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<a name="Stepping-Functions"></a>
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<p>
Next: <a href="Adaptive-Step_002dsize-Control.html#Adaptive-Step_002dsize-Control" accesskey="n" rel="next">Adaptive Step-size Control</a>, Previous: <a href="Defining-the-ODE-System.html#Defining-the-ODE-System" accesskey="p" rel="previous">Defining the ODE System</a>, Up: <a href="Ordinary-Differential-Equations.html#Ordinary-Differential-Equations" accesskey="u" rel="up">Ordinary Differential Equations</a> [<a href="Function-Index.html#Function-Index" title="Index" rel="index">Index</a>]</p>
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<hr>
<a name="Stepping-Functions-1"></a>
<h3 class="section">27.2 Stepping Functions</h3>
<p>The lowest level components are the <em>stepping functions</em> which
advance a solution from time <em>t</em> to <em>t+h</em> for a fixed
step-size <em>h</em> and estimate the resulting local error.
</p>
<dl>
<dt><a name="index-gsl_005fodeiv2_005fstep_005falloc"></a>Function: <em>gsl_odeiv2_step *</em> <strong>gsl_odeiv2_step_alloc</strong> <em>(const gsl_odeiv2_step_type * <var>T</var>, size_t <var>dim</var>)</em></dt>
<dd><a name="index-gsl_005fodeiv2_005fstep"></a>
<a name="index-gsl_005fodeiv2_005fstep_005ftype"></a>
<p>This function returns a pointer to a newly allocated instance of a
stepping function of type <var>T</var> for a system of <var>dim</var>
dimensions. Please note that if you use a stepper method that
requires access to a driver object, it is advisable to use a driver
allocation method, which automatically allocates a stepper, too.
</p></dd></dl>
<dl>
<dt><a name="index-gsl_005fodeiv2_005fstep_005freset"></a>Function: <em>int</em> <strong>gsl_odeiv2_step_reset</strong> <em>(gsl_odeiv2_step * <var>s</var>)</em></dt>
<dd><p>This function resets the stepping function <var>s</var>. It should be used
whenever the next use of <var>s</var> will not be a continuation of a
previous step.
</p></dd></dl>
<dl>
<dt><a name="index-gsl_005fodeiv2_005fstep_005ffree"></a>Function: <em>void</em> <strong>gsl_odeiv2_step_free</strong> <em>(gsl_odeiv2_step * <var>s</var>)</em></dt>
<dd><p>This function frees all the memory associated with the stepping function
<var>s</var>.
</p></dd></dl>
<dl>
<dt><a name="index-gsl_005fodeiv2_005fstep_005fname"></a>Function: <em>const char *</em> <strong>gsl_odeiv2_step_name</strong> <em>(const gsl_odeiv2_step * <var>s</var>)</em></dt>
<dd><p>This function returns a pointer to the name of the stepping function.
For example,
</p>
<div class="example">
<pre class="example">printf ("step method is '%s'\n",
gsl_odeiv2_step_name (s));
</pre></div>
<p>would print something like <code>step method is 'rkf45'</code>.
</p></dd></dl>
<dl>
<dt><a name="index-gsl_005fodeiv2_005fstep_005forder"></a>Function: <em>unsigned int</em> <strong>gsl_odeiv2_step_order</strong> <em>(const gsl_odeiv2_step * <var>s</var>)</em></dt>
<dd><p>This function returns the order of the stepping function on the previous
step. The order can vary if the stepping function itself is adaptive.
</p></dd></dl>
<dl>
<dt><a name="index-gsl_005fodeiv2_005fstep_005fset_005fdriver"></a>Function: <em>int</em> <strong>gsl_odeiv2_step_set_driver</strong> <em>(gsl_odeiv2_step * <var>s</var>, const gsl_odeiv2_driver * <var>d</var>)</em></dt>
<dd><p>This function sets a pointer of the driver object <var>d</var> for stepper
<var>s</var>, to allow the stepper to access control (and evolve) object
through the driver object. This is a requirement for some steppers, to
get the desired error level for internal iteration of
stepper. Allocation of a driver object calls this function
automatically.
</p></dd></dl>
<dl>
<dt><a name="index-gsl_005fodeiv2_005fstep_005fapply"></a>Function: <em>int</em> <strong>gsl_odeiv2_step_apply</strong> <em>(gsl_odeiv2_step * <var>s</var>, double <var>t</var>, double <var>h</var>, double <var>y</var>[], double <var>yerr</var>[], const double <var>dydt_in</var>[], double <var>dydt_out</var>[], const gsl_odeiv2_system * <var>sys</var>)</em></dt>
<dd><p>This function applies the stepping function <var>s</var> to the system of
equations defined by <var>sys</var>, using the step-size <var>h</var> to advance
the system from time <var>t</var> and state <var>y</var> to time <var>t</var>+<var>h</var>.
The new state of the system is stored in <var>y</var> on output, with an
estimate of the absolute error in each component stored in <var>yerr</var>.
If the argument <var>dydt_in</var> is not null it should point an array
containing the derivatives for the system at time <var>t</var> on input. This
is optional as the derivatives will be computed internally if they are
not provided, but allows the reuse of existing derivative information.
On output the new derivatives of the system at time <var>t</var>+<var>h</var> will
be stored in <var>dydt_out</var> if it is not null.
</p>
<p>The stepping function returns <code>GSL_FAILURE</code> if it is unable to
compute the requested step. Also, if the user-supplied functions
defined in the system <var>sys</var> return a status other than
<code>GSL_SUCCESS</code> the step will be aborted. In that case, the
elements of <var>y</var> will be restored to their pre-step values and the
error code from the user-supplied function will be returned. Failure
may be due to a singularity in the system or too large step-size
<var>h</var>. In that case the step should be attempted again with a
smaller step-size, e.g. <em><var>h</var>/2</em>.
</p>
<p>If the driver object is not appropriately set via
<code>gsl_odeiv2_step_set_driver</code> for those steppers that need it, the
stepping function returns <code>GSL_EFAULT</code>. If the user-supplied
functions defined in the system <var>sys</var> returns <code>GSL_EBADFUNC</code>,
the function returns immediately with the same return code. In this
case the user must call <code>gsl_odeiv2_step_reset</code> before calling
this function again.
</p>
</dd></dl>
<p>The following algorithms are available,
</p>
<dl>
<dt><a name="index-gsl_005fodeiv2_005fstep_005frk2"></a>Step Type: <strong>gsl_odeiv2_step_rk2</strong></dt>
<dd><a name="index-RK2_002c-Runge_002dKutta-method"></a>
<a name="index-Runge_002dKutta-methods_002c-ordinary-differential-equations"></a>
<p>Explicit embedded Runge-Kutta (2, 3) method.
</p></dd></dl>
<dl>
<dt><a name="index-gsl_005fodeiv2_005fstep_005frk4"></a>Step Type: <strong>gsl_odeiv2_step_rk4</strong></dt>
<dd><a name="index-RK4_002c-Runge_002dKutta-method"></a>
<p>Explicit 4th order (classical) Runge-Kutta. Error estimation is
carried out by the step doubling method. For more efficient estimate
of the error, use the embedded methods described below.
</p></dd></dl>
<dl>
<dt><a name="index-gsl_005fodeiv2_005fstep_005frkf45"></a>Step Type: <strong>gsl_odeiv2_step_rkf45</strong></dt>
<dd><a name="index-Fehlberg-method_002c-differential-equations"></a>
<a name="index-RKF45_002c-Runge_002dKutta_002dFehlberg-method"></a>
<p>Explicit embedded Runge-Kutta-Fehlberg (4, 5) method. This method is
a good general-purpose integrator.
</p></dd></dl>
<dl>
<dt><a name="index-gsl_005fodeiv2_005fstep_005frkck"></a>Step Type: <strong>gsl_odeiv2_step_rkck</strong></dt>
<dd><a name="index-Runge_002dKutta-Cash_002dKarp-method"></a>
<a name="index-Cash_002dKarp_002c-Runge_002dKutta-method"></a>
<p>Explicit embedded Runge-Kutta Cash-Karp (4, 5) method.
</p></dd></dl>
<dl>
<dt><a name="index-gsl_005fodeiv2_005fstep_005frk8pd"></a>Step Type: <strong>gsl_odeiv2_step_rk8pd</strong></dt>
<dd><a name="index-Runge_002dKutta-Prince_002dDormand-method"></a>
<a name="index-Prince_002dDormand_002c-Runge_002dKutta-method"></a>
<p>Explicit embedded Runge-Kutta Prince-Dormand (8, 9) method.
</p></dd></dl>
<dl>
<dt><a name="index-gsl_005fodeiv2_005fstep_005frk1imp"></a>Step Type: <strong>gsl_odeiv2_step_rk1imp</strong></dt>
<dd><a name="index-Implicit-Euler-method"></a>
<p>Implicit Gaussian first order Runge-Kutta. Also known as implicit
Euler or backward Euler method. Error estimation is carried out by the
step doubling method. This algorithm requires the Jacobian and
access to the driver object via <code>gsl_odeiv2_step_set_driver</code>.
</p></dd></dl>
<dl>
<dt><a name="index-gsl_005fodeiv2_005fstep_005frk2imp"></a>Step Type: <strong>gsl_odeiv2_step_rk2imp</strong></dt>
<dd><a name="index-Implicit-Runge_002dKutta-method"></a>
<p>Implicit Gaussian second order Runge-Kutta. Also known as implicit
mid-point rule. Error estimation is carried out by the step doubling
method. This stepper requires the Jacobian and access to the driver
object via <code>gsl_odeiv2_step_set_driver</code>.
</p></dd></dl>
<dl>
<dt><a name="index-gsl_005fodeiv2_005fstep_005frk4imp"></a>Step Type: <strong>gsl_odeiv2_step_rk4imp</strong></dt>
<dd><p>Implicit Gaussian 4th order Runge-Kutta. Error estimation is carried
out by the step doubling method. This algorithm requires the Jacobian
and access to the driver object via <code>gsl_odeiv2_step_set_driver</code>.
</p></dd></dl>
<dl>
<dt><a name="index-gsl_005fodeiv2_005fstep_005fbsimp"></a>Step Type: <strong>gsl_odeiv2_step_bsimp</strong></dt>
<dd><a name="index-Bulirsch_002dStoer-method"></a>
<a name="index-Bader-and-Deuflhard_002c-Bulirsch_002dStoer-method_002e"></a>
<a name="index-Deuflhard-and-Bader_002c-Bulirsch_002dStoer-method_002e"></a>
<p>Implicit Bulirsch-Stoer method of Bader and Deuflhard. The method is
generally suitable for stiff problems. This stepper requires the
Jacobian.
</p></dd></dl>
<dl>
<dt><a name="index-gsl_005fodeiv2_005fstep_005fmsadams"></a>Step Type: <strong>gsl_odeiv2_step_msadams</strong></dt>
<dd><a name="index-Adams-method"></a>
<a name="index-multistep-methods_002c-ODEs"></a>
<a name="index-predictor_002dcorrector-method_002c-ODEs"></a>
<a name="index-Nordsieck-form"></a>
<p>A variable-coefficient linear multistep Adams method in Nordsieck
form. This stepper uses explicit Adams-Bashforth (predictor) and
implicit Adams-Moulton (corrector) methods in <em>P(EC)^m</em>
functional iteration mode. Method order varies dynamically between 1
and 12. This stepper requires the access to the driver object via
<code>gsl_odeiv2_step_set_driver</code>.
</p></dd></dl>
<dl>
<dt><a name="index-gsl_005fodeiv2_005fstep_005fmsbdf"></a>Step Type: <strong>gsl_odeiv2_step_msbdf</strong></dt>
<dd><a name="index-BDF-method"></a>
<p>A variable-coefficient linear multistep backward differentiation
formula (BDF) method in Nordsieck form. This stepper uses the explicit
BDF formula as predictor and implicit BDF formula as corrector. A
modified Newton iteration method is used to solve the system of
non-linear equations. Method order varies dynamically between 1 and
5. The method is generally suitable for stiff problems. This stepper
requires the Jacobian and the access to the driver object via
<code>gsl_odeiv2_step_set_driver</code>.
</p></dd></dl>
<hr>
<div class="header">
<p>
Next: <a href="Adaptive-Step_002dsize-Control.html#Adaptive-Step_002dsize-Control" accesskey="n" rel="next">Adaptive Step-size Control</a>, Previous: <a href="Defining-the-ODE-System.html#Defining-the-ODE-System" accesskey="p" rel="previous">Defining the ODE System</a>, Up: <a href="Ordinary-Differential-Equations.html#Ordinary-Differential-Equations" accesskey="u" rel="up">Ordinary Differential Equations</a> [<a href="Function-Index.html#Function-Index" title="Index" rel="index">Index</a>]</p>
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