```  1 /*
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
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  *
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
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     // Formula from "Incremental calculation of weighted mean and variance" by Tony Finch
45     // diff := x - mean
46     // incr := alpha * diff
47     // mean := mean + incr
48     // variance := (1 - alpha) * (variance + diff * incr)
49     // PDF available at https://fanf2.user.srcf.net/hermes/doc/antiforgery/stats.pdf
50     double diff = val - _davg;
51     double incr = _alpha * diff;
52     _davg += incr;
53     _dvariance = (1.0 - _alpha) * (_dvariance + diff * incr);
54   }
55 }
56
57 double AbsSeq::avg() const {
58   if (_num == 0)
59     return 0.0;
60   else
61     return _sum / total();
62 }
63
64 double AbsSeq::variance() const {
65   if (_num <= 1)
66     return 0.0;
67
68   double x_bar = avg();
69   double result = _sum_of_squares / total() - x_bar * x_bar;
70   if (result < 0.0) {
71     // due to loss-of-precision errors, the variance might be negative
72     // by a small bit
73
74     //    guarantee(-0.1 < result && result < 0.0,
75     //        "if variance is negative, it should be very small");
76     result = 0.0;
77   }
78   return result;
79 }
80
81 double AbsSeq::sd() const {
82   double var = variance();
83   guarantee( var >= 0.0, "variance should not be negative" );
84   return sqrt(var);
85 }
86
87 double AbsSeq::davg() const {
88   return _davg;
89 }
90
91 double AbsSeq::dvariance() const {
92   if (_num <= 1)
93     return 0.0;
94
95   double result = _dvariance;
96   if (result < 0.0) {
97     // due to loss-of-precision errors, the variance might be negative
98     // by a small bit
99
100     guarantee(-0.1 < result && result < 0.0,
101                "if variance is negative, it should be very small");
102     result = 0.0;
103   }
104   return result;
105 }
106
107 double AbsSeq::dsd() const {
108   double var = dvariance();
109   guarantee( var >= 0.0, "variance should not be negative" );
110   return sqrt(var);
111 }
112
113 void AbsSeq::merge(AbsSeq& abs2, bool clear_this) {
114
115   if (num() == 0) return;  // nothing to do
116
117   abs2._num += _num;
118   abs2._sum += _sum;
119   abs2._sum_of_squares += _sum_of_squares;
120
121   // Decaying stats need a bit more thought
122   assert(abs2._alpha == _alpha, "Caution: merge incompatible?");
123   // Until JDK-8298902 is fixed, we taint the decaying statistics
124   if (abs2._davg != NAN) {
125     abs2._davg = NAN;
126     abs2._dvariance = NAN;
127   }
128
129   if (clear_this) {
130     _num = 0;
131     _sum = 0;
132     _sum_of_squares = 0;
133     _davg = 0;
134     _dvariance = 0;
135   }
136 }
137
138
139 NumberSeq::NumberSeq(double alpha) :
140   AbsSeq(alpha), _last(0.0), _maximum(0.0) {
141 }
142
143 bool NumberSeq::check_nums(NumberSeq *total, int n, NumberSeq **parts) {
144   for (int i = 0; i < n; ++i) {
145     if (parts[i] != nullptr && total->num() != parts[i]->num())
146       return false;
147   }
148   return true;
149 }
150
153
154   _last = val;
155   if (_num == 0) {
156     _maximum = val;
157   } else {
158     if (val > _maximum)
159       _maximum = val;
160   }
161   _sum += val;
162   _sum_of_squares += val * val;
163   ++_num;
164 }
165
166 void NumberSeq::merge(NumberSeq& nseq2, bool clear_this) {
167
168   if (num() == 0) return;  // nothing to do
169
170   nseq2._last = _last;   // this is newer than that
171   nseq2._maximum = MAX2(_maximum, nseq2._maximum);
172
173   AbsSeq::merge(nseq2, clear_this);
174
175   if (clear_this) {
176     _last = 0;
177     _maximum = 0;
178     assert(num() == 0, "Not cleared");
179   }
180 }
181
182
183 TruncatedSeq::TruncatedSeq(int length, double alpha):
184   AbsSeq(alpha), _length(length), _next(0) {
185   _sequence = NEW_C_HEAP_ARRAY(double, _length, mtInternal);
186   for (int i = 0; i < _length; ++i)
187     _sequence[i] = 0.0;
188 }
189
190 TruncatedSeq::~TruncatedSeq() {
191   FREE_C_HEAP_ARRAY(double, _sequence);
192 }
193
196
197   // get the oldest value in the sequence...
198   double old_val = _sequence[_next];
199   // ...remove it from the sum and sum of squares
200   _sum -= old_val;
201   _sum_of_squares -= old_val * old_val;
202
203   // ...and update them with the new value
204   _sum += val;
205   _sum_of_squares += val * val;
206
207   // now replace the old value with the new one
208   _sequence[_next] = val;
209   _next = (_next + 1) % _length;
210
211   // only increase it if the buffer is not full
212   if (_num < _length)
213     ++_num;
214
215   guarantee( variance() > -1.0, "variance should be >= 0" );
216 }
217
218 // can't easily keep track of this incrementally...
219 double TruncatedSeq::maximum() const {
220   if (_num == 0)
221     return 0.0;
222   double ret = _sequence[0];
223   for (int i = 1; i < _num; ++i) {
224     double val = _sequence[i];
225     if (val > ret)
226       ret = val;
227   }
228   return ret;
229 }
230
231 double TruncatedSeq::last() const {
232   if (_num == 0)
233     return 0.0;
234   unsigned last_index = (_next + _length - 1) % _length;
235   return _sequence[last_index];
236 }
237
238 double TruncatedSeq::oldest() const {
239   if (_num == 0)
240     return 0.0;
241   else if (_num < _length)
242     // index 0 always oldest value until the array is full
243     return _sequence[0];
244   else {
245     // since the array is full, _next is over the oldest value
246     return _sequence[_next];
247   }
248 }
249
250 double TruncatedSeq::predict_next() const {
251   if (_num == 0)
252     return 0.0;
253
254   double num           = (double) _num;
255   double x_squared_sum = 0.0;
256   double x_sum         = 0.0;
257   double y_sum         = 0.0;
258   double xy_sum        = 0.0;
259   double x_avg         = 0.0;
260   double y_avg         = 0.0;
261
262   int first = (_next + _length - _num) % _length;
263   for (int i = 0; i < _num; ++i) {
264     double x = (double) i;
265     double y =  _sequence[(first + i) % _length];
266
267     x_squared_sum += x * x;
268     x_sum         += x;
269     y_sum         += y;
270     xy_sum        += x * y;
271   }
272   x_avg = x_sum / num;
273   y_avg = y_sum / num;
274
275   double Sxx = x_squared_sum - x_sum * x_sum / num;
276   double Sxy = xy_sum - x_sum * y_sum / num;
277   double b1 = Sxy / Sxx;
278   double b0 = y_avg - b1 * x_avg;
279
280   return b0 + b1 * num;
281 }
282
283
284 // Printing/Debugging Support
285
286 void AbsSeq::dump() { dump_on(tty); }
287
288 void AbsSeq::dump_on(outputStream* s) {
289   s->print_cr("\t _num = %d, _sum = %7.3f, _sum_of_squares = %7.3f",
290                   _num,      _sum,         _sum_of_squares);
291   s->print_cr("\t _davg = %7.3f, _dvariance = %7.3f, _alpha = %7.3f",
292                   _davg,         _dvariance,         _alpha);
293 }
294
295 void NumberSeq::dump_on(outputStream* s) {
296   AbsSeq::dump_on(s);
297   s->print_cr("\t\t _last = %7.3f, _maximum = %7.3f", _last, _maximum);
298 }
299
300 void TruncatedSeq::dump_on(outputStream* s) {
301   AbsSeq::dump_on(s);
302   s->print_cr("\t\t _length = %d, _next = %d", _length, _next);
303   for (int i = 0; i < _length; i++) {
304     if (i%5 == 0) {
305       s->cr();
306       s->print("\t");
307     }
308     s->print("\t[%d]=%7.3f", i, _sequence[i]);
309   }
310   s->cr();
311 }
```