6#ifndef THEORETICA_ERRORPROP_H
7#define THEORETICA_ERRORPROP_H
9#include "../core/core_traits.h"
10#include "../algebra/vec.h"
11#include "../autodiff/autodiff.h"
12#include "../statistics/statistics.h"
13#include "../pseudorandom/montecarlo.h"
14#include "../pseudorandom/sampling.h"
29 typename Matrix = mat<real>,
typename Dataset = vec<real>,
30 enable_vector<Dataset> =
true
32 inline Matrix
covar_mat(
const std::vector<Dataset>& v) {
35 cm.resize(v.size(), v.size());
37 for (
unsigned int i = 0; i < cm.rows(); ++i)
38 for (
unsigned int j = 0; j < cm.cols(); ++j)
62 const vec<real, N>& x_best,
const vec<real, N>& delta_x) {
67 for (
unsigned int i = 0; i < x_best.size(); ++i)
68 err_sqr +=
square(df.Dual(i) * delta_x[i]);
89 typename Matrix, enable_matrix<Matrix> =
true,
93 MultiDualFunction f,
const vec<real, N>& x_best,
const Matrix& cm) {
96 if(cm.rows() != x_best.size()) {
101 if(cm.cols() != x_best.size()) {
109 for (
unsigned int i = 0; i < cm.rows(); ++i)
110 for (
unsigned int j = 0; j < cm.cols(); ++j)
111 err_sqr += df.Dual(i) * df.Dual(j) * cm(i, j);
113 return sqrt(err_sqr);
131 typename Dataset = vec<real, N>
135 const std::vector<Dataset>& v) {
138 x_mean.resize(v.size());
140 for (
unsigned int i = 0; i < v.size(); ++i)
144 f, x_mean,
covar_mat<mat<real, N, N>, Dataset>(v));
166 template<
typename Function>
168 Function f, std::vector<pdf_sampler>& rv,
unsigned int N = 1
E+6) {
Multidual number algebra for functions of the form .
Definition multidual.h:26
#define TH_MATH_ERROR(F_NAME, VALUE, EXCEPTION)
TH_MATH_ERROR is a macro which throws exceptions or modifies errno (depending on which compiling opti...
Definition error.h:225
multidual< N > dreal_t
Real type for multivariate automatic differentiation (read "differential real").
Definition autodiff_types.h:117
vec< dreal_t< N >, N > dvec_t
Vector type for multivariate automatic differentiation (read "differential vector").
Definition autodiff_types.h:122
real propagerr(MultiDualFunction f, const vec< real, N > &x_best, const vec< real, N > &delta_x)
Automatically propagate uncertainties under quadrature on an arbitrary function given the uncertainti...
Definition errorprop.h:60
real stdev(const histogram &h)
Compute the standard deviation of the values of a histogram.
Definition histogram.h:320
real propagerr_mc(Function f, std::vector< pdf_sampler > &rv, unsigned int N=1E+6)
Propagate the statistical error on a given function using the Monte Carlo method, by generating a sam...
Definition errorprop.h:167
real covariance(const Dataset1 &X, const Dataset2 &Y, unsigned int constraints=1)
Compute the covariance between two datasets with the given number of constraints.
Definition statistics.h:262
real mean(const histogram &h)
Compute the mean of the values of a histogram.
Definition histogram.h:296
Matrix covar_mat(const std::vector< Dataset > &v)
Build the covariance matrix given a vector of datasets by computing the covariance between all couple...
Definition errorprop.h:32
Main namespace of the library which contains all functions and objects.
Definition algebra.h:27
double real
A real number, defined as a floating point type.
Definition constants.h:198
dual2 sqrt(dual2 x)
Compute the square root of a second order dual number.
Definition dual2_functions.h:54
TH_CONSTEXPR real nan()
Return a quiet NaN number in floating point representation.
Definition error.h:54
Vector sample_mc(Function f, std::vector< pdf_sampler > &rv, unsigned int N)
Generate a Monte Carlo sample of values of a given function of arbitrary variables following the give...
Definition montecarlo.h:376
constexpr real E
The Euler mathematical constant (e)
Definition constants.h:237
dual2 square(dual2 x)
Return the square of a second order dual number.
Definition dual2_functions.h:23