yes, all of those. They will be integrated into the Advance C++. In fact, some new features in C++17/20 course are in Boost (so, essentially replace boost namespace by std).
Just curious to know if there's any updates on this? Haven't seen any announcements on this yet. I'm excited to see what you done.
Fantastic! Christmas has come early for me!I have all the code ready. I just need to do the videos. Sorry for the slipped schedule (had a new pde/fdm deadline..) So, soon 2-3 weeks I reckon
Here is video #1 for kick off
And Easter eggs.Fantastic! Christmas has come early for me!
// TestExp5.cpp
//
// Using ODEs for optimisation. The very very simplest example to show how it works in the scalar
// case.
// DJD
// Systems? this is an execise.
//
//
// http://www.unige.ch/~hairer/preprints/gradientflow.pdf
//
// dx/dt = - nabla(U(x)) - lambda * nabla(c*x))
//
// Transform f(x) = 0 to a least-squares problem.
//
// (C) Datasim Education BV 2018-2022
//
#include <iostream>
#include <vector>
#include <cmath>
#include <complex>
#include <boost/numeric/odeint.hpp>
using value_type = double;
using state_type = std::vector<value_type>;
template <typename T>
using FunctionType = std::function<T(const T& arg)>;
using CFunctionType = FunctionType<std::complex<value_type>>;
value_type CSM(const CFunctionType& f, value_type x, value_type h)
{ // df/dx at x using tbe Complex step method
std::complex<value_type> z(x, h); // x + ih, i = sqrt(-1)
return std::imag(f(z)) / h;
}
// We choose min (f(x) - a)*(f(x)-a), f(x) = exp(x)
// Change the value of a to suit needs
const std::complex<value_type> a(std::exp(5.0), 0.0);
auto func = [](const std::complex<value_type>& z)
{
return (z - a) * (z - a);
};
value_type h = 1.0e-9;
// Free function to model RHS in dy/dt = RHS(t,y)
void Ode(const state_type &x, state_type &dxdt, const value_type t)
{
// dx/dt = - grad(f(x)
// We need to compute gradient
// 1. Exact
//
value_type a = std::exp(5.0);
dxdt[0] = 2.0 * (x[0] - a);
// 2. Complex Step method
//dxdt[0] = CSM(func, x[0], h);
// Transform semi-infinite time to (0,1)
// I use this technique in many places, dx/dtau = dx/dt (dt/dtau)
value_type tau = (1.0 - t) * (1.0 - t);
dxdt[0] = -dxdt[0]/tau;
}
int main()
{
namespace Bode = boost::numeric::odeint;
// Initial condition
value_type L = 0.0;
value_type T = 0.99;
value_type dt = 0.01001;
// Initial condition
state_type x{0.8};
// Middle-of-the-road solver
std::size_t steps = Bode::integrate(Ode, x, L, T, dt);
std::cout << "Number of steps Cash Karp 54: " << std::setprecision(16) << steps
<< "approximate: " << x[0] << '\n';
{
state_type x{0.8};
// Adaptive solver
Bode::bulirsch_stoer<state_type, value_type> bsStepper; // O(variable), controlled stepper
steps = Bode::integrate_const(bsStepper, Ode, x, L, T, dt);
std::cout << "Number of steps Bulirsch-Stoer: " << steps << ", approximate: " << x[0] << '\n';
}
return 0;
}Any plans, DevonFantastic! Christmas has come early for me!
I'm taking Christmas to NYE off to work on the new C++20 materials. I've already started working on it now too. I'm very happy.Any plans, Devon
