annotate src/share/vm/utilities/numberSeq.cpp @ 17524:89152779163c

Merge with jdk8-b132
author Gilles Duboscq <duboscq@ssw.jku.at>
date Wed, 15 Oct 2014 11:59:32 +0200
parents 4ca6dc0799b6
children 52b4284cb496
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1 /*
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Gilles Duboscq <duboscq@ssw.jku.at>
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2 * Copyright (c) 2001, 2013, Oracle and/or its affiliates. All rights reserved.
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3 * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
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4 *
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5 * This code is free software; you can redistribute it and/or modify it
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6 * under the terms of the GNU General Public License version 2 only, as
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7 * published by the Free Software Foundation.
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8 *
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9 * This code is distributed in the hope that it will be useful, but WITHOUT
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10 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
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11 * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
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12 * version 2 for more details (a copy is included in the LICENSE file that
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13 * accompanied this code).
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14 *
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15 * You should have received a copy of the GNU General Public License version
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16 * 2 along with this work; if not, write to the Free Software Foundation,
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17 * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
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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.
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22 *
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23 */
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24
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25 #include "precompiled.hpp"
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26 #include "memory/allocation.inline.hpp"
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27 #include "utilities/debug.hpp"
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28 #include "utilities/globalDefinitions.hpp"
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29 #include "utilities/numberSeq.hpp"
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30
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31 AbsSeq::AbsSeq(double alpha) :
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32 _num(0), _sum(0.0), _sum_of_squares(0.0),
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33 _davg(0.0), _dvariance(0.0), _alpha(alpha) {
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34 }
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35
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36 void AbsSeq::add(double val) {
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37 if (_num == 0) {
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38 // if the sequence is empty, the davg is the same as the value
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39 _davg = val;
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40 // and the variance is 0
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41 _dvariance = 0.0;
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42 } else {
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43 // otherwise, calculate both
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44 _davg = (1.0 - _alpha) * val + _alpha * _davg;
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45 double diff = val - _davg;
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46 _dvariance = (1.0 - _alpha) * diff * diff + _alpha * _dvariance;
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47 }
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48 }
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49
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50 double AbsSeq::avg() const {
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51 if (_num == 0)
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52 return 0.0;
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53 else
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54 return _sum / total();
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55 }
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56
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57 double AbsSeq::variance() const {
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58 if (_num <= 1)
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59 return 0.0;
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60
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61 double x_bar = avg();
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62 double result = _sum_of_squares / total() - x_bar * x_bar;
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63 if (result < 0.0) {
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64 // due to loss-of-precision errors, the variance might be negative
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65 // by a small bit
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66
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67 // guarantee(-0.1 < result && result < 0.0,
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68 // "if variance is negative, it should be very small");
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69 result = 0.0;
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70 }
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71 return result;
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72 }
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73
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74 double AbsSeq::sd() const {
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75 double var = variance();
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76 guarantee( var >= 0.0, "variance should not be negative" );
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77 return sqrt(var);
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78 }
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79
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80 double AbsSeq::davg() const {
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81 return _davg;
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82 }
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83
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84 double AbsSeq::dvariance() const {
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85 if (_num <= 1)
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86 return 0.0;
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87
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88 double result = _dvariance;
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89 if (result < 0.0) {
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90 // due to loss-of-precision errors, the variance might be negative
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91 // by a small bit
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92
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93 guarantee(-0.1 < result && result < 0.0,
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94 "if variance is negative, it should be very small");
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95 result = 0.0;
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96 }
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97 return result;
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98 }
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99
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100 double AbsSeq::dsd() const {
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101 double var = dvariance();
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102 guarantee( var >= 0.0, "variance should not be negative" );
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103 return sqrt(var);
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104 }
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105
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106 NumberSeq::NumberSeq(double alpha) :
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107 AbsSeq(alpha), _maximum(0.0), _last(0.0) {
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108 }
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109
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110 bool NumberSeq::check_nums(NumberSeq *total, int n, NumberSeq **parts) {
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111 for (int i = 0; i < n; ++i) {
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112 if (parts[i] != NULL && total->num() != parts[i]->num())
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113 return false;
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114 }
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115 return true;
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116 }
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117
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118 void NumberSeq::add(double val) {
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119 AbsSeq::add(val);
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120
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121 _last = val;
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122 if (_num == 0) {
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123 _maximum = val;
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124 } else {
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125 if (val > _maximum)
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126 _maximum = val;
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127 }
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128 _sum += val;
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129 _sum_of_squares += val * val;
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130 ++_num;
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131 }
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132
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133
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134 TruncatedSeq::TruncatedSeq(int length, double alpha):
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135 AbsSeq(alpha), _length(length), _next(0) {
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136 _sequence = NEW_C_HEAP_ARRAY(double, _length, mtInternal);
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137 for (int i = 0; i < _length; ++i)
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138 _sequence[i] = 0.0;
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139 }
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140
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141 TruncatedSeq::~TruncatedSeq() {
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142 FREE_C_HEAP_ARRAY(double, _sequence, mtGC);
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143 }
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144
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145 void TruncatedSeq::add(double val) {
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146 AbsSeq::add(val);
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147
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148 // get the oldest value in the sequence...
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149 double old_val = _sequence[_next];
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150 // ...remove it from the sum and sum of squares
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151 _sum -= old_val;
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152 _sum_of_squares -= old_val * old_val;
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153
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154 // ...and update them with the new value
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155 _sum += val;
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156 _sum_of_squares += val * val;
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157
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158 // now replace the old value with the new one
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159 _sequence[_next] = val;
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160 _next = (_next + 1) % _length;
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161
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162 // only increase it if the buffer is not full
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163 if (_num < _length)
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164 ++_num;
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165
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166 guarantee( variance() > -1.0, "variance should be >= 0" );
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167 }
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168
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169 // can't easily keep track of this incrementally...
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170 double TruncatedSeq::maximum() const {
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171 if (_num == 0)
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172 return 0.0;
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173 double ret = _sequence[0];
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174 for (int i = 1; i < _num; ++i) {
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175 double val = _sequence[i];
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176 if (val > ret)
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177 ret = val;
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178 }
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179 return ret;
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180 }
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181
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182 double TruncatedSeq::last() const {
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183 if (_num == 0)
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184 return 0.0;
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185 unsigned last_index = (_next + _length - 1) % _length;
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186 return _sequence[last_index];
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187 }
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188
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189 double TruncatedSeq::oldest() const {
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190 if (_num == 0)
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191 return 0.0;
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192 else if (_num < _length)
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193 // index 0 always oldest value until the array is full
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194 return _sequence[0];
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195 else {
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196 // since the array is full, _next is over the oldest value
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197 return _sequence[_next];
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198 }
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199 }
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200
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201 double TruncatedSeq::predict_next() const {
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202 if (_num == 0)
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203 return 0.0;
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204
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205 double num = (double) _num;
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206 double x_squared_sum = 0.0;
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207 double x_sum = 0.0;
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208 double y_sum = 0.0;
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209 double xy_sum = 0.0;
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210 double x_avg = 0.0;
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211 double y_avg = 0.0;
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212
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213 int first = (_next + _length - _num) % _length;
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214 for (int i = 0; i < _num; ++i) {
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215 double x = (double) i;
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216 double y = _sequence[(first + i) % _length];
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217
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218 x_squared_sum += x * x;
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219 x_sum += x;
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220 y_sum += y;
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221 xy_sum += x * y;
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222 }
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223 x_avg = x_sum / num;
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224 y_avg = y_sum / num;
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225
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226 double Sxx = x_squared_sum - x_sum * x_sum / num;
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227 double Sxy = xy_sum - x_sum * y_sum / num;
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228 double b1 = Sxy / Sxx;
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229 double b0 = y_avg - b1 * x_avg;
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230
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231 return b0 + b1 * num;
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232 }
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233
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234
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235 // Printing/Debugging Support
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236
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237 void AbsSeq::dump() { dump_on(gclog_or_tty); }
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238
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239 void AbsSeq::dump_on(outputStream* s) {
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240 s->print_cr("\t _num = %d, _sum = %7.3f, _sum_of_squares = %7.3f",
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241 _num, _sum, _sum_of_squares);
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242 s->print_cr("\t _davg = %7.3f, _dvariance = %7.3f, _alpha = %7.3f",
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243 _davg, _dvariance, _alpha);
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244 }
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245
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246 void NumberSeq::dump_on(outputStream* s) {
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247 AbsSeq::dump_on(s);
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248 s->print_cr("\t\t _last = %7.3f, _maximum = %7.3f", _last, _maximum);
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249 }
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250
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251 void TruncatedSeq::dump_on(outputStream* s) {
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252 AbsSeq::dump_on(s);
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253 s->print_cr("\t\t _length = %d, _next = %d", _length, _next);
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254 for (int i = 0; i < _length; i++) {
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255 if (i%5 == 0) {
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256 s->cr();
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257 s->print("\t");
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258 }
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259 s->print("\t[%d]=%7.3f", i, _sequence[i]);
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260 }
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261 s->print_cr("");
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262 }