本文整理汇总了C++中ArrayXd::cube方法的典型用法代码示例。如果您正苦于以下问题：C++ ArrayXd::cube方法的具体用法？C++ ArrayXd::cube怎么用？C++ ArrayXd::cube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ArrayXd的用法示例。
在下文中一共展示了ArrayXd::cube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: variance
const ArrayXd inverseGaussianDist::variance(const ArrayXd& mu) const {return mu.cube();}示例2: cubicSplineInterpolation
//.........这里部分代码省略.........
secondDerivatives[0] = 0.0;
partialSolution[0] = 0.0;
// Do tridiagonal decomposition for computing second derivatives of observed ordinate
ArrayXd sigma = differenceAbscissa.segment(0,size-2)/differenceAbscissa2.segment(0,size-2);
double beta;
// Forward computation of partial solutions in tridiagonal system
for (int i = 1; i < size-1; ++i)
{
beta = sigma(i-1) * secondDerivatives[i-1] + 2.0;
secondDerivatives[i] = (sigma(i-1) - 1.0)/beta;
partialSolution[i] = differenceOrdinate(i)/differenceAbscissa(i) - differenceOrdinate(i-1)/differenceAbscissa(i-1);
partialSolution[i] = (6.0*partialSolution[i]/differenceAbscissa2(i-1)-sigma(i-1)*partialSolution[i-1])/beta;
}
// Upper bound condition for natural spline
secondDerivatives[size-1] = 0.0;
// Backward substitution
for (int k = (size-2); k >= 0; --k)
{
secondDerivatives[k] = secondDerivatives[k]*secondDerivatives[k+1]+partialSolution[k];
}
// Initialize arrays of differences in both ordinate and abscissa
ArrayXd interpolatedOrdinate = ArrayXd::Zero(interpolatedSize);
ArrayXd remainingInterpolatedAbscissa = interpolatedAbscissa; // The remaining part of the array of interpolated abscissa
int cumulatedBinSize = 0; // The cumulated number of interpolated points from the beginning
int i = 0; // Bin counter
while ((i < size-1) && (cumulatedBinSize < interpolatedSize))
{
// Find which values of interpolatedAbscissa are containined within the selected bin of observedAbscissa.
// Since elements in interpolatedAbscissa are monotonically increasing, we cut the input array each time
// we identify the elements of the current bin. This allows to speed up the process.
double lowerAbscissa = observedAbscissa(i);
double upperAbscissa = observedAbscissa(i+1);
// Find total number of interpolated points falling in the current bin
int binSize = Functions::countArrayIndicesWithinBoundaries(remainingInterpolatedAbscissa, lowerAbscissa, upperAbscissa);
// Do interpolation only if interpolated points are found within the bin
if (binSize > 0)
{
double lowerOrdinate = observedOrdinate(i);
double upperOrdinate = observedOrdinate(i+1);
double denominator = differenceAbscissa(i);
double upperSecondDerivative = secondDerivatives[i+1];
double lowerSecondDerivative = secondDerivatives[i];
ArrayXd interpolatedAbscissaInCurrentBin = remainingInterpolatedAbscissa.segment(0, binSize);
ArrayXd interpolatedOrdinateInCurrentBin = ArrayXd::Zero(binSize);
// Compute coefficients for cubic spline interpolation function
ArrayXd a = (upperAbscissa - interpolatedAbscissaInCurrentBin) / denominator;
ArrayXd b = 1.0 - a;
ArrayXd c = (1.0/6.0) * (a.cube() - a)*denominator*denominator;
ArrayXd d = (1.0/6.0) * (b.cube() - b)*denominator*denominator;
interpolatedOrdinateInCurrentBin = a*lowerOrdinate + b*upperOrdinate + c*lowerSecondDerivative + d*upperSecondDerivative;
// Merge bin ordinate into total array of ordinate
interpolatedOrdinate.segment(cumulatedBinSize, binSize) = interpolatedOrdinateInCurrentBin;
// Reduce size of array remainingInterpolatedAbscissa by binSize elements and initialize the array
// with remaining part of interpolatedAbscissa
int currentRemainingSize = interpolatedSize - cumulatedBinSize;
remainingInterpolatedAbscissa.resize(currentRemainingSize - binSize);
cumulatedBinSize += binSize;
remainingInterpolatedAbscissa = interpolatedAbscissa.segment(cumulatedBinSize, interpolatedSize-cumulatedBinSize);
}
// Move to next bin
++i;
}
return interpolatedOrdinate;
}