public Vector <double>[] bvpsolver_zzz(Func <double, Vector <double>, Vector <double> > system,
double ya, double yb,
double xa, double xb,
int N)
{
//先求解方程得到初始斜率的估计值，再进行打靶法迭代。--zzz
Vector <double>[] res;
Vector <double> y0;
double s_guess, s_guess_pre;
double fais, fais_pre;
double dfai, ds;
int count = 0;
//计算20组s_guess和fais，然后样条插值得到连续函数，再通过解方程，得到使fais=0的初始s_guess
int M = 50;
double[] sLst = Vector <double> .Build.Dense(M, i => yb / M *i).ToArray();
double[] faisLst = new double[M];
count = 0;
while (count < M)
{
y0 = Vector <double> .Build.DenseOfArray(new[] { ya, sLst[count] });
// observer_pr ob_pr = this->write_targetFunc_end;
res = RungeKutta.FourthOrder(y0, xa, xb, N, system);
faisLst[count] = res[N - 1][0] - yb;
count++;
}
//样条插值得到连续函数
var cubicSpl = CubicSpline.InterpolateNatural(sLst, faisLst);
/*如果初始值离解太远，牛顿法会不收敛。故采用Mathnet包中的RobustNewtonRaphson
* double s_cur = 0, s_next;
* count = 0;
* while (count < 1000)
* {
* fais = cubicSpl.Interpolate(s_cur);
* dfaids = cubicSpl.Differentiate(s_cur);
* if (fais < 1e-5 && fais > -1e-5)
* {
* break;
* }
*
* s_next = s_cur - fais / dfaids;
* s_cur = s_next;
* count += 1;
* }*/
//解方程fais=0,得到初始斜率s_guess。该法先尝试牛顿法，如失败会采用二分法（bisection）。
s_guess = RobustNewtonRaphson.FindRoot(cubicSpl.Interpolate, cubicSpl.Differentiate, 0, yb, 1e-5);
//利用解得的s_guess，构造s_guess_pre，目的是求导数dfai/ds。
if (s_guess == 0)
{
s_guess_pre = 1e-2;
}
else
{
s_guess_pre = s_guess * 0.99;
}
//求s_guess_pre对应的fais_pre，目的是求导数dfai/ds。
y0 = Vector <double> .Build.DenseOfArray(new[] { ya, s_guess_pre });
res = RungeKutta.FourthOrder(y0, xa, xb, N, system);
fais_pre = res[N - 1][0] - yb;
count = 0;
while (count < 50)
{
y0 = Vector <double> .Build.DenseOfArray(new[] { ya, s_guess });
res = RungeKutta.FourthOrder(y0, xa, xb, N, system);
fais = res[N - 1][0] - yb;
dfai = fais - fais_pre;
ds = s_guess - s_guess_pre;
if (fais < 1e-5 && fais > -1e-5)
{
break;
}
fais_pre = fais;
s_guess_pre = s_guess;
s_guess = s_guess - fais * ds / dfai;
count++;
}
return(res);
}
public double[,] rabbit_fox_horizontal_diff_ts(float r, float r_ts, float f, float f_ts, int yr, string r_integ_method, string f_integ_method)
{
int ts_factor = 10; //time step factor, to define numer of loops in unit of time, e.g. if ts=0.1 then we will have 10 loops in each unit of time
float ts;
if (r_ts > f_ts)
ts = f_ts;
else if (r_ts > f_ts)
ts = r_ts;
else
ts = r_ts;
if (ts >= 0.1)
{
ts_factor = 10;
}
else if (ts >= 0.009) //>=0.01
{
ts_factor = 100;
}
else if (ts >= 0.0009) //>=0.001
ts_factor = 1000;
//ts_factor = 1000;
Rabbit rab = new Rabbit();
Fox fx_m = new Fox();
RungeKutta rk = new RungeKutta();
//the system will loop for each time step
//int lp = Convert.ToInt32(Math.Truncate(yr / 0.1)); //total number of loop due to the defined year
int lp = yr * ts_factor;
lp = lp + 1;
// r_result = new double[lp]; //array for rab
//f_result = new double[lp]; //array for fox
double[,] result = new double[lp, 2];
double[] t = new double[3];
t[1] = Convert.ToDouble(r_ts.ToString("#.####")); //time step of rabbit
t[2] = Convert.ToDouble(f_ts.ToString("#.####")); //time step of fox
int temp_r_ts = Convert.ToInt16(r_ts * ts_factor);
int temp_f_ts = Convert.ToInt16(f_ts * ts_factor);
float rx = r;
float ry = f;
float fx = r;
float fy = f;
for (int i = 1; i < lp; i++)
{
int m = i % temp_r_ts; //m for maintaining result of % operation
if (m == 0 && i > 0) //check if the current time step is valid to run rabit model
{
if (r_integ_method == "Runge-Kutta") // Runge-Kutta integration of rabbit model
{
rx = rk.calc_Rabbit_Runge_Kutta(rx, ry, r_ts);
}
else
rx = rx + rab.rabbit_model(rx, ry) * r_ts;
//rx = rx + rabbit_with_diff_func(rx, ry) * r_ts;
r = rx;
}
int n = i % temp_f_ts;
if (n == 0 && i > 0) //check if the current time step is valid to run fox model
{
if (m == 0)
fx = r;
if (f_integ_method == "Runge-Kutta") // for Runge-Kutta integration of fox model
{
fy = rk.calc_Fox_Runge_Kutta(fy, fx, f_ts);
}
else
fy = fy + fx_m.fox_model(fy, fx) * f_ts;
//fy = fy + fox_with_diff_func(fy, fx) * f_ts;
f = fy;
fx = r;
}
if (m == 0) //if the time step meets ts of rabbit then copy value of f
ry = f;
//r_result[i] = r; // Convert.ToDouble(r.ToString("#.##"));
result[i,0] = r;
if (f >= 0)
//f_result[i] = f;
result[i, 1] = f;
else //if fox pop <0 set it to 0
{
f = 0;
//f_result[i] = 0;
result[i, 1] = 0;
}
if (result[i, 0] < 0) // (r_result[i] < 0)
{
//r_result[i] = 0;//if rab pop<0 then set the pop value to 0 and quit
//f_result[i] = 0;
result[i, 0] = 0;//if rab pop<0 then set the pop value to 0 and quit
result[i, 1] = 0;
break;
}
}
return result;
}
/// <summary>
/// Obtaining the time integrated spatial discretization of the reinitialization equation in a narrow band around the zero level set, based on a Godunov's numerical Hamiltonian calculation
/// </summary>
/// <param name="LS"> The level set function </param>
/// <param name="Restriction"> The narrow band around the zero level set </param>
/// <param name="NumberOfTimesteps">
/// maximum number of pseudo-timesteps
/// </param>
/// <param name="thickness">
/// The smoothing width of the signum function.
/// This is the main stabilization parameter for re-initialization.
/// It should be set to approximately 3 cells.
/// </param>
/// <param name="TimestepSize">
/// size of the pseudo-timestep
/// </param>
public void ReInitialize(LevelSet LS, SubGrid Restriction, double thickness, double TimestepSize, int NumberOfTimesteps)
{
using (var tr = new FuncTrace()) {
// log parameters:
tr.Info("thickness: " + thickness.ToString(NumberFormatInfo.InvariantInfo));
tr.Info("TimestepSize: " + TimestepSize.ToString(NumberFormatInfo.InvariantInfo));
tr.Info("NumberOfTimesteps: " + NumberOfTimesteps);
ExplicitEuler TimeIntegrator;
SpatialOperator SO;
Func <int[], int[], int[], int> QuadratureOrder = QuadOrderFunc.NonLinear(3);
if (m_ctx.SpatialDimension == 2)
{
SO = new SpatialOperator(1, 5, 1, QuadratureOrder, new string[] { "LS", "LSCGV", "LSDG[0]", "LSUG[0]", "LSDG[1]", "LSUG[1]", "Result" });
SO.EquationComponents["Result"].Add(new GodunovHamiltonian(m_ctx, thickness));
SO.Commit();
TimeIntegrator = new RungeKutta(m_Scheme, SO, new CoordinateMapping(LS), new CoordinateMapping(LSCGV, LSDG[0], LSUG[0], LSDG[1], LSUG[1]), sgrd: Restriction);
}
else
{
SO = new SpatialOperator(1, 7, 1, QuadratureOrder, new string[] { "LS", "LSCGV", "LSDG[0]", "LSUG[0]", "LSDG[1]", "LSUG[1]", "LSDG[2]", "LSUG[2]", "Result" });
SO.EquationComponents["Result"].Add(new GodunovHamiltonian(m_ctx, thickness));
SO.Commit();
TimeIntegrator = new RungeKutta(m_Scheme, SO, new CoordinateMapping(LS), new CoordinateMapping(LSCGV, LSDG[0], LSUG[0], LSDG[1], LSUG[1], LSDG[2], LSUG[2]), sgrd: Restriction);
}
// Calculating the gradients in each sub-stage of a Runge-Kutta integration procedure
ExplicitEuler.ChangeRateCallback EvalGradients = delegate(double t1, double t2) {
LSUG.Clear();
CalculateLevelSetGradient(LS, LSUG, "Upwind", Restriction);
LSDG.Clear();
CalculateLevelSetGradient(LS, LSDG, "Downwind", Restriction);
LSCG.Clear();
CalculateLevelSetGradient(LS, LSCG, "Central", Restriction);
LSCGV.Clear();
var VolMask = (Restriction != null) ? Restriction.VolumeMask : null;
LSCGV.ProjectAbs(1.0, VolMask, LSCG.ToArray());
};
TimeIntegrator.OnBeforeComputeChangeRate += EvalGradients;
{
EvalGradients(0, 0);
var GodunovResi = new SinglePhaseField(LS.Basis, "Residual");
SO.Evaluate(1.0, 0.0, LS.Mapping, TimeIntegrator.ParameterMapping.Fields, GodunovResi.Mapping, Restriction);
//Tecplot.Tecplot.PlotFields(ArrayTools.Cat<DGField>( LSUG, LSDG, LS, GodunovResi), "Residual", 0, 3);
}
// pseudo-timestepping
// ===================
double factor = 1.0;
double time = 0;
LevelSet prevLevSet = new LevelSet(LS.Basis, "prevLevSet");
CellMask RestrictionMask = (Restriction == null) ? null : Restriction.VolumeMask;
for (int i = 0; (i < NumberOfTimesteps); i++)
{
tr.Info("Level set reinitialization pseudo-timestepping, timestep " + i);
// backup old Levelset
// -------------------
prevLevSet.Clear();
prevLevSet.Acc(1.0, LS, RestrictionMask);
// time integration
// ----------------
double dt = TimestepSize * factor;
tr.Info("dt = " + dt.ToString(NumberFormatInfo.InvariantInfo) + " (factor = " + factor.ToString(NumberFormatInfo.InvariantInfo) + ")");
TimeIntegrator.Perform(dt);
time += dt;
// change norm
// ------
prevLevSet.Acc(-1.0, LS, RestrictionMask);
double ChangeNorm = prevLevSet.L2Norm(RestrictionMask);
Console.WriteLine("Reinit: PseudoTime: {0} - Changenorm: {1}", i, ChangeNorm);
//Tecplot.Tecplot.PlotFields(new SinglePhaseField[] { LS }, m_ctx, "Reinit-" + i, "Reinit-" + i, i, 3);
}
//*/
}
}
private static void Main()
//****************************************************************************80
//
// Purpose:
//
// MAIN is the main program for LORENZ_ODE.
//
// Discussion:
//
// Thanks to Ben Whitney for pointing out an error in specifying a loop,
// 24 May 2016.
//
// Licensing:
//
// This code is distributed under the GNU LGPL license.
//
// Modified:
//
// 24 May 2016
//
// Author:
//
// John Burkardt
//
{
const string command_filename = "lorenz_ode_commands.txt";
List <string> command_unit = new();
const string data_filename = "lorenz_ode_data.txt";
List <string> data_unit = new();
int j;
const int m = 3;
const int n = 200000;
Console.WriteLine("");
Console.WriteLine("LORENZ_ODE");
Console.WriteLine(" Compute solutions of the Lorenz system.");
Console.WriteLine(" Write data to a file for use by gnuplot.");
//
// Data
//
double t_final = 40.0;
double dt = t_final / n;
//
// Store the initial conditions in entry 0.
//
double[] t = typeMethods.r8vec_linspace_new(n + 1, 0.0, t_final);
double[] x = new double[m * (n + 1)];
x[0 + 0 * m] = 8.0;
x[0 + 1 * m] = 1.0;
x[0 + 2 * m] = 1.0;
//
// Compute the approximate solution at equally spaced times.
//
for (j = 0; j < n; j++)
{
double[] xnew = RungeKutta.rk4vec(t[j], m, x, dt, Lorenz.lorenz_rhs, index: +j * m);
int i;
for (i = 0; i < m; i++)
{
x[i + (j + 1) * m] = xnew[i];
}
}
//
// Create the plot data file.
//
for (j = 0; j <= n; j += 50)
{
data_unit.Add(" " + t[j].ToString(CultureInfo.InvariantCulture).PadLeft(14)
+ " " + x[0 + j * m].ToString(CultureInfo.InvariantCulture).PadLeft(14)
+ " " + x[1 + j * m].ToString(CultureInfo.InvariantCulture).PadLeft(14)
+ " " + x[2 + j * m].ToString(CultureInfo.InvariantCulture).PadLeft(14) + "");
}
File.WriteAllLines(data_filename, data_unit);
Console.WriteLine(" Created data file \"" + data_filename + "\".");
/*
* Create the plot command file.
*/
command_unit.Add("# " + command_filename + "");
command_unit.Add("#");
command_unit.Add("# Usage:");
command_unit.Add("# gnuplot < " + command_filename + "");
command_unit.Add("#");
command_unit.Add("set term png");
command_unit.Add("set output 'xyz_time.png'");
command_unit.Add("set xlabel '<--- T --->'");
command_unit.Add("set ylabel '<--- X(T), Y(T), Z(T) --->'");
command_unit.Add("set title 'X, Y and Z versus Time'");
command_unit.Add("set grid");
command_unit.Add("set style data lines");
command_unit.Add("plot '" + data_filename
+ "' using 1:2 lw 3 linecolor rgb 'blue',"
+ "'' using 1:3 lw 3 linecolor rgb 'red',"
+ "'' using 1:4 lw 3 linecolor rgb 'green'");
command_unit.Add("set output 'xyz_3d.png'");
command_unit.Add("set xlabel '<--- X(T) --->'");
command_unit.Add("set ylabel '<--- Y(T) --->'");
command_unit.Add("set zlabel '<--- Z(T) --->'");
command_unit.Add("set title '(X(T),Y(T),Z(T)) trajectory'");
command_unit.Add("set grid");
command_unit.Add("set style data lines");
command_unit.Add("splot '" + data_filename
+ "' using 2:3:4 lw 1 linecolor rgb 'blue'");
command_unit.Add("quit");
File.WriteAllLines(command_filename, command_unit);
Console.WriteLine(" Created command file '" + command_filename + "'");
Console.WriteLine("");
Console.WriteLine("LORENZ_ODE:");
Console.WriteLine(" Normal end of execution.");
Console.WriteLine("");
}
/// <summary>
/// Método Runge Kutta de Segunda ordem para equações diferenciais
/// </summary>
/// <param name="y0">Valor Inicial</param>
/// <param name="start">Tempo Inicial</param>
/// <param name="end">Tempo Final</param>
/// <param name="dydx">Equação diferencial a ser calculada</param>
/// <returns></returns>
public double RungeKutta2(double y0, double start, double end, Func <double, double, double> dydx)
{
return(RungeKutta.SecondOrder(y0, start, end, 10, dydx)[9]);
}
/// <summary>
/// Método Runge Kutta de Quarta ordem para equações diferenciais
/// </summary>
/// <param name="y0">Valor Inicial</param>
/// <param name="start">Tempo Inicial</param>
/// <param name="end">Tempo Final</param>
/// <param name="dydx">Equação diferencial a ser calculada</param>
/// <returns></returns>
public double RungeKutta4(double y0, double start, double end, Func <double, double, double> dydx)
{
return(RungeKutta.FourthOrder(y0, start, end, 10, dydx)[9]);
}
public double[,] rabbit_fox_horizontal_same_ts(float r, float f, int yr, float ts, string r_integ_method, string f_integ_method)
{
int ts_factor = 10; //time step factor, to define numer of loops in unit of time, e.g. if ts=0.1 then we will have 10 loops in each unit of time
if (ts >= 0.1)
{
ts_factor = 10;
}
else if (ts >= 0.009) //>=0.01
{
ts_factor = 100;
}
else if (ts >= 0.0009) //>=0.001
ts_factor = 1000;
//ts_factor = 1000;
Rabbit rab = new Rabbit();
Fox fx = new Fox();
RungeKutta rk = new RungeKutta();
//the system will loop according to the defined time step
//int lp = Convert.ToInt16(Math.Truncate(yr / ts)); //total number of loop due to the defined time step
//int lp = Convert.ToInt32(Math.Truncate(yr / 0.1)); //10 timestep in 1 year
int lp = yr * ts_factor;
lp = lp + 2;
double[,] result = new double[lp, 2];
float fr = r; //rabbit population for fox model
for (int i = 1; i < lp; i++)
{
//if (i % (Convert.ToInt16(Math.Truncate(ts * 10))) == 0)
if (i % (Convert.ToInt16(ts * ts_factor)) == 0)
{
//run rabbit model
if (r_integ_method == "Runge-Kutta") // for Runge-Kutta integration of rabbit
{
r = rk.calc_Rabbit_Runge_Kutta(r, f, ts);
}
else
//for euler integration
r = r + rab.rabbit_model(r, f) * ts;
// r = r + rabbit_with_diff_func(r, f) * ts; //rabbit with px/(q+x) function than bx
//run fox model
if (f_integ_method == "Runge-Kutta") // for Runge-Kutta integration of fox model
{
f = rk.calc_Fox_Runge_Kutta(f, fr, ts);
}
else
f = f + fx.fox_model(f, fr) * ts;
//f = f + fox_with_diff_func(f, fr) * ts; //fox with px/(q+x) function than bx
fr = r; //update current rabbit population for fox model
if (r < 0)
result[i, 0] = 0;
else
result[i, 0] = r; //Convert.ToDouble(r.ToString("#.##"));
if (f < 0)
result[i, 1] = 0;
else
result[i, 1] = f; // Convert.ToDouble(f.ToString("#.##"));
if (result[i, 0] < 0) //(result[i, 0] < 1)
{
result[i, 0] = 0; //if pop<0 then set the pop value to 0
result[i, 1] = 0;
break;
}
}
else
{
if (r < 0) //(result[i, 0] < 1)
{
result[i, 0] = 0; //if pop<0 then set the pop value to 0
result[i, 1] = 0;
break;
}
else
{
result[i, 0] = r;
result[i, 1] = f;
}
}
}
return result;
}
/// <summary>
/// Creates the appropriate time-stepper for a given
/// <paramref name="timeStepperType"/>
/// </summary>
/// <param name="timeStepperType">
/// The type of the time-stepper (e.g., Runge-Kutta) to be created
/// </param>
/// <param name="control">
/// Configuration options
/// </param>
/// <param name="equationSystem">
/// The equation system to be solved
/// </param>
/// <param name="fieldSet">
/// Fields affected by the time-stepper
/// </param>
/// <param name="parameterMap">
/// Fields serving as parameter for the time-stepper.
/// </param>
/// <param name="speciesMap">
/// Mapping of different species inside the domain
/// </param>
/// <param name="program"></param>
/// <returns>
/// Depending on <paramref name="timeStepperType"/>, an appropriate
/// implementation of <see cref="ITimeStepper"/>.
/// </returns>
/// <remarks>
/// Currently limiting is not supported for Adams-Bashforth methods
/// </remarks>
public static ITimeStepper Instantiate <T>(
this ExplicitSchemes timeStepperType,
CNSControl control,
OperatorFactory equationSystem,
CNSFieldSet fieldSet,
CoordinateMapping parameterMap,
ISpeciesMap speciesMap,
IProgram <T> program)
where T : CNSControl, new()
{
CoordinateMapping variableMap = new CoordinateMapping(fieldSet.ConservativeVariables);
IBMControl ibmControl = control as IBMControl;
IBMOperatorFactory ibmFactory = equationSystem as IBMOperatorFactory;
if (control.DomainType != DomainTypes.Standard &&
(ibmFactory == null || ibmControl == null))
{
throw new Exception();
}
ITimeStepper timeStepper;
switch (timeStepperType)
{
case ExplicitSchemes.RungeKutta when control.DomainType == DomainTypes.Standard:
timeStepper = new RungeKutta(
RungeKutta.GetDefaultScheme(control.ExplicitOrder),
equationSystem.GetJoinedOperator().ToSpatialOperator(fieldSet),
variableMap,
parameterMap,
equationSystem.GetJoinedOperator().CFLConstraints);
break;
case ExplicitSchemes.RungeKutta:
timeStepper = ibmControl.TimesteppingStrategy.CreateRungeKuttaTimeStepper(
ibmControl,
equationSystem,
fieldSet,
parameterMap,
speciesMap,
equationSystem.GetJoinedOperator().CFLConstraints);
break;
case ExplicitSchemes.AdamsBashforth when control.DomainType == DomainTypes.Standard:
timeStepper = new AdamsBashforth(
equationSystem.GetJoinedOperator().ToSpatialOperator(fieldSet),
variableMap,
parameterMap,
control.ExplicitOrder,
equationSystem.GetJoinedOperator().CFLConstraints);
break;
case ExplicitSchemes.AdamsBashforth:
timeStepper = new IBMAdamsBashforth(
ibmFactory.GetJoinedOperator().ToSpatialOperator(fieldSet),
ibmFactory.GetImmersedBoundaryOperator().ToSpatialOperator(fieldSet),
variableMap,
parameterMap,
speciesMap,
ibmControl,
equationSystem.GetJoinedOperator().CFLConstraints);
break;
case ExplicitSchemes.LTS when control.DomainType == DomainTypes.Standard:
timeStepper = new AdamsBashforthLTS(
equationSystem.GetJoinedOperator().ToSpatialOperator(fieldSet),
variableMap,
parameterMap,
control.ExplicitOrder,
control.NumberOfSubGrids,
equationSystem.GetJoinedOperator().CFLConstraints,
reclusteringInterval: control.ReclusteringInterval,
fluxCorrection: control.FluxCorrection,
saveToDBCallback: program.SaveToDatabase,
maxNumOfSubSteps: control.maxNumOfSubSteps);
break;
case ExplicitSchemes.LTS:
timeStepper = new IBMAdamsBashforthLTS(
equationSystem.GetJoinedOperator().ToSpatialOperator(fieldSet),
ibmFactory.GetImmersedBoundaryOperator().ToSpatialOperator(fieldSet),
variableMap,
parameterMap,
speciesMap,
ibmControl,
equationSystem.GetJoinedOperator().CFLConstraints,
reclusteringInterval: control.ReclusteringInterval,
fluxCorrection: control.FluxCorrection,
maxNumOfSubSteps: control.maxNumOfSubSteps);
break;
case ExplicitSchemes.Rock4 when control.DomainType == DomainTypes.Standard:
timeStepper = new ROCK4(equationSystem.GetJoinedOperator().ToSpatialOperator(fieldSet), new CoordinateVector(variableMap), null);
break;
case ExplicitSchemes.SSP54 when control.DomainType == DomainTypes.Standard:
timeStepper = new RungeKutta(
RungeKuttaScheme.SSP54,
equationSystem.GetJoinedOperator().ToSpatialOperator(fieldSet),
variableMap,
parameterMap,
equationSystem.GetJoinedOperator().CFLConstraints);
break;
case ExplicitSchemes.RKC84 when control.DomainType == DomainTypes.Standard:
timeStepper = new RungeKutta(
RungeKuttaScheme.RKC84,
equationSystem.GetJoinedOperator().ToSpatialOperator(fieldSet),
variableMap,
parameterMap,
equationSystem.GetJoinedOperator().CFLConstraints);
break;
case ExplicitSchemes.None:
throw new System.ArgumentException("Cannot instantiate empty scheme");
default:
throw new NotImplementedException(String.Format(
"Explicit time stepper type '{0}' not implemented for domain type '{1}'",
timeStepperType,
control.DomainType));
}
// Make sure shock sensor is updated before every flux evaluation
if (control.ShockSensor != null)
{
ExplicitEuler explicitEulerBasedTimestepper = timeStepper as ExplicitEuler;
if (explicitEulerBasedTimestepper == null)
{
throw new Exception(String.Format(
"Shock-capturing currently not implemented for time-steppers of type '{0}'",
timeStepperType));
}
explicitEulerBasedTimestepper.OnBeforeComputeChangeRate += delegate(double absTime, double relTime) {
// Note: Only shock sensor is updated, _NOT_ the corresponding variable
program.Control.ShockSensor.UpdateSensorValues(
program.WorkingSet,
program.SpeciesMap,
explicitEulerBasedTimestepper.SubGrid.VolumeMask);
// Note: When being called, artificial viscosity is updated in the _ENTIRE_ (fluid) domain
var avField = program.WorkingSet.DerivedFields[Variables.ArtificialViscosity];
Variables.ArtificialViscosity.UpdateFunction(avField, program.SpeciesMap.SubGrid.VolumeMask, program);
// Test
//double sensorNorm = program.WorkingSet.DerivedFields[Variables.ShockSensor].L2Norm();
//double avNorm = program.WorkingSet.DerivedFields[Variables.ArtificialViscosity].L2Norm();
//Console.WriteLine("\r\nThis is OnBeforeComputeChangeRate");
//Console.WriteLine("SensorNeu: {0}", sensorNorm);
//Console.WriteLine("AVNeu: {0}", avNorm);
};
}
// Make sure limiter is applied after each modification of conservative variables
if (control.Limiter != null)
{
ExplicitEuler explicitEulerBasedTimestepper = timeStepper as ExplicitEuler;
if (explicitEulerBasedTimestepper == null)
{
throw new Exception(String.Format(
"Limiting currently not implemented for time-steppers of type '{0}~",
timeStepperType));
}
explicitEulerBasedTimestepper.OnAfterFieldUpdate +=
(t, f) => control.Limiter.LimitFieldValues(program);
}
return(timeStepper);
}
static void Main(string[] args)
{
RungeKutta Result = new RungeKutta();
Result.Wynik();
}
private static void test01()
//****************************************************************************80
//
// Purpose:
//
// TEST01 tests RK1_TI_STEP.
//
// Licensing:
//
// This code is distributed under the GNU LGPL license.
//
// Modified:
//
// 06 July 2010
//
// Author:
//
// John Burkardt
//
{
const double t0 = 0.0;
const double tn = 1.0;
Console.WriteLine("");
Console.WriteLine("TEST01");
Console.WriteLine(" RK1_TI_STEP uses a first order RK method");
Console.WriteLine(" for a problem whose right hand side does not");
Console.WriteLine(" depend explicitly on time.");
const int n = 10;
double[] x = new double[n + 1];
const double h = (tn - t0) / n;
const double q = 1.0;
int seed = 123456789;
int i = 0;
double t = t0;
x[i] = 0.0;
Console.WriteLine("");
Console.WriteLine(" I T X");
Console.WriteLine("");
Console.WriteLine(" " + i.ToString().PadLeft(8)
+ " " + t.ToString(CultureInfo.InvariantCulture).PadLeft(14)
+ " " + x[i].ToString(CultureInfo.InvariantCulture).PadLeft(14) + "");
for (i = 1; i <= n; i++)
{
t = ((n - i) * t0
+ i * tn)
/ n;
x[i] = RungeKutta.rk1_ti_step(x[i - 1], t, h, q, fi, gi, ref seed);
Console.WriteLine(" " + i.ToString().PadLeft(8)
+ " " + t.ToString(CultureInfo.InvariantCulture).PadLeft(14)
+ " " + x[i].ToString(CultureInfo.InvariantCulture).PadLeft(14) + "");
}
}
public Vector <double>[] Integrate(IReadOnlyList <double> Control)
{
_params = Control;
return(RungeKutta.FourthOrder(_x0, 0, _tMax, _sizeOfRes, OdeFunction));
}
