Mercurial > hg > graal-compiler
annotate src/share/vm/utilities/numberSeq.cpp @ 1972:f95d63e2154a
6989984: Use standard include model for Hospot
Summary: Replaced MakeDeps and the includeDB files with more standardized solutions.
Reviewed-by: coleenp, kvn, kamg
| author | stefank |
|---|---|
| date | Tue, 23 Nov 2010 13:22:55 -0800 |
| parents | c18cbe5936b8 |
| children | 2c0751569716 |
| rev | line source |
|---|---|
| 342 | 1 /* |
| 1972 | 2 * Copyright (c) 2001, 2010, Oracle and/or its affiliates. All rights reserved. |
| 342 | 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 * | |
|
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19 * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA |
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20 * or visit www.oracle.com if you need additional information or have any |
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21 * questions. |
| 342 | 22 * |
| 23 */ | |
| 24 | |
| 1972 | 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" | |
| 342 | 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 void TruncatedSeq::add(double val) { | |
| 160 AbsSeq::add(val); | |
| 161 | |
| 162 // get the oldest value in the sequence... | |
| 163 double old_val = _sequence[_next]; | |
| 164 // ...remove it from the sum and sum of squares | |
| 165 _sum -= old_val; | |
| 166 _sum_of_squares -= old_val * old_val; | |
| 167 | |
| 168 // ...and update them with the new value | |
| 169 _sum += val; | |
| 170 _sum_of_squares += val * val; | |
| 171 | |
| 172 // now replace the old value with the new one | |
| 173 _sequence[_next] = val; | |
| 174 _next = (_next + 1) % _length; | |
| 175 | |
| 176 // only increase it if the buffer is not full | |
| 177 if (_num < _length) | |
| 178 ++_num; | |
| 179 | |
| 180 guarantee( variance() > -1.0, "variance should be >= 0" ); | |
| 181 } | |
| 182 | |
| 183 // can't easily keep track of this incrementally... | |
| 184 double TruncatedSeq::maximum() const { | |
| 185 if (_num == 0) | |
| 186 return 0.0; | |
| 187 double ret = _sequence[0]; | |
| 188 for (int i = 1; i < _num; ++i) { | |
| 189 double val = _sequence[i]; | |
| 190 if (val > ret) | |
| 191 ret = val; | |
| 192 } | |
| 193 return ret; | |
| 194 } | |
| 195 | |
| 196 double TruncatedSeq::last() const { | |
| 197 if (_num == 0) | |
| 198 return 0.0; | |
| 199 unsigned last_index = (_next + _length - 1) % _length; | |
| 200 return _sequence[last_index]; | |
| 201 } | |
| 202 | |
| 203 double TruncatedSeq::oldest() const { | |
| 204 if (_num == 0) | |
| 205 return 0.0; | |
| 206 else if (_num < _length) | |
| 207 // index 0 always oldest value until the array is full | |
| 208 return _sequence[0]; | |
| 209 else { | |
| 210 // since the array is full, _next is over the oldest value | |
| 211 return _sequence[_next]; | |
| 212 } | |
| 213 } | |
| 214 | |
| 215 double TruncatedSeq::predict_next() const { | |
| 216 if (_num == 0) | |
| 217 return 0.0; | |
| 218 | |
| 219 double num = (double) _num; | |
| 220 double x_squared_sum = 0.0; | |
| 221 double x_sum = 0.0; | |
| 222 double y_sum = 0.0; | |
| 223 double xy_sum = 0.0; | |
| 224 double x_avg = 0.0; | |
| 225 double y_avg = 0.0; | |
| 226 | |
| 227 int first = (_next + _length - _num) % _length; | |
| 228 for (int i = 0; i < _num; ++i) { | |
| 229 double x = (double) i; | |
| 230 double y = _sequence[(first + i) % _length]; | |
| 231 | |
| 232 x_squared_sum += x * x; | |
| 233 x_sum += x; | |
| 234 y_sum += y; | |
| 235 xy_sum += x * y; | |
| 236 } | |
| 237 x_avg = x_sum / num; | |
| 238 y_avg = y_sum / num; | |
| 239 | |
| 240 double Sxx = x_squared_sum - x_sum * x_sum / num; | |
| 241 double Sxy = xy_sum - x_sum * y_sum / num; | |
| 242 double b1 = Sxy / Sxx; | |
| 243 double b0 = y_avg - b1 * x_avg; | |
| 244 | |
| 245 return b0 + b1 * num; | |
| 246 } | |
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248 |
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249 // Printing/Debugging Support |
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250 |
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251 void AbsSeq::dump() { dump_on(gclog_or_tty); } |
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252 |
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253 void AbsSeq::dump_on(outputStream* s) { |
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254 s->print_cr("\t _num = %d, _sum = %7.3f, _sum_of_squares = %7.3f", |
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255 _num, _sum, _sum_of_squares); |
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256 s->print_cr("\t _davg = %7.3f, _dvariance = %7.3f, _alpha = %7.3f", |
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257 _davg, _dvariance, _alpha); |
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258 } |
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259 |
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260 void NumberSeq::dump_on(outputStream* s) { |
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261 AbsSeq::dump_on(s); |
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262 s->print_cr("\t\t _last = %7.3f, _maximum = %7.3f"); |
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263 } |
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264 |
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265 void TruncatedSeq::dump_on(outputStream* s) { |
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266 AbsSeq::dump_on(s); |
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267 s->print_cr("\t\t _length = %d, _next = %d", _length, _next); |
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268 for (int i = 0; i < _length; i++) { |
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269 if (i%5 == 0) { |
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270 s->cr(); |
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271 s->print("\t"); |
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272 } |
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273 s->print("\t[%d]=%7.3f", i, _sequence[i]); |
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274 } |
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275 s->print_cr(""); |
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276 } |