1 /*
2 * Copyright (c) 2001, 2012, 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
31 AbsSeq::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
36 void 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
50 double AbsSeq::avg() const {
51 if (_num == 0)
52 return 0.0;
53 else
54 return _sum / total();
55 }
56
57 double 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
74 double AbsSeq::sd() const {
75 double var = variance();
76 guarantee( var >= 0.0, "variance should not be negative" );
77 return sqrt(var);
78 }
79
80 double AbsSeq::davg() const {
81 return _davg;
82 }
83
84 double 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
100 double AbsSeq::dsd() const {
101 double var = dvariance();
102 guarantee( var >= 0.0, "variance should not be negative" );
103 return sqrt(var);
104 }
105
106 NumberSeq::NumberSeq(double alpha) :
107 AbsSeq(alpha), _maximum(0.0), _last(0.0) {
108 }
109
110 bool 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
118 NumberSeq::NumberSeq(NumberSeq *total, int n, NumberSeq **parts) {
119 guarantee(check_nums(total, n, parts), "all seq lengths should match");
120 double sum = total->sum();
121 for (int i = 0; i < n; ++i) {
122 if (parts[i] != NULL)
123 sum -= parts[i]->sum();
124 }
125
126 _num = total->num();
127 _sum = sum;
128
129 // we do not calculate these...
130 _sum_of_squares = -1.0;
131 _maximum = -1.0;
132 _davg = -1.0;
133 _dvariance = -1.0;
134 }
135
136 void NumberSeq::add(double val) {
137 AbsSeq::add(val);
138
139 _last = val;
140 if (_num == 0) {
141 _maximum = val;
142 } else {
143 if (val > _maximum)
144 _maximum = val;
145 }
146 _sum += val;
147 _sum_of_squares += val * val;
148 ++_num;
149 }
150
151
152 TruncatedSeq::TruncatedSeq(int length, double alpha):
153 AbsSeq(alpha), _length(length), _next(0) {
154 _sequence = NEW_C_HEAP_ARRAY(double, _length);
155 for (int i = 0; i < _length; ++i)
156 _sequence[i] = 0.0;
157 }
158
159 TruncatedSeq::~TruncatedSeq() {
160 FREE_C_HEAP_ARRAY(double, _sequence);
161 }
162
163 void TruncatedSeq::add(double val) {
164 AbsSeq::add(val);
165
166 // get the oldest value in the sequence...
167 double old_val = _sequence[_next];
168 // ...remove it from the sum and sum of squares
169 _sum -= old_val;
170 _sum_of_squares -= old_val * old_val;
171
172 // ...and update them with the new value
173 _sum += val;
174 _sum_of_squares += val * val;
175
176 // now replace the old value with the new one
177 _sequence[_next] = val;
178 _next = (_next + 1) % _length;
179
180 // only increase it if the buffer is not full
181 if (_num < _length)
182 ++_num;
183
184 guarantee( variance() > -1.0, "variance should be >= 0" );
185 }
186
187 // can't easily keep track of this incrementally...
188 double TruncatedSeq::maximum() const {
189 if (_num == 0)
190 return 0.0;
191 double ret = _sequence[0];
192 for (int i = 1; i < _num; ++i) {
193 double val = _sequence[i];
194 if (val > ret)
195 ret = val;
196 }
197 return ret;
198 }
199
200 double TruncatedSeq::last() const {
201 if (_num == 0)
202 return 0.0;
203 unsigned last_index = (_next + _length - 1) % _length;
204 return _sequence[last_index];
205 }
206
207 double TruncatedSeq::oldest() const {
208 if (_num == 0)
209 return 0.0;
210 else if (_num < _length)
211 // index 0 always oldest value until the array is full
212 return _sequence[0];
213 else {
214 // since the array is full, _next is over the oldest value
215 return _sequence[_next];
216 }
217 }
218
219 double TruncatedSeq::predict_next() const {
220 if (_num == 0)
221 return 0.0;
222
223 double num = (double) _num;
224 double x_squared_sum = 0.0;
225 double x_sum = 0.0;
226 double y_sum = 0.0;
227 double xy_sum = 0.0;
228 double x_avg = 0.0;
229 double y_avg = 0.0;
230
231 int first = (_next + _length - _num) % _length;
232 for (int i = 0; i < _num; ++i) {
233 double x = (double) i;
234 double y = _sequence[(first + i) % _length];
235
236 x_squared_sum += x * x;
237 x_sum += x;
238 y_sum += y;
239 xy_sum += x * y;
240 }
241 x_avg = x_sum / num;
242 y_avg = y_sum / num;
243
244 double Sxx = x_squared_sum - x_sum * x_sum / num;
245 double Sxy = xy_sum - x_sum * y_sum / num;
246 double b1 = Sxy / Sxx;
247 double b0 = y_avg - b1 * x_avg;
248
249 return b0 + b1 * num;
250 }
251
252
253 // Printing/Debugging Support
254
255 void AbsSeq::dump() { dump_on(gclog_or_tty); }
256
257 void AbsSeq::dump_on(outputStream* s) {
258 s->print_cr("\t _num = %d, _sum = %7.3f, _sum_of_squares = %7.3f",
259 _num, _sum, _sum_of_squares);
260 s->print_cr("\t _davg = %7.3f, _dvariance = %7.3f, _alpha = %7.3f",
261 _davg, _dvariance, _alpha);
262 }
263
264 void NumberSeq::dump_on(outputStream* s) {
265 AbsSeq::dump_on(s);
266 s->print_cr("\t\t _last = %7.3f, _maximum = %7.3f");
267 }
268
269 void TruncatedSeq::dump_on(outputStream* s) {
270 AbsSeq::dump_on(s);
271 s->print_cr("\t\t _length = %d, _next = %d", _length, _next);
272 for (int i = 0; i < _length; i++) {
273 if (i%5 == 0) {
274 s->cr();
275 s->print("\t");
276 }
277 s->print("\t[%d]=%7.3f", i, _sequence[i]);
278 }
279 s->print_cr("");
280 }