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view scripts/ode/private/integrate_adaptive.m @ 20830:b65888ec820e draft default tip gccjit
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author | Stefan Mahr <dac922@gmx.de> |
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date | Fri, 27 Feb 2015 16:59:36 +0100 |
parents | a260a6acb70f |
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## Copyright (C) 2015, Carlo de Falco ## Copyright (C) 2013, Roberto Porcu' <roberto.porcu@polimi.it> ## ## This file is part of Octave. ## ## Octave is free software; you can redistribute it and/or modify it ## under the terms of the GNU General Public License as published by ## the Free Software Foundation; either version 3 of the License, or (at ## your option) any later version. ## ## Octave is distributed in the hope that it will be useful, but ## WITHOUT ANY WARRANTY; without even the implied warranty of ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU ## General Public License for more details. ## ## You should have received a copy of the GNU General Public License ## along with Octave; see the file COPYING. If not, see ## <http://www.gnu.org/licenses/>. ## -*- texinfo -*- ## @deftypefn {Function File} {[@var{t}, @var{y}] =} integrate_adaptive (@var{@@stepper}, @var{order}, @var{@@fun}, @var{tspan}, @var{x0}, @var{options}) ## ## This function file can be called by an ODE solver function in order to ## integrate the set of ODEs on the interval @var{[t0,t1]} with an ## adaptive timestep. ## ## This function must be called with two output arguments: @var{t} and @var{y}. ## Variable @var{t} is a column vector and contains the time stamps, instead ## @var{y} is a matrix in which each column refers to a different unknown ## of the problem and the rows number is the same of @var{t} rows number so ## that each row of @var{y} contains the values of all unknowns at the time ## value contained in the corresponding row in @var{t}. ## ## The first input argument must be a function_handle or an inline function ## representing the stepper, that is the function responsible for step-by-step ## integration. This function discriminates one method from the others. ## ## The second input argument is the order of the stepper. It is needed ## to compute the adaptive timesteps. ## ## The third input argument is a function_handle or an inline function that ## defines the set of ODE: ## @ifhtml ## @example ## @math{y' = f(t,y)} ## @end example ## @end ifhtml ## @ifnothtml ## @math{y' = f(t,y)}. ## @end ifnothtml ## ## The fourth input argument is the time vector which defines integration ## interval, that is @var{[tspan(1),tspan(end)]} and all the intermediate ## elements are taken as times at which the solution is required. ## ## The fifth argument represents the initial conditions for the ODEs and the ## last input argument contains some options that may be needed for the stepper. ## ## @end deftypefn ## ## @seealso{integrate_const, integrate_n_steps} function solution = integrate_adaptive (stepper, order, func, tspan, x0, options) fixed_times = numel (tspan) > 2; t_new = t_old = t = tspan(1); x_new = x_old = x = x0(:); ## get first initial timestep dt = starting_stepsize (order, func, t, x, options.AbsTol, options.RelTol, options.vnormcontrol); dt = odeget (options, "InitialStep", dt, "fast_not_empty"); dir = odeget (options, "vdirection", [], "fast"); dt = dir * min (abs (dt), options.MaxStep); options.comp = 0.0; ## Factor multiplying the stepsize guess facmin = 0.8; facmax = 1.5; fac = 0.38^(1/(order+1)); # formula taken from Hairer ## Initialize the OutputFcn if (options.vhaveoutputfunction) if (options.vhaveoutputselection) solution.vretout = x(options.OutputSel,end); else solution.vretout = x; endif feval (options.OutputFcn, tspan, solution.vretout, "init", options.vfunarguments{:}); endif ## Initialize the EventFcn if (options.vhaveeventfunction) odepkg_event_handle (options.Events, tspan(end), x, "init", options.vfunarguments{:}); endif if (options.vhavenonnegative) nn = options.NonNegative; endif solution.vcntloop = 2; solution.vcntcycles = 1; solution.vcntsave = 2; solution.vunhandledtermination = true; ireject = 0; k_vals = []; iout = istep = 1; while (dir * t_old < dir * tspan(end)) ## Compute integration step from t_old to t_new = t_old + dt [t_new, options.comp] = kahan (t_old, options.comp, dt); [t_new, x_new, x_est, new_k_vals] = ... stepper (func, t_old, x_old, dt, options, k_vals, t_new); solution.vcntcycles++; if (options.vhavenonnegative) x_new(nn, end) = abs (x_new(nn, end)); x_est(nn, end) = abs (x_est(nn, end)); endif err = AbsRel_Norm (x_new, x_old, options.AbsTol, options.RelTol, options.vnormcontrol, x_est); ## Accepted solution only if err <= 1.0 if (err <= 1) solution.vcntloop++; ireject = 0; ## if output time steps are fixed if (fixed_times) t_caught = find ((dir * tspan(iout:end) > dir * t_old) & (dir * tspan(iout:end) <= dir * t_new)); t_caught = t_caught + iout - 1; if (! isempty (t_caught)) t(t_caught) = tspan(t_caught); iout = max (t_caught); x(:, t_caught) = ... ode_rk_interpolate (order, [t_old t_new], [x_old x_new], tspan(t_caught), new_k_vals, dt, options.vfunarguments{:}); istep++; if (options.vhaveeventfunction) ## Call event on each dense output timestep. ## Stop integration if veventbreak is true break_loop = false; for idenseout = 1:numel (t_caught) id = t_caught(idenseout); td = t(id); solution.vevent = ... odepkg_event_handle (options.Events, t(id), x(:, id), [], options.vfunarguments{:}); if (! isempty (solution.vevent{1}) && solution.vevent{1} == 1) t(id) = solution.vevent{3}(end); t = t(1:id); x(:, id) = solution.vevent{4}(end, :).'; x = x(:,1:id); solution.vunhandledtermination = false; break_loop = true; break; endif endfor if (break_loop) break; endif endif ## Call plot. Stop integration if plot function ## returns true. if (options.vhaveoutputfunction) vcnt = options.Refine + 1; vapproxtime = linspace (t_old, t_new, vcnt); vapproxvals = interp1 ([t_old, t(t_caught), t_new], [x_old, x(:, t_caught), x_new] .', vapproxtime, 'linear') .'; if (options.vhaveoutputselection) vapproxvals = vapproxvals(options.OutputSel, :); endif for ii = 1:numel (vapproxtime) vpltret = feval (options.OutputFcn, vapproxtime(ii), vapproxvals(:, ii), [], options.vfunarguments{:}); endfor if (vpltret) # Leave main loop solution.vunhandledtermination = false; break; endif endif endif else t(++istep) = t_new; x(:, istep) = x_new; iout = istep; ## Call event handler on new timestep. ## Stop integration if veventbreak is true if (options.vhaveeventfunction) solution.vevent = ... odepkg_event_handle (options.Events, t(istep), x(:, istep), [], options.vfunarguments{:}); if (! isempty (solution.vevent{1}) && solution.vevent{1} == 1) t(istep) = solution.vevent{3}(end); x(:, istep) = solution.vevent{4}(end, :).'; solution.vunhandledtermination = false; break; endif endif ## Call plot. Stop integration if plot function ## returns true. if (options.vhaveoutputfunction) vcnt = options.Refine + 1; vapproxtime = linspace (t_old, t_new, vcnt); vapproxvals = interp1 ([t_old, t_new], [x_old, x_new] .', vapproxtime, 'linear') .'; if (options.vhaveoutputselection) vapproxvals = vapproxvals(options.OutputSel, :); endif for ii = 1:numel (vapproxtime) vpltret = feval (options.OutputFcn, vapproxtime(ii), vapproxvals(:, ii), [], options.vfunarguments{:}); endfor if (vpltret) # Leave main loop solution.vunhandledtermination = false; break; endif endif endif ## move to next time-step t_old = t_new; x_old = x_new; k_vals = new_k_vals; solution.vcntloop = solution.vcntloop + 1; vcntiter = 0; else ireject++; ## Stop solving because in the last 5000 steps no successful valid ## value has been found if (ireject >= 5000) error (["integrate_adaptive: Solving has not been successful. ", " The iterative integration loop exited at time", " t = %f before endpoint at tend = %f was reached. ", " This happened because the iterative integration loop", " does not find a valid solution at this time", " stamp. Try to reduce the value of 'InitialStep' and/or", " 'MaxStep' with the command 'odeset'.\n"], t_old, tspan(end)); endif endif ## Compute next timestep, formula taken from Hairer err += eps; # avoid divisions by zero dt *= min (facmax, max (facmin, fac * (1 / err)^(1 / (order + 1)))); dt = dir * min (abs (dt), options.MaxStep); ## make sure we don't go past tpan(end) dt = dir * min (abs (dt), abs (tspan(end) - t_old)); endwhile ## Check if integration of the ode has been successful if (dir * t(end) < dir * tspan(end)) if (solution.vunhandledtermination == true) error ("integrate_adaptive:unexpected_termination", [" Solving has not been successful. The iterative", ... " integration loop exited at time t = %f ", ... " before endpoint at tend = %f was reached. This may", ... " happen if the stepsize grows too small. ", ... " Try to reduce the value of 'InitialStep'", ... " and/or 'MaxStep' with the command 'odeset'.\n"], t(end), tspan(end)); else warning ("integrate_adaptive:unexpected_termination", ["Solver has been stopped by a call of 'break' ", ... " in the main iteration loop at time t = %f before", ... " endpoint at tend = %f was reached. This may", ... " happen because the @odeplot function", ... " returned 'true' or the @event function returned", ... " 'true'.\n"], t(end), tspan(end)); endif endif ## Set up return structure solution.t = t(:); solution.x = x.'; endfunction