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1 /* |
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2 * Copyright (c) 2001, 2014, 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->cr(); |
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262 } |