本文整理汇总了C++中MetaData::getColumnValues方法的典型用法代码示例。如果您正苦于以下问题：C++ MetaData::getColumnValues方法的具体用法？C++ MetaData::getColumnValues怎么用？C++ MetaData::getColumnValues使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类MetaData的用法示例。
在下文中一共展示了MetaData::getColumnValues方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: sin
void ProgValidationNonTilt::obtainSumU_2(const MetaData & mdGallery, const MetaData & tempMd,std::vector<double> & sum_u,std::vector<double> & H0)
{
const size_t tempMdSz= tempMd.size();
const size_t numGallery= mdGallery.size();
double xRan,yRan,zRan;
size_t indx;
double sumWRan;
double * xRanArray = new double[tempMdSz];
double * yRanArray = new double[tempMdSz];
double * zRanArray = new double[tempMdSz];
std::vector<double> weightV;
double a;
double rot,tilt,w;
bool mirror;
for (size_t n=0; n<sum_u.size(); n++)
{
sumWRan = 0;
for (size_t nS=0; nS<tempMd.size(); nS++)
{
indx = (size_t) (double( std::rand())*numGallery)/RAND_MAX;
while ( (indx ==0) || (indx > numGallery) )
indx = (size_t) (double( std::rand())*numGallery )/RAND_MAX;
mdGallery.getValue(MDL_ANGLE_ROT,rot,indx);
mdGallery.getValue(MDL_ANGLE_TILT,tilt,indx);
mdGallery.getValue(MDL_FLIP,mirror,indx);
if (mirror == 1)
tilt = tilt + 180;
xRan = sin(tilt*PI/180.)*cos(rot*PI/180.);
yRan = sin(tilt*PI/180.)*sin(rot*PI/180.);
zRan = std::abs(cos(tilt*PI/180.));
xRanArray[nS] = xRan;
yRanArray[nS] = yRan;
zRanArray[nS] = zRan;
//tempMd.getColumnValues(MDL_WEIGHT, weightV);
tempMd.getColumnValues(MDL_MAXCC, weightV);
std::random_shuffle(weightV.begin(), weightV.end());
}
sumWRan = 0;
double WRan=0;
double tempWRan, tempW1, tempW2, temp;
for (size_t nS1=0; nS1<tempMd.size(); nS1++)
{
tempWRan = 1e3;
for (size_t nS2=0; nS2<tempMd.size(); nS2++)
{
temp = xRanArray[nS1]*xRanArray[nS2]+yRanArray[nS1]*yRanArray[nS2]+zRanArray[nS1]*zRanArray[nS2];
if (temp < 1)
a = std::abs(std::acos(temp));
else
a = 0;
if ( (a<tempWRan) && (a > 0.00001) && (temp<1) )
{
tempWRan = a;
tempW2 = weightV[nS2];
tempW1 = weightV[nS1];
WRan = a*std::exp(std::abs(tempW1-tempW2))*std::exp(-(tempW1+tempW2));
if (WRan == 0)
WRan = a;
}
}
sumWRan += WRan;
}
if (sumWRan == 0)
sumWRan = 0.075*tempMd.size();
sum_u.at(n)=sumWRan;
}
size_t idx = 0;
while (idx < sum_u.size())
{
std::random_shuffle(sum_u.begin(), sum_u.end());
if(sum_u.at(0) != sum_u.at(1))
{
H0[idx] = sum_u.at(0)/(sum_u.at(0)+sum_u.at(1));
idx += 1;
}
}
delete xRanArray;
delete yRanArray;
delete zRanArray;
}示例2: obtainSumU
void ProgValidationNonTilt::obtainSumU(const MetaData & tempMd,std::vector<double> & sum_u,std::vector<double> & H0)
{
const size_t tempMdSz= tempMd.size();
double xRan,yRan,zRan;
double x,y;
double sumWRan;
double * xRanArray = new double[tempMdSz];
double * yRanArray = new double[tempMdSz];
double * zRanArray = new double[tempMdSz];
std::vector<double> weightV;
double a;
for (size_t n=0; n<sum_u.size(); n++)
{
sumWRan = 0;
for (size_t nS=0; nS<tempMd.size(); nS++)
{
/*
x = sin(tilt*PI/180)*cos(rot*PI/180);
y = sin(tilt*PI/180)*sin(rot*PI/180);
z = std::abs(cos(tilt*PI/180));
*/
//http://mathworld.wolfram.com/SpherePointPicking.html
x = 2*(double(std::rand())-RAND_MAX/2)/RAND_MAX;
y = 2*(double(std::rand())-RAND_MAX/2)/RAND_MAX;
while (x*x+y*y >= 1 )
{
x = 2*(std::rand()-RAND_MAX/2)/RAND_MAX;
y = 2*(std::rand()-RAND_MAX/2)/RAND_MAX;
}
xRan = 2*x*std::sqrt(1-x*x-y*y);
yRan = 2*y*std::sqrt(1-x*x-y*y);
zRan = std::abs(1-2*(x*x+y*y));
/* tilt = (double(std::rand())/RAND_MAX)*(PI);
rot = (std::rand()-RAND_MAX/2)*(2*PI/RAND_MAX);
xRan = sin(tilt)*cos(rot);
yRan = sin(tilt)*sin(rot);
zRan = std::abs(cos(tilt));
*/
//std::cout << tilt << " " << rot << std::endl;
//std::cout << xRan << " " << yRan << " " << zRan << " " << std::endl;
//zRan=(std::rand()-RAND_MAX/2);
//norm = std::sqrt(xRan*xRan+yRan*yRan+zRan*zRan);
//xRan = (xRan/norm);
//yRan = (yRan/norm);
//zRan = std::abs(zRan/norm);
xRanArray[nS] = xRan;
yRanArray[nS] = yRan;
zRanArray[nS] = zRan;
//tempMd.getColumnValues(MDL_WEIGHT, weightV);
tempMd.getColumnValues(MDL_MAXCC, weightV);
std::random_shuffle(weightV.begin(), weightV.end());
}
sumWRan = 0;
double WRan=0;
double tempWRan, tempW1, tempW2, temp;
for (size_t nS1=0; nS1<tempMd.size(); nS1++)
{
tempWRan = 1e3;
for (size_t nS2=0; nS2<tempMd.size(); nS2++)
{
temp = xRanArray[nS1]*xRanArray[nS2]+yRanArray[nS1]*yRanArray[nS2]+zRanArray[nS1]*zRanArray[nS2];
if (temp < 1)
a = std::abs(std::acos(temp));
else
a = 0;
if ( (a<tempWRan) && (a > 0.00001) && (temp<1) )
{
tempWRan = a;
tempW2 = weightV[nS2];
tempW1 = weightV[nS1];
WRan = a*std::exp(std::abs(tempW1-tempW2))*std::exp(-(tempW1+tempW2));
if (WRan == 0)
WRan = a;
}
}
sumWRan += WRan;
}
if (sumWRan == 0)
sumWRan = 0.075*tempMd.size();
sum_u.at(n)=sumWRan;
}
size_t idx = 0;
while (idx < sum_u.size())
{
std::random_shuffle(sum_u.begin(), sum_u.end());
//.........这里部分代码省略.........