BetaDistributionWithTrend::BetaDistributionWithTrend(const NRLib::Trend * mean,
const NRLib::Trend * var,
const double & lower_limit,
const double & upper_limit,
int shared)
: DistributionWithTrend(shared,true)
{
mean_ = mean->Clone();
var_ = var->Clone();
use_trend_cube_.resize(2);
for(int i=0; i<2; i++)
use_trend_cube_[i] = false;
FindUseTrendCube(use_trend_cube_, mean_->GetTrendDimension(), mean_->GetReference());
FindUseTrendCube(use_trend_cube_, var_ ->GetTrendDimension(), var_ ->GetReference());
if(mean_->GetTrendDimension() == 0) {
ni_ = 1;
n_samples_mean_ = 1;
}
else {
ni_ = 2;
n_samples_mean_ = 100;
}
if(var_->GetTrendDimension() == 0) {
nj_ = 1;
n_samples_var_ = 1;
}
else {
nj_ = 2;
n_samples_var_ = 100;
}
double mean_min = mean_->GetMinValue();
double mean_max = mean_->GetMaxValue();
double var_min = var_->GetMinValue();
double var_max = var_->GetMaxValue();
double dx;
if(ni_ == 1)
dx = 0;
else
dx = (mean_max - mean_min)/(n_samples_mean_ - 1);
double dy;
if(nj_ == 1)
dy = 0;
else
dy = (var_max - var_min) /(n_samples_var_ - 1);
mean_sampling_.resize(n_samples_mean_);
for(int i=0; i<n_samples_mean_; i++)
mean_sampling_[i] = mean_min + i*dx;
var_sampling_.resize(n_samples_var_);
for(int j=0; j<n_samples_var_; j++)
var_sampling_[j] = var_min + j*dy;
double a;
double b;
beta_distribution_ = new NRLib::Grid2D<NRLib::Distribution<double> *>(n_samples_mean_, n_samples_var_, NULL);
for(int i=0; i<n_samples_mean_; i++) {
for(int j=0; j<n_samples_var_; j++) {
CalculateAlpha(mean_sampling_[i], var_sampling_[j], lower_limit, upper_limit, a);
CalculateBeta(mean_sampling_[i], var_sampling_[j], lower_limit, upper_limit, b);
NRLib::Distribution<double> * dist = NULL;
if(a > 0 && b > 0)
dist = new NRLib::Beta(lower_limit, upper_limit, a, b);
(*beta_distribution_)(i,j) = dist;
}
}
}
void CalcAlphaBeta(void) {
CalculateAlpha();
CalculateBeta();
}
