpp"
#include "utilities/debug.hpp"
#include "utilities/globalDefinitions.hpp"
#include "utilities/numberSeq.hpp"
AbsSeq::AbsSeq(double alpha) :
_num(0), _sum(0.0), _sum_of_squares(0.0),
_davg(0.0), _dvariance(0.0), _alpha(alpha) {
}
void AbsSeq::add(double val) {
if (_num == 0) {
// if the sequence is empty, the davg is the same as the value
_davg = val;
// and the variance is 0
_dvariance = 0.0;
} else {
// otherwise, calculate both
_davg = (1.0 - _alpha) * val + _alpha * _davg;
double diff = val - _davg;
_dvariance = (1.0 - _alpha) * diff * diff + _alpha * _dvariance;
}
}
double AbsSeq::avg() const {
if (_num == 0)
return 0.0;
else
return _sum / total();
}
double AbsSeq::variance() const {
if (_num <= 1)
return 0.0;
double x_bar = avg();
double result = _sum_of_squares / total() - x_bar * x_bar;
if (result < 0.0) {
// due to loss-of-precision errors, the variance might be negative
// by a small bit
// guarantee(-0.1 < result && result < 0.0,
// "if variance is negative, it should be very small");
result = 0.0;
}
return result;
}
double AbsSeq::sd() const {
double var = variance();
guarantee( var >= 0.0, "variance should not be negative" );
return sqrt(var);
}
double AbsSeq::davg() const {
return _davg;
}
double AbsSeq::dvariance() const {
if (_num <= 1)
return 0.0;
double result = _dvariance;
if (result < 0.0) {
// due to loss-of-precision errors, the variance might be negative
// by a small bit
guarantee(-0.1 < result && result < 0.0,
"if variance is negative, it should be very small");
result = 0.0;
}
return result;
}
double AbsSeq::dsd() const {
double var = dvariance();
guarantee( var >= 0.0, "variance should not be negative" );
return sqrt(var);
}
NumberSeq::NumberSeq(double alpha) :
AbsSeq(alpha), _maximum(0.0), _last(0.0) {
}
bool NumberSeq::check_nums(NumberSeq *total, int n, NumberSeq **parts) {
for (int i = 0; i < n; ++i) {
if (parts[i] != NULL && total->num() != parts[i]->num())
return false;
}
return true;
}
void NumberSeq::add(double val) {
AbsSeq::add(val);
_last = val;
if (_num == 0) {
_maximum = val;
} else {
if (val > _maximum)
_maximum = val;
}
_sum += val;
_sum_of_squares += val * val;
++_num;
}
TruncatedSeq::TruncatedSeq(int length, double alpha):
AbsSeq(alpha), _length(length), _next(0) {
_sequence = NEW_C_HEAP_ARRAY(double, _length, mtInternal);
for (int i = 0; i < _length; ++i)
_sequence[i] = 0.0;
}
TruncatedSeq::~TruncatedSeq() {
FREE_C_HEAP_ARRAY(double, _sequence, mtGC);
}
void TruncatedSeq::add(double val) {
AbsSeq::add(val);
// get the oldest value in the sequence...
double old_val = _sequence[_next];
// ...remove it from the sum and sum of squares
_sum -= old_val;
_sum_of_squares -= old_val * old_val;
// ...and update them with the new value
_sum += val;
_sum_of_squares += val * val;
// now replace the old value with the new one
_sequence[_next] = val;
_next = (_next + 1) % _length;
// only increase it if the buffer is not full
if (_num < _length)
++_num;
guarantee( variance() > -1.0, "variance should be >= 0" );
}
// can't easily keep track of this incrementally...
double TruncatedSeq::maximum() const {
if (_num == 0)
return 0.0;
double ret = _sequence[0];
for (int i = 1; i < _num; ++i) {
double val = _sequence[i];
if (val > ret)
ret = val;
}
return ret;
}
double TruncatedSeq::last() const {
if (_num == 0)
return 0.0;
unsigned last_index = (_next + _length - 1) % _length;
return _sequence[last_index];
}
double TruncatedSeq::oldest() const {
if (_num == 0)
return 0.0;
else if (_num < _length)
// index 0 always oldest value until the array is full
return _sequence[0];
else {
// since the array is full, _next is over the oldest value
return _sequence[_next];
}
}
double TruncatedSeq::predict_next() const {
if (_num == 0)
return 0.0;
double num = (double) _num;
double x_squared_sum = 0.0;
double x_sum = 0.0;
double y_sum = 0.0;
double xy_sum = 0.0;
double x_avg = 0.0;
double y_avg = 0.0;
int first = (_next + _length - _num) % _length;
for (int i = 0; i < _num; ++i) {
double x = (double) i;
double y = _sequence[(first + i) % _length];
x_squared_sum += x * x;
x_sum += x;
y_sum += y;
xy_sum += x * y;
}
x_avg = x_sum / num;
y_avg = y_sum / num;
double Sxx = x_squared_sum - x_sum * x_sum / num;
double Sxy = xy_sum - x_sum * y_sum / num;
double b1 = Sxy / Sxx;
double b0 = y_avg - b1 * x_avg;
return b0 + b1 * num;
}
// Printing/Debugging Support
void AbsSeq::dump() { dump_on(gclog_or_tty); }
void AbsSeq::dump_on(outputStream* s) {
s->print_cr("\t _num = %d, _sum = %7.3f, _sum_of_squares = %7.3f",
_num, _sum, _sum_of_squares);
s->print_cr("\t _davg = %7.3f, _dvariance = %7.3f, _alpha = %7.3f",
_davg, _dvariance, _alpha);
}
void NumberSeq::dump_on(outputStream* s) {
AbsSeq::dump_on(s);
s->print_cr("\t\t _last = %7.3f, _maximum = %7.3f", _last, _maximum);
}
void TruncatedSeq::dump_on(outputStream* s) {
AbsSeq::dump_on(s);
s->print_cr("\t\t _length = %d, _next = %d", _length, _next);
for (int i = 0; i < _length; i++) {
if (i%5 == 0) {
s->cr();
s->print("\t");
}
s->print("\t[%d]=%7.3f", i, _sequence[i]);
}
s->print_cr("");
}