numberSeq.cpp revision 1472:c18cbe5936b8
1/* 2 * Copyright (c) 2001, 2007, 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 "incls/_precompiled.incl" 26# include "incls/_numberSeq.cpp.incl" 27 28AbsSeq::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 33void 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 47double AbsSeq::avg() const { 48 if (_num == 0) 49 return 0.0; 50 else 51 return _sum / total(); 52} 53 54double 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 71double AbsSeq::sd() const { 72 double var = variance(); 73 guarantee( var >= 0.0, "variance should not be negative" ); 74 return sqrt(var); 75} 76 77double AbsSeq::davg() const { 78 return _davg; 79} 80 81double 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 97double AbsSeq::dsd() const { 98 double var = dvariance(); 99 guarantee( var >= 0.0, "variance should not be negative" ); 100 return sqrt(var); 101} 102 103NumberSeq::NumberSeq(double alpha) : 104 AbsSeq(alpha), _maximum(0.0), _last(0.0) { 105} 106 107bool 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 115NumberSeq::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 133void 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 149TruncatedSeq::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 156void 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... 181double 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 193double 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 200double 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 212double 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} 244 245 246// Printing/Debugging Support 247 248void AbsSeq::dump() { dump_on(gclog_or_tty); } 249 250void AbsSeq::dump_on(outputStream* s) { 251 s->print_cr("\t _num = %d, _sum = %7.3f, _sum_of_squares = %7.3f", 252 _num, _sum, _sum_of_squares); 253 s->print_cr("\t _davg = %7.3f, _dvariance = %7.3f, _alpha = %7.3f", 254 _davg, _dvariance, _alpha); 255} 256 257void NumberSeq::dump_on(outputStream* s) { 258 AbsSeq::dump_on(s); 259 s->print_cr("\t\t _last = %7.3f, _maximum = %7.3f"); 260} 261 262void TruncatedSeq::dump_on(outputStream* s) { 263 AbsSeq::dump_on(s); 264 s->print_cr("\t\t _length = %d, _next = %d", _length, _next); 265 for (int i = 0; i < _length; i++) { 266 if (i%5 == 0) { 267 s->cr(); 268 s->print("\t"); 269 } 270 s->print("\t[%d]=%7.3f", i, _sequence[i]); 271 } 272 s->print_cr(""); 273} 274