| /* |
| * Copyright (c) 2001, 2014, 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); |
| } |
| |
| 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(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->cr(); |
| } |