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diff scripts/ode/private/runge_kutta_23s.m @ 30893:e1788b1a315f

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maint: Use "fcn" as preferred abbreviation for "function" in m-files. * accumarray.m, accumdim.m, quadl.m, quadv.m, randi.m, structfun.m, __is_function__.m, uigetfile.m, uimenu.m, uiputfile.m, doc_cache_create.m, colorspace_conversion_input_check.m, imageIO.m, argnames.m, vectorize.m, vectorize.m, normest1.m, inputname.m, nthargout.m, display_info_file.m, decic.m, ode15i.m, ode15s.m, ode23.m, ode23s.m, ode45.m, odeset.m, check_default_input.m, integrate_adaptive.m, ode_event_handler.m, runge_kutta_23.m, runge_kutta_23s.m, runge_kutta_45_dorpri.m, runge_kutta_interpolate.m, starting_stepsize.m, __all_opts__.m, fminbnd.m, fminsearch.m, fminunc.m, fsolve.m, fzero.m, sqp.m, fplot.m, plotyy.m, __bar__.m, __ezplot__.m, flat_entry.html, profexport.m, movfun.m, bicg.m, bicgstab.m, cgs.m, eigs.m, gmres.m, pcg.m, __alltohandles__.m, __sprand__.m, qmr.m, tfqmr.m, dump_demos.m: Replace "func", "fun", "fn" in documentation and variable names with "fcn".
author Rik <rik@octave.org>
date Mon, 04 Apr 2022 18:14:56 -0700
parents 796f54d4ddbf
children 597f3ee61a48
line wrap: on
line diff
--- a/scripts/ode/private/runge_kutta_23s.m	Mon Apr 04 11:22:26 2022 -0700
+++ b/scripts/ode/private/runge_kutta_23s.m	Mon Apr 04 18:14:56 2022 -0700
@@ -24,10 +24,10 @@
 ########################################################################
 
 ## -*- texinfo -*-
-## @deftypefn  {} {[@var{t_next}, @var{x_next}] =} runge_kutta_23s (@var{fun}, @var{t}, @var{x}, @var{dt})
-## @deftypefnx {} {[@var{t_next}, @var{x_next}] =} runge_kutta_23s (@var{fun}, @var{t}, @var{x}, @var{dt}, @var{options})
-## @deftypefnx {} {[@var{t_next}, @var{x_next}] =} runge_kutta_23s (@var{fun}, @var{t}, @var{x}, @var{dt}, @var{options}, @var{k_vals})
-## @deftypefnx {} {[@var{t_next}, @var{x_next}] =} runge_kutta_23s (@var{fun}, @var{t}, @var{x}, @var{dt}, @var{options}, @var{k_vals}, @var{t_next})
+## @deftypefn  {} {[@var{t_next}, @var{x_next}] =} runge_kutta_23s (@var{fcn}, @var{t}, @var{x}, @var{dt})
+## @deftypefnx {} {[@var{t_next}, @var{x_next}] =} runge_kutta_23s (@var{fcn}, @var{t}, @var{x}, @var{dt}, @var{options})
+## @deftypefnx {} {[@var{t_next}, @var{x_next}] =} runge_kutta_23s (@var{fcn}, @var{t}, @var{x}, @var{dt}, @var{options}, @var{k_vals})
+## @deftypefnx {} {[@var{t_next}, @var{x_next}] =} runge_kutta_23s (@var{fcn}, @var{t}, @var{x}, @var{dt}, @var{options}, @var{k_vals}, @var{t_next})
 ## @deftypefnx {} {[@var{t_next}, @var{x_next}, @var{x_est}] =} runge_kutta_23s (@dots{})
 ## @deftypefnx {} {[@var{t_next}, @var{x_next}, @var{x_est}, @var{k_vals_out}] =} runge_kutta_23s (@dots{})
 ##
@@ -50,7 +50,7 @@
 ## The optional fourth argument @var{options} specifies options for the ODE
 ## solver.  It is a structure generated by @code{odeset}.  In particular it
 ## contains the field @var{funarguments} with the optional arguments to be used
-## in the evaluation of @var{fun}.
+## in the evaluation of @var{fcn}.
 ##
 ## The optional fifth argument @var{k_vals_in} contains the Runge-Kutta
 ## evaluations of the previous step to use in a FSAL scheme.
@@ -67,7 +67,7 @@
 ## @seealso{runge_kutta_23}
 ## @end deftypefn
 
-function [t_next, x_next, x_est, k] = runge_kutta_23s (fun, t, x, dt,
+function [t_next, x_next, x_est, k] = runge_kutta_23s (fcn, t, x, dt,
                                                        options = [],
                                                        k_vals = [],
                                                        t_next = t + dt)
@@ -83,14 +83,14 @@
     args = {};
   endif
 
-  jacfun = false;
+  jacfcn = false;
   jacmat = false;
   if (! isempty (options.Jacobian))
     if (ischar (options.Jacobian))
-      jacfun = true;
+      jacfcn = true;
       jac = str2fun (options.Jacobian);
     elseif (is_function_handle (options.Jacobian))
-      jacfun = true;
+      jacfcn = true;
       jac = options.Jacobian;
     elseif (ismatrix (options.Jacobian))
       jacmat = true;
@@ -110,15 +110,15 @@
   ## Jacobian matrix, dfxpdp
   if (jacmat)
     J = jac;
-  elseif (jacfun)
+  elseif (jacfcn)
     J = jac (t, x);
   elseif (! jacpat)
-    J = __dfxpdp__ (x, @(a) feval (fun, t, a, args{:}), options.RelTol);
+    J = __dfxpdp__ (x, @(a) feval (fcn, t, a, args{:}), options.RelTol);
   elseif (jacpat)
-    J = __dfxpdp__ (x, @(a) feval (fun, t, a, args{:}), options.RelTol, pattern);
+    J = __dfxpdp__ (x, @(a) feval (fcn, t, a, args{:}), options.RelTol, pattern);
   endif
 
-  T = (feval (fun, t + .1 * dt, x) - feval (fun, t, x, args{:})) / (.1 * dt);
+  T = (feval (fcn, t + .1 * dt, x) - feval (fcn, t, x, args{:})) / (.1 * dt);
 
   ## Wolfbrandt coefficient
   if (isempty (options.Mass))
@@ -135,13 +135,13 @@
   endif
 
   ## compute the slopes
-  F(:,1) = feval (fun, t, x, args{:});
+  F(:,1) = feval (fcn, t, x, args{:});
   if (issparse (W))
     k(:,1) = Qw * (Uw \ (Lw \ (Pw * (Rw \ (F(:,1) + dt*d*T)))));
   else
     k(:,1) = Uw \ (Lw \ (Pw * (F(:,1) + dt*d*T)));
   endif
-  F(:,2) = feval (fun, t+a*dt, x+a*dt*k(:,1), args{:});
+  F(:,2) = feval (fcn, t+a*dt, x+a*dt*k(:,1), args{:});
   if (issparse (W))
     k(:,2) = Uw * (Uw \ (Lw \ (Pw * (Rw \ (F(:,2) - M*k(:,1)))))) + k(:,1);
   else
@@ -153,7 +153,7 @@
 
   if (nargout >= 3)
     ## 3rd order, needed in error formula
-    F(:,3) = feval (fun, t+dt, x_next, args{:});
+    F(:,3) = feval (fcn, t+dt, x_next, args{:});
     if (issparse (W))
       k(:,3) = Qw * (Uw \ (Lw \ (Pw * (Rw \ (F(:,3) - e32 * (M*k(:,2) - F(:,2)) - 2 * (M*k(:,1) - F(:,1)) + dt*d*T)))));
     else
@@ -170,12 +170,12 @@
 endfunction
 
 
-function prt = __dfxpdp__ (p, func, rtol, pattern)
+function prt = __dfxpdp__ (p, fcn, rtol, pattern)
 
   ## This subfunction was copied 2011 from the OF "optim" package
   ## "inst/private/__dfdp__.m".
 
-  f = func (p)(:);
+  f = fcn (p)(:);
   m = numel (f);
   n = numel (p);
 
@@ -193,9 +193,9 @@
     prt = pattern;  # initialize Jacobian
     for j = find (any (pattern, 1))
       ps(j) = p1(j);
-      tp1 = func (ps);
+      tp1 = fcn (ps);
       ps(j) = p2(j);
-      tp2 = func (ps);
+      tp2 = fcn (ps);
       pattern_nnz = find (pattern(:, j));
       prt(pattern_nnz, j) = (tp1(pattern_nnz) - tp2(pattern_nnz)) / absdel(j);
       ps(j) = p(j);
@@ -204,9 +204,9 @@
     prt = zeros (m, n); # initialize Jacobian
     for j = 1:n
       ps(j) = p1(j);
-      tp1 = func (ps);
+      tp1 = fcn (ps);
       ps(j) = p2(j);
-      tp2 = func (ps);
+      tp2 = fcn (ps);
       prt(:, j) = (tp1(:) - tp2(:)) / absdel(j);
       ps(j) = p(j);
     endfor