Mercurial > hg > graal-compiler
comparison src/share/vm/utilities/numberSeq.cpp @ 360:5d254928c888
Merge
author | ysr |
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date | Wed, 27 Aug 2008 11:20:46 -0700 |
parents | 37f87013dfd8 |
children | 89f1b9ae8991 |
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341:d60e4e6d7f72 | 360:5d254928c888 |
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1 /* | |
2 * Copyright 2001-2007 Sun Microsystems, Inc. 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 Sun Microsystems, Inc., 4150 Network Circle, Santa Clara, | |
20 * CA 95054 USA or visit www.sun.com if you need additional information or | |
21 * have any questions. | |
22 * | |
23 */ | |
24 | |
25 # include "incls/_precompiled.incl" | |
26 # include "incls/_numberSeq.cpp.incl" | |
27 | |
28 AbsSeq::AbsSeq(double alpha) : | |
29 _num(0), _sum(0.0), _sum_of_squares(0.0), | |
30 _davg(0.0), _dvariance(0.0), _alpha(alpha) { | |
31 } | |
32 | |
33 void AbsSeq::add(double val) { | |
34 if (_num == 0) { | |
35 // if the sequence is empty, the davg is the same as the value | |
36 _davg = val; | |
37 // and the variance is 0 | |
38 _dvariance = 0.0; | |
39 } else { | |
40 // otherwise, calculate both | |
41 _davg = (1.0 - _alpha) * val + _alpha * _davg; | |
42 double diff = val - _davg; | |
43 _dvariance = (1.0 - _alpha) * diff * diff + _alpha * _dvariance; | |
44 } | |
45 } | |
46 | |
47 double AbsSeq::avg() const { | |
48 if (_num == 0) | |
49 return 0.0; | |
50 else | |
51 return _sum / total(); | |
52 } | |
53 | |
54 double AbsSeq::variance() const { | |
55 if (_num <= 1) | |
56 return 0.0; | |
57 | |
58 double x_bar = avg(); | |
59 double result = _sum_of_squares / total() - x_bar * x_bar; | |
60 if (result < 0.0) { | |
61 // due to loss-of-precision errors, the variance might be negative | |
62 // by a small bit | |
63 | |
64 // guarantee(-0.1 < result && result < 0.0, | |
65 // "if variance is negative, it should be very small"); | |
66 result = 0.0; | |
67 } | |
68 return result; | |
69 } | |
70 | |
71 double AbsSeq::sd() const { | |
72 double var = variance(); | |
73 guarantee( var >= 0.0, "variance should not be negative" ); | |
74 return sqrt(var); | |
75 } | |
76 | |
77 double AbsSeq::davg() const { | |
78 return _davg; | |
79 } | |
80 | |
81 double AbsSeq::dvariance() const { | |
82 if (_num <= 1) | |
83 return 0.0; | |
84 | |
85 double result = _dvariance; | |
86 if (result < 0.0) { | |
87 // due to loss-of-precision errors, the variance might be negative | |
88 // by a small bit | |
89 | |
90 guarantee(-0.1 < result && result < 0.0, | |
91 "if variance is negative, it should be very small"); | |
92 result = 0.0; | |
93 } | |
94 return result; | |
95 } | |
96 | |
97 double AbsSeq::dsd() const { | |
98 double var = dvariance(); | |
99 guarantee( var >= 0.0, "variance should not be negative" ); | |
100 return sqrt(var); | |
101 } | |
102 | |
103 NumberSeq::NumberSeq(double alpha) : | |
104 AbsSeq(alpha), _maximum(0.0), _last(0.0) { | |
105 } | |
106 | |
107 bool NumberSeq::check_nums(NumberSeq *total, int n, NumberSeq **parts) { | |
108 for (int i = 0; i < n; ++i) { | |
109 if (parts[i] != NULL && total->num() != parts[i]->num()) | |
110 return false; | |
111 } | |
112 return true; | |
113 } | |
114 | |
115 NumberSeq::NumberSeq(NumberSeq *total, int n, NumberSeq **parts) { | |
116 guarantee(check_nums(total, n, parts), "all seq lengths should match"); | |
117 double sum = total->sum(); | |
118 for (int i = 0; i < n; ++i) { | |
119 if (parts[i] != NULL) | |
120 sum -= parts[i]->sum(); | |
121 } | |
122 | |
123 _num = total->num(); | |
124 _sum = sum; | |
125 | |
126 // we do not calculate these... | |
127 _sum_of_squares = -1.0; | |
128 _maximum = -1.0; | |
129 _davg = -1.0; | |
130 _dvariance = -1.0; | |
131 } | |
132 | |
133 void NumberSeq::add(double val) { | |
134 AbsSeq::add(val); | |
135 | |
136 _last = val; | |
137 if (_num == 0) { | |
138 _maximum = val; | |
139 } else { | |
140 if (val > _maximum) | |
141 _maximum = val; | |
142 } | |
143 _sum += val; | |
144 _sum_of_squares += val * val; | |
145 ++_num; | |
146 } | |
147 | |
148 | |
149 TruncatedSeq::TruncatedSeq(int length, double alpha): | |
150 AbsSeq(alpha), _length(length), _next(0) { | |
151 _sequence = NEW_C_HEAP_ARRAY(double, _length); | |
152 for (int i = 0; i < _length; ++i) | |
153 _sequence[i] = 0.0; | |
154 } | |
155 | |
156 void TruncatedSeq::add(double val) { | |
157 AbsSeq::add(val); | |
158 | |
159 // get the oldest value in the sequence... | |
160 double old_val = _sequence[_next]; | |
161 // ...remove it from the sum and sum of squares | |
162 _sum -= old_val; | |
163 _sum_of_squares -= old_val * old_val; | |
164 | |
165 // ...and update them with the new value | |
166 _sum += val; | |
167 _sum_of_squares += val * val; | |
168 | |
169 // now replace the old value with the new one | |
170 _sequence[_next] = val; | |
171 _next = (_next + 1) % _length; | |
172 | |
173 // only increase it if the buffer is not full | |
174 if (_num < _length) | |
175 ++_num; | |
176 | |
177 guarantee( variance() > -1.0, "variance should be >= 0" ); | |
178 } | |
179 | |
180 // can't easily keep track of this incrementally... | |
181 double TruncatedSeq::maximum() const { | |
182 if (_num == 0) | |
183 return 0.0; | |
184 double ret = _sequence[0]; | |
185 for (int i = 1; i < _num; ++i) { | |
186 double val = _sequence[i]; | |
187 if (val > ret) | |
188 ret = val; | |
189 } | |
190 return ret; | |
191 } | |
192 | |
193 double TruncatedSeq::last() const { | |
194 if (_num == 0) | |
195 return 0.0; | |
196 unsigned last_index = (_next + _length - 1) % _length; | |
197 return _sequence[last_index]; | |
198 } | |
199 | |
200 double TruncatedSeq::oldest() const { | |
201 if (_num == 0) | |
202 return 0.0; | |
203 else if (_num < _length) | |
204 // index 0 always oldest value until the array is full | |
205 return _sequence[0]; | |
206 else { | |
207 // since the array is full, _next is over the oldest value | |
208 return _sequence[_next]; | |
209 } | |
210 } | |
211 | |
212 double TruncatedSeq::predict_next() const { | |
213 if (_num == 0) | |
214 return 0.0; | |
215 | |
216 double num = (double) _num; | |
217 double x_squared_sum = 0.0; | |
218 double x_sum = 0.0; | |
219 double y_sum = 0.0; | |
220 double xy_sum = 0.0; | |
221 double x_avg = 0.0; | |
222 double y_avg = 0.0; | |
223 | |
224 int first = (_next + _length - _num) % _length; | |
225 for (int i = 0; i < _num; ++i) { | |
226 double x = (double) i; | |
227 double y = _sequence[(first + i) % _length]; | |
228 | |
229 x_squared_sum += x * x; | |
230 x_sum += x; | |
231 y_sum += y; | |
232 xy_sum += x * y; | |
233 } | |
234 x_avg = x_sum / num; | |
235 y_avg = y_sum / num; | |
236 | |
237 double Sxx = x_squared_sum - x_sum * x_sum / num; | |
238 double Sxy = xy_sum - x_sum * y_sum / num; | |
239 double b1 = Sxy / Sxx; | |
240 double b0 = y_avg - b1 * x_avg; | |
241 | |
242 return b0 + b1 * num; | |
243 } |