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 xl of the lower bounds on the optimization variables x. The j-th component of x_l, j=0,,n1, contains xjl.

x_u

is a one-dimensional array of size n and type rpc_, that holds the values xu of the upper bounds on the optimization variables x. The j-th component of x_u, j=0,,n1, contains xju.

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=xxf(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 xj.

g

is a one-dimensional array of size n and type rpc_, that holds the gradient g=xf(x) of the objective function. The j-th component of g, j = 0, … , n-1, contains gj.

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=xf(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=xxf(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=xxf(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=xf(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 xj.

g

is a one-dimensional array of size n and type rpc_, that holds the gradient g=xf(x) of the objective function. The j-th component of g, j = 0, … , n-1, contains gj.

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+xxf(x)v of the product of the Hessian xxf(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=xxf(x)v of the Hessian xxf(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=xxf(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 xf(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 xf(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 xxf(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 xxf(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 xj.

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=xf(x) of the objective function. The j-th component of g, j = 0, … , n-1, contains gj.

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=xxf(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 xf(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 xf(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 xxf(x)v of the Hessian of the objective function xxf(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+xxf(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=xxf(x)v of the Hessian of the objective function xxf(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 xj.

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=xf(x) of the objective function. The j-th component of g, j = 0, … , n-1, contains gj.

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)