Private API

DOCP_Hessian_pattern(
    docp::CTDirect.DOCP{D<:CTDirect.Discretization}
) -> SparseArrays.SparseMatrixCSC{Bool, Int64}

Build sparsity pattern for Hessian of Lagrangian (to be implemented for each discretization scheme)

DOCP_Hessian_pattern(
    docp::CTDirect.DOCP{CTDirect.Euler}
) -> SparseArrays.SparseMatrixCSC{Bool, Int64}

Build sparsity pattern for Hessian of Lagrangian

DOCP_Hessian_pattern(
    docp::CTDirect.DOCP{<:CTDirect.GenericIRK}
) -> SparseArrays.SparseMatrixCSC{Bool, Int64}

Build sparsity pattern for Hessian of Lagrangian

DOCP_Hessian_pattern(
    docp::CTDirect.DOCP{CTDirect.Midpoint}
) -> SparseArrays.SparseMatrixCSC{Bool, Int64}

Build sparsity pattern for Hessian of Lagrangian

DOCP_Hessian_pattern(
    docp::CTDirect.DOCP{CTDirect.Trapeze}
) -> SparseArrays.SparseMatrixCSC{Bool, Int64}

Build sparsity pattern for Hessian of Lagrangian

DOCP_Jacobian_pattern(
    docp::CTDirect.DOCP{D<:CTDirect.Discretization}
) -> SparseArrays.SparseMatrixCSC{Bool, Int64}

Build sparsity pattern for Jacobian of constraints (to be implemented for each discretization scheme)

DOCP_Jacobian_pattern(
    docp::CTDirect.DOCP{CTDirect.Euler}
) -> SparseArrays.SparseMatrixCSC{Bool, Int64}

Build sparsity pattern for Jacobian of constraints

DOCP_Jacobian_pattern(
    docp::CTDirect.DOCP{<:CTDirect.GenericIRK}
) -> SparseArrays.SparseMatrixCSC{Bool, Int64}

Build sparsity pattern for Jacobian of constraints

DOCP_Jacobian_pattern(
    docp::CTDirect.DOCP{CTDirect.Midpoint}
) -> SparseArrays.SparseMatrixCSC{Bool, Int64}

Build sparsity pattern for Jacobian of constraints

DOCP_Jacobian_pattern(
    docp::CTDirect.DOCP{CTDirect.Trapeze}
) -> SparseArrays.SparseMatrixCSC{Bool, Int64}

Build sparsity pattern for Jacobian of constraints

Implicit Midpoint discretization, formulated as a generic IRK (ie Gauss Legendre 1) For testing purpose only, use :midpoint instead (cf midpoint.jl) !

Gauss Legendre 2 discretization, formulated as a generic IRK

Gauss Legendre 3 discretization, formulated as a generic IRK

IRK_dims(
    dim_NLP_steps,
    dim_NLP_x,
    dim_NLP_u,
    dim_NLP_v,
    dim_path_cons,
    dim_boundary_cons,
    stage
) -> NTuple{5, Any}

Return the dimension of the NLP variables and constraints for a generic IRK discretizion, with the control taken constant per step (ie not distinct controls at time stages)

add_nonzero_block!(M, i_start, i_end, j_start, j_end; sym)

Add block of nonzeros elements to a sparsity pattern Format: boolean matrix (M) or index vectors (Is, Js) Includes a more compact method for single element case Option to add the symmetric block also (eg for Hessian) Note: independent from discretization scheme

get_OCP_control_at_time_step(
    xu,
    docp::CTDirect.DOCP,
    i
) -> Any

Retrieve control variables at given time step from the NLP variables. Convention: 1 <= i <= dimNLPsteps(+1), with convention u(tf) = U_N Vector output

get_OCP_control_at_time_step(
    xu,
    docp::CTDirect.DOCP{CTDirect.Euler},
    i
) -> Any

Retrieve control variables at given time step from the NLP variables. Convention: see above for explicit / implicit versions Vector output

get_OCP_state_at_time_step(
    xu,
    docp::CTDirect.DOCP,
    i
) -> Any

Retrieve state variables at given time step from the NLP variables. Convention: 1 <= i <= dimNLPsteps+1 Vector output

get_OCP_variable(xu, docp::CTDirect.DOCP) -> Any

Retrieve optimization variables from the NLP variables. Convention: stored at the end, hence not dependent on the discretization method Vector output

get_stagevars_at_time_step(
    xu,
    docp::CTDirect.DOCP,
    i,
    j
) -> Any

Retrieve stage variables at given time step/stage from the NLP variables. Convention: 1 <= i <= dimNLPsteps(+1), 1 <= j <= s Vector output Note that passing correct indices is up to the caller, no checks are made here.

runningCost(
    docp::CTDirect.DOCP{D<:CTDirect.Discretization},
    xu,
    v,
    time_grid
) -> Any

Compute the running cost (must be implemented for each discretization scheme)

runningCost(
    docp::CTDirect.DOCP{CTDirect.Euler},
    xu,
    v,
    time_grid
) -> Any

Compute the running cost

runningCost(
    docp::CTDirect.DOCP{<:CTDirect.GenericIRK},
    xu,
    v,
    time_grid
) -> Any

Compute the running cost

runningCost(
    docp::CTDirect.DOCP{CTDirect.Midpoint},
    xu,
    v,
    time_grid
) -> Any

Compute the running cost

runningCost(
    docp::CTDirect.DOCP{CTDirect.Trapeze},
    xu,
    v,
    time_grid
) -> Any

Compute the running cost

setStepConstraints!(
    docp::CTDirect.DOCP{CTDirect.Euler},
    c,
    xu,
    v,
    time_grid,
    i,
    work
) -> Any

Set the constraints corresponding to the state equation Convention: 1 <= i <= dimNLPsteps+1

setStepConstraints!(
    docp::CTDirect.DOCP{<:CTDirect.GenericIRK},
    c,
    xu,
    v,
    time_grid,
    i,
    work
) -> Any

Set the constraints corresponding to the state equation Convention: 1 <= i <= dimNLPsteps (+1)

setStepConstraints!(
    docp::CTDirect.DOCP{CTDirect.Midpoint},
    c,
    xu,
    v,
    time_grid,
    i,
    work
) -> Any

Set the constraints corresponding to the state equation Convention: 1 <= i <= dimNLPsteps+1

setStepConstraints!(
    docp::CTDirect.DOCP{CTDirect.Trapeze},
    c,
    xu,
    v,
    time_grid,
    i,
    work
) -> Any

Set the constraints corresponding to the state equation Convention: 1 <= i <= dimNLPsteps+1

setWorkArray(docp::CTDirect.DOCP, xu, time_grid, v) -> Any

Set work array for all dynamics evaluations

setWorkArray(
    docp::CTDirect.DOCP{CTDirect.Euler},
    xu,
    time_grid,
    v
) -> Any

Set work array for all dynamics and lagrange cost evaluations

setWorkArray(
    docp::CTDirect.DOCP{<:CTDirect.GenericIRK},
    xu,
    time_grid,
    v
) -> Any

Set work array for all dynamics and lagrange cost evaluations

setWorkArray(
    docp::CTDirect.DOCP{CTDirect.Midpoint},
    xu,
    time_grid,
    v
) -> Any

Set work array for all dynamics cost evaluations

setWorkArray(
    docp::CTDirect.DOCP{CTDirect.Trapeze},
    xu,
    time_grid,
    v
) -> Any

Set work array for all dynamics evaluations

set_control_at_time_step!(
    xu,
    u_init,
    docp::CTDirect.DOCP,
    i
)

Set initial guess for control variables at given time step Convention: 1 <= i <= dimNLPsteps(+1)

set_optim_variable!(xu, v_init, docp) -> Any

Set optimization variables in the NLP variables (for initial guess)

set_state_at_time_step!(xu, x_init, docp::CTDirect.DOCP, i)

Set initial guess for state variables at given time step Convention: 1 <= i <= dimNLPsteps+1