Type2LargestValueRV.cppGo to the documentation of this file.00001 /* ****************************************************************** ** 00002 ** OpenSees - Open System for Earthquake Engineering Simulation ** 00003 ** Pacific Earthquake Engineering Research Center ** 00004 ** ** 00005 ** ** 00006 ** (C) Copyright 2001, The Regents of the University of California ** 00007 ** All Rights Reserved. ** 00008 ** ** 00009 ** Commercial use of this program without express permission of the ** 00010 ** University of California, Berkeley, is strictly prohibited. See ** 00011 ** file 'COPYRIGHT' in main directory for information on usage and ** 00012 ** redistribution, and for a DISCLAIMER OF ALL WARRANTIES. ** 00013 ** ** 00014 ** Developed by: ** 00015 ** Frank McKenna (fmckenna@ce.berkeley.edu) ** 00016 ** Gregory L. Fenves (fenves@ce.berkeley.edu) ** 00017 ** Filip C. Filippou (filippou@ce.berkeley.edu) ** 00018 ** ** 00019 ** Reliability module developed by: ** 00020 ** Terje Haukaas (haukaas@ce.berkeley.edu) ** 00021 ** Armen Der Kiureghian (adk@ce.berkeley.edu) ** 00022 ** ** 00023 ** ****************************************************************** */ 00024 00025 // $Revision: 1.6 $ 00026 // $Date: 2003/03/04 00:44:36 $ 00027 // $Source: /usr/local/cvs/OpenSees/SRC/reliability/domain/distributions/Type2LargestValueRV.cpp,v $ 00028 00029 00030 // 00031 // Written by Terje Haukaas (haukaas@ce.berkeley.edu) 00032 // 00033 00034 #include <Type2LargestValueRV.h> 00035 #include <GammaRV.h> 00036 #include <math.h> 00037 #include <string.h> 00038 #include <classTags.h> 00039 #include <OPS_Globals.h> 00040 00041 Type2LargestValueRV::Type2LargestValueRV(int passedTag, 00042 double passedMean, 00043 double passedStdv, 00044 double passedStartValue) 00045 :RandomVariable(passedTag, RANDOM_VARIABLE_type2largestvalue) 00046 { 00047 tag = passedTag ; 00048 setParameters(passedMean,passedStdv); 00049 startValue = passedStartValue; 00050 } 00051 Type2LargestValueRV::Type2LargestValueRV(int passedTag, 00052 double passedParameter1, 00053 double passedParameter2, 00054 double passedParameter3, 00055 double passedParameter4, 00056 double passedStartValue) 00057 :RandomVariable(passedTag, RANDOM_VARIABLE_type2largestvalue) 00058 { 00059 tag = passedTag ; 00060 u = passedParameter1; 00061 k = passedParameter2; 00062 startValue = passedStartValue; 00063 } 00064 Type2LargestValueRV::Type2LargestValueRV(int passedTag, 00065 double passedMean, 00066 double passedStdv) 00067 :RandomVariable(passedTag, RANDOM_VARIABLE_type2largestvalue) 00068 { 00069 tag = passedTag ; 00070 setParameters(passedMean,passedStdv); 00071 startValue = getMean(); 00072 } 00073 Type2LargestValueRV::Type2LargestValueRV(int passedTag, 00074 double passedParameter1, 00075 double passedParameter2, 00076 double passedParameter3, 00077 double passedParameter4) 00078 :RandomVariable(passedTag, RANDOM_VARIABLE_type2largestvalue) 00079 { 00080 tag = passedTag ; 00081 u = passedParameter1; 00082 k = passedParameter2; 00083 startValue = getMean(); 00084 } 00085 00086 00087 Type2LargestValueRV::~Type2LargestValueRV() 00088 { 00089 } 00090 00091 00092 void 00093 Type2LargestValueRV::Print(OPS_Stream &s, int flag) 00094 { 00095 } 00096 00097 00098 double 00099 Type2LargestValueRV::getPDFvalue(double rvValue) 00100 { 00101 double result; 00102 if ( 0.0 < rvValue ) { 00103 result = k/u * pow(u/rvValue,k+1) * exp(-pow(u/rvValue,k)); 00104 } 00105 else { 00106 result = 0.0; 00107 } 00108 return result; 00109 } 00110 00111 00112 double 00113 Type2LargestValueRV::getCDFvalue(double rvValue) 00114 { 00115 double result; 00116 if ( 0.0 < rvValue ) { 00117 result = exp(-pow(u/rvValue,k)); 00118 } 00119 else { 00120 result = 0.0; 00121 } 00122 return result; 00123 } 00124 00125 00126 double 00127 Type2LargestValueRV::getInverseCDFvalue(double probValue) 00128 { 00129 return u * pow((-log(probValue)),(-1.0/k)); 00130 } 00131 00132 00133 const char * 00134 Type2LargestValueRV::getType() 00135 { 00136 return "TYPE2LARGESTVALUE"; 00137 } 00138 00139 00140 double 00141 Type2LargestValueRV::getMean() 00142 { 00143 double result; 00144 GammaRV *aGammaRV = new GammaRV(1, 0.0, 1.0, 0.0); 00145 result = u * aGammaRV->gammaFunction(1.0-1.0/k); 00146 delete aGammaRV; 00147 return result; 00148 } 00149 00150 00151 00152 double 00153 Type2LargestValueRV::getStdv() 00154 { 00155 GammaRV *aGammaRV = new GammaRV(1, 0.0, 1.0, 0.0); 00156 double a = aGammaRV->gammaFunction(1.0-2.0/k); 00157 double b = aGammaRV->gammaFunction(1.0-1.0/k); 00158 delete aGammaRV; 00159 double result = u*sqrt(a-b*b); 00160 return result; 00161 } 00162 00163 00164 double 00165 Type2LargestValueRV::getStartValue() 00166 { 00167 return startValue; 00168 } 00169 00170 double Type2LargestValueRV::getParameter1() {return u;} 00171 double Type2LargestValueRV::getParameter2() {return k;} 00172 double Type2LargestValueRV::getParameter3() {opserr<<"No such parameter in r.v. #"<<tag<<endln; return 0.0;} 00173 double Type2LargestValueRV::getParameter4() {opserr<<"No such parameter in r.v. #"<<tag<<endln; return 0.0;} 00174 00175 00176 00177 void 00178 Type2LargestValueRV::setParameters(double mean, double stdv) 00179 { 00180 double cov = stdv/mean; 00181 double xk = 1.5; 00182 function131(xk, cov,mean); 00183 } 00184 00185 00186 void 00187 Type2LargestValueRV::function131(double xk, double cov, double mean) 00188 { 00189 GammaRV *aGammaRV = new GammaRV(1, 0.0, 1.0, 0.0); 00190 xk = xk + 1.0; 00191 double x1 = 1.0 - 1.0/xk; 00192 double x2 = 1.0 - 2.0/xk; 00193 double gm1 = aGammaRV->gammaFunction(x1); 00194 double gm2 = aGammaRV->gammaFunction(x2); 00195 delete aGammaRV; 00196 double vy = sqrt(gm2/gm1/gm1 - 1.0); 00197 if (cov-vy < 0.0) 00198 function131(xk,cov,mean); 00199 else if (cov-vy == 0.0) 00200 function134(xk,cov,mean); 00201 else 00202 function132(xk,cov,mean); 00203 } 00204 void 00205 Type2LargestValueRV::function132(double xk, double cov, double mean) 00206 { 00207 xk = xk - 0.1; 00208 double x1 = 1.0 - 1.0/xk; 00209 double x2 = 1.0 - 2.0/xk; 00210 GammaRV *aGammaRV = new GammaRV(1, 0.0, 1.0, 0.0); 00211 double gm1 = aGammaRV->gammaFunction(x1); 00212 double gm2 = aGammaRV->gammaFunction(x2); 00213 delete aGammaRV; 00214 double vy = sqrt(gm2/gm1/gm1 - 1.0); 00215 if (cov-vy < 0.0) 00216 function133(xk,cov,mean); 00217 else if (cov-vy == 0.0) 00218 function134(xk,cov,mean); 00219 else 00220 function132(xk,cov,mean); 00221 } 00222 void 00223 Type2LargestValueRV::function133(double xk, double cov, double mean) 00224 { 00225 xk = xk + 0.01; 00226 double x1 = 1.0 - 1.0/xk; 00227 double x2 = 1.0 - 2.0/xk; 00228 GammaRV *aGammaRV = new GammaRV(1, 0.0, 1.0, 0.0); 00229 double gm1 = aGammaRV->gammaFunction(x1); 00230 double gm2 = aGammaRV->gammaFunction(x2); 00231 delete aGammaRV; 00232 double vy = sqrt(gm2/gm1/gm1 - 1.0); 00233 if (cov-vy < 0.0) 00234 function133(xk,cov,mean); 00235 else if (cov-vy == 0.0) 00236 function134(xk,cov,mean); 00237 else 00238 function134(xk,cov,mean); 00239 00240 00241 } 00242 void 00243 Type2LargestValueRV::function134(double xk, double gm1, double mean) 00244 { 00245 u = mean/gm1; 00246 k = xk; 00247 }
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