Revision a53065a09c3fce65a63e137deb5bccb6162e6cff authored by Matthias Templ on 18 November 2020, 20:10 UTC, committed by cran-robot on 18 November 2020, 20:10 UTC
1 parent 9ae1e67
classData.cpp
``````#include <math.h>
#include <Eigen/Dense>
#include <iostream>
#include <iterator>
#include <vector>
#include <algorithm>
#include <functional>
#include <Rcpp.h>
#include "zeros.h"
#include "density_estimation.h"
#include "classData.h"

void
(const Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>,0, Eigen::Stride<0, 0> >, 1, -1, false> & row,
PRIOR prior, const int & cancel)
{
numbers.clear();

if( (row.array()!=0.0).any() )
BM(numbers, row, prior);
else
{
for(unsigned int i = 0, n = row.size(); i < n; i++)
numbers.push_back(row(i));
}

if(cancel!=-1) numbers.erase(numbers.begin() + cancel);

howmanyclasses = numbers.size();
};

void
dataManager::transfData
()
{
// clr transformation of prop_data in transf_data
double a = 0.0;

// computing geometric mean
for (const auto& y:numbers)
a += log(y);

// clr transformation
for (auto& y:numbers)
y = log(y) - a/howmanyclasses;
};

std::vector<double>
dataManager::getNumbers
()
{
return numbers;
}

void
dataManager::pacs
(densityEstimator & dens, Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> bspline)
{
dens.solve(bspline,numbers);
};

void
dataManager::antitData
(Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> x)
{
// Using trapezoidal integration in continuous setting
double len = (grid.back() - grid.front())/(grid.size()-1);
unsigned int x_len = x.size();
double den = 0.5*exp(x(0))*len + 0.5*exp(x(x_len-1))*len;
for(int i=1; i<x_len-1;i++){
den += exp(x(i))*len;
}

for(int i=0; i<x.size();i++){
x(i) = exp(x(i))/den;
}
};

void
dataManager::fillGrid
(double start, double end, unsigned int numPoints)
{
double step = (end - start)/numPoints;
grid.resize(numPoints);
grid[0] = start;
for (unsigned int i = 1; i < numPoints-1 ; ++i) {
grid[i] = grid[i-1] + step;
}
grid[numPoints-1] = end;
};

void
dataManager::plotData
(const densityEstimator & dens, unsigned long int numPoints,
Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> bspline,
Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> yplot)
{

double start = dens.get_u();
double end = dens.get_v();
unsigned int degree = dens.get_k();
unsigned int G = dens.get_G();
const std::vector<double> knots = dens.get_lambda();

fillGrid(start, end, numPoints);

Eigen::ArrayXd N;

for (int i = 0; i < grid.size(); ++i)
{
int j = bspline::findspan(degree,grid[i],knots);
N = Eigen::ArrayXd::Constant(G, 0.0);
bspline::basisfun(j, grid[i], degree, knots, N);
long double fvalue = compute_fvalue(bspline, N);
yplot(i)=fvalue;
}

antitData(yplot);
return;
};

void
dataManager::plotData_Clr
(const densityEstimator & dens, unsigned long int numPoints,
Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> bspline,
Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> yplot)
{

double start = dens.get_u();
double end = dens.get_v();
unsigned int degree = dens.get_k();
unsigned int G = dens.get_G();
const std::vector<double> knots = dens.get_lambda();

fillGrid(start, end, numPoints);

Eigen::ArrayXd N;

for (int i = 0; i < grid.size(); ++i) {
int j = bspline::findspan(degree,grid[i],knots);
N = Eigen::ArrayXd::Constant(G, 0.0);
bspline::basisfun(j, grid[i], degree, knots, N);
long double fvalue = compute_fvalue(bspline, N);
yplot(i)=fvalue;
}

return;
};

long double
dataManager::compute_fvalue
(Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> vec1, Eigen::ArrayXd vec2 )
{
long double res = 0.0;
unsigned int n = vec1.size();
if(vec2.size() != n){
Rcpp::Rcerr << "Error in compute_fvalue function. Check dimensions of the vectors.."
<< std::endl;
Rcpp::stop("Error in the C++ execution");
// exit(1);
}
for (int i = 0; i < n; ++i) {
res += vec1[i]*vec2[i];
}
return res;
};
``````

Computing file changes ...