overview of functions provided

// typedefs

typedef float spc_;
typedef double rpc_;
typedef int ipc_;

// structs

struct trb_control_type;
struct trb_inform_type;
struct trb_time_type;

// function calls

void trb_initialize(void **data, struct trb_control_type* control, ipc_ *status);
void trb_read_specfile(struct trb_control_type* control, const char specfile[]);

void trb_import(
    struct trb_control_type* control,
    void **data,
    ipc_ *status,
    ipc_ n,
    const rpc_ x_l[],
    const rpc_ x_u[],
    const char H_type[],
    ipc_ ne,
    const ipc_ H_row[],
    const ipc_ H_col[],
    const ipc_ H_ptr[]
);

void trb_reset_control(
    struct trb_control_type* control,
    void **data,
    ipc_ *status
);

void trb_solve_with_mat(
    void **data,
    void *userdata,
    ipc_ *status,
    ipc_ n,
    rpc_ x[],
    rpc_ g[],
    ipc_ ne,
    ipc_(*)(ipc_, const rpc_[], rpc_*, const void*) eval_f,
    ipc_(*)(ipc_, const rpc_[], rpc_[], const void*) eval_g,
    ipc_(*)(ipc_, ipc_, const rpc_[], rpc_[], const void*) eval_h,
    ipc_(*)(ipc_, const rpc_[], rpc_[], const rpc_[], const void*) eval_prec
);

void trb_solve_without_mat(
    void **data,
    void *userdata,
    ipc_ *status,
    ipc_ n,
    rpc_ x[],
    rpc_ g[],
    ipc_(*)(ipc_, const rpc_[], rpc_*, const void*) eval_f,
    ipc_(*)(ipc_, const rpc_[], rpc_[], const void*) eval_g,
    ipc_(*)(ipc_, const rpc_[], rpc_[], const rpc_[], bool, const void*) eval_hprod,
    ipc_(*)(ipc_, const rpc_[], ipc_, const int[], const rpc_[], int*, int[], rpc_[], bool, const void*) eval_shprod,
    ipc_(*)(ipc_, const rpc_[], rpc_[], const rpc_[], const void*) eval_prec
);

void trb_solve_reverse_with_mat(
    void **data,
    ipc_ *status,
    ipc_ *eval_status,
    ipc_ n,
    rpc_ x[],
    rpc_ f,
    rpc_ g[],
    ipc_ ne,
    rpc_ H_val[],
    const rpc_ u[],
    rpc_ v[]
);

void trb_solve_reverse_without_mat(
    void **data,
    ipc_ *status,
    ipc_ *eval_status,
    ipc_ n,
    rpc_ x[],
    rpc_ f,
    rpc_ g[],
    rpc_ u[],
    rpc_ v[],
    ipc_ index_nz_v[],
    ipc_ *nnz_v,
    const ipc_ index_nz_u[],
    ipc_ nnz_u
);

void trb_information(void **data, struct trb_inform_type* inform, ipc_ *status);

void trb_terminate(
    void **data,
    struct trb_control_type* control,
    struct trb_inform_type* inform
);

typedefs

typedef float spc_

spc_ is real single precision

typedef double rpc_

rpc_ is the real working precision used, but may be changed to float by defining the preprocessor variable REAL_32 or (if supported) to __real128 using the variable REAL_128.

typedef int ipc_

ipc_ is the default integer word length used, but may be changed to int64_t by defining the preprocessor variable INTEGER_64.

function calls

void trb_initialize(void **data, struct trb_control_type* control, ipc_ *status)

Set default control values and initialize private data

Parameters:

data	holds private internal data
control	is a struct containing control information (see trb_control_type)
status	is a scalar variable of type ipc_, that gives the exit status from the package. Possible values are (currently): 0 The initialization was successful.

void trb_read_specfile(struct trb_control_type* control, const char specfile[])

Read the content of a specification file, and assign values associated with given keywords to the corresponding control parameters. An in-depth discussion of specification files is available, and a detailed list of keywords with associated default values is provided in $GALAHAD/src/trb/TRB.template. See also Table 2.1 in the Fortran documentation provided in $GALAHAD/doc/trb.pdf for a list of how these keywords relate to the components of the control structure.

Parameters:

control	is a struct containing control information (see trb_control_type)
specfile	is a character string containing the name of the specification file

void trb_import(
    struct trb_control_type* control,
    void **data,
    ipc_ *status,
    ipc_ n,
    const rpc_ x_l[],
    const rpc_ x_u[],
    const char H_type[],
    ipc_ ne,
    const ipc_ H_row[],
    const ipc_ H_col[],
    const ipc_ H_ptr[]
)

Import problem data into internal storage prior to solution.

Parameters:

control	is a struct whose members provide control paramters for the remaining prcedures (see trb_control_type)
data	holds private internal data
status	is a scalar variable of type ipc_, that gives the exit status from the package. Possible values are: 1 The import was successful, and the package is ready for the solve phase -1 An allocation error occurred. A message indicating the offending array is written on unit control.error, and the returned allocation status and a string containing the name of the offending array are held in inform.alloc_status and inform.bad_alloc respectively. -2 A deallocation error occurred. A message indicating the offending array is written on unit control.error and the returned allocation status and a string containing the name of the offending array are held in inform.alloc_status and inform.bad_alloc respectively. -3 The restriction n > 0 or requirement that type contains its relevant string ‘dense’, ‘coordinate’, ‘sparse_by_rows’, ‘diagonal’ or ‘absent’ has been violated.
n	is a scalar variable of type ipc_, that holds the number of variables.
x_l	is a one-dimensional array of size n and type rpc_, that holds the values $x^l$ of the lower bounds on the optimization variables $x$. The j-th component of x_l, $j=0,\dots ,n-1$, contains $x_j^l$.
x_u	is a one-dimensional array of size n and type rpc_, that holds the values $x^u$ of the upper bounds on the optimization variables $x$. The j-th component of x_u, $j=0,\dots ,n-1$, contains $x_j^u$.
H_type	is a one-dimensional array of type char that specifies the symmetric storage scheme used for the Hessian. It should be one of ‘coordinate’, ‘sparse_by_rows’, ‘dense’, ‘diagonal’ or ‘absent’, the latter if access to the Hessian is via matrix-vector products; lower or upper case variants are allowed.
ne	is a scalar variable of type ipc_, that holds the number of entries in the lower triangular part of H in the sparse co-ordinate storage scheme. It need not be set for any of the other three schemes.
H_row	is a one-dimensional array of size ne and type ipc_, that holds the row indices of the lower triangular part of H in the sparse co-ordinate storage scheme. It need not be set for any of the other three schemes, and in this case can be NULL
H_col	is a one-dimensional array of size ne and type ipc_, that holds the column indices of the lower triangular part of H in either the sparse co-ordinate, or the sparse row-wise storage scheme. It need not be set when the dense or diagonal storage schemes are used, and in this case can be NULL
H_ptr	is a one-dimensional array of size n+1 and type ipc_, that holds the starting position of each row of the lower triangular part of H, as well as the total number of entries, in the sparse row-wise storage scheme. It need not be set when the other schemes are used, and in this case can be NULL

void trb_reset_control(
    struct trb_control_type* control,
    void **data,
    ipc_ *status
)

Reset control parameters after import if required.

Parameters:

control	is a struct whose members provide control paramters for the remaining prcedures (see trb_control_type)
data	holds private internal data
status	is a scalar variable of type ipc_, that gives the exit status from the package. Possible values are: 1 The import was successful, and the package is ready for the solve phase

void trb_solve_with_mat(
    void **data,
    void *userdata,
    ipc_ *status,
    ipc_ n,
    rpc_ x[],
    rpc_ g[],
    ipc_ ne,
    ipc_(*)(ipc_, const rpc_[], rpc_*, const void*) eval_f,
    ipc_(*)(ipc_, const rpc_[], rpc_[], const void*) eval_g,
    ipc_(*)(ipc_, ipc_, const rpc_[], rpc_[], const void*) eval_h,
    ipc_(*)(ipc_, const rpc_[], rpc_[], const rpc_[], const void*) eval_prec
)

Find a local minimizer of a given function subject to simple bounds on the variables using a trust-region method.

This call is for the case where $H={\mathrm{\nabla }}_{xx}f(x)$ is provided specifically, and all function/derivative information is available by function calls.

Parameters:

data	holds private internal data
userdata	is a structure that allows data to be passed into the function and derivative evaluation programs.
status	is a scalar variable of type ipc_, that gives the entry and exit status from the package. On initial entry, status must be set to 1. Possible exit values are: 0 The run was successful -1 An allocation error occurred. A message indicating the offending array is written on unit control.error, and the returned allocation status and a string containing the name of the offending array are held in inform.alloc_status and inform.bad_alloc respectively. -2 A deallocation error occurred. A message indicating the offending array is written on unit control.error and the returned allocation status and a string containing the name of the offending array are held in inform.alloc_status and inform.bad_alloc respectively. -3 The restriction n > 0 or requirement that type contains its relevant string ‘dense’, ‘coordinate’, ‘sparse_by_rows’, ‘diagonal’ or ‘absent’ has been violated. -7 The objective function appears to be unbounded from below -9 The analysis phase of the factorization failed; the return status from the factorization package is given in the component inform.factor_status -10 The factorization failed; the return status from the factorization package is given in the component inform.factor_status. -11 The solution of a set of linear equations using factors from the factorization package failed; the return status from the factorization package is given in the component inform.factor_status. -16 The problem is so ill-conditioned that further progress is impossible. -18 Too many iterations have been performed. This may happen if control.maxit is too small, but may also be symptomatic of a badly scaled problem. -19 The CPU time limit has been reached. This may happen if control.cpu_time_limit is too small, but may also be symptomatic of a badly scaled problem. -82 The user has forced termination of solver by removing the file named control.alive_file from unit unit control.alive_unit.
n	is a scalar variable of type ipc_, that holds the number of variables
x	is a one-dimensional array of size n and type rpc_, that holds the values $x$ of the optimization variables. The j-th component of x, j = 0, … , n-1, contains $x_j$.
g	is a one-dimensional array of size n and type rpc_, that holds the gradient $g={\mathrm{\nabla }}_{x}f(x)$ of the objective function. The j-th component of g, j = 0, … , n-1, contains $g_j$.
ne	is a scalar variable of type ipc_, that holds the number of entries in the lower triangular part of the Hessian matrix $H$.
eval_f	is a user-supplied function that must have the following signature: ipc_ eval_f( ipc_ n, const rpc_ x[], rpc_ *f, const void *userdata ) The value of the objective function $f(x)$ evaluated at x= $x$ must be assigned to f, and the function return value set to 0. If the evaluation is impossible at x, return should be set to a nonzero value. Data may be passed into eval_f via the structure userdata.
eval_g	is a user-supplied function that must have the following signature: ipc_ eval_g( ipc_ n, const rpc_ x[], rpc_ g[], const void *userdata ) The components of the gradient $g={\mathrm{\nabla }}_{x}f(x$) of the objective function evaluated at x= $x$ must be assigned to g, and the function return value set to 0. If the evaluation is impossible at x, return should be set to a nonzero value. Data may be passed into eval_g via the structure userdata.
eval_h	is a user-supplied function that must have the following signature: ipc_ eval_h( ipc_ n, ipc_ ne, const rpc_ x[], rpc_ h[], const void *userdata ) The nonzeros of the Hessian $H={\mathrm{\nabla }}_{xx}f(x)$ of the objective function evaluated at x= $x$ must be assigned to h in the same order as presented to trb_import, and the function return value set to 0. If the evaluation is impossible at x, return should be set to a nonzero value. Data may be passed into eval_h via the structure userdata.
eval_prec	is an optional user-supplied function that may be NULL. If non-NULL, it must have the following signature: ipc_ eval_prec( ipc_ n, const rpc_ x[], rpc_ u[], const rpc_ v[], const void *userdata ) The product $u=P(x)v$ of the user’s preconditioner $P(x)$ evaluated at $x$ with the vector v = $v$, the result $u$ must be retured in u, and the function return value set to 0. If the evaluation is impossible at x, return should be set to a nonzero value. Data may be passed into eval_prec via the structure userdata.

void trb_solve_without_mat(
    void **data,
    void *userdata,
    ipc_ *status,
    ipc_ n,
    rpc_ x[],
    rpc_ g[],
    ipc_(*)(ipc_, const rpc_[], rpc_*, const void*) eval_f,
    ipc_(*)(ipc_, const rpc_[], rpc_[], const void*) eval_g,
    ipc_(*)(ipc_, const rpc_[], rpc_[], const rpc_[], bool, const void*) eval_hprod,
    ipc_(*)(ipc_, const rpc_[], ipc_, const int[], const rpc_[], int*, int[], rpc_[], bool, const void*) eval_shprod,
    ipc_(*)(ipc_, const rpc_[], rpc_[], const rpc_[], const void*) eval_prec
)

Find a local minimizer of a given function subject to simple bounds on the variables using a trust-region method.

This call is for the case where access to $H={\mathrm{\nabla }}_{xx}f(x)$ is provided by Hessian-vector products, and all function/derivative information is available by function calls.

ipc_ eval_g( ipc_ n, const rpc_ x[], rpc_ g[], const void *userdata )

The components of the gradient $g={\mathrm{\nabla }}_{x}f(x$) of the objective function evaluated at x= $x$ must be assigned to g, and the function return value set to 0. If the evaluation is impossible at x, return should be set to a nonzero value. Data may be passed into eval_g via the structure userdata.

Parameters:

data	holds private internal data
userdata	is a structure that allows data to be passed into the function and derivative evaluation programs.
status	is a scalar variable of type ipc_, that gives the entry and exit status from the package. On initial entry, status must be set to 1. Possible exit values are: 0 The run was successful -1 An allocation error occurred. A message indicating the offending array is written on unit control.error, and the returned allocation status and a string containing the name of the offending array are held in inform.alloc_status and inform.bad_alloc respectively. -2 A deallocation error occurred. A message indicating the offending array is written on unit control.error and the returned allocation status and a string containing the name of the offending array are held in inform.alloc_status and inform.bad_alloc respectively. -3 The restriction n > 0 or requirement that type contains its relevant string ‘dense’, ‘coordinate’, ‘sparse_by_rows’, ‘diagonal’ or ‘absent’ has been violated. -7 The objective function appears to be unbounded from below -9 The analysis phase of the factorization failed; the return status from the factorization package is given in the component inform.factor_status -10 The factorization failed; the return status from the factorization package is given in the component inform.factor_status. -11 The solution of a set of linear equations using factors from the factorization package failed; the return status from the factorization package is given in the component inform.factor_status. -16 The problem is so ill-conditioned that further progress is impossible. -18 Too many iterations have been performed. This may happen if control.maxit is too small, but may also be symptomatic of a badly scaled problem. -19 The CPU time limit has been reached. This may happen if control.cpu_time_limit is too small, but may also be symptomatic of a badly scaled problem. -82 The user has forced termination of solver by removing the file named control.alive_file from unit unit control.alive_unit.
n	is a scalar variable of type ipc_, that holds the number of variables
x	is a one-dimensional array of size n and type rpc_, that holds the values $x$ of the optimization variables. The j-th component of x, j = 0, … , n-1, contains $x_j$.
g	is a one-dimensional array of size n and type rpc_, that holds the gradient $g={\mathrm{\nabla }}_{x}f(x)$ of the objective function. The j-th component of g, j = 0, … , n-1, contains $g_j$.
eval_f	is a user-supplied function that must have the following signature: ipc_ eval_f( ipc_ n, const rpc_ x[], rpc_ *f, const void *userdata ) The value of the objective function $f(x)$ evaluated at x= $x$ must be assigned to f, and the function return value set to 0. If the evaluation is impossible at x, return should be set to a nonzero value. Data may be passed into eval_f via the structure userdata.
eval_g	is a user-supplied function that must have the following signature:
eval_hprod	is a user-supplied function that must have the following signature: ipc_ eval_hprod( ipc_ n, const rpc_ x[], rpc_ u[], const rpc_ v[], bool got_h, const void *userdata ) The sum $u+{\mathrm{\nabla }}_{xx}f(x)v$ of the product of the Hessian ${\mathrm{\nabla }}_{xx}f(x)$ of the objective function evaluated at x= $x$ with the vector v= $v$ and the vector $ $u$ must be returned in u, and the function return value set to 0. If the evaluation is impossible at x, return should be set to a nonzero value. The Hessian has already been evaluated or used at x if got_h is true. Data may be passed into eval_hprod via the structure userdata.
eval_shprod	is a user-supplied function that must have the following signature: ipc_ eval_shprod( ipc_ n, const rpc_ x[], ipc_ nnz_v, const ipc_ index_nz_v[], const rpc_ v[], ipc_ *nnz_u, ipc_ index_nz_u[], rpc_ u[], bool got_h, const void *userdata ) The product $u={\mathrm{\nabla }}_{xx}f(x)v$ of the Hessian ${\mathrm{\nabla }}_{xx}f(x)$ of the objective function evaluated at $x$ with the sparse vector v= $v$ must be returned in u, and the function return value set to 0. Only the components index_nz_v[0:nnz_v-1] of v are nonzero, and the remaining components may not have been be set. On exit, the user must indicate the nnz_u indices of u that are nonzero in index_nz_u[0:nnz_u-1], and only these components of u need be set. If the evaluation is impossible at x, return should be set to a nonzero value. The Hessian has already been evaluated or used at x if got_h is true. Data may be passed into eval_prec via the structure userdata.
eval_prec	is an optional user-supplied function that may be NULL. If non-NULL, it must have the following signature: ipc_ eval_prec( ipc_ n, const rpc_ x[], rpc_ u[], const rpc_ v[], const void *userdata ) The product $u=P(x)v$ of the user’s preconditioner $P(x)$ evaluated at $x$ with the vector v = $v$, the result $u$ must be retured in u, and the function return value set to 0. If the evaluation is impossible at x, return should be set to a nonzero value. Data may be passed into eval_prec via the structure userdata.

void trb_solve_reverse_with_mat(
    void **data,
    ipc_ *status,
    ipc_ *eval_status,
    ipc_ n,
    rpc_ x[],
    rpc_ f,
    rpc_ g[],
    ipc_ ne,
    rpc_ H_val[],
    const rpc_ u[],
    rpc_ v[]
)

Find a local minimizer of a given function subject to simple bounds on the variables using a trust-region method.

This call is for the case where $H={\mathrm{\nabla }}_{xx}f(x)$ is provided specifically, but function/derivative information is only available by returning to the calling procedure

Parameters:

data	holds private internal data
status	is a scalar variable of type ipc_, that gives the entry and exit status from the package. On initial entry, status must be set to 1. Possible exit values are: 0 The run was successful -1 An allocation error occurred. A message indicating the offending array is written on unit control.error, and the returned allocation status and a string containing the name of the offending array are held in inform.alloc_status and inform.bad_alloc respectively. -2 A deallocation error occurred. A message indicating the offending array is written on unit control.error and the returned allocation status and a string containing the name of the offending array are held in inform.alloc_status and inform.bad_alloc respectively. -3 The restriction n > 0 or requirement that type contains its relevant string ‘dense’, ‘coordinate’, ‘sparse_by_rows’, ‘diagonal’ or ‘absent’ has been violated. -7 The objective function appears to be unbounded from below -9 The analysis phase of the factorization failed; the return status from the factorization package is given in the component inform.factor_status -10 The factorization failed; the return status from the factorization package is given in the component inform.factor_status. -11 The solution of a set of linear equations using factors from the factorization package failed; the return status from the factorization package is given in the component inform.factor_status. -16 The problem is so ill-conditioned that further progress is impossible. -18 Too many iterations have been performed. This may happen if control.maxit is too small, but may also be symptomatic of a badly scaled problem. -19 The CPU time limit has been reached. This may happen if control.cpu_time_limit is too small, but may also be symptomatic of a badly scaled problem. -82 The user has forced termination of solver by removing the file named control.alive_file from unit unit control.alive_unit. 2 The user should compute the objective function value $f(x)$ at the point $x$ indicated in x and then re-enter the function. The required value should be set in f, and eval_status should be set to 0. If the user is unable to evaluate $f(x)$ for instance, if the function is undefined at $x$ the user need not set f, but should then set eval_status to a non-zero value. 3 The user should compute the gradient of the objective function ${\mathrm{\nabla }}_{x}f(x)$ at the point $x$ indicated in x and then re-enter the function. The value of the i-th component of the g radient should be set in g[i], for i = 0, …, n-1 and eval_status should be set to 0. If the user is unable to evaluate a component of ${\mathrm{\nabla }}_{x}f(x)$ for instance if a component of the gradient is undefined at $x$ -the user need not set g, but should then set eval_status to a non-zero value. 4 The user should compute the Hessian of the objective function ${\mathrm{\nabla }}_{xx}f(x)$ at the point x indicated in $x$ and then re-enter the function. The value l-th component of the Hessian stored according to the scheme input in the remainder of $H$ should be set in H_val[l], for l = 0, …, ne-1 and eval_status should be set to 0. If the user is unable to evaluate a component of ${\mathrm{\nabla }}_{xx}f(x)$ for instance, if a component of the Hessian is undefined at $x$ the user need not set H_val, but should then set eval_status to a non-zero value. 6 The user should compute the product $u=P(x)v$ of their preconditioner $P(x)$ at the point x indicated in $x$ with the vector $v$ and then re-enter the function. The vector $v$ is given in v, the resulting vector $u=P(x)v$ should be set in u and eval_status should be set to 0. If the user is unable to evaluate the product for instance, if a component of the preconditioner is undefined at $x$ the user need not set u, but should then set eval_status to a non-zero value.
eval_status	is a scalar variable of type ipc_, that is used to indicate if objective function/gradient/Hessian values can be provided (see above)
n	is a scalar variable of type ipc_, that holds the number of variables
x	is a one-dimensional array of size n and type rpc_, that holds the values $x$ of the optimization variables. The j-th component of x, j = 0, … , n-1, contains $x_j$.
f	is a scalar variable pointer of type rpc_, that holds the value of the objective function.
g	is a one-dimensional array of size n and type rpc_, that holds the gradient $g={\mathrm{\nabla }}_{x}f(x)$ of the objective function. The j-th component of g, j = 0, … , n-1, contains $g_j$.
ne	is a scalar variable of type ipc_, that holds the number of entries in the lower triangular part of the Hessian matrix $H$.
H_val	is a one-dimensional array of size ne and type rpc_, that holds the values of the entries of the lower triangular part of the Hessian matrix $H$ in any of the available storage schemes.
u	is a one-dimensional array of size n and type rpc_, that is used for reverse communication (see above for details)
v	is a one-dimensional array of size n and type rpc_, that is used for reverse communication (see above for details)

void trb_solve_reverse_without_mat(
    void **data,
    ipc_ *status,
    ipc_ *eval_status,
    ipc_ n,
    rpc_ x[],
    rpc_ f,
    rpc_ g[],
    rpc_ u[],
    rpc_ v[],
    ipc_ index_nz_v[],
    ipc_ *nnz_v,
    const ipc_ index_nz_u[],
    ipc_ nnz_u
)

Find a local minimizer of a given function subject to simple bounds on the variables using a trust-region method.

This call is for the case where access to $H={\mathrm{\nabla }}_{xx}f(x)$ is provided by Hessian-vector products, but function/derivative information is only available by returning to the calling procedure.

Parameters:

data	holds private internal data
status	is a scalar variable of type ipc_, that gives the entry and exit status from the package. On initial entry, status must be set to 1. Possible exit values are: 0 The run was successful -1 An allocation error occurred. A message indicating the offending array is written on unit control.error, and the returned allocation status and a string containing the name of the offending array are held in inform.alloc_status and inform.bad_alloc respectively. -2 A deallocation error occurred. A message indicating the offending array is written on unit control.error and the returned allocation status and a string containing the name of the offending array are held in inform.alloc_status and inform.bad_alloc respectively. -3 The restriction n > 0 or requirement that type contains its relevant string ‘dense’, ‘coordinate’, ‘sparse_by_rows’, ‘diagonal’ or ‘absent’ has been violated. -7 The objective function appears to be unbounded from below -9 The analysis phase of the factorization failed; the return status from the factorization package is given in the component inform.factor_status -10 The factorization failed; the return status from the factorization package is given in the component inform.factor_status. -11 The solution of a set of linear equations using factors from the factorization package failed; the return status from the factorization package is given in the component inform.factor_status. -16 The problem is so ill-conditioned that further progress is impossible. -18 Too many iterations have been performed. This may happen if control.maxit is too small, but may also be symptomatic of a badly scaled problem. -19 The CPU time limit has been reached. This may happen if control.cpu_time_limit is too small, but may also be symptomatic of a badly scaled problem. -82 The user has forced termination of solver by removing the file named control.alive_file from unit unit control.alive_unit. 2 The user should compute the objective function value $f(x)$ at the point $x$ indicated in x and then re-enter the function. The required value should be set in f, and eval_status should be set to 0. If the user is unable to evaluate $f(x)$ for instance, if the function is undefined at $x$ the user need not set f, but should then set eval_status to a non-zero value. 3 The user should compute the gradient of the objective function ${\mathrm{\nabla }}_{x}f(x)$ at the point $x$ indicated in x and then re-enter the function. The value of the i-th component of the g radient should be set in g[i], for i = 0, …, n-1 and eval_status should be set to 0. If the user is unable to evaluate a component of ${\mathrm{\nabla }}_{x}f(x)$ for instance if a component of the gradient is undefined at $x$ -the user need not set g, but should then set eval_status to a non-zero value. 5 The user should compute the product ${\mathrm{\nabla }}_{xx}f(x)v$ of the Hessian of the objective function ${\mathrm{\nabla }}_{xx}f(x)$ at the point $x$ indicated in x with the vector $v$, add the result to the vector $u$ and then re-enter the function. The vectors $u$ and $v$ are given in u and v respectively, the resulting vector $u+{\mathrm{\nabla }}_{xx}f(x)v$ should be set in u and eval_status should be set to 0. If the user is unable to evaluate the product for instance, if a component of the Hessian is undefined at $x$ the user need not alter u, but should then set eval_status to a non-zero value. 6 The user should compute the product $u=P(x)v$ of their preconditioner $P(x)$ at the point x indicated in $x$ with the vector $v$ and then re-enter the function. The vector $v$ is given in v, the resulting vector $u=P(x)v$ should be set in u and eval_status should be set to 0. If the user is unable to evaluate the product for instance, if a component of the preconditioner is undefined at $x$ the user need not set u, but should then set eval_status to a non-zero value. 7 The user should compute the product $u={\mathrm{\nabla }}_{xx}f(x)v$ of the Hessian of the objective function ${\mathrm{\nabla }}_{xx}f(x)$ at the point $x$ indicated in x with the sparse vector v= $v$ and then re-enter the function. The nonzeros of $v$ are stored in v[index_nz_v[0:nnz_v-1]] while the nonzeros of $u$ should be returned in u[index_nz_u[0:nnz_u-1]]; the user must set nnz_u and index_nz_u accordingly, and set eval_status to 0. If the user is unable to evaluate the product for instance, if a component of the Hessian is undefined at $x$ the user need not alter u, but should then set eval_status to a non-zero value.
eval_status	is a scalar variable of type ipc_, that is used to indicate if objective function/gradient/Hessian values can be provided (see above)
n	is a scalar variable of type ipc_, that holds the number of variables
x	is a one-dimensional array of size n and type rpc_, that holds the values $x$ of the optimization variables. The j-th component of x, j = 0, … , n-1, contains $x_j$.
f	is a scalar variable pointer of type rpc_, that holds the value of the objective function.
g	is a one-dimensional array of size n and type rpc_, that holds the gradient $g={\mathrm{\nabla }}_{x}f(x)$ of the objective function. The j-th component of g, j = 0, … , n-1, contains $g_j$.
u	is a one-dimensional array of size n and type rpc_, that is used for reverse communication (see status=5,6,7 above for details)
v	is a one-dimensional array of size n and type rpc_, that is used for reverse communication (see status=5,6,7 above for details)
index_nz_v	is a one-dimensional array of size n and type ipc_, that is used for reverse communication (see status=7 above for details)
nnz_v	is a scalar variable of type ipc_, that is used for reverse communication (see status=7 above for details)
index_nz_u	s a one-dimensional array of size n and type ipc_, that is used for reverse communication (see status=7 above for details)
nnz_u	is a scalar variable of type ipc_, that is used for reverse communication (see status=7 above for details). On initial (status=1) entry, nnz_u should be set to an (arbitrary) nonzero value, and nnz_u=0 is recommended

void trb_information(void **data, struct trb_inform_type* inform, ipc_ *status)

Provides output information

Parameters:

data	holds private internal data
inform	is a struct containing output information (see trb_inform_type)
status	is a scalar variable of type ipc_, that gives the exit status from the package. Possible values are (currently): 0 The values were recorded successfully

void trb_terminate(
    void **data,
    struct trb_control_type* control,
    struct trb_inform_type* inform
)

Deallocate all internal private storage

Parameters:

data	holds private internal data
control	is a struct containing control information (see trb_control_type)
inform	is a struct containing output information (see trb_inform_type)