Boost
C++ Libraries
...one of the most highly
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Coding Standards
This is an older version of Boost and was released in 2020. The current version is 1.90.0.
The following table gives an overview over all examples.
Table 1.4. Examples Overview
|
File |
Brief Description |
|---|---|
|
This examples shows how member functions can be used as system functions in odeint. |
|
|
This examples shows how member functions can be used as system
functions in odeint with |
|
|
Shows the usage of the Bulirsch-Stoer method. |
|
|
The chaotic system examples integrates the Lorenz system and calculates the Lyapunov exponents. |
|
|
Example calculating the elliptic functions using Bulirsch-Stoer and Runge-Kutta-Dopri5 Steppers with dense output. |
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|
The Fermi-Pasta-Ulam (FPU) example shows how odeint can be used to integrate lattice systems. |
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Shows skeletal code on how to implement own factory functions. |
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|
The harmonic oscillator examples gives a brief introduction to odeint and shows the usage of the classical Runge-Kutta-solvers. |
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|
This examples shows how Boost.Units can be used with odeint. |
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The Heun example shows how an custom Runge-Kutta stepper can be created with odeint generic Runge-Kutta method. |
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|
Example of a phase lattice integration using |
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|
Alternative way of integrating lorenz by using a self defined point3d data type as state type. |
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|
Simple example showing how to get odeint to work with a self-defined vector type. |
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|
The phase oscillator ensemble example shows how globally coupled oscillators can be analyzed and how statistical measures can be computed during integration. |
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|
Shows the strength of odeint's memory management by simulating a Hamiltonian system on an expanding lattice. |
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Integrating a simple, one-dimensional ODE showing the usage of integrate- and generate-functions. |
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The solar system example shows the usage of the symplectic solvers. |
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|
Trivial example showing the usability of the several stepper classes. |
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|
The stiff system example shows the usage of the stiff solvers using the Jacobian of the system function. |
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|
Implementation of a custom stepper - the stochastic euler - for solving stochastic differential equations. |
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|
The Stuart-Landau example shows how odeint can be used with complex state types. |
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|
The 2D phase oscillator example shows how a two-dimensional lattice works with odeint and how matrix types can be used as state types in odeint. |
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|
This stiff system example again shows the usage of the stiff solvers by integrating the van der Pol oscillator. |
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|
This examples integrates the Lorenz system by means of an arbitrary precision type. |
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The MTL-Gauss-packet example shows how the MTL can be easily used with odeint. |
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This examples shows the usage of the MTL implicit Euler method with a sparse matrix type. |
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The Thrust phase oscillator ensemble example shows how globally coupled oscillators can be analyzed with Thrust and CUDA, employing the power of modern graphic devices. |
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The Thrust phase oscillator chain example shows how chains of nearest neighbor coupled oscillators can be integrated with Thrust and odeint. |
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|
The Lorenz parameters examples show how ensembles of ordinary differential equations can be solved by means of Thrust to study the dependence of an ODE on some parameters. |
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|
Another examples for the usage of Thrust. |
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|
This example shows how the ublas vector types can be used with odeint. |
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This example shows how the VexCL - a framework for OpenCL computation - can be used with odeint. |
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|
OpenMP Lorenz attractor parameter study with continuous data. |
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OpenMP Lorenz attractor parameter study with split data. |
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|
OpenMP Lorenz attractor parameter study with nested |
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|
OpenMP nearest neighbour coupled phase chain with continuous state. |
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OpenMP nearest neighbour coupled phase chain with split state. |
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|
MPI nearest neighbour coupled phase chain. |
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|
This examples shows how a |
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|
This examples shows how gcc libquadmath can be used with odeint. It provides a high precision floating point type which is adapted to odeint in this example. |
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A very basic molecular dynamics simulation with the Velocity-Verlet method. |