Functions
CASADI_EXPORT Function	casadi::rootfinder (const std::string &name, const std::string &solver, const SXDict &rfp, const Dict &opts=Dict())

CASADI_EXPORT Function	casadi::rootfinder (const std::string &name, const std::string &solver, const MXDict &rfp, const Dict &opts=Dict())

CASADI_EXPORT Function	casadi::rootfinder (const std::string &name, const std::string &solver, const Function &f, const Dict &opts=Dict())

CASADI_EXPORT std::vector< std::string >	casadi::rootfinder_in ()
	Get the rootfinder input scheme. More...

CASADI_EXPORT std::vector< std::string >	casadi::rootfinder_out ()
	Get the rootfinder output scheme. More...

CASADI_EXPORT std::string	casadi::rootfinder_in (casadi_int ind)
	Get the name of a rootfinder input by index. More...

CASADI_EXPORT std::string	casadi::rootfinder_out (casadi_int ind)
	Get the name of a rootfinder output by index. More...

CASADI_EXPORT casadi_int	casadi::rootfinder_n_in ()
	Number of rootfinder inputs. More...

CASADI_EXPORT casadi_int	casadi::rootfinder_n_out ()
	Number of rootfinder outputs. More...

CASADI_EXPORT std::vector< std::string >	casadi::rootfinder_options (const std::string &name)
	Get all options of a rootfinder plugin. More...

CASADI_EXPORT std::string	casadi::rootfinder_option_type (const std::string &name, const std::string &op)
	Get the type of an option of a rootfinder plugin. More...

CASADI_EXPORT std::string	casadi::rootfinder_option_info (const std::string &name, const std::string &op)
	Get the documentation string of an option of a rootfinder plugin. More...

CASADI_EXPORT bool	casadi::has_rootfinder (const std::string &name)
	Check if a rootfinder plugin is available. More...

CASADI_EXPORT void	casadi::load_rootfinder (const std::string &name)
	Explicitly load a rootfinder plugin. More...

CASADI_EXPORT std::string	casadi::doc_rootfinder (const std::string &name)
	Get the documentation string of a rootfinder plugin. More...

Detailed Description

Create a solver for rootfinding problems

Returns a Function that solves a system of nonlinear equations g(x, p) = 0 for x, given the parameters p and an initial guess for x. The problem is given as a dictionary with fields "x" (unknowns, dense column vector), "g" (residual, dense column vector of the same size) and optionally "p" (parameters); any other field name is an error. The returned Function has inputs x0 (the guess) and p, and output x (see rootfinder_in and rootfinder_out). Omitted inputs are zero.

More generally, the problem is given as a Function [y0, y1, ..., yi, ..., yn] = F(x0, x1, ..., xj, ..., xm) where input xj is unknown and output yi is the residual that must be zero. The result is [y0, y1, ..., xj, ..., yn] = G(x0, x1, ..., xj_guess, ..., xm): the unknown input is replaced by a guess (its name gets a "0" suffix) and the residual output is replaced by the solution (named like the unknown input); the other inputs and outputs are passed through. By default j = 0 and i = 0; options "implicit_input" and "implicit_output" select other indices. xj and yi must be dense column vectors of the same size and d(yi)/d(xj) must be structurally and numerically invertible: a structurally rank-deficient Jacobian is an error at construction, a singular one makes the plugin fail.

The call can be embedded in an MX expression and differentiated: derivatives follow from the implicit function theorem, using the linear solver chosen with "linear_solver". "error_on_fail" defaults to true: a solve that does not converge raises; with false the last iterate is returned and stats() reports "success" and "return_status".

Options common to all plugins (the plugin options follow in the tables below):

"implicit_input", "implicit_output": indices j and i above (default 0).
"linear_solver", "linear_solver_options": Linsol plugin for the Newton steps and the sensitivities (default "qr").
"jacobian_function": user-supplied Function for d(yi)/d(xj) (generated by default).
"constraints": list with one entry per unknown, 0 (default) for no constraint, 1 for >= 0, -1 for <= 0, 2 for > 0, -2 for < 0; only honored by plugins that support it (e.g. kinsol), ignored by newton.
"expand", "print_time", "verbose", "common_options", "specific_options": as for nlpsol.

* >>> x = SX.sym("x"); p = SX.sym("p")
* >>> G = rootfinder("G", "newton", {"x": x, "p": p, "g": x**2 - p})
* >>> G
* Function(G:(x0,p)->(x) Newton)
* >>> G(x0=1, p=2)["x"], G(1, 2)
* (DM(1.4142), DM(1.4142))
* >>> G.stats()["success"], G.stats()["return_status"]
* (True, 'success')
* >>> pm = MX.sym("p")
* >>> dxdp = Function("dxdp", [pm], [jacobian(G(x0=1, p=pm)["x"], pm)])
* >>> dxdp(4)
* DM(0.25)
* >>> f = Function("f", [x, p], [x**2 - p, 3*x], ["x", "p"], ["g", "h"])
* >>> G = rootfinder("G", "newton", f)
* >>> G
* Function(G:(x0,p)->(x,h) Newton)
* >>> G(x0=1, p=4)
* {'h': DM(6), 'x': DM(2)}
* >>> f = Function("f", [p, x], [3*x, x**2 - p], ["p", "x"], ["h", "g"])
* >>> G = rootfinder("G", "newton", f, {"implicit_input": 1, "implicit_output": 1})
* >>> G
* Function(G:(p,x0)->(h,x) Newton)
*

* >> x = SX.sym('x'); p = SX.sym('p');
* >> G = rootfinder('G', 'newton', struct('x', x, 'p', p, 'g', x^2 - p)); disp(G)
* G:(x0,p)->(x) Newton
* >> r = G('x0', 1, 'p', 2); r.x, G(1, 2)
* 1.4142
* 1.4142
* >> st = G.stats(); disp(st.success), disp(st.return_status)
* 1
* success
* >> pm = MX.sym('p'); r = G('x0', 1, 'p', pm);
* >> dxdp = Function('dxdp', {pm}, {jacobian(r.x, pm)}); disp(dxdp(4))
* 0.25
* >> f = Function('f', {x, p}, {x^2 - p, 3*x}, {'x', 'p'}, {'g', 'h'});
* >> G = rootfinder('G', 'newton', f); disp(G)
* G:(x0,p)->(x,h) Newton
* >> r = G('x0', 1, 'p', 4); disp(r.x), disp(r.h)
* 2
* 6
* >> f = Function('f', {p, x}, {3*x, x^2 - p}, {'p', 'x'}, {'h', 'g'});
* >> G = rootfinder('G', 'newton', f, struct('implicit_input', 1, 'implicit_output', 1)); disp(G)
* G:(p,x0)->(h,x) Newton
*

* julia> x = ca.SX.sym("x"); p = ca.SX.sym("p");
* julia> G = ca.rootfinder("G", "newton", Dict("x" => x, "p" => p, "g" => x^2 - p))
* Function(G:(x0,p)->(x) Newton)
* julia> G(x0=1, p=2)["x"], G(1, 2)
* (1.4142, 1.4142)
* julia> ca.stats(G)["success"], ca.stats(G)["return_status"]
* (true, "success")
* julia> pm = ca.MX.sym("p");
* julia> dxdp = ca.Function("dxdp", [pm], [ca.jacobian(G(x0=1, p=pm)["x"], pm)]);
* julia> dxdp(4)
* DM(0.25)
* julia> f = ca.Function("f", [x, p], [x^2 - p, 3*x], ["x", "p"], ["g", "h"]);
* julia> G = ca.rootfinder("G", "newton", f)
* Function(G:(x0,p)->(x,h) Newton)
* julia> G(x0=1, p=4)
* Dict{String, DM} with 2 entries:
*   "h" => 6
*   "x" => 2
* julia> f = ca.Function("f", [p, x], [3*x, x^2 - p], ["p", "x"], ["h", "g"]);
* julia> opts = Dict("implicit_input" => 1, "implicit_output" => 1);
* julia> G = ca.rootfinder("G", "newton", f, opts)
* Function(G:(p,x0)->(h,x) Newton)
*

* >>> x = SX.sym("x"); p = SX.sym("p")
* >>> G = rootfinder("G", "newton", {"x": x, "p": p, "g": x**2 - p}, {"max_iter": 2})
* >>> try:
* ...     G(x0=1, p=2)
* ... except RuntimeError as e:
* ...     print("rootfinder process failed" in str(e))
* True
* >>> opts = {"max_iter": 2, "error_on_fail": False, "print_iteration": False}
* >>> G = rootfinder("G", "newton", {"x": x, "p": p, "g": x**2 - p}, opts)
* >>> G(x0=1, p=2)["x"], G.stats()["return_status"]
* (DM(1.4167), 'max_iteration_reached')
* >>> X = SX.sym("x", 2)
* >>> try:
* ...     rootfinder("G", "newton", {"x": X, "g": vertcat(X[0] - 1, 1)})
* ... except RuntimeError as e:
* ...     print("structurally rank-deficient" in str(e))
* True
* >>> try:
* ...     rootfinder("G", "newton", {"x": X, "g": X[0]})
* ... except RuntimeError as e:
* ...     print("Dimension mismatch" in str(e))
* True
*

* >> x = SX.sym('x'); p = SX.sym('p'); rfp = struct('x', x, 'p', p, 'g', x^2 - p);
* >> G = rootfinder('G', 'newton', rfp, struct('max_iter', 2));
* >> try, G('x0', 1, 'p', 2); catch e, msg = e.message; end
* >> contains(msg, 'rootfinder process failed')
* 1
* >> opts = struct('max_iter', 2, 'error_on_fail', false, 'print_iteration', false);
* >> G = rootfinder('G', 'newton', rfp, opts);
* >> r = G('x0', 1, 'p', 2); st = G.stats(); r.x, st.return_status
* 1.4167
* max_iteration_reached
* >> X = SX.sym('x', 2);
* >> rfp = struct('x', X, 'g', [X(1) - 1; 1]);
* >> try, rootfinder('G', 'newton', rfp); catch e, msg = e.message; end
* >> contains(msg, 'structurally rank-deficient')
* 1
* >> try, rootfinder('G', 'newton', struct('x', X, 'g', X(1))); catch e, msg = e.message; end
* >> contains(msg, 'Dimension mismatch')
* 1
*

* julia> x = ca.SX.sym("x"); p = ca.SX.sym("p");
* julia> rfp = Dict("x" => x, "p" => p, "g" => x^2 - p);
* julia> G = ca.rootfinder("G", "newton", rfp, Dict("max_iter" => 2));
* julia> try
*            G(x0=1, p=2)
*        catch e
*            println(occursin("rootfinder process failed", sprint(showerror, e)))
*        end
* true
* julia> opts = Dict("max_iter" => 2, "error_on_fail" => false, "print_iteration" => false);
* julia> G = ca.rootfinder("G", "newton", rfp, opts);
* julia> G(x0=1, p=2)["x"], ca.stats(G)["return_status"]
* (1.4167, "max_iteration_reached")
* julia> X = ca.SX.sym("x", 2);
* julia> try
*            ca.rootfinder("G", "newton", Dict("x" => X, "g" => [X[1] - 1; 1]))
*        catch e
*            println(occursin("structurally rank-deficient", sprint(showerror, e)))
*        end
* true
* julia> try
*            ca.rootfinder("G", "newton", Dict("x" => X, "g" => X[1]))
*        catch e
*            println(occursin("Dimension mismatch", sprint(showerror, e)))
*        end
* true
*

General information

List of available options
Id	Type	Description	Used in
ad_weight	OT_DOUBLE	Weighting factor for derivative calculation.When there is an option of either using forward or reverse mode directional derivatives, the condition ad_weightnf<=(1-ad_weight)na is used where nf and na are estimates of the number of forward/reverse mode directional derivatives needed. By default, ad_weight is calculated automatically, but this can be overridden by setting this option. In particular, 0 means forcing forward mode and 1 forcing reverse mode. Leave unset for (class specific) heuristics.	casadi::FunctionInternal
ad_weight_sp	OT_DOUBLE	Weighting factor for sparsity pattern calculation calculation.Overrides default behavior. Set to 0 and 1 to force forward and reverse mode respectively. Cf. option "ad_weight". When set to -1, sparsity is completely ignored and dense matrices are used.	casadi::FunctionInternal
always_inline	OT_BOOL	Force inlining.	casadi::FunctionInternal
cache	OT_DICT	Prepopulate the function cache. Default: empty	casadi::FunctionInternal
codegen_options	OT_DICT	Options to be passed to the code generator of jit, e.g. {"stats": true} to record statistics inside the compiled code. Default: none	casadi::FunctionInternal
common_options	OT_DICT	Options for auto-generated functions	casadi::OracleFunction
compiler	OT_STRING	Just-in-time compiler plugin to be used.	casadi::FunctionInternal
constraints	OT_INTVECTOR	Constrain the unknowns. 0 (default): no constraint on ui, 1: ui >= 0.0, -1: ui <= 0.0, 2: ui > 0.0, -2: ui < 0.0.	casadi::Rootfinder
custom_jacobian	OT_FUNCTION	Override CasADi's AD. Use together with 'jac_penalty': 0. Note: Highly experimental. Syntax may break often.	casadi::FunctionInternal
der_options	OT_DICT	Default options to be used to populate forward_options, reverse_options, and jacobian_options before those options are merged in.	casadi::FunctionInternal
derivative_of	OT_FUNCTION	The function is a derivative of another function. The type of derivative (directional derivative, Jacobian) is inferred from the function name.	casadi::FunctionInternal
dump	OT_BOOL	Dump function to file upon first evaluation. [false]	casadi::FunctionInternal
dump_dir	OT_STRING	Directory to dump inputs/outputs and traces to. Make sure the directory exists [.]	casadi::FunctionInternal
dump_format	OT_STRING	Choose file format to dump matrices. See DM.from_file [mtx]	casadi::FunctionInternal
dump_in	OT_BOOL	Dump numerical values of inputs to file (readable with DM.from_file) [default: false] A counter is used to generate unique names. The counter may be reset using reset_dump_count.	casadi::FunctionInternal
dump_out	OT_BOOL	Dump numerical values of outputs to file (readable with DM.from_file) [default: false] A counter is used to generate unique names. The counter may be reset using reset_dump_count.	casadi::FunctionInternal
enable_fd	OT_BOOL	Enable derivative calculation by finite differencing. [default: false]]	casadi::FunctionInternal
enable_forward	OT_BOOL	Enable derivative calculation using generated functions for Jacobian-times-vector products - typically using forward mode AD - if available. [default: true]	casadi::FunctionInternal
enable_jacobian	OT_BOOL	Enable derivative calculation using generated functions for Jacobians of all differentiable outputs with respect to all differentiable inputs - if available. [default: true]	casadi::FunctionInternal
enable_reverse	OT_BOOL	Enable derivative calculation using generated functions for transposed Jacobian-times-vector products - typically using reverse mode AD - if available. [default: true]	casadi::FunctionInternal
error_on_fail	OT_BOOL	Throw exceptions when function evaluation fails (default true).	casadi::ProtoFunction
expand	OT_BOOL	Replace MX with SX expressions in problem formulation [false] This happens before creating derivatives unless indicated by postpone_expand	casadi::OracleFunction
external_transform	OT_VECTORVECTOR	List of external_transform instruction arguments. Default: empty	casadi::FunctionInternal
fd_method	OT_STRING	Method for finite differencing [default 'central']	casadi::FunctionInternal
fd_options	OT_DICT	Options to be passed to the finite difference instance	casadi::FunctionInternal
forward_options	OT_DICT	Options to be passed to a forward mode constructor	casadi::FunctionInternal
gather_stats	OT_BOOL	Deprecated option (ignored): Statistics are now always collected.	casadi::FunctionInternal
implicit_input	OT_INT	Index of the input that corresponds to the actual root-finding	casadi::Rootfinder
implicit_output	OT_INT	Index of the output that corresponds to the actual root-finding	casadi::Rootfinder
inputs_check	OT_BOOL	Throw exceptions when the numerical values of the inputs don't make sense	casadi::FunctionInternal
is_diff_in	OT_BOOLVECTOR	Indicate for each input if it should be differentiable.	casadi::FunctionInternal
is_diff_out	OT_BOOLVECTOR	Indicate for each output if it should be differentiable.	casadi::FunctionInternal
jac_penalty	OT_DOUBLE	When requested for a number of forward/reverse directions, it may be cheaper to compute first the full jacobian and then multiply with seeds, rather than obtain the requested directions in a straightforward manner. Casadi uses a heuristic to decide which is cheaper. A high value of 'jac_penalty' makes it less likely for the heurstic to chose the full Jacobian strategy. The special value -1 indicates never to use the full Jacobian strategy	casadi::FunctionInternal
jacobian_function	OT_FUNCTION	Function object for calculating the Jacobian (autogenerated by default)	casadi::Rootfinder
jacobian_options	OT_DICT	Options to be passed to a Jacobian constructor	casadi::FunctionInternal
jit	OT_BOOL	Use just-in-time compiler to speed up the evaluation	casadi::FunctionInternal
jit_cleanup	OT_BOOL	Cleanup up the temporary source file that jit creates. Default: true	casadi::FunctionInternal
jit_name	OT_STRING	The file name used to write out code. The actual file names used depend on 'jit_temp_suffix' and include extensions. Default: 'jit_tmp'	casadi::FunctionInternal
jit_options	OT_DICT	Options to be passed to the jit compiler.	casadi::FunctionInternal
jit_serialize	OT_STRING	Specify behaviour when serializing a jitted function: SOURCE\|link\|embed.	casadi::FunctionInternal
jit_temp_suffix	OT_BOOL	Use a temporary (seemingly random) filename suffix for generated code and libraries. This is desired for thread-safety. This behaviour may defeat caching compiler wrappers. Default: true	casadi::FunctionInternal
linear_solver	OT_STRING	User-defined linear solver class. Needed for sensitivities.	casadi::Rootfinder
linear_solver_options	OT_DICT	Options to be passed to the linear solver.	casadi::Rootfinder
max_io	OT_INT	Acceptable number of inputs and outputs. Warn if exceeded.	casadi::FunctionInternal
max_num_dir	OT_INT	Specify the maximum number of directions for derivative functions. Overrules the builtin optimized_num_dir.	casadi::FunctionInternal
monitor	OT_STRINGVECTOR	Set of user problem functions to be monitored	casadi::OracleFunction
never_inline	OT_BOOL	Forbid inlining.	casadi::FunctionInternal
post_expand	OT_BOOL	After construction, expand this Function. Default: False	casadi::FunctionInternal
post_expand_options	OT_DICT	Options to be passed to post-construction expansion. Default: empty	casadi::FunctionInternal
postpone_expand	OT_BOOL	When expand is active, postpone it until after creation of derivatives. Default: False	casadi::OracleFunction
print_canonical	OT_BOOL	When printing numerical matrices, use a format that is exact and reproducible in generated C code.	casadi::FunctionInternal
print_in	OT_BOOL	Print numerical values of inputs [default: false]	casadi::FunctionInternal
print_out	OT_BOOL	Print numerical values of outputs [default: false]	casadi::FunctionInternal
print_time	OT_BOOL	print information about execution time. Implies record_time.	casadi::ProtoFunction
record_time	OT_BOOL	record information about execution time, for retrieval with stats().	casadi::ProtoFunction
regularity_check	OT_BOOL	Throw exceptions when NaN or Inf appears during evaluation	casadi::ProtoFunction
reverse_options	OT_DICT	Options to be passed to a reverse mode constructor	casadi::FunctionInternal
show_eval_warnings	OT_BOOL	Show warnings generated from function evaluations [true]	casadi::OracleFunction
specific_options	OT_DICT	Options for specific auto-generated functions, overwriting the defaults from common_options. Nested dictionary.	casadi::OracleFunction
user_data	OT_VOIDPTR	A user-defined field that can be used to identify the function or pass additional information	casadi::FunctionInternal
verbose	OT_BOOL	Verbose evaluation – for debugging	casadi::ProtoFunction

Input scheme: casadi::RootfinderInput (ROOTFINDER_NUM_IN = 2)
Full name	Short	Description
ROOTFINDER_X0	x0	Initial guess for the solution.
ROOTFINDER_P	p	Parameters.

Output scheme: casadi::RootfinderOutput (ROOTFINDER_NUM_OUT = 1)
Full name	Short	Description
ROOTFINDER_X	x	Solution to the system of equations.

List of plugins

- kinsol

- fast_newton

- nlpsol

- newton

Note: some of the plugins in this list might not be available on your system. Also, there might be extra plugins available to you that are not listed here. You can obtain their documentation with Rootfinder.doc("myextraplugin")

kinsol

KINSOL interface from the Sundials suite

Extra doc: https://github.com/casadi/casadi/wiki/L_226

List of available options
Id	Type	Description
abstol	OT_DOUBLE	Stopping criterion tolerance
disable_internal_warnings	OT_BOOL	Disable KINSOL internal warning messages
exact_jacobian	OT_BOOL	Use exact Jacobian information
f_scale	OT_DOUBLEVECTOR	Equation scaling factors
iterative_solver	OT_STRING	gmres\|bcgstab\|tfqmr
linear_solver_type	OT_STRING	dense\|banded\|iterative\|user_defined
lower_bandwidth	OT_INT	Lower bandwidth for banded linear solvers
max_iter	OT_INT	Maximum number of Newton iterations. Putting 0 sets the default value of KinSol.
max_krylov	OT_INT	Maximum Krylov space dimension
pretype	OT_STRING	Type of preconditioner
print_level	OT_INT	Verbosity level
strategy	OT_STRING	Globalization strategy
u_scale	OT_DOUBLEVECTOR	Variable scaling factors
upper_bandwidth	OT_INT	Upper bandwidth for banded linear solvers
use_preconditioner	OT_BOOL	Precondition an iterative solver

fast_newton

Implements simple newton iterations to solve an implicit function.

Extra doc: https://github.com/casadi/casadi/wiki/L_237

List of available options
Id	Type	Description
abstol	OT_DOUBLE	Stopping criterion tolerance on \|\|g\|\|__inf)
abstolStep	OT_DOUBLE	Stopping criterion tolerance on step size
max_iter	OT_INT	Maximum number of Newton iterations to perform before returning.

nlpsol

newton

Implements simple newton iterations to solve an implicit function.

Extra doc: https://github.com/casadi/casadi/wiki/L_236

List of available options
Id	Type	Description
abstol	OT_DOUBLE	Stopping criterion tolerance on max(\|F\|)
abstolStep	OT_DOUBLE	Stopping criterion tolerance on step size
line_search	OT_BOOL	Enable line-search (default: true)
max_iter	OT_INT	Maximum number of Newton iterations to perform before returning.
print_iteration	OT_BOOL	Print information about each iteration

Author: Joel Andersson

Date: 2011-2015

Extra doc: https://github.com/casadi/casadi/wiki/L_21r

Function Documentation

◆ doc_rootfinder()

CASADI_EXPORT std::string casadi::doc_rootfinder ( const std::string & name )

The text includes the plugin-specific option table.

>>> "newton iterations" in doc_rootfinder("newton")
True

>> contains(doc_rootfinder('newton'), 'newton iterations')
1

julia> occursin("newton iterations", ca.doc_rootfinder("newton"))
true

Extra doc: https://github.com/casadi/casadi/wiki/L_2ni

◆ has_rootfinder()

CASADI_EXPORT bool casadi::has_rootfinder ( const std::string & name )

Tries to load the plugin name if it is not loaded yet; false when it is not found.

>>> has_rootfinder("newton"), has_rootfinder("no_such_plugin")
(True, False)

>> has_rootfinder('newton'), has_rootfinder('no_such_plugin')
1
0

julia> ca.has_rootfinder("newton"), ca.has_rootfinder("no_such_plugin")
(true, false)

Extra doc: https://github.com/casadi/casadi/wiki/L_2ng

◆ load_rootfinder()

CASADI_EXPORT void casadi::load_rootfinder ( const std::string & name )

Normally plugins are loaded on first use; this raises an error when the plugin cannot be found.

>>> try:
...     load_rootfinder("no_such_plugin")
... except RuntimeError as e:
...     print("no_such_plugin" in str(e))
True

>> try, load_rootfinder('no_such_plugin'); catch e, msg = e.message; end
>> contains(msg, 'no_such_plugin')
1

julia> try
           ca.load_rootfinder("no_such_plugin")
       catch e
           println(occursin("no_such_plugin", sprint(showerror, e)))
       end
true

Extra doc: https://github.com/casadi/casadi/wiki/L_2nh

◆ rootfinder() [1/3]

CASADI_EXPORT Function casadi::rootfinder	(	const std::string &	name,
		const std::string &	solver,
		const Function &	f,
		const Dict &	opts = `Dict()`
	)

◆ rootfinder() [2/3]

CASADI_EXPORT Function casadi::rootfinder	(	const std::string &	name,
		const std::string &	solver,
		const MXDict &	rfp,
		const Dict &	opts = `Dict()`
	)

◆ rootfinder() [3/3]

CASADI_EXPORT Function casadi::rootfinder	(	const std::string &	name,
		const std::string &	solver,
		const SXDict &	rfp,
		const Dict &	opts = `Dict()`
	)

Examples: solvers/KinsolSolver.py, solvers/NLPImplicitSolver.py, and solvers/NewtonImplicitSolver.py.

◆ rootfinder_in() [1/2]

CASADI_EXPORT std::vector<std::string> casadi::rootfinder_in ( )

Returns the names of the 2 inputs of a Function created by rootfinder from a dictionary, in order: x0, p. A Function created from a general Function keeps that Function's input names, with "0" appended to the unknown.

>>> rootfinder_in()
['x0', 'p']

>> rootfinder_in()
x0
p

julia> ca.rootfinder_in()
2-element Vector{String}:
 "x0"
 "p"

See also: rootfinder_out, rootfinder_n_in

Extra doc: https://github.com/casadi/casadi/wiki/L_1ty

◆ rootfinder_in() [2/2]

CASADI_EXPORT std::string casadi::rootfinder_in ( casadi_int ind )

Parameters

ind	Index in 0..rootfinder_n_in()-1; any other value gives an empty string

>>> rootfinder_in(0), rootfinder_in(1), repr(rootfinder_in(2))
('x0', 'p', "''")

>> rootfinder_in(0), rootfinder_in(1), isempty(rootfinder_in(2))
x0
p
1

julia> ca.rootfinder_in(0), ca.rootfinder_in(1), ca.rootfinder_in(2)
("x0", "p", "")

Extra doc: https://github.com/casadi/casadi/wiki/L_1u0

◆ rootfinder_n_in()

CASADI_EXPORT casadi_int casadi::rootfinder_n_in ( )

>>> rootfinder_n_in()
2

>> rootfinder_n_in()
2

julia> ca.rootfinder_n_in()
2

Extra doc: https://github.com/casadi/casadi/wiki/L_1u2

◆ rootfinder_n_out()

CASADI_EXPORT casadi_int casadi::rootfinder_n_out ( )

>>> rootfinder_n_out()
1

>> rootfinder_n_out()
1

julia> ca.rootfinder_n_out()
1

Extra doc: https://github.com/casadi/casadi/wiki/L_1u3

◆ rootfinder_option_info()

CASADI_EXPORT std::string casadi::rootfinder_option_info	(	const std::string &	name,
		const std::string &	op
	)

Parameters

name	Plugin name
op	Option name; an unknown option raises an error

>>> rootfinder_option_info("newton", "abstol")
'Stopping criterion tolerance on max(|F|)'

>> rootfinder_option_info('newton', 'abstol')
Stopping criterion tolerance on max(|F|)

julia> ca.rootfinder_option_info("newton", "abstol")
"Stopping criterion tolerance on max(|F|)"

Extra doc: https://github.com/casadi/casadi/wiki/L_1u6

◆ rootfinder_option_type()

CASADI_EXPORT std::string casadi::rootfinder_option_type	(	const std::string &	name,
		const std::string &	op
	)

Parameters

name	Plugin name
op	Option name; an unknown option raises an error

Returns: Type name such as "OT_INT", "OT_DOUBLE", "OT_BOOL"

>>> rootfinder_option_type("newton", "max_iter")
'OT_INT'
>>> rootfinder_option_type("newton", "abstol")
'OT_DOUBLE'

>> rootfinder_option_type('newton', 'max_iter')
OT_INT
>> rootfinder_option_type('newton', 'abstol')
OT_DOUBLE

julia> ca.rootfinder_option_type("newton", "max_iter")
"OT_INT"
julia> ca.rootfinder_option_type("newton", "abstol")
"OT_DOUBLE"

Extra doc: https://github.com/casadi/casadi/wiki/L_1u5

◆ rootfinder_options()

CASADI_EXPORT std::vector<std::string> casadi::rootfinder_options ( const std::string & name )

Returns the names of the plugin-specific options only; the options shared by all plugins (e.g. "linear_solver", "error_on_fail") are not included. Raises an error for an unknown plugin.

>>> opts = rootfinder_options("newton")
>>> "max_iter" in opts, "abstol" in opts, "linear_solver" in opts
(True, True, False)

>> opts = cellstr(rootfinder_options('newton'));
>> ismember({'max_iter', 'abstol', 'linear_solver'}, opts)
1 1 0

julia> opts = ca.rootfinder_options("newton");
julia> "max_iter" in opts, "abstol" in opts, "linear_solver" in opts
(true, true, false)

See also: rootfinder_option_type, rootfinder_option_info

Extra doc: https://github.com/casadi/casadi/wiki/L_1u4

◆ rootfinder_out() [1/2]

CASADI_EXPORT std::vector<std::string> casadi::rootfinder_out ( )

Returns the name of the single output of a Function created by rootfinder from a dictionary: x.

>>> rootfinder_out()
['x']

>> rootfinder_out()
x

julia> ca.rootfinder_out()
1-element Vector{String}:
 "x"

See also: rootfinder_in, rootfinder_n_out

Extra doc: https://github.com/casadi/casadi/wiki/L_1tz

◆ rootfinder_out() [2/2]

CASADI_EXPORT std::string casadi::rootfinder_out ( casadi_int ind )

Parameters

ind	Index in 0..rootfinder_n_out()-1; any other value gives an empty string

>>> rootfinder_out(0), repr(rootfinder_out(1))
('x', "''")

>> rootfinder_out(0), isempty(rootfinder_out(1))
x
1

julia> ca.rootfinder_out(0), ca.rootfinder_out(1)
("x", "")

Extra doc: https://github.com/casadi/casadi/wiki/L_1u1

Functions

Detailed Description

General information

List of plugins

kinsol

fast_newton

nlpsol

newton

Function Documentation

◆ doc_rootfinder()

◆ has_rootfinder()

◆ load_rootfinder()

◆ rootfinder() [1/3]

◆ rootfinder() [2/3]

◆ rootfinder() [3/3]

◆ rootfinder_in() [1/2]

◆ rootfinder_in() [2/2]

◆ rootfinder_n_in()

◆ rootfinder_n_out()

◆ rootfinder_option_info()

◆ rootfinder_option_type()

◆ rootfinder_options()

◆ rootfinder_out() [1/2]

◆ rootfinder_out() [2/2]