o.. _global:

overview of functions provided#

// typedefs

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

// structs

struct wcp_control_type;
struct wcp_inform_type;
struct wcp_time_type;

// function calls

void wcp_initialize(void **data, struct wcp_control_type *control, ipc_ *status);
void wcp_read_specfile(struct wcp_control_type *control, const char specfile[]);

void wcp_import(
    struct wcp_control_type *control,
    void **data,
    ipc_ *status,
    ipc_ n,
    ipc_ m,
    const char A_type[],
    ipc_ A_ne,
    const ipc_ A_row[],
    const ipc_ A_col[],
    const ipc_ A_ptr[]
);

void wcp_reset_control(
    struct wcp_control_type *control,
    void **data,
    ipc_ *status
);

void wcp_find_wcp(
    void **data,
    ipc_ *status,
    ipc_ n,
    ipc_ m,
    const rpc_ g[],
    ipc_ a_ne,
    const rpc_ A_val[],
    const rpc_ c_l[],
    const rpc_ c_u[],
    const rpc_ x_l[],
    const rpc_ x_u[],
    rpc_ x[],
    rpc_ c[],
    rpc_ y_l[],
    rpc_ y_u[],
    rpc_ z_l[],
    rpc_ z_u[],
    ipc_x_stat[],
    ipc_c_stat[]
);

void wcp_information(void **data, struct wcp_inform_type *inform, ipc_*status);

void wcp_terminate(
    void **data,
    struct wcp_control_type *control,
    struct wcp_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 wcp_initialize(void **data, struct wcp_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 wcp_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 wcp_read_specfile(struct wcp_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/wcp/WCP.template. See also Table 2.1 in the Fortran documentation provided in $GALAHAD/doc/wcp.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 wcp_control_type)
specfile	is a character string containing the name of the specification file

void wcp_import(
    struct wcp_control_type *control,
    void **data,
    ipc_ *status,
    ipc_ n,
    ipc_ m,
    const char A_type[],
    ipc_ A_ne,
    const ipc_ A_row[],
    const ipc_ A_col[],
    const ipc_ A_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 wcp_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: 0 The import 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 restrictions n > 0 or m > 0 or requirement that a type contains its relevant string ‘dense’, ‘coordinate’, ‘sparse_by_rows’, ‘diagonal’, ‘scaled_identity’, ‘identity’, ‘zero’ or ‘none’ has been violated.
n	is a scalar variable of type ipc_, that holds the number of variables.
m	is a scalar variable of type ipc_, that holds the number of general linear constraints.
A_type	is a one-dimensional array of type char that specifies the unsymmetric storage scheme used for the constraint Jacobian, $A$. It should be one of ‘coordinate’, ‘sparse_by_rows’ or ‘dense; lower or upper case variants are allowed.
A_ne	is a scalar variable of type ipc_, that holds the number of entries in $A$ in the sparse co-ordinate storage scheme. It need not be set for any of the other schemes.
A_row	is a one-dimensional array of size A_ne and type ipc_, that holds the row indices of $A$ in the sparse co-ordinate storage scheme. It need not be set for any of the other schemes, and in this case can be NULL.
A_col	is a one-dimensional array of size A_ne and type ipc_, that holds the column indices of $A$ 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.
A_ptr	is a one-dimensional array of size n+1 and type ipc_, that holds the starting position of each row of $A$, 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 wcp_reset_control(
    struct wcp_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 wcp_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:

0
The import was successful.

void wcp_find_wcp(
    void **data,
    ipc_ *status,
    ipc_ n,
    ipc_ m,
    const rpc_ g[],
    ipc_ a_ne,
    const rpc_ A_val[],
    const rpc_ c_l[],
    const rpc_ c_u[],
    const rpc_ x_l[],
    const rpc_ x_u[],
    rpc_ x[],
    rpc_ c[],
    rpc_ y_l[],
    rpc_ y_u[],
    rpc_ z_l[],
    rpc_ z_u[],
    ipc_ x_stat[],
    ipc_ c_stat[]
)

Find a well-centered point in the feasible region

Parameters:

data	holds private internal data
status	is a scalar variable of type ipc_, that gives the entry and exit status from the package. 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 restrictions n > 0 and m > 0 or requirement that a type contains its relevant string ‘dense’, ‘coordinate’, ‘sparse_by_rows’, ‘diagonal’, ‘scaled_identity’, ‘identity’, ‘zero’ or ‘none’ has been violated. -4 The constraint bounds are inconsistent. -5 The constraints appear to have no feasible point. -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. -17 The step is too small to make further impact. -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.
n	is a scalar variable of type ipc_, that holds the number of variables
m	is a scalar variable of type ipc_, that holds the number of general linear constraints.
g	is a one-dimensional array of size n and type rpc_, that holds the target vector $g$. The j-th component of g, j = 0, … , n-1, contains $g_j$.
a_ne	is a scalar variable of type ipc_, that holds the number of entries in the constraint Jacobian matrix $A$.
A_val	is a one-dimensional array of size a_ne and type rpc_, that holds the values of the entries of the constraint Jacobian matrix $A$ in any of the available storage schemes.
c_l	is a one-dimensional array of size m and type rpc_, that holds the lower bounds $c^l$ on the constraints $A x$. The i-th component of c_l, i = 0, … , m-1, contains $c^l_i$.
c_u	is a one-dimensional array of size m and type rpc_, that holds the upper bounds $c^l$ on the constraints $A x$. The i-th component of c_u, i = 0, … , m-1, contains $c^u_i$.
x_l	is a one-dimensional array of size n and type rpc_, that holds the lower bounds $x^l$ on the variables $x$. The j-th component of x_l, j = 0, … , n-1, contains $x^l_j$.
x_u	is a one-dimensional array of size n and type rpc_, that holds the upper bounds $x^l$ on the variables $x$. The j-th component of x_u, j = 0, … , n-1, contains $x^l_j$.
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 $x_j$.
c	is a one-dimensional array of size m and type rpc_, that holds the residual $c(x)$. The i-th component of c, i = 0, … , m-1, contains $c_i(x)$.
y_l	is a one-dimensional array of size n and type rpc_, that holds the values $y^l$ of the Lagrange multipliers for the lower bounds on the general linear constraints. The j-th component of y_l, i = 0, … , m-1, contains $y^l_i$.
y_u	is a one-dimensional array of size n and type rpc_, that holds the values $y^u$ of the Lagrange multipliers for the upper bounds on the general linear constraints. The j-th component of y_u, i = 0, … , m-1, contains $y^u_i$.
z_l	is a one-dimensional array of size n and type rpc_, that holds the values $z^l$ of the dual variables for the lower bounds on the variables. The j-th component of z_l, j = 0, … , n-1, contains $z^l_j$.
z_u	is a one-dimensional array of size n and type rpc_, that holds the values $z^u$ of the dual variables for the upper bounds on the variables. The j-th component of z_u, j = 0, … , n-1, contains $z^u_j$.
x_stat	is a one-dimensional array of size n and type ipc_, that gives the optimal status of the problem variables. If x_stat(j) is negative, the variable $x_j$ most likely lies on its lower bound, if it is positive, it lies on its upper bound, and if it is zero, it lies between its bounds.
c_stat	is a one-dimensional array of size m and type ipc_, that gives the optimal status of the general linear constraints. If c_stat(i) is negative, the constraint value $a_i^T x$ most likely lies on its lower bound, if it is positive, it lies on its upper bound, and if it is zero, it lies between its bounds.

void wcp_information(void **data, struct wcp_inform_type *inform, ipc_ *status)

Provides output information.

Parameters:

data

holds private internal data

inform

is a struct containing output information (see wcp_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 wcp_terminate(
    void **data,
    struct wcp_control_type *control,
    struct wcp_inform_type *inform
)

Deallocate all internal private storage.

Parameters:

data	holds private internal data
control	is a struct containing control information (see wcp_control_type)
inform	is a struct containing output information (see wcp_inform_type)