module Dls:sig
..end
Direct Linear Solvers operating on dense, banded, and sparse matrices.
include Sundials_LinearSolver.Direct
type'm
jac_fn =(Sundials.RealArray.t Kinsol.double, Sundials.RealArray.t)
Kinsol.jacobian_arg -> 'm -> unit
Callback functions that compute dense approximations to a Jacobian
matrix. In the call jac arg jm
, arg
is a Kinsol.jacobian_arg
with two work vectors and the computed Jacobian must be stored
in jm
.
The callback should load the (i,j)
th entry of jm
with
$\partial y_i/\partial y_j$, i.e., the partial derivative of the
i
th equation with respect to the j
th variable, evaluated at the
values of t
and y
obtained from arg
. Only nonzero elements need
be loaded into jm
.
arg
nor the matrix jm
should
be accessed after the function has returned.val solver : ?jac:'m jac_fn ->
('m, Sundials.RealArray.t, [> Nvector_serial.kind ] as 'a, [> `Dls ])
Sundials.LinearSolver.t -> 'a Kinsol.serial_linear_solver
Create a Kinsol-specific linear solver from a Jacobian approximation
function and a generic direct linear solver.
The Jacobian approximation function is optional for dense and banded
solvers (if not given an internal difference quotient approximation is
used), but must be provided for other solvers (or Invalid_argument
is
raised).
val get_work_space : [> Nvector_serial.kind ] Kinsol.serial_session -> int * int
Returns the sizes of the real and integer workspaces used by a direct linear solver.
real_size
, integer_size
)val get_num_jac_evals : [> Nvector_serial.kind ] Kinsol.serial_session -> int
Returns the number of calls made by a direct linear solver to the Jacobian approximation function.
val get_num_lin_func_evals : [> Nvector_serial.kind ] Kinsol.serial_session -> int
Returns the number of calls made by a direct linear solver to the user system function for computing the difference quotient approximation to the Jacobian.