Task()

Task(
int numcon,
int numvar)

Task(mosek.Env env)

Task(
mosek.Env env,
int numcon,
int numvar)

Task(mosek.Task task)


Constructor of a new optimization task.

Parameters
• numcon (int) – An optional hint about the maximal number of constraints in the task. (input)

• numvar (int) – An optional hint about the maximal number of variables in the task. (input)

• env (Env) – Parent environment. (input)

• task (Task) – A task that will be cloned. (input)

public synchronized void analyzenames
(streamtype whichstream,
nametype nametype)


The function analyzes the names and issues an error if a name is invalid.

Parameters
Groups

Names

public synchronized void analyzeproblem(streamtype whichstream)


The function analyzes the data of a task and writes out a report.

Parameters

whichstream (streamtype) – Index of the stream. (input)

Groups

public synchronized void analyzesolution
(streamtype whichstream,
soltype whichsol)


Print information related to the quality of the solution and other solution statistics.

By default this function prints information about the largest infeasibilites in the solution, the primal (and possibly dual) objective value and the solution status.

Following parameters can be used to configure the printed statistics:

Parameters
Groups
public synchronized void appendacc
(long domidx,
long[] afeidxlist,
double[] b)


Appends an affine conic constraint to the task. The affine constraint has the form a sequence of affine expressions belongs to a domain.

The domain index is specified with domidx and should refer to a domain previously appended with one of the append...domain functions.

The length of the affine expression list afeidxlist must be equal to the dimension $$n$$ of the domain. The elements of afeidxlist are indexes to the store of affine expressions, i.e. the affine expressions appearing in the affine conic constraint are:

$F_{\mathrm{afeidxlist}[k],:}x + g_{\mathrm{afeidxlist}[k]} \quad \mathrm{for}\ k=0,\ldots,n-1.$

If an optional vector b of the same length as afeidxlist is specified then the expressions appearing in the affine constraint will instead be taken as:

$F_{\mathrm{afeidxlist}[k],:}x + g_{\mathrm{afeidxlist}[k]} - b_k \quad \mathrm{for}\ k=0,\ldots,n-1.$
Parameters
• domidx (long) – Domain index. (input)

• afeidxlist (long[]) – List of affine expression indexes. (input)

• b (double[]) – The vector of constant terms added to affine expressions. Optional, can be NULL. (input)

Groups

Problem data - affine conic constraints

public synchronized void appendaccs
(long[] domidxs,
long[] afeidxlist,
double[] b)


Appends numaccs affine conic constraint to the task. Each single affine conic constraint should be specified as in Task.appendacc and the input of this function should contain the concatenation of all these descriptions.

In particular, the length of afeidxlist must equal the sum of dimensions of domains indexed in domainsidxs.

Parameters
• domidxs (long[]) – Domain indices. (input)

• afeidxlist (long[]) – List of affine expression indexes. (input)

• b (double[]) – The vector of constant terms added to affine expressions. Optional, can be NULL. (input)

Groups

Problem data - affine conic constraints

public synchronized void appendaccseq
(long domidx,
long afeidxfirst,
double[] b)


Appends an affine conic constraint to the task, as in Task.appendacc. The function assumes the affine expressions forming the constraint are sequential. The affine constraint has the form a sequence of affine expressions belongs to a domain.

The domain index is specified with domidx and should refer to a domain previously appended with one of the append...domain functions.

The number of affine expressions should be equal to the dimension $$n$$ of the domain. The affine expressions forming the affine constraint are arranged sequentially in a contiguous block of the affine expression store starting from position afeidxfirst. That is, the affine expressions appearing in the affine conic constraint are:

$F_{\mathrm{afeidxfirst}+k,:}x + g_{\mathrm{afeidxfirst}+k} \quad \mathrm{for}\ k=0,\ldots,n-1.$

If an optional vector b of length numafeidx is specified then the expressions appearing in the affine constraint will instead be taken as

$F_{\mathrm{afeidxfirst}+k,:}x + g_{\mathrm{afeidxfirst}+k} - b_k \quad \mathrm{for}\ k=0,\ldots,n-1.$
Parameters
• domidx (long) – Domain index. (input)

• afeidxfirst (long) – Index of the first affine expression. (input)

• b (double[]) – The vector of constant terms added to affine expressions. Optional, can be NULL. (input)

Groups

Problem data - affine conic constraints

public synchronized void appendaccsseq
(long[] domidxs,
long numafeidx,
long afeidxfirst,
double[] b)


Appends numaccs affine conic constraint to the task. It is the block variant of Task.appendaccs, that is it assumes that the affine expressions appearing in the affine conic constraints are sequential in the affine expression store, starting from position afeidxfirst.

Parameters
• domidxs (long[]) – Domain indices. (input)

• numafeidx (long) – Number of affine expressions in the affine expression list (must equal the sum of dimensions of the domains). (input)

• afeidxfirst (long) – Index of the first affine expression. (input)

• b (double[]) – The vector of constant terms added to affine expressions. Optional, can be NULL. (input)

Groups

Problem data - affine conic constraints

public synchronized void appendafes(long num)


Appends a number of empty affine expressions to the task.

Parameters

num (long) – Number of empty affine expressions which should be appended. (input)

Groups

Problem data - affine expressions

public synchronized void appendbarvars(int[] dim)


Appends positive semidefinite matrix variables of dimensions given by dim to the problem.

Parameters

dim (int[]) – Dimensions of symmetric matrix variables to be added. (input)

Groups

Problem data - semidefinite

public synchronized void appendcone
(conetype ct,
double conepar,
int[] submem)


NOTE: This interface to conic optimization is deprecated and will be removed in a future major release. Conic problems should be specified using the affine conic constraints interface (ACC), see Sec. 6.2 (From Linear to Conic Optimization) for details.

Appends a new conic constraint to the problem. Hence, add a constraint

$\hat{x} \in \K$

to the problem, where $$\K$$ is a convex cone. $$\hat{x}$$ is a subset of the variables which will be specified by the argument submem. Cone type is specified by ct.

Define

$\hat{x} = x_{\mathtt{submem}[0]},\ldots,x_{\mathtt{submem}[\mathtt{nummem}-1]}.$

Depending on the value of ct this function appends one of the constraints:

• Quadratic cone (conetype.quad, requires $$\mathtt{nummem}\geq 1$$):

$\hat{x}_0 \geq \sqrt{\sum_{i=1}^{i<\mathtt{nummem}} \hat{x}_i^2}$
• Rotated quadratic cone (conetype.rquad, requires $$\mathtt{nummem}\geq 2$$):

$2 \hat{x}_0 \hat{x}_1 \geq \sum_{i=2}^{i<\mathtt{nummem}} \hat{x}^2_i, \quad \hat{x}_{0}, \hat{x}_1 \geq 0$
• Primal exponential cone (conetype.pexp, requires $$\mathtt{nummem}=3$$):

$\hat{x}_0 \geq \hat{x}_1\exp(\hat{x}_2/\hat{x}_1), \quad \hat{x}_0,\hat{x}_1 \geq 0$
• Primal power cone (conetype.ppow, requires $$\mathtt{nummem}\geq 2$$):

$\hat{x}_0^\alpha \hat{x}_1^{1-\alpha} \geq \sqrt{\sum_{i=2}^{i<\mathtt{nummem}} \hat{x}^2_i}, \quad \hat{x}_{0}, \hat{x}_1 \geq 0$

where $$\alpha$$ is the cone parameter specified by conepar.

• Dual exponential cone (conetype.dexp, requires $$\mathtt{nummem}=3$$):

$\hat{x}_0 \geq -\hat{x}_2 e^{-1}\exp(\hat{x}_1/\hat{x}_2), \quad \hat{x}_2\leq 0,\hat{x}_0 \geq 0$
• Dual power cone (conetype.dpow, requires $$\mathtt{nummem}\geq 2$$):

$\left(\frac{\hat{x}_0}{\alpha}\right)^\alpha \left(\frac{\hat{x}_1}{1-\alpha}\right)^{1-\alpha} \geq \sqrt{\sum_{i=2}^{i<\mathtt{nummem}} \hat{x}^2_i}, \quad \hat{x}_{0}, \hat{x}_1 \geq 0$

where $$\alpha$$ is the cone parameter specified by conepar.

• Zero cone (conetype.zero):

$\hat{x}_i = 0 \ \textrm{for all}\ i$

Please note that the sets of variables appearing in different conic constraints must be disjoint.

For an explained code example see Sec. 6.3 (Conic Quadratic Optimization), Sec. 6.5 (Conic Exponential Optimization) or Sec. 6.4 (Power Cone Optimization).

Parameters
• ct (conetype) – Specifies the type of the cone. (input)

• conepar (double) – For the power cone it denotes the exponent alpha. For other cone types it is unused and can be set to 0. (input)

• submem (int[]) – Variable subscripts of the members in the cone. (input)

Groups

Problem data - cones (deprecated)

public synchronized void appendconeseq
(conetype ct,
double conepar,
int nummem,
int j)


NOTE: This interface to conic optimization is deprecated and will be removed in a future major release. Conic problems should be specified using the affine conic constraints interface (ACC), see Sec. 6.2 (From Linear to Conic Optimization) for details.

Appends a new conic constraint to the problem, as in Task.appendcone. The function assumes the members of cone are sequential where the first member has index j and the last j+nummem-1.

Parameters
• ct (conetype) – Specifies the type of the cone. (input)

• conepar (double) – For the power cone it denotes the exponent alpha. For other cone types it is unused and can be set to 0. (input)

• nummem (int) – Number of member variables in the cone. (input)

• j (int) – Index of the first variable in the conic constraint. (input)

Groups

Problem data - cones (deprecated)

public synchronized void appendconesseq
(conetype[] ct,
double[] conepar,
int[] nummem,
int j)


NOTE: This interface to conic optimization is deprecated and will be removed in a future major release. Conic problems should be specified using the affine conic constraints interface (ACC), see Sec. 6.2 (From Linear to Conic Optimization) for details.

Appends a number of conic constraints to the problem, as in Task.appendcone. The $$k$$th cone is assumed to be of dimension nummem[k]. Moreover, it is assumed that the first variable of the first cone has index $$j$$ and starting from there the sequentially following variables belong to the first cone, then to the second cone and so on.

Parameters
• ct (conetype[]) – Specifies the type of the cone. (input)

• conepar (double[]) – For the power cone it denotes the exponent alpha. For other cone types it is unused and can be set to 0. (input)

• nummem (int[]) – Numbers of member variables in the cones. (input)

• j (int) – Index of the first variable in the first cone to be appended. (input)

Groups

Problem data - cones (deprecated)

public synchronized void appendcons(int num)


Appends a number of constraints to the model. Appended constraints will be declared free. Please note that MOSEK will automatically expand the problem dimension to accommodate the additional constraints.

Parameters

num (int) – Number of constraints which should be appended. (input)

Groups
public synchronized void appenddjcs(long num)


Appends a number of empty disjunctive constraints to the task.

Parameters

num (long) – Number of empty disjunctive constraints which should be appended. (input)

Groups

Problem data - disjunctive constraints

public synchronized void appenddualexpconedomain(long[] domidx)

public synchronized long appenddualexpconedomain()


Appends the dual exponential cone $$\left\{ x\in \real^3 ~:~ x_0 \geq -x_2 e^{-1} e^{x_1/x_2},\ x_0> 0,\ x_2< 0 \right\}$$ to the list of domains.

Parameters

domidx (long by reference) – Index of the domain. (output)

Return

(long) – Index of the domain.

Groups

Problem data - domain

public synchronized void appenddualgeomeanconedomain
(long n,
long[] domidx)

public synchronized long appenddualgeomeanconedomain(long n)


Appends the dual geometric mean cone $$\left\{ x\in \real^n ~:~ (n-1) \left(\prod_{i=0}^{n-2} x_i\right)^{1/(n-1)} \geq |x_{n-1}|,\ x_0,\ldots,x_{n-2}\geq 0 \right\}$$ to the list of domains.

Parameters
• n (long) – Dimmension of the domain. (input)

• domidx (long by reference) – Index of the domain. (output)

Return

(long) – Index of the domain.

Groups

Problem data - domain

public synchronized void appenddualpowerconedomain
(long n,
double[] alpha,
long[] domidx)

public synchronized long appenddualpowerconedomain
(long n,
double[] alpha)


Appends the dual power cone domain of dimension $$n$$, with $$n_\ell$$ variables appearing on the left-hand side, where $$n_\ell$$ is the length of $$\alpha$$, and with a homogenous sequence of exponents $$\alpha_0,\ldots,\alpha_{n_\ell-1}$$.

Formally, let $$s = \sum_i \alpha_i$$ and $$\beta_i = \alpha_i / s$$, so that $$\sum_i \beta_i=1$$. Then the dual power cone is defined as follows:

$\left\{ x\in \real^n ~:~ \prod_{i=0}^{n_\ell-1} \left(\frac{x_i}{\beta_i}\right)^{\beta_i} \geq \sqrt{\sum_{j=n_\ell}^{n-1}x_j^2},\ x_0\ldots,x_{n_\ell-1}\geq 0 \right\}$
Parameters
• n (long) – Dimension of the domain. (input)

• alpha (double[]) – The sequence proportional to exponents. Must be positive. (input)

• domidx (long by reference) – Index of the domain. (output)

Return

(long) – Index of the domain.

Groups

Problem data - domain

public synchronized void appendprimalexpconedomain(long[] domidx)

public synchronized long appendprimalexpconedomain()


Appends the primal exponential cone $$\left\{ x\in \real^3 ~:~ x_0 \geq x_1 e^{x_2/x_1},\ x_0,x_1> 0 \right\}$$ to the list of domains.

Parameters

domidx (long by reference) – Index of the domain. (output)

Return

(long) – Index of the domain.

Groups

Problem data - domain

public synchronized void appendprimalgeomeanconedomain
(long n,
long[] domidx)

public synchronized long appendprimalgeomeanconedomain(long n)


Appends the primal geometric mean cone $$\left\{ x\in \real^n ~:~ \left(\prod_{i=0}^{n-2} x_i\right)^{1/(n-1)} \geq |x_{n-1}|,\ x_0\ldots,x_{n-2}\geq 0 \right\}$$ to the list of domains.

Parameters
• n (long) – Dimmension of the domain. (input)

• domidx (long by reference) – Index of the domain. (output)

Return

(long) – Index of the domain.

Groups

Problem data - domain

public synchronized void appendprimalpowerconedomain
(long n,
double[] alpha,
long[] domidx)

public synchronized long appendprimalpowerconedomain
(long n,
double[] alpha)


Appends the primal power cone domain of dimension $$n$$, with $$n_\ell$$ variables appearing on the left-hand side, where $$n_\ell$$ is the length of $$\alpha$$, and with a homogenous sequence of exponents $$\alpha_0,\ldots,\alpha_{n_\ell-1}$$.

Formally, let $$s = \sum_i \alpha_i$$ and $$\beta_i = \alpha_i / s$$, so that $$\sum_i \beta_i=1$$. Then the primal power cone is defined as follows:

$\left\{ x\in \real^n ~:~ \prod_{i=0}^{n_\ell-1} x_i^{\beta_i} \geq \sqrt{\sum_{j=n_\ell}^{n-1}x_j^2},\ x_0\ldots,x_{n_\ell-1}\geq 0 \right\}$
Parameters
• n (long) – Dimension of the domain. (input)

• alpha (double[]) – The sequence proportional to exponents. Must be positive. (input)

• domidx (long by reference) – Index of the domain. (output)

Return

(long) – Index of the domain.

Groups

Problem data - domain

public synchronized void appendquadraticconedomain
(long n,
long[] domidx)

public synchronized long appendquadraticconedomain(long n)


Appends the $$n$$-dimensional quadratic cone $$\left\{x\in\real^n~:~x_0 \geq \sqrt{\sum_{i=1}^{n-1} x_i^2}\right\}$$ to the list of domains.

Parameters
• n (long) – Dimmension of the domain. (input)

• domidx (long by reference) – Index of the domain. (output)

Return

(long) – Index of the domain.

Groups

Problem data - domain

public synchronized void appendrdomain
(long n,
long[] domidx)

public synchronized long appendrdomain(long n)


Appends the $$n$$-dimensional real space $$\{ x \in \real^n \}$$ to the list of domains.

Parameters
• n (long) – Dimmension of the domain. (input)

• domidx (long by reference) – Index of the domain. (output)

Return

(long) – Index of the domain.

Groups

Problem data - domain

public synchronized void appendrminusdomain
(long n,
long[] domidx)

public synchronized long appendrminusdomain(long n)


Appends the $$n$$-dimensional negative orthant $$\{ x \in \real^n: \, x \leq 0 \}$$ to the list of domains.

Parameters
• n (long) – Dimmension of the domain. (input)

• domidx (long by reference) – Index of the domain. (output)

Return

(long) – Index of the domain.

Groups

Problem data - domain

public synchronized void appendrplusdomain
(long n,
long[] domidx)

public synchronized long appendrplusdomain(long n)


Appends the $$n$$-dimensional positive orthant $$\{ x \in \real^n: \, x \geq 0 \}$$ to the list of domains.

Parameters
• n (long) – Dimmension of the domain. (input)

• domidx (long by reference) – Index of the domain. (output)

Return

(long) – Index of the domain.

Groups

Problem data - domain

public synchronized void appendrquadraticconedomain
(long n,
long[] domidx)

public synchronized long appendrquadraticconedomain(long n)


Appends the $$n$$-dimensional rotated quadratic cone $$\left\{x\in\real^n~:~2 x_0 x_1 \geq \sum_{i=2}^{n-1} x_i^2,\ x_0,x_1\geq 0\right\}$$ to the list of domains.

Parameters
• n (long) – Dimmension of the domain. (input)

• domidx (long by reference) – Index of the domain. (output)

Return

(long) – Index of the domain.

Groups

Problem data - domain

public synchronized void appendrzerodomain
(long n,
long[] domidx)

public synchronized long appendrzerodomain(long n)


Appends the zero in $$n$$-dimensional real space $$\{ x \in \real^n: \, x = 0 \}$$ to the list of domains.

Parameters
• n (long) – Dimmension of the domain. (input)

• domidx (long by reference) – Index of the domain. (output)

Return

(long) – Index of the domain.

Groups

Problem data - domain

public synchronized void appendsparsesymmat
(int dim,
int[] subi,
int[] subj,
double[] valij,
long[] idx)

public synchronized long appendsparsesymmat
(int dim,
int[] subi,
int[] subj,
double[] valij)


MOSEK maintains a storage of symmetric data matrices that is used to build $$\barC$$ and $$\barA$$. The storage can be thought of as a vector of symmetric matrices denoted $$E$$. Hence, $$E_i$$ is a symmetric matrix of certain dimension.

This function appends a general sparse symmetric matrix on triplet form to the vector $$E$$ of symmetric matrices. The vectors subi, subj, and valij contains the row subscripts, column subscripts and values of each element in the symmetric matrix to be appended. Since the matrix that is appended is symmetric, only the lower triangular part should be specified. Moreover, duplicates are not allowed.

Observe the function reports the index (position) of the appended matrix in $$E$$. This index should be used for later references to the appended matrix.

Parameters
• dim (int) – Dimension of the symmetric matrix that is appended. (input)

• subi (int[]) – Row subscript in the triplets. (input)

• subj (int[]) – Column subscripts in the triplets. (input)

• valij (double[]) – Values of each triplet. (input)

• idx (long by reference) – Unique index assigned to the inputted matrix that can be used for later reference. (output)

Return

(long) – Unique index assigned to the inputted matrix that can be used for later reference.

Groups

Problem data - semidefinite

public synchronized void appendsparsesymmatlist
(int[] dims,
long[] nz,
int[] subi,
int[] subj,
double[] valij,
long[] idx)


MOSEK maintains a storage of symmetric data matrices that is used to build $$\barC$$ and $$\barA$$. The storage can be thought of as a vector of symmetric matrices denoted $$E$$. Hence, $$E_i$$ is a symmetric matrix of certain dimension.

This function appends general sparse symmetric matrixes on triplet form to the vector $$E$$ of symmetric matrices. The vectors subi, subj, and valij contains the row subscripts, column subscripts and values of each element in the symmetric matrix to be appended. Since the matrix that is appended is symmetric, only the lower triangular part should be specified. Moreover, duplicates are not allowed.

Observe the function reports the index (position) of the appended matrix in $$E$$. This index should be used for later references to the appended matrix.

Parameters
• dims (int[]) – Dimensions of the symmetric matrixes. (input)

• nz (long[]) – Number of nonzeros for each matrix. (input)

• subi (int[]) – Row subscript in the triplets. (input)

• subj (int[]) – Column subscripts in the triplets. (input)

• valij (double[]) – Values of each triplet. (input)

• idx (long[]) – Unique index assigned to the inputted matrix that can be used for later reference. (output)

Groups

Problem data - semidefinite

public synchronized void appendsvecpsdconedomain
(long n,
long[] domidx)

public synchronized long appendsvecpsdconedomain(long n)


Appends the domain consisting of vectors of length $$n=d(d+1)/2$$ defined as follows

$\{(x_1,\ldots,x_{d(d+1)/2})\in \real^n~:~ \mathrm{sMat}(x)\in\PSD^d\} = \{\mathrm{sVec}(X)~:~X\in\PSD^d\},$

where

$\mathrm{sVec}(X) = (X_{11},\sqrt{2}X_{21},\ldots,\sqrt{2}X_{d1},X_{22},\sqrt{2}X_{32},\ldots,X_{dd}),$

and

$\begin{split}\mathrm{sMat}(x) = \left[\begin{array}{cccc}x_1 & x_2/\sqrt{2} & \cdots & x_{d}/\sqrt{2} \\ x_2/\sqrt{2} & x_{d+1} & \cdots & x_{2d-1}/\sqrt{2} \\ \cdots & \cdots & \cdots & \cdots \\ x_{d}/\sqrt{2} & x_{2d-1}/\sqrt{2} & \cdots & x_{d(d+1)/2}\end{array}\right].\end{split}$

In other words, the domain consists of vectorizations of the lower-triangular part of a positive semidefinite matrix, with the non-diagonal elements additionally rescaled.

This domain is a self-dual cone.

Parameters
• n (long) – Dimension of the domain, must be of the form $$d(d+1)/2$$. (input)

• domidx (long by reference) – Index of the domain. (output)

Return

(long) – Index of the domain.

Groups

Problem data - domain

public synchronized void appendvars(int num)


Appends a number of variables to the model. Appended variables will be fixed at zero. Please note that MOSEK will automatically expand the problem dimension to accommodate the additional variables.

Parameters

num (int) – Number of variables which should be appended. (input)

Groups
public synchronized void asyncgetresult
String accesstoken,
String token,
boolean[] respavailable,
rescode[] resp,
rescode[] trm)

public synchronized boolean asyncgetresult
String accesstoken,
String token,
rescode[] resp,
rescode[] trm)


Request a solution from a remote job identified by the argument token. For other arguments see Task.asyncoptimize. If the solution is available it will be retrieved and loaded into the local task.

Parameters
• address (String) – Address of the OptServer. (input)

• accesstoken (String) – Access token. (input)

• token (String) – The task token. (input)

• respavailable (boolean by reference) – Indicates if a remote response is available. If this is not true, resp and trm should be ignored. (output)

• resp (mosek.rescode by reference) – Is the response code from the remote solver. (output)

• trm (mosek.rescode by reference) – Is either rescode.ok or a termination response code. (output)

Return

(boolean) – Indicates if a remote response is available. If this is not true, resp and trm should be ignored.

Groups

Remote optimization

public synchronized String asyncoptimize
String accesstoken)


Offload the optimization task to an instance of OptServer specified by addr, which should be a valid URL, for example http://server:port or https://server:port. The call will exit immediately.

If the server requires authentication, the authentication token can be passed in the accesstoken argument.

If the server requires encryption, the keys can be passed using one of the solver parameters sparam.remote_tls_cert or sparam.remote_tls_cert_path.

The function returns a token which should be used in future calls to identify the task.

Parameters
• address (String) – Address of the OptServer. (input)

• accesstoken (String) – Access token. (input)

Return

(String) – Returns the task token.

Groups

Remote optimization

public synchronized void asyncpoll
String accesstoken,
String token,
boolean[] respavailable,
rescode[] resp,
rescode[] trm)

public synchronized boolean asyncpoll
String accesstoken,
String token,
rescode[] resp,
rescode[] trm)


Requests information about the status of the remote job identified by the argument token. For other arguments see Task.asyncoptimize.

Parameters
• address (String) – Address of the OptServer. (input)

• accesstoken (String) – Access token. (input)

• token (String) – The task token. (input)

• respavailable (boolean by reference) – Indicates if a remote response is available. If this is not true, resp and trm should be ignored. (output)

• resp (mosek.rescode by reference) – Is the response code from the remote solver. (output)

• trm (mosek.rescode by reference) – Is either rescode.ok or a termination response code. (output)

Return

(boolean) – Indicates if a remote response is available. If this is not true, resp and trm should be ignored.

Groups

Remote optimization

public synchronized void asyncstop
String accesstoken,
String token)


Request that the remote job identified by token is terminated. For other arguments see Task.asyncoptimize.

Parameters
• address (String) – Address of the OptServer. (input)

• accesstoken (String) – Access token. (input)

• token (String) – The task token. (input)

Groups

Remote optimization

public synchronized void basiscond
(double[] nrmbasis,
double[] nrminvbasis)


If a basic solution is available and it defines a nonsingular basis, then this function computes the 1-norm estimate of the basis matrix and a 1-norm estimate for the inverse of the basis matrix. The 1-norm estimates are computed using the method outlined in [Ste98], pp. 388-391.

By definition the 1-norm condition number of a matrix $$B$$ is defined as

$\kappa_1(B) := \|B\|_1 \|B^{-1}\|_1.$

Moreover, the larger the condition number is the harder it is to solve linear equation systems involving $$B$$. Given estimates for $$\|B\|_1$$ and $$\|B^{-1}\|_1$$ it is also possible to estimate $$\kappa_1(B)$$.

Parameters
• nrmbasis (double by reference) – An estimate for the 1-norm of the basis. (output)

• nrminvbasis (double by reference) – An estimate for the 1-norm of the inverse of the basis. (output)

Groups

Solving systems with basis matrix

public synchronized void checkmem
(String file,
int line)


Checks the memory allocated by the task.

Parameters
• file (String) – File from which the function is called. (input)

• line (int) – Line in the file from which the function is called. (input)

Groups

System, memory and debugging

public synchronized void chgconbound
(int i,
int lower,
int finite,
double value)


Changes a bound for one constraint.

If lower is non-zero, then the lower bound is changed as follows:

$\begin{split}\mbox{new lower bound} = \left\{ \begin{array}{ll} - \infty, & \mathtt{finite}=0, \\ \mathtt{value} & \mbox{otherwise}. \end{array} \right.\end{split}$

Otherwise if lower is zero, then

$\begin{split}\mbox{new upper bound} = \left\{ \begin{array}{ll} \infty, & \mathtt{finite}=0, \\ \mathtt{value} & \mbox{otherwise}. \end{array} \right.\end{split}$

Please note that this function automatically updates the bound key for the bound, in particular, if the lower and upper bounds are identical, the bound key is changed to fixed.

Parameters
• i (int) – Index of the constraint for which the bounds should be changed. (input)

• lower (int) – If non-zero, then the lower bound is changed, otherwise the upper bound is changed. (input)

• finite (int) – If non-zero, then value is assumed to be finite. (input)

• value (double) – New value for the bound. (input)

Groups
public synchronized void chgvarbound
(int j,
int lower,
int finite,
double value)


Changes a bound for one variable.

If lower is non-zero, then the lower bound is changed as follows:

$\begin{split}\mbox{new lower bound} = \left\{ \begin{array}{ll} - \infty, & \mathtt{finite}=0, \\ \mathtt{value} & \mbox{otherwise}. \end{array} \right.\end{split}$

Otherwise if lower is zero, then

$\begin{split}\mbox{new upper bound} = \left\{ \begin{array}{ll} \infty, & \mathtt{finite}=0, \\ \mathtt{value} & \mbox{otherwise}. \end{array} \right.\end{split}$

Please note that this function automatically updates the bound key for the bound, in particular, if the lower and upper bounds are identical, the bound key is changed to fixed.

Parameters
• j (int) – Index of the variable for which the bounds should be changed. (input)

• lower (int) – If non-zero, then the lower bound is changed, otherwise the upper bound is changed. (input)

• finite (int) – If non-zero, then value is assumed to be finite. (input)

• value (double) – New value for the bound. (input)

Groups
public synchronized void commitchanges()


Commits all cached problem changes to the task. It is usually not necessary to call this function explicitly since changes will be committed automatically when required.

Groups

public synchronized void deletesolution(soltype whichsol)


Undefine a solution and free the memory it uses.

Parameters

whichsol (soltype) – Selects a solution. (input)

Groups
void dispose()


Free the underlying native allocation.

public synchronized void dualsensitivity
(int[] subj,
double[] leftpricej,
double[] rightpricej,
double[] leftrangej,
double[] rightrangej)


Calculates sensitivity information for objective coefficients. The indexes of the coefficients to analyze are

$\{\mathtt{subj}[i] ~|~ i = 0,\ldots,\mathtt{numj}-1\}$

The type of sensitivity analysis to perform (basis or optimal partition) is controlled by the parameter iparam.sensitivity_type.

For an example, please see Section Example: Sensitivity Analysis.

Parameters
• subj (int[]) – Indexes of objective coefficients to analyze. (input)

• leftpricej (double[]) – $$\mathtt{leftpricej}[j]$$ is the left shadow price for the coefficient with index $$\mathtt{subj[j]}$$. (output)

• rightpricej (double[]) – $$\mathtt{rightpricej}[j]$$ is the right shadow price for the coefficient with index $$\mathtt{subj[j]}$$. (output)

• leftrangej (double[]) – $$\mathtt{leftrangej}[j]$$ is the left range $$\beta_1$$ for the coefficient with index $$\mathtt{subj[j]}$$. (output)

• rightrangej (double[]) – $$\mathtt{rightrangej}[j]$$ is the right range $$\beta_2$$ for the coefficient with index $$\mathtt{subj[j]}$$. (output)

Groups

Sensitivity analysis

public synchronized void emptyafebarfrow(long afeidx)


Clears a row in $$\barF$$ i.e. sets $$\barF_{\mathrm{afeidx},*} = 0$$.

Parameters

afeidx (long) – Row index of $$\barF$$. (input)

Groups
public synchronized void emptyafebarfrowlist(long[] afeidxlist)


Clears a number of rows in $$\barF$$ i.e. sets $$\barF_{i,*} = 0$$ for all indices $$i$$ in afeidxlist.

Parameters

afeidxlist (long[]) – Indices of rows in $$\barF$$ to clear. (input)

Groups
public synchronized void emptyafefcol(int varidx)


Clears one column in the affine constraint matrix $$F$$, that is sets $$F_{*,\mathrm{varidx}}=0$$.

Parameters

varidx (int) – Index of a variable (column in $$F$$). (input)

Groups

Problem data - affine expressions

public synchronized void emptyafefcollist(int[] varidx)


Clears a number of columns in $$F$$ i.e. sets $$F_{*,j} = 0$$ for all indices $$j$$ in varidx.

Parameters

varidx (int[]) – Indices of variables (columns) in $$F$$ to clear. (input)

Groups

Problem data - affine expressions

public synchronized void emptyafefrow(long afeidx)


Clears one row in the affine constraint matrix $$F$$, that is sets $$F_{\mathrm{afeidx},*}=0$$.

Parameters

afeidx (long) – Index of a row in $$F$$. (input)

Groups

Problem data - affine expressions

public synchronized void emptyafefrowlist(long[] afeidx)


Clears a number of rows in $$F$$ i.e. sets $$F_{i,*} = 0$$ for all indices $$i$$ in afeidx.

Parameters

afeidx (long[]) – Indices of rows in $$F$$ to clear. (input)

Groups

Problem data - affine expressions

public synchronized void evaluateacc
(soltype whichsol,
long accidx,
double[] activity)


Evaluates the activity of an affine conic constraint.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• accidx (long) – The index of the affine conic constraint. (input)

• activity (double[]) – The activity of the affine conic constraint. The array should have length equal to the dimension of the constraint. (output)

Groups
public synchronized void evaluateaccs
(soltype whichsol,
double[] activity)


Evaluates the activities of all affine conic constraints.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• activity (double[]) – The activity of affine conic constraints. The array should have length equal to the sum of dimensions of all affine conic constraints. (output)

Groups
public synchronized void generateaccnames
(long[] sub,
String fmt,
int[] dims,
long[] sp,
int[] namedaxisidxs,
String[] names)


Internal.

Parameters
• sub (long[]) – Indexes of the affine conic constraints. (input)

• fmt (String) – The variable name formatting string. (input)

• dims (int[]) – Dimensions in the shape. (input)

• sp (long[]) – Items that should be named. (input)

• namedaxisidxs (int[]) – List if named index axes (input)

Groups

Names

public synchronized void generatebarvarnames
(int[] subj,
String fmt,
int[] dims,
long[] sp,
int[] namedaxisidxs,
String[] names)


Generates systematic names for variables.

Parameters
• subj (int[]) – Indexes of the variables. (input)

• fmt (String) – The variable name formatting string. (input)

• dims (int[]) – Dimensions in the shape. (input)

• sp (long[]) – Items that should be named. (input)

• namedaxisidxs (int[]) – List if named index axes (input)

Groups
public synchronized void generateconenames
(int[] subk,
String fmt,
int[] dims,
long[] sp,
int[] namedaxisidxs,
String[] names)


Internal, deprecated.

Parameters
• subk (int[]) – Indexes of the cone. (input)

• fmt (String) – The cone name formatting string. (input)

• dims (int[]) – Dimensions in the shape. (input)

• sp (long[]) – Items that should be named. (input)

• namedaxisidxs (int[]) – List if named index axes (input)

Groups
public synchronized void generateconnames
(int[] subi,
String fmt,
int[] dims,
long[] sp,
int[] namedaxisidxs,
String[] names)


Generates systematic names for constraints.

Parameters
• subi (int[]) – Indexes of the constraints. (input)

• fmt (String) – The constraint name formatting string. (input)

• dims (int[]) – Dimensions in the shape. (input)

• sp (long[]) – Items that should be named. (input)

• namedaxisidxs (int[]) – List if named index axes (input)

Groups
public synchronized void generatedjcnames
(long[] sub,
String fmt,
int[] dims,
long[] sp,
int[] namedaxisidxs,
String[] names)


Internal.

Parameters
• sub (long[]) – Indexes of the disjunctive constraints. (input)

• fmt (String) – The variable name formatting string. (input)

• dims (int[]) – Dimensions in the shape. (input)

• sp (long[]) – Items that should be named. (input)

• namedaxisidxs (int[]) – List if named index axes (input)

Groups

Names

public synchronized void generatevarnames
(int[] subj,
String fmt,
int[] dims,
long[] sp,
int[] namedaxisidxs,
String[] names)


Generates systematic names for variables.

Parameters
• subj (int[]) – Indexes of the variables. (input)

• fmt (String) – The variable name formatting string. (input)

• dims (int[]) – Dimensions in the shape. (input)

• sp (long[]) – Items that should be named. (input)

• namedaxisidxs (int[]) – List if named index axes (input)

Groups
public synchronized void getaccafeidxlist
(long accidx,
long[] afeidxlist)


Obtains the list of affine expressions appearing in the affine conic constraint.

Parameters
• accidx (long) – Index of the affine conic constraint. (input)

• afeidxlist (long[]) – List of indexes of affine expressions appearing in the constraint. (output)

Groups
public synchronized void getaccb
(long accidx,
double[] b)


Obtains the additional constant term vector appearing in the affine conic constraint.

Parameters
• accidx (long) – Index of the affine conic constraint. (input)

• b (double[]) – The vector b appearing in the constraint. (output)

Groups
public synchronized void getaccbarfblocktriplet
(long[] numtrip,
long[] acc_afe,
int[] bar_var,
int[] blk_row,
int[] blk_col,
double[] blk_val)

public synchronized long getaccbarfblocktriplet
(long[] acc_afe,
int[] bar_var,
int[] blk_row,
int[] blk_col,
double[] blk_val)


Obtains $$\barF$$, implied by the ACCs, in block triplet form. If the AFEs passed to the ACCs were out of order, then this function can be used to obtain the barF as seen by the ACCs.

Parameters
• numtrip (long by reference) – Number of elements in the block triplet form. (output)

• acc_afe (long[]) – Index of the AFE within the concatenated list of AFEs in ACCs. (output)

• bar_var (int[]) – Symmetric matrix variable index. (output)

• blk_row (int[]) – Block row index. (output)

• blk_col (int[]) – Block column index. (output)

• blk_val (double[]) – The numerical value associated with each block triplet. (output)

Return

(long) – Number of elements in the block triplet form.

Groups
public synchronized void getaccbarfnumblocktriplets(long[] numtrip)

public synchronized long getaccbarfnumblocktriplets()


Obtains an upper bound on the number of elements in the block triplet form of $$\barF$$, as used within the ACCs.

Parameters

numtrip (long by reference) – An upper bound on the number of elements in the block triplet form of $$\barF.$$, as used within the ACCs. (output)

Return

(long) – An upper bound on the number of elements in the block triplet form of $$\barF.$$, as used within the ACCs.

Groups
public synchronized void getaccdomain
(long accidx,
long[] domidx)


Obtains the domain appearing in the affine conic constraint.

Parameters
• accidx (long) – The index of the affine conic constraint. (input)

• domidx (long by reference) – The index of domain in the affine conic constraint. (output)

Groups
public synchronized void getaccdoty
(soltype whichsol,
long accidx,
double[] doty)

public synchronized double[] getaccdoty
(soltype whichsol,
long accidx)


Obtains the $$\dot{y}$$ vector for a solution (the dual values of an affine conic constraint).

Parameters
• whichsol (soltype) – Selects a solution. (input)

• accidx (long) – The index of the affine conic constraint. (input)

• doty (double[]) – The dual values for this affine conic constraint. The array should have length equal to the dimension of the constraint. (output)

Return

(double[]) – The dual values for this affine conic constraint. The array should have length equal to the dimension of the constraint.

Groups
public synchronized void getaccdotys
(soltype whichsol,
double[] doty)


Obtains the $$\dot{y}$$ vector for a solution (the dual values of all affine conic constraint).

Parameters
• whichsol (soltype) – Selects a solution. (input)

• doty (double[]) – The dual values of affine conic constraints. The array should have length equal to the sum of dimensions of all affine conic constraints. (output)

Groups
public synchronized void getaccfnumnz(long[] accfnnz)

public synchronized long getaccfnumnz()


If the AFEs are not added sequentially to the ACCs, then the present function gives the number of nonzero elements in the F matrix that would be implied by the ordering of AFEs within ACCs.

Parameters

accfnnz (long by reference) – Number of non-zeros in $$F$$ implied by ACCs. (output)

Return

(long) – Number of non-zeros in $$F$$ implied by ACCs.

Groups
public synchronized void getaccftrip
(long[] frow,
int[] fcol,
double[] fval)


Obtains the $$F$$ (that would be implied by the ordering of the AFEs within the ACCs) in triplet format.

Parameters
• frow (long[]) – Row indices of nonzeros in the implied F matrix. (output)

• fcol (int[]) – Column indices of nonzeros in the implied F matrix. (output)

• fval (double[]) – Values of nonzero entries in the implied F matrix. (output)

Groups
public synchronized void getaccgvector(double[] g)


If the AFEs are passed out of sequence to the ACCs, then this function can be used to obtain the vector $$g$$ of constant terms used within the ACCs.

Parameters

g (double[]) – The $$g$$ used within the ACCs as a dense vector. The length is sum of the dimensions of the ACCs. (output)

Groups
public synchronized void getaccn
(long accidx,
long[] n)

public synchronized long getaccn(long accidx)


Obtains the dimension of the affine conic constraint.

Parameters
• accidx (long) – The index of the affine conic constraint. (input)

• n (long by reference) – The dimension of the affine conic constraint (equal to the dimension of its domain). (output)

Return

(long) – The dimension of the affine conic constraint (equal to the dimension of its domain).

Groups
public synchronized String getaccname(long accidx)


Obtains the name of an affine conic constraint.

Parameters

accidx (long) – Index of an affine conic constraint. (input)

Return

(String) – Returns the required name.

Groups
public synchronized void getaccnamelen
(long accidx,
int[] len)

public synchronized int getaccnamelen(long accidx)


Obtains the length of the name of an affine conic constraint.

Parameters
• accidx (long) – Index of an affine conic constraint. (input)

• len (int by reference) – Returns the length of the indicated name. (output)

Return

(int) – Returns the length of the indicated name.

Groups
public synchronized void getaccntot(long[] n)

public synchronized long getaccntot()


Obtains the total dimension of all affine conic constraints (the sum of all their dimensions).

Parameters

n (long by reference) – The total dimension of all affine conic constraints. (output)

Return

(long) – The total dimension of all affine conic constraints.

Groups
public synchronized void getaccs
(long[] domidxlist,
long[] afeidxlist,
double[] b)


Obtains full data of all affine conic constraints. The output array domainidxlist must have at least length determined by Task.getnumacc. The output arrays afeidxlist and b must have at least length determined by Task.getaccntot.

Parameters
• domidxlist (long[]) – The list of domains appearing in all affine conic constraints. (output)

• afeidxlist (long[]) – The concatenation of index lists of affine expressions appearing in all affine conic constraints. (output)

• b (double[]) – The concatenation of vectors b appearing in all affine conic constraints. (output)

Groups
public synchronized void getacol
(int j,
int[] nzj,
int[] subj,
double[] valj)


Obtains one column of $$A$$ in a sparse format.

Parameters
• j (int) – Index of the column. (input)

• nzj (int by reference) – Number of non-zeros in the column obtained. (output)

• subj (int[]) – Row indices of the non-zeros in the column obtained. (output)

• valj (double[]) – Numerical values in the column obtained. (output)

Groups
public synchronized void getacolnumnz
(int i,
int[] nzj)

public synchronized int getacolnumnz(int i)


Obtains the number of non-zero elements in one column of $$A$$.

Parameters
• i (int) – Index of the column. (input)

• nzj (int by reference) – Number of non-zeros in the $$j$$-th column of $$A$$. (output)

Return

(int) – Number of non-zeros in the $$j$$-th column of $$A$$.

Groups
public synchronized void getacolslice
(int first,
int last,
long[] ptrb,
long[] ptre,
int[] sub,
double[] val)


Obtains a sequence of columns from $$A$$ in sparse format.

Parameters
• first (int) – Index of the first column in the sequence. (input)

• last (int) – Index of the last column in the sequence plus one. (input)

• ptrb (long[]) – ptrb[t] is an index pointing to the first element in the $$t$$-th column obtained. (output)

• ptre (long[]) – ptre[t] is an index pointing to the last element plus one in the $$t$$-th column obtained. (output)

• sub (int[]) – Contains the row subscripts. (output)

• val (double[]) – Contains the coefficient values. (output)

Groups
public synchronized void getacolslicenumnz
(int first,
int last,
long[] numnz)

public synchronized long getacolslicenumnz
(int first,
int last)


Obtains the number of non-zeros in a slice of columns of $$A$$.

Parameters
• first (int) – Index of the first column in the sequence. (input)

• last (int) – Index of the last column plus one in the sequence. (input)

• numnz (long by reference) – Number of non-zeros in the slice. (output)

Return

(long) – Number of non-zeros in the slice.

Groups
public synchronized void getacolslicetrip
(int first,
int last,
int[] subi,
int[] subj,
double[] val)


Obtains a sequence of columns from $$A$$ in sparse triplet format. The function returns the content of all columns whose index j satisfies first <= j < last. The triplets corresponding to nonzero entries are stored in the arrays subi, subj and val.

Parameters
• first (int) – Index of the first column in the sequence. (input)

• last (int) – Index of the last column in the sequence plus one. (input)

• subi (int[]) – Constraint subscripts. (output)

• subj (int[]) – Column subscripts. (output)

• val (double[]) – Values. (output)

Groups
public synchronized void getafebarfblocktriplet
(long[] numtrip,
long[] afeidx,
int[] barvaridx,
int[] subk,
int[] subl,
double[] valkl)

public synchronized long getafebarfblocktriplet
(long[] afeidx,
int[] barvaridx,
int[] subk,
int[] subl,
double[] valkl)


Obtains $$\barF$$ in block triplet form.

Parameters
• numtrip (long by reference) – Number of elements in the block triplet form. (output)

• afeidx (long[]) – Constraint index. (output)

• barvaridx (int[]) – Symmetric matrix variable index. (output)

• subk (int[]) – Block row index. (output)

• subl (int[]) – Block column index. (output)

• valkl (double[]) – The numerical value associated with each block triplet. (output)

Return

(long) – Number of elements in the block triplet form.

Groups
public synchronized void getafebarfnumblocktriplets(long[] numtrip)

public synchronized long getafebarfnumblocktriplets()


Obtains an upper bound on the number of elements in the block triplet form of $$\barF$$.

Parameters

numtrip (long by reference) – An upper bound on the number of elements in the block triplet form of $$\barF.$$ (output)

Return

(long) – An upper bound on the number of elements in the block triplet form of $$\barF.$$

Groups
public synchronized void getafebarfnumrowentries
(long afeidx,
int[] numentr)

public synchronized int getafebarfnumrowentries(long afeidx)


Obtains the number of nonzero entries in one row of $$\barF$$, that is the number of $$j$$ such that $$\barF_{\mathrm{afeidx},j}$$ is not the zero matrix.

Parameters
• afeidx (long) – Row index of $$\barF$$. (input)

• numentr (int by reference) – Number of nonzero entries in a row of $$\barF$$. (output)

Return

(int) – Number of nonzero entries in a row of $$\barF$$.

Groups
public synchronized void getafebarfrow
(long afeidx,
int[] barvaridx,
long[] ptrterm,
long[] numterm,
long[] termidx,
double[] termweight)


Obtains all nonzero entries in one row $$\barF_{\mathrm{afeidx},*}$$ of $$\barF$$. For every $$k$$ there is a nonzero entry $$\barF_{\mathrm{afeidx}, \mathrm{barvaridx}[k]}$$, which is represented as a weighted sum of $$\mathrm{numterm}[k]$$ terms. The indices in the matrix store $$E$$ and their weights for the $$k$$-th entry appear in the arrays termidx and termweight in positions

$\mathrm{ptrterm}[k],\ldots,\mathrm{ptrterm}[k]+\mathrm{numterm}[k]-1.$

The arrays should be long enough to accommodate the data; their required lengths can be obtained with Task.getafebarfrowinfo.

Parameters
• afeidx (long) – Row index of $$\barF$$. (input)

• barvaridx (int[]) – Semidefinite variable indices of nonzero entries in the row of $$\barF$$. (output)

• ptrterm (long[]) – Pointers to the start of each entry’s description. (output)

• numterm (long[]) – Number of terms in the weighted sum representation of each entry. (output)

• termidx (long[]) – Indices of semidefinite matrices from the matrix store $$E$$. (output)

• termweight (double[]) – Weights appearing in the weighted sum representations of all entries. (output)

Groups
public synchronized void getafebarfrowinfo
(long afeidx,
int[] numentr,
long[] numterm)


Obtains information about one row of $$\barF$$: the number of nonzero entries, that is the number of $$j$$ such that $$\barF_{\mathrm{afeidx},j}$$ is not the zero matrix, as well as the total number of terms in the representations of all these entries as weighted sums of matrices from $$E$$. This information provides the data sizes required for a call to Task.getafebarfrow.

Parameters
• afeidx (long) – Row index of $$\barF$$. (input)

• numentr (int by reference) – Number of nonzero entries in a row of $$\barF$$. (output)

• numterm (long by reference) – Number of terms in the weighted sums representation of the row of $$\barF$$. (output)

Groups
public synchronized void getafefnumnz(long[] numnz)

public synchronized long getafefnumnz()


Obtains the total number of nonzeros in $$F$$.

Parameters

numnz (long by reference) – Number of non-zeros in $$F$$. (output)

Return

(long) – Number of non-zeros in $$F$$.

Groups
public synchronized void getafefrow
(long afeidx,
int[] numnz,
int[] varidx,
double[] val)


Obtains one row of $$F$$ in sparse format.

Parameters
• afeidx (long) – Index of a row in $$F$$. (input)

• numnz (int by reference) – Number of non-zeros in the row obtained. (output)

• varidx (int[]) – Column indices of the non-zeros in the row obtained. (output)

• val (double[]) – Values of the non-zeros in the row obtained. (output)

Groups
public synchronized void getafefrownumnz
(long afeidx,
int[] numnz)

public synchronized int getafefrownumnz(long afeidx)


Obtains the number of nonzeros in one row of $$F$$.

Parameters
• afeidx (long) – Index of a row in $$F$$. (input)

• numnz (int by reference) – Number of non-zeros in row afeidx of $$F$$. (output)

Return

(int) – Number of non-zeros in row afeidx of $$F$$.

Groups
public synchronized void getafeftrip
(long[] afeidx,
int[] varidx,
double[] val)


Obtains the $$F$$ in triplet format.

Parameters
• afeidx (long[]) – Row indices of nonzeros. (output)

• varidx (int[]) – Column indices of nonzeros. (output)

• val (double[]) – Values of nonzero entries. (output)

Groups
public synchronized void getafeg
(long afeidx,
double[] g)

public synchronized double getafeg(long afeidx)


Obtains a single coefficient in $$g$$.

Parameters
• afeidx (long) – Index of an element in $$g$$. (input)

• g (double by reference) – The value of $$g_{\mathrm{afeidx}}$$. (output)

Return

(double) – The value of $$g_{\mathrm{afeidx}}$$.

Groups
public synchronized void getafegslice
(long first,
long last,
double[] g)


Obtains a sequence of elements from the vector $$g$$ of constant terms in the affine expressions list.

Parameters
• first (long) – First index in the sequence. (input)

• last (long) – Last index plus 1 in the sequence. (input)

• g (double[]) – The slice $$g$$ as a dense vector. The length is last-first. (output)

Groups
public synchronized void getaij
(int i,
int j,
double[] aij)

public synchronized double getaij
(int i,
int j)


Obtains a single coefficient in $$A$$.

Parameters
• i (int) – Row index of the coefficient to be returned. (input)

• j (int) – Column index of the coefficient to be returned. (input)

• aij (double by reference) – The required coefficient $$a_{i,j}$$. (output)

Return

(double) – The required coefficient $$a_{i,j}$$.

Groups
public synchronized void getapiecenumnz
(int firsti,
int lasti,
int firstj,
int lastj,
int[] numnz)

public synchronized int getapiecenumnz
(int firsti,
int lasti,
int firstj,
int lastj)


Obtains the number non-zeros in a rectangular piece of $$A$$, i.e. the number of elements in the set

$\{ (i,j)~:~ a_{i,j} \neq 0,~ \mathtt{firsti} \leq i \leq \mathtt{lasti}-1, ~\mathtt{firstj} \leq j \leq \mathtt{lastj}-1\}$

This function is not an efficient way to obtain the number of non-zeros in one row or column. In that case use the function Task.getarownumnz or Task.getacolnumnz.

Parameters
• firsti (int) – Index of the first row in the rectangular piece. (input)

• lasti (int) – Index of the last row plus one in the rectangular piece. (input)

• firstj (int) – Index of the first column in the rectangular piece. (input)

• lastj (int) – Index of the last column plus one in the rectangular piece. (input)

• numnz (int by reference) – Number of non-zero $$A$$ elements in the rectangular piece. (output)

Return

(int) – Number of non-zero $$A$$ elements in the rectangular piece.

Groups
public synchronized void getarow
(int i,
int[] nzi,
int[] subi,
double[] vali)


Obtains one row of $$A$$ in a sparse format.

Parameters
• i (int) – Index of the row. (input)

• nzi (int by reference) – Number of non-zeros in the row obtained. (output)

• subi (int[]) – Column indices of the non-zeros in the row obtained. (output)

• vali (double[]) – Numerical values of the row obtained. (output)

Groups
public synchronized void getarownumnz
(int i,
int[] nzi)

public synchronized int getarownumnz(int i)


Obtains the number of non-zero elements in one row of $$A$$.

Parameters
• i (int) – Index of the row. (input)

• nzi (int by reference) – Number of non-zeros in the $$i$$-th row of $$A$$. (output)

Return

(int) – Number of non-zeros in the $$i$$-th row of $$A$$.

Groups
public synchronized void getarowslice
(int first,
int last,
long[] ptrb,
long[] ptre,
int[] sub,
double[] val)


Obtains a sequence of rows from $$A$$ in sparse format.

Parameters
• first (int) – Index of the first row in the sequence. (input)

• last (int) – Index of the last row in the sequence plus one. (input)

• ptrb (long[]) – ptrb[t] is an index pointing to the first element in the $$t$$-th row obtained. (output)

• ptre (long[]) – ptre[t] is an index pointing to the last element plus one in the $$t$$-th row obtained. (output)

• sub (int[]) – Contains the column subscripts. (output)

• val (double[]) – Contains the coefficient values. (output)

Groups
public synchronized void getarowslicenumnz
(int first,
int last,
long[] numnz)

public synchronized long getarowslicenumnz
(int first,
int last)


Obtains the number of non-zeros in a slice of rows of $$A$$.

Parameters
• first (int) – Index of the first row in the sequence. (input)

• last (int) – Index of the last row plus one in the sequence. (input)

• numnz (long by reference) – Number of non-zeros in the slice. (output)

Return

(long) – Number of non-zeros in the slice.

Groups
public synchronized void getarowslicetrip
(int first,
int last,
int[] subi,
int[] subj,
double[] val)


Obtains a sequence of rows from $$A$$ in sparse triplet format. The function returns the content of all rows whose index i satisfies first <= i < last. The triplets corresponding to nonzero entries are stored in the arrays subi, subj and val.

Parameters
• first (int) – Index of the first row in the sequence. (input)

• last (int) – Index of the last row in the sequence plus one. (input)

• subi (int[]) – Constraint subscripts. (output)

• subj (int[]) – Column subscripts. (output)

• val (double[]) – Values. (output)

Groups
public synchronized void getatrip
(int[] subi,
int[] subj,
double[] val)


Obtains $$A$$ in sparse triplet format. The triplets corresponding to nonzero entries are stored in the arrays subi, subj and val.

Parameters
• subi (int[]) – Constraint subscripts. (output)

• subj (int[]) – Column subscripts. (output)

• val (double[]) – Values. (output)

Groups
public synchronized void getatruncatetol(double[] tolzero)


Obtains the tolerance value set with Task.putatruncatetol.

Parameters

tolzero (double[]) – All elements $$|a_{i,j}|$$ less than this tolerance is truncated to zero. (output)

Groups
public synchronized void getbarablocktriplet
(long[] num,
int[] subi,
int[] subj,
int[] subk,
int[] subl,
double[] valijkl)

public synchronized long getbarablocktriplet
(int[] subi,
int[] subj,
int[] subk,
int[] subl,
double[] valijkl)


Obtains $$\barA$$ in block triplet form.

Parameters
• num (long by reference) – Number of elements in the block triplet form. (output)

• subi (int[]) – Constraint index. (output)

• subj (int[]) – Symmetric matrix variable index. (output)

• subk (int[]) – Block row index. (output)

• subl (int[]) – Block column index. (output)

• valijkl (double[]) – The numerical value associated with each block triplet. (output)

Return

(long) – Number of elements in the block triplet form.

Groups
public synchronized void getbaraidx
(long idx,
int[] i,
int[] j,
long[] num,
long[] sub,
double[] weights)

public synchronized long getbaraidx
(long idx,
int[] i,
int[] j,
long[] sub,
double[] weights)


Obtains information about an element in $$\barA$$. Since $$\barA$$ is a sparse matrix of symmetric matrices, only the nonzero elements in $$\barA$$ are stored in order to save space. Now $$\barA$$ is stored vectorized i.e. as one long vector. This function makes it possible to obtain information such as the row index and the column index of a particular element of the vectorized form of $$\barA$$.

Please observe if one element of $$\barA$$ is inputted multiple times then it may be stored several times in vectorized form. In that case the element with the highest index is the one that is used.

Parameters
• idx (long) – Position of the element in the vectorized form. (input)

• i (int by reference) – Row index of the element at position idx. (output)

• j (int by reference) – Column index of the element at position idx. (output)

• num (long by reference) – Number of terms in weighted sum that forms the element. (output)

• sub (long[]) – A list indexes of the elements from symmetric matrix storage that appear in the weighted sum. (output)

• weights (double[]) – The weights associated with each term in the weighted sum. (output)

Return

(long) – Number of terms in weighted sum that forms the element.

Groups
public synchronized void getbaraidxij
(long idx,
int[] i,
int[] j)


Obtains information about an element in $$\barA$$. Since $$\barA$$ is a sparse matrix of symmetric matrices, only the nonzero elements in $$\barA$$ are stored in order to save space. Now $$\barA$$ is stored vectorized i.e. as one long vector. This function makes it possible to obtain information such as the row index and the column index of a particular element of the vectorized form of $$\barA$$.

Please note that if one element of $$\barA$$ is inputted multiple times then it may be stored several times in vectorized form. In that case the element with the highest index is the one that is used.

Parameters
• idx (long) – Position of the element in the vectorized form. (input)

• i (int by reference) – Row index of the element at position idx. (output)

• j (int by reference) – Column index of the element at position idx. (output)

Groups
public synchronized void getbaraidxinfo
(long idx,
long[] num)

public synchronized long getbaraidxinfo(long idx)


Each nonzero element in $$\barA_{ij}$$ is formed as a weighted sum of symmetric matrices. Using this function the number of terms in the weighted sum can be obtained. See description of Task.appendsparsesymmat for details about the weighted sum.

Parameters
• idx (long) – The internal position of the element for which information should be obtained. (input)

• num (long by reference) – Number of terms in the weighted sum that form the specified element in $$\barA$$. (output)

Return

(long) – Number of terms in the weighted sum that form the specified element in $$\barA$$.

Groups
public synchronized void getbarasparsity
(long[] numnz,
long[] idxij)


The matrix $$\barA$$ is assumed to be a sparse matrix of symmetric matrices. This implies that many of the elements in $$\barA$$ are likely to be zero matrices. Therefore, in order to save space, only nonzero elements in $$\barA$$ are stored on vectorized form. This function is used to obtain the sparsity pattern of $$\barA$$ and the position of each nonzero element in the vectorized form of $$\barA$$. From the index detailed information about each nonzero $$\barA_{i,j}$$ can be obtained using Task.getbaraidxinfo and Task.getbaraidx.

Parameters
• numnz (long by reference) – Number of nonzero elements in $$\barA$$. (output)

• idxij (long[]) – Position of each nonzero element in the vectorized form of $$\barA$$. (output)

Groups
public synchronized void getbarcblocktriplet
(long[] num,
int[] subj,
int[] subk,
int[] subl,
double[] valjkl)

public synchronized long getbarcblocktriplet
(int[] subj,
int[] subk,
int[] subl,
double[] valjkl)


Obtains $$\barC$$ in block triplet form.

Parameters
• num (long by reference) – Number of elements in the block triplet form. (output)

• subj (int[]) – Symmetric matrix variable index. (output)

• subk (int[]) – Block row index. (output)

• subl (int[]) – Block column index. (output)

• valjkl (double[]) – The numerical value associated with each block triplet. (output)

Return

(long) – Number of elements in the block triplet form.

Groups
public synchronized void getbarcidx
(long idx,
int[] j,
long[] num,
long[] sub,
double[] weights)


Obtains information about an element in $$\barC$$.

Parameters
• idx (long) – Index of the element for which information should be obtained. (input)

• j (int by reference) – Row index in $$\barC$$. (output)

• num (long by reference) – Number of terms in the weighted sum. (output)

• sub (long[]) – Elements appearing the weighted sum. (output)

• weights (double[]) – Weights of terms in the weighted sum. (output)

Groups
public synchronized void getbarcidxinfo
(long idx,
long[] num)

public synchronized long getbarcidxinfo(long idx)


Obtains the number of terms in the weighted sum that forms a particular element in $$\barC$$.

Parameters
• idx (long) – Index of the element for which information should be obtained. The value is an index of a symmetric sparse variable. (input)

• num (long by reference) – Number of terms that appear in the weighted sum that forms the requested element. (output)

Return

(long) – Number of terms that appear in the weighted sum that forms the requested element.

Groups
public synchronized void getbarcidxj
(long idx,
int[] j)


Obtains the row index of an element in $$\barC$$.

Parameters
• idx (long) – Index of the element for which information should be obtained. (input)

• j (int by reference) – Row index in $$\barC$$. (output)

Groups
public synchronized void getbarcsparsity
(long[] numnz,
long[] idxj)


Internally only the nonzero elements of $$\barC$$ are stored in a vector. This function is used to obtain the nonzero elements of $$\barC$$ and their indexes in the internal vector representation (in idx). From the index detailed information about each nonzero $$\barC_j$$ can be obtained using Task.getbarcidxinfo and Task.getbarcidx.

Parameters
• numnz (long by reference) – Number of nonzero elements in $$\barC$$. (output)

• idxj (long[]) – Internal positions of the nonzeros elements in $$\barC$$. (output)

Groups
public synchronized void getbarsj
(soltype whichsol,
int j,
double[] barsj)

public synchronized double[] getbarsj
(soltype whichsol,
int j)


Obtains the dual solution for a semidefinite variable. Only the lower triangular part of $$\barS_j$$ is returned because the matrix by construction is symmetric. The format is that the columns are stored sequentially in the natural order.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• j (int) – Index of the semidefinite variable. (input)

• barsj (double[]) – Value of $$\barS_j$$. (output)

Return

(double[]) – Value of $$\barS_j$$.

Groups

Solution - semidefinite

public synchronized void getbarsslice
(soltype whichsol,
int first,
int last,
long slicesize,

public synchronized double[] getbarsslice
(soltype whichsol,
int first,
int last,
long slicesize)


Obtains the dual solution for a sequence of semidefinite variables. The format is that matrices are stored sequentially, and in each matrix the columns are stored as in Task.getbarsj.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – Index of the first semidefinite variable in the slice. (input)

• last (int) – Index of the last semidefinite variable in the slice plus one. (input)

• slicesize (long) – Denotes the length of the array barsslice. (input)

• barsslice (double[]) – Dual solution values of symmetric matrix variables in the slice, stored sequentially. (output)

Return

(double[]) – Dual solution values of symmetric matrix variables in the slice, stored sequentially.

Groups

Solution - semidefinite

public synchronized String getbarvarname(int i)


Obtains the name of a semidefinite variable.

Parameters

i (int) – Index of the variable. (input)

Return

(String) – The requested name is copied to this buffer.

Groups
public synchronized void getbarvarnameindex
(String somename,
int[] asgn,
int[] index)

public synchronized int getbarvarnameindex
(String somename,
int[] asgn)


Obtains the index of semidefinite variable from its name.

Parameters
• somename (String) – The name of the variable. (input)

• asgn (int by reference) – Non-zero if the name somename is assigned to some semidefinite variable. (output)

• index (int by reference) – The index of a semidefinite variable with the name somename (if one exists). (output)

Return

(int) – The index of a semidefinite variable with the name somename (if one exists).

Groups
public synchronized void getbarvarnamelen
(int i,
int[] len)

public synchronized int getbarvarnamelen(int i)


Obtains the length of the name of a semidefinite variable.

Parameters
• i (int) – Index of the variable. (input)

• len (int by reference) – Returns the length of the indicated name. (output)

Return

(int) – Returns the length of the indicated name.

Groups
public synchronized void getbarxj
(soltype whichsol,
int j,
double[] barxj)

public synchronized double[] getbarxj
(soltype whichsol,
int j)


Obtains the primal solution for a semidefinite variable. Only the lower triangular part of $$\barX_j$$ is returned because the matrix by construction is symmetric. The format is that the columns are stored sequentially in the natural order.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• j (int) – Index of the semidefinite variable. (input)

• barxj (double[]) – Value of $$\barX_j$$. (output)

Return

(double[]) – Value of $$\barX_j$$.

Groups

Solution - semidefinite

public synchronized void getbarxslice
(soltype whichsol,
int first,
int last,
long slicesize,
double[] barxslice)

public synchronized double[] getbarxslice
(soltype whichsol,
int first,
int last,
long slicesize)


Obtains the primal solution for a sequence of semidefinite variables. The format is that matrices are stored sequentially, and in each matrix the columns are stored as in Task.getbarxj.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – Index of the first semidefinite variable in the slice. (input)

• last (int) – Index of the last semidefinite variable in the slice plus one. (input)

• slicesize (long) – Denotes the length of the array barxslice. (input)

• barxslice (double[]) – Solution values of symmetric matrix variables in the slice, stored sequentially. (output)

Return

(double[]) – Solution values of symmetric matrix variables in the slice, stored sequentially.

Groups

Solution - semidefinite

public synchronized void getc(double[] c)


Obtains all objective coefficients $$c$$.

Parameters

c (double[]) – Linear terms of the objective as a dense vector. The length is the number of variables. (output)

Groups
public synchronized void getcfix(double[] cfix)

public synchronized double getcfix()


Obtains the fixed term in the objective.

Parameters

cfix (double by reference) – Fixed term in the objective. (output)

Return

(double) – Fixed term in the objective.

Groups
public synchronized void getcj
(int j,
double[] cj)


Obtains one coefficient of $$c$$.

Parameters
• j (int) – Index of the variable for which the $$c$$ coefficient should be obtained. (input)

• cj (double by reference) – The value of $$c_j$$. (output)

Groups
public synchronized void getclist
(int[] subj,
double[] c)


Obtains a sequence of elements in $$c$$.

Parameters
• subj (int[]) – A list of variable indexes. (input)

• c (double[]) – Linear terms of the requested list of the objective as a dense vector. (output)

Groups
public synchronized void getconbound
(int i,
boundkey[] bk,
double[] bl,
double[] bu)


Obtains bound information for one constraint.

Parameters
• i (int) – Index of the constraint for which the bound information should be obtained. (input)

• bk (mosek.boundkey by reference) – Bound keys. (output)

• bl (double by reference) – Values for lower bounds. (output)

• bu (double by reference) – Values for upper bounds. (output)

Groups
public synchronized void getconboundslice
(int first,
int last,
boundkey[] bk,
double[] bl,
double[] bu)


Obtains bounds information for a slice of the constraints.

Parameters
• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• bk (boundkey[]) – Bound keys. (output)

• bl (double[]) – Values for lower bounds. (output)

• bu (double[]) – Values for upper bounds. (output)

Groups
public synchronized void getcone
(int k,
conetype[] ct,
double[] conepar,
int[] nummem,
int[] submem)


NOTE: This interface to conic optimization is deprecated and will be removed in a future major release. Conic problems should be specified using the affine conic constraints interface (ACC), see Sec. 6.2 (From Linear to Conic Optimization) for details.

Parameters
• k (int) – Index of the cone. (input)

• ct (mosek.conetype by reference) – Specifies the type of the cone. (output)

• conepar (double by reference) – For the power cone it denotes the exponent alpha. For other cone types it is unused and can be set to 0. (output)

• nummem (int by reference) – Number of member variables in the cone. (output)

• submem (int[]) – Variable subscripts of the members in the cone. (output)

Groups
public synchronized void getconeinfo
(int k,
conetype[] ct,
double[] conepar,
int[] nummem)


NOTE: This interface to conic optimization is deprecated and will be removed in a future major release. Conic problems should be specified using the affine conic constraints interface (ACC), see Sec. 6.2 (From Linear to Conic Optimization) for details.

Parameters
• k (int) – Index of the cone. (input)

• ct (mosek.conetype by reference) – Specifies the type of the cone. (output)

• conepar (double by reference) – For the power cone it denotes the exponent alpha. For other cone types it is unused and can be set to 0. (output)

• nummem (int by reference) – Number of member variables in the cone. (output)

Groups
public synchronized String getconename(int i)


NOTE: This interface to conic optimization is deprecated and will be removed in a future major release. Conic problems should be specified using the affine conic constraints interface (ACC), see Sec. 6.2 (From Linear to Conic Optimization) for details.

Parameters

i (int) – Index of the cone. (input)

Return

(String) – The required name.

Groups
public synchronized void getconenameindex
(String somename,
int[] asgn,
int[] index)

public synchronized int getconenameindex
(String somename,
int[] asgn)


NOTE: This interface to conic optimization is deprecated and will be removed in a future major release. Conic problems should be specified using the affine conic constraints interface (ACC), see Sec. 6.2 (From Linear to Conic Optimization) for details.

Checks whether the name somename has been assigned to any cone. If it has been assigned to a cone, then the index of the cone is reported.

Parameters
• somename (String) – The name which should be checked. (input)

• asgn (int by reference) – Is non-zero if the name somename is assigned to some cone. (output)

• index (int by reference) – If the name somename is assigned to some cone, then index is the index of the cone. (output)

Return

(int) – If the name somename is assigned to some cone, then index is the index of the cone.

Groups
public synchronized void getconenamelen
(int i,
int[] len)

public synchronized int getconenamelen(int i)


NOTE: This interface to conic optimization is deprecated and will be removed in a future major release. Conic problems should be specified using the affine conic constraints interface (ACC), see Sec. 6.2 (From Linear to Conic Optimization) for details.

Parameters
• i (int) – Index of the cone. (input)

• len (int by reference) – Returns the length of the indicated name. (output)

Return

(int) – Returns the length of the indicated name.

Groups
public synchronized String getconname(int i)


Obtains the name of a constraint.

Parameters

i (int) – Index of the constraint. (input)

Return

(String) – The required name.

Groups
public synchronized void getconnameindex
(String somename,
int[] asgn,
int[] index)

public synchronized int getconnameindex
(String somename,
int[] asgn)


Checks whether the name somename has been assigned to any constraint. If so, the index of the constraint is reported.

Parameters
• somename (String) – The name which should be checked. (input)

• asgn (int by reference) – Is non-zero if the name somename is assigned to some constraint. (output)

• index (int by reference) – If the name somename is assigned to a constraint, then index is the index of the constraint. (output)

Return

(int) – If the name somename is assigned to a constraint, then index is the index of the constraint.

Groups
public synchronized void getconnamelen
(int i,
int[] len)

public synchronized int getconnamelen(int i)


Obtains the length of the name of a constraint.

Parameters
• i (int) – Index of the constraint. (input)

• len (int by reference) – Returns the length of the indicated name. (output)

Return

(int) – Returns the length of the indicated name.

Groups
public synchronized void getcslice
(int first,
int last,
double[] c)


Obtains a sequence of elements in $$c$$.

Parameters
• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• c (double[]) – Linear terms of the requested slice of the objective as a dense vector. The length is last-first. (output)

Groups
public synchronized void getdimbarvarj
(int j,
int[] dimbarvarj)

public synchronized int getdimbarvarj(int j)


Obtains the dimension of a symmetric matrix variable.

Parameters
• j (int) – Index of the semidefinite variable whose dimension is requested. (input)

• dimbarvarj (int by reference) – The dimension of the $$j$$-th semidefinite variable. (output)

Return

(int) – The dimension of the $$j$$-th semidefinite variable.

Groups
public synchronized void getdjcafeidxlist
(long djcidx,
long[] afeidxlist)


Obtains the list of affine expression indexes in a disjunctive constraint.

Parameters
• djcidx (long) – Index of the disjunctive constraint. (input)

• afeidxlist (long[]) – List of affine expression indexes. (output)

Groups
public synchronized void getdjcb
(long djcidx,
double[] b)


Obtains the optional constant term vector of a disjunctive constraint.

Parameters
• djcidx (long) – Index of the disjunctive constraint. (input)

• b (double[]) – The vector b. (output)

Groups
public synchronized void getdjcdomainidxlist
(long djcidx,
long[] domidxlist)


Obtains the list of domain indexes in a disjunctive constraint.

Parameters
• djcidx (long) – Index of the disjunctive constraint. (input)

• domidxlist (long[]) – List of term sizes. (output)

Groups
public synchronized String getdjcname(long djcidx)


Obtains the name of a disjunctive constraint.

Parameters

djcidx (long) – Index of a disjunctive constraint. (input)

Return

(String) – Returns the required name.

Groups
public synchronized void getdjcnamelen
(long djcidx,
int[] len)

public synchronized int getdjcnamelen(long djcidx)


Obtains the length of the name of a disjunctive constraint.

Parameters
• djcidx (long) – Index of a disjunctive constraint. (input)

• len (int by reference) – Returns the length of the indicated name. (output)

Return

(int) – Returns the length of the indicated name.

Groups
public synchronized void getdjcnumafe
(long djcidx,
long[] numafe)

public synchronized long getdjcnumafe(long djcidx)


Obtains the number of affine expressions in the disjunctive constraint.

Parameters
• djcidx (long) – Index of the disjunctive constraint. (input)

• numafe (long by reference) – Number of affine expressions in the disjunctive constraint. (output)

Return

(long) – Number of affine expressions in the disjunctive constraint.

Groups
public synchronized void getdjcnumafetot(long[] numafetot)

public synchronized long getdjcnumafetot()


Obtains the total number of affine expressions in all disjunctive constraints.

Parameters

numafetot (long by reference) – Number of affine expressions in all disjunctive constraints. (output)

Return

(long) – Number of affine expressions in all disjunctive constraints.

Groups
public synchronized void getdjcnumdomain
(long djcidx,
long[] numdomain)

public synchronized long getdjcnumdomain(long djcidx)


Obtains the number of domains in the disjunctive constraint.

Parameters
• djcidx (long) – Index of the disjunctive constraint. (input)

• numdomain (long by reference) – Number of domains in the disjunctive constraint. (output)

Return

(long) – Number of domains in the disjunctive constraint.

Groups
public synchronized void getdjcnumdomaintot(long[] numdomaintot)

public synchronized long getdjcnumdomaintot()


Obtains the total number of domains in all disjunctive constraints.

Parameters

numdomaintot (long by reference) – Number of domains in all disjunctive constraints. (output)

Return

(long) – Number of domains in all disjunctive constraints.

Groups
public synchronized void getdjcnumterm
(long djcidx,
long[] numterm)

public synchronized long getdjcnumterm(long djcidx)


Obtains the number terms in the disjunctive constraint.

Parameters
• djcidx (long) – Index of the disjunctive constraint. (input)

• numterm (long by reference) – Number of terms in the disjunctive constraint. (output)

Return

(long) – Number of terms in the disjunctive constraint.

Groups
public synchronized void getdjcnumtermtot(long[] numtermtot)

public synchronized long getdjcnumtermtot()


Obtains the total number of terms in all disjunctive constraints.

Parameters

numtermtot (long by reference) – Total number of terms in all disjunctive constraints. (output)

Return

(long) – Total number of terms in all disjunctive constraints.

Groups
public synchronized void getdjcs
(long[] domidxlist,
long[] afeidxlist,
double[] b,
long[] termsizelist,
long[] numterms)


Obtains full data of all disjunctive constraints. The output arrays must have minimal lengths determined by the following methods: domainidxlist by Task.getdjcnumdomaintot, afeidxlist and b by Task.getdjcnumafetot, termsizelist by Task.getdjcnumtermtot and numterms by Task.getnumdomain.

Parameters
• domidxlist (long[]) – The concatenation of index lists of domains appearing in all disjunctive constraints. (output)

• afeidxlist (long[]) – The concatenation of index lists of affine expressions appearing in all disjunctive constraints. (output)

• b (double[]) – The concatenation of vectors b appearing in all disjunctive constraints. (output)

• termsizelist (long[]) – The concatenation of lists of term sizes appearing in all disjunctive constraints. (output)

• numterms (long[]) – The number of terms in each of the disjunctive constraints. (output)

Groups
public synchronized void getdjctermsizelist
(long djcidx,
long[] termsizelist)


Obtains the list of term sizes in a disjunctive constraint.

Parameters
• djcidx (long) – Index of the disjunctive constraint. (input)

• termsizelist (long[]) – List of term sizes. (output)

Groups
public synchronized void getdomainn
(long domidx,
long[] n)

public synchronized long getdomainn(long domidx)


Obtains the dimension of the domain.

Parameters
• domidx (long) – Index of the domain. (input)

• n (long by reference) – Dimension of the domain. (output)

Return

(long) – Dimension of the domain.

Groups
public synchronized String getdomainname(long domidx)


Obtains the name of a domain.

Parameters

domidx (long) – Index of a domain. (input)

Return

(String) – Returns the required name.

Groups
public synchronized void getdomainnamelen
(long domidx,
int[] len)

public synchronized int getdomainnamelen(long domidx)


Obtains the length of the name of a domain.

Parameters
• domidx (long) – Index of a domain. (input)

• len (int by reference) – Returns the length of the indicated name. (output)

Return

(int) – Returns the length of the indicated name.

Groups
public synchronized void getdomaintype
(long domidx,
domaintype[] domtype)

public synchronized domaintype getdomaintype(long domidx)


Returns the type of the domain.

Parameters
Return

(mosek.domaintype) – The type of the domain.

Groups
public synchronized void getdouinf
(dinfitem whichdinf,
double[] dvalue)

public synchronized double getdouinf(dinfitem whichdinf)


Obtains a double information item from the task information database.

Parameters
• whichdinf (dinfitem) – Specifies a double information item. (input)

• dvalue (double by reference) – The value of the required double information item. (output)

Return

(double) – The value of the required double information item.

Groups

Information items and statistics

public synchronized void getdouparam
(dparam param,
double[] parvalue)

public synchronized double getdouparam(dparam param)


Obtains the value of a double parameter.

Parameters
• param (dparam) – Which parameter. (input)

• parvalue (double by reference) – Parameter value. (output)

Return

(double) – Parameter value.

Groups

Parameters

public synchronized void getdualobj
(soltype whichsol,
double[] dualobj)


Computes the dual objective value associated with the solution. Note that if the solution is a primal infeasibility certificate, then the fixed term in the objective value is not included.

Moreover, since there is no dual solution associated with an integer solution, an error will be reported if the dual objective value is requested for the integer solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• dualobj (double by reference) – Objective value corresponding to the dual solution. (output)

Groups
public synchronized void getdualsolutionnorms
(soltype whichsol,
double[] nrmy,
double[] nrmslc,
double[] nrmsuc,
double[] nrmslx,
double[] nrmsux,
double[] nrmsnx,
double[] nrmbars)


Compute norms of the dual solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• nrmy (double by reference) – The norm of the $$y$$ vector. (output)

• nrmslc (double by reference) – The norm of the $$s_l^c$$ vector. (output)

• nrmsuc (double by reference) – The norm of the $$s_u^c$$ vector. (output)

• nrmslx (double by reference) – The norm of the $$s_l^x$$ vector. (output)

• nrmsux (double by reference) – The norm of the $$s_u^x$$ vector. (output)

• nrmsnx (double by reference) – The norm of the $$s_n^x$$ vector. (output)

• nrmbars (double by reference) – The norm of the $$\barS$$ vector. (output)

Groups

Solution information

public synchronized void getdviolacc
(soltype whichsol,
long[] accidxlist,
double[] viol)


Let $$(s_n^x)^*$$ be the value of variable $$(s_n^x)$$ for the specified solution. For simplicity let us assume that $$s_n^x$$ is a member of a quadratic cone, then the violation is computed as follows

$\begin{split}\left\{ \begin{array}{ll} \max(0,(\|s_n^x\|_{2:n}^*-(s_n^x)_1^*) / \sqrt{2}, & (s_n^x)^* \geq -\|(s_n^x)_{2:n}^*\|, \\ \|(s_n^x)^*\|, & \mbox{otherwise.} \end{array} \right.\end{split}$

Both when the solution is a certificate of primal infeasibility or when it is a dual feasible solution the violation should be small.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• accidxlist (long[]) – An array of indexes of conic constraints. (input)

• viol (double[]) – viol[k] is the violation of the dual solution associated with the conic constraint sub[k]. (output)

Groups

Solution information

public synchronized void getdviolbarvar
(soltype whichsol,
int[] sub,
double[] viol)


Let $$(\barS_j)^*$$ be the value of variable $$\barS_j$$ for the specified solution. Then the dual violation of the solution associated with variable $$\barS_j$$ is given by

$\max(-\lambda_{\min}(\barS_j),\ 0.0).$

Both when the solution is a certificate of primal infeasibility and when it is dual feasible solution the violation should be small.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• sub (int[]) – An array of indexes of $$\barX$$ variables. (input)

• viol (double[]) – viol[k] is the violation of the solution for the constraint $$\barS_{\mathtt{sub}[k]} \in \PSD$$. (output)

Groups

Solution information

public synchronized void getdviolcon
(soltype whichsol,
int[] sub,
double[] viol)


The violation of the dual solution associated with the $$i$$-th constraint is computed as follows

$\max( \rho( (s_l^c)_i^*,(b_l^c)_i ),\ \rho( (s_u^c)_i^*, -(b_u^c)_i ),\ |-y_i+(s_l^c)_i^*-(s_u^c)_i^*| )$

where

$\begin{split}\rho(x,l) = \left\{ \begin{array}{ll} -x, & l > -\infty , \\ |x|, & \mbox{otherwise}.\\ \end{array} \right.\end{split}$

Both when the solution is a certificate of primal infeasibility or it is a dual feasible solution the violation should be small.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• sub (int[]) – An array of indexes of constraints. (input)

• viol (double[]) – viol[k] is the violation of dual solution associated with the constraint sub[k]. (output)

Groups

Solution information

public synchronized void getdviolcones
(soltype whichsol,
int[] sub,
double[] viol)


NOTE: This interface to conic optimization is deprecated and will be removed in a future major release. Conic problems should be specified using the affine conic constraints interface (ACC), see Sec. 6.2 (From Linear to Conic Optimization) for details.

Let $$(s_n^x)^*$$ be the value of variable $$(s_n^x)$$ for the specified solution. For simplicity let us assume that $$s_n^x$$ is a member of a quadratic cone, then the violation is computed as follows

$\begin{split}\left\{ \begin{array}{ll} \max(0,(\|s_n^x\|_{2:n}^*-(s_n^x)_1^*) / \sqrt{2}, & (s_n^x)^* \geq -\|(s_n^x)_{2:n}^*\|, \\ \|(s_n^x)^*\|, & \mbox{otherwise.} \end{array} \right.\end{split}$

Both when the solution is a certificate of primal infeasibility or when it is a dual feasible solution the violation should be small.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• sub (int[]) – An array of indexes of conic constraints. (input)

• viol (double[]) – viol[k] is the violation of the dual solution associated with the conic constraint sub[k]. (output)

Groups

Solution information

public synchronized void getdviolvar
(soltype whichsol,
int[] sub,
double[] viol)


The violation of the dual solution associated with the $$j$$-th variable is computed as follows

$\max \left(\rho((s_l^x)_j^*,(b_l^x)_j),\ \rho((s_u^x)_j^*,-(b_u^x)_j),\ |\sum_{i=\idxbeg}^{\idxend{numcon}} a_{ij} y_i+(s_l^x)_j^*-(s_u^x)_j^* - \tau c_j| \right)$

where

$\begin{split}\rho(x,l) = \left\{ \begin{array}{ll} -x, & l > -\infty , \\ |x|, & \mbox{otherwise} \end{array} \right.\end{split}$

and $$\tau=0$$ if the solution is a certificate of primal infeasibility and $$\tau=1$$ otherwise. The formula for computing the violation is only shown for the linear case but is generalized appropriately for the more general problems. Both when the solution is a certificate of primal infeasibility or when it is a dual feasible solution the violation should be small.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• sub (int[]) – An array of indexes of $$x$$ variables. (input)

• viol (double[]) – viol[k] is the violation of dual solution associated with the variable sub[k]. (output)

Groups

Solution information

public synchronized void getinfeasiblesubproblem
(soltype whichsol,

public synchronized mosek.Task getinfeasiblesubproblem(soltype whichsol)


Given the solution is a certificate of primal or dual infeasibility then a primal or dual infeasible subproblem is obtained respectively. The subproblem tends to be much smaller than the original problem and hence it is easier to locate the infeasibility inspecting the subproblem than the original problem.

For the procedure to be useful it is important to assign meaningful names to constraints, variables etc. in the original task because those names will be duplicated in the subproblem.

The function is only applicable to linear and conic quadratic optimization problems.

For more information see Sec. 8.3 (Debugging infeasibility) and Sec. 14.2 (Automatic Repair of Infeasible Problems).

Parameters
Return

(Task) – A new task containing the infeasible subproblem.

Groups

Infeasibility diagnostic

public synchronized void getinfindex
(inftype inftype,
String infname,
int[] infindex)


Obtains the index of a named information item.

Parameters
• inftype (inftype) – Type of the information item. (input)

• infname (String) – Name of the information item. (input)

• infindex (int by reference) – The item index. (output)

Groups

Information items and statistics

public synchronized void getinfmax
(inftype inftype,
int[] infmax)


Obtains the maximum index of an information item of a given type inftype plus 1.

Parameters
• inftype (inftype) – Type of the information item. (input)

• infmax (int[]) – The maximum index (plus 1) requested. (output)

Groups

Information items and statistics

public synchronized void getinfname
(inftype inftype,
int whichinf,
StringBuffer infname)


Obtains the name of an information item.

Parameters
• inftype (inftype) – Type of the information item. (input)

• whichinf (int) – An information item. (input)

• infname (StringBuffer) – Name of the information item. (output)

Groups
public synchronized void getintinf
(iinfitem whichiinf,
int[] ivalue)

public synchronized int getintinf(iinfitem whichiinf)


Obtains an integer information item from the task information database.

Parameters
• whichiinf (iinfitem) – Specifies an integer information item. (input)

• ivalue (int by reference) – The value of the required integer information item. (output)

Return

(int) – The value of the required integer information item.

Groups

Information items and statistics

public synchronized void getintparam
(iparam param,
int[] parvalue)

public synchronized int getintparam(iparam param)


Obtains the value of an integer parameter.

Parameters
Return

(int) – Parameter value.

Groups

Parameters

public synchronized void getlenbarvarj
(int j,
long[] lenbarvarj)

public synchronized long getlenbarvarj(int j)


Obtains the length of the $$j$$-th semidefinite variable i.e. the number of elements in the lower triangular part.

Parameters
• j (int) – Index of the semidefinite variable whose length if requested. (input)

• lenbarvarj (long by reference) – Number of scalar elements in the lower triangular part of the semidefinite variable. (output)

Return

(long) – Number of scalar elements in the lower triangular part of the semidefinite variable.

Groups
public synchronized void getlintinf
(liinfitem whichliinf,
long[] ivalue)

public synchronized long getlintinf(liinfitem whichliinf)


Obtains a long integer information item from the task information database.

Parameters
• whichliinf (liinfitem) – Specifies a long information item. (input)

• ivalue (long by reference) – The value of the required long integer information item. (output)

Return

(long) – The value of the required long integer information item.

Groups

Information items and statistics

public synchronized void getmaxnumanz(long[] maxnumanz)

public synchronized long getmaxnumanz()


Obtains number of preallocated non-zeros in $$A$$. When this number of non-zeros is reached MOSEK will automatically allocate more space for $$A$$.

Parameters

maxnumanz (long by reference) – Number of preallocated non-zero linear matrix elements. (output)

Return

(long) – Number of preallocated non-zero linear matrix elements.

Groups
public synchronized void getmaxnumbarvar(int[] maxnumbarvar)

public synchronized int getmaxnumbarvar()


Obtains maximum number of symmetric matrix variables for which space is currently preallocated.

Parameters

maxnumbarvar (int by reference) – Maximum number of symmetric matrix variables for which space is currently preallocated. (output)

Return

(int) – Maximum number of symmetric matrix variables for which space is currently preallocated.

Groups
public synchronized void getmaxnumcon(int[] maxnumcon)


Obtains the number of preallocated constraints in the optimization task. When this number of constraints is reached MOSEK will automatically allocate more space for constraints.

Parameters

maxnumcon (int by reference) – Number of preallocated constraints in the optimization task. (output)

Groups
public synchronized void getmaxnumcone(int[] maxnumcone)


NOTE: This interface to conic optimization is deprecated and will be removed in a future major release. Conic problems should be specified using the affine conic constraints interface (ACC), see Sec. 6.2 (From Linear to Conic Optimization) for details.

Obtains the number of preallocated cones in the optimization task. When this number of cones is reached MOSEK will automatically allocate space for more cones.

Parameters

maxnumcone (int by reference) – Number of preallocated conic constraints in the optimization task. (output)

Groups
public synchronized void getmaxnumqnz(long[] maxnumqnz)


Obtains the number of preallocated non-zeros for $$Q$$ (both objective and constraints). When this number of non-zeros is reached MOSEK will automatically allocate more space for $$Q$$.

Parameters

maxnumqnz (long by reference) – Number of non-zero elements preallocated in quadratic coefficient matrices. (output)

Groups
public synchronized void getmaxnumvar(int[] maxnumvar)


Obtains the number of preallocated variables in the optimization task. When this number of variables is reached MOSEK will automatically allocate more space for variables.

Parameters

maxnumvar (int by reference) – Number of preallocated variables in the optimization task. (output)

Groups
public synchronized void getmemusage
(long[] meminuse,
long[] maxmemuse)


Parameters
• meminuse (long by reference) – Amount of memory currently used by the task. (output)

• maxmemuse (long by reference) – Maximum amount of memory used by the task until now. (output)

Groups

System, memory and debugging

public synchronized void getnumacc(long[] num)

public synchronized long getnumacc()


Obtains the number of affine conic constraints.

Parameters

num (long by reference) – The number of affine conic constraints. (output)

Return

(long) – The number of affine conic constraints.

Groups
public synchronized void getnumafe(long[] numafe)

public synchronized long getnumafe()


Obtains the number of affine expressions.

Parameters

numafe (long by reference) – Number of affine expressions. (output)

Return

(long) – Number of affine expressions.

Groups
public synchronized void getnumanz(int[] numanz)

public synchronized int getnumanz()


Obtains the number of non-zeros in $$A$$.

Parameters

numanz (int by reference) – Number of non-zero elements in the linear constraint matrix. (output)

Return

(int) – Number of non-zero elements in the linear constraint matrix.

Groups
public synchronized void getnumanz64(long[] numanz)

public synchronized long getnumanz64()


Obtains the number of non-zeros in $$A$$.

Parameters

numanz (long by reference) – Number of non-zero elements in the linear constraint matrix. (output)

Return

(long) – Number of non-zero elements in the linear constraint matrix.

Groups
public synchronized void getnumbarablocktriplets(long[] num)

public synchronized long getnumbarablocktriplets()


Obtains an upper bound on the number of elements in the block triplet form of $$\barA$$.

Parameters

num (long by reference) – An upper bound on the number of elements in the block triplet form of $$\barA.$$ (output)

Return

(long) – An upper bound on the number of elements in the block triplet form of $$\barA.$$

Groups
public synchronized void getnumbaranz(long[] nz)

public synchronized long getnumbaranz()


Get the number of nonzero elements in $$\barA$$.

Parameters

nz (long by reference) – The number of nonzero block elements in $$\barA$$ i.e. the number of $$\barA_{ij}$$ elements that are nonzero. (output)

Return

(long) – The number of nonzero block elements in $$\barA$$ i.e. the number of $$\barA_{ij}$$ elements that are nonzero.

Groups
public synchronized void getnumbarcblocktriplets(long[] num)

public synchronized long getnumbarcblocktriplets()


Obtains an upper bound on the number of elements in the block triplet form of $$\barC$$.

Parameters

num (long by reference) – An upper bound on the number of elements in the block triplet form of $$\barC.$$ (output)

Return

(long) – An upper bound on the number of elements in the block triplet form of $$\barC.$$

Groups
public synchronized void getnumbarcnz(long[] nz)

public synchronized long getnumbarcnz()


Obtains the number of nonzero elements in $$\barC$$.

Parameters

nz (long by reference) – The number of nonzeros in $$\barC$$ i.e. the number of elements $$\barC_j$$ that are nonzero. (output)

Return

(long) – The number of nonzeros in $$\barC$$ i.e. the number of elements $$\barC_j$$ that are nonzero.

Groups
public synchronized void getnumbarvar(int[] numbarvar)

public synchronized int getnumbarvar()


Obtains the number of semidefinite variables.

Parameters

numbarvar (int by reference) – Number of semidefinite variables in the problem. (output)

Return

(int) – Number of semidefinite variables in the problem.

Groups
public synchronized void getnumcon(int[] numcon)

public synchronized int getnumcon()


Obtains the number of constraints.

Parameters

numcon (int by reference) – Number of constraints. (output)

Return

(int) – Number of constraints.

Groups
public synchronized void getnumcone(int[] numcone)

public synchronized int getnumcone()


NOTE: This interface to conic optimization is deprecated and will be removed in a future major release. Conic problems should be specified using the affine conic constraints interface (ACC), see Sec. 6.2 (From Linear to Conic Optimization) for details.

Parameters

numcone (int by reference) – Number of conic constraints. (output)

Return

(int) – Number of conic constraints.

Groups
public synchronized void getnumconemem
(int k,
int[] nummem)


NOTE: This interface to conic optimization is deprecated and will be removed in a future major release. Conic problems should be specified using the affine conic constraints interface (ACC), see Sec. 6.2 (From Linear to Conic Optimization) for details.

Parameters
• k (int) – Index of the cone. (input)

• nummem (int by reference) – Number of member variables in the cone. (output)

Groups
public synchronized void getnumdjc(long[] num)

public synchronized long getnumdjc()


Obtains the number of disjunctive constraints.

Parameters

num (long by reference) – The number of disjunctive constraints. (output)

Return

(long) – The number of disjunctive constraints.

Groups
public synchronized void getnumdomain(long[] numdomain)

public synchronized long getnumdomain()


Obtain the number of domains defined.

Parameters

numdomain (long by reference) – Number of domains in the task. (output)

Return

(long) – Number of domains in the task.

Groups
public synchronized void getnumintvar(int[] numintvar)

public synchronized int getnumintvar()


Obtains the number of integer-constrained variables.

Parameters

numintvar (int by reference) – Number of integer variables. (output)

Return

(int) – Number of integer variables.

Groups
public synchronized void getnumparam
(parametertype partype,
int[] numparam)


Obtains the number of parameters of a given type.

Parameters
• partype (parametertype) – Parameter type. (input)

• numparam (int by reference) – The number of parameters of type partype. (output)

Groups
public synchronized void getnumqconknz
(int k,
long[] numqcnz)

public synchronized long getnumqconknz(int k)


Obtains the number of non-zero quadratic terms in a constraint.

Parameters
• k (int) – Index of the constraint for which the number quadratic terms should be obtained. (input)

• numqcnz (long by reference) – Number of quadratic terms. (output)

Return

(long) – Number of quadratic terms.

Groups
public synchronized void getnumqobjnz(long[] numqonz)

public synchronized long getnumqobjnz()


Obtains the number of non-zero quadratic terms in the objective.

Parameters

numqonz (long by reference) – Number of non-zero elements in the quadratic objective terms. (output)

Return

(long) – Number of non-zero elements in the quadratic objective terms.

Groups
public synchronized void getnumsymmat(long[] num)


Obtains the number of symmetric matrices stored in the vector $$E$$.

Parameters

num (long by reference) – The number of symmetric sparse matrices. (output)

Groups
public synchronized void getnumvar(int[] numvar)

public synchronized int getnumvar()


Obtains the number of variables.

Parameters

numvar (int by reference) – Number of variables. (output)

Return

(int) – Number of variables.

Groups
public synchronized String getobjname()


Obtains the name assigned to the objective function.

Return

(String) – Assigned the objective name.

Groups
public synchronized void getobjnamelen(int[] len)

public synchronized int getobjnamelen()


Obtains the length of the name assigned to the objective function.

Parameters

len (int by reference) – Assigned the length of the objective name. (output)

Return

(int) – Assigned the length of the objective name.

Groups
public synchronized void getobjsense(objsense[] sense)

public synchronized objsense getobjsense()


Gets the objective sense of the task.

Parameters
Return

(mosek.objsense) – The returned objective sense.

Groups

Problem data - linear part

public synchronized void getparammax
(parametertype partype,
int[] parammax)


Obtains the maximum index of a parameter of type partype plus 1.

Parameters
• partype (parametertype) – Parameter type. (input)

• parammax (int by reference) – The maximum index (plus 1) of the given parameter type. (output)

Groups

Parameters

public synchronized void getparamname
(parametertype partype,
int param,
StringBuffer parname)


Obtains the name for a parameter param of type partype.

Parameters
• partype (parametertype) – Parameter type. (input)

• param (int) – Which parameter. (input)

• parname (StringBuffer) – Parameter name. (output)

Groups
public synchronized void getpowerdomainalpha
(long domidx,
double[] alpha)


Obtains the exponent vector $$\alpha$$ of a primal or dual power cone domain.

Parameters
• domidx (long) – Index of the domain. (input)

• alpha (double[]) – The vector $$\alpha$$. (output)

Groups
public synchronized void getpowerdomaininfo
(long domidx,
long[] n,
long[] nleft)


Obtains structural information about a primal or dual power cone domain.

Parameters
• domidx (long) – Index of the domain. (input)

• n (long by reference) – Dimension of the domain. (output)

• nleft (long by reference) – Number of variables on the left hand side. (output)

Groups
public synchronized void getprimalobj
(soltype whichsol,
double[] primalobj)

public synchronized double getprimalobj(soltype whichsol)


Computes the primal objective value for the desired solution. Note that if the solution is an infeasibility certificate, then the fixed term in the objective is not included.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• primalobj (double by reference) – Objective value corresponding to the primal solution. (output)

Return

(double) – Objective value corresponding to the primal solution.

Groups
public synchronized void getprimalsolutionnorms
(soltype whichsol,
double[] nrmxc,
double[] nrmxx,
double[] nrmbarx)


Compute norms of the primal solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• nrmxc (double by reference) – The norm of the $$x^c$$ vector. (output)

• nrmxx (double by reference) – The norm of the $$x$$ vector. (output)

• nrmbarx (double by reference) – The norm of the $$\barX$$ vector. (output)

Groups

Solution information

public synchronized void getprobtype(problemtype[] probtype)

public synchronized problemtype getprobtype()


Obtains the problem type.

Parameters
Return

(mosek.problemtype) – The problem type.

Groups

public synchronized void getprosta
(soltype whichsol,
prosta[] problemsta)

public synchronized prosta getprosta(soltype whichsol)


Obtains the problem status.

Parameters
Return

(mosek.prosta) – Problem status.

Groups

Solution information

public synchronized void getpviolacc
(soltype whichsol,
long[] accidxlist,
double[] viol)


Computes the primal solution violation for a set of affine conic constraints. Let $$x^*$$ be the value of the variable $$x$$ for the specified solution. For simplicity let us assume that $$x$$ is a member of a quadratic cone, then the violation is computed as follows

$\begin{split}\left\{ \begin{array}{ll} \max(0,\|x_{2:n}\|-x_1) / \sqrt{2}, & x_1 \geq -\|x_{2:n}\|, \\ \|x\|, & \mbox{otherwise.} \end{array} \right.\end{split}$

Both when the solution is a certificate of dual infeasibility or when it is primal feasible the violation should be small.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• accidxlist (long[]) – An array of indexes of conic constraints. (input)

• viol (double[]) – viol[k] is the violation of the solution associated with the affine conic constraint number accidxlist[k]. (output)

Groups

Solution information

public synchronized void getpviolbarvar
(soltype whichsol,
int[] sub,
double[] viol)


Computes the primal solution violation for a set of semidefinite variables. Let $$(\barX_j)^*$$ be the value of the variable $$\barX_j$$ for the specified solution. Then the primal violation of the solution associated with variable $$\barX_j$$ is given by

$\max(-\lambda_{\min}(\barX_j),\ 0.0).$

Both when the solution is a certificate of dual infeasibility or when it is primal feasible the violation should be small.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• sub (int[]) – An array of indexes of $$\barX$$ variables. (input)

• viol (double[]) – viol[k] is how much the solution violates the constraint $$\barX_{\mathtt{sub}[k]} \in \PSD$$. (output)

Groups

Solution information

public synchronized void getpviolcon
(soltype whichsol,
int[] sub,
double[] viol)


Computes the primal solution violation for a set of constraints. The primal violation of the solution associated with the $$i$$-th constraint is given by

$\max(\tau l_i^c - (x_i^c)^*,\ (x_i^c)^* - \tau u_i^c),\ |\sum_{j=\idxbeg}^{\idxend{numvar}} a_{ij} x_j^* - x_i^c|)$

where $$\tau=0$$ if the solution is a certificate of dual infeasibility and $$\tau=1$$ otherwise. Both when the solution is a certificate of dual infeasibility and when it is primal feasible the violation should be small. The above formula applies for the linear case but is appropriately generalized in other cases.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• sub (int[]) – An array of indexes of constraints. (input)

• viol (double[]) – viol[k] is the violation associated with the solution for the constraint sub[k]. (output)

Groups

Solution information

public synchronized void getpviolcones
(soltype whichsol,
int[] sub,
double[] viol)


NOTE: This interface to conic optimization is deprecated and will be removed in a future major release. Conic problems should be specified using the affine conic constraints interface (ACC), see Sec. 6.2 (From Linear to Conic Optimization) for details.

Computes the primal solution violation for a set of conic constraints. Let $$x^*$$ be the value of the variable $$x$$ for the specified solution. For simplicity let us assume that $$x$$ is a member of a quadratic cone, then the violation is computed as follows

$\begin{split}\left\{ \begin{array}{ll} \max(0,\|x_{2:n}\|-x_1) / \sqrt{2}, & x_1 \geq -\|x_{2:n}\|, \\ \|x\|, & \mbox{otherwise.} \end{array} \right.\end{split}$

Both when the solution is a certificate of dual infeasibility or when it is primal feasible the violation should be small.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• sub (int[]) – An array of indexes of conic constraints. (input)

• viol (double[]) – viol[k] is the violation of the solution associated with the conic constraint number sub[k]. (output)

Groups

Solution information

public synchronized void getpvioldjc
(soltype whichsol,
long[] djcidxlist,
double[] viol)


Computes the primal solution violation for a set of disjunctive constraints. For a single DJC the violation is defined as

$\mathrm{viol}\left(\bigvee_{i=1}^t \bigwedge_{j=1}^{s_i} T_{i,j}\right) = \min_{i=1,\ldots,t}\left(\max_{j=1,\ldots,s_j}(\mathrm{viol}(T_{i,j}))\right)$

where the violation of each simple term $$T_{i,j}$$ is defined as for an ordinary linear constraint.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• djcidxlist (long[]) – An array of indexes of disjunctive constraints. (input)

• viol (double[]) – viol[k] is the violation of the solution associated with the disjunctive constraint number djcidxlist[k]. (output)

Groups

Solution information

public synchronized void getpviolvar
(soltype whichsol,
int[] sub,
double[] viol)


Computes the primal solution violation associated to a set of variables. Let $$x_j^*$$ be the value of $$x_j$$ for the specified solution. Then the primal violation of the solution associated with variable $$x_j$$ is given by

$\max( \tau l_j^x - x_j^*,\ x_j^* - \tau u_j^x,\ 0).$

where $$\tau=0$$ if the solution is a certificate of dual infeasibility and $$\tau=1$$ otherwise. Both when the solution is a certificate of dual infeasibility and when it is primal feasible the violation should be small.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• sub (int[]) – An array of indexes of $$x$$ variables. (input)

• viol (double[]) – viol[k] is the violation associated with the solution for the variable $$x_\mathtt{sub[k]}$$. (output)

Groups

Solution information

public synchronized void getqconk
(int k,
long[] numqcnz,
int[] qcsubi,
int[] qcsubj,
double[] qcval)

public synchronized long getqconk
(int k,
int[] qcsubi,
int[] qcsubj,
double[] qcval)


Obtains all the quadratic terms in a constraint. The quadratic terms are stored sequentially in qcsubi, qcsubj, and qcval.

Parameters
• k (int) – Which constraint. (input)

• numqcnz (long by reference) – Number of quadratic terms. (output)

• qcsubi (int[]) – Row subscripts for quadratic constraint matrix. (output)

• qcsubj (int[]) – Column subscripts for quadratic constraint matrix. (output)

• qcval (double[]) – Quadratic constraint coefficient values. (output)

Return

(long) – Number of quadratic terms.

Groups
public synchronized void getqobj
(long[] numqonz,
int[] qosubi,
int[] qosubj,
double[] qoval)


Obtains the quadratic terms in the objective. The required quadratic terms are stored sequentially in qosubi, qosubj, and qoval.

Parameters
• numqonz (long by reference) – Number of non-zero elements in the quadratic objective terms. (output)

• qosubi (int[]) – Row subscripts for quadratic objective coefficients. (output)

• qosubj (int[]) – Column subscripts for quadratic objective coefficients. (output)

• qoval (double[]) – Quadratic objective coefficient values. (output)

Groups
public synchronized void getqobjij
(int i,
int j,
double[] qoij)


Obtains one coefficient $$q_{ij}^o$$ in the quadratic term of the objective.

Parameters
• i (int) – Row index of the coefficient. (input)

• j (int) – Column index of coefficient. (input)

• qoij (double by reference) – The required coefficient. (output)

Groups
public synchronized void getreducedcosts
(soltype whichsol,
int first,
int last,
double[] redcosts)


Computes the reduced costs for a slice of variables and returns them in the array redcosts i.e.

(15.2)$\mathtt{redcosts}[j-\mathtt{first}] = (s_l^x)_j-(s_u^x)_j, ~j=\mathtt{first},\ldots,\mathtt{last}-1$
Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – The index of the first variable in the sequence. (input)

• last (int) – The index of the last variable in the sequence plus 1. (input)

• redcosts (double[]) – The reduced costs for the required slice of variables. (output)

Groups

Solution - dual

public synchronized void getskc
(soltype whichsol,
stakey[] skc)

public synchronized mosek.stakey[] getskc(soltype whichsol)


Obtains the status keys for the constraints.

Parameters
Return

(stakey[]) – Status keys for the constraints.

Groups

Solution information

public synchronized void getskcslice
(soltype whichsol,
int first,
int last,
stakey[] skc)

public synchronized mosek.stakey[] getskcslice
(soltype whichsol,
int first,
int last)


Obtains the status keys for a slice of the constraints.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• skc (stakey[]) – Status keys for the constraints. (output)

Return

(stakey[]) – Status keys for the constraints.

Groups

Solution information

public synchronized void getskn
(soltype whichsol,
stakey[] skn)

public synchronized mosek.stakey[] getskn(soltype whichsol)


Obtains the status keys for the conic constraints.

Parameters
Return

(stakey[]) – Status keys for the conic constraints.

Groups

Solution information

public synchronized void getskx
(soltype whichsol,
stakey[] skx)

public synchronized mosek.stakey[] getskx(soltype whichsol)


Obtains the status keys for the scalar variables.

Parameters
Return

(stakey[]) – Status keys for the variables.

Groups

Solution information

public synchronized void getskxslice
(soltype whichsol,
int first,
int last,
stakey[] skx)

public synchronized mosek.stakey[] getskxslice
(soltype whichsol,
int first,
int last)


Obtains the status keys for a slice of the scalar variables.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• skx (stakey[]) – Status keys for the variables. (output)

Return

(stakey[]) – Status keys for the variables.

Groups

Solution information

public synchronized void getslc
(soltype whichsol,
double[] slc)

public synchronized double[] getslc(soltype whichsol)


Obtains the $$s_l^c$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• slc (double[]) – Dual variables corresponding to the lower bounds on the constraints. (output)

Return

(double[]) – Dual variables corresponding to the lower bounds on the constraints.

Groups

Solution - dual

public synchronized void getslcslice
(soltype whichsol,
int first,
int last,
double[] slc)

public synchronized double[] getslcslice
(soltype whichsol,
int first,
int last)


Obtains a slice of the $$s_l^c$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• slc (double[]) – Dual variables corresponding to the lower bounds on the constraints. (output)

Return

(double[]) – Dual variables corresponding to the lower bounds on the constraints.

Groups

Solution - dual

public synchronized void getslx
(soltype whichsol,
double[] slx)

public synchronized double[] getslx(soltype whichsol)


Obtains the $$s_l^x$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• slx (double[]) – Dual variables corresponding to the lower bounds on the variables. (output)

Return

(double[]) – Dual variables corresponding to the lower bounds on the variables.

Groups

Solution - dual

public synchronized void getslxslice
(soltype whichsol,
int first,
int last,
double[] slx)

public synchronized double[] getslxslice
(soltype whichsol,
int first,
int last)


Obtains a slice of the $$s_l^x$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• slx (double[]) – Dual variables corresponding to the lower bounds on the variables. (output)

Return

(double[]) – Dual variables corresponding to the lower bounds on the variables.

Groups

Solution - dual

public synchronized void getsnx
(soltype whichsol,
double[] snx)

public synchronized double[] getsnx(soltype whichsol)


Obtains the $$s_n^x$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• snx (double[]) – Dual variables corresponding to the conic constraints on the variables. (output)

Return

(double[]) – Dual variables corresponding to the conic constraints on the variables.

Groups

Solution - dual

public synchronized void getsnxslice
(soltype whichsol,
int first,
int last,
double[] snx)

public synchronized double[] getsnxslice
(soltype whichsol,
int first,
int last)


Obtains a slice of the $$s_n^x$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• snx (double[]) – Dual variables corresponding to the conic constraints on the variables. (output)

Return

(double[]) – Dual variables corresponding to the conic constraints on the variables.

Groups

Solution - dual

public synchronized void getsolsta
(soltype whichsol,
solsta[] solutionsta)

public synchronized solsta getsolsta(soltype whichsol)


Obtains the solution status.

Parameters
Return

(mosek.solsta) – Solution status.

Groups

Solution information

public synchronized void getsolution
(soltype whichsol,
prosta[] problemsta,
solsta[] solutionsta,
stakey[] skc,
stakey[] skx,
stakey[] skn,
double[] xc,
double[] xx,
double[] y,
double[] slc,
double[] suc,
double[] slx,
double[] sux,
double[] snx)


Obtains the complete solution.

Consider the case of linear programming. The primal problem is given by

$\begin{split}\begin{array}{lccccl} \mbox{minimize} & & & c^T x+c^f & & \\ \mbox{subject to} & l^c & \leq & A x & \leq & u^c, \\ & l^x & \leq & x & \leq & u^x. \\ \end{array}\end{split}$

and the corresponding dual problem is

$\begin{split}\begin{array}{lccl} \mbox{maximize} & (l^c)^T s_l^c - (u^c)^T s_u^c & \\ & + (l^x)^T s_l^x - (u^x)^T s_u^x + c^f & \\ \mbox{subject to} & A^T y + s_l^x - s_u^x & = & c, \\ & -y + s_l^c - s_u^c & = & 0, \\ & s_l^c,s_u^c,s_l^x,s_u^x \geq 0. & & \\ \end{array}\end{split}$

A conic optimization problem has the same primal variables as in the linear case. Recall that the dual of a conic optimization problem is given by:

$\begin{split}\begin{array}{lccccc} \mbox{maximize} & (l^c)^T s_l^c - (u^c)^T s_u^c & & \\ & +(l^x)^T s_l^x - (u^x)^T s_u^x + c^f & & \\ \mbox{subject to} & A^T y + s_l^x - s_u^x + s_n^x & = & c, \\ & -y + s_l^c - s_u^c & = & 0, \\ & s_l^c,s_u^c,s_l^x,s_u^x & \geq & 0, \\ & s_n^x \in \K^* & & \\ \end{array}\end{split}$

The mapping between variables and arguments to the function is as follows:

• xx : Corresponds to variable $$x$$ (also denoted $$x^x$$).

• xc : Corresponds to $$x^c:=Ax$$.

• y : Corresponds to variable $$y$$.

• slc: Corresponds to variable $$s_l^c$$.

• suc: Corresponds to variable $$s_u^c$$.

• slx: Corresponds to variable $$s_l^x$$.

• sux: Corresponds to variable $$s_u^x$$.

• snx: Corresponds to variable $$s_n^x$$.

The meaning of the values returned by this function depend on the solution status returned in the argument solsta. The most important possible values of solsta are:

In order to retrieve the primal and dual values of semidefinite variables see Task.getbarxj and Task.getbarsj.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• problemsta (mosek.prosta by reference) – Problem status. (output)

• solutionsta (mosek.solsta by reference) – Solution status. (output)

• skc (stakey[]) – Status keys for the constraints. (output)

• skx (stakey[]) – Status keys for the variables. (output)

• skn (stakey[]) – Status keys for the conic constraints. (output)

• xc (double[]) – Primal constraint solution. (output)

• xx (double[]) – Primal variable solution. (output)

• y (double[]) – Vector of dual variables corresponding to the constraints. (output)

• slc (double[]) – Dual variables corresponding to the lower bounds on the constraints. (output)

• suc (double[]) – Dual variables corresponding to the upper bounds on the constraints. (output)

• slx (double[]) – Dual variables corresponding to the lower bounds on the variables. (output)

• sux (double[]) – Dual variables corresponding to the upper bounds on the variables. (output)

• snx (double[]) – Dual variables corresponding to the conic constraints on the variables. (output)

Groups
public synchronized void getsolutioninfo
(soltype whichsol,
double[] pobj,
double[] pviolcon,
double[] pviolvar,
double[] pviolbarvar,
double[] pviolcone,
double[] pviolitg,
double[] dobj,
double[] dviolcon,
double[] dviolvar,
double[] dviolbarvar,
double[] dviolcone)


Parameters
Groups

Solution information

public synchronized void getsolutioninfonew
(soltype whichsol,
double[] pobj,
double[] pviolcon,
double[] pviolvar,
double[] pviolbarvar,
double[] pviolcone,
double[] pviolacc,
double[] pvioldjc,
double[] pviolitg,
double[] dobj,
double[] dviolcon,
double[] dviolvar,
double[] dviolbarvar,
double[] dviolcone,
double[] dviolacc)


Parameters
Groups

Solution information

public synchronized void getsolutionnew
(soltype whichsol,
prosta[] problemsta,
solsta[] solutionsta,
stakey[] skc,
stakey[] skx,
stakey[] skn,
double[] xc,
double[] xx,
double[] y,
double[] slc,
double[] suc,
double[] slx,
double[] sux,
double[] snx,
double[] doty)


Obtains the complete solution. See Task.getsolution for further information.

In order to retrieve the primal and dual values of semidefinite variables see Task.getbarxj and Task.getbarsj.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• problemsta (mosek.prosta by reference) – Problem status. (output)

• solutionsta (mosek.solsta by reference) – Solution status. (output)

• skc (stakey[]) – Status keys for the constraints. (output)

• skx (stakey[]) – Status keys for the variables. (output)

• skn (stakey[]) – Status keys for the conic constraints. (output)

• xc (double[]) – Primal constraint solution. (output)

• xx (double[]) – Primal variable solution. (output)

• y (double[]) – Vector of dual variables corresponding to the constraints. (output)

• slc (double[]) – Dual variables corresponding to the lower bounds on the constraints. (output)

• suc (double[]) – Dual variables corresponding to the upper bounds on the constraints. (output)

• slx (double[]) – Dual variables corresponding to the lower bounds on the variables. (output)

• sux (double[]) – Dual variables corresponding to the upper bounds on the variables. (output)

• snx (double[]) – Dual variables corresponding to the conic constraints on the variables. (output)

• doty (double[]) – Dual variables corresponding to affine conic constraints. (output)

Groups
public synchronized void getsolutionslice
(soltype whichsol,
solitem solitem,
int first,
int last,
double[] values)


Obtains a slice of one item from the solution. The format of the solution is exactly as in Task.getsolution. The parameter solitem determines which of the solution vectors should be returned.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• solitem (solitem) – Which part of the solution is required. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• values (double[]) – The values in the required sequence are stored sequentially in values. (output)

Groups
public synchronized void getsparsesymmat
(long idx,
int[] subi,
int[] subj,
double[] valij)


Get a single symmetric matrix from the matrix store.

Parameters
• idx (long) – Index of the matrix to retrieve. (input)

• subi (int[]) – Row subscripts of the matrix non-zero elements. (output)

• subj (int[]) – Column subscripts of the matrix non-zero elements. (output)

• valij (double[]) – Coefficients of the matrix non-zero elements. (output)

Groups
public synchronized String getstrparam
(sparam param,
int[] len)


Obtains the value of a string parameter.

Parameters
• param (sparam) – Which parameter. (input)

• len (int by reference) – The length of the parameter value. (output)

Return

(String) – Parameter value.

Groups
public synchronized void getstrparamlen
(sparam param,
int[] len)

public synchronized int getstrparamlen(sparam param)


Obtains the length of a string parameter.

Parameters
• param (sparam) – Which parameter. (input)

• len (int by reference) – The length of the parameter value. (output)

Return

(int) – The length of the parameter value.

Groups
public synchronized void getsuc
(soltype whichsol,
double[] suc)

public synchronized double[] getsuc(soltype whichsol)


Obtains the $$s_u^c$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• suc (double[]) – Dual variables corresponding to the upper bounds on the constraints. (output)

Return

(double[]) – Dual variables corresponding to the upper bounds on the constraints.

Groups

Solution - dual

public synchronized void getsucslice
(soltype whichsol,
int first,
int last,
double[] suc)

public synchronized double[] getsucslice
(soltype whichsol,
int first,
int last)


Obtains a slice of the $$s_u^c$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• suc (double[]) – Dual variables corresponding to the upper bounds on the constraints. (output)

Return

(double[]) – Dual variables corresponding to the upper bounds on the constraints.

Groups

Solution - dual

public synchronized void getsux
(soltype whichsol,
double[] sux)

public synchronized double[] getsux(soltype whichsol)


Obtains the $$s_u^x$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• sux (double[]) – Dual variables corresponding to the upper bounds on the variables. (output)

Return

(double[]) – Dual variables corresponding to the upper bounds on the variables.

Groups

Solution - dual

public synchronized void getsuxslice
(soltype whichsol,
int first,
int last,
double[] sux)

public synchronized double[] getsuxslice
(soltype whichsol,
int first,
int last)


Obtains a slice of the $$s_u^x$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• sux (double[]) – Dual variables corresponding to the upper bounds on the variables. (output)

Return

(double[]) – Dual variables corresponding to the upper bounds on the variables.

Groups

Solution - dual

public synchronized void getsymmatinfo
(long idx,
int[] dim,
long[] nz,
symmattype[] mattype)


MOSEK maintains a vector denoted by $$E$$ of symmetric data matrices. This function makes it possible to obtain important information about a single matrix in $$E$$.

Parameters
• idx (long) – Index of the matrix for which information is requested. (input)

• dim (int by reference) – Returns the dimension of the requested matrix. (output)

• nz (long by reference) – Returns the number of non-zeros in the requested matrix. (output)

• mattype (mosek.symmattype by reference) – Returns the type of the requested matrix. (output)

Groups
public synchronized String gettaskname()


Obtains the name assigned to the task.

Return

(String) – Returns the task name.

Groups
public synchronized void gettasknamelen(int[] len)

public synchronized int gettasknamelen()


Obtains the length the task name.

Parameters

len (int by reference) – Returns the length of the task name. (output)

Return

(int) – Returns the length of the task name.

Groups
public synchronized void getvarbound
(int i,
boundkey[] bk,
double[] bl,
double[] bu)


Obtains bound information for one variable.

Parameters
• i (int) – Index of the variable for which the bound information should be obtained. (input)

• bk (mosek.boundkey by reference) – Bound keys. (output)

• bl (double by reference) – Values for lower bounds. (output)

• bu (double by reference) – Values for upper bounds. (output)

Groups
public synchronized void getvarboundslice
(int first,
int last,
boundkey[] bk,
double[] bl,
double[] bu)


Obtains bounds information for a slice of the variables.

Parameters
• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• bk (boundkey[]) – Bound keys. (output)

• bl (double[]) – Values for lower bounds. (output)

• bu (double[]) – Values for upper bounds. (output)

Groups
public synchronized String getvarname(int j)


Obtains the name of a variable.

Parameters

j (int) – Index of a variable. (input)

Return

(String) – Returns the required name.

Groups
public synchronized void getvarnameindex
(String somename,
int[] asgn,
int[] index)

public synchronized int getvarnameindex
(String somename,
int[] asgn)


Checks whether the name somename has been assigned to any variable. If so, the index of the variable is reported.

Parameters
• somename (String) – The name which should be checked. (input)

• asgn (int by reference) – Is non-zero if the name somename is assigned to a variable. (output)

• index (int by reference) – If the name somename is assigned to a variable, then index is the index of the variable. (output)

Return

(int) – If the name somename is assigned to a variable, then index is the index of the variable.

Groups
public synchronized void getvarnamelen
(int i,
int[] len)

public synchronized int getvarnamelen(int i)


Obtains the length of the name of a variable.

Parameters
• i (int) – Index of a variable. (input)

• len (int by reference) – Returns the length of the indicated name. (output)

Return

(int) – Returns the length of the indicated name.

Groups
public synchronized void getvartype
(int j,
variabletype[] vartype)

public synchronized variabletype getvartype(int j)


Gets the variable type of one variable.

Parameters
Return

(mosek.variabletype) – Variable type of the $$j$$-th variable.

Groups
public synchronized void getvartypelist
(int[] subj,
variabletype[] vartype)


Obtains the variable type of one or more variables. Upon return vartype[k] is the variable type of variable subj[k].

Parameters
• subj (int[]) – A list of variable indexes. (input)

• vartype (variabletype[]) – The variables types corresponding to the variables specified by subj. (output)

Groups
public synchronized void getxc
(soltype whichsol,
double[] xc)

public synchronized double[] getxc(soltype whichsol)


Obtains the $$x^c$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• xc (double[]) – Primal constraint solution. (output)

Return

(double[]) – Primal constraint solution.

Groups

Solution - primal

public synchronized void getxcslice
(soltype whichsol,
int first,
int last,
double[] xc)

public synchronized double[] getxcslice
(soltype whichsol,
int first,
int last)


Obtains a slice of the $$x^c$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• xc (double[]) – Primal constraint solution. (output)

Return

(double[]) – Primal constraint solution.

Groups

Solution - primal

public synchronized void getxx
(soltype whichsol,
double[] xx)

public synchronized double[] getxx(soltype whichsol)


Obtains the $$x^x$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• xx (double[]) – Primal variable solution. (output)

Return

(double[]) – Primal variable solution.

Groups

Solution - primal

public synchronized void getxxslice
(soltype whichsol,
int first,
int last,
double[] xx)

public synchronized double[] getxxslice
(soltype whichsol,
int first,
int last)


Obtains a slice of the $$x^x$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• xx (double[]) – Primal variable solution. (output)

Return

(double[]) – Primal variable solution.

Groups

Solution - primal

public synchronized void gety
(soltype whichsol,
double[] y)

public synchronized double[] gety(soltype whichsol)


Obtains the $$y$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• y (double[]) – Vector of dual variables corresponding to the constraints. (output)

Return

(double[]) – Vector of dual variables corresponding to the constraints.

Groups

Solution - dual

public synchronized void getyslice
(soltype whichsol,
int first,
int last,
double[] y)

public synchronized double[] getyslice
(soltype whichsol,
int first,
int last)


Obtains a slice of the $$y$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• y (double[]) – Vector of dual variables corresponding to the constraints. (output)

Return

(double[]) – Vector of dual variables corresponding to the constraints.

Groups

Solution - dual

public synchronized void infeasibilityreport
(streamtype whichstream,
soltype whichsol)


Prints the infeasibility report to an output stream.

Parameters
Groups

Infeasibility diagnostic

public synchronized void initbasissolve(int[] basis)


Prepare a task for use with the Task.solvewithbasis function.

This function should be called

If the basis is singular i.e. not invertible, then the error rescode.err_basis_singular is reported.

Parameters

basis (int[]) – The array of basis indexes to use. The array is interpreted as follows: If $$\mathtt{basis}[i] \leq \idxend{numcon}$$, then $$x_{\mathtt{basis}[i]}^c$$ is in the basis at position $$i$$, otherwise $$x_{\mathtt{basis}[i]-\mathtt{numcon}}$$ is in the basis at position $$i$$. (output)

Groups

Solving systems with basis matrix

public synchronized void inputdata
(int maxnumcon,
int maxnumvar,
double[] c,
double cfix,
int[] aptrb,
int[] aptre,
int[] asub,
double[] aval,
boundkey[] bkc,
double[] blc,
double[] buc,
boundkey[] bkx,
double[] blx,
double[] bux)

public synchronized void inputdata
(int maxnumcon,
int maxnumvar,
double[] c,
double cfix,
long[] aptrb,
long[] aptre,
int[] asub,
double[] aval,
boundkey[] bkc,
double[] blc,
double[] buc,
boundkey[] bkx,
double[] blx,
double[] bux)


Input the linear part of an optimization task in one function call.

Parameters
• maxnumcon (int) – Number of preallocated constraints in the optimization task. (input)

• maxnumvar (int) – Number of preallocated variables in the optimization task. (input)

• c (double[]) – Linear terms of the objective as a dense vector. The length is the number of variables. (input)

• cfix (double) – Fixed term in the objective. (input)

• aptrb (int[]) – Row or column start pointers. (input)

• aptrb (long[]) – Row or column start pointers. (input)

• aptre (int[]) – Row or column end pointers. (input)

• aptre (long[]) – Row or column end pointers. (input)

• asub (int[]) – Coefficient subscripts. (input)

• aval (double[]) – Coefficient values. (input)

• bkc (boundkey[]) – Bound keys for the constraints. (input)

• blc (double[]) – Lower bounds for the constraints. (input)

• buc (double[]) – Upper bounds for the constraints. (input)

• bkx (boundkey[]) – Bound keys for the variables. (input)

• blx (double[]) – Lower bounds for the variables. (input)

• bux (double[]) – Upper bounds for the variables. (input)

Groups
public synchronized void isdouparname
(String parname,
dparam[] param)


Checks whether parname is a valid double parameter name.

Parameters
• parname (String) – Parameter name. (input)

• param (mosek.dparam by reference) – Returns the parameter corresponding to the name, if one exists. (output)

Groups
public synchronized void isintparname
(String parname,
iparam[] param)


Checks whether parname is a valid integer parameter name.

Parameters
• parname (String) – Parameter name. (input)

• param (mosek.iparam by reference) – Returns the parameter corresponding to the name, if one exists. (output)

Groups
public synchronized void isstrparname
(String parname,
sparam[] param)


Checks whether parname is a valid string parameter name.

Parameters
• parname (String) – Parameter name. (input)

• param (mosek.sparam by reference) – Returns the parameter corresponding to the name, if one exists. (output)

Groups
public synchronized void linkfiletostream
(streamtype whichstream,
String filename,
int append)


Directs all output from a task stream whichstream to a file filename.

Parameters
• whichstream (streamtype) – Index of the stream. (input)

• filename (String) – A valid file name. (input)

• append (int) – If this argument is 0 the output file will be overwritten, otherwise it will be appended to. (input)

Groups

Logging

public synchronized void onesolutionsummary
(streamtype whichstream,
soltype whichsol)


Prints a short summary of a specified solution.

Parameters
Groups
public synchronized void optimize(rescode[] trmcode)

public synchronized rescode optimize()


Calls the optimizer. Depending on the problem type and the selected optimizer this will call one of the optimizers in MOSEK. By default the interior point optimizer will be selected for continuous problems. The optimizer may be selected manually by setting the parameter iparam.optimizer.

Parameters
Return

(mosek.rescode) – Is either rescode.ok or a termination response code.

Groups

Optimization

public synchronized void optimizermt
String accesstoken,
rescode[] trmcode)


Offload the optimization task to an instance of OptServer specified by addr, which should be a valid URL, for example http://server:port or https://server:port. The call will block until a result is available or the connection closes.

If the server requires authentication, the authentication token can be passed in the accesstoken argument.

If the server requires encryption, the keys can be passed using one of the solver parameters sparam.remote_tls_cert or sparam.remote_tls_cert_path.

Parameters
Groups

Remote optimization

public synchronized void optimizersummary(streamtype whichstream)


Prints a short summary with optimizer statistics from last optimization.

Parameters

whichstream (streamtype) – Index of the stream. (input)

Groups

Logging

public synchronized void primalrepair
(double[] wlc,
double[] wuc,
double[] wlx,
double[] wux)


The function repairs a primal infeasible optimization problem by adjusting the bounds on the constraints and variables where the adjustment is computed as the minimal weighted sum of relaxations to the bounds on the constraints and variables. Observe the function only repairs the problem but does not solve it. If an optimal solution is required the problem should be optimized after the repair.

The function is applicable to linear and conic problems possibly with integer variables.

Observe that when computing the minimal weighted relaxation the termination tolerance specified by the parameters of the task is employed. For instance the parameter iparam.mio_mode can be used to make MOSEK ignore the integer constraints during the repair which usually leads to a much faster repair. However, the drawback is of course that the repaired problem may not have an integer feasible solution.

Note the function modifies the task in place. If this is not desired, then apply the function to a cloned task.

Parameters
• wlc (double[]) – $$(w_l^c)_i$$ is the weight associated with relaxing the lower bound on constraint $$i$$. If the weight is negative, then the lower bound is not relaxed. Moreover, if the argument is NULL, then all the weights are assumed to be $$1$$. (input)

• wuc (double[]) – $$(w_u^c)_i$$ is the weight associated with relaxing the upper bound on constraint $$i$$. If the weight is negative, then the upper bound is not relaxed. Moreover, if the argument is NULL, then all the weights are assumed to be $$1$$. (input)

• wlx (double[]) – $$(w_l^x)_j$$ is the weight associated with relaxing the lower bound on variable $$j$$. If the weight is negative, then the lower bound is not relaxed. Moreover, if the argument is NULL, then all the weights are assumed to be $$1$$. (input)

• wux (double[]) – $$(w_l^x)_i$$ is the weight associated with relaxing the upper bound on variable $$j$$. If the weight is negative, then the upper bound is not relaxed. Moreover, if the argument is NULL, then all the weights are assumed to be $$1$$. (input)

Groups

Infeasibility diagnostic

public synchronized void primalsensitivity
(int[] subi,
mark[] marki,
int[] subj,
mark[] markj,
double[] leftpricei,
double[] rightpricei,
double[] leftrangei,
double[] rightrangei,
double[] leftpricej,
double[] rightpricej,
double[] leftrangej,
double[] rightrangej)


Calculates sensitivity information for bounds on variables and constraints. For details on sensitivity analysis, the definitions of shadow price and linearity interval and an example see Section Sensitivity Analysis.

The type of sensitivity analysis to be performed (basis or optimal partition) is controlled by the parameter iparam.sensitivity_type.

Parameters
• subi (int[]) – Indexes of constraints to analyze. (input)

• marki (mark[]) – The value of marki[i] indicates for which bound of constraint subi[i] sensitivity analysis is performed. If marki[i] = mark.up the upper bound of constraint subi[i] is analyzed, and if marki[i] = mark.lo the lower bound is analyzed. If subi[i] is an equality constraint, either mark.lo or mark.up can be used to select the constraint for sensitivity analysis. (input)

• subj (int[]) – Indexes of variables to analyze. (input)

• markj (mark[]) – The value of markj[j] indicates for which bound of variable subj[j] sensitivity analysis is performed. If markj[j] = mark.up the upper bound of variable subj[j] is analyzed, and if markj[j] = mark.lo the lower bound is analyzed. If subj[j] is a fixed variable, either mark.lo or mark.up can be used to select the bound for sensitivity analysis. (input)

• leftpricei (double[]) – leftpricei[i] is the left shadow price for the bound marki[i] of constraint subi[i]. (output)

• rightpricei (double[]) – rightpricei[i] is the right shadow price for the bound marki[i] of constraint subi[i]. (output)

• leftrangei (double[]) – leftrangei[i] is the left range $$\beta_1$$ for the bound marki[i] of constraint subi[i]. (output)

• rightrangei (double[]) – rightrangei[i] is the right range $$\beta_2$$ for the bound marki[i] of constraint subi[i]. (output)

• leftpricej (double[]) – leftpricej[j] is the left shadow price for the bound markj[j] of variable subj[j]. (output)

• rightpricej (double[]) – rightpricej[j] is the right shadow price for the bound markj[j] of variable subj[j]. (output)

• leftrangej (double[]) – leftrangej[j] is the left range $$\beta_1$$ for the bound markj[j] of variable subj[j]. (output)

• rightrangej (double[]) – rightrangej[j] is the right range $$\beta_2$$ for the bound markj[j] of variable subj[j]. (output)

Groups

Sensitivity analysis

public synchronized void putacc
(long accidx,
long domidx,
long[] afeidxlist,
double[] b)


Puts an affine conic constraint. This method overwrites an existing affine conic constraint number accidx with new data specified in the same format as in Task.appendacc.

Parameters
• accidx (long) – Affine conic constraint index. (input)

• domidx (long) – Domain index. (input)

• afeidxlist (long[]) – List of affine expression indexes. (input)

• b (double[]) – The vector of constant terms added to affine expressions. Optional, can be NULL. (input)

Groups

Problem data - affine conic constraints

public synchronized void putaccb
(long accidx,
double[] b)


Updates an existing affine conic constraint number accidx by putting a new vector $$b$$.

Parameters
• accidx (long) – Affine conic constraint index. (input)

• b (double[]) – The vector of constant terms added to affine expressions. Optional, can be NULL. (input)

Groups

Problem data - affine conic constraints

public synchronized void putaccbj
(long accidx,
long j,
double bj)


Sets one value $$b[j]$$ in the $$b$$ vector for the affine conic constraint number accidx.

Parameters
• accidx (long) – Affine conic constraint index. (input)

• j (long) – The index of an element in b to change. (input)

• bj (double) – The new value of $$b[j]$$. (input)

Groups

Problem data - affine conic constraints

public synchronized void putaccdoty
(soltype whichsol,
long accidx,
double[] doty)


Puts the $$\dot{y}$$ vector for a solution (the dual values of an affine conic constraint).

Parameters
• whichsol (soltype) – Selects a solution. (input)

• accidx (long) – The index of the affine conic constraint. (input)

• doty (double[]) – The dual values for this affine conic constraint. The array should have length equal to the dimension of the constraint. (output)

Groups
public synchronized void putacclist
(long[] accidxs,
long[] domidxs,
long[] afeidxlist,
double[] b)


Puts affine conic constraints. This method overwrites existing affine conic constraints whose numbers are provided in the list accidxs with new data which is a concatenation of individual constraint descriptions in the same format as in Task.appendacc (see also Task.appendaccs).

Parameters
• accidxs (long[]) – Affine conic constraint indices. (input)

• domidxs (long[]) – Domain indices. (input)

• afeidxlist (long[]) – List of affine expression indexes. (input)

• b (double[]) – The vector of constant terms added to affine expressions. Optional, can be NULL. (input)

Groups

Problem data - affine conic constraints

public synchronized void putaccname
(long accidx,
String name)


Sets the name of an affine conic constraint.

Parameters
• accidx (long) – Index of the affine conic constraint. (input)

• name (String) – The name of the affine conic constraint. (input)

Groups
public synchronized void putacol
(int j,
int[] subj,
double[] valj)


Change one column of the linear constraint matrix $$A$$. Resets all the elements in column $$j$$ to zero and then sets

$a_{\mathtt{subj}[k],\mathtt{j}} = \mathtt{valj}[k], \quad k=0,\ldots,\mathtt{nzj}-1.$
Parameters
• j (int) – Index of a column in $$A$$. (input)

• subj (int[]) – Row indexes of non-zero values in column $$j$$ of $$A$$. (input)

• valj (double[]) – New non-zero values of column $$j$$ in $$A$$. (input)

Groups

Problem data - linear part

public synchronized void putacollist
(int[] sub,
int[] ptrb,
int[] ptre,
int[] asub,
double[] aval)


Change a set of columns in the linear constraint matrix $$A$$ with data in sparse triplet format. The requested columns are set to zero and then updated with:

$\begin{split}\begin{array}{rl} \mathtt{for} & i=\idxbeg,\ldots,\idxend{num}\\ & a_{\mathtt{asub}[k],\mathtt{sub}[i]} = \mathtt{aval}[k],\quad k=\mathtt{ptrb}[i],\ldots,\mathtt{ptre}[i]-1. \end{array}\end{split}$
Parameters
• sub (int[]) – Indexes of columns that should be replaced, no duplicates. (input)

• ptrb (int[]) – Array of pointers to the first element in each column. (input)

• ptre (int[]) – Array of pointers to the last element plus one in each column. (input)

• asub (int[]) – Row indexes of new elements. (input)

• aval (double[]) – Coefficient values. (input)

Groups

Problem data - linear part

public synchronized void putacolslice
(int first,
int last,
int[] ptrb,
int[] ptre,
int[] asub,
double[] aval)

public synchronized void putacolslice
(int first,
int last,
long[] ptrb,
long[] ptre,
int[] asub,
double[] aval)


Change a slice of columns in the linear constraint matrix $$A$$ with data in sparse triplet format. The requested columns are set to zero and then updated with:

$\begin{split}\begin{array}{rl} \mathtt{for} & i=\mathtt{first},\ldots,\mathtt{last}-1\\ & a_{\mathtt{asub}[k],i} = \mathtt{aval}[k],\quad k=\mathtt{ptrb}[i-\mathtt{first}],\ldots,\mathtt{ptre}[i-\mathtt{first}]-1. \end{array}\end{split}$
Parameters
• first (int) – First column in the slice. (input)

• last (int) – Last column plus one in the slice. (input)

• ptrb (int[]) – Array of pointers to the first element in each column. (input)

• ptrb (long[]) – Array of pointers to the first element in each column. (input)

• ptre (int[]) – Array of pointers to the last element plus one in each column. (input)

• ptre (long[]) – Array of pointers to the last element plus one in each column. (input)

• asub (int[]) – Row indexes of new elements. (input)

• aval (double[]) – Coefficient values. (input)

Groups

Problem data - linear part

public synchronized void putafebarfblocktriplet
(long[] afeidx,
int[] barvaridx,
int[] subk,
int[] subl,
double[] valkl)


Inputs the $$\barF$$ matrix data in block triplet form.

Parameters
• afeidx (long[]) – Constraint index. (input)

• barvaridx (int[]) – Symmetric matrix variable index. (input)

• subk (int[]) – Block row index. (input)

• subl (int[]) – Block column index. (input)

• valkl (double[]) – The numerical value associated with each block triplet. (input)

Groups
public synchronized void putafebarfentry
(long afeidx,
int barvaridx,
long[] termidx,
double[] termweight)


This function sets one entry $$\barF_{ij}$$ where $$i=\mathrm{afeidx}$$ is the row index in the store of affine expressions and $$j=\mathrm{barvaridx}$$ is the index of a symmetric variable. That is, the expression

$\langle \barF_{ij}, \barX_j\rangle$

will be added to the $$i$$-th affine expression.

The matrix $$\barF_{ij}$$ is specified as a weighted sum of symmetric matrices from the symmetric matrix storage $$E$$, so $$\barF_{ij}$$ is a symmetric matrix, precisely:

$\barF_{\mathrm{afeidx},\mathrm{barvaridx}} = \sum_{k} \mathrm{termweight}[k] \cdot E_{\mathrm{termidx}[k]}.$

By default all elements in $$\barF$$ are 0, so only non-zero elements need be added. Setting the same entry again will overwrite the earlier entry.

The symmetric matrices from $$E$$ are defined separately using the function Task.appendsparsesymmat.

Parameters
• afeidx (long) – Row index of $$\barF$$. (input)

• barvaridx (int) – Semidefinite variable index. (input)

• termidx (long[]) – Indices in $$E$$ of the matrices appearing in the weighted sum for the $$\barF$$ entry being specified. (input)

• termweight (double[]) – termweight[k] is the coefficient of the termidx[k]-th element of $$E$$ in the weighted sum the $$\barF$$ entry being specified. (input)

Groups
public synchronized void putafebarfentrylist
(long[] afeidx,
int[] barvaridx,
long[] numterm,
long[] ptrterm,
long[] termidx,
double[] termweight)


This function sets a list of entries in $$\barF$$. Each entry should be described as in Task.putafebarfentry and all those descriptions should be combined (for example concatenated) in the input to this method. That means the $$k$$-th entry set will have row index afeidx[k], symmetric variable index barvaridx[k] and the description of this term consists of indices in $$E$$ and weights appearing in positions

$\mathrm{ptrterm}[k],\ldots,\mathrm{ptrterm}[k] + \mathrm{lenterm}[k] - 1$

in the corresponding arrays termidx and termweight. See Task.putafebarfentry for details.

Parameters
• afeidx (long[]) – Row indexes of $$\barF$$. (input)

• barvaridx (int[]) – Semidefinite variable indexes. (input)

• numterm (long[]) – The number of terms in the weighted sums that form each entry. (input)

• ptrterm (long[]) – The pointer to the beginning of the description of each entry. (input)

• termidx (long[]) – Concatenated lists of indices in $$E$$ of the matrices appearing in the weighted sums for the $$\barF$$ being specified. (input)

• termweight (double[]) – Concatenated lists of weights appearing in the weighted sums forming the $$\barF$$ elements being specified. (input)

Groups
public synchronized void putafebarfrow
(long afeidx,
int[] barvaridx,
long[] numterm,
long[] ptrterm,
long[] termidx,
double[] termweight)


This function inputs one row in $$\barF$$. It first clears the row, i.e. sets $$\barF_{\mathrm{afeidx},*}=0$$ and then sets the new entries. Each entry should be described as in Task.putafebarfentry and all those descriptions should be combined (for example concatenated) in the input to this method. That means the $$k$$-th entry set will have row index afeidx, symmetric variable index barvaridx[k] and the description of this term consists of indices in $$E$$ and weights appearing in positions

$\mathrm{ptrterm}[k],\ldots,\mathrm{ptrterm}[k] + \mathrm{numterm}[k] - 1$

in the corresponding arrays termidx and termweight. See Task.putafebarfentry for details.

Parameters
• afeidx (long) – Row index of $$\barF$$. (input)

• barvaridx (int[]) – Semidefinite variable indexes. (input)

• numterm (long[]) – The number of terms in the weighted sums that form each entry. (input)

• ptrterm (long[]) – The pointer to the beginning of the description of each entry. (input)

• termidx (long[]) – Concatenated lists of indices in $$E$$ of the matrices appearing in the weighted sums for the $$\barF$$ entries in the row. (input)

• termweight (double[]) – Concatenated lists of weights appearing in the weighted sums forming the $$\barF$$ entries in the row. (input)

Groups
public synchronized void putafefcol
(int varidx,
long[] afeidx,
double[] val)


Change one column of the matrix $$F$$ of affine expressions. Resets all the elements in column varidx to zero and then sets

$F_{\mathtt{afeidx}[k],\mathtt{varidx}} = \mathtt{val}[k], \quad k=0,\ldots,\mathtt{numnz}-1.$
Parameters
• varidx (int) – Index of a column in $$F$$. (input)

• afeidx (long[]) – Row indexes of non-zero values in the column of $$F$$. (input)

• val (double[]) – New non-zero values in the column of $$F$$. (input)

Groups

Problem data - affine expressions

public synchronized void putafefentry
(long afeidx,
int varidx,
double value)


Replaces one entry in the affine expression store $$F$$, that is it sets:

$F_{\mathrm{afeidx}, \mathrm{varidx}} = \mathrm{value}.$
Parameters
• afeidx (long) – Row index in $$F$$. (input)

• varidx (int) – Column index in $$F$$. (input)

• value (double) – Value of $$F_{\mathrm{afeidx},\mathrm{varidx}}$$. (input)

Groups

Problem data - affine expressions

public synchronized void putafefentrylist
(long[] afeidx,
int[] varidx,
double[] val)


Replaces a number of entries in the affine expression store $$F$$, that is it sets:

$F_{\mathrm{afeidxs}[k], \mathrm{varidx}[k]} = \mathrm{val}[k]$

for all $$k$$.

Parameters
• afeidx (long[]) – Row indices in $$F$$. (input)

• varidx (int[]) – Column indices in $$F$$. (input)

• val (double[]) – Values of the entries in $$F$$. (input)

Groups

Problem data - affine expressions

public synchronized void putafefrow
(long afeidx,
int[] varidx,
double[] val)


Change one row of the matrix $$F$$ of affine expressions. Resets all the elements in row afeidx to zero and then sets

$F_{\mathtt{afeidx},\mathtt{varidx}[k]} = \mathtt{val}[k], \quad k=0,\ldots,\mathtt{numnz}-1.$
Parameters
• afeidx (long) – Index of a row in $$F$$. (input)

• varidx (int[]) – Column indexes of non-zero values in the row of $$F$$. (input)

• val (double[]) – New non-zero values in the row of $$F$$. (input)

Groups

Problem data - affine expressions

public synchronized void putafefrowlist
(long[] afeidx,
int[] numnzrow,
long[] ptrrow,
int[] varidx,
double[] val)


Clears and then changes a number of rows of the matrix $$F$$ of affine expressions. The $$k$$-th of the rows to be changed has index $$i = \mathrm{afeidx}[k]$$, contains $$\mathrm{numnzrow}[k]$$ nonzeros and its description as in Task.putafefrow starts in position $$\mathrm{ptrrow}[k]$$ of the arrays varidx and val. Formally, the row with index $$i$$ is cleared and then set as:

$F_{i,\mathrm{varidx}[\mathrm{ptrrow}[k]+j]} = \mathrm{val}[\mathrm{ptrrow}[k] + j], \quad j=0,\ldots,\mathrm{numnzrow}[k]-1.$
Parameters
• afeidx (long[]) – Indices of rows in $$F$$. (input)

• numnzrow (int[]) – Number of non-zeros in each of the modified rows of $$F$$. (input)

• ptrrow (long[]) – Pointer to the first nonzero in each row of $$F$$. (input)

• varidx (int[]) – Column indexes of non-zero values. (input)

• val (double[]) – New non-zero values in the rows of $$F$$. (input)

Groups

Problem data - affine expressions

public synchronized void putafeg
(long afeidx,
double g)


Change one element of the vector $$g$$ in affine expressions i.e.

$g_{\mathtt{afeidx}} = \mathtt{gi}.$
Parameters
• afeidx (long) – Index of an entry in $$g$$. (input)

• g (double) – New value for $$g_{\mathrm{afeidx}}$$. (input)

Groups

Problem data - affine expressions

public synchronized void putafeglist
(long[] afeidx,
double[] g)


Changes a list of elements of the vector $$g$$ in affine expressions i.e. for all $$k$$ it sets

$g_{\mathrm{afeidx}[k]} = \mathrm{glist}[k].$
Parameters
• afeidx (long[]) – Indices of entries in $$g$$. (input)

• g (double[]) – New values for $$g$$. (input)

Groups

Problem data - affine expressions

public synchronized void putafegslice
(long first,
long last,
double[] slice)


Modifies a slice in the vector $$g$$ of constant terms in affine expressions using the principle

$g_{\mathtt{j}} = \mathtt{slice[j-first]}, \quad j=\mathrm{first},..,\idxend{\mathrm{last}}$
Parameters
• first (long) – First index in the sequence. (input)

• last (long) – Last index plus 1 in the sequence. (input)

• slice (double[]) – The slice of $$g$$ as a dense vector. The length is last-first. (input)

Groups

Problem data - affine expressions

public synchronized void putaij
(int i,
int j,
double aij)


Changes a coefficient in the linear coefficient matrix $$A$$ using the method

$a_{i,j} = \mathtt{aij}.$
Parameters
• i (int) – Constraint (row) index. (input)

• j (int) – Variable (column) index. (input)

• aij (double) – New coefficient for $$a_{i,j}$$. (input)

Groups

Problem data - linear part

public synchronized void putaijlist
(int[] subi,
int[] subj,
double[] valij)


Changes one or more coefficients in $$A$$ using the method

$a_{\mathtt{subi[k]},\mathtt{subj[k]}} = \mathtt{valij[k]}, \quad k=\idxbeg,\ldots,\idxend{num}.$

Duplicates are not allowed.

Parameters
• subi (int[]) – Constraint (row) indices. (input)

• subj (int[]) – Variable (column) indices. (input)

• valij (double[]) – New coefficient values for $$a_{i,j}$$. (input)

Groups

Problem data - linear part

public synchronized void putarow
(int i,
int[] subi,
double[] vali)


Change one row of the linear constraint matrix $$A$$. Resets all the elements in row $$i$$ to zero and then sets

$a_{\mathtt{i},\mathtt{subi}[k]} = \mathtt{vali}[k], \quad k=0,\ldots,\mathtt{nzi}-1.$
Parameters
• i (int) – Index of a row in $$A$$. (input)

• subi (int[]) – Column indexes of non-zero values in row $$i$$ of $$A$$. (input)

• vali (double[]) – New non-zero values of row $$i$$ in $$A$$. (input)

Groups

Problem data - linear part

public synchronized void putarowlist
(int[] sub,
int[] ptrb,
int[] ptre,
int[] asub,
double[] aval)

public synchronized void putarowlist
(int[] sub,
long[] ptrb,
long[] ptre,
int[] asub,
double[] aval)


Change a set of rows in the linear constraint matrix $$A$$ with data in sparse triplet format. The requested rows are set to zero and then updated with:

$\begin{split}\begin{array}{rl} \mathtt{for} & i=\idxbeg,\ldots,\idxend{num} \\ & a_{\mathtt{sub}[i],\mathtt{asub}[k]} = \mathtt{aval}[k],\quad k=\mathtt{ptrb}[i],\ldots,\mathtt{ptre}[i]-1. \end{array}\end{split}$
Parameters
• sub (int[]) – Indexes of rows that should be replaced, no duplicates. (input)

• ptrb (int[]) – Array of pointers to the first element in each row. (input)

• ptrb (long[]) – Array of pointers to the first element in each row. (input)

• ptre (int[]) – Array of pointers to the last element plus one in each row. (input)

• ptre (long[]) – Array of pointers to the last element plus one in each row. (input)

• asub (int[]) – Column indexes of new elements. (input)

• aval (double[]) – Coefficient values. (input)

Groups

Problem data - linear part

public synchronized void putarowslice
(int first,
int last,
int[] ptrb,
int[] ptre,
int[] asub,
double[] aval)

public synchronized void putarowslice
(int first,
int last,
long[] ptrb,
long[] ptre,
int[] asub,
double[] aval)


Change a slice of rows in the linear constraint matrix $$A$$ with data in sparse triplet format. The requested rows are set to zero and then updated with:

$\begin{split}\begin{array}{rl} \mathtt{for} & i=\mathtt{first},\ldots,\mathtt{last}-1 \\ & a_{i,\mathtt{asub}[k]} = \mathtt{aval}[k],\quad k=\mathtt{ptrb}[i-\mathtt{first}],\ldots,\mathtt{ptre}[i-\mathtt{first}]-1. \end{array}\end{split}$
Parameters
• first (int) – First row in the slice. (input)

• last (int) – Last row plus one in the slice. (input)

• ptrb (int[]) – Array of pointers to the first element in each row. (input)

• ptrb (long[]) – Array of pointers to the first element in each row. (input)

• ptre (int[]) – Array of pointers to the last element plus one in each row. (input)

• ptre (long[]) – Array of pointers to the last element plus one in each row. (input)

• asub (int[]) – Column indexes of new elements. (input)

• aval (double[]) – Coefficient values. (input)

Groups

Problem data - linear part

public synchronized void putatruncatetol(double tolzero)


Truncates (sets to zero) all elements in $$A$$ that satisfy

$|a_{i,j}| \leq \mathtt{tolzero}.$
Parameters

tolzero (double) – Truncation tolerance. (input)

Groups

Problem data - linear part

public synchronized void putbarablocktriplet
(int[] subi,
int[] subj,
int[] subk,
int[] subl,
double[] valijkl)


Inputs the $$\barA$$ matrix in block triplet form.

Parameters
• subi (int[]) – Constraint index. (input)

• subj (int[]) – Symmetric matrix variable index. (input)

• subk (int[]) – Block row index. (input)

• subl (int[]) – Block column index. (input)

• valijkl (double[]) – The numerical value associated with each block triplet. (input)

Groups

Problem data - semidefinite

public synchronized void putbaraij
(int i,
int j,
long[] sub,
double[] weights)


This function sets one element in the $$\barA$$ matrix.

Each element in the $$\barA$$ matrix is a weighted sum of symmetric matrices from the symmetric matrix storage $$E$$, so $$\barA_{ij}$$ is a symmetric matrix. By default all elements in $$\barA$$ are 0, so only non-zero elements need be added. Setting the same element again will overwrite the earlier entry.

The symmetric matrices from $$E$$ are defined separately using the function Task.appendsparsesymmat.

Parameters
• i (int) – Row index of $$\barA$$. (input)

• j (int) – Column index of $$\barA$$. (input)

• sub (long[]) – Indices in $$E$$ of the matrices appearing in the weighted sum for $$\barA_{ij}$$. (input)

• weights (double[]) – weights[k] is the coefficient of the sub[k]-th element of $$E$$ in the weighted sum forming $$\barA_{ij}$$. (input)

Groups

Problem data - semidefinite

public synchronized void putbaraijlist
(int[] subi,
int[] subj,
long[] alphaptrb,
long[] alphaptre,
long[] matidx,
double[] weights)


This function sets a list of elements in the $$\barA$$ matrix.

Each element in the $$\barA$$ matrix is a weighted sum of symmetric matrices from the symmetric matrix storage $$E$$, so $$\barA_{ij}$$ is a symmetric matrix. By default all elements in $$\barA$$ are 0, so only non-zero elements need be added. Setting the same element again will overwrite the earlier entry.

The symmetric matrices from $$E$$ are defined separately using the function Task.appendsparsesymmat.

Parameters
• subi (int[]) – Row index of $$\barA$$. (input)

• subj (int[]) – Column index of $$\barA$$. (input)

• alphaptrb (long[]) – Start entries for terms in the weighted sum that forms $$\barA_{ij}$$. (input)

• alphaptre (long[]) – End entries for terms in the weighted sum that forms $$\barA_{ij}$$. (input)

• matidx (long[]) – Indices in $$E$$ of the matrices appearing in the weighted sum for $$\barA_{ij}$$. (input)

• weights (double[]) – weights[k] is the coefficient of the sub[k]-th element of $$E$$ in the weighted sum forming $$\barA_{ij}$$. (input)

Groups

Problem data - semidefinite

public synchronized void putbararowlist
(int[] subi,
long[] ptrb,
long[] ptre,
int[] subj,
long[] nummat,
long[] matidx,
double[] weights)


This function replaces a list of rows in the $$\barA$$ matrix.

Parameters
• subi (int[]) – Row indexes of $$\barA$$. (input)

• ptrb (long[]) – Start of rows in $$\barA$$. (input)

• ptre (long[]) – End of rows in $$\barA$$. (input)

• subj (int[]) – Column index of $$\barA$$. (input)

• nummat (long[]) – Number of entries in weighted sum of matrixes. (input)

• matidx (long[]) – Matrix indexes for weighted sum of matrixes. (input)

• weights (double[]) – Weights for weighted sum of matrixes. (input)

Groups

Problem data - semidefinite

public synchronized void putbarcblocktriplet
(int[] subj,
int[] subk,
int[] subl,
double[] valjkl)


Inputs the $$\barC$$ matrix in block triplet form.

Parameters
• subj (int[]) – Symmetric matrix variable index. (input)

• subk (int[]) – Block row index. (input)

• subl (int[]) – Block column index. (input)

• valjkl (double[]) – The numerical value associated with each block triplet. (input)

Groups

Problem data - semidefinite

public synchronized void putbarcj
(int j,
long[] sub,
double[] weights)


This function sets one entry in the $$\barC$$ vector.

Each element in the $$\barC$$ vector is a weighted sum of symmetric matrices from the symmetric matrix storage $$E$$, so $$\barC_{j}$$ is a symmetric matrix. By default all elements in $$\barC$$ are 0, so only non-zero elements need be added. Setting the same element again will overwrite the earlier entry.

The symmetric matrices from $$E$$ are defined separately using the function Task.appendsparsesymmat.

Parameters
• j (int) – Index of the element in $$\barC$$ that should be changed. (input)

• sub (long[]) – Indices in $$E$$ of matrices appearing in the weighted sum for $$\barC_j$$ (input)

• weights (double[]) – weights[k] is the coefficient of the sub[k]-th element of $$E$$ in the weighted sum forming $$\barC_j$$. (input)

Groups
public synchronized void putbarsj
(soltype whichsol,
int j,
double[] barsj)


Sets the dual solution for a semidefinite variable.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• j (int) – Index of the semidefinite variable. (input)

• barsj (double[]) – Value of $$\barS_j$$. Format as in Task.getbarsj. (input)

Groups

Solution - semidefinite

public synchronized void putbarvarname
(int j,
String name)


Sets the name of a semidefinite variable.

Parameters
• j (int) – Index of the variable. (input)

• name (String) – The variable name. (input)

Groups
public synchronized void putbarxj
(soltype whichsol,
int j,
double[] barxj)


Sets the primal solution for a semidefinite variable.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• j (int) – Index of the semidefinite variable. (input)

• barxj (double[]) – Value of $$\barX_j$$. Format as in Task.getbarxj. (input)

Groups

Solution - semidefinite

public synchronized void putcfix(double cfix)


Replaces the fixed term in the objective by a new one.

Parameters

cfix (double) – Fixed term in the objective. (input)

Groups
public synchronized void putcj
(int j,
double cj)


Modifies one coefficient in the linear objective vector $$c$$, i.e.

$c_{\mathtt{j}} = \mathtt{cj}.$

If the absolute value exceeds dparam.data_tol_c_huge an error is generated. If the absolute value exceeds dparam.data_tol_cj_large, a warning is generated, but the coefficient is inputted as specified.

Parameters
• j (int) – Index of the variable for which $$c$$ should be changed. (input)

• cj (double) – New value of $$c_j$$. (input)

Groups
public synchronized void putclist
(int[] subj,
double[] val)


Modifies the coefficients in the linear term $$c$$ in the objective using the principle

$c_{\mathtt{subj[t]}} = \mathtt{val[t]}, \quad t=\idxbeg,\ldots,\idxend{num}.$

If a variable index is specified multiple times in subj only the last entry is used. Data checks are performed as in Task.putcj.

Parameters
• subj (int[]) – Indices of variables for which the coefficient in $$c$$ should be changed. (input)

• val (double[]) – New numerical values for coefficients in $$c$$ that should be modified. (input)

Groups
public synchronized void putconbound
(int i,
boundkey bkc,
double blc,
double buc)


Changes the bounds for one constraint.

If the bound value specified is numerically larger than dparam.data_tol_bound_inf it is considered infinite and the bound key is changed accordingly. If a bound value is numerically larger than dparam.data_tol_bound_wrn, a warning will be displayed, but the bound is inputted as specified.

Parameters
• i (int) – Index of the constraint. (input)

• bkc (boundkey) – New bound key. (input)

• blc (double) – New lower bound. (input)

• buc (double) – New upper bound. (input)

Groups
public synchronized void putconboundlist
(int[] sub,
boundkey[] bkc,
double[] blc,
double[] buc)


Changes the bounds for a list of constraints. If multiple bound changes are specified for a constraint, then only the last change takes effect. Data checks are performed as in Task.putconbound.

Parameters
• sub (int[]) – List of constraint indexes. (input)

• bkc (boundkey[]) – Bound keys for the constraints. (input)

• blc (double[]) – Lower bounds for the constraints. (input)

• buc (double[]) – Upper bounds for the constraints. (input)

Groups
public synchronized void putconboundlistconst
(int[] sub,
boundkey bkc,
double blc,
double buc)


Changes the bounds for one or more constraints. Data checks are performed as in Task.putconbound.

Parameters
• sub (int[]) – List of constraint indexes. (input)

• bkc (boundkey) – New bound key for all constraints in the list. (input)

• blc (double) – New lower bound for all constraints in the list. (input)

• buc (double) – New upper bound for all constraints in the list. (input)

Groups
public synchronized void putconboundslice
(int first,
int last,
boundkey[] bkc,
double[] blc,
double[] buc)


Changes the bounds for a slice of the constraints. Data checks are performed as in Task.putconbound.

Parameters
• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• bkc (boundkey[]) – Bound keys for the constraints. (input)

• blc (double[]) – Lower bounds for the constraints. (input)

• buc (double[]) – Upper bounds for the constraints. (input)

Groups
public synchronized void putconboundsliceconst
(int first,
int last,
boundkey bkc,
double blc,
double buc)


Changes the bounds for a slice of the constraints. Data checks are performed as in Task.putconbound.

Parameters
• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• bkc (boundkey) – New bound key for all constraints in the slice. (input)

• blc (double) – New lower bound for all constraints in the slice. (input)

• buc (double) – New upper bound for all constraints in the slice. (input)

Groups
public synchronized void putcone
(int k,
conetype ct,
double conepar,
int[] submem)


NOTE: This interface to conic optimization is deprecated and will be removed in a future major release. Conic problems should be specified using the affine conic constraints interface (ACC), see Sec. 6.2 (From Linear to Conic Optimization) for details.

Parameters
• k (int) – Index of the cone. (input)

• ct (conetype) – Specifies the type of the cone. (input)

• conepar (double) – For the power cone it denotes the exponent alpha. For other cone types it is unused and can be set to 0. (input)

• submem (int[]) – Variable subscripts of the members in the cone. (input)

Groups

Problem data - cones (deprecated)

public synchronized void putconename
(int j,
String name)


NOTE: This interface to conic optimization is deprecated and will be removed in a future major release. Conic problems should be specified using the affine conic constraints interface (ACC), see Sec. 6.2 (From Linear to Conic Optimization) for details.

Parameters
• j (int) – Index of the cone. (input)

• name (String) – The name of the cone. (input)

Groups
public synchronized void putconname
(int i,
String name)


Sets the name of a constraint.

Parameters
• i (int) – Index of the constraint. (input)

• name (String) – The name of the constraint. (input)

Groups
public synchronized void putconsolutioni
(int i,
soltype whichsol,
stakey sk,
double x,
double sl,
double su)


Sets the primal and dual solution information for a single constraint.

Parameters
• i (int) – Index of the constraint. (input)

• whichsol (soltype) – Selects a solution. (input)

• sk (stakey) – Status key of the constraint. (input)

• x (double) – Primal solution value of the constraint. (input)

• sl (double) – Solution value of the dual variable associated with the lower bound. (input)

• su (double) – Solution value of the dual variable associated with the upper bound. (input)

Groups
public synchronized void putcslice
(int first,
int last,
double[] slice)


Modifies a slice in the linear term $$c$$ in the objective using the principle

$c_{\mathtt{j}} = \mathtt{slice[j-first]}, \quad j=first,..,\idxend{last}$

Data checks are performed as in Task.putcj.

Parameters
• first (int) – First element in the slice of $$c$$. (input)

• last (int) – Last element plus 1 of the slice in $$c$$ to be changed. (input)

• slice (double[]) – New numerical values for coefficients in $$c$$ that should be modified. (input)

Groups
public synchronized void putdjc
(long djcidx,
long[] domidxlist,
long[] afeidxlist,
double[] b,
long[] termsizelist)


Inputs a disjunctive constraint. The constraint has the form

$T_1\ \mathrm{or}\ T_2\ \mathrm{or}\ \cdots\ \mathrm{or}\ T_{\mathrm{numterms}}$

For each $$i=1,\ldots\mathrm{numterms}$$ the $$i$$-th clause (term) $$T_i$$ has the form a sequence of affine expressions belongs to a product of domains, where the number of domains is $$\mathrm{termsizelist}[i]$$ and the number of affine expressions is equal to the sum of dimensions of all domains appearing in $$T_i$$.

All the domains and all the affine expressions appearing in the above description are arranged sequentially in the lists domidxlist and afeidxlist, respectively. In particular, the length of domidxlist must be equal to the sum of elements of termsizelist, and the length of afeidxlist must be equal to the sum of dimensions of all the domains appearing in domidxlist.

The elements of domidxlist are indexes of domains previously defined with one of the append...domain functions.

The elements of afeidxlist are indexes to the store of affine expressions, i.e. the $$k$$-th affine expression appearing in the disjunctive constraint is going to be

$F_{\mathrm{afeidxlist}[k],:}x + g_{\mathrm{afeidxlist}[k]}$

If an optional vector b of the same length as afeidxlist is specified then the $$k$$-th affine expression appearing in the disjunctive constraint will be taken as

$F_{\mathrm{afeidxlist}[k],:}x + g_{\mathrm{afeidxlist}[k]} - b_k$
Parameters
• djcidx (long) – Index of the disjunctive constraint. (input)

• domidxlist (long[]) – List of domain indexes. (input)

• afeidxlist (long[]) – List of affine expression indexes. (input)

• b (double[]) – The vector of constant terms added to affine expressions. (input)

• termsizelist (long[]) – List of term sizes. (input)

Groups

Problem data - disjunctive constraints

public synchronized void putdjcname
(long djcidx,
String name)


Sets the name of a disjunctive constraint.

Parameters
• djcidx (long) – Index of the disjunctive constraint. (input)

• name (String) – The name of the disjunctive constraint. (input)

Groups
public synchronized void putdjcslice
(long idxfirst,
long idxlast,
long[] domidxlist,
long[] afeidxlist,
double[] b,
long[] termsizelist,
long[] termsindjc)


Inputs a slice of disjunctive constraints.

The array termsindjc should have length $$\mathrm{idxlast}-\mathrm{idxfirst}$$ and contain the number of terms in consecutive constraints forming the slice.

The rest of the input consists of concatenated descriptions of individual constraints, where each constraint is described as in Task.putdjc.

Parameters
• idxfirst (long) – Index of the first disjunctive constraint in the slice. (input)

• idxlast (long) – Index of the last disjunctive constraint in the slice plus 1. (input)

• domidxlist (long[]) – List of domain indexes. (input)

• afeidxlist (long[]) – List of affine expression indexes. (input)

• b (double[]) – The vector of constant terms added to affine expressions. Optional, may be NULL. (input)

• termsizelist (long[]) – List of term sizes. (input)

• termsindjc (long[]) – Number of terms in each of the disjunctive constraints in the slice. (input)

Groups

Problem data - disjunctive constraints

public synchronized void putdomainname
(long domidx,
String name)


Sets the name of a domain.

Parameters
• domidx (long) – Index of the domain. (input)

• name (String) – The name of the domain. (input)

Groups
public synchronized void putdouparam
(dparam param,
double parvalue)


Sets the value of a double parameter.

Parameters
• param (dparam) – Which parameter. (input)

• parvalue (double) – Parameter value. (input)

Groups

Parameters

public synchronized void putintparam
(iparam param,
int parvalue)


Sets the value of an integer parameter.

Please notice that some parameters take values that are defined in Enum classes. This function accepts only integer values, so to use e.g. the value onoffkey.on, is necessary to use the member .value. For example:

task.putintparam(mosek.iparam.opf_write_problem, mosek.onoffkey.on.value)

Parameters
• param (iparam) – Which parameter. (input)

• parvalue (int) – Parameter value. (input)

Groups

Parameters

public synchronized void putmaxnumacc(long maxnumacc)


Sets the number of preallocated affine conic constraints in the optimization task. When this number is reached MOSEK will automatically allocate more space. It is never mandatory to call this function, since MOSEK will reallocate any internal structures whenever it is required.

Parameters

maxnumacc (long) – Number of preallocated affine conic constraints. (input)

Groups
public synchronized void putmaxnumafe(long maxnumafe)


Sets the number of preallocated affine expressions in the optimization task. When this number is reached MOSEK will automatically allocate more space for affine expressions. It is never mandatory to call this function, since MOSEK will reallocate any internal structures whenever it is required.

Parameters

maxnumafe (long) – Number of preallocated affine expressions. (input)

Groups
public synchronized void putmaxnumanz(long maxnumanz)


Sets the number of preallocated non-zero entries in $$A$$.

MOSEK stores only the non-zero elements in the linear coefficient matrix $$A$$ and it cannot predict how much storage is required to store $$A$$. Using this function it is possible to specify the number of non-zeros to preallocate for storing $$A$$.

If the number of non-zeros in the problem is known, it is a good idea to set maxnumanz slightly larger than this number, otherwise a rough estimate can be used. In general, if $$A$$ is inputted in many small chunks, setting this value may speed up the data input phase.

It is not mandatory to call this function, since MOSEK will reallocate internal structures whenever it is necessary.

The function call has no effect if both maxnumcon and maxnumvar are zero.

Parameters

maxnumanz (long) – Number of preallocated non-zeros in $$A$$. (input)

Groups
public synchronized void putmaxnumbarvar(int maxnumbarvar)


Sets the number of preallocated symmetric matrix variables in the optimization task. When this number of variables is reached MOSEK will automatically allocate more space for variables.

It is not mandatory to call this function. It only gives a hint about the amount of data to preallocate for efficiency reasons.

Please note that maxnumbarvar must be larger than the current number of symmetric matrix variables in the task.

Parameters

maxnumbarvar (int) – Number of preallocated symmetric matrix variables. (input)

Groups
public synchronized void putmaxnumcon(int maxnumcon)


Sets the number of preallocated constraints in the optimization task. When this number of constraints is reached MOSEK will automatically allocate more space for constraints.

It is never mandatory to call this function, since MOSEK will reallocate any internal structures whenever it is required.

Please note that maxnumcon must be larger than the current number of constraints in the task.

Parameters

maxnumcon (int) – Number of preallocated constraints in the optimization task. (input)

Groups
public synchronized void putmaxnumcone(int maxnumcone)


NOTE: This interface to conic optimization is deprecated and will be removed in a future major release. Conic problems should be specified using the affine conic constraints interface (ACC), see Sec. 6.2 (From Linear to Conic Optimization) for details.

Sets the number of preallocated conic constraints in the optimization task. When this number of conic constraints is reached MOSEK will automatically allocate more space for conic constraints.

It is not mandatory to call this function, since MOSEK will reallocate any internal structures whenever it is required.

Please note that maxnumcon must be larger than the current number of conic constraints in the task.

Parameters

maxnumcone (int) – Number of preallocated conic constraints in the optimization task. (input)

Groups
public synchronized void putmaxnumdjc(long maxnumdjc)


Sets the number of preallocated disjunctive constraints in the optimization task. When this number is reached MOSEK will automatically allocate more space. It is never mandatory to call this function, since MOSEK will reallocate any internal structures whenever it is required.

Parameters

maxnumdjc (long) – Number of preallocated disjunctive constraints in the task. (input)

Groups
public synchronized void putmaxnumdomain(long maxnumdomain)


Sets the number of preallocated domains in the optimization task. When this number is reached MOSEK will automatically allocate more space. It is never mandatory to call this function, since MOSEK will reallocate any internal structures whenever it is required.

Parameters

maxnumdomain (long) – Number of preallocated domains. (input)

Groups
public synchronized void putmaxnumqnz(long maxnumqnz)


Sets the number of preallocated non-zero entries in quadratic terms.

MOSEK stores only the non-zero elements in $$Q$$. Therefore, MOSEK cannot predict how much storage is required to store $$Q$$. Using this function it is possible to specify the number non-zeros to preallocate for storing $$Q$$ (both objective and constraints).

It may be advantageous to reserve more non-zeros for $$Q$$ than actually needed since it may improve the internal efficiency of MOSEK, however, it is never worthwhile to specify more than the double of the anticipated number of non-zeros in $$Q$$.

It is not mandatory to call this function, since MOSEK will reallocate internal structures whenever it is necessary.

Parameters

maxnumqnz (long) – Number of non-zero elements preallocated in quadratic coefficient matrices. (input)

Groups
public synchronized void putmaxnumvar(int maxnumvar)


Sets the number of preallocated variables in the optimization task. When this number of variables is reached MOSEK will automatically allocate more space for variables.

It is not mandatory to call this function. It only gives a hint about the amount of data to preallocate for efficiency reasons.

Please note that maxnumvar must be larger than the current number of variables in the task.

Parameters

maxnumvar (int) – Number of preallocated variables in the optimization task. (input)

Groups
public synchronized void putnadouparam
(String paramname,
double parvalue)


Sets the value of a named double parameter.

Parameters
• paramname (String) – Name of a parameter. (input)

• parvalue (double) – Parameter value. (input)

Groups

Parameters

public synchronized void putnaintparam
(String paramname,
int parvalue)


Sets the value of a named integer parameter.

Parameters
• paramname (String) – Name of a parameter. (input)

• parvalue (int) – Parameter value. (input)

Groups

Parameters

public synchronized void putnastrparam
(String paramname,
String parvalue)


Sets the value of a named string parameter.

Parameters
• paramname (String) – Name of a parameter. (input)

• parvalue (String) – Parameter value. (input)

Groups

Parameters

public synchronized void putobjname(String objname)


Assigns a new name to the objective.

Parameters

objname (String) – Name of the objective. (input)

Groups
public synchronized void putobjsense(objsense sense)


Sets the objective sense of the task.

Parameters

sense (objsense) – The objective sense of the task. The values objsense.maximize and objsense.minimize mean that the problem is maximized or minimized respectively. (input)

Groups
public synchronized void putoptserverhost(String host)


Specify an OptServer URL for remote calls. The URL should contain protocol, host and port in the form http://server:port or https://server:port. If the URL is set using this function, all subsequent calls to any MOSEK function that involves synchronous optimization will be sent to the specified OptServer instead of being executed locally. Passing NULL deactivates this redirection.

Has the same effect as setting the parameter sparam.remote_optserver_host.

Parameters

host (String) – A URL specifying the optimization server to be used. (input)

Groups

Remote optimization

public synchronized void putparam
(String parname,
String parvalue)


Checks if parname is valid parameter name. If it is, the parameter is assigned the value specified by parvalue.

Parameters
• parname (String) – Parameter name. (input)

• parvalue (String) – Parameter value. (input)

Groups

Parameters

public synchronized void putqcon
(int[] qcsubk,
int[] qcsubi,
int[] qcsubj,
double[] qcval)


Replace all quadratic entries in the constraints. The list of constraints has the form

$l_k^c \leq \half \sum_{i=0}^{\idxend{numvar}} \sum_{j=0}^{\idxend{numvar}} q_{ij}^k x_i x_j + \sum_{j=0}^{\idxend{numvar}} a_{kj} x_j \leq u_k^c, ~\ k=0,\ldots,m-1.$

This function sets all the quadratic terms to zero and then performs the update:

$q_{\mathtt{qcsubi[t]},\mathtt{qcsubj[t]}}^{\mathtt{qcsubk[t]}} = q_{\mathtt{\mathtt{qcsubj[t]},qcsubi[t]}}^{\mathtt{qcsubk[t]}} = q_{\mathtt{\mathtt{qcsubj[t]},qcsubi[t]}}^{\mathtt{qcsubk[t]}} + \mathtt{qcval[t]},$

for $$t=\idxbeg,\ldots,\idxend{numqcnz}$$.

• For large problems it is essential for the efficiency that the function Task.putmaxnumqnz is employed to pre-allocate space.

• Only the lower triangular parts should be specified because the $$Q$$ matrices are symmetric. Specifying entries where $$i < j$$ will result in an error.

• Only non-zero elements should be specified.

• The order in which the non-zero elements are specified is insignificant.

• Duplicate elements are added together as shown above. Hence, it is usually not recommended to specify the same entry multiple times.

For a code example see Section Quadratic Optimization

Parameters
• qcsubk (int[]) – Constraint subscripts for quadratic coefficients. (input)

• qcsubi (int[]) – Row subscripts for quadratic constraint matrix. (input)

• qcsubj (int[]) – Column subscripts for quadratic constraint matrix. (input)

• qcval (double[]) – Quadratic constraint coefficient values. (input)

Groups

public synchronized void putqconk
(int k,
int[] qcsubi,
int[] qcsubj,
double[] qcval)


Replaces all the quadratic entries in one constraint. This function performs the same operations as Task.putqcon but only with respect to constraint number k and it does not modify the other constraints. See the description of Task.putqcon for definitions and important remarks.

Parameters
• k (int) – The constraint in which the new $$Q$$ elements are inserted. (input)

• qcsubi (int[]) – Row subscripts for quadratic constraint matrix. (input)

• qcsubj (int[]) – Column subscripts for quadratic constraint matrix. (input)

• qcval (double[]) – Quadratic constraint coefficient values. (input)

Groups

public synchronized void putqobj
(int[] qosubi,
int[] qosubj,
double[] qoval)


Replace all quadratic terms in the objective. If the objective has the form

$\half \sum_{i=0}^{\idxend{numvar}} \sum_{j=0}^{\idxend{numvar}} q_{ij}^o x_i x_j + \sum_{j=0}^{\idxend{numvar}} c_{j} x_j + c^f$

then this function sets all the quadratic terms to zero and then performs the update:

$q_{\mathtt{qosubi[t]},\mathtt{qosubj[t]}}^{o} = q_{\mathtt{\mathtt{qosubj[t]},qosubi[t]}}^{o} = q_{\mathtt{\mathtt{qosubj[t]},qosubi[t]}}^{o} + \mathtt{qoval[t]},$

for $$t=\idxbeg,\ldots,\idxend{numqonz}$$.

See the description of Task.putqcon for important remarks and example.

Parameters
• qosubi (int[]) – Row subscripts for quadratic objective coefficients. (input)

• qosubj (int[]) – Column subscripts for quadratic objective coefficients. (input)

• qoval (double[]) – Quadratic objective coefficient values. (input)

Groups
public synchronized void putqobjij
(int i,
int j,
double qoij)


Replaces one coefficient in the quadratic term in the objective. The function performs the assignment

$q_{ij}^o = q_{ji}^o = \mathtt{qoij}.$

Only the elements in the lower triangular part are accepted. Setting $$q_{ij}$$ with $$j>i$$ will cause an error.

Please note that replacing all quadratic elements one by one is more computationally expensive than replacing them all at once. Use Task.putqobj instead whenever possible.

Parameters
• i (int) – Row index for the coefficient to be replaced. (input)

• j (int) – Column index for the coefficient to be replaced. (input)

• qoij (double) – The new value for $$q_{ij}^o$$. (input)

Groups
public synchronized void putskc
(soltype whichsol,
stakey[] skc)


Sets the status keys for the constraints.

Parameters
Groups

Solution information

public synchronized void putskcslice
(soltype whichsol,
int first,
int last,
stakey[] skc)


Sets the status keys for a slice of the constraints.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• skc (stakey[]) – Status keys for the constraints. (input)

Groups

Solution information

public synchronized void putskx
(soltype whichsol,
stakey[] skx)


Sets the status keys for the scalar variables.

Parameters
Groups

Solution information

public synchronized void putskxslice
(soltype whichsol,
int first,
int last,
stakey[] skx)


Sets the status keys for a slice of the variables.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• skx (stakey[]) – Status keys for the variables. (input)

Groups

Solution information

public synchronized void putslc
(soltype whichsol,
double[] slc)


Sets the $$s_l^c$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• slc (double[]) – Dual variables corresponding to the lower bounds on the constraints. (input)

Groups

Solution - dual

public synchronized void putslcslice
(soltype whichsol,
int first,
int last,
double[] slc)


Sets a slice of the $$s_l^c$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• slc (double[]) – Dual variables corresponding to the lower bounds on the constraints. (input)

Groups

Solution - dual

public synchronized void putslx
(soltype whichsol,
double[] slx)


Sets the $$s_l^x$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• slx (double[]) – Dual variables corresponding to the lower bounds on the variables. (input)

Groups

Solution - dual

public synchronized void putslxslice
(soltype whichsol,
int first,
int last,
double[] slx)


Sets a slice of the $$s_l^x$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• slx (double[]) – Dual variables corresponding to the lower bounds on the variables. (input)

Groups

Solution - dual

public synchronized void putsnx
(soltype whichsol,
double[] sux)


Sets the $$s_n^x$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• sux (double[]) – Dual variables corresponding to the upper bounds on the variables. (input)

Groups

Solution - dual

public synchronized void putsnxslice
(soltype whichsol,
int first,
int last,
double[] snx)


Sets a slice of the $$s_n^x$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• snx (double[]) – Dual variables corresponding to the conic constraints on the variables. (input)

Groups

Solution - dual

public synchronized void putsolution
(soltype whichsol,
stakey[] skc,
stakey[] skx,
stakey[] skn,
double[] xc,
double[] xx,
double[] y,
double[] slc,
double[] suc,
double[] slx,
double[] sux,
double[] snx)


Inserts a solution into the task.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• skc (stakey[]) – Status keys for the constraints. (input)

• skx (stakey[]) – Status keys for the variables. (input)

• skn (stakey[]) – Status keys for the conic constraints. (input)

• xc (double[]) – Primal constraint solution. (input)

• xx (double[]) – Primal variable solution. (input)

• y (double[]) – Vector of dual variables corresponding to the constraints. (input)

• slc (double[]) – Dual variables corresponding to the lower bounds on the constraints. (input)

• suc (double[]) – Dual variables corresponding to the upper bounds on the constraints. (input)

• slx (double[]) – Dual variables corresponding to the lower bounds on the variables. (input)

• sux (double[]) – Dual variables corresponding to the upper bounds on the variables. (input)

• snx (double[]) – Dual variables corresponding to the conic constraints on the variables. (input)

Groups
public synchronized void putsolutionnew
(soltype whichsol,
stakey[] skc,
stakey[] skx,
stakey[] skn,
double[] xc,
double[] xx,
double[] y,
double[] slc,
double[] suc,
double[] slx,
double[] sux,
double[] snx,
double[] doty)


Inserts a solution into the task.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• skc (stakey[]) – Status keys for the constraints. (input)

• skx (stakey[]) – Status keys for the variables. (input)

• skn (stakey[]) – Status keys for the conic constraints. (input)

• xc (double[]) – Primal constraint solution. (input)

• xx (double[]) – Primal variable solution. (input)

• y (double[]) – Vector of dual variables corresponding to the constraints. (input)

• slc (double[]) – Dual variables corresponding to the lower bounds on the constraints. (input)

• suc (double[]) – Dual variables corresponding to the upper bounds on the constraints. (input)

• slx (double[]) – Dual variables corresponding to the lower bounds on the variables. (input)

• sux (double[]) – Dual variables corresponding to the upper bounds on the variables. (input)

• snx (double[]) – Dual variables corresponding to the conic constraints on the variables. (input)

• doty (double[]) – Dual variables corresponding to affine conic constraints. (input)

Groups
public synchronized void putsolutionyi
(int i,
soltype whichsol,
double y)


Inputs the dual variable of a solution.

Parameters
• i (int) – Index of the dual variable. (input)

• whichsol (soltype) – Selects a solution. (input)

• y (double) – Solution value of the dual variable. (input)

Groups
public synchronized void putstrparam
(sparam param,
String parvalue)


Sets the value of a string parameter.

Parameters
• param (sparam) – Which parameter. (input)

• parvalue (String) – Parameter value. (input)

Groups

Parameters

public synchronized void putsuc
(soltype whichsol,
double[] suc)


Sets the $$s_u^c$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• suc (double[]) – Dual variables corresponding to the upper bounds on the constraints. (input)

Groups

Solution - dual

public synchronized void putsucslice
(soltype whichsol,
int first,
int last,
double[] suc)


Sets a slice of the $$s_u^c$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• suc (double[]) – Dual variables corresponding to the upper bounds on the constraints. (input)

Groups

Solution - dual

public synchronized void putsux
(soltype whichsol,
double[] sux)


Sets the $$s_u^x$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• sux (double[]) – Dual variables corresponding to the upper bounds on the variables. (input)

Groups

Solution - dual

public synchronized void putsuxslice
(soltype whichsol,
int first,
int last,
double[] sux)


Sets a slice of the $$s_u^x$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• sux (double[]) – Dual variables corresponding to the upper bounds on the variables. (input)

Groups

Solution - dual

public synchronized void puttaskname(String taskname)


Assigns a new name to the task.

Parameters

taskname (String) – Name assigned to the task. (input)

Groups
public synchronized void putvarbound
(int j,
boundkey bkx,
double blx,
double bux)


Changes the bounds for one variable.

If the bound value specified is numerically larger than dparam.data_tol_bound_inf it is considered infinite and the bound key is changed accordingly. If a bound value is numerically larger than dparam.data_tol_bound_wrn, a warning will be displayed, but the bound is inputted as specified.

Parameters
• j (int) – Index of the variable. (input)

• bkx (boundkey) – New bound key. (input)

• blx (double) – New lower bound. (input)

• bux (double) – New upper bound. (input)

Groups
public synchronized void putvarboundlist
(int[] sub,
boundkey[] bkx,
double[] blx,
double[] bux)


Changes the bounds for one or more variables. If multiple bound changes are specified for a variable, then only the last change takes effect. Data checks are performed as in Task.putvarbound.

Parameters
• sub (int[]) – List of variable indexes. (input)

• bkx (boundkey[]) – Bound keys for the variables. (input)

• blx (double[]) – Lower bounds for the variables. (input)

• bux (double[]) – Upper bounds for the variables. (input)

Groups
public synchronized void putvarboundlistconst
(int[] sub,
boundkey bkx,
double blx,
double bux)


Changes the bounds for one or more variables. Data checks are performed as in Task.putvarbound.

Parameters
• sub (int[]) – List of variable indexes. (input)

• bkx (boundkey) – New bound key for all variables in the list. (input)

• blx (double) – New lower bound for all variables in the list. (input)

• bux (double) – New upper bound for all variables in the list. (input)

Groups
public synchronized void putvarboundslice
(int first,
int last,
boundkey[] bkx,
double[] blx,
double[] bux)


Changes the bounds for a slice of the variables. Data checks are performed as in Task.putvarbound.

Parameters
• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• bkx (boundkey[]) – Bound keys for the variables. (input)

• blx (double[]) – Lower bounds for the variables. (input)

• bux (double[]) – Upper bounds for the variables. (input)

Groups
public synchronized void putvarboundsliceconst
(int first,
int last,
boundkey bkx,
double blx,
double bux)


Changes the bounds for a slice of the variables. Data checks are performed as in Task.putvarbound.

Parameters
• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• bkx (boundkey) – New bound key for all variables in the slice. (input)

• blx (double) – New lower bound for all variables in the slice. (input)

• bux (double) – New upper bound for all variables in the slice. (input)

Groups
public synchronized void putvarname
(int j,
String name)


Sets the name of a variable.

Parameters
• j (int) – Index of the variable. (input)

• name (String) – The variable name. (input)

Groups
public synchronized void putvarsolutionj
(int j,
soltype whichsol,
stakey sk,
double x,
double sl,
double su,
double sn)


Sets the primal and dual solution information for a single variable.

Parameters
• j (int) – Index of the variable. (input)

• whichsol (soltype) – Selects a solution. (input)

• sk (stakey) – Status key of the variable. (input)

• x (double) – Primal solution value of the variable. (input)

• sl (double) – Solution value of the dual variable associated with the lower bound. (input)

• su (double) – Solution value of the dual variable associated with the upper bound. (input)

• sn (double) – Solution value of the dual variable associated with the conic constraint. (input)

Groups
public synchronized void putvartype
(int j,
variabletype vartype)


Sets the variable type of one variable.

Parameters
• j (int) – Index of the variable. (input)

• vartype (variabletype) – The new variable type. (input)

Groups

Problem data - variables

public synchronized void putvartypelist
(int[] subj,
variabletype[] vartype)


Sets the variable type for one or more variables. If the same index is specified multiple times in subj only the last entry takes effect.

Parameters
• subj (int[]) – A list of variable indexes for which the variable type should be changed. (input)

• vartype (variabletype[]) – A list of variable types that should be assigned to the variables specified by subj. (input)

Groups

Problem data - variables

public synchronized void putxc
(soltype whichsol,
double[] xc)


Sets the $$x^c$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• xc (double[]) – Primal constraint solution. (output)

Groups

Solution - primal

public synchronized void putxcslice
(soltype whichsol,
int first,
int last,
double[] xc)


Sets a slice of the $$x^c$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• xc (double[]) – Primal constraint solution. (input)

Groups

Solution - primal

public synchronized void putxx
(soltype whichsol,
double[] xx)


Sets the $$x^x$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• xx (double[]) – Primal variable solution. (input)

Groups

Solution - primal

public synchronized void putxxslice
(soltype whichsol,
int first,
int last,
double[] xx)


Sets a slice of the $$x^x$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• xx (double[]) – Primal variable solution. (input)

Groups

Solution - primal

public synchronized void puty
(soltype whichsol,
double[] y)


Sets the $$y$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• y (double[]) – Vector of dual variables corresponding to the constraints. (input)

Groups

Solution - primal

public synchronized void putyslice
(soltype whichsol,
int first,
int last,
double[] y)


Sets a slice of the $$y$$ vector for a solution.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• first (int) – First index in the sequence. (input)

• last (int) – Last index plus 1 in the sequence. (input)

• y (double[]) – Vector of dual variables corresponding to the constraints. (input)

Groups

Solution - dual

public synchronized void readbsolution
(String filename,
compresstype compress)


Parameters
• filename (String) – A valid file name. (input)

• compress (compresstype) – Data compression type. (input)

Groups

Input/Output

public synchronized void readdata(String filename)


Reads an optimization problem and associated data from a file.

Parameters

filename (String) – A valid file name. (input)

Groups

Input/Output

public synchronized void readdataformat
(String filename,
dataformat format,
compresstype compress)


Reads an optimization problem and associated data from a file.

Parameters
Groups

Input/Output

public synchronized void readjsonsol(String filename)


Reads a solution file in JSON format (JSOL file) and inserts it in the task. Only the section Task/solutions is taken into consideration.

Parameters

filename (String) – A valid file name. (input)

Groups

Input/Output

public synchronized void readjsonstring(String data)


Load task data from a JSON string, replacing any data that already exists in the task object. All problem data, parameters and other settings are resorted, but if the string contains solutions, the solution status after loading a file is set to unknown, even if it is optimal or otherwise well-defined.

Parameters

data (String) – Problem data in text format. (input)

Groups

Input/Output

public synchronized void readlpstring(String data)


Parameters

data (String) – Problem data in text format. (input)

Groups

Input/Output

public synchronized void readopfstring(String data)


Parameters

data (String) – Problem data in text format. (input)

Groups

Input/Output

public synchronized void readparamfile(String filename)


Reads MOSEK parameters from a file. Data is read from the file filename if it is a nonempty string. Otherwise data is read from the file specified by sparam.param_read_file_name.

Parameters

filename (String) – A valid file name. (input)

Groups
public synchronized void readptfstring(String data)


Load task data from a PTF string, replacing any data that already exists in the task object. All problem data, parameters and other settings are resorted, but if the string contains solutions, the solution status after loading a file is set to unknown, even if it is optimal or otherwise well-defined.

Parameters

data (String) – Problem data in text format. (input)

Groups

Input/Output

public synchronized void readsolution
(soltype whichsol,
String filename)


Reads a solution file and inserts it as a specified solution in the task. Data is read from the file filename if it is a nonempty string. Otherwise data is read from one of the files specified by sparam.bas_sol_file_name, sparam.itr_sol_file_name or sparam.int_sol_file_name depending on which solution is chosen.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• filename (String) – A valid file name. (input)

Groups

Input/Output

public synchronized void readsolutionfile(String filename)


Read solution file in format determined by the filename

Parameters

filename (String) – A valid file name. (input)

Groups

Input/Output

public synchronized void readsummary(streamtype whichstream)


Prints a short summary of last file that was read.

Parameters

whichstream (streamtype) – Index of the stream. (input)

Groups
public synchronized void readtask(String filename)


Load task data from a file, replacing any data that already exists in the task object. All problem data, parameters and other settings are resorted, but if the file contains solutions, the solution status after loading a file is set to unknown, even if it was optimal or otherwise well-defined when the file was dumped.

See section The Task Format for a description of the Task format.

Parameters

filename (String) – A valid file name. (input)

Groups

Input/Output

public synchronized void removebarvars(int[] subset)


The function removes a subset of the symmetric matrices from the optimization task. This implies that the remaining symmetric matrices are renumbered.

Parameters

subset (int[]) – Indexes of symmetric matrices which should be removed. (input)

Groups

Problem data - semidefinite

public synchronized void removecones(int[] subset)


NOTE: This interface to conic optimization is deprecated and will be removed in a future major release. Conic problems should be specified using the affine conic constraints interface (ACC), see Sec. 6.2 (From Linear to Conic Optimization) for details.

Removes a number of conic constraints from the problem. This implies that the remaining conic constraints are renumbered. In general, it is much more efficient to remove a cone with a high index than a low index.

Parameters

subset (int[]) – Indexes of cones which should be removed. (input)

Groups

Problem data - cones (deprecated)

public synchronized void removecons(int[] subset)


The function removes a subset of the constraints from the optimization task. This implies that the remaining constraints are renumbered.

Parameters

subset (int[]) – Indexes of constraints which should be removed. (input)

Groups
public synchronized void removevars(int[] subset)


The function removes a subset of the variables from the optimization task. This implies that the remaining variables are renumbered.

Parameters

subset (int[]) – Indexes of variables which should be removed. (input)

Groups
public synchronized void resizetask
(int maxnumcon,
int maxnumvar,
int maxnumcone,
long maxnumanz,
long maxnumqnz)


Sets the amount of preallocated space assigned for each type of data in an optimization task.

It is never mandatory to call this function, since it only gives a hint about the amount of data to preallocate for efficiency reasons.

Please note that the procedure is destructive in the sense that all existing data stored in the task is destroyed.

Parameters
• maxnumcon (int) – New maximum number of constraints. (input)

• maxnumvar (int) – New maximum number of variables. (input)

• maxnumcone (int) – New maximum number of cones. (input)

• maxnumanz (long) – New maximum number of non-zeros in $$A$$. (input)

• maxnumqnz (long) – New maximum number of non-zeros in all $$Q$$ matrices. (input)

Groups

public synchronized void sensitivityreport(streamtype whichstream)


Reads a sensitivity format file from a location given by sparam.sensitivity_file_name and writes the result to the stream whichstream. If sparam.sensitivity_res_file_name is set to a non-empty string, then the sensitivity report is also written to a file of this name.

Parameters

whichstream (streamtype) – Index of the stream. (input)

Groups

Sensitivity analysis

void set_InfoCallback (mosek.DataCallback callback)


Receive callbacks with solver status and information during optimization.

For example:

task.set_InfoCallback(
new mosek.InfoCallback() {
int callback(mosek.callbackcode code, double[] dinf, int[]iinf, long[] liinf) {
System.println("Callback "+code+", intpnt time : "+dinf[mosek.dinfitem.intpnt_time.getValue()]);
return 0;
} } );

Parameters

callback (DataCallback) – The callback object. (input)

void set_ItgSolutionCallback (mosek.ItgSolutionCallback callback)


For example:

task.set_ItgSolutionCallback(
new mosek.ItgSolutionCallback() {
void callback(double[] xx) {
System.out.print("New integer solution: ");
for (double v : xx) System.out.print("" + v + " ");
System.out.println("");
} } );

Parameters

callback (ItgSolutionCallback) – The callback object. (input)

void set_Progress (mosek.Progress callback)


For example:

task.set_Progress(new mosek.Progress() { int progress(mosek.callbackcode code) { System.println("Callback "+code); return 0; } });

Parameters

callback (Progress) – The callback object. (input)

void set_Stream(
mosek.streamtype whichstream,
mosek.Stream callback)


Directs all output from a task stream to a callback object.

Can for example be called as:

task.set_Stream(mosek.streamtype.log, new Stream() { public void stream(String s) { System.out.print(s); } } );

Parameters
public synchronized void setdefaults()


Resets all the parameters to their default values.

Groups

Parameters

public synchronized void solutiondef
(soltype whichsol,
boolean[] isdef)

public synchronized boolean solutiondef(soltype whichsol)


Checks whether a solution is defined.

Parameters
• whichsol (soltype) – Selects a solution. (input)

• isdef (boolean by reference) – Is non-zero if the requested solution is defined. (output)

Return

(boolean) – Is non-zero if the requested solution is defined.

Groups

Solution information

public synchronized void solutionsummary(streamtype whichstream)


Prints a short summary of the current solutions.

Parameters

whichstream (streamtype) – Index of the stream. (input)

Groups
public synchronized void solvewithbasis
(boolean transp,
int numnz,
int[] sub,
double[] val,
int[] numnzout)

public synchronized int solvewithbasis
(boolean transp,
int numnz,
int[] sub,
double[] val)


If a basic solution is available, then exactly $$numcon$$ basis variables are defined. These $$numcon$$ basis variables are denoted the basis. Associated with the basis is a basis matrix denoted $$B$$. This function solves either the linear equation system

(15.3)$B \barX = b$

or the system

(15.4)$B^T \barX = b$

for the unknowns $$\barX$$, with $$b$$ being a user-defined vector. In order to make sense of the solution $$\barX$$ it is important to know the ordering of the variables in the basis because the ordering specifies how $$B$$ is constructed. When calling Task.initbasissolve an ordering of the basis variables is obtained, which can be used to deduce how MOSEK has constructed $$B$$. Indeed if the $$k$$-th basis variable is variable $$x_j$$ it implies that

$B_{i,k} = A_{i,j}, ~i=\idxbeg,\ldots,\idxend{numcon}.$

Otherwise if the $$k$$-th basis variable is variable $$x_j^c$$ it implies that

$\begin{split}B_{i,k} = \left\{ \begin{array}{ll} -1, & i = j, \\ 0 , & i \neq j. \\ \end{array} \right.\end{split}$

The function Task.initbasissolve must be called before a call to this function. Please note that this function exploits the sparsity in the vector $$b$$ to speed up the computations.

Parameters
• transp (boolean) – If this argument is zero, then