tauodepw
Piecewise Lanczos' tau method for linear ODEs.
Syntax
a = tauodepw(x, y, ode, conditions, varargin)
Description
a = tauodepw(varargin) returns the coefficients, on basis P, of the
(n-1)th degree polinomial approximation yn = Pa, of the
linear differential equation dy/dx=f(t,y). The domain is automatically
decomposed in subintervals and the tau method is applied to each
of these subintervals.
Inputs (required)
x = independent tau variable (itau object).
y = dependent tau variable (dtau oject).
ode = ordinary differential equation (char).
conditions = problem conditions (cell of char).
Input (optional)
pieces = number of steps for piecewise approach (integer).
exact_solution = exact solution (char).
step = step on the x vector to show the results.
precond = preconditioner ('no', 'ilu', 'diag').
for 'ndiad' define: 'numbd' (number od diagonals);
for 'ilu' define: 'milu', 'typeilu', 'droptol',
'thresh' and 'udiag'
solver = linear system solver (check guide).
apsol = boolean varargin to show the graphical solution.
resid = boolean varargin to show the graphical error.
coeff = boolean varargin to show the coefficients a.
spy = boolean varargin to spy the T matrix.
infor = boolean varargin to show infomations at the CLI.
saves = name varargin to save the results at .mat.
Output
a = approximate solution coefficients at basis P.
See also
tau, tausys, tausyspw and schursolver.
a = tauodepw(varargin) returns the coefficients, on basis P, of the (n-1)th degree polinomial approximation yn = Pa, of the linear differential equation dy/dx=f(t,y). The domain is automatically decomposed in subintervals and the tau method is applied to each of these subintervals.
Inputs (required)
x = independent tau variable (itau object).
y = dependent tau variable (dtau oject).
ode = ordinary differential equation (char).
conditions = problem conditions (cell of char).
Input (optional)
pieces = number of steps for piecewise approach (integer).
exact_solution = exact solution (char).
step = step on the x vector to show the results.
precond = preconditioner ('no', 'ilu', 'diag').
for 'ndiad' define: 'numbd' (number od diagonals);
for 'ilu' define: 'milu', 'typeilu', 'droptol',
'thresh' and 'udiag'
solver = linear system solver (check guide).
apsol = boolean varargin to show the graphical solution.
resid = boolean varargin to show the graphical error.
coeff = boolean varargin to show the coefficients a.
spy = boolean varargin to spy the T matrix.
infor = boolean varargin to show infomations at the CLI.
saves = name varargin to save the results at .mat.
Output
a = approximate solution coefficients at basis P.
See also
tau, tausys, tausyspw and schursolver.
pieces = number of steps for piecewise approach (integer).
exact_solution = exact solution (char).
step = step on the x vector to show the results.
precond = preconditioner ('no', 'ilu', 'diag').
for 'ndiad' define: 'numbd' (number od diagonals);
for 'ilu' define: 'milu', 'typeilu', 'droptol',
'thresh' and 'udiag'
solver = linear system solver (check guide).
apsol = boolean varargin to show the graphical solution.
resid = boolean varargin to show the graphical error.
coeff = boolean varargin to show the coefficients a.
spy = boolean varargin to spy the T matrix.
infor = boolean varargin to show infomations at the CLI.
saves = name varargin to save the results at .mat.
Output
a = approximate solution coefficients at basis P.
See also
tau, tausys, tausyspw and schursolver.
tau, tausys, tausyspw and schursolver.