1/*
2 * Copyright (c) 2001, 2014, Oracle and/or its affiliates. All rights reserved.
3 * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
4 *
5 * This code is free software; you can redistribute it and/or modify it
6 * under the terms of the GNU General Public License version 2 only, as
7 * published by the Free Software Foundation.
8 *
9 * This code is distributed in the hope that it will be useful, but WITHOUT
10 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
11 * FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License
12 * version 2 for more details (a copy is included in the LICENSE file that
13 * accompanied this code).
14 *
15 * You should have received a copy of the GNU General Public License version
16 * 2 along with this work; if not, write to the Free Software Foundation,
17 * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
18 *
19 * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
20 * or visit www.oracle.com if you need additional information or have any
21 * questions.
22 *
23 */
24
25#include "precompiled.hpp"
26#include "memory/allocation.inline.hpp"
27#include "utilities/debug.hpp"
28#include "utilities/globalDefinitions.hpp"
29#include "utilities/numberSeq.hpp"
30
31AbsSeq::AbsSeq(double alpha) :
32  _num(0), _sum(0.0), _sum_of_squares(0.0),
33  _davg(0.0), _dvariance(0.0), _alpha(alpha) {
34}
35
36void AbsSeq::add(double val) {
37  if (_num == 0) {
38    // if the sequence is empty, the davg is the same as the value
39    _davg = val;
40    // and the variance is 0
41    _dvariance = 0.0;
42  } else {
43    // otherwise, calculate both
44    _davg = (1.0 - _alpha) * val + _alpha * _davg;
45    double diff = val - _davg;
46    _dvariance = (1.0 - _alpha) * diff * diff + _alpha * _dvariance;
47  }
48}
49
50double AbsSeq::avg() const {
51  if (_num == 0)
52    return 0.0;
53  else
54    return _sum / total();
55}
56
57double AbsSeq::variance() const {
58  if (_num <= 1)
59    return 0.0;
60
61  double x_bar = avg();
62  double result = _sum_of_squares / total() - x_bar * x_bar;
63  if (result < 0.0) {
64    // due to loss-of-precision errors, the variance might be negative
65    // by a small bit
66
67    //    guarantee(-0.1 < result && result < 0.0,
68    //        "if variance is negative, it should be very small");
69    result = 0.0;
70  }
71  return result;
72}
73
74double AbsSeq::sd() const {
75  double var = variance();
76  guarantee( var >= 0.0, "variance should not be negative" );
77  return sqrt(var);
78}
79
80double AbsSeq::davg() const {
81  return _davg;
82}
83
84double AbsSeq::dvariance() const {
85  if (_num <= 1)
86    return 0.0;
87
88  double result = _dvariance;
89  if (result < 0.0) {
90    // due to loss-of-precision errors, the variance might be negative
91    // by a small bit
92
93    guarantee(-0.1 < result && result < 0.0,
94               "if variance is negative, it should be very small");
95    result = 0.0;
96  }
97  return result;
98}
99
100double AbsSeq::dsd() const {
101  double var = dvariance();
102  guarantee( var >= 0.0, "variance should not be negative" );
103  return sqrt(var);
104}
105
106NumberSeq::NumberSeq(double alpha) :
107  AbsSeq(alpha), _maximum(0.0), _last(0.0) {
108}
109
110bool NumberSeq::check_nums(NumberSeq *total, int n, NumberSeq **parts) {
111  for (int i = 0; i < n; ++i) {
112    if (parts[i] != NULL && total->num() != parts[i]->num())
113      return false;
114  }
115  return true;
116}
117
118void NumberSeq::add(double val) {
119  AbsSeq::add(val);
120
121  _last = val;
122  if (_num == 0) {
123    _maximum = val;
124  } else {
125    if (val > _maximum)
126      _maximum = val;
127  }
128  _sum += val;
129  _sum_of_squares += val * val;
130  ++_num;
131}
132
133
134TruncatedSeq::TruncatedSeq(int length, double alpha):
135  AbsSeq(alpha), _length(length), _next(0) {
136  _sequence = NEW_C_HEAP_ARRAY(double, _length, mtInternal);
137  for (int i = 0; i < _length; ++i)
138    _sequence[i] = 0.0;
139}
140
141TruncatedSeq::~TruncatedSeq() {
142  FREE_C_HEAP_ARRAY(double, _sequence);
143}
144
145void TruncatedSeq::add(double val) {
146  AbsSeq::add(val);
147
148  // get the oldest value in the sequence...
149  double old_val = _sequence[_next];
150  // ...remove it from the sum and sum of squares
151  _sum -= old_val;
152  _sum_of_squares -= old_val * old_val;
153
154  // ...and update them with the new value
155  _sum += val;
156  _sum_of_squares += val * val;
157
158  // now replace the old value with the new one
159  _sequence[_next] = val;
160  _next = (_next + 1) % _length;
161
162  // only increase it if the buffer is not full
163  if (_num < _length)
164    ++_num;
165
166  guarantee( variance() > -1.0, "variance should be >= 0" );
167}
168
169// can't easily keep track of this incrementally...
170double TruncatedSeq::maximum() const {
171  if (_num == 0)
172    return 0.0;
173  double ret = _sequence[0];
174  for (int i = 1; i < _num; ++i) {
175    double val = _sequence[i];
176    if (val > ret)
177      ret = val;
178  }
179  return ret;
180}
181
182double TruncatedSeq::last() const {
183  if (_num == 0)
184    return 0.0;
185  unsigned last_index = (_next + _length - 1) % _length;
186  return _sequence[last_index];
187}
188
189double TruncatedSeq::oldest() const {
190  if (_num == 0)
191    return 0.0;
192  else if (_num < _length)
193    // index 0 always oldest value until the array is full
194    return _sequence[0];
195  else {
196    // since the array is full, _next is over the oldest value
197    return _sequence[_next];
198  }
199}
200
201double TruncatedSeq::predict_next() const {
202  if (_num == 0)
203    return 0.0;
204
205  double num           = (double) _num;
206  double x_squared_sum = 0.0;
207  double x_sum         = 0.0;
208  double y_sum         = 0.0;
209  double xy_sum        = 0.0;
210  double x_avg         = 0.0;
211  double y_avg         = 0.0;
212
213  int first = (_next + _length - _num) % _length;
214  for (int i = 0; i < _num; ++i) {
215    double x = (double) i;
216    double y =  _sequence[(first + i) % _length];
217
218    x_squared_sum += x * x;
219    x_sum         += x;
220    y_sum         += y;
221    xy_sum        += x * y;
222  }
223  x_avg = x_sum / num;
224  y_avg = y_sum / num;
225
226  double Sxx = x_squared_sum - x_sum * x_sum / num;
227  double Sxy = xy_sum - x_sum * y_sum / num;
228  double b1 = Sxy / Sxx;
229  double b0 = y_avg - b1 * x_avg;
230
231  return b0 + b1 * num;
232}
233
234
235// Printing/Debugging Support
236
237void AbsSeq::dump() { dump_on(tty); }
238
239void AbsSeq::dump_on(outputStream* s) {
240  s->print_cr("\t _num = %d, _sum = %7.3f, _sum_of_squares = %7.3f",
241                  _num,      _sum,         _sum_of_squares);
242  s->print_cr("\t _davg = %7.3f, _dvariance = %7.3f, _alpha = %7.3f",
243                  _davg,         _dvariance,         _alpha);
244}
245
246void NumberSeq::dump_on(outputStream* s) {
247  AbsSeq::dump_on(s);
248  s->print_cr("\t\t _last = %7.3f, _maximum = %7.3f", _last, _maximum);
249}
250
251void TruncatedSeq::dump_on(outputStream* s) {
252  AbsSeq::dump_on(s);
253  s->print_cr("\t\t _length = %d, _next = %d", _length, _next);
254  for (int i = 0; i < _length; i++) {
255    if (i%5 == 0) {
256      s->cr();
257      s->print("\t");
258    }
259    s->print("\t[%d]=%7.3f", i, _sequence[i]);
260  }
261  s->cr();
262}
263