pub struct Task { /* private fields */ }Expand description
The Task structure encapsulates a MOSEK Task containing problem data, parameters and other information used to solve the optimization problem, and provides the API for interacting with the task data.
The Task object does not support callbacks, but can be passed or
shared between threads. If callbacks are needed, use the
with_callbacks metho to convert it into a TaskCB object.
Implementations§
source§impl Task
impl Task
sourcepub fn with_capacity(
env: Option<&Env>,
numcon: i32,
numvar: i32
) -> Option<Task>
pub fn with_capacity( env: Option<&Env>, numcon: i32, numvar: i32 ) -> Option<Task>
Create a new task in the given environment or with the default environment with a given capacity
sourcepub fn from_env(env: Option<&Env>) -> Option<Task>
pub fn from_env(env: Option<&Env>) -> Option<Task>
Create a new task in the given environment or with the default environment
sourcepub fn clone(&self) -> Option<Task>
pub fn clone(&self) -> Option<Task>
Create a new task in the given environment or with the default environment
Examples found in repository?
examples/concurrent1.rs (line 47)
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fn optimize_concurrent(task : &mut mosek::Task,
optimizers : &[i32]) -> Vec<(usize,i32,mosek::Task)> {
let stop = Arc::new(Mutex::new(false));
optimizers.iter().enumerate()
.filter_map(|(i,&ot)|
if let Some(mut t) = task.clone() {
if let Err(_) = t.put_int_param(mosek::Iparam::OPTIMIZER, ot as i32) { None }
else {
let stopopt = Arc::clone(&stop);
Some((i,thread::spawn(move || optimize(t,stopopt))))
}
}
else { None })
.filter_map(|(i,th)|
match th.join().unwrap() {
None => None,
Some((r,t)) => Some((i,r,t)) } )
.collect()
}
fn optimize_concurrent_mio(task : & mut mosek::Task,
seeds : &[i32]) -> Vec<(usize,i32,mosek::Task)> {
let stop = Arc::new(Mutex::new(false));
seeds.iter().enumerate()
.filter_map(|(i,&seed)| {
if let Some(mut t) = task.clone() {
if let Err(_) = t.put_int_param(mosek::Iparam::MIO_SEED, seed) { None }
else {
let stopopt = Arc::clone(&stop);
Some((i,thread::spawn(move || optimize(t,stopopt))))
}
}
else { None }})
.filter_map(|(i,th)|
match th.join().unwrap() {
None => None,
Some((r,t)) => Some((i,r,t)) } )
.collect()
}sourcepub fn new() -> Option<Task>
pub fn new() -> Option<Task>
Create a new task in the default environment
Examples found in repository?
More examples
examples/helloworld.rs (line 15)
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fn main() -> Result<(),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
task.append_vars(1)?; // 1 variable x
task.put_c_j(0, 1.0)?; // c_0 = 1.0
task.put_var_bound(0, Boundkey::RA, 2.0, 3.0)?; // 2.0 <= x <= 3.0
task.put_obj_sense(Objsense::MINIMIZE)?; // minimize
task.optimize()?; // Optimize
let mut x = vec![0.0; 1];
task.get_xx(Soltype::ITR, x.as_mut_slice())?; // Get solution
println!("Solution x = {}", x[0]); // Print solution
return Result::Ok(());
}examples/opt_server_sync.rs (line 32)
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fn opt_server_sync(inputfile : FileOrText, addr : String, cert : Option<String>) -> Result<(),String> {
let mut task = Task::new().unwrap().with_callbacks();
task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
// Load some data into the task
match inputfile {
FileOrText::File(filename) => task.read_data(filename.as_str())?,
FileOrText::Text(data) => task.read_ptf_string(data.as_str())?
}
// Set OptServer URL
task.put_optserver_host(addr.as_str())?;
// Path to certificate, if any
if let Some(cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH, cert.as_str())?;
}
// Optimize remotely, no access token
let _trm = task.optimize()?;
task.solution_summary(Streamtype::LOG)?;
Ok(())
}examples/pinfeas.rs (line 16)
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fn test_problem() -> Result<mosek::Task,String> {
let mut task = mosek::Task::new().unwrap();
task.append_vars(7)?;
task.append_cons(7)?;
task.put_c_list(&[0,1,2,3,4,5,6],
&[1.0,2.0,5.0,2.0,1.0,2.0,1.0])?;
task.put_aij_list(&[0,0,1,1,2,2,2,3,3,4,5,5,6,6],
&[0,1,2,3,4,5,6,0,4,1,2,5,3,6],
&[1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0])?;
task.put_con_bound_slice(0, 7,
&[Boundkey::UP,Boundkey::UP,Boundkey::UP,Boundkey::FX,Boundkey::FX,Boundkey::FX,Boundkey::FX],
&[-INF, -INF, -INF, 1100.0, 200.0, 500.0, 500.0],
&[200.0, 1000.0, 1000.0, 1100.0, 200.0, 500.0, 500.0])?;
task.put_var_bound_slice_const(0, 7, Boundkey::UP, 0.0, INF)?;
Ok(task)
}examples/feasrepairex1.rs (line 37)
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fn feasrepairex1(filename : FileOrText) -> Result<(),String> {
let mut task = Task::new().unwrap().with_callbacks();
task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
match filename {
FileOrText::File(fname) => task.read_data(fname.as_str())?,
FileOrText::Text(data) => task.read_lp_string(data.as_str())?
}
task.put_int_param(mosek::Iparam::LOG_FEAS_REPAIR, 3)?;
let wc = vec![1.0; task.get_num_con()? as usize];
let wx = vec![1.0; task.get_num_var()? as usize];
task.primal_repair(wc.as_slice(),wc.as_slice(),wx.as_slice(),wx.as_slice())?;
let sum_viol = task.get_dou_inf(mosek::Dinfitem::PRIMAL_REPAIR_PENALTY_OBJ)?;
println!("Minimized sum of violations = {}", sum_viol);
let _ = task.optimize()?;
task.solution_summary(mosek::Streamtype::MSG)?;
Ok(())
}examples/callback.rs (line 109)
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fn callbackmain(which : &str, data : FileOrText) -> Result<(),String> {
/* Create the optimization task. */
let mut task = Task::new().unwrap();
match data {
FileOrText::Text(data) => { task.read_ptf_string(data)? },
FileOrText::File(fname) => { task.read_data(fname)? }
}
task.write_data("callback.ptf")?;
match which {
"psim" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::PRIMAL_SIMPLEX)?,
"dsim" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::DUAL_SIMPLEX)?,
"intpnt" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::INTPNT)?,
s => return Err(format!("Invalid argument '{}'",s))
}
/* Directs the log task stream to the 'printstr' function. */
task.with_stream_callback(
Streamtype::LOG,
& mut |msg| print!("{}",msg),
|task|
task.with_info_callback(
& mut callback,
|task|
task.optimize()
)
)?;
Result::Ok(())
}Additional examples can be found in:
- examples/simple.rs
- examples/parameters.rs
- examples/response.rs
- examples/logistic.rs
- examples/parallel.rs
- examples/solvelinear.rs
- examples/mico1.rs
- examples/mioinitsol.rs
- examples/acc1.rs
- examples/acc2.rs
- examples/pow1.rs
- examples/gp1.rs
- examples/portfolio_1_basic.rs
- examples/opt_server_async.rs
- examples/portfolio_2_frontier.rs
- examples/solvebasis.rs
- examples/djc1.rs
- examples/ceo1.rs
- examples/sdo_lmi.rs
- examples/lo2.rs
- examples/sdo2.rs
- examples/qo1.rs
- examples/qcqo1.rs
- examples/solutionquality.rs
- examples/portfolio_6_factor.rs
- examples/lo1.rs
- examples/cqo1.rs
- examples/sensitivity.rs
- examples/concurrent1.rs
- examples/reoptimization.rs
- examples/portfolio_4_transcost.rs
- examples/portfolio_5_card.rs
- examples/portfolio_3_impact.rs
- examples/milo1.rs
- examples/sdo1.rs
sourcepub fn with_stream_callback<F, G, R>(
&mut self,
whichstream: i32,
streamfunc: &F,
func: G
) -> R
pub fn with_stream_callback<F, G, R>( &mut self, whichstream: i32, streamfunc: &F, func: G ) -> R
Temporarily attach a stream printer function to the task.
§Arguments
whichstreamWhich stream to attach to (See Streamtype)streamfuncThe callback functionfuncThe function to call with the updated task. The stream callback will be attached for the duration of this call.
Examples found in repository?
examples/callback.rs (lines 125-134)
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fn callbackmain(which : &str, data : FileOrText) -> Result<(),String> {
/* Create the optimization task. */
let mut task = Task::new().unwrap();
match data {
FileOrText::Text(data) => { task.read_ptf_string(data)? },
FileOrText::File(fname) => { task.read_data(fname)? }
}
task.write_data("callback.ptf")?;
match which {
"psim" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::PRIMAL_SIMPLEX)?,
"dsim" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::DUAL_SIMPLEX)?,
"intpnt" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::INTPNT)?,
s => return Err(format!("Invalid argument '{}'",s))
}
/* Directs the log task stream to the 'printstr' function. */
task.with_stream_callback(
Streamtype::LOG,
& mut |msg| print!("{}",msg),
|task|
task.with_info_callback(
& mut callback,
|task|
task.optimize()
)
)?;
Result::Ok(())
}More examples
examples/opt_server_async.rs (lines 39-51)
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fn opt_server_async(inputfile : FileOrText, addr : String, numpolls : usize, cert : Option<String>) -> Result<(),String> {
// Path to certificate, if any
let token = {
Task::new().unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| {
match inputfile {
FileOrText::File(ref filename) => task.read_data(filename.as_str()).unwrap(),
FileOrText::Text(ref data) => task.read_ptf_string(data.as_str()).unwrap()
}
if let Some(ref cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH,cert.as_str())?;
}
task.async_optimize(addr.as_str(),"")
}).expect("Failed to submit async optimization")
};
println!("Task token = '{}'", token);
println!("Setting log stream...");
Task::new().unwrap().with_stream_callback(
Streamtype::LOG,
& mut |msg| print!("{}",msg),
|task| task.with_callback(
&mut|caller| { println!("caller = {}",caller); false },
|task| {
println!("Reading input file '{:?}'...",inputfile);
match inputfile {
FileOrText::File(ref filename) => task.read_data(filename.as_str()).unwrap(),
FileOrText::Text(ref data) => task.read_ptf_string(data.as_str()).unwrap()
}
if let Some(ref cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH,cert.as_str())?;
}
println!("Starting polling loop...");
for i in 0..numpolls {
sleep(Duration::new(1,0));
println!("\tpoll {}...", i);
let mut trm : i32 = 0;
let mut resp : i32 = 0;
let respavailable = task.async_poll(addr.as_str(),
"",
token.as_str(),
& mut resp,
& mut trm)?;
if respavailable {
println!("solution available!");
task.async_get_result(addr.as_str(),
"",
token.as_str(),
& mut resp,
& mut trm)?;
task.solution_summary (Streamtype::LOG)?;
return Ok(());
}
}
println!("max num polls reached, stopping host.");
task.async_stop (addr.as_str(), "", token.as_str())?;
Err("Max num polls".to_string())
}))
}examples/ceo1.rs (lines 45-99)
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fn main() -> Result<(),String> {
let numcon = 1;
let numvar = 3;
let bkc = mosek::Boundkey::FX;
let blc = 1.0;
let buc = 1.0;
let bkx = vec![ Boundkey::FR,
Boundkey::FR,
Boundkey::FR ];
let blx = vec![ -INF, -INF, -INF ];
let bux = vec![ INF, INF, INF ];
let c = vec![ 1.0, 1.0, 0.0 ];
let a = vec![ 1.0, 1.0, 1.0 ];
let asub = vec![0, 1, 2];
//let csub = new int[numvar];
//double[] xx = new double[numvar];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|task| task.with_callback(
&mut |caller| { println!("caller = {}",caller); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
/* Define the linear part of the problem */
task.put_c_slice(0, numvar, c.as_slice())?;
task.put_a_row(0, asub.as_slice(), a.as_slice())?;
task.put_con_bound(0, bkc, blc, buc)?;
task.put_var_bound_slice(0, numvar, bkx.as_slice(), blx.as_slice(), bux.as_slice())?;
/* Add a conic constraint */
task.append_afes(3)?;
let afeidxs = vec![0, 1, 2 ];
let b = vec![0.0,0.0,0.0];
let domidx = task.append_primal_exp_cone_domain()?;
task.put_afe_f_row_list(afeidxs.as_slice(),
vec![1,1,1].as_slice(),
vec![0,1,2].as_slice(),
vec![0,1,2].as_slice(),
vec![1.0,1.0,1.0].as_slice())?;
task.append_acc(domidx,afeidxs.as_slice(),b.as_slice())?;
task.put_obj_sense(Objsense::MINIMIZE)?;
println!("optimize");
/* Solve the problem */
task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
/* Get status information about the solution */
let solsta = task.get_sol_sta(Soltype::ITR)?;
assert!(solsta == Solsta::OPTIMAL);
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITR, & mut xx[..])?;
println!("Optimal primal solution");
for j in 0..numvar as usize {
println!("x[{}]: {:.4}",j,xx[j]);
}
Ok(())
}))
}examples/concurrent1.rs (lines 163-170)
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fn concurrent1(data : FileOrText, timelimit : Option<String>) -> Result<(),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
match data {
FileOrText::File(fname) => task.read_data(fname.as_str())?,
FileOrText::Text(text) => task.read_ptf_string(text.as_str())?
}
if let Some(timelimit) = timelimit {
task.put_dou_param(mosek::Dparam::OPTIMIZER_MAX_TIME, timelimit.parse().unwrap())?;
}
let numintvar = task.get_num_int_var()?;
let r = if numintvar == 0 {
let optimizers = &[mosek::Optimizertype::CONIC,
mosek::Optimizertype::DUAL_SIMPLEX,
mosek::Optimizertype::PRIMAL_SIMPLEX];
optimize_concurrent(& mut task, optimizers)
}
else {
let seeds = &[ 42, 13, 71749373 ];
optimize_concurrent_mio(& mut task, seeds)
};
let sense = task.get_obj_sense()?;
// Pick the feasible result. For non-integer problems all
// solutions should be the same if more than one is returned, but
// for integer problems tasks may have hit the time limit and
// returned non-optimal solutions.
let n = r.len();
if n == 0 {
println!("All optimizers failed.");
}
else if numintvar > 0 {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
ii.iter().zip(tasks.iter()).enumerate()
.filter_map(|(k,(_i,t))|
match (*t).solution_def(Soltype::ITG) {
Ok(true) => match t.get_sol_sta(Soltype::ITG).unwrap() {
Solsta::PRIM_FEAS|Solsta::INTEGER_OPTIMAL => Some((k,t.get_primal_obj(Soltype::ITG).unwrap())),
_ => None
},
_ => None
})
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
else {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
tasks.iter().enumerate()
.filter_map(|(k,t)|
match t.get_sol_sta(Soltype::BAS) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::BAS).unwrap())),
_ => None
}.or_else(|| match t.get_sol_sta(Soltype::ITR) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::ITR).unwrap())),
_ => None
}))
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
Result::Ok(())
}examples/milo1.rs (lines 38-125)
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fn main() -> Result<(),String> {
let numcon : i32 = 2;
let numvar : i32 = 2;
let infinity = 0.0; // only for symbolic purposes, value never used
let bkc = vec![Boundkey::UP, Boundkey::LO];
let blc = vec![ -infinity, -4.0 ];
let buc = vec![ 250.0, infinity ];
let bkx = vec![ Boundkey::LO, Boundkey::LO ];
let blx = vec![ 0.0, 0.0 ];
let bux = vec![ infinity, infinity ];
let c = vec![1.0, 0.64];
let asub = vec![0, 1,
0, 1];
let aval = vec![50.0, 3.0, 31.0, -2.0];
let ptrb : Vec<usize> = vec![ 0, 2 ];
let ptre : Vec<usize> = vec![ 2, 4 ];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| task.with_itg_sol_callback(
&mut |xx| { println!("Found a new solution = {:?}",xx); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
for ((((j,cj),bk),bl),bu) in (0..numvar).zip(c.iter()).zip(bkx.iter()).zip(blx.iter()).zip(bux.iter()) {
/* Set the linear term c_j in the objective.*/
task.put_c_j(j, *cj)?;
/* Set the bounds on variable j.
blx[j] <= x_j <= bux[j] */
task.put_var_bound(j, *bk, *bl, *bu)?;
/* Input column j of A */
task.put_a_col(j, /* Variable (column) index.*/
&asub[ptrb[j as usize]..ptre[j as usize]], /* Row index of non-zeros in column j.*/
&aval[ptrb[j as usize]..ptre[j as usize]])?; /* Non-zero Values of column j. */
}
// Set the bounds on constraints.
// for i=1, ...,numcon : blc[i] <= constraint i <= buc[i]
for (((i,bk),bl),bu) in (0..numcon).zip(bkc.iter()).zip(blc.iter()).zip(buc.iter()) {
task.put_con_bound(i, *bk, *bl, *bu)?;
}
/* Specify integer variables. */
for j in 0..numvar {
task.put_var_type(j, Variabletype::TYPE_INT)?;
}
/* Set max solution time */
task.put_dou_param(Dparam::MIO_MAX_TIME, 60.0)?;
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITG, xx.as_mut_slice())?;
/* Get status information about the solution */
match task.get_sol_sta(Soltype::ITG)? {
Solsta::INTEGER_OPTIMAL => {
println!("Optimal solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::PRIM_FEAS => {
println!("Feasible solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::UNKNOWN => {
match task.get_pro_sta(Soltype::ITG)? {
Prosta::PRIM_INFEAS_OR_UNBOUNDED => {
println!("Problem status Infeasible or unbounded");
}
Prosta::PRIM_INFEAS => {
println!("Problem status Infeasible.");
}
Prosta::UNKNOWN => {
println!("Problem status unknown.");
}
_ => {
println!("Other problem status.");
}
}
}
_ => {
println!("Other solution status");
}
}
Ok(())
}))
}sourcepub fn with_callback<F, G, R>(&mut self, cbfunc: &mut F, body: G) -> R
pub fn with_callback<F, G, R>(&mut self, cbfunc: &mut F, body: G) -> R
Temporarily attach a code callback to the task.
For the duration of the call of body, the code callback will be set to cbfunc.
§Arguments
cbfuncA callback function that may be called repeatedlybodyA function(& mut Task) -> Rthat is called exactly once.
Examples found in repository?
examples/concurrent1.rs (lines 25-34)
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fn optimize(mut t : mosek::Task, stop : Arc<Mutex<bool>>) -> Option<(i32,mosek::Task)> {
let cbstop = Arc::clone(&stop);
if let Some(trm) = t.with_callback(
&mut |_| cbstop.lock().and_then(|p| Ok(*p)).unwrap_or(false),
|task|
if let Ok(trm) = task.optimize() {
let mut st = stop.lock().unwrap();
*st = true;
Some(trm)
} else {
None
}) {
Some((trm,t))
}
else {
None
}
}More examples
examples/opt_server_async.rs (lines 60-104)
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fn opt_server_async(inputfile : FileOrText, addr : String, numpolls : usize, cert : Option<String>) -> Result<(),String> {
// Path to certificate, if any
let token = {
Task::new().unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| {
match inputfile {
FileOrText::File(ref filename) => task.read_data(filename.as_str()).unwrap(),
FileOrText::Text(ref data) => task.read_ptf_string(data.as_str()).unwrap()
}
if let Some(ref cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH,cert.as_str())?;
}
task.async_optimize(addr.as_str(),"")
}).expect("Failed to submit async optimization")
};
println!("Task token = '{}'", token);
println!("Setting log stream...");
Task::new().unwrap().with_stream_callback(
Streamtype::LOG,
& mut |msg| print!("{}",msg),
|task| task.with_callback(
&mut|caller| { println!("caller = {}",caller); false },
|task| {
println!("Reading input file '{:?}'...",inputfile);
match inputfile {
FileOrText::File(ref filename) => task.read_data(filename.as_str()).unwrap(),
FileOrText::Text(ref data) => task.read_ptf_string(data.as_str()).unwrap()
}
if let Some(ref cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH,cert.as_str())?;
}
println!("Starting polling loop...");
for i in 0..numpolls {
sleep(Duration::new(1,0));
println!("\tpoll {}...", i);
let mut trm : i32 = 0;
let mut resp : i32 = 0;
let respavailable = task.async_poll(addr.as_str(),
"",
token.as_str(),
& mut resp,
& mut trm)?;
if respavailable {
println!("solution available!");
task.async_get_result(addr.as_str(),
"",
token.as_str(),
& mut resp,
& mut trm)?;
task.solution_summary (Streamtype::LOG)?;
return Ok(());
}
}
println!("max num polls reached, stopping host.");
task.async_stop (addr.as_str(), "", token.as_str())?;
Err("Max num polls".to_string())
}))
}examples/ceo1.rs (lines 48-99)
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fn main() -> Result<(),String> {
let numcon = 1;
let numvar = 3;
let bkc = mosek::Boundkey::FX;
let blc = 1.0;
let buc = 1.0;
let bkx = vec![ Boundkey::FR,
Boundkey::FR,
Boundkey::FR ];
let blx = vec![ -INF, -INF, -INF ];
let bux = vec![ INF, INF, INF ];
let c = vec![ 1.0, 1.0, 0.0 ];
let a = vec![ 1.0, 1.0, 1.0 ];
let asub = vec![0, 1, 2];
//let csub = new int[numvar];
//double[] xx = new double[numvar];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|task| task.with_callback(
&mut |caller| { println!("caller = {}",caller); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
/* Define the linear part of the problem */
task.put_c_slice(0, numvar, c.as_slice())?;
task.put_a_row(0, asub.as_slice(), a.as_slice())?;
task.put_con_bound(0, bkc, blc, buc)?;
task.put_var_bound_slice(0, numvar, bkx.as_slice(), blx.as_slice(), bux.as_slice())?;
/* Add a conic constraint */
task.append_afes(3)?;
let afeidxs = vec![0, 1, 2 ];
let b = vec![0.0,0.0,0.0];
let domidx = task.append_primal_exp_cone_domain()?;
task.put_afe_f_row_list(afeidxs.as_slice(),
vec![1,1,1].as_slice(),
vec![0,1,2].as_slice(),
vec![0,1,2].as_slice(),
vec![1.0,1.0,1.0].as_slice())?;
task.append_acc(domidx,afeidxs.as_slice(),b.as_slice())?;
task.put_obj_sense(Objsense::MINIMIZE)?;
println!("optimize");
/* Solve the problem */
task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
/* Get status information about the solution */
let solsta = task.get_sol_sta(Soltype::ITR)?;
assert!(solsta == Solsta::OPTIMAL);
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITR, & mut xx[..])?;
println!("Optimal primal solution");
for j in 0..numvar as usize {
println!("x[{}]: {:.4}",j,xx[j]);
}
Ok(())
}))
}sourcepub fn with_info_callback<F, G, R>(&mut self, cbfunc: &mut F, body: G) -> R
pub fn with_info_callback<F, G, R>(&mut self, cbfunc: &mut F, body: G) -> R
Temporarily attach an info callback to the task.
For the duration of the call of body, the code callback will be set to cbfunc.
§Arguments
cbfuncA callback function that may be called repeatedlybodyA function(& mut Task) -> Rthat is called exactly once.
Examples found in repository?
examples/callback.rs (lines 129-133)
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fn callbackmain(which : &str, data : FileOrText) -> Result<(),String> {
/* Create the optimization task. */
let mut task = Task::new().unwrap();
match data {
FileOrText::Text(data) => { task.read_ptf_string(data)? },
FileOrText::File(fname) => { task.read_data(fname)? }
}
task.write_data("callback.ptf")?;
match which {
"psim" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::PRIMAL_SIMPLEX)?,
"dsim" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::DUAL_SIMPLEX)?,
"intpnt" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::INTPNT)?,
s => return Err(format!("Invalid argument '{}'",s))
}
/* Directs the log task stream to the 'printstr' function. */
task.with_stream_callback(
Streamtype::LOG,
& mut |msg| print!("{}",msg),
|task|
task.with_info_callback(
& mut callback,
|task|
task.optimize()
)
)?;
Result::Ok(())
}sourcepub fn with_itg_sol_callback<F, G, R>(&mut self, cbfunc: &mut F, body: G) -> R
pub fn with_itg_sol_callback<F, G, R>(&mut self, cbfunc: &mut F, body: G) -> R
Temporarily attach an info callback to the task.
For the duration of the call of body, the code callback will be set to cbfunc.
§Arguments
cbfuncA callback function that may be called repeatedlybodyA function(& mut Task) -> Rthat is called exactly once.
Examples found in repository?
examples/milo1.rs (lines 41-125)
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fn main() -> Result<(),String> {
let numcon : i32 = 2;
let numvar : i32 = 2;
let infinity = 0.0; // only for symbolic purposes, value never used
let bkc = vec![Boundkey::UP, Boundkey::LO];
let blc = vec![ -infinity, -4.0 ];
let buc = vec![ 250.0, infinity ];
let bkx = vec![ Boundkey::LO, Boundkey::LO ];
let blx = vec![ 0.0, 0.0 ];
let bux = vec![ infinity, infinity ];
let c = vec![1.0, 0.64];
let asub = vec![0, 1,
0, 1];
let aval = vec![50.0, 3.0, 31.0, -2.0];
let ptrb : Vec<usize> = vec![ 0, 2 ];
let ptre : Vec<usize> = vec![ 2, 4 ];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| task.with_itg_sol_callback(
&mut |xx| { println!("Found a new solution = {:?}",xx); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
for ((((j,cj),bk),bl),bu) in (0..numvar).zip(c.iter()).zip(bkx.iter()).zip(blx.iter()).zip(bux.iter()) {
/* Set the linear term c_j in the objective.*/
task.put_c_j(j, *cj)?;
/* Set the bounds on variable j.
blx[j] <= x_j <= bux[j] */
task.put_var_bound(j, *bk, *bl, *bu)?;
/* Input column j of A */
task.put_a_col(j, /* Variable (column) index.*/
&asub[ptrb[j as usize]..ptre[j as usize]], /* Row index of non-zeros in column j.*/
&aval[ptrb[j as usize]..ptre[j as usize]])?; /* Non-zero Values of column j. */
}
// Set the bounds on constraints.
// for i=1, ...,numcon : blc[i] <= constraint i <= buc[i]
for (((i,bk),bl),bu) in (0..numcon).zip(bkc.iter()).zip(blc.iter()).zip(buc.iter()) {
task.put_con_bound(i, *bk, *bl, *bu)?;
}
/* Specify integer variables. */
for j in 0..numvar {
task.put_var_type(j, Variabletype::TYPE_INT)?;
}
/* Set max solution time */
task.put_dou_param(Dparam::MIO_MAX_TIME, 60.0)?;
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITG, xx.as_mut_slice())?;
/* Get status information about the solution */
match task.get_sol_sta(Soltype::ITG)? {
Solsta::INTEGER_OPTIMAL => {
println!("Optimal solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::PRIM_FEAS => {
println!("Feasible solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::UNKNOWN => {
match task.get_pro_sta(Soltype::ITG)? {
Prosta::PRIM_INFEAS_OR_UNBOUNDED => {
println!("Problem status Infeasible or unbounded");
}
Prosta::PRIM_INFEAS => {
println!("Problem status Infeasible.");
}
Prosta::UNKNOWN => {
println!("Problem status unknown.");
}
_ => {
println!("Other problem status.");
}
}
}
_ => {
println!("Other solution status");
}
}
Ok(())
}))
}sourcepub fn with_callbacks(self) -> TaskCB
pub fn with_callbacks(self) -> TaskCB
This converts the Task object into a TaskCB object. The main difference is the the TaskCB enables attaching callback functions (message printing and information callbacks), and that it due to the callbacks cannot be shared between multiple threads.
Examples found in repository?
examples/opt_server_sync.rs (line 32)
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fn opt_server_sync(inputfile : FileOrText, addr : String, cert : Option<String>) -> Result<(),String> {
let mut task = Task::new().unwrap().with_callbacks();
task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
// Load some data into the task
match inputfile {
FileOrText::File(filename) => task.read_data(filename.as_str())?,
FileOrText::Text(data) => task.read_ptf_string(data.as_str())?
}
// Set OptServer URL
task.put_optserver_host(addr.as_str())?;
// Path to certificate, if any
if let Some(cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH, cert.as_str())?;
}
// Optimize remotely, no access token
let _trm = task.optimize()?;
task.solution_summary(Streamtype::LOG)?;
Ok(())
}More examples
examples/feasrepairex1.rs (line 37)
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fn feasrepairex1(filename : FileOrText) -> Result<(),String> {
let mut task = Task::new().unwrap().with_callbacks();
task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
match filename {
FileOrText::File(fname) => task.read_data(fname.as_str())?,
FileOrText::Text(data) => task.read_lp_string(data.as_str())?
}
task.put_int_param(mosek::Iparam::LOG_FEAS_REPAIR, 3)?;
let wc = vec![1.0; task.get_num_con()? as usize];
let wx = vec![1.0; task.get_num_var()? as usize];
task.primal_repair(wc.as_slice(),wc.as_slice(),wx.as_slice(),wx.as_slice())?;
let sum_viol = task.get_dou_inf(mosek::Dinfitem::PRIMAL_REPAIR_PENALTY_OBJ)?;
println!("Minimized sum of violations = {}", sum_viol);
let _ = task.optimize()?;
task.solution_summary(mosek::Streamtype::MSG)?;
Ok(())
}examples/simple.rs (line 30)
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fn simple(filename : FileOrText, outfile : Option<String>) -> Result<(),String> {
let mut task = Task::new().unwrap().with_callbacks();
task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
// We assume that a problem file was given as the first command
// line argument (received in `args')
match filename {
FileOrText::File(fname) => {
task.read_data(fname.as_str())?
},
FileOrText::Text(data) => {
task.read_ptf_string(data.as_str())?
}
}
// Solve the problem
let _ = task.optimize()?;
// Print a summary of the solution
task.solution_summary(Streamtype::LOG)?;
// If an output file was specified, save problem to file
if let Some(outfile) = outfile {
// If using OPF format, these parameters will specify what to include in output
task.put_int_param(Iparam::OPF_WRITE_SOLUTIONS, Onoffkey::ON)?;
task.put_int_param(Iparam::OPF_WRITE_PROBLEM, Onoffkey::ON)?;
task.put_int_param(Iparam::OPF_WRITE_HINTS, Onoffkey::OFF)?;
task.put_int_param(Iparam::OPF_WRITE_PARAMETERS, Onoffkey::OFF)?;
task.put_int_param(Iparam::PTF_WRITE_SOLUTIONS, Onoffkey::ON)?;
task.write_data(outfile.as_str())?;
}
Ok(())
}examples/response.rs (line 34)
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fn main() -> Result<(),String> {
let args: Vec<String> = env::args().collect();
let mut task = Task::new().unwrap().with_callbacks();
if args.len() < 2 {
task.read_ptf_string(CQO1_PTF)?;
}
else {
task.read_data(args[1].as_str())?;
}
// Perform optimization.
let trm = task.optimize()?;
task.solution_summary(Streamtype::LOG)?;
// Handle solution status. We expect Optimal
let solsta = task.get_sol_sta(Soltype::ITR)?;
match solsta {
Solsta::OPTIMAL => {
// Fetch and print the solution
println!("An optimal interior point solution is located.");
let numvar = task.get_num_var()?;
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITR, xx.as_mut_slice())?;
println!("xx = {:?}",xx)
},
Solsta::DUAL_INFEAS_CER =>
println!("Dual infeasibility certificate found."),
Solsta::PRIM_INFEAS_CER =>
println!("Primal infeasibility certificate found."),
Solsta::UNKNOWN => {
// The solutions status is unknown. The termination code
// indicates why the optimizer terminated prematurely.
println!("The solution status is unknown.");
let (symname,desc) = mosek::get_code_desc(trm)?;
println!(" Termination code: {} {}\n", symname, desc)
},
_ =>
println!("Unexpected solution status {}\n",solsta)
}
Ok(())
}examples/pinfeas.rs (line 50)
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fn main() -> Result<(),String> {
// In this example we set up a simple problem
// One could use any task or a task read from a file
let mut task = test_problem()?.with_callbacks();
let n = task.get_num_var()?;
let m = task.get_num_con()?;
// Useful for debugging
task.write_data("pinfeas.ptf")?; // Write file in human-readable format
// Attach a log stream printer to the task
task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
// Perform the optimization.
task.optimize()?;
task.solution_summary(Streamtype::LOG)?;
// Check problem status, we use the interior point solution
if task.get_pro_sta(Soltype::ITR)? == Prosta::PRIM_INFEAS {
// Set the tolerance at which we consider a dual value as essential
let eps = 1e-7;
println!("Variable bounds important for infeasibility: ");
let mut slx = vec![0.0; n as usize]; task.get_slx(Soltype::ITR, slx.as_mut_slice())?;
let mut sux = vec![0.0; n as usize]; task.get_sux(Soltype::ITR, sux.as_mut_slice())?;
analyze_certificate(slx.as_slice(), sux.as_slice(), eps);
println!("Constraint bounds important for infeasibility: ");
let mut slc = vec![0.0; m as usize]; task.get_slc(Soltype::ITR, slc.as_mut_slice())?;
let mut suc = vec![0.0; m as usize]; task.get_suc(Soltype::ITR, suc.as_mut_slice())?;
analyze_certificate(slc.as_mut_slice(), suc.as_mut_slice(), eps);
}
else {
println!("The problem is not primal infeasible, no certificate to show");
}
Ok(())
}examples/logistic.rs (line 147)
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fn logistic_regression(X : &[f64],
Y : &[bool],
lamb : f64) -> Result<Vec<f64>,String> {
let n = Y.len() as i32;
let d = (X.len()/Y.len()) as i32; // num samples, dimension
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
}.with_callbacks();
task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
// Variables [r; theta; t]
let nvar : i32 = 1+d+n;
task.append_vars(nvar)?;
task.put_var_bound_slice_const(0, nvar, Boundkey::FR, -INF, INF)?;
let (r,theta,t) = (0i32,1i32,1+d);
task.put_var_name(r,"r")?;
for j in 0..d { task.put_var_name(theta+j,format!("theta[{}]",j).as_str())?; }
for j in 0..n { task.put_var_name(t+j,format!("t[{}]",j).as_str())?; }
// Objective lambda*r + sum(t)
task.put_c_j(r, lamb)?;
for i in 0..n { task.put_c_j(t+i, 1.0)?; }
task.put_obj_sense(Objsense::MINIMIZE)?;
// Softplus function constraints
softplus(& mut task, d, n, theta, t, X, Y)?;
// Regularization
// Append a sequence of linear expressions (r, theta) to F
let numafe = task.get_num_afe()?;
task.append_afes(1+d as i64)?;
task.put_afe_f_entry(numafe, r, 1.0)?;
for i in 0..d {
task.put_afe_f_entry(numafe + i as i64 + 1, theta + i, 1.0)?;
}
// Add the constraint
{
let dom = task.append_quadratic_cone_domain((1+d) as i64)?;
task.append_acc_seq(dom,
numafe,
vec![0.0; 1+d as usize].as_slice())?;
}
// Solution
task.write_data("logistic.ptf")?;
task.optimize()?;
let mut xx = vec![0.0; d as usize];
task.get_xx_slice(Soltype::ITR, theta, theta+d as i32,xx.as_mut_slice())?;
Ok(xx)
}Additional examples can be found in:
- examples/solvelinear.rs
- examples/mico1.rs
- examples/mioinitsol.rs
- examples/acc1.rs
- examples/acc2.rs
- examples/pow1.rs
- examples/gp1.rs
- examples/portfolio_1_basic.rs
- examples/solvebasis.rs
- examples/djc1.rs
- examples/sdo_lmi.rs
- examples/lo2.rs
- examples/sdo2.rs
- examples/qo1.rs
- examples/qcqo1.rs
- examples/solutionquality.rs
- examples/portfolio_6_factor.rs
- examples/lo1.rs
- examples/cqo1.rs
- examples/sensitivity.rs
- examples/portfolio_4_transcost.rs
- examples/portfolio_3_impact.rs
- examples/sdo1.rs
sourcepub fn write_data_stream<F>(
&self,
func: F,
format: i32,
compress: i32
) -> Result<(), String>
pub fn write_data_stream<F>( &self, func: F, format: i32, compress: i32 ) -> Result<(), String>
sourcepub fn analyze_names(
&self,
whichstream_: i32,
nametype_: i32
) -> Result<(), String>
pub fn analyze_names( &self, whichstream_: i32, nametype_: i32 ) -> Result<(), String>
Analyze the names and issue an error for the first invalid name.
§Arguments
-
whichstream_Index of the stream.See Streamtype
-
nametype_The type of names e.g. valid in MPS or LP files.See Nametype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.analyzenames
sourcepub fn analyze_problem(&self, whichstream_: i32) -> Result<(), String>
pub fn analyze_problem(&self, whichstream_: i32) -> Result<(), String>
Analyze the data of a task.
§Arguments
-
whichstream_Index of the stream.See Streamtype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.analyzeproblem
sourcepub fn analyze_solution(
&self,
whichstream_: i32,
whichsol_: i32
) -> Result<(), String>
pub fn analyze_solution( &self, whichstream_: i32, whichsol_: i32 ) -> Result<(), String>
Print information related to the quality of the solution.
§Arguments
-
whichstream_Index of the stream.See Streamtype
-
whichsol_Selects a solution.See Soltype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.analyzesolution
sourcepub fn append_acc(
&mut self,
domidx_: i64,
afeidxlist_: &[i64],
b_: &[f64]
) -> Result<(), String>
pub fn append_acc( &mut self, domidx_: i64, afeidxlist_: &[i64], b_: &[f64] ) -> Result<(), String>
Appends an affine conic constraint to the task.
§Arguments
domidx_Domain index.afeidxlist_List of affine expression indexes.b_The vector of constant terms modifying affine expressions. Optional.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendacc
Examples found in repository?
examples/ceo1.rs (line 75)
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fn main() -> Result<(),String> {
let numcon = 1;
let numvar = 3;
let bkc = mosek::Boundkey::FX;
let blc = 1.0;
let buc = 1.0;
let bkx = vec![ Boundkey::FR,
Boundkey::FR,
Boundkey::FR ];
let blx = vec![ -INF, -INF, -INF ];
let bux = vec![ INF, INF, INF ];
let c = vec![ 1.0, 1.0, 0.0 ];
let a = vec![ 1.0, 1.0, 1.0 ];
let asub = vec![0, 1, 2];
//let csub = new int[numvar];
//double[] xx = new double[numvar];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|task| task.with_callback(
&mut |caller| { println!("caller = {}",caller); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
/* Define the linear part of the problem */
task.put_c_slice(0, numvar, c.as_slice())?;
task.put_a_row(0, asub.as_slice(), a.as_slice())?;
task.put_con_bound(0, bkc, blc, buc)?;
task.put_var_bound_slice(0, numvar, bkx.as_slice(), blx.as_slice(), bux.as_slice())?;
/* Add a conic constraint */
task.append_afes(3)?;
let afeidxs = vec![0, 1, 2 ];
let b = vec![0.0,0.0,0.0];
let domidx = task.append_primal_exp_cone_domain()?;
task.put_afe_f_row_list(afeidxs.as_slice(),
vec![1,1,1].as_slice(),
vec![0,1,2].as_slice(),
vec![0,1,2].as_slice(),
vec![1.0,1.0,1.0].as_slice())?;
task.append_acc(domidx,afeidxs.as_slice(),b.as_slice())?;
task.put_obj_sense(Objsense::MINIMIZE)?;
println!("optimize");
/* Solve the problem */
task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
/* Get status information about the solution */
let solsta = task.get_sol_sta(Soltype::ITR)?;
assert!(solsta == Solsta::OPTIMAL);
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITR, & mut xx[..])?;
println!("Optimal primal solution");
for j in 0..numvar as usize {
println!("x[{}]: {:.4}",j,xx[j]);
}
Ok(())
}))
}sourcepub fn append_accs(
&mut self,
domidxs_: &[i64],
afeidxlist_: &[i64],
b_: &[f64]
) -> Result<(), String>
pub fn append_accs( &mut self, domidxs_: &[i64], afeidxlist_: &[i64], b_: &[f64] ) -> Result<(), String>
Appends a number of affine conic constraint to the task.
§Arguments
domidxs_Domain indices.afeidxlist_List of affine expression indexes.b_The vector of constant terms modifying affine expressions. Optional.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendaccs
sourcepub fn append_acc_seq(
&mut self,
domidx_: i64,
afeidxfirst_: i64,
b_: &[f64]
) -> Result<(), String>
pub fn append_acc_seq( &mut self, domidx_: i64, afeidxfirst_: i64, b_: &[f64] ) -> Result<(), String>
Appends an affine conic constraint to the task.
§Arguments
domidx_Domain index.afeidxfirst_Index of the first affine expression.b_The vector of constant terms modifying affine expressions. Optional.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendaccseq
Examples found in repository?
examples/portfolio_2_frontier.rs (lines 85-87)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}More examples
examples/portfolio_5_card.rs (lines 138-140)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}sourcepub fn append_accs_seq(
&mut self,
domidxs_: &[i64],
numafeidx_: i64,
afeidxfirst_: i64,
b_: &[f64]
) -> Result<(), String>
pub fn append_accs_seq( &mut self, domidxs_: &[i64], numafeidx_: i64, afeidxfirst_: i64, b_: &[f64] ) -> Result<(), String>
Appends a number of affine conic constraint to the task.
§Arguments
domidxs_Domain indices.numafeidx_Number of affine expressions in the affine expression list (must equal the sum of dimensions of the domains).afeidxfirst_Index of the first affine expression.b_The vector of constant terms modifying affine expressions. Optional.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendaccsseq
sourcepub fn append_afes(&mut self, num_: i64) -> Result<(), String>
pub fn append_afes(&mut self, num_: i64) -> Result<(), String>
Appends a number of empty affine expressions to the optimization task.
§Arguments
num_Number of empty affine expressions which should be appended.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendafes
Examples found in repository?
examples/portfolio_2_frontier.rs (line 83)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}More examples
examples/ceo1.rs (line 66)
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fn main() -> Result<(),String> {
let numcon = 1;
let numvar = 3;
let bkc = mosek::Boundkey::FX;
let blc = 1.0;
let buc = 1.0;
let bkx = vec![ Boundkey::FR,
Boundkey::FR,
Boundkey::FR ];
let blx = vec![ -INF, -INF, -INF ];
let bux = vec![ INF, INF, INF ];
let c = vec![ 1.0, 1.0, 0.0 ];
let a = vec![ 1.0, 1.0, 1.0 ];
let asub = vec![0, 1, 2];
//let csub = new int[numvar];
//double[] xx = new double[numvar];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|task| task.with_callback(
&mut |caller| { println!("caller = {}",caller); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
/* Define the linear part of the problem */
task.put_c_slice(0, numvar, c.as_slice())?;
task.put_a_row(0, asub.as_slice(), a.as_slice())?;
task.put_con_bound(0, bkc, blc, buc)?;
task.put_var_bound_slice(0, numvar, bkx.as_slice(), blx.as_slice(), bux.as_slice())?;
/* Add a conic constraint */
task.append_afes(3)?;
let afeidxs = vec![0, 1, 2 ];
let b = vec![0.0,0.0,0.0];
let domidx = task.append_primal_exp_cone_domain()?;
task.put_afe_f_row_list(afeidxs.as_slice(),
vec![1,1,1].as_slice(),
vec![0,1,2].as_slice(),
vec![0,1,2].as_slice(),
vec![1.0,1.0,1.0].as_slice())?;
task.append_acc(domidx,afeidxs.as_slice(),b.as_slice())?;
task.put_obj_sense(Objsense::MINIMIZE)?;
println!("optimize");
/* Solve the problem */
task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
/* Get status information about the solution */
let solsta = task.get_sol_sta(Soltype::ITR)?;
assert!(solsta == Solsta::OPTIMAL);
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITR, & mut xx[..])?;
println!("Optimal primal solution");
for j in 0..numvar as usize {
println!("x[{}]: {:.4}",j,xx[j]);
}
Ok(())
}))
}examples/portfolio_5_card.rs (line 136)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}sourcepub fn append_barvars(&mut self, dim_: &[i32]) -> Result<(), String>
pub fn append_barvars(&mut self, dim_: &[i32]) -> Result<(), String>
Appends semidefinite variables to the problem.
§Arguments
dim_Dimensions of symmetric matrix variables to be added.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendbarvars
sourcepub fn append_cone(
&mut self,
ct_: i32,
conepar_: f64,
submem_: &[i32]
) -> Result<(), String>
pub fn append_cone( &mut self, ct_: i32, conepar_: f64, submem_: &[i32] ) -> Result<(), String>
Appends a new conic constraint to the problem.
§Arguments
-
ct_Specifies the type of the cone.See Conetype
-
conepar_For the power cone it denotes the exponent alpha. For other cone types it is unused and can be set to 0. -
submem_Variable subscripts of the members in the cone.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendcone
sourcepub fn append_cone_seq(
&mut self,
ct_: i32,
conepar_: f64,
nummem_: i32,
j_: i32
) -> Result<(), String>
pub fn append_cone_seq( &mut self, ct_: i32, conepar_: f64, nummem_: i32, j_: i32 ) -> Result<(), String>
Appends a new conic constraint to the problem.
§Arguments
-
ct_Specifies the type of the cone.See Conetype
-
conepar_For the power cone it denotes the exponent alpha. For other cone types it is unused and can be set to 0. -
nummem_Number of member variables in the cone. -
j_Index of the first variable in the conic constraint.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendconeseq
sourcepub fn append_cones_seq(
&mut self,
ct_: &[i32],
conepar_: &[f64],
nummem_: &[i32],
j_: i32
) -> Result<(), String>
pub fn append_cones_seq( &mut self, ct_: &[i32], conepar_: &[f64], nummem_: &[i32], j_: i32 ) -> Result<(), String>
Appends multiple conic constraints to the problem.
§Arguments
-
ct_Specifies the type of the cone.See Conetype
-
conepar_For the power cone it denotes the exponent alpha. For other cone types it is unused and can be set to 0. -
nummem_Numbers of member variables in the cones. -
j_Index of the first variable in the first cone to be appended.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendconesseq
sourcepub fn append_cons(&mut self, num_: i32) -> Result<(), String>
pub fn append_cons(&mut self, num_: i32) -> Result<(), String>
Appends a number of constraints to the optimization task.
§Arguments
num_Number of constraints which should be appended.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendcons
Examples found in repository?
examples/pinfeas.rs (line 18)
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fn test_problem() -> Result<mosek::Task,String> {
let mut task = mosek::Task::new().unwrap();
task.append_vars(7)?;
task.append_cons(7)?;
task.put_c_list(&[0,1,2,3,4,5,6],
&[1.0,2.0,5.0,2.0,1.0,2.0,1.0])?;
task.put_aij_list(&[0,0,1,1,2,2,2,3,3,4,5,5,6,6],
&[0,1,2,3,4,5,6,0,4,1,2,5,3,6],
&[1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0])?;
task.put_con_bound_slice(0, 7,
&[Boundkey::UP,Boundkey::UP,Boundkey::UP,Boundkey::FX,Boundkey::FX,Boundkey::FX,Boundkey::FX],
&[-INF, -INF, -INF, 1100.0, 200.0, 500.0, 500.0],
&[200.0, 1000.0, 1000.0, 1100.0, 200.0, 500.0, 500.0])?;
task.put_var_bound_slice_const(0, 7, Boundkey::UP, 0.0, INF)?;
Ok(task)
}More examples
examples/solvelinear.rs (line 42)
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fn setup(task : & mut mosek::Task,
aval : &[f64],
asub : &[i32],
ptrb : &[i64],
ptre : &[i64],
numvar : i32) -> Result<Vec<i32>,String> {
// mosek.stakey[] skx = new mosek.stakey [numvar];
// mosek.stakey[] skc = new mosek.stakey [numvar];
// for (int i = 0; i < numvar ; ++i) {
// skx[i] = mosek.stakey.bas;
// skc[i] = mosek.stakey.fix;
// }
task.append_vars(numvar)?;
task.append_cons(numvar)?;
task.put_a_col_slice(0,numvar,ptrb,ptre,asub,aval)?;
task.put_con_bound_slice_const(0,numvar,Boundkey::FX,0.0,0.0)?;
task.put_var_bound_slice_const(0,numvar,Boundkey::FR,-INF,INF)?;
/* Define a basic solution by specifying
status keys for variables & constraints. */
task.delete_solution(Soltype::BAS)?;
task.put_skc_slice(Soltype::BAS, 0, numvar, vec![Stakey::FIX; numvar as usize].as_slice())?;
task.put_skx_slice(Soltype::BAS, 0, numvar, vec![Stakey::BAS; numvar as usize].as_slice())?;
let mut basis = vec![0; numvar as usize];
task.init_basis_solve(basis.as_mut_slice())?;
Ok(basis)
}examples/portfolio_2_frontier.rs (line 50)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}examples/ceo1.rs (line 53)
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fn main() -> Result<(),String> {
let numcon = 1;
let numvar = 3;
let bkc = mosek::Boundkey::FX;
let blc = 1.0;
let buc = 1.0;
let bkx = vec![ Boundkey::FR,
Boundkey::FR,
Boundkey::FR ];
let blx = vec![ -INF, -INF, -INF ];
let bux = vec![ INF, INF, INF ];
let c = vec![ 1.0, 1.0, 0.0 ];
let a = vec![ 1.0, 1.0, 1.0 ];
let asub = vec![0, 1, 2];
//let csub = new int[numvar];
//double[] xx = new double[numvar];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|task| task.with_callback(
&mut |caller| { println!("caller = {}",caller); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
/* Define the linear part of the problem */
task.put_c_slice(0, numvar, c.as_slice())?;
task.put_a_row(0, asub.as_slice(), a.as_slice())?;
task.put_con_bound(0, bkc, blc, buc)?;
task.put_var_bound_slice(0, numvar, bkx.as_slice(), blx.as_slice(), bux.as_slice())?;
/* Add a conic constraint */
task.append_afes(3)?;
let afeidxs = vec![0, 1, 2 ];
let b = vec![0.0,0.0,0.0];
let domidx = task.append_primal_exp_cone_domain()?;
task.put_afe_f_row_list(afeidxs.as_slice(),
vec![1,1,1].as_slice(),
vec![0,1,2].as_slice(),
vec![0,1,2].as_slice(),
vec![1.0,1.0,1.0].as_slice())?;
task.append_acc(domidx,afeidxs.as_slice(),b.as_slice())?;
task.put_obj_sense(Objsense::MINIMIZE)?;
println!("optimize");
/* Solve the problem */
task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
/* Get status information about the solution */
let solsta = task.get_sol_sta(Soltype::ITR)?;
assert!(solsta == Solsta::OPTIMAL);
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITR, & mut xx[..])?;
println!("Optimal primal solution");
for j in 0..numvar as usize {
println!("x[{}]: {:.4}",j,xx[j]);
}
Ok(())
}))
}examples/reoptimization.rs (line 51)
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fn main() -> Result<(),String> {
let numcon = 3;
let numvar = 3;
let c = &[1.5, 2.5, 3.0 ];
let bkc = &[ Boundkey::UP,
Boundkey::UP,
Boundkey::UP ];
let blc = &[ -INF,
-INF,
-INF ];
let buc = &[ 100000.0,
50000.0,
60000.0 ];
let bkx = &[ Boundkey::LO,
Boundkey::LO,
Boundkey::LO
];
let blx = &[ 0.0, 0.0, 0.0 ];
let bux = &[ INF,
INF,
INF ];
let asub = &[
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ] ];
let aval = &[
&[ 2.0, 3.0, 2.0 ],
&[ 4.0, 2.0, 3.0 ],
&[ 3.0, 3.0, 2.0 ] ];
let mut task = Task::new().unwrap();
/* Append the constraints. */
task.append_cons(numcon)?;
/* Append the variables. */
task.append_vars(numvar)?;
/* Put C. */
for (j,&cj) in (0..numvar).zip(c.iter()) {
task.put_c_j(j,cj)?;
}
/* Put constraint bounds. */
for (i,&bki,&bli,&bui) in izip!(0..numcon,bkc,blc,buc) {
task.put_con_bound(i, bki, bli, bui)?;
}
/* Put variable bounds. */
for (j,&bki,&bli,&bui) in izip!(0..numvar,bkx,blx,bux) {
task.put_var_bound(j, bki, bli, bui)?;
}
/* Put A. */
if numcon > 0 {
for (j,&asubj,&avalj) in izip!(0..numvar,asub,aval) {
task.put_a_col(j,
asubj,
avalj)?;
}
}
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/****************** Make a change to the A matrix ******************/
task.put_aij(0, 0, 3.0)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/***************** Add a new variable ******************************/
/* Get index of new variable. */
let varidx = task.get_num_var()?;
/* Append a new variable x_3 to the problem */
task.append_vars(1)?;
let numvar = numvar + 1;
/* Set bounds on new varaible */
task.put_var_bound(varidx, Boundkey::LO, 0.0, INF)?;
/* Change objective */
task.put_c_j(varidx, 1.0)?;
/* Put new values in the A matrix */
let acolsub = &[0i32, 2];
let acolval = &[4.0, 1.0];
task.put_a_col(varidx, /* column index */
acolsub,
acolval)?;
/* Change optimizer to simplex free and reoptimize */
task.put_int_param(mosek::Iparam::OPTIMIZER, mosek::Optimizertype::FREE_SIMPLEX)?;
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Add a new constraint ***************************/
/* Get index of new constraint. */
let conidx = task.get_num_con()?;
/* Append a new constraint */
task.append_cons(1)?;
let numcon = numcon + 1;
/* Set bounds on new constraint */
task.put_con_bound(conidx,
Boundkey::UP,
-INF,
30000.0)?;
/* Put new values in the A matrix */
let arowsub = &[0i32, 1, 2, 3 ];
let arowval = &[1.0, 2.0, 1.0, 1.0 ];
task.put_a_row(conidx, /* row index */
arowsub,
arowval)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Change constraint bounds ********************/
let newbkc = &[Boundkey::UP,
Boundkey::UP,
Boundkey::UP,
Boundkey::UP];
let newblc = &[-INF,
-INF,
-INF,
-INF];
let newbuc = &[ 80000.0, 40000.0, 50000.0, 22000.0 ];
task.put_con_bound_slice(0, numcon, newbkc, newblc, newbuc)?;
let _ = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
Ok(())
}examples/portfolio_5_card.rs (line 94)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}Additional examples can be found in:
sourcepub fn append_djcs(&mut self, num_: i64) -> Result<(), String>
pub fn append_djcs(&mut self, num_: i64) -> Result<(), String>
Appends a number of empty disjunctive constraints to the task.
§Arguments
num_Number of empty disjunctive constraints which should be appended.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appenddjcs
sourcepub fn append_dual_exp_cone_domain(&mut self) -> Result<i64, String>
pub fn append_dual_exp_cone_domain(&mut self) -> Result<i64, String>
Appends the dual exponential cone domain.
§Returns
domidxIndex of the domain.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appenddualexpconedomain
sourcepub fn append_dual_geo_mean_cone_domain(
&mut self,
n_: i64
) -> Result<i64, String>
pub fn append_dual_geo_mean_cone_domain( &mut self, n_: i64 ) -> Result<i64, String>
Appends the dual geometric mean cone domain.
§Arguments
n_Dimmension of the domain.
§Returns
domidxIndex of the domain.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appenddualgeomeanconedomain
sourcepub fn append_dual_power_cone_domain(
&mut self,
n_: i64,
alpha_: &[f64]
) -> Result<i64, String>
pub fn append_dual_power_cone_domain( &mut self, n_: i64, alpha_: &[f64] ) -> Result<i64, String>
Appends the dual power cone domain.
§Arguments
n_Dimension of the domain.alpha_The sequence proportional to exponents. Must be positive.
§Returns
domidxIndex of the domain.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appenddualpowerconedomain
sourcepub fn append_primal_exp_cone_domain(&mut self) -> Result<i64, String>
pub fn append_primal_exp_cone_domain(&mut self) -> Result<i64, String>
Appends the primal exponential cone domain.
§Returns
domidxIndex of the domain.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendprimalexpconedomain
Examples found in repository?
examples/ceo1.rs (line 69)
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fn main() -> Result<(),String> {
let numcon = 1;
let numvar = 3;
let bkc = mosek::Boundkey::FX;
let blc = 1.0;
let buc = 1.0;
let bkx = vec![ Boundkey::FR,
Boundkey::FR,
Boundkey::FR ];
let blx = vec![ -INF, -INF, -INF ];
let bux = vec![ INF, INF, INF ];
let c = vec![ 1.0, 1.0, 0.0 ];
let a = vec![ 1.0, 1.0, 1.0 ];
let asub = vec![0, 1, 2];
//let csub = new int[numvar];
//double[] xx = new double[numvar];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|task| task.with_callback(
&mut |caller| { println!("caller = {}",caller); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
/* Define the linear part of the problem */
task.put_c_slice(0, numvar, c.as_slice())?;
task.put_a_row(0, asub.as_slice(), a.as_slice())?;
task.put_con_bound(0, bkc, blc, buc)?;
task.put_var_bound_slice(0, numvar, bkx.as_slice(), blx.as_slice(), bux.as_slice())?;
/* Add a conic constraint */
task.append_afes(3)?;
let afeidxs = vec![0, 1, 2 ];
let b = vec![0.0,0.0,0.0];
let domidx = task.append_primal_exp_cone_domain()?;
task.put_afe_f_row_list(afeidxs.as_slice(),
vec![1,1,1].as_slice(),
vec![0,1,2].as_slice(),
vec![0,1,2].as_slice(),
vec![1.0,1.0,1.0].as_slice())?;
task.append_acc(domidx,afeidxs.as_slice(),b.as_slice())?;
task.put_obj_sense(Objsense::MINIMIZE)?;
println!("optimize");
/* Solve the problem */
task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
/* Get status information about the solution */
let solsta = task.get_sol_sta(Soltype::ITR)?;
assert!(solsta == Solsta::OPTIMAL);
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITR, & mut xx[..])?;
println!("Optimal primal solution");
for j in 0..numvar as usize {
println!("x[{}]: {:.4}",j,xx[j]);
}
Ok(())
}))
}sourcepub fn append_primal_geo_mean_cone_domain(
&mut self,
n_: i64
) -> Result<i64, String>
pub fn append_primal_geo_mean_cone_domain( &mut self, n_: i64 ) -> Result<i64, String>
Appends the primal geometric mean cone domain.
§Arguments
n_Dimmension of the domain.
§Returns
domidxIndex of the domain.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendprimalgeomeanconedomain
sourcepub fn append_primal_power_cone_domain(
&mut self,
n_: i64,
alpha_: &[f64]
) -> Result<i64, String>
pub fn append_primal_power_cone_domain( &mut self, n_: i64, alpha_: &[f64] ) -> Result<i64, String>
Appends the primal power cone domain.
§Arguments
n_Dimension of the domain.alpha_The sequence proportional to exponents. Must be positive.
§Returns
domidxIndex of the domain.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendprimalpowerconedomain
sourcepub fn append_quadratic_cone_domain(&mut self, n_: i64) -> Result<i64, String>
pub fn append_quadratic_cone_domain(&mut self, n_: i64) -> Result<i64, String>
Appends the n dimensional quadratic cone domain.
§Arguments
n_Dimmension of the domain.
§Returns
domidxIndex of the domain.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendquadraticconedomain
Examples found in repository?
examples/portfolio_5_card.rs (line 137)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}sourcepub fn append_r_domain(&mut self, n_: i64) -> Result<i64, String>
pub fn append_r_domain(&mut self, n_: i64) -> Result<i64, String>
Appends the n dimensional real number domain.
§Arguments
n_Dimmension of the domain.
§Returns
domidxIndex of the domain.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendrdomain
sourcepub fn append_rminus_domain(&mut self, n_: i64) -> Result<i64, String>
pub fn append_rminus_domain(&mut self, n_: i64) -> Result<i64, String>
Appends the n dimensional negative orthant to the list of domains.
§Arguments
n_Dimmension of the domain.
§Returns
domidxIndex of the domain.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendrminusdomain
sourcepub fn append_rplus_domain(&mut self, n_: i64) -> Result<i64, String>
pub fn append_rplus_domain(&mut self, n_: i64) -> Result<i64, String>
Appends the n dimensional positive orthant to the list of domains.
§Arguments
n_Dimmension of the domain.
§Returns
domidxIndex of the domain.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendrplusdomain
sourcepub fn append_r_quadratic_cone_domain(&mut self, n_: i64) -> Result<i64, String>
pub fn append_r_quadratic_cone_domain(&mut self, n_: i64) -> Result<i64, String>
Appends the n dimensional rotated quadratic cone domain.
§Arguments
n_Dimmension of the domain.
§Returns
domidxIndex of the domain.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendrquadraticconedomain
Examples found in repository?
examples/portfolio_2_frontier.rs (line 84)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}sourcepub fn append_rzero_domain(&mut self, n_: i64) -> Result<i64, String>
pub fn append_rzero_domain(&mut self, n_: i64) -> Result<i64, String>
Appends the n dimensional 0 domain.
§Arguments
n_Dimmension of the domain.
§Returns
domidxIndex of the domain.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendrzerodomain
sourcepub fn append_sparse_sym_mat(
&mut self,
dim_: i32,
subi_: &[i32],
subj_: &[i32],
valij_: &[f64]
) -> Result<i64, String>
pub fn append_sparse_sym_mat( &mut self, dim_: i32, subi_: &[i32], subj_: &[i32], valij_: &[f64] ) -> Result<i64, String>
Appends a general sparse symmetric matrix to the storage of symmetric matrices.
§Arguments
dim_Dimension of the symmetric matrix that is appended.subi_Row subscript in the triplets.subj_Column subscripts in the triplets.valij_Values of each triplet.
§Returns
idxUnique index assigned to the inputted matrix.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendsparsesymmat
sourcepub fn append_sparse_sym_mat_list(
&mut self,
dims_: &[i32],
nz_: &[i64],
subi_: &[i32],
subj_: &[i32],
valij_: &[f64],
idx_: &mut [i64]
) -> Result<(), String>
pub fn append_sparse_sym_mat_list( &mut self, dims_: &[i32], nz_: &[i64], subi_: &[i32], subj_: &[i32], valij_: &[f64], idx_: &mut [i64] ) -> Result<(), String>
Appends a general sparse symmetric matrix to the storage of symmetric matrices.
§Arguments
dims_Dimensions of the symmetric matrixes.nz_Number of nonzeros for each matrix.subi_Row subscript in the triplets.subj_Column subscripts in the triplets.valij_Values of each triplet.idx_Unique index assigned to the inputted matrix.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendsparsesymmatlist
sourcepub fn append_svec_psd_cone_domain(&mut self, n_: i64) -> Result<i64, String>
pub fn append_svec_psd_cone_domain(&mut self, n_: i64) -> Result<i64, String>
Appends the vectorized SVEC PSD cone domain.
§Arguments
n_Dimension of the domain.
§Returns
domidxIndex of the domain.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendsvecpsdconedomain
sourcepub fn append_vars(&mut self, num_: i32) -> Result<(), String>
pub fn append_vars(&mut self, num_: i32) -> Result<(), String>
Appends a number of variables to the optimization task.
§Arguments
num_Number of variables which should be appended.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.appendvars
Examples found in repository?
examples/helloworld.rs (line 20)
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fn main() -> Result<(),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
task.append_vars(1)?; // 1 variable x
task.put_c_j(0, 1.0)?; // c_0 = 1.0
task.put_var_bound(0, Boundkey::RA, 2.0, 3.0)?; // 2.0 <= x <= 3.0
task.put_obj_sense(Objsense::MINIMIZE)?; // minimize
task.optimize()?; // Optimize
let mut x = vec![0.0; 1];
task.get_xx(Soltype::ITR, x.as_mut_slice())?; // Get solution
println!("Solution x = {}", x[0]); // Print solution
return Result::Ok(());
}More examples
examples/pinfeas.rs (line 17)
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fn test_problem() -> Result<mosek::Task,String> {
let mut task = mosek::Task::new().unwrap();
task.append_vars(7)?;
task.append_cons(7)?;
task.put_c_list(&[0,1,2,3,4,5,6],
&[1.0,2.0,5.0,2.0,1.0,2.0,1.0])?;
task.put_aij_list(&[0,0,1,1,2,2,2,3,3,4,5,5,6,6],
&[0,1,2,3,4,5,6,0,4,1,2,5,3,6],
&[1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0])?;
task.put_con_bound_slice(0, 7,
&[Boundkey::UP,Boundkey::UP,Boundkey::UP,Boundkey::FX,Boundkey::FX,Boundkey::FX,Boundkey::FX],
&[-INF, -INF, -INF, 1100.0, 200.0, 500.0, 500.0],
&[200.0, 1000.0, 1000.0, 1100.0, 200.0, 500.0, 500.0])?;
task.put_var_bound_slice_const(0, 7, Boundkey::UP, 0.0, INF)?;
Ok(task)
}examples/solvelinear.rs (line 41)
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fn setup(task : & mut mosek::Task,
aval : &[f64],
asub : &[i32],
ptrb : &[i64],
ptre : &[i64],
numvar : i32) -> Result<Vec<i32>,String> {
// mosek.stakey[] skx = new mosek.stakey [numvar];
// mosek.stakey[] skc = new mosek.stakey [numvar];
// for (int i = 0; i < numvar ; ++i) {
// skx[i] = mosek.stakey.bas;
// skc[i] = mosek.stakey.fix;
// }
task.append_vars(numvar)?;
task.append_cons(numvar)?;
task.put_a_col_slice(0,numvar,ptrb,ptre,asub,aval)?;
task.put_con_bound_slice_const(0,numvar,Boundkey::FX,0.0,0.0)?;
task.put_var_bound_slice_const(0,numvar,Boundkey::FR,-INF,INF)?;
/* Define a basic solution by specifying
status keys for variables & constraints. */
task.delete_solution(Soltype::BAS)?;
task.put_skc_slice(Soltype::BAS, 0, numvar, vec![Stakey::FIX; numvar as usize].as_slice())?;
task.put_skx_slice(Soltype::BAS, 0, numvar, vec![Stakey::BAS; numvar as usize].as_slice())?;
let mut basis = vec![0; numvar as usize];
task.init_basis_solve(basis.as_mut_slice())?;
Ok(basis)
}examples/portfolio_2_frontier.rs (line 49)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}examples/ceo1.rs (line 57)
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fn main() -> Result<(),String> {
let numcon = 1;
let numvar = 3;
let bkc = mosek::Boundkey::FX;
let blc = 1.0;
let buc = 1.0;
let bkx = vec![ Boundkey::FR,
Boundkey::FR,
Boundkey::FR ];
let blx = vec![ -INF, -INF, -INF ];
let bux = vec![ INF, INF, INF ];
let c = vec![ 1.0, 1.0, 0.0 ];
let a = vec![ 1.0, 1.0, 1.0 ];
let asub = vec![0, 1, 2];
//let csub = new int[numvar];
//double[] xx = new double[numvar];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|task| task.with_callback(
&mut |caller| { println!("caller = {}",caller); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
/* Define the linear part of the problem */
task.put_c_slice(0, numvar, c.as_slice())?;
task.put_a_row(0, asub.as_slice(), a.as_slice())?;
task.put_con_bound(0, bkc, blc, buc)?;
task.put_var_bound_slice(0, numvar, bkx.as_slice(), blx.as_slice(), bux.as_slice())?;
/* Add a conic constraint */
task.append_afes(3)?;
let afeidxs = vec![0, 1, 2 ];
let b = vec![0.0,0.0,0.0];
let domidx = task.append_primal_exp_cone_domain()?;
task.put_afe_f_row_list(afeidxs.as_slice(),
vec![1,1,1].as_slice(),
vec![0,1,2].as_slice(),
vec![0,1,2].as_slice(),
vec![1.0,1.0,1.0].as_slice())?;
task.append_acc(domidx,afeidxs.as_slice(),b.as_slice())?;
task.put_obj_sense(Objsense::MINIMIZE)?;
println!("optimize");
/* Solve the problem */
task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
/* Get status information about the solution */
let solsta = task.get_sol_sta(Soltype::ITR)?;
assert!(solsta == Solsta::OPTIMAL);
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITR, & mut xx[..])?;
println!("Optimal primal solution");
for j in 0..numvar as usize {
println!("x[{}]: {:.4}",j,xx[j]);
}
Ok(())
}))
}examples/reoptimization.rs (line 54)
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fn main() -> Result<(),String> {
let numcon = 3;
let numvar = 3;
let c = &[1.5, 2.5, 3.0 ];
let bkc = &[ Boundkey::UP,
Boundkey::UP,
Boundkey::UP ];
let blc = &[ -INF,
-INF,
-INF ];
let buc = &[ 100000.0,
50000.0,
60000.0 ];
let bkx = &[ Boundkey::LO,
Boundkey::LO,
Boundkey::LO
];
let blx = &[ 0.0, 0.0, 0.0 ];
let bux = &[ INF,
INF,
INF ];
let asub = &[
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ] ];
let aval = &[
&[ 2.0, 3.0, 2.0 ],
&[ 4.0, 2.0, 3.0 ],
&[ 3.0, 3.0, 2.0 ] ];
let mut task = Task::new().unwrap();
/* Append the constraints. */
task.append_cons(numcon)?;
/* Append the variables. */
task.append_vars(numvar)?;
/* Put C. */
for (j,&cj) in (0..numvar).zip(c.iter()) {
task.put_c_j(j,cj)?;
}
/* Put constraint bounds. */
for (i,&bki,&bli,&bui) in izip!(0..numcon,bkc,blc,buc) {
task.put_con_bound(i, bki, bli, bui)?;
}
/* Put variable bounds. */
for (j,&bki,&bli,&bui) in izip!(0..numvar,bkx,blx,bux) {
task.put_var_bound(j, bki, bli, bui)?;
}
/* Put A. */
if numcon > 0 {
for (j,&asubj,&avalj) in izip!(0..numvar,asub,aval) {
task.put_a_col(j,
asubj,
avalj)?;
}
}
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/****************** Make a change to the A matrix ******************/
task.put_aij(0, 0, 3.0)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/***************** Add a new variable ******************************/
/* Get index of new variable. */
let varidx = task.get_num_var()?;
/* Append a new variable x_3 to the problem */
task.append_vars(1)?;
let numvar = numvar + 1;
/* Set bounds on new varaible */
task.put_var_bound(varidx, Boundkey::LO, 0.0, INF)?;
/* Change objective */
task.put_c_j(varidx, 1.0)?;
/* Put new values in the A matrix */
let acolsub = &[0i32, 2];
let acolval = &[4.0, 1.0];
task.put_a_col(varidx, /* column index */
acolsub,
acolval)?;
/* Change optimizer to simplex free and reoptimize */
task.put_int_param(mosek::Iparam::OPTIMIZER, mosek::Optimizertype::FREE_SIMPLEX)?;
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Add a new constraint ***************************/
/* Get index of new constraint. */
let conidx = task.get_num_con()?;
/* Append a new constraint */
task.append_cons(1)?;
let numcon = numcon + 1;
/* Set bounds on new constraint */
task.put_con_bound(conidx,
Boundkey::UP,
-INF,
30000.0)?;
/* Put new values in the A matrix */
let arowsub = &[0i32, 1, 2, 3 ];
let arowval = &[1.0, 2.0, 1.0, 1.0 ];
task.put_a_row(conidx, /* row index */
arowsub,
arowval)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Change constraint bounds ********************/
let newbkc = &[Boundkey::UP,
Boundkey::UP,
Boundkey::UP,
Boundkey::UP];
let newblc = &[-INF,
-INF,
-INF,
-INF];
let newbuc = &[ 80000.0, 40000.0, 50000.0, 22000.0 ];
task.put_con_bound_slice(0, numcon, newbkc, newblc, newbuc)?;
let _ = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
Ok(())
}Additional examples can be found in:
sourcepub fn async_get_log(
&mut self,
addr_: &str,
accesstoken_: &str,
token_: &str
) -> Result<(), String>
pub fn async_get_log( &mut self, addr_: &str, accesstoken_: &str, token_: &str ) -> Result<(), String>
Get the optimizer log from a remote job.
§Arguments
addr_Address of the solver serveraccesstoken_Access token string.token_Job token
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.asyncgetlog
sourcepub fn async_get_result(
&mut self,
address_: &str,
accesstoken_: &str,
token_: &str,
resp_: &mut i32,
trm_: &mut i32
) -> Result<bool, String>
pub fn async_get_result( &mut self, address_: &str, accesstoken_: &str, token_: &str, resp_: &mut i32, trm_: &mut i32 ) -> Result<bool, String>
Request a solution from a remote job.
§Arguments
-
address_Address of the OptServer. -
accesstoken_Access token. -
token_The task token. -
resp_Is the response code from the remote solver.See Rescode
-
trm_Is either OK or a termination response code.See Rescode
§Returns
respavailableIndicates if a remote response is available.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.asyncgetresult
Examples found in repository?
examples/opt_server_async.rs (lines 90-94)
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fn opt_server_async(inputfile : FileOrText, addr : String, numpolls : usize, cert : Option<String>) -> Result<(),String> {
// Path to certificate, if any
let token = {
Task::new().unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| {
match inputfile {
FileOrText::File(ref filename) => task.read_data(filename.as_str()).unwrap(),
FileOrText::Text(ref data) => task.read_ptf_string(data.as_str()).unwrap()
}
if let Some(ref cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH,cert.as_str())?;
}
task.async_optimize(addr.as_str(),"")
}).expect("Failed to submit async optimization")
};
println!("Task token = '{}'", token);
println!("Setting log stream...");
Task::new().unwrap().with_stream_callback(
Streamtype::LOG,
& mut |msg| print!("{}",msg),
|task| task.with_callback(
&mut|caller| { println!("caller = {}",caller); false },
|task| {
println!("Reading input file '{:?}'...",inputfile);
match inputfile {
FileOrText::File(ref filename) => task.read_data(filename.as_str()).unwrap(),
FileOrText::Text(ref data) => task.read_ptf_string(data.as_str()).unwrap()
}
if let Some(ref cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH,cert.as_str())?;
}
println!("Starting polling loop...");
for i in 0..numpolls {
sleep(Duration::new(1,0));
println!("\tpoll {}...", i);
let mut trm : i32 = 0;
let mut resp : i32 = 0;
let respavailable = task.async_poll(addr.as_str(),
"",
token.as_str(),
& mut resp,
& mut trm)?;
if respavailable {
println!("solution available!");
task.async_get_result(addr.as_str(),
"",
token.as_str(),
& mut resp,
& mut trm)?;
task.solution_summary (Streamtype::LOG)?;
return Ok(());
}
}
println!("max num polls reached, stopping host.");
task.async_stop (addr.as_str(), "", token.as_str())?;
Err("Max num polls".to_string())
}))
}sourcepub fn async_optimize(
&mut self,
address_: &str,
accesstoken_: &str
) -> Result<String, String>
pub fn async_optimize( &mut self, address_: &str, accesstoken_: &str ) -> Result<String, String>
Offload the optimization task to a solver server in asynchronous mode.
§Arguments
address_Address of the OptServer.accesstoken_Access token.
§Returns
tokenReturns the task token.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.asyncoptimize
Examples found in repository?
examples/opt_server_async.rs (line 50)
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fn opt_server_async(inputfile : FileOrText, addr : String, numpolls : usize, cert : Option<String>) -> Result<(),String> {
// Path to certificate, if any
let token = {
Task::new().unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| {
match inputfile {
FileOrText::File(ref filename) => task.read_data(filename.as_str()).unwrap(),
FileOrText::Text(ref data) => task.read_ptf_string(data.as_str()).unwrap()
}
if let Some(ref cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH,cert.as_str())?;
}
task.async_optimize(addr.as_str(),"")
}).expect("Failed to submit async optimization")
};
println!("Task token = '{}'", token);
println!("Setting log stream...");
Task::new().unwrap().with_stream_callback(
Streamtype::LOG,
& mut |msg| print!("{}",msg),
|task| task.with_callback(
&mut|caller| { println!("caller = {}",caller); false },
|task| {
println!("Reading input file '{:?}'...",inputfile);
match inputfile {
FileOrText::File(ref filename) => task.read_data(filename.as_str()).unwrap(),
FileOrText::Text(ref data) => task.read_ptf_string(data.as_str()).unwrap()
}
if let Some(ref cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH,cert.as_str())?;
}
println!("Starting polling loop...");
for i in 0..numpolls {
sleep(Duration::new(1,0));
println!("\tpoll {}...", i);
let mut trm : i32 = 0;
let mut resp : i32 = 0;
let respavailable = task.async_poll(addr.as_str(),
"",
token.as_str(),
& mut resp,
& mut trm)?;
if respavailable {
println!("solution available!");
task.async_get_result(addr.as_str(),
"",
token.as_str(),
& mut resp,
& mut trm)?;
task.solution_summary (Streamtype::LOG)?;
return Ok(());
}
}
println!("max num polls reached, stopping host.");
task.async_stop (addr.as_str(), "", token.as_str())?;
Err("Max num polls".to_string())
}))
}sourcepub fn async_poll(
&mut self,
address_: &str,
accesstoken_: &str,
token_: &str,
resp_: &mut i32,
trm_: &mut i32
) -> Result<bool, String>
pub fn async_poll( &mut self, address_: &str, accesstoken_: &str, token_: &str, resp_: &mut i32, trm_: &mut i32 ) -> Result<bool, String>
Requests information about the status of the remote job.
§Arguments
-
address_Address of the OptServer. -
accesstoken_Access token. -
token_The task token. -
resp_Is the response code from the remote solver.See Rescode
-
trm_Is either OK or a termination response code.See Rescode
§Returns
respavailableIndicates if a remote response is available.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.asyncpoll
Examples found in repository?
examples/opt_server_async.rs (lines 81-85)
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fn opt_server_async(inputfile : FileOrText, addr : String, numpolls : usize, cert : Option<String>) -> Result<(),String> {
// Path to certificate, if any
let token = {
Task::new().unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| {
match inputfile {
FileOrText::File(ref filename) => task.read_data(filename.as_str()).unwrap(),
FileOrText::Text(ref data) => task.read_ptf_string(data.as_str()).unwrap()
}
if let Some(ref cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH,cert.as_str())?;
}
task.async_optimize(addr.as_str(),"")
}).expect("Failed to submit async optimization")
};
println!("Task token = '{}'", token);
println!("Setting log stream...");
Task::new().unwrap().with_stream_callback(
Streamtype::LOG,
& mut |msg| print!("{}",msg),
|task| task.with_callback(
&mut|caller| { println!("caller = {}",caller); false },
|task| {
println!("Reading input file '{:?}'...",inputfile);
match inputfile {
FileOrText::File(ref filename) => task.read_data(filename.as_str()).unwrap(),
FileOrText::Text(ref data) => task.read_ptf_string(data.as_str()).unwrap()
}
if let Some(ref cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH,cert.as_str())?;
}
println!("Starting polling loop...");
for i in 0..numpolls {
sleep(Duration::new(1,0));
println!("\tpoll {}...", i);
let mut trm : i32 = 0;
let mut resp : i32 = 0;
let respavailable = task.async_poll(addr.as_str(),
"",
token.as_str(),
& mut resp,
& mut trm)?;
if respavailable {
println!("solution available!");
task.async_get_result(addr.as_str(),
"",
token.as_str(),
& mut resp,
& mut trm)?;
task.solution_summary (Streamtype::LOG)?;
return Ok(());
}
}
println!("max num polls reached, stopping host.");
task.async_stop (addr.as_str(), "", token.as_str())?;
Err("Max num polls".to_string())
}))
}sourcepub fn async_stop(
&mut self,
address_: &str,
accesstoken_: &str,
token_: &str
) -> Result<(), String>
pub fn async_stop( &mut self, address_: &str, accesstoken_: &str, token_: &str ) -> Result<(), String>
Request that the job identified by the token is terminated.
§Arguments
address_Address of the OptServer.accesstoken_Access token.token_The task token.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.asyncstop
Examples found in repository?
examples/opt_server_async.rs (line 102)
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fn opt_server_async(inputfile : FileOrText, addr : String, numpolls : usize, cert : Option<String>) -> Result<(),String> {
// Path to certificate, if any
let token = {
Task::new().unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| {
match inputfile {
FileOrText::File(ref filename) => task.read_data(filename.as_str()).unwrap(),
FileOrText::Text(ref data) => task.read_ptf_string(data.as_str()).unwrap()
}
if let Some(ref cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH,cert.as_str())?;
}
task.async_optimize(addr.as_str(),"")
}).expect("Failed to submit async optimization")
};
println!("Task token = '{}'", token);
println!("Setting log stream...");
Task::new().unwrap().with_stream_callback(
Streamtype::LOG,
& mut |msg| print!("{}",msg),
|task| task.with_callback(
&mut|caller| { println!("caller = {}",caller); false },
|task| {
println!("Reading input file '{:?}'...",inputfile);
match inputfile {
FileOrText::File(ref filename) => task.read_data(filename.as_str()).unwrap(),
FileOrText::Text(ref data) => task.read_ptf_string(data.as_str()).unwrap()
}
if let Some(ref cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH,cert.as_str())?;
}
println!("Starting polling loop...");
for i in 0..numpolls {
sleep(Duration::new(1,0));
println!("\tpoll {}...", i);
let mut trm : i32 = 0;
let mut resp : i32 = 0;
let respavailable = task.async_poll(addr.as_str(),
"",
token.as_str(),
& mut resp,
& mut trm)?;
if respavailable {
println!("solution available!");
task.async_get_result(addr.as_str(),
"",
token.as_str(),
& mut resp,
& mut trm)?;
task.solution_summary (Streamtype::LOG)?;
return Ok(());
}
}
println!("max num polls reached, stopping host.");
task.async_stop (addr.as_str(), "", token.as_str())?;
Err("Max num polls".to_string())
}))
}sourcepub fn basis_cond(
&mut self,
nrmbasis_: &mut f64,
nrminvbasis_: &mut f64
) -> Result<(), String>
pub fn basis_cond( &mut self, nrmbasis_: &mut f64, nrminvbasis_: &mut f64 ) -> Result<(), String>
Computes conditioning information for the basis matrix.
§Arguments
nrmbasis_An estimate for the 1-norm of the basis.nrminvbasis_An estimate for the 1-norm of the inverse of the basis.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.basiscond
sourcepub fn check_mem(&mut self, file_: &str, line_: i32) -> Result<(), String>
pub fn check_mem(&mut self, file_: &str, line_: i32) -> Result<(), String>
Checks the memory allocated by the task.
§Arguments
file_File from which the function is called.line_Line in the file from which the function is called.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.checkmemtask
sourcepub fn chg_con_bound(
&mut self,
i_: i32,
lower_: i32,
finite_: i32,
value_: f64
) -> Result<(), String>
pub fn chg_con_bound( &mut self, i_: i32, lower_: i32, finite_: i32, value_: f64 ) -> Result<(), String>
Changes the bounds for one constraint.
§Arguments
i_Index of the constraint for which the bounds should be changed.lower_If non-zero, then the lower bound is changed, otherwise the upper bound is changed.finite_If non-zero, then the given value is assumed to be finite.value_New value for the bound.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.chgconbound
sourcepub fn chg_var_bound(
&mut self,
j_: i32,
lower_: i32,
finite_: i32,
value_: f64
) -> Result<(), String>
pub fn chg_var_bound( &mut self, j_: i32, lower_: i32, finite_: i32, value_: f64 ) -> Result<(), String>
Changes the bounds for one variable.
§Arguments
j_Index of the variable for which the bounds should be changed.lower_If non-zero, then the lower bound is changed, otherwise the upper bound is changed.finite_If non-zero, then the given value is assumed to be finite.value_New value for the bound.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.chgvarbound
sourcepub fn commit_changes(&mut self) -> Result<(), String>
pub fn commit_changes(&mut self) -> Result<(), String>
Commits all cached problem changes.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.commitchanges
sourcepub fn delete_solution(&mut self, whichsol_: i32) -> Result<(), String>
pub fn delete_solution(&mut self, whichsol_: i32) -> Result<(), String>
Undefine a solution and free the memory it uses.
§Arguments
-
whichsol_Selects a solution.See Soltype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.deletesolution
Examples found in repository?
examples/solvelinear.rs (line 51)
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fn setup(task : & mut mosek::Task,
aval : &[f64],
asub : &[i32],
ptrb : &[i64],
ptre : &[i64],
numvar : i32) -> Result<Vec<i32>,String> {
// mosek.stakey[] skx = new mosek.stakey [numvar];
// mosek.stakey[] skc = new mosek.stakey [numvar];
// for (int i = 0; i < numvar ; ++i) {
// skx[i] = mosek.stakey.bas;
// skc[i] = mosek.stakey.fix;
// }
task.append_vars(numvar)?;
task.append_cons(numvar)?;
task.put_a_col_slice(0,numvar,ptrb,ptre,asub,aval)?;
task.put_con_bound_slice_const(0,numvar,Boundkey::FX,0.0,0.0)?;
task.put_var_bound_slice_const(0,numvar,Boundkey::FR,-INF,INF)?;
/* Define a basic solution by specifying
status keys for variables & constraints. */
task.delete_solution(Soltype::BAS)?;
task.put_skc_slice(Soltype::BAS, 0, numvar, vec![Stakey::FIX; numvar as usize].as_slice())?;
task.put_skx_slice(Soltype::BAS, 0, numvar, vec![Stakey::BAS; numvar as usize].as_slice())?;
let mut basis = vec![0; numvar as usize];
task.init_basis_solve(basis.as_mut_slice())?;
Ok(basis)
}sourcepub fn dual_sensitivity(
&self,
subj_: &[i32],
leftpricej_: &mut [f64],
rightpricej_: &mut [f64],
leftrangej_: &mut [f64],
rightrangej_: &mut [f64]
) -> Result<(), String>
pub fn dual_sensitivity( &self, subj_: &[i32], leftpricej_: &mut [f64], rightpricej_: &mut [f64], leftrangej_: &mut [f64], rightrangej_: &mut [f64] ) -> Result<(), String>
Performs sensitivity analysis on objective coefficients.
§Arguments
subj_Indexes of objective coefficients to analyze.leftpricej_Left shadow prices for requested coefficients.rightpricej_Right shadow prices for requested coefficients.leftrangej_Left range for requested coefficients.rightrangej_Right range for requested coefficients.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.dualsensitivity
sourcepub fn empty_afe_barf_row(&mut self, afeidx_: i64) -> Result<(), String>
pub fn empty_afe_barf_row(&mut self, afeidx_: i64) -> Result<(), String>
Clears a row in barF
§Arguments
afeidx_Row index of barF.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.emptyafebarfrow
sourcepub fn empty_afe_barf_row_list(
&mut self,
afeidxlist_: &[i64]
) -> Result<(), String>
pub fn empty_afe_barf_row_list( &mut self, afeidxlist_: &[i64] ) -> Result<(), String>
Clears rows in barF.
§Arguments
afeidxlist_Indices of rows in barF to clear.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.emptyafebarfrowlist
sourcepub fn empty_afe_f_col(&mut self, varidx_: i32) -> Result<(), String>
pub fn empty_afe_f_col(&mut self, varidx_: i32) -> Result<(), String>
Clears a column in F.
§Arguments
varidx_Variable index.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.emptyafefcol
sourcepub fn empty_afe_f_col_list(&mut self, varidx_: &[i32]) -> Result<(), String>
pub fn empty_afe_f_col_list(&mut self, varidx_: &[i32]) -> Result<(), String>
Clears columns in F.
§Arguments
varidx_Indices of variables in F to clear.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.emptyafefcollist
sourcepub fn empty_afe_f_row(&mut self, afeidx_: i64) -> Result<(), String>
pub fn empty_afe_f_row(&mut self, afeidx_: i64) -> Result<(), String>
Clears a row in F.
§Arguments
afeidx_Row index.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.emptyafefrow
sourcepub fn empty_afe_f_row_list(&mut self, afeidx_: &[i64]) -> Result<(), String>
pub fn empty_afe_f_row_list(&mut self, afeidx_: &[i64]) -> Result<(), String>
Clears rows in F.
§Arguments
afeidx_Indices of rows in F to clear.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.emptyafefrowlist
sourcepub fn evaluate_acc(
&self,
whichsol_: i32,
accidx_: i64,
activity_: &mut [f64]
) -> Result<(), String>
pub fn evaluate_acc( &self, whichsol_: i32, accidx_: i64, activity_: &mut [f64] ) -> Result<(), String>
Evaluates the activity of an affine conic constraint.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
accidx_The index of the affine conic constraint. -
activity_The activity of the affine conic constraint. The array should have length equal to the dimension of the constraint.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.evaluateacc
sourcepub fn evaluate_accs(
&self,
whichsol_: i32,
activity_: &mut [f64]
) -> Result<(), String>
pub fn evaluate_accs( &self, whichsol_: i32, activity_: &mut [f64] ) -> Result<(), String>
Evaluates the activities of all affine conic constraints.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
activity_The activity of affine conic constraints. The array should have length equal to the sum of dimensions of all affine conic constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.evaluateaccs
sourcepub fn generate_acc_names(
&mut self,
sub_: &[i64],
fmt_: &str,
dims_: &[i32],
sp_: &[i64],
namedaxisidxs_: &[i32],
names_: &[String]
) -> Result<(), String>
pub fn generate_acc_names( &mut self, sub_: &[i64], fmt_: &str, dims_: &[i32], sp_: &[i64], namedaxisidxs_: &[i32], names_: &[String] ) -> Result<(), String>
Generates systematic names for affine conic constraints.
§Arguments
sub_Indexes of the affine conic constraints.fmt_The variable name formatting string.dims_Dimensions in the shape.sp_Items that should be named.namedaxisidxs_List if named index axesnames_All axis names.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.generateaccnames
sourcepub fn generate_barvar_names(
&mut self,
subj_: &[i32],
fmt_: &str,
dims_: &[i32],
sp_: &[i64],
namedaxisidxs_: &[i32],
names_: &[String]
) -> Result<(), String>
pub fn generate_barvar_names( &mut self, subj_: &[i32], fmt_: &str, dims_: &[i32], sp_: &[i64], namedaxisidxs_: &[i32], names_: &[String] ) -> Result<(), String>
Generates systematic names for variables.
§Arguments
subj_Indexes of the variables.fmt_The variable name formatting string.dims_Dimensions in the shape.sp_Items that should be named.namedaxisidxs_List if named index axesnames_All axis names.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.generatebarvarnames
sourcepub fn generate_cone_names(
&mut self,
subk_: &[i32],
fmt_: &str,
dims_: &[i32],
sp_: &[i64],
namedaxisidxs_: &[i32],
names_: &[String]
) -> Result<(), String>
pub fn generate_cone_names( &mut self, subk_: &[i32], fmt_: &str, dims_: &[i32], sp_: &[i64], namedaxisidxs_: &[i32], names_: &[String] ) -> Result<(), String>
Generates systematic names for cone.
§Arguments
subk_Indexes of the cone.fmt_The cone name formatting string.dims_Dimensions in the shape.sp_Items that should be named.namedaxisidxs_List if named index axesnames_All axis names.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.generateconenames
sourcepub fn generate_con_names(
&mut self,
subi_: &[i32],
fmt_: &str,
dims_: &[i32],
sp_: &[i64],
namedaxisidxs_: &[i32],
names_: &[String]
) -> Result<(), String>
pub fn generate_con_names( &mut self, subi_: &[i32], fmt_: &str, dims_: &[i32], sp_: &[i64], namedaxisidxs_: &[i32], names_: &[String] ) -> Result<(), String>
Generates systematic names for constraints.
§Arguments
subi_Indexes of the constraints.fmt_The constraint name formatting string.dims_Dimensions in the shape.sp_Items that should be named.namedaxisidxs_List if named index axesnames_All axis names.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.generateconnames
sourcepub fn generate_djc_names(
&mut self,
sub_: &[i64],
fmt_: &str,
dims_: &[i32],
sp_: &[i64],
namedaxisidxs_: &[i32],
names_: &[String]
) -> Result<(), String>
pub fn generate_djc_names( &mut self, sub_: &[i64], fmt_: &str, dims_: &[i32], sp_: &[i64], namedaxisidxs_: &[i32], names_: &[String] ) -> Result<(), String>
Generates systematic names for affine conic constraints.
§Arguments
sub_Indexes of the disjunctive constraints.fmt_The variable name formatting string.dims_Dimensions in the shape.sp_Items that should be named.namedaxisidxs_List if named index axesnames_All axis names.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.generatedjcnames
sourcepub fn generate_var_names(
&mut self,
subj_: &[i32],
fmt_: &str,
dims_: &[i32],
sp_: &[i64],
namedaxisidxs_: &[i32],
names_: &[String]
) -> Result<(), String>
pub fn generate_var_names( &mut self, subj_: &[i32], fmt_: &str, dims_: &[i32], sp_: &[i64], namedaxisidxs_: &[i32], names_: &[String] ) -> Result<(), String>
Generates systematic names for variables.
§Arguments
subj_Indexes of the variables.fmt_The variable name formatting string.dims_Dimensions in the shape.sp_Items that should be named.namedaxisidxs_List if named index axesnames_All axis names.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.generatevarnames
sourcepub fn get_acc_afe_idx_list(
&self,
accidx_: i64,
afeidxlist_: &mut [i64]
) -> Result<(), String>
pub fn get_acc_afe_idx_list( &self, accidx_: i64, afeidxlist_: &mut [i64] ) -> Result<(), String>
Obtains the list of affine expressions appearing in the affine conic constraint.
§Arguments
accidx_Index of the affine conic constraint.afeidxlist_List of indexes of affine expressions appearing in the constraint.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getaccafeidxlist
sourcepub fn get_acc_b(&self, accidx_: i64, b_: &mut [f64]) -> Result<(), String>
pub fn get_acc_b(&self, accidx_: i64, b_: &mut [f64]) -> Result<(), String>
Obtains the additional constant term vector appearing in the affine conic constraint.
§Arguments
accidx_Index of the affine conic constraint.b_The vector b appearing in the constraint.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getaccb
sourcepub fn get_acc_barf_block_triplet(
&self,
acc_afe_: &mut [i64],
bar_var_: &mut [i32],
blk_row_: &mut [i32],
blk_col_: &mut [i32],
blk_val_: &mut [f64]
) -> Result<i64, String>
pub fn get_acc_barf_block_triplet( &self, acc_afe_: &mut [i64], bar_var_: &mut [i32], blk_row_: &mut [i32], blk_col_: &mut [i32], blk_val_: &mut [f64] ) -> Result<i64, String>
Obtains barF, implied by the ACCs, in block triplet form.
§Arguments
acc_afe_Index of the AFE within the concatenated list of AFEs in ACCs.bar_var_Symmetric matrix variable index.blk_row_Block row index.blk_col_Block column index.blk_val_The numerical value associated with each block triplet.
§Returns
numtripNumber of elements in the block triplet form.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getaccbarfblocktriplet
sourcepub fn get_acc_barf_num_block_triplets(&self) -> Result<i64, String>
pub fn get_acc_barf_num_block_triplets(&self) -> Result<i64, String>
Obtains an upper bound on the number of elements in the block triplet form of barf, as used within the ACCs.
§Returns
numtripAn upper bound on the number of elements in the block triplet form of barf, as used within the ACCs.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getaccbarfnumblocktriplets
sourcepub fn get_acc_domain(&mut self, accidx_: i64) -> Result<i64, String>
pub fn get_acc_domain(&mut self, accidx_: i64) -> Result<i64, String>
Obtains the domain appearing in the affine conic constraint.
§Arguments
accidx_The index of the affine conic constraint.
§Returns
domidxThe index of domain in the affine conic constraint.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getaccdomain
sourcepub fn get_acc_dot_y(
&self,
whichsol_: i32,
accidx_: i64,
doty_: &mut [f64]
) -> Result<(), String>
pub fn get_acc_dot_y( &self, whichsol_: i32, accidx_: i64, doty_: &mut [f64] ) -> Result<(), String>
Obtains the doty vector for an affine conic constraint.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
accidx_The index of the affine conic constraint. -
doty_The dual values for this affine conic constraint. The array should have length equal to the dimension of the constraint.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getaccdoty
sourcepub fn get_acc_dot_y_s(
&self,
whichsol_: i32,
doty_: &mut [f64]
) -> Result<(), String>
pub fn get_acc_dot_y_s( &self, whichsol_: i32, doty_: &mut [f64] ) -> Result<(), String>
Obtains the doty vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
doty_The dual values of affine conic constraints. The array should have length equal to the sum of dimensions of all affine conic constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getaccdotys
sourcepub fn get_acc_f_numnz(&mut self) -> Result<i64, String>
pub fn get_acc_f_numnz(&mut self) -> Result<i64, String>
Obtains the total number of nonzeros in the ACC implied F matrix.
§Returns
accfnnzNumber of nonzeros in the F matrix implied by ACCs.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getaccfnumnz
sourcepub fn get_acc_f_trip(
&mut self,
frow_: &mut [i64],
fcol_: &mut [i32],
fval_: &mut [f64]
) -> Result<(), String>
pub fn get_acc_f_trip( &mut self, frow_: &mut [i64], fcol_: &mut [i32], fval_: &mut [f64] ) -> Result<(), String>
Obtains the F matrix (implied by the AFE ordering within the ACCs) in triplet format.
§Arguments
frow_Row indices of nonzeros in the implied F matrix.fcol_Column indices of nonzeros in the implied F matrix.fval_Values of nonzero entries in the implied F matrix.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getaccftrip
sourcepub fn get_acc_g_vector(&self, g_: &mut [f64]) -> Result<(), String>
pub fn get_acc_g_vector(&self, g_: &mut [f64]) -> Result<(), String>
The g vector as used within the ACCs.
§Arguments
g_The g vector as used within the ACCs.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getaccgvector
sourcepub fn get_acc_n(&mut self, accidx_: i64) -> Result<i64, String>
pub fn get_acc_n(&mut self, accidx_: i64) -> Result<i64, String>
Obtains the dimension of the affine conic constraint.
§Arguments
accidx_The index of the affine conic constraint.
§Returns
nThe dimension of the affine conic constraint (equal to the dimension of its domain).
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getaccn
sourcepub fn get_acc_name(&self, accidx_: i64) -> Result<String, String>
pub fn get_acc_name(&self, accidx_: i64) -> Result<String, String>
Obtains the name of an affine conic constraint.
§Arguments
accidx_Index of an affine conic constraint.
§Returns
nameReturns the required name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getaccname
sourcepub fn get_acc_name_len(&self, accidx_: i64) -> Result<i32, String>
pub fn get_acc_name_len(&self, accidx_: i64) -> Result<i32, String>
Obtains the length of the name of an affine conic constraint.
§Arguments
accidx_Index of an affine conic constraint.
§Returns
lenReturns the length of the indicated name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getaccnamelen
sourcepub fn get_acc_n_tot(&mut self) -> Result<i64, String>
pub fn get_acc_n_tot(&mut self) -> Result<i64, String>
Obtains the total dimension of all affine conic constraints.
§Returns
nThe total dimension of all affine conic constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getaccntot
sourcepub fn get_accs(
&self,
domidxlist_: &mut [i64],
afeidxlist_: &mut [i64],
b_: &mut [f64]
) -> Result<(), String>
pub fn get_accs( &self, domidxlist_: &mut [i64], afeidxlist_: &mut [i64], b_: &mut [f64] ) -> Result<(), String>
Obtains full data of all affine conic constraints.
§Arguments
domidxlist_The list of domains appearing in all affine conic constraints.afeidxlist_The concatenation of index lists of affine expressions appearing in all affine conic constraints.b_The concatenation of vectors b appearing in all affine conic constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getaccs
sourcepub fn get_a_col(
&self,
j_: i32,
nzj_: &mut i32,
subj_: &mut [i32],
valj_: &mut [f64]
) -> Result<(), String>
pub fn get_a_col( &self, j_: i32, nzj_: &mut i32, subj_: &mut [i32], valj_: &mut [f64] ) -> Result<(), String>
Obtains one column of the linear constraint matrix.
§Arguments
j_Index of the column.nzj_Number of non-zeros in the column obtained.subj_Row indices of the non-zeros in the column obtained.valj_Numerical values in the column obtained.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getacol
sourcepub fn get_a_col_num_nz(&self, i_: i32) -> Result<i32, String>
pub fn get_a_col_num_nz(&self, i_: i32) -> Result<i32, String>
Obtains the number of non-zero elements in one column of the linear constraint matrix
§Arguments
i_Index of the column.
§Returns
nzjNumber of non-zeros in the j’th column of (A).
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getacolnumnz
sourcepub fn get_a_col_slice(
&self,
first_: i32,
last_: i32,
ptrb_: &mut [i64],
ptre_: &mut [i64],
sub_: &mut [i32],
val_: &mut [f64]
) -> Result<(), String>
pub fn get_a_col_slice( &self, first_: i32, last_: i32, ptrb_: &mut [i64], ptre_: &mut [i64], sub_: &mut [i32], val_: &mut [f64] ) -> Result<(), String>
Obtains a sequence of columns from the coefficient matrix.
§Arguments
first_Index of the first column in the sequence.last_Index of the last column in the sequence plus one.ptrb_Column start pointers.ptre_Column end pointers.sub_Contains the row subscripts.val_Contains the coefficient values.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getacolslice64
sourcepub fn get_a_col_slice_num_nz(
&self,
first_: i32,
last_: i32
) -> Result<i64, String>
pub fn get_a_col_slice_num_nz( &self, first_: i32, last_: i32 ) -> Result<i64, String>
Obtains the number of non-zeros in a slice of columns of the coefficient matrix.
§Arguments
first_Index of the first column in the sequence.last_Index of the last column plus one in the sequence.
§Returns
numnzNumber of non-zeros in the slice.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getacolslicenumnz64
sourcepub fn get_a_col_slice_trip(
&self,
first_: i32,
last_: i32,
subi_: &mut [i32],
subj_: &mut [i32],
val_: &mut [f64]
) -> Result<(), String>
pub fn get_a_col_slice_trip( &self, first_: i32, last_: i32, subi_: &mut [i32], subj_: &mut [i32], val_: &mut [f64] ) -> Result<(), String>
Obtains a sequence of columns from the coefficient matrix in triplet format.
§Arguments
first_Index of the first column in the sequence.last_Index of the last column in the sequence plus one.subi_Constraint subscripts.subj_Column subscripts.val_Values.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getacolslicetrip
sourcepub fn get_afe_barf_block_triplet(
&self,
afeidx_: &mut [i64],
barvaridx_: &mut [i32],
subk_: &mut [i32],
subl_: &mut [i32],
valkl_: &mut [f64]
) -> Result<i64, String>
pub fn get_afe_barf_block_triplet( &self, afeidx_: &mut [i64], barvaridx_: &mut [i32], subk_: &mut [i32], subl_: &mut [i32], valkl_: &mut [f64] ) -> Result<i64, String>
Obtains barF in block triplet form.
§Arguments
afeidx_Constraint index.barvaridx_Symmetric matrix variable index.subk_Block row index.subl_Block column index.valkl_The numerical value associated with each block triplet.
§Returns
numtripNumber of elements in the block triplet form.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getafebarfblocktriplet
sourcepub fn get_afe_barf_num_block_triplets(&self) -> Result<i64, String>
pub fn get_afe_barf_num_block_triplets(&self) -> Result<i64, String>
Obtains an upper bound on the number of elements in the block triplet form of barf.
§Returns
numtripAn upper bound on the number of elements in the block triplet form of barf.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getafebarfnumblocktriplets
sourcepub fn get_afe_barf_num_row_entries(
&mut self,
afeidx_: i64
) -> Result<i32, String>
pub fn get_afe_barf_num_row_entries( &mut self, afeidx_: i64 ) -> Result<i32, String>
Obtains the number of nonzero entries in a row of barF.
§Arguments
afeidx_Row index of barF.
§Returns
numentrNumber of nonzero entries in a row of barF.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getafebarfnumrowentries
sourcepub fn get_afe_barf_row(
&mut self,
afeidx_: i64,
barvaridx_: &mut [i32],
ptrterm_: &mut [i64],
numterm_: &mut [i64],
termidx_: &mut [i64],
termweight_: &mut [f64]
) -> Result<(), String>
pub fn get_afe_barf_row( &mut self, afeidx_: i64, barvaridx_: &mut [i32], ptrterm_: &mut [i64], numterm_: &mut [i64], termidx_: &mut [i64], termweight_: &mut [f64] ) -> Result<(), String>
Obtains nonzero entries in one row of barF.
§Arguments
afeidx_Row index of barF.barvaridx_Semidefinite variable indices.ptrterm_Pointers to the description of entries.numterm_Number of terms in each entry.termidx_Indices of semidefinite matrices from E.termweight_Weights appearing in the weighted sum representation.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getafebarfrow
sourcepub fn get_afe_barf_row_info(
&mut self,
afeidx_: i64,
numentr_: &mut i32,
numterm_: &mut i64
) -> Result<(), String>
pub fn get_afe_barf_row_info( &mut self, afeidx_: i64, numentr_: &mut i32, numterm_: &mut i64 ) -> Result<(), String>
Obtains information about one row of barF.
§Arguments
afeidx_Row index of barF.numentr_Number of nonzero entries in a row of barF.numterm_Number of terms in the weighted sums representation of the row of barF.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getafebarfrowinfo
sourcepub fn get_afe_f_num_nz(&mut self) -> Result<i64, String>
pub fn get_afe_f_num_nz(&mut self) -> Result<i64, String>
Obtains the total number of nonzeros in F.
§Returns
numnzNumber of nonzeros in F.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getafefnumnz
sourcepub fn get_afe_f_row(
&mut self,
afeidx_: i64,
numnz_: &mut i32,
varidx_: &mut [i32],
val_: &mut [f64]
) -> Result<(), String>
pub fn get_afe_f_row( &mut self, afeidx_: i64, numnz_: &mut i32, varidx_: &mut [i32], val_: &mut [f64] ) -> Result<(), String>
Obtains one row of F in sparse format.
§Arguments
afeidx_Row index.numnz_Number of non-zeros in the row obtained.varidx_Column indices of the non-zeros in the row obtained.val_Values of the non-zeros in the row obtained.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getafefrow
sourcepub fn get_afe_f_row_num_nz(&mut self, afeidx_: i64) -> Result<i32, String>
pub fn get_afe_f_row_num_nz(&mut self, afeidx_: i64) -> Result<i32, String>
Obtains the number of nonzeros in a row of F.
§Arguments
afeidx_Row index.
§Returns
numnzNumber of non-zeros in the row.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getafefrownumnz
sourcepub fn get_afe_f_trip(
&mut self,
afeidx_: &mut [i64],
varidx_: &mut [i32],
val_: &mut [f64]
) -> Result<(), String>
pub fn get_afe_f_trip( &mut self, afeidx_: &mut [i64], varidx_: &mut [i32], val_: &mut [f64] ) -> Result<(), String>
Obtains the F matrix in triplet format.
§Arguments
afeidx_Row indices of nonzeros.varidx_Column indices of nonzeros.val_Values of nonzero entries.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getafeftrip
sourcepub fn get_afe_g(&mut self, afeidx_: i64) -> Result<f64, String>
pub fn get_afe_g(&mut self, afeidx_: i64) -> Result<f64, String>
Obtains a single coefficient in g.
§Arguments
afeidx_Element index.
§Returns
gThe entry in g.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getafeg
sourcepub fn get_afe_g_slice(
&self,
first_: i64,
last_: i64,
g_: &mut [f64]
) -> Result<(), String>
pub fn get_afe_g_slice( &self, first_: i64, last_: i64, g_: &mut [f64] ) -> Result<(), String>
Obtains a sequence of coefficients from the vector g.
§Arguments
first_First index in the sequence.last_Last index plus 1 in the sequence.g_The slice of g as a dense vector.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getafegslice
sourcepub fn get_aij(&self, i_: i32, j_: i32) -> Result<f64, String>
pub fn get_aij(&self, i_: i32, j_: i32) -> Result<f64, String>
Obtains a single coefficient in linear constraint matrix.
§Arguments
i_Row index of the coefficient to be returned.j_Column index of the coefficient to be returned.
§Returns
aijReturns the requested coefficient.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getaij
sourcepub fn get_a_piece_num_nz(
&self,
firsti_: i32,
lasti_: i32,
firstj_: i32,
lastj_: i32
) -> Result<i32, String>
pub fn get_a_piece_num_nz( &self, firsti_: i32, lasti_: i32, firstj_: i32, lastj_: i32 ) -> Result<i32, String>
Obtains the number non-zeros in a rectangular piece of the linear constraint matrix.
§Arguments
firsti_Index of the first row in the rectangular piece.lasti_Index of the last row plus one in the rectangular piece.firstj_Index of the first column in the rectangular piece.lastj_Index of the last column plus one in the rectangular piece.
§Returns
numnzNumber of non-zero elements in the rectangular piece of the linear constraint matrix.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getapiecenumnz
sourcepub fn get_a_row(
&self,
i_: i32,
nzi_: &mut i32,
subi_: &mut [i32],
vali_: &mut [f64]
) -> Result<(), String>
pub fn get_a_row( &self, i_: i32, nzi_: &mut i32, subi_: &mut [i32], vali_: &mut [f64] ) -> Result<(), String>
Obtains one row of the linear constraint matrix.
§Arguments
i_Index of the row.nzi_Number of non-zeros in the row obtained.subi_Column indices of the non-zeros in the row obtained.vali_Numerical values of the row obtained.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getarow
sourcepub fn get_a_row_num_nz(&self, i_: i32) -> Result<i32, String>
pub fn get_a_row_num_nz(&self, i_: i32) -> Result<i32, String>
Obtains the number of non-zero elements in one row of the linear constraint matrix
§Arguments
i_Index of the row.
§Returns
nziNumber of non-zeros in the i’th row ofA.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getarownumnz
sourcepub fn get_a_row_slice(
&self,
first_: i32,
last_: i32,
ptrb_: &mut [i64],
ptre_: &mut [i64],
sub_: &mut [i32],
val_: &mut [f64]
) -> Result<(), String>
pub fn get_a_row_slice( &self, first_: i32, last_: i32, ptrb_: &mut [i64], ptre_: &mut [i64], sub_: &mut [i32], val_: &mut [f64] ) -> Result<(), String>
Obtains a sequence of rows from the coefficient matrix.
§Arguments
first_Index of the first row in the sequence.last_Index of the last row in the sequence plus one.ptrb_Row start pointers.ptre_Row end pointers.sub_Contains the column subscripts.val_Contains the coefficient values.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getarowslice64
sourcepub fn get_a_row_slice_num_nz(
&self,
first_: i32,
last_: i32
) -> Result<i64, String>
pub fn get_a_row_slice_num_nz( &self, first_: i32, last_: i32 ) -> Result<i64, String>
Obtains the number of non-zeros in a slice of rows of the coefficient matrix.
§Arguments
first_Index of the first row in the sequence.last_Index of the last row plus one in the sequence.
§Returns
numnzNumber of non-zeros in the slice.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getarowslicenumnz64
sourcepub fn get_a_row_slice_trip(
&self,
first_: i32,
last_: i32,
subi_: &mut [i32],
subj_: &mut [i32],
val_: &mut [f64]
) -> Result<(), String>
pub fn get_a_row_slice_trip( &self, first_: i32, last_: i32, subi_: &mut [i32], subj_: &mut [i32], val_: &mut [f64] ) -> Result<(), String>
Obtains a sequence of rows from the coefficient matrix in sparse triplet format.
§Arguments
first_Index of the first row in the sequence.last_Index of the last row in the sequence plus one.subi_Constraint subscripts.subj_Column subscripts.val_Values.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getarowslicetrip
sourcepub fn get_a_trip(
&self,
subi_: &mut [i32],
subj_: &mut [i32],
val_: &mut [f64]
) -> Result<(), String>
pub fn get_a_trip( &self, subi_: &mut [i32], subj_: &mut [i32], val_: &mut [f64] ) -> Result<(), String>
Obtains the A matrix in sparse triplet format.
§Arguments
subi_Constraint subscripts.subj_Column subscripts.val_Values.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getatrip
sourcepub fn get_a_truncate_tol(&self, tolzero_: &mut [f64]) -> Result<(), String>
pub fn get_a_truncate_tol(&self, tolzero_: &mut [f64]) -> Result<(), String>
Gets the current A matrix truncation threshold.
§Arguments
tolzero_Truncation tolerance.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getatruncatetol
sourcepub fn get_bara_block_triplet(
&self,
subi_: &mut [i32],
subj_: &mut [i32],
subk_: &mut [i32],
subl_: &mut [i32],
valijkl_: &mut [f64]
) -> Result<i64, String>
pub fn get_bara_block_triplet( &self, subi_: &mut [i32], subj_: &mut [i32], subk_: &mut [i32], subl_: &mut [i32], valijkl_: &mut [f64] ) -> Result<i64, String>
Obtains barA in block triplet form.
§Arguments
subi_Constraint index.subj_Symmetric matrix variable index.subk_Block row index.subl_Block column index.valijkl_The numerical value associated with each block triplet.
§Returns
numNumber of elements in the block triplet form.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getbarablocktriplet
sourcepub fn get_bara_idx(
&self,
idx_: i64,
i_: &mut i32,
j_: &mut i32,
sub_: &mut [i64],
weights_: &mut [f64]
) -> Result<i64, String>
pub fn get_bara_idx( &self, idx_: i64, i_: &mut i32, j_: &mut i32, sub_: &mut [i64], weights_: &mut [f64] ) -> Result<i64, String>
Obtains information about an element in barA.
§Arguments
idx_Position of the element in the vectorized form.i_Row index of the element at position idx.j_Column index of the element at position idx.sub_A list indexes of the elements from symmetric matrix storage that appear in the weighted sum.weights_The weights associated with each term in the weighted sum.
§Returns
numNumber of terms in weighted sum that forms the element.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getbaraidx
sourcepub fn get_bara_idx_i_j(
&self,
idx_: i64,
i_: &mut i32,
j_: &mut i32
) -> Result<(), String>
pub fn get_bara_idx_i_j( &self, idx_: i64, i_: &mut i32, j_: &mut i32 ) -> Result<(), String>
Obtains information about an element in barA.
§Arguments
idx_Position of the element in the vectorized form.i_Row index of the element at position idx.j_Column index of the element at position idx.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getbaraidxij
sourcepub fn get_bara_idx_info(&self, idx_: i64) -> Result<i64, String>
pub fn get_bara_idx_info(&self, idx_: i64) -> Result<i64, String>
Obtains the number of terms in the weighted sum that form a particular element in barA.
§Arguments
idx_The internal position of the element for which information should be obtained.
§Returns
numNumber of terms in the weighted sum that form the specified element in barA.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getbaraidxinfo
sourcepub fn get_bara_sparsity(
&self,
numnz_: &mut i64,
idxij_: &mut [i64]
) -> Result<(), String>
pub fn get_bara_sparsity( &self, numnz_: &mut i64, idxij_: &mut [i64] ) -> Result<(), String>
Obtains the sparsity pattern of the barA matrix.
§Arguments
numnz_Number of nonzero elements in barA.idxij_Position of each nonzero element in the vector representation of barA.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getbarasparsity
sourcepub fn get_barc_block_triplet(
&self,
subj_: &mut [i32],
subk_: &mut [i32],
subl_: &mut [i32],
valjkl_: &mut [f64]
) -> Result<i64, String>
pub fn get_barc_block_triplet( &self, subj_: &mut [i32], subk_: &mut [i32], subl_: &mut [i32], valjkl_: &mut [f64] ) -> Result<i64, String>
Obtains barC in block triplet form.
§Arguments
subj_Symmetric matrix variable index.subk_Block row index.subl_Block column index.valjkl_The numerical value associated with each block triplet.
§Returns
numNumber of elements in the block triplet form.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getbarcblocktriplet
sourcepub fn get_barc_idx(
&self,
idx_: i64,
j_: &mut i32,
num_: &mut i64,
sub_: &mut [i64],
weights_: &mut [f64]
) -> Result<(), String>
pub fn get_barc_idx( &self, idx_: i64, j_: &mut i32, num_: &mut i64, sub_: &mut [i64], weights_: &mut [f64] ) -> Result<(), String>
Obtains information about an element in barc.
§Arguments
idx_Index of the element for which information should be obtained.j_Row index in barc.num_Number of terms in the weighted sum.sub_Elements appearing the weighted sum.weights_Weights of terms in the weighted sum.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getbarcidx
sourcepub fn get_barc_idx_info(&self, idx_: i64) -> Result<i64, String>
pub fn get_barc_idx_info(&self, idx_: i64) -> Result<i64, String>
Obtains information about an element in barc.
§Arguments
idx_Index of the element for which information should be obtained. The value is an index of a symmetric sparse variable.
§Returns
numNumber of terms that appear in the weighted sum that forms the requested element.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getbarcidxinfo
sourcepub fn get_barc_idx_j(&self, idx_: i64, j_: &mut i32) -> Result<(), String>
pub fn get_barc_idx_j(&self, idx_: i64, j_: &mut i32) -> Result<(), String>
Obtains the row index of an element in barc.
§Arguments
idx_Index of the element for which information should be obtained.j_Row index in barc.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getbarcidxj
sourcepub fn get_barc_sparsity(
&self,
numnz_: &mut i64,
idxj_: &mut [i64]
) -> Result<(), String>
pub fn get_barc_sparsity( &self, numnz_: &mut i64, idxj_: &mut [i64] ) -> Result<(), String>
Get the positions of the nonzero elements in barc.
§Arguments
numnz_Number of nonzero elements in barc.idxj_Internal positions of the nonzeros elements in barc.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getbarcsparsity
sourcepub fn get_bars_j(
&self,
whichsol_: i32,
j_: i32,
barsj_: &mut [f64]
) -> Result<(), String>
pub fn get_bars_j( &self, whichsol_: i32, j_: i32, barsj_: &mut [f64] ) -> Result<(), String>
Obtains the dual solution for a semidefinite variable.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
j_Index of the semidefinite variable. -
barsj_Value of the j’th dual variable of barx.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getbarsj
sourcepub fn get_bars_slice(
&self,
whichsol_: i32,
first_: i32,
last_: i32,
slicesize_: i64,
barsslice_: &mut [f64]
) -> Result<(), String>
pub fn get_bars_slice( &self, whichsol_: i32, first_: i32, last_: i32, slicesize_: i64, barsslice_: &mut [f64] ) -> Result<(), String>
Obtains the dual solution for a sequence of semidefinite variables.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_Index of the first semidefinite variable in the slice. -
last_Index of the last semidefinite variable in the slice plus one. -
slicesize_Denotes the length of the array barsslice. -
barsslice_Dual solution values of symmetric matrix variables in the slice, stored sequentially.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getbarsslice
sourcepub fn get_barvar_name(&self, i_: i32) -> Result<String, String>
pub fn get_barvar_name(&self, i_: i32) -> Result<String, String>
Obtains the name of a semidefinite variable.
§Arguments
i_Index of the variable.
§Returns
nameThe requested name is copied to this buffer.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getbarvarname
sourcepub fn get_barvar_name_index(
&self,
somename_: &str,
asgn_: &mut i32
) -> Result<i32, String>
pub fn get_barvar_name_index( &self, somename_: &str, asgn_: &mut i32 ) -> Result<i32, String>
Obtains the index of semidefinite variable from its name.
§Arguments
somename_The name of the variable.asgn_Non-zero if the name somename is assigned to some semidefinite variable.
§Returns
indexThe index of a semidefinite variable with the name somename (if one exists).
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getbarvarnameindex
sourcepub fn get_barvar_name_len(&self, i_: i32) -> Result<i32, String>
pub fn get_barvar_name_len(&self, i_: i32) -> Result<i32, String>
Obtains the length of the name of a semidefinite variable.
§Arguments
i_Index of the variable.
§Returns
lenReturns the length of the indicated name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getbarvarnamelen
sourcepub fn get_barx_j(
&self,
whichsol_: i32,
j_: i32,
barxj_: &mut [f64]
) -> Result<(), String>
pub fn get_barx_j( &self, whichsol_: i32, j_: i32, barxj_: &mut [f64] ) -> Result<(), String>
Obtains the primal solution for a semidefinite variable.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
j_Index of the semidefinite variable. -
barxj_Value of the j’th variable of barx.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getbarxj
sourcepub fn get_barx_slice(
&self,
whichsol_: i32,
first_: i32,
last_: i32,
slicesize_: i64,
barxslice_: &mut [f64]
) -> Result<(), String>
pub fn get_barx_slice( &self, whichsol_: i32, first_: i32, last_: i32, slicesize_: i64, barxslice_: &mut [f64] ) -> Result<(), String>
Obtains the primal solution for a sequence of semidefinite variables.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_Index of the first semidefinite variable in the slice. -
last_Index of the last semidefinite variable in the slice plus one. -
slicesize_Denotes the length of the array barxslice. -
barxslice_Solution values of symmetric matrix variables in the slice, stored sequentially.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getbarxslice
sourcepub fn get_c(&self, c_: &mut [f64]) -> Result<(), String>
pub fn get_c(&self, c_: &mut [f64]) -> Result<(), String>
Obtains all objective coefficients.
§Arguments
c_Linear terms of the objective as a dense vector. The length is the number of variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getc
sourcepub fn get_cfix(&self) -> Result<f64, String>
pub fn get_cfix(&self) -> Result<f64, String>
Obtains the fixed term in the objective.
§Returns
cfixFixed term in the objective.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getcfix
sourcepub fn get_c_j(&self, j_: i32, cj_: &mut f64) -> Result<(), String>
pub fn get_c_j(&self, j_: i32, cj_: &mut f64) -> Result<(), String>
Obtains one objective coefficient.
§Arguments
j_Index of the variable for which the c coefficient should be obtained.cj_The c coefficient value.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getcj
sourcepub fn get_c_list(&self, subj_: &[i32], c_: &mut [f64]) -> Result<(), String>
pub fn get_c_list(&self, subj_: &[i32], c_: &mut [f64]) -> Result<(), String>
Obtains a sequence of coefficients from the objective.
§Arguments
subj_A list of variable indexes.c_Linear terms of the requested list of the objective as a dense vector.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getclist
sourcepub fn get_con_bound(
&self,
i_: i32,
bk_: &mut i32,
bl_: &mut f64,
bu_: &mut f64
) -> Result<(), String>
pub fn get_con_bound( &self, i_: i32, bk_: &mut i32, bl_: &mut f64, bu_: &mut f64 ) -> Result<(), String>
Obtains bound information for one constraint.
§Arguments
-
i_Index of the constraint for which the bound information should be obtained. -
bk_Bound keys.See Boundkey
-
bl_Values for lower bounds. -
bu_Values for upper bounds.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getconbound
sourcepub fn get_con_bound_slice(
&self,
first_: i32,
last_: i32,
bk_: &mut [i32],
bl_: &mut [f64],
bu_: &mut [f64]
) -> Result<(), String>
pub fn get_con_bound_slice( &self, first_: i32, last_: i32, bk_: &mut [i32], bl_: &mut [f64], bu_: &mut [f64] ) -> Result<(), String>
Obtains bounds information for a slice of the constraints.
§Arguments
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
bk_Bound keys.See Boundkey
-
bl_Values for lower bounds. -
bu_Values for upper bounds.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getconboundslice
sourcepub fn get_cone(
&mut self,
k_: i32,
ct_: &mut i32,
conepar_: &mut f64,
nummem_: &mut i32,
submem_: &mut [i32]
) -> Result<(), String>
pub fn get_cone( &mut self, k_: i32, ct_: &mut i32, conepar_: &mut f64, nummem_: &mut i32, submem_: &mut [i32] ) -> Result<(), String>
Obtains a cone.
§Arguments
-
k_Index of the cone. -
ct_Specifies the type of the cone.See Conetype
-
conepar_For the power cone it denotes the exponent alpha. For other cone types it is unused and can be set to 0. -
nummem_Number of member variables in the cone. -
submem_Variable subscripts of the members in the cone.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getcone
sourcepub fn get_cone_info(
&self,
k_: i32,
ct_: &mut i32,
conepar_: &mut f64,
nummem_: &mut i32
) -> Result<(), String>
pub fn get_cone_info( &self, k_: i32, ct_: &mut i32, conepar_: &mut f64, nummem_: &mut i32 ) -> Result<(), String>
Obtains information about a cone.
§Arguments
-
k_Index of the cone. -
ct_Specifies the type of the cone.See Conetype
-
conepar_For the power cone it denotes the exponent alpha. For other cone types it is unused and can be set to 0. -
nummem_Number of member variables in the cone.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getconeinfo
sourcepub fn get_cone_name(&self, i_: i32) -> Result<String, String>
pub fn get_cone_name(&self, i_: i32) -> Result<String, String>
Obtains the name of a cone.
§Arguments
i_Index of the cone.
§Returns
nameThe required name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getconename
sourcepub fn get_cone_name_index(
&self,
somename_: &str,
asgn_: &mut i32
) -> Result<i32, String>
pub fn get_cone_name_index( &self, somename_: &str, asgn_: &mut i32 ) -> Result<i32, String>
Checks whether the name has been assigned to any cone.
§Arguments
somename_The name which should be checked.asgn_Is non-zero if the name somename is assigned to some cone.
§Returns
indexIf the name somename is assigned to some cone, this is the index of the cone.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getconenameindex
sourcepub fn get_cone_name_len(&self, i_: i32) -> Result<i32, String>
pub fn get_cone_name_len(&self, i_: i32) -> Result<i32, String>
Obtains the length of the name of a cone.
§Arguments
i_Index of the cone.
§Returns
lenReturns the length of the indicated name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getconenamelen
sourcepub fn get_con_name(&self, i_: i32) -> Result<String, String>
pub fn get_con_name(&self, i_: i32) -> Result<String, String>
Obtains the name of a constraint.
§Arguments
i_Index of the constraint.
§Returns
nameThe required name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getconname
sourcepub fn get_con_name_index(
&self,
somename_: &str,
asgn_: &mut i32
) -> Result<i32, String>
pub fn get_con_name_index( &self, somename_: &str, asgn_: &mut i32 ) -> Result<i32, String>
Checks whether the name has been assigned to any constraint.
§Arguments
somename_The name which should be checked.asgn_Is non-zero if the name somename is assigned to some constraint.
§Returns
indexIf the name somename is assigned to a constraint, then return the index of the constraint.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getconnameindex
sourcepub fn get_con_name_len(&self, i_: i32) -> Result<i32, String>
pub fn get_con_name_len(&self, i_: i32) -> Result<i32, String>
Obtains the length of the name of a constraint.
§Arguments
i_Index of the constraint.
§Returns
lenReturns the length of the indicated name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getconnamelen
sourcepub fn get_c_slice(
&self,
first_: i32,
last_: i32,
c_: &mut [f64]
) -> Result<(), String>
pub fn get_c_slice( &self, first_: i32, last_: i32, c_: &mut [f64] ) -> Result<(), String>
Obtains a sequence of coefficients from the objective.
§Arguments
first_First index in the sequence.last_Last index plus 1 in the sequence.c_Linear terms of the requested slice of the objective as a dense vector.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getcslice
sourcepub fn get_dim_barvar_j(&self, j_: i32) -> Result<i32, String>
pub fn get_dim_barvar_j(&self, j_: i32) -> Result<i32, String>
Obtains the dimension of a symmetric matrix variable.
§Arguments
j_Index of the semidefinite variable whose dimension is requested.
§Returns
dimbarvarjThe dimension of the j’th semidefinite variable.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdimbarvarj
sourcepub fn get_djc_afe_idx_list(
&self,
djcidx_: i64,
afeidxlist_: &mut [i64]
) -> Result<(), String>
pub fn get_djc_afe_idx_list( &self, djcidx_: i64, afeidxlist_: &mut [i64] ) -> Result<(), String>
Obtains the list of affine expression indexes in a disjunctive constraint.
§Arguments
djcidx_Index of the disjunctive constraint.afeidxlist_List of affine expression indexes.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdjcafeidxlist
sourcepub fn get_djc_b(&self, djcidx_: i64, b_: &mut [f64]) -> Result<(), String>
pub fn get_djc_b(&self, djcidx_: i64, b_: &mut [f64]) -> Result<(), String>
Obtains the optional constant term vector of a disjunctive constraint.
§Arguments
djcidx_Index of the disjunctive constraint.b_The vector b.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdjcb
sourcepub fn get_djc_domain_idx_list(
&self,
djcidx_: i64,
domidxlist_: &mut [i64]
) -> Result<(), String>
pub fn get_djc_domain_idx_list( &self, djcidx_: i64, domidxlist_: &mut [i64] ) -> Result<(), String>
Obtains the list of domain indexes in a disjunctive constraint.
§Arguments
djcidx_Index of the disjunctive constraint.domidxlist_List of term sizes.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdjcdomainidxlist
sourcepub fn get_djc_name(&self, djcidx_: i64) -> Result<String, String>
pub fn get_djc_name(&self, djcidx_: i64) -> Result<String, String>
Obtains the name of a disjunctive constraint.
§Arguments
djcidx_Index of a disjunctive constraint.
§Returns
nameReturns the required name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdjcname
sourcepub fn get_djc_name_len(&self, djcidx_: i64) -> Result<i32, String>
pub fn get_djc_name_len(&self, djcidx_: i64) -> Result<i32, String>
Obtains the length of the name of a disjunctive constraint.
§Arguments
djcidx_Index of a disjunctive constraint.
§Returns
lenReturns the length of the indicated name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdjcnamelen
sourcepub fn get_djc_num_afe(&mut self, djcidx_: i64) -> Result<i64, String>
pub fn get_djc_num_afe(&mut self, djcidx_: i64) -> Result<i64, String>
Obtains the number of affine expressions in the disjunctive constraint.
§Arguments
djcidx_Index of the disjunctive constraint.
§Returns
numafeNumber of affine expressions in the disjunctive constraint.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdjcnumafe
sourcepub fn get_djc_num_afe_tot(&mut self) -> Result<i64, String>
pub fn get_djc_num_afe_tot(&mut self) -> Result<i64, String>
Obtains the number of affine expressions in all disjunctive constraints.
§Returns
numafetotNumber of affine expressions in all disjunctive constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdjcnumafetot
sourcepub fn get_djc_num_domain(&mut self, djcidx_: i64) -> Result<i64, String>
pub fn get_djc_num_domain(&mut self, djcidx_: i64) -> Result<i64, String>
Obtains the number of domains in the disjunctive constraint.
§Arguments
djcidx_Index of the disjunctive constraint.
§Returns
numdomainNumber of domains in the disjunctive constraint.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdjcnumdomain
sourcepub fn get_djc_num_domain_tot(&mut self) -> Result<i64, String>
pub fn get_djc_num_domain_tot(&mut self) -> Result<i64, String>
Obtains the number of domains in all disjunctive constraints.
§Returns
numdomaintotNumber of domains in all disjunctive constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdjcnumdomaintot
sourcepub fn get_djc_num_term(&mut self, djcidx_: i64) -> Result<i64, String>
pub fn get_djc_num_term(&mut self, djcidx_: i64) -> Result<i64, String>
Obtains the number terms in the disjunctive constraint.
§Arguments
djcidx_Index of the disjunctive constraint.
§Returns
numtermNumber of terms in the disjunctive constraint.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdjcnumterm
sourcepub fn get_djc_num_term_tot(&mut self) -> Result<i64, String>
pub fn get_djc_num_term_tot(&mut self) -> Result<i64, String>
Obtains the number of terms in all disjunctive constraints.
§Returns
numtermtotTotal number of terms in all disjunctive constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdjcnumtermtot
sourcepub fn get_djcs(
&self,
domidxlist_: &mut [i64],
afeidxlist_: &mut [i64],
b_: &mut [f64],
termsizelist_: &mut [i64],
numterms_: &mut [i64]
) -> Result<(), String>
pub fn get_djcs( &self, domidxlist_: &mut [i64], afeidxlist_: &mut [i64], b_: &mut [f64], termsizelist_: &mut [i64], numterms_: &mut [i64] ) -> Result<(), String>
Obtains full data of all disjunctive constraints.
§Arguments
domidxlist_The concatenation of index lists of domains appearing in all disjunctive constraints.afeidxlist_The concatenation of index lists of affine expressions appearing in all disjunctive constraints.b_The concatenation of vectors b appearing in all disjunctive constraints.termsizelist_The concatenation of lists of term sizes appearing in all disjunctive constraints.numterms_The number of terms in each of the disjunctive constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdjcs
sourcepub fn get_djc_term_size_list(
&self,
djcidx_: i64,
termsizelist_: &mut [i64]
) -> Result<(), String>
pub fn get_djc_term_size_list( &self, djcidx_: i64, termsizelist_: &mut [i64] ) -> Result<(), String>
Obtains the list of term sizes in a disjunctive constraint.
§Arguments
djcidx_Index of the disjunctive constraint.termsizelist_List of term sizes.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdjctermsizelist
sourcepub fn get_domain_n(&self, domidx_: i64) -> Result<i64, String>
pub fn get_domain_n(&self, domidx_: i64) -> Result<i64, String>
Obtains the dimension of the domain.
§Arguments
domidx_Index of the domain.
§Returns
nDimension of the domain.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdomainn
sourcepub fn get_domain_name(&self, domidx_: i64) -> Result<String, String>
pub fn get_domain_name(&self, domidx_: i64) -> Result<String, String>
Obtains the name of a domain.
§Arguments
domidx_Index of a domain.
§Returns
nameReturns the required name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdomainname
sourcepub fn get_domain_name_len(&self, domidx_: i64) -> Result<i32, String>
pub fn get_domain_name_len(&self, domidx_: i64) -> Result<i32, String>
Obtains the length of the name of a domain.
§Arguments
domidx_Index of a domain.
§Returns
lenReturns the length of the indicated name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdomainnamelen
sourcepub fn get_domain_type(&self, domidx_: i64) -> Result<i32, String>
pub fn get_domain_type(&self, domidx_: i64) -> Result<i32, String>
Returns the type of the domain.
§Arguments
domidx_Index of the domain.
§Returns
domtypeThe type of the domain.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdomaintype
sourcepub fn get_dou_inf(&self, whichdinf_: i32) -> Result<f64, String>
pub fn get_dou_inf(&self, whichdinf_: i32) -> Result<f64, String>
Obtains a double information item.
§Arguments
-
whichdinf_Specifies a double information item.See Dinfitem
§Returns
dvalueThe value of the required double information item.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdouinf
Examples found in repository?
examples/parameters.rs (line 47)
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fn main() -> Result<(),String> {
let mut task = Task::new().unwrap();
println!("Test MOSEK parameter get/set functions");
// Set log level (integer parameter)
task.put_int_param(Iparam::LOG, 1)?;
// Select interior-point optimizer... (integer parameter)
task.put_int_param(Iparam::OPTIMIZER, Optimizertype::INTPNT)?;
// ... without basis identification (integer parameter)
task.put_int_param(Iparam::INTPNT_BASIS,Basindtype::NEVER)?;
// Set relative gap tolerance (double parameter)
task.put_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP, 1.0e-7)?;
// The same using explicit string names
task.put_param("MSK_DPAR_INTPNT_CO_TOL_REL_GAP", "1.0e-7")?;
task.put_na_dou_param("MSK_DPAR_INTPNT_CO_TOL_REL_GAP", 1.0e-7 )?;
// Incorrect value
if let Err(_) = task.put_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP, -1.0) {
println!("Wrong parameter value");
}
let param = task.get_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP)?;
println!("Current value for parameter intpnt_co_tol_rel_gap = $param");
// Define and solve an optimization problem here
// optimize(task,)
// After optimization:
println!("Get MOSEK information items");
let tm = task.get_dou_inf(Dinfitem::OPTIMIZER_TIME)?;
let iter = task.get_int_inf(Iinfitem::INTPNT_ITER)?;
println!("Time: {}",tm);
println!("Iterations: {}",iter);
Ok(())
}More examples
examples/parallel.rs (line 76)
32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80
fn parallel(files : Vec<FileOrText>) -> Result<(),String> {
// Create an example list of tasks to optimize
let mut tasks : Vec<(String,Task)> = files.iter().filter_map(|fname| {
let mut t = Task::new().unwrap();
match fname {
FileOrText::File(fname) => {
if let Err(_) = t.read_data(fname.as_str()) { None }
else {
t.put_int_param(mosek::Iparam::NUM_THREADS, 2).unwrap();
Some((fname.as_str().to_string(),t))
}
},
FileOrText::Text(data) => {
if let Err(_) = t.read_ptf_string(data.as_str()) { None }
else {
t.put_int_param(mosek::Iparam::NUM_THREADS, 2).unwrap();
Some(("-".to_string(),t))
}
}
}
}).collect();
let mut res = vec![0i32; tasks.len()];
let mut trm = vec![0i32; tasks.len()];
{
let taskrs : Vec<& mut Task> = tasks.iter_mut().map(|(_a,b)| b).collect();
// Size of thread pool available for all tasks
let threadpoolsize : i32 = 6;
// Optimize all the given tasks in parallel
mosek::optimize_batch(false, // No race
-1.0, // No time limit
threadpoolsize,
taskrs.as_slice(), // Array of tasks to optimize
trm.as_mut_slice(),
res.as_mut_slice())?;
}
for (resi,trmi,(fname,ti)) in izip!(res,trm,tasks.iter()) {
println!("Task {} res {} trm {} obj_val {} time {}",
fname,
resi,
trmi,
ti.get_dou_inf(mosek::Dinfitem::INTPNT_PRIMAL_OBJ)?,
ti.get_dou_inf(mosek::Dinfitem::OPTIMIZER_TIME)?);
}
Ok(())
}sourcepub fn get_dou_param(&self, param_: i32) -> Result<f64, String>
pub fn get_dou_param(&self, param_: i32) -> Result<f64, String>
Obtains a double parameter.
§Arguments
-
param_Which parameter.See Dparam
§Returns
parvalueParameter value.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdouparam
Examples found in repository?
examples/parameters.rs (line 38)
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fn main() -> Result<(),String> {
let mut task = Task::new().unwrap();
println!("Test MOSEK parameter get/set functions");
// Set log level (integer parameter)
task.put_int_param(Iparam::LOG, 1)?;
// Select interior-point optimizer... (integer parameter)
task.put_int_param(Iparam::OPTIMIZER, Optimizertype::INTPNT)?;
// ... without basis identification (integer parameter)
task.put_int_param(Iparam::INTPNT_BASIS,Basindtype::NEVER)?;
// Set relative gap tolerance (double parameter)
task.put_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP, 1.0e-7)?;
// The same using explicit string names
task.put_param("MSK_DPAR_INTPNT_CO_TOL_REL_GAP", "1.0e-7")?;
task.put_na_dou_param("MSK_DPAR_INTPNT_CO_TOL_REL_GAP", 1.0e-7 )?;
// Incorrect value
if let Err(_) = task.put_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP, -1.0) {
println!("Wrong parameter value");
}
let param = task.get_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP)?;
println!("Current value for parameter intpnt_co_tol_rel_gap = $param");
// Define and solve an optimization problem here
// optimize(task,)
// After optimization:
println!("Get MOSEK information items");
let tm = task.get_dou_inf(Dinfitem::OPTIMIZER_TIME)?;
let iter = task.get_int_inf(Iinfitem::INTPNT_ITER)?;
println!("Time: {}",tm);
println!("Iterations: {}",iter);
Ok(())
}sourcepub fn get_dual_obj(
&self,
whichsol_: i32,
dualobj_: &mut f64
) -> Result<(), String>
pub fn get_dual_obj( &self, whichsol_: i32, dualobj_: &mut f64 ) -> Result<(), String>
Computes the dual objective value associated with the solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
dualobj_Objective value corresponding to the dual solution.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdualobj
sourcepub fn get_dual_solution_norms(
&self,
whichsol_: i32,
nrmy_: &mut f64,
nrmslc_: &mut f64,
nrmsuc_: &mut f64,
nrmslx_: &mut f64,
nrmsux_: &mut f64,
nrmsnx_: &mut f64,
nrmbars_: &mut f64
) -> Result<(), String>
pub fn get_dual_solution_norms( &self, whichsol_: i32, nrmy_: &mut f64, nrmslc_: &mut f64, nrmsuc_: &mut f64, nrmslx_: &mut f64, nrmsux_: &mut f64, nrmsnx_: &mut f64, nrmbars_: &mut f64 ) -> Result<(), String>
Compute norms of the dual solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
nrmy_The norm of the y vector. -
nrmslc_The norm of the slc vector. -
nrmsuc_The norm of the suc vector. -
nrmslx_The norm of the slx vector. -
nrmsux_The norm of the sux vector. -
nrmsnx_The norm of the snx vector. -
nrmbars_The norm of the bars vector.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdualsolutionnorms
sourcepub fn get_dviol_acc(
&self,
whichsol_: i32,
accidxlist_: &[i64],
viol_: &mut [f64]
) -> Result<(), String>
pub fn get_dviol_acc( &self, whichsol_: i32, accidxlist_: &[i64], viol_: &mut [f64] ) -> Result<(), String>
Computes the violation of the dual solution for set of affine conic constraints.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
accidxlist_An array of indexes of conic constraints. -
viol_List of violations corresponding to sub.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdviolacc
sourcepub fn get_dviol_barvar(
&self,
whichsol_: i32,
sub_: &[i32],
viol_: &mut [f64]
) -> Result<(), String>
pub fn get_dviol_barvar( &self, whichsol_: i32, sub_: &[i32], viol_: &mut [f64] ) -> Result<(), String>
Computes the violation of dual solution for a set of semidefinite variables.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
sub_An array of indexes of barx variables. -
viol_List of violations corresponding to sub.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdviolbarvar
sourcepub fn get_dviol_con(
&self,
whichsol_: i32,
sub_: &[i32],
viol_: &mut [f64]
) -> Result<(), String>
pub fn get_dviol_con( &self, whichsol_: i32, sub_: &[i32], viol_: &mut [f64] ) -> Result<(), String>
Computes the violation of a dual solution associated with a set of constraints.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
sub_An array of indexes of constraints. -
viol_List of violations corresponding to sub.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdviolcon
sourcepub fn get_dviol_cones(
&self,
whichsol_: i32,
sub_: &[i32],
viol_: &mut [f64]
) -> Result<(), String>
pub fn get_dviol_cones( &self, whichsol_: i32, sub_: &[i32], viol_: &mut [f64] ) -> Result<(), String>
Computes the violation of a solution for set of dual conic constraints.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
sub_An array of indexes of conic constraints. -
viol_List of violations corresponding to sub.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdviolcones
sourcepub fn get_dviol_var(
&self,
whichsol_: i32,
sub_: &[i32],
viol_: &mut [f64]
) -> Result<(), String>
pub fn get_dviol_var( &self, whichsol_: i32, sub_: &[i32], viol_: &mut [f64] ) -> Result<(), String>
Computes the violation of a dual solution associated with a set of scalar variables.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
sub_An array of indexes of x variables. -
viol_List of violations corresponding to sub.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getdviolvar
sourcepub fn get_inf_index(
&self,
inftype_: i32,
infname_: &str,
infindex_: &mut i32
) -> Result<(), String>
pub fn get_inf_index( &self, inftype_: i32, infname_: &str, infindex_: &mut i32 ) -> Result<(), String>
Obtains the index of a named information item.
§Arguments
-
inftype_Type of the information item.See Inftype
-
infname_Name of the information item. -
infindex_The item index.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getinfindex
sourcepub fn get_inf_max(
&self,
inftype_: i32,
infmax_: &mut [i32]
) -> Result<(), String>
pub fn get_inf_max( &self, inftype_: i32, infmax_: &mut [i32] ) -> Result<(), String>
Obtains the maximum index of an information item of a given type.
§Arguments
-
inftype_Type of the information item.See Inftype
-
infmax_The maximum index (plus 1) requested.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getinfmax
sourcepub fn get_inf_name(
&self,
inftype_: i32,
whichinf_: i32
) -> Result<String, String>
pub fn get_inf_name( &self, inftype_: i32, whichinf_: i32 ) -> Result<String, String>
Obtains the name of an information item.
§Arguments
-
inftype_Type of the information item.See Inftype
-
whichinf_An information item.
§Returns
infnameName of the information item.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getinfname
sourcepub fn get_int_inf(&self, whichiinf_: i32) -> Result<i32, String>
pub fn get_int_inf(&self, whichiinf_: i32) -> Result<i32, String>
Obtains an integer information item.
§Arguments
-
whichiinf_Specifies an integer information item.See Iinfitem
§Returns
ivalueThe value of the required integer information item.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getintinf
Examples found in repository?
examples/parameters.rs (line 48)
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fn main() -> Result<(),String> {
let mut task = Task::new().unwrap();
println!("Test MOSEK parameter get/set functions");
// Set log level (integer parameter)
task.put_int_param(Iparam::LOG, 1)?;
// Select interior-point optimizer... (integer parameter)
task.put_int_param(Iparam::OPTIMIZER, Optimizertype::INTPNT)?;
// ... without basis identification (integer parameter)
task.put_int_param(Iparam::INTPNT_BASIS,Basindtype::NEVER)?;
// Set relative gap tolerance (double parameter)
task.put_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP, 1.0e-7)?;
// The same using explicit string names
task.put_param("MSK_DPAR_INTPNT_CO_TOL_REL_GAP", "1.0e-7")?;
task.put_na_dou_param("MSK_DPAR_INTPNT_CO_TOL_REL_GAP", 1.0e-7 )?;
// Incorrect value
if let Err(_) = task.put_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP, -1.0) {
println!("Wrong parameter value");
}
let param = task.get_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP)?;
println!("Current value for parameter intpnt_co_tol_rel_gap = $param");
// Define and solve an optimization problem here
// optimize(task,)
// After optimization:
println!("Get MOSEK information items");
let tm = task.get_dou_inf(Dinfitem::OPTIMIZER_TIME)?;
let iter = task.get_int_inf(Iinfitem::INTPNT_ITER)?;
println!("Time: {}",tm);
println!("Iterations: {}",iter);
Ok(())
}sourcepub fn get_int_param(&self, param_: i32) -> Result<i32, String>
pub fn get_int_param(&self, param_: i32) -> Result<i32, String>
Obtains an integer parameter.
§Arguments
-
param_Which parameter.See Iparam
§Returns
parvalueParameter value.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getintparam
sourcepub fn get_len_barvar_j(&self, j_: i32) -> Result<i64, String>
pub fn get_len_barvar_j(&self, j_: i32) -> Result<i64, String>
Obtains the length of one semidefinite variable.
§Arguments
j_Index of the semidefinite variable whose length if requested.
§Returns
lenbarvarjNumber of scalar elements in the lower triangular part of the semidefinite variable.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getlenbarvarj
sourcepub fn get_lint_inf(&self, whichliinf_: i32) -> Result<i64, String>
pub fn get_lint_inf(&self, whichliinf_: i32) -> Result<i64, String>
Obtains a long integer information item.
§Arguments
-
whichliinf_Specifies a long information item.See Liinfitem
§Returns
ivalueThe value of the required long integer information item.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getlintinf
sourcepub fn get_max_name_len(&self, maxlen_: &mut i32) -> Result<(), String>
pub fn get_max_name_len(&self, maxlen_: &mut i32) -> Result<(), String>
Obtains the maximum length (not including terminating zero character) of any objective, constraint, variable, domain or cone name.
§Arguments
maxlen_The maximum length of any name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getmaxnamelen
sourcepub fn get_max_num_a_nz(&self) -> Result<i64, String>
pub fn get_max_num_a_nz(&self) -> Result<i64, String>
Obtains number of preallocated non-zeros in the linear constraint matrix.
§Returns
maxnumanzNumber of preallocated non-zero linear matrix elements.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getmaxnumanz64
sourcepub fn get_max_num_barvar(&self) -> Result<i32, String>
pub fn get_max_num_barvar(&self) -> Result<i32, String>
Obtains maximum number of symmetric matrix variables for which space is currently preallocated.
§Returns
maxnumbarvarMaximum number of symmetric matrix variables for which space is currently preallocated.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getmaxnumbarvar
sourcepub fn get_max_num_con(&self, maxnumcon_: &mut i32) -> Result<(), String>
pub fn get_max_num_con(&self, maxnumcon_: &mut i32) -> Result<(), String>
Obtains the number of preallocated constraints in the optimization task.
§Arguments
maxnumcon_Number of preallocated constraints in the optimization task.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getmaxnumcon
sourcepub fn get_max_num_cone(&self, maxnumcone_: &mut i32) -> Result<(), String>
pub fn get_max_num_cone(&self, maxnumcone_: &mut i32) -> Result<(), String>
Obtains the number of preallocated cones in the optimization task.
§Arguments
maxnumcone_Number of preallocated conic constraints in the optimization task.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getmaxnumcone
sourcepub fn get_max_num_q_nz(&self, maxnumqnz_: &mut i64) -> Result<(), String>
pub fn get_max_num_q_nz(&self, maxnumqnz_: &mut i64) -> Result<(), String>
Obtains the number of preallocated non-zeros for all quadratic terms in objective and constraints.
§Arguments
maxnumqnz_Number of non-zero elements preallocated in quadratic coefficient matrices.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getmaxnumqnz64
sourcepub fn get_max_num_var(&self, maxnumvar_: &mut i32) -> Result<(), String>
pub fn get_max_num_var(&self, maxnumvar_: &mut i32) -> Result<(), String>
Obtains the maximum number variables allowed.
§Arguments
maxnumvar_Number of preallocated variables in the optimization task.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getmaxnumvar
sourcepub fn get_mem_usage(
&self,
meminuse_: &mut i64,
maxmemuse_: &mut i64
) -> Result<(), String>
pub fn get_mem_usage( &self, meminuse_: &mut i64, maxmemuse_: &mut i64 ) -> Result<(), String>
Obtains information about the amount of memory used by a task.
§Arguments
meminuse_Amount of memory currently used by the task.maxmemuse_Maximum amount of memory used by the task until now.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getmemusagetask
sourcepub fn get_mio_num_threads(&self) -> Result<i32, String>
pub fn get_mio_num_threads(&self) -> Result<i32, String>
Obtains the number of threads used by the mixed integer optimizer.
§Returns
numthreadsThe number of threads.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getmionumthreads
sourcepub fn get_na_dou_inf(
&self,
infitemname_: &str,
dvalue_: &mut f64
) -> Result<(), String>
pub fn get_na_dou_inf( &self, infitemname_: &str, dvalue_: &mut f64 ) -> Result<(), String>
Obtains a named double information item.
§Arguments
infitemname_The name of a double information item.dvalue_The value of the required double information item.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnadouinf
sourcepub fn get_na_dou_param(
&self,
paramname_: &str,
parvalue_: &mut f64
) -> Result<(), String>
pub fn get_na_dou_param( &self, paramname_: &str, parvalue_: &mut f64 ) -> Result<(), String>
Obtains a double parameter.
§Arguments
paramname_Name of a parameter.parvalue_Parameter value.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnadouparam
sourcepub fn get_na_int_inf(
&self,
infitemname_: &str,
ivalue_: &mut i32
) -> Result<(), String>
pub fn get_na_int_inf( &self, infitemname_: &str, ivalue_: &mut i32 ) -> Result<(), String>
Obtains a named integer information item.
§Arguments
infitemname_The name of an integer information item.ivalue_The value of the required integer information item.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnaintinf
sourcepub fn get_na_int_param(
&self,
paramname_: &str,
parvalue_: &mut i32
) -> Result<(), String>
pub fn get_na_int_param( &self, paramname_: &str, parvalue_: &mut i32 ) -> Result<(), String>
Obtains an integer parameter.
§Arguments
paramname_Name of a parameter.parvalue_Parameter value.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnaintparam
sourcepub fn get_na_str_param(
&self,
paramname_: &str,
sizeparamname_: i32,
len_: &mut i32
) -> Result<String, String>
pub fn get_na_str_param( &self, paramname_: &str, sizeparamname_: i32, len_: &mut i32 ) -> Result<String, String>
Obtains a string parameter.
§Arguments
paramname_Name of a parameter.sizeparamname_Size of the name buffer.len_Returns the length of the parameter value.
§Returns
parvalueParameter value.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnastrparam
sourcepub fn get_num_acc(&mut self) -> Result<i64, String>
pub fn get_num_acc(&mut self) -> Result<i64, String>
Obtains the number of affine conic constraints.
§Returns
numThe number of affine conic constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnumacc
Examples found in repository?
examples/portfolio_2_frontier.rs (line 80)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}More examples
examples/portfolio_5_card.rs (line 134)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}sourcepub fn get_num_afe(&mut self) -> Result<i64, String>
pub fn get_num_afe(&mut self) -> Result<i64, String>
Obtains the number of affine expressions.
§Returns
numafeNumber of affine expressions.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnumafe
Examples found in repository?
examples/portfolio_2_frontier.rs (line 81)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}More examples
examples/portfolio_5_card.rs (line 133)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}sourcepub fn get_num_a_nz(&self) -> Result<i32, String>
pub fn get_num_a_nz(&self) -> Result<i32, String>
Obtains the number of non-zeros in the coefficient matrix.
§Returns
numanzNumber of non-zero elements in the linear constraint matrix.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnumanz
sourcepub fn get_num_a_nz_64(&self) -> Result<i64, String>
pub fn get_num_a_nz_64(&self) -> Result<i64, String>
Obtains the number of non-zeros in the coefficient matrix.
§Returns
numanzNumber of non-zero elements in the linear constraint matrix.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnumanz64
sourcepub fn get_num_bara_block_triplets(&self) -> Result<i64, String>
pub fn get_num_bara_block_triplets(&self) -> Result<i64, String>
Obtains an upper bound on the number of scalar elements in the block triplet form of bara.
§Returns
numAn upper bound on the number of elements in the block triplet form of bara.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnumbarablocktriplets
sourcepub fn get_num_bara_nz(&self) -> Result<i64, String>
pub fn get_num_bara_nz(&self) -> Result<i64, String>
Get the number of nonzero elements in barA.
§Returns
nzThe number of nonzero block elements in barA.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnumbaranz
sourcepub fn get_num_barc_block_triplets(&self) -> Result<i64, String>
pub fn get_num_barc_block_triplets(&self) -> Result<i64, String>
Obtains an upper bound on the number of elements in the block triplet form of barc.
§Returns
numAn upper bound on the number of elements in the block triplet form of barc.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnumbarcblocktriplets
sourcepub fn get_num_barc_nz(&self) -> Result<i64, String>
pub fn get_num_barc_nz(&self) -> Result<i64, String>
Obtains the number of nonzero elements in barc.
§Returns
nzThe number of nonzero elements in barc.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnumbarcnz
sourcepub fn get_num_barvar(&self) -> Result<i32, String>
pub fn get_num_barvar(&self) -> Result<i32, String>
Obtains the number of semidefinite variables.
§Returns
numbarvarNumber of semidefinite variables in the problem.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnumbarvar
sourcepub fn get_num_con(&self) -> Result<i32, String>
pub fn get_num_con(&self) -> Result<i32, String>
Obtains the number of constraints.
§Returns
numconNumber of constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnumcon
Examples found in repository?
examples/reoptimization.rs (line 138)
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fn main() -> Result<(),String> {
let numcon = 3;
let numvar = 3;
let c = &[1.5, 2.5, 3.0 ];
let bkc = &[ Boundkey::UP,
Boundkey::UP,
Boundkey::UP ];
let blc = &[ -INF,
-INF,
-INF ];
let buc = &[ 100000.0,
50000.0,
60000.0 ];
let bkx = &[ Boundkey::LO,
Boundkey::LO,
Boundkey::LO
];
let blx = &[ 0.0, 0.0, 0.0 ];
let bux = &[ INF,
INF,
INF ];
let asub = &[
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ] ];
let aval = &[
&[ 2.0, 3.0, 2.0 ],
&[ 4.0, 2.0, 3.0 ],
&[ 3.0, 3.0, 2.0 ] ];
let mut task = Task::new().unwrap();
/* Append the constraints. */
task.append_cons(numcon)?;
/* Append the variables. */
task.append_vars(numvar)?;
/* Put C. */
for (j,&cj) in (0..numvar).zip(c.iter()) {
task.put_c_j(j,cj)?;
}
/* Put constraint bounds. */
for (i,&bki,&bli,&bui) in izip!(0..numcon,bkc,blc,buc) {
task.put_con_bound(i, bki, bli, bui)?;
}
/* Put variable bounds. */
for (j,&bki,&bli,&bui) in izip!(0..numvar,bkx,blx,bux) {
task.put_var_bound(j, bki, bli, bui)?;
}
/* Put A. */
if numcon > 0 {
for (j,&asubj,&avalj) in izip!(0..numvar,asub,aval) {
task.put_a_col(j,
asubj,
avalj)?;
}
}
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/****************** Make a change to the A matrix ******************/
task.put_aij(0, 0, 3.0)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/***************** Add a new variable ******************************/
/* Get index of new variable. */
let varidx = task.get_num_var()?;
/* Append a new variable x_3 to the problem */
task.append_vars(1)?;
let numvar = numvar + 1;
/* Set bounds on new varaible */
task.put_var_bound(varidx, Boundkey::LO, 0.0, INF)?;
/* Change objective */
task.put_c_j(varidx, 1.0)?;
/* Put new values in the A matrix */
let acolsub = &[0i32, 2];
let acolval = &[4.0, 1.0];
task.put_a_col(varidx, /* column index */
acolsub,
acolval)?;
/* Change optimizer to simplex free and reoptimize */
task.put_int_param(mosek::Iparam::OPTIMIZER, mosek::Optimizertype::FREE_SIMPLEX)?;
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Add a new constraint ***************************/
/* Get index of new constraint. */
let conidx = task.get_num_con()?;
/* Append a new constraint */
task.append_cons(1)?;
let numcon = numcon + 1;
/* Set bounds on new constraint */
task.put_con_bound(conidx,
Boundkey::UP,
-INF,
30000.0)?;
/* Put new values in the A matrix */
let arowsub = &[0i32, 1, 2, 3 ];
let arowval = &[1.0, 2.0, 1.0, 1.0 ];
task.put_a_row(conidx, /* row index */
arowsub,
arowval)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Change constraint bounds ********************/
let newbkc = &[Boundkey::UP,
Boundkey::UP,
Boundkey::UP,
Boundkey::UP];
let newblc = &[-INF,
-INF,
-INF,
-INF];
let newbuc = &[ 80000.0, 40000.0, 50000.0, 22000.0 ];
task.put_con_bound_slice(0, numcon, newbkc, newblc, newbuc)?;
let _ = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
Ok(())
}More examples
examples/portfolio_5_card.rs (line 93)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}sourcepub fn get_num_cone(&self) -> Result<i32, String>
pub fn get_num_cone(&self) -> Result<i32, String>
Obtains the number of cones.
§Returns
numconeNumber of conic constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnumcone
sourcepub fn get_num_cone_mem(&self, k_: i32, nummem_: &mut i32) -> Result<(), String>
pub fn get_num_cone_mem(&self, k_: i32, nummem_: &mut i32) -> Result<(), String>
Obtains the number of members in a cone.
§Arguments
k_Index of the cone.nummem_Number of member variables in the cone.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnumconemem
sourcepub fn get_num_djc(&mut self) -> Result<i64, String>
pub fn get_num_djc(&mut self) -> Result<i64, String>
Obtains the number of disjunctive constraints.
§Returns
numThe number of disjunctive constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnumdjc
sourcepub fn get_num_domain(&mut self) -> Result<i64, String>
pub fn get_num_domain(&mut self) -> Result<i64, String>
Obtain the number of domains defined.
§Returns
numdomainNumber of domains in the task.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnumdomain
sourcepub fn get_num_int_var(&self) -> Result<i32, String>
pub fn get_num_int_var(&self) -> Result<i32, String>
Obtains the number of integer-constrained variables.
§Returns
numintvarNumber of integer variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnumintvar
Examples found in repository?
examples/concurrent1.rs (line 115)
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fn concurrent1(data : FileOrText, timelimit : Option<String>) -> Result<(),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
match data {
FileOrText::File(fname) => task.read_data(fname.as_str())?,
FileOrText::Text(text) => task.read_ptf_string(text.as_str())?
}
if let Some(timelimit) = timelimit {
task.put_dou_param(mosek::Dparam::OPTIMIZER_MAX_TIME, timelimit.parse().unwrap())?;
}
let numintvar = task.get_num_int_var()?;
let r = if numintvar == 0 {
let optimizers = &[mosek::Optimizertype::CONIC,
mosek::Optimizertype::DUAL_SIMPLEX,
mosek::Optimizertype::PRIMAL_SIMPLEX];
optimize_concurrent(& mut task, optimizers)
}
else {
let seeds = &[ 42, 13, 71749373 ];
optimize_concurrent_mio(& mut task, seeds)
};
let sense = task.get_obj_sense()?;
// Pick the feasible result. For non-integer problems all
// solutions should be the same if more than one is returned, but
// for integer problems tasks may have hit the time limit and
// returned non-optimal solutions.
let n = r.len();
if n == 0 {
println!("All optimizers failed.");
}
else if numintvar > 0 {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
ii.iter().zip(tasks.iter()).enumerate()
.filter_map(|(k,(_i,t))|
match (*t).solution_def(Soltype::ITG) {
Ok(true) => match t.get_sol_sta(Soltype::ITG).unwrap() {
Solsta::PRIM_FEAS|Solsta::INTEGER_OPTIMAL => Some((k,t.get_primal_obj(Soltype::ITG).unwrap())),
_ => None
},
_ => None
})
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
else {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
tasks.iter().enumerate()
.filter_map(|(k,t)|
match t.get_sol_sta(Soltype::BAS) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::BAS).unwrap())),
_ => None
}.or_else(|| match t.get_sol_sta(Soltype::ITR) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::ITR).unwrap())),
_ => None
}))
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
Result::Ok(())
}sourcepub fn get_num_param(
&self,
partype_: i32,
numparam_: &mut i32
) -> Result<(), String>
pub fn get_num_param( &self, partype_: i32, numparam_: &mut i32 ) -> Result<(), String>
Obtains the number of parameters of a given type.
§Arguments
-
partype_Parameter type.See Parametertype
-
numparam_Returns the number of parameters of the requested type.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnumparam
sourcepub fn get_num_q_con_k_nz(&self, k_: i32) -> Result<i64, String>
pub fn get_num_q_con_k_nz(&self, k_: i32) -> Result<i64, String>
Obtains the number of non-zero quadratic terms in a constraint.
§Arguments
k_Index of the constraint for which the number quadratic terms should be obtained.
§Returns
numqcnzNumber of quadratic terms.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnumqconknz64
sourcepub fn get_num_q_obj_nz(&self) -> Result<i64, String>
pub fn get_num_q_obj_nz(&self) -> Result<i64, String>
Obtains the number of non-zero quadratic terms in the objective.
§Returns
numqonzNumber of non-zero elements in the quadratic objective terms.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnumqobjnz64
sourcepub fn get_num_sym_mat(&self, num_: &mut i64) -> Result<(), String>
pub fn get_num_sym_mat(&self, num_: &mut i64) -> Result<(), String>
Obtains the number of symmetric matrices stored.
§Arguments
num_The number of symmetric sparse matrices.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnumsymmat
sourcepub fn get_num_var(&self) -> Result<i32, String>
pub fn get_num_var(&self) -> Result<i32, String>
Obtains the number of variables.
§Returns
numvarNumber of variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getnumvar
Examples found in repository?
examples/reoptimization.rs (line 84)
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fn main() -> Result<(),String> {
let numcon = 3;
let numvar = 3;
let c = &[1.5, 2.5, 3.0 ];
let bkc = &[ Boundkey::UP,
Boundkey::UP,
Boundkey::UP ];
let blc = &[ -INF,
-INF,
-INF ];
let buc = &[ 100000.0,
50000.0,
60000.0 ];
let bkx = &[ Boundkey::LO,
Boundkey::LO,
Boundkey::LO
];
let blx = &[ 0.0, 0.0, 0.0 ];
let bux = &[ INF,
INF,
INF ];
let asub = &[
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ] ];
let aval = &[
&[ 2.0, 3.0, 2.0 ],
&[ 4.0, 2.0, 3.0 ],
&[ 3.0, 3.0, 2.0 ] ];
let mut task = Task::new().unwrap();
/* Append the constraints. */
task.append_cons(numcon)?;
/* Append the variables. */
task.append_vars(numvar)?;
/* Put C. */
for (j,&cj) in (0..numvar).zip(c.iter()) {
task.put_c_j(j,cj)?;
}
/* Put constraint bounds. */
for (i,&bki,&bli,&bui) in izip!(0..numcon,bkc,blc,buc) {
task.put_con_bound(i, bki, bli, bui)?;
}
/* Put variable bounds. */
for (j,&bki,&bli,&bui) in izip!(0..numvar,bkx,blx,bux) {
task.put_var_bound(j, bki, bli, bui)?;
}
/* Put A. */
if numcon > 0 {
for (j,&asubj,&avalj) in izip!(0..numvar,asub,aval) {
task.put_a_col(j,
asubj,
avalj)?;
}
}
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/****************** Make a change to the A matrix ******************/
task.put_aij(0, 0, 3.0)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/***************** Add a new variable ******************************/
/* Get index of new variable. */
let varidx = task.get_num_var()?;
/* Append a new variable x_3 to the problem */
task.append_vars(1)?;
let numvar = numvar + 1;
/* Set bounds on new varaible */
task.put_var_bound(varidx, Boundkey::LO, 0.0, INF)?;
/* Change objective */
task.put_c_j(varidx, 1.0)?;
/* Put new values in the A matrix */
let acolsub = &[0i32, 2];
let acolval = &[4.0, 1.0];
task.put_a_col(varidx, /* column index */
acolsub,
acolval)?;
/* Change optimizer to simplex free and reoptimize */
task.put_int_param(mosek::Iparam::OPTIMIZER, mosek::Optimizertype::FREE_SIMPLEX)?;
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Add a new constraint ***************************/
/* Get index of new constraint. */
let conidx = task.get_num_con()?;
/* Append a new constraint */
task.append_cons(1)?;
let numcon = numcon + 1;
/* Set bounds on new constraint */
task.put_con_bound(conidx,
Boundkey::UP,
-INF,
30000.0)?;
/* Put new values in the A matrix */
let arowsub = &[0i32, 1, 2, 3 ];
let arowval = &[1.0, 2.0, 1.0, 1.0 ];
task.put_a_row(conidx, /* row index */
arowsub,
arowval)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Change constraint bounds ********************/
let newbkc = &[Boundkey::UP,
Boundkey::UP,
Boundkey::UP,
Boundkey::UP];
let newblc = &[-INF,
-INF,
-INF,
-INF];
let newbuc = &[ 80000.0, 40000.0, 50000.0, 22000.0 ];
task.put_con_bound_slice(0, numcon, newbkc, newblc, newbuc)?;
let _ = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
Ok(())
}sourcepub fn get_obj_name(&self) -> Result<String, String>
pub fn get_obj_name(&self) -> Result<String, String>
Obtains the name assigned to the objective function.
§Returns
objnameAssigned the objective name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getobjname
sourcepub fn get_obj_name_len(&self) -> Result<i32, String>
pub fn get_obj_name_len(&self) -> Result<i32, String>
Obtains the length of the name assigned to the objective function.
§Returns
lenAssigned the length of the objective name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getobjnamelen
sourcepub fn get_obj_sense(&self) -> Result<i32, String>
pub fn get_obj_sense(&self) -> Result<i32, String>
Gets the objective sense.
§Returns
senseThe returned objective sense.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getobjsense
Examples found in repository?
examples/concurrent1.rs (line 129)
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fn concurrent1(data : FileOrText, timelimit : Option<String>) -> Result<(),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
match data {
FileOrText::File(fname) => task.read_data(fname.as_str())?,
FileOrText::Text(text) => task.read_ptf_string(text.as_str())?
}
if let Some(timelimit) = timelimit {
task.put_dou_param(mosek::Dparam::OPTIMIZER_MAX_TIME, timelimit.parse().unwrap())?;
}
let numintvar = task.get_num_int_var()?;
let r = if numintvar == 0 {
let optimizers = &[mosek::Optimizertype::CONIC,
mosek::Optimizertype::DUAL_SIMPLEX,
mosek::Optimizertype::PRIMAL_SIMPLEX];
optimize_concurrent(& mut task, optimizers)
}
else {
let seeds = &[ 42, 13, 71749373 ];
optimize_concurrent_mio(& mut task, seeds)
};
let sense = task.get_obj_sense()?;
// Pick the feasible result. For non-integer problems all
// solutions should be the same if more than one is returned, but
// for integer problems tasks may have hit the time limit and
// returned non-optimal solutions.
let n = r.len();
if n == 0 {
println!("All optimizers failed.");
}
else if numintvar > 0 {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
ii.iter().zip(tasks.iter()).enumerate()
.filter_map(|(k,(_i,t))|
match (*t).solution_def(Soltype::ITG) {
Ok(true) => match t.get_sol_sta(Soltype::ITG).unwrap() {
Solsta::PRIM_FEAS|Solsta::INTEGER_OPTIMAL => Some((k,t.get_primal_obj(Soltype::ITG).unwrap())),
_ => None
},
_ => None
})
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
else {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
tasks.iter().enumerate()
.filter_map(|(k,t)|
match t.get_sol_sta(Soltype::BAS) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::BAS).unwrap())),
_ => None
}.or_else(|| match t.get_sol_sta(Soltype::ITR) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::ITR).unwrap())),
_ => None
}))
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
Result::Ok(())
}sourcepub fn get_param_max(
&self,
partype_: i32,
parammax_: &mut i32
) -> Result<(), String>
pub fn get_param_max( &self, partype_: i32, parammax_: &mut i32 ) -> Result<(), String>
Obtains the maximum index of a parameter of a given type.
§Arguments
-
partype_Parameter type.See Parametertype
-
parammax_The maximum index (plus 1) of the given parameter type.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getparammax
sourcepub fn get_param_name(
&self,
partype_: i32,
param_: i32
) -> Result<String, String>
pub fn get_param_name( &self, partype_: i32, param_: i32 ) -> Result<String, String>
Obtains the name of a parameter.
§Arguments
-
partype_Parameter type.See Parametertype
-
param_Which parameter.
§Returns
parnameParameter name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getparamname
sourcepub fn get_power_domain_alpha(
&mut self,
domidx_: i64,
alpha_: &mut [f64]
) -> Result<(), String>
pub fn get_power_domain_alpha( &mut self, domidx_: i64, alpha_: &mut [f64] ) -> Result<(), String>
Obtains the exponent vector of a power domain.
§Arguments
domidx_Index of the domain.alpha_The exponent vector of the domain.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getpowerdomainalpha
sourcepub fn get_power_domain_info(
&mut self,
domidx_: i64,
n_: &mut i64,
nleft_: &mut i64
) -> Result<(), String>
pub fn get_power_domain_info( &mut self, domidx_: i64, n_: &mut i64, nleft_: &mut i64 ) -> Result<(), String>
Obtains structural information about a power domain.
§Arguments
domidx_Index of the domain.n_Dimension of the domain.nleft_Number of variables on the left hand side.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getpowerdomaininfo
sourcepub fn get_primal_obj(&self, whichsol_: i32) -> Result<f64, String>
pub fn get_primal_obj(&self, whichsol_: i32) -> Result<f64, String>
Computes the primal objective value for the desired solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
§Returns
primalobjObjective value corresponding to the primal solution.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getprimalobj
Examples found in repository?
examples/concurrent1.rs (line 148)
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fn concurrent1(data : FileOrText, timelimit : Option<String>) -> Result<(),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
match data {
FileOrText::File(fname) => task.read_data(fname.as_str())?,
FileOrText::Text(text) => task.read_ptf_string(text.as_str())?
}
if let Some(timelimit) = timelimit {
task.put_dou_param(mosek::Dparam::OPTIMIZER_MAX_TIME, timelimit.parse().unwrap())?;
}
let numintvar = task.get_num_int_var()?;
let r = if numintvar == 0 {
let optimizers = &[mosek::Optimizertype::CONIC,
mosek::Optimizertype::DUAL_SIMPLEX,
mosek::Optimizertype::PRIMAL_SIMPLEX];
optimize_concurrent(& mut task, optimizers)
}
else {
let seeds = &[ 42, 13, 71749373 ];
optimize_concurrent_mio(& mut task, seeds)
};
let sense = task.get_obj_sense()?;
// Pick the feasible result. For non-integer problems all
// solutions should be the same if more than one is returned, but
// for integer problems tasks may have hit the time limit and
// returned non-optimal solutions.
let n = r.len();
if n == 0 {
println!("All optimizers failed.");
}
else if numintvar > 0 {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
ii.iter().zip(tasks.iter()).enumerate()
.filter_map(|(k,(_i,t))|
match (*t).solution_def(Soltype::ITG) {
Ok(true) => match t.get_sol_sta(Soltype::ITG).unwrap() {
Solsta::PRIM_FEAS|Solsta::INTEGER_OPTIMAL => Some((k,t.get_primal_obj(Soltype::ITG).unwrap())),
_ => None
},
_ => None
})
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
else {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
tasks.iter().enumerate()
.filter_map(|(k,t)|
match t.get_sol_sta(Soltype::BAS) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::BAS).unwrap())),
_ => None
}.or_else(|| match t.get_sol_sta(Soltype::ITR) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::ITR).unwrap())),
_ => None
}))
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
Result::Ok(())
}More examples
examples/portfolio_5_card.rs (line 176)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}sourcepub fn get_primal_solution_norms(
&self,
whichsol_: i32,
nrmxc_: &mut f64,
nrmxx_: &mut f64,
nrmbarx_: &mut f64
) -> Result<(), String>
pub fn get_primal_solution_norms( &self, whichsol_: i32, nrmxc_: &mut f64, nrmxx_: &mut f64, nrmbarx_: &mut f64 ) -> Result<(), String>
Compute norms of the primal solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
nrmxc_The norm of the xc vector. -
nrmxx_The norm of the xx vector. -
nrmbarx_The norm of the barX vector.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getprimalsolutionnorms
sourcepub fn get_prob_type(&self) -> Result<i32, String>
pub fn get_prob_type(&self) -> Result<i32, String>
Obtains the problem type.
§Returns
probtypeThe problem type.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getprobtype
sourcepub fn get_pro_sta(&self, whichsol_: i32) -> Result<i32, String>
pub fn get_pro_sta(&self, whichsol_: i32) -> Result<i32, String>
Obtains the problem status.
§Arguments
-
whichsol_Selects a solution.See Soltype
§Returns
problemstaProblem status.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getprosta
Examples found in repository?
examples/milo1.rs (line 105)
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fn main() -> Result<(),String> {
let numcon : i32 = 2;
let numvar : i32 = 2;
let infinity = 0.0; // only for symbolic purposes, value never used
let bkc = vec![Boundkey::UP, Boundkey::LO];
let blc = vec![ -infinity, -4.0 ];
let buc = vec![ 250.0, infinity ];
let bkx = vec![ Boundkey::LO, Boundkey::LO ];
let blx = vec![ 0.0, 0.0 ];
let bux = vec![ infinity, infinity ];
let c = vec![1.0, 0.64];
let asub = vec![0, 1,
0, 1];
let aval = vec![50.0, 3.0, 31.0, -2.0];
let ptrb : Vec<usize> = vec![ 0, 2 ];
let ptre : Vec<usize> = vec![ 2, 4 ];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| task.with_itg_sol_callback(
&mut |xx| { println!("Found a new solution = {:?}",xx); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
for ((((j,cj),bk),bl),bu) in (0..numvar).zip(c.iter()).zip(bkx.iter()).zip(blx.iter()).zip(bux.iter()) {
/* Set the linear term c_j in the objective.*/
task.put_c_j(j, *cj)?;
/* Set the bounds on variable j.
blx[j] <= x_j <= bux[j] */
task.put_var_bound(j, *bk, *bl, *bu)?;
/* Input column j of A */
task.put_a_col(j, /* Variable (column) index.*/
&asub[ptrb[j as usize]..ptre[j as usize]], /* Row index of non-zeros in column j.*/
&aval[ptrb[j as usize]..ptre[j as usize]])?; /* Non-zero Values of column j. */
}
// Set the bounds on constraints.
// for i=1, ...,numcon : blc[i] <= constraint i <= buc[i]
for (((i,bk),bl),bu) in (0..numcon).zip(bkc.iter()).zip(blc.iter()).zip(buc.iter()) {
task.put_con_bound(i, *bk, *bl, *bu)?;
}
/* Specify integer variables. */
for j in 0..numvar {
task.put_var_type(j, Variabletype::TYPE_INT)?;
}
/* Set max solution time */
task.put_dou_param(Dparam::MIO_MAX_TIME, 60.0)?;
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITG, xx.as_mut_slice())?;
/* Get status information about the solution */
match task.get_sol_sta(Soltype::ITG)? {
Solsta::INTEGER_OPTIMAL => {
println!("Optimal solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::PRIM_FEAS => {
println!("Feasible solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::UNKNOWN => {
match task.get_pro_sta(Soltype::ITG)? {
Prosta::PRIM_INFEAS_OR_UNBOUNDED => {
println!("Problem status Infeasible or unbounded");
}
Prosta::PRIM_INFEAS => {
println!("Problem status Infeasible.");
}
Prosta::UNKNOWN => {
println!("Problem status unknown.");
}
_ => {
println!("Other problem status.");
}
}
}
_ => {
println!("Other solution status");
}
}
Ok(())
}))
}sourcepub fn get_pviol_acc(
&self,
whichsol_: i32,
accidxlist_: &[i64],
viol_: &mut [f64]
) -> Result<(), String>
pub fn get_pviol_acc( &self, whichsol_: i32, accidxlist_: &[i64], viol_: &mut [f64] ) -> Result<(), String>
Computes the violation of a solution for set of affine conic constraints.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
accidxlist_An array of indexes of conic constraints. -
viol_List of violations corresponding to sub.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getpviolacc
sourcepub fn get_pviol_barvar(
&self,
whichsol_: i32,
sub_: &[i32],
viol_: &mut [f64]
) -> Result<(), String>
pub fn get_pviol_barvar( &self, whichsol_: i32, sub_: &[i32], viol_: &mut [f64] ) -> Result<(), String>
Computes the violation of a primal solution for a list of semidefinite variables.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
sub_An array of indexes of barX variables. -
viol_List of violations corresponding to sub.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getpviolbarvar
sourcepub fn get_pviol_con(
&self,
whichsol_: i32,
sub_: &[i32],
viol_: &mut [f64]
) -> Result<(), String>
pub fn get_pviol_con( &self, whichsol_: i32, sub_: &[i32], viol_: &mut [f64] ) -> Result<(), String>
Computes the violation of a primal solution associated to a constraint.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
sub_An array of indexes of constraints. -
viol_List of violations corresponding to sub.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getpviolcon
sourcepub fn get_pviol_cones(
&self,
whichsol_: i32,
sub_: &[i32],
viol_: &mut [f64]
) -> Result<(), String>
pub fn get_pviol_cones( &self, whichsol_: i32, sub_: &[i32], viol_: &mut [f64] ) -> Result<(), String>
Computes the violation of a solution for set of conic constraints.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
sub_An array of indexes of conic constraints. -
viol_List of violations corresponding to sub.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getpviolcones
sourcepub fn get_pviol_djc(
&self,
whichsol_: i32,
djcidxlist_: &[i64],
viol_: &mut [f64]
) -> Result<(), String>
pub fn get_pviol_djc( &self, whichsol_: i32, djcidxlist_: &[i64], viol_: &mut [f64] ) -> Result<(), String>
Computes the violation of a solution for set of disjunctive constraints.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
djcidxlist_An array of indexes of disjunctive constraints. -
viol_List of violations corresponding to sub.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getpvioldjc
sourcepub fn get_pviol_var(
&self,
whichsol_: i32,
sub_: &[i32],
viol_: &mut [f64]
) -> Result<(), String>
pub fn get_pviol_var( &self, whichsol_: i32, sub_: &[i32], viol_: &mut [f64] ) -> Result<(), String>
Computes the violation of a primal solution for a list of scalar variables.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
sub_An array of indexes of x variables. -
viol_List of violations corresponding to sub.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getpviolvar
sourcepub fn get_q_con_k(
&self,
k_: i32,
qcsubi_: &mut [i32],
qcsubj_: &mut [i32],
qcval_: &mut [f64]
) -> Result<i64, String>
pub fn get_q_con_k( &self, k_: i32, qcsubi_: &mut [i32], qcsubj_: &mut [i32], qcval_: &mut [f64] ) -> Result<i64, String>
Obtains all the quadratic terms in a constraint.
§Arguments
k_Which constraint.qcsubi_Row subscripts for quadratic constraint matrix.qcsubj_Column subscripts for quadratic constraint matrix.qcval_Quadratic constraint coefficient values.
§Returns
numqcnzNumber of quadratic terms.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getqconk64
sourcepub fn get_q_obj(
&self,
numqonz_: &mut i64,
qosubi_: &mut [i32],
qosubj_: &mut [i32],
qoval_: &mut [f64]
) -> Result<(), String>
pub fn get_q_obj( &self, numqonz_: &mut i64, qosubi_: &mut [i32], qosubj_: &mut [i32], qoval_: &mut [f64] ) -> Result<(), String>
Obtains all the quadratic terms in the objective.
§Arguments
numqonz_Number of non-zero elements in the quadratic objective terms.qosubi_Row subscripts for quadratic objective coefficients.qosubj_Column subscripts for quadratic objective coefficients.qoval_Quadratic objective coefficient values.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getqobj64
sourcepub fn get_q_obj_i_j(
&self,
i_: i32,
j_: i32,
qoij_: &mut f64
) -> Result<(), String>
pub fn get_q_obj_i_j( &self, i_: i32, j_: i32, qoij_: &mut f64 ) -> Result<(), String>
Obtains one coefficient from the quadratic term of the objective
§Arguments
i_Row index of the coefficient.j_Column index of coefficient.qoij_The required coefficient.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getqobjij
sourcepub fn get_reduced_costs(
&self,
whichsol_: i32,
first_: i32,
last_: i32,
redcosts_: &mut [f64]
) -> Result<(), String>
pub fn get_reduced_costs( &self, whichsol_: i32, first_: i32, last_: i32, redcosts_: &mut [f64] ) -> Result<(), String>
Obtains the reduced costs for a sequence of variables.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_The index of the first variable in the sequence. -
last_The index of the last variable in the sequence plus 1. -
redcosts_Returns the requested reduced costs.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getreducedcosts
sourcepub fn get_skc(&self, whichsol_: i32, skc_: &mut [i32]) -> Result<(), String>
pub fn get_skc(&self, whichsol_: i32, skc_: &mut [i32]) -> Result<(), String>
Obtains the status keys for the constraints.
§Arguments
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getskc
sourcepub fn get_skc_slice(
&self,
whichsol_: i32,
first_: i32,
last_: i32,
skc_: &mut [i32]
) -> Result<(), String>
pub fn get_skc_slice( &self, whichsol_: i32, first_: i32, last_: i32, skc_: &mut [i32] ) -> Result<(), String>
Obtains the status keys for a slice of the constraints.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
skc_Status keys for the constraints.See Stakey
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getskcslice
sourcepub fn get_skn(&self, whichsol_: i32, skn_: &mut [i32]) -> Result<(), String>
pub fn get_skn(&self, whichsol_: i32, skn_: &mut [i32]) -> Result<(), String>
Obtains the status keys for the conic constraints.
§Arguments
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getskn
sourcepub fn get_skx(&self, whichsol_: i32, skx_: &mut [i32]) -> Result<(), String>
pub fn get_skx(&self, whichsol_: i32, skx_: &mut [i32]) -> Result<(), String>
Obtains the status keys for the scalar variables.
§Arguments
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getskx
sourcepub fn get_skx_slice(
&self,
whichsol_: i32,
first_: i32,
last_: i32,
skx_: &mut [i32]
) -> Result<(), String>
pub fn get_skx_slice( &self, whichsol_: i32, first_: i32, last_: i32, skx_: &mut [i32] ) -> Result<(), String>
Obtains the status keys for a slice of the scalar variables.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
skx_Status keys for the variables.See Stakey
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getskxslice
sourcepub fn get_slc(&self, whichsol_: i32, slc_: &mut [f64]) -> Result<(), String>
pub fn get_slc(&self, whichsol_: i32, slc_: &mut [f64]) -> Result<(), String>
Obtains the slc vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
slc_Dual variables corresponding to the lower bounds on the constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getslc
sourcepub fn get_slc_slice(
&self,
whichsol_: i32,
first_: i32,
last_: i32,
slc_: &mut [f64]
) -> Result<(), String>
pub fn get_slc_slice( &self, whichsol_: i32, first_: i32, last_: i32, slc_: &mut [f64] ) -> Result<(), String>
Obtains a slice of the slc vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
slc_Dual variables corresponding to the lower bounds on the constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getslcslice
sourcepub fn get_slx(&self, whichsol_: i32, slx_: &mut [f64]) -> Result<(), String>
pub fn get_slx(&self, whichsol_: i32, slx_: &mut [f64]) -> Result<(), String>
Obtains the slx vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
slx_Dual variables corresponding to the lower bounds on the variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getslx
sourcepub fn get_slx_slice(
&self,
whichsol_: i32,
first_: i32,
last_: i32,
slx_: &mut [f64]
) -> Result<(), String>
pub fn get_slx_slice( &self, whichsol_: i32, first_: i32, last_: i32, slx_: &mut [f64] ) -> Result<(), String>
Obtains a slice of the slx vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
slx_Dual variables corresponding to the lower bounds on the variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getslxslice
sourcepub fn get_snx(&self, whichsol_: i32, snx_: &mut [f64]) -> Result<(), String>
pub fn get_snx(&self, whichsol_: i32, snx_: &mut [f64]) -> Result<(), String>
Obtains the snx vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
snx_Dual variables corresponding to the conic constraints on the variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getsnx
sourcepub fn get_snx_slice(
&self,
whichsol_: i32,
first_: i32,
last_: i32,
snx_: &mut [f64]
) -> Result<(), String>
pub fn get_snx_slice( &self, whichsol_: i32, first_: i32, last_: i32, snx_: &mut [f64] ) -> Result<(), String>
Obtains a slice of the snx vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
snx_Dual variables corresponding to the conic constraints on the variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getsnxslice
sourcepub fn get_sol_sta(&self, whichsol_: i32) -> Result<i32, String>
pub fn get_sol_sta(&self, whichsol_: i32) -> Result<i32, String>
Obtains the solution status.
§Arguments
-
whichsol_Selects a solution.See Soltype
§Returns
solutionstaSolution status.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getsolsta
Examples found in repository?
examples/portfolio_2_frontier.rs (line 102)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}More examples
examples/ceo1.rs (line 87)
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fn main() -> Result<(),String> {
let numcon = 1;
let numvar = 3;
let bkc = mosek::Boundkey::FX;
let blc = 1.0;
let buc = 1.0;
let bkx = vec![ Boundkey::FR,
Boundkey::FR,
Boundkey::FR ];
let blx = vec![ -INF, -INF, -INF ];
let bux = vec![ INF, INF, INF ];
let c = vec![ 1.0, 1.0, 0.0 ];
let a = vec![ 1.0, 1.0, 1.0 ];
let asub = vec![0, 1, 2];
//let csub = new int[numvar];
//double[] xx = new double[numvar];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|task| task.with_callback(
&mut |caller| { println!("caller = {}",caller); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
/* Define the linear part of the problem */
task.put_c_slice(0, numvar, c.as_slice())?;
task.put_a_row(0, asub.as_slice(), a.as_slice())?;
task.put_con_bound(0, bkc, blc, buc)?;
task.put_var_bound_slice(0, numvar, bkx.as_slice(), blx.as_slice(), bux.as_slice())?;
/* Add a conic constraint */
task.append_afes(3)?;
let afeidxs = vec![0, 1, 2 ];
let b = vec![0.0,0.0,0.0];
let domidx = task.append_primal_exp_cone_domain()?;
task.put_afe_f_row_list(afeidxs.as_slice(),
vec![1,1,1].as_slice(),
vec![0,1,2].as_slice(),
vec![0,1,2].as_slice(),
vec![1.0,1.0,1.0].as_slice())?;
task.append_acc(domidx,afeidxs.as_slice(),b.as_slice())?;
task.put_obj_sense(Objsense::MINIMIZE)?;
println!("optimize");
/* Solve the problem */
task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
/* Get status information about the solution */
let solsta = task.get_sol_sta(Soltype::ITR)?;
assert!(solsta == Solsta::OPTIMAL);
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITR, & mut xx[..])?;
println!("Optimal primal solution");
for j in 0..numvar as usize {
println!("x[{}]: {:.4}",j,xx[j]);
}
Ok(())
}))
}examples/concurrent1.rs (line 147)
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fn concurrent1(data : FileOrText, timelimit : Option<String>) -> Result<(),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
match data {
FileOrText::File(fname) => task.read_data(fname.as_str())?,
FileOrText::Text(text) => task.read_ptf_string(text.as_str())?
}
if let Some(timelimit) = timelimit {
task.put_dou_param(mosek::Dparam::OPTIMIZER_MAX_TIME, timelimit.parse().unwrap())?;
}
let numintvar = task.get_num_int_var()?;
let r = if numintvar == 0 {
let optimizers = &[mosek::Optimizertype::CONIC,
mosek::Optimizertype::DUAL_SIMPLEX,
mosek::Optimizertype::PRIMAL_SIMPLEX];
optimize_concurrent(& mut task, optimizers)
}
else {
let seeds = &[ 42, 13, 71749373 ];
optimize_concurrent_mio(& mut task, seeds)
};
let sense = task.get_obj_sense()?;
// Pick the feasible result. For non-integer problems all
// solutions should be the same if more than one is returned, but
// for integer problems tasks may have hit the time limit and
// returned non-optimal solutions.
let n = r.len();
if n == 0 {
println!("All optimizers failed.");
}
else if numintvar > 0 {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
ii.iter().zip(tasks.iter()).enumerate()
.filter_map(|(k,(_i,t))|
match (*t).solution_def(Soltype::ITG) {
Ok(true) => match t.get_sol_sta(Soltype::ITG).unwrap() {
Solsta::PRIM_FEAS|Solsta::INTEGER_OPTIMAL => Some((k,t.get_primal_obj(Soltype::ITG).unwrap())),
_ => None
},
_ => None
})
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
else {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
tasks.iter().enumerate()
.filter_map(|(k,t)|
match t.get_sol_sta(Soltype::BAS) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::BAS).unwrap())),
_ => None
}.or_else(|| match t.get_sol_sta(Soltype::ITR) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::ITR).unwrap())),
_ => None
}))
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
Result::Ok(())
}examples/portfolio_5_card.rs (line 168)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}examples/milo1.rs (line 91)
13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126
fn main() -> Result<(),String> {
let numcon : i32 = 2;
let numvar : i32 = 2;
let infinity = 0.0; // only for symbolic purposes, value never used
let bkc = vec![Boundkey::UP, Boundkey::LO];
let blc = vec![ -infinity, -4.0 ];
let buc = vec![ 250.0, infinity ];
let bkx = vec![ Boundkey::LO, Boundkey::LO ];
let blx = vec![ 0.0, 0.0 ];
let bux = vec![ infinity, infinity ];
let c = vec![1.0, 0.64];
let asub = vec![0, 1,
0, 1];
let aval = vec![50.0, 3.0, 31.0, -2.0];
let ptrb : Vec<usize> = vec![ 0, 2 ];
let ptre : Vec<usize> = vec![ 2, 4 ];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| task.with_itg_sol_callback(
&mut |xx| { println!("Found a new solution = {:?}",xx); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
for ((((j,cj),bk),bl),bu) in (0..numvar).zip(c.iter()).zip(bkx.iter()).zip(blx.iter()).zip(bux.iter()) {
/* Set the linear term c_j in the objective.*/
task.put_c_j(j, *cj)?;
/* Set the bounds on variable j.
blx[j] <= x_j <= bux[j] */
task.put_var_bound(j, *bk, *bl, *bu)?;
/* Input column j of A */
task.put_a_col(j, /* Variable (column) index.*/
&asub[ptrb[j as usize]..ptre[j as usize]], /* Row index of non-zeros in column j.*/
&aval[ptrb[j as usize]..ptre[j as usize]])?; /* Non-zero Values of column j. */
}
// Set the bounds on constraints.
// for i=1, ...,numcon : blc[i] <= constraint i <= buc[i]
for (((i,bk),bl),bu) in (0..numcon).zip(bkc.iter()).zip(blc.iter()).zip(buc.iter()) {
task.put_con_bound(i, *bk, *bl, *bu)?;
}
/* Specify integer variables. */
for j in 0..numvar {
task.put_var_type(j, Variabletype::TYPE_INT)?;
}
/* Set max solution time */
task.put_dou_param(Dparam::MIO_MAX_TIME, 60.0)?;
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITG, xx.as_mut_slice())?;
/* Get status information about the solution */
match task.get_sol_sta(Soltype::ITG)? {
Solsta::INTEGER_OPTIMAL => {
println!("Optimal solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::PRIM_FEAS => {
println!("Feasible solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::UNKNOWN => {
match task.get_pro_sta(Soltype::ITG)? {
Prosta::PRIM_INFEAS_OR_UNBOUNDED => {
println!("Problem status Infeasible or unbounded");
}
Prosta::PRIM_INFEAS => {
println!("Problem status Infeasible.");
}
Prosta::UNKNOWN => {
println!("Problem status unknown.");
}
_ => {
println!("Other problem status.");
}
}
}
_ => {
println!("Other solution status");
}
}
Ok(())
}))
}sourcepub fn get_solution(
&self,
whichsol_: i32,
problemsta_: &mut i32,
solutionsta_: &mut i32,
skc_: &mut [i32],
skx_: &mut [i32],
skn_: &mut [i32],
xc_: &mut [f64],
xx_: &mut [f64],
y_: &mut [f64],
slc_: &mut [f64],
suc_: &mut [f64],
slx_: &mut [f64],
sux_: &mut [f64],
snx_: &mut [f64]
) -> Result<(), String>
pub fn get_solution( &self, whichsol_: i32, problemsta_: &mut i32, solutionsta_: &mut i32, skc_: &mut [i32], skx_: &mut [i32], skn_: &mut [i32], xc_: &mut [f64], xx_: &mut [f64], y_: &mut [f64], slc_: &mut [f64], suc_: &mut [f64], slx_: &mut [f64], sux_: &mut [f64], snx_: &mut [f64] ) -> Result<(), String>
Obtains the complete solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
problemsta_Problem status.See Prosta
-
solutionsta_Solution status.See Solsta
-
skc_Status keys for the constraints.See Stakey
-
skx_Status keys for the variables.See Stakey
-
skn_Status keys for the conic constraints.See Stakey
-
xc_Primal constraint solution. -
xx_Primal variable solution. -
y_Vector of dual variables corresponding to the constraints. -
slc_Dual variables corresponding to the lower bounds on the constraints. -
suc_Dual variables corresponding to the upper bounds on the constraints. -
slx_Dual variables corresponding to the lower bounds on the variables. -
sux_Dual variables corresponding to the upper bounds on the variables. -
snx_Dual variables corresponding to the conic constraints on the variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getsolution
sourcepub fn get_solution_info(
&self,
whichsol_: i32,
pobj_: &mut f64,
pviolcon_: &mut f64,
pviolvar_: &mut f64,
pviolbarvar_: &mut f64,
pviolcone_: &mut f64,
pviolitg_: &mut f64,
dobj_: &mut f64,
dviolcon_: &mut f64,
dviolvar_: &mut f64,
dviolbarvar_: &mut f64,
dviolcone_: &mut f64
) -> Result<(), String>
pub fn get_solution_info( &self, whichsol_: i32, pobj_: &mut f64, pviolcon_: &mut f64, pviolvar_: &mut f64, pviolbarvar_: &mut f64, pviolcone_: &mut f64, pviolitg_: &mut f64, dobj_: &mut f64, dviolcon_: &mut f64, dviolvar_: &mut f64, dviolbarvar_: &mut f64, dviolcone_: &mut f64 ) -> Result<(), String>
Obtains information about of a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
pobj_The primal objective value. -
pviolcon_Maximal primal bound violation for a xc variable. -
pviolvar_Maximal primal bound violation for a xx variable. -
pviolbarvar_Maximal primal bound violation for a barx variable. -
pviolcone_Maximal primal violation of the solution with respect to the conic constraints. -
pviolitg_Maximal violation in the integer constraints. -
dobj_Dual objective value. -
dviolcon_Maximal dual bound violation for a xc variable. -
dviolvar_Maximal dual bound violation for a xx variable. -
dviolbarvar_Maximal dual bound violation for a bars variable. -
dviolcone_Maximum violation of the dual solution in the dual conic constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getsolutioninfo
sourcepub fn get_solution_info_new(
&self,
whichsol_: i32,
pobj_: &mut f64,
pviolcon_: &mut f64,
pviolvar_: &mut f64,
pviolbarvar_: &mut f64,
pviolcone_: &mut f64,
pviolacc_: &mut f64,
pvioldjc_: &mut f64,
pviolitg_: &mut f64,
dobj_: &mut f64,
dviolcon_: &mut f64,
dviolvar_: &mut f64,
dviolbarvar_: &mut f64,
dviolcone_: &mut f64,
dviolacc_: &mut f64
) -> Result<(), String>
pub fn get_solution_info_new( &self, whichsol_: i32, pobj_: &mut f64, pviolcon_: &mut f64, pviolvar_: &mut f64, pviolbarvar_: &mut f64, pviolcone_: &mut f64, pviolacc_: &mut f64, pvioldjc_: &mut f64, pviolitg_: &mut f64, dobj_: &mut f64, dviolcon_: &mut f64, dviolvar_: &mut f64, dviolbarvar_: &mut f64, dviolcone_: &mut f64, dviolacc_: &mut f64 ) -> Result<(), String>
Obtains information about of a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
pobj_The primal objective value. -
pviolcon_Maximal primal bound violation for a xc variable. -
pviolvar_Maximal primal bound violation for a xx variable. -
pviolbarvar_Maximal primal bound violation for a barx variable. -
pviolcone_Maximal primal violation of the solution with respect to the conic constraints. -
pviolacc_Maximal primal violation of the solution with respect to the affine conic constraints. -
pvioldjc_Maximal primal violation of the solution with respect to the disjunctive constraints. -
pviolitg_Maximal violation in the integer constraints. -
dobj_Dual objective value. -
dviolcon_Maximal dual bound violation for a xc variable. -
dviolvar_Maximal dual bound violation for a xx variable. -
dviolbarvar_Maximal dual bound violation for a bars variable. -
dviolcone_Maximum violation of the dual solution in the dual conic constraints. -
dviolacc_Maximum violation of the dual solution in the dual affine conic constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getsolutioninfonew
sourcepub fn get_solution_new(
&self,
whichsol_: i32,
problemsta_: &mut i32,
solutionsta_: &mut i32,
skc_: &mut [i32],
skx_: &mut [i32],
skn_: &mut [i32],
xc_: &mut [f64],
xx_: &mut [f64],
y_: &mut [f64],
slc_: &mut [f64],
suc_: &mut [f64],
slx_: &mut [f64],
sux_: &mut [f64],
snx_: &mut [f64],
doty_: &mut [f64]
) -> Result<(), String>
pub fn get_solution_new( &self, whichsol_: i32, problemsta_: &mut i32, solutionsta_: &mut i32, skc_: &mut [i32], skx_: &mut [i32], skn_: &mut [i32], xc_: &mut [f64], xx_: &mut [f64], y_: &mut [f64], slc_: &mut [f64], suc_: &mut [f64], slx_: &mut [f64], sux_: &mut [f64], snx_: &mut [f64], doty_: &mut [f64] ) -> Result<(), String>
Obtains the complete solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
problemsta_Problem status.See Prosta
-
solutionsta_Solution status.See Solsta
-
skc_Status keys for the constraints.See Stakey
-
skx_Status keys for the variables.See Stakey
-
skn_Status keys for the conic constraints.See Stakey
-
xc_Primal constraint solution. -
xx_Primal variable solution. -
y_Vector of dual variables corresponding to the constraints. -
slc_Dual variables corresponding to the lower bounds on the constraints. -
suc_Dual variables corresponding to the upper bounds on the constraints. -
slx_Dual variables corresponding to the lower bounds on the variables. -
sux_Dual variables corresponding to the upper bounds on the variables. -
snx_Dual variables corresponding to the conic constraints on the variables. -
doty_Dual variables corresponding to affine conic constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getsolutionnew
sourcepub fn get_solution_slice(
&self,
whichsol_: i32,
solitem_: i32,
first_: i32,
last_: i32,
values_: &mut [f64]
) -> Result<(), String>
pub fn get_solution_slice( &self, whichsol_: i32, solitem_: i32, first_: i32, last_: i32, values_: &mut [f64] ) -> Result<(), String>
Obtains a slice of the solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
solitem_Which part of the solution is required.See Solitem
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
values_The values of the requested solution elements.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getsolutionslice
sourcepub fn get_sparse_sym_mat(
&self,
idx_: i64,
subi_: &mut [i32],
subj_: &mut [i32],
valij_: &mut [f64]
) -> Result<(), String>
pub fn get_sparse_sym_mat( &self, idx_: i64, subi_: &mut [i32], subj_: &mut [i32], valij_: &mut [f64] ) -> Result<(), String>
Gets a single symmetric matrix from the matrix store.
§Arguments
idx_Index of the matrix to retrieve.subi_Row subscripts of the matrix non-zero elements.subj_Column subscripts of the matrix non-zero elements.valij_Coefficients of the matrix non-zero elements.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getsparsesymmat
sourcepub fn get_str_param(
&self,
param_: i32,
len_: &mut i32
) -> Result<String, String>
pub fn get_str_param( &self, param_: i32, len_: &mut i32 ) -> Result<String, String>
Obtains the value of a string parameter.
§Arguments
-
param_Which parameter.See Sparam
-
len_The length of the parameter value.
§Returns
parvalueIf this is not a null pointer, the parameter value is stored here.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getstrparam
sourcepub fn get_str_param_len(&self, param_: i32) -> Result<i32, String>
pub fn get_str_param_len(&self, param_: i32) -> Result<i32, String>
Obtains the length of a string parameter.
§Arguments
-
param_Which parameter.See Sparam
§Returns
lenThe length of the parameter value.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getstrparamlen
sourcepub fn get_suc(&self, whichsol_: i32, suc_: &mut [f64]) -> Result<(), String>
pub fn get_suc(&self, whichsol_: i32, suc_: &mut [f64]) -> Result<(), String>
Obtains the suc vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
suc_Dual variables corresponding to the upper bounds on the constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getsuc
sourcepub fn get_suc_slice(
&self,
whichsol_: i32,
first_: i32,
last_: i32,
suc_: &mut [f64]
) -> Result<(), String>
pub fn get_suc_slice( &self, whichsol_: i32, first_: i32, last_: i32, suc_: &mut [f64] ) -> Result<(), String>
Obtains a slice of the suc vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
suc_Dual variables corresponding to the upper bounds on the constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getsucslice
sourcepub fn get_sux(&self, whichsol_: i32, sux_: &mut [f64]) -> Result<(), String>
pub fn get_sux(&self, whichsol_: i32, sux_: &mut [f64]) -> Result<(), String>
Obtains the sux vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
sux_Dual variables corresponding to the upper bounds on the variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getsux
sourcepub fn get_sux_slice(
&self,
whichsol_: i32,
first_: i32,
last_: i32,
sux_: &mut [f64]
) -> Result<(), String>
pub fn get_sux_slice( &self, whichsol_: i32, first_: i32, last_: i32, sux_: &mut [f64] ) -> Result<(), String>
Obtains a slice of the sux vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
sux_Dual variables corresponding to the upper bounds on the variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getsuxslice
sourcepub fn get_symb_con(&self, i_: i32, value_: &mut i32) -> Result<String, String>
pub fn get_symb_con(&self, i_: i32, value_: &mut i32) -> Result<String, String>
Obtains a cone type string identifier.
§Arguments
i_Index.value_The corresponding value.
§Returns
nameName of the i’th symbolic constant.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getsymbcon
sourcepub fn get_sym_mat_info(
&self,
idx_: i64,
dim_: &mut i32,
nz_: &mut i64,
mattype_: &mut i32
) -> Result<(), String>
pub fn get_sym_mat_info( &self, idx_: i64, dim_: &mut i32, nz_: &mut i64, mattype_: &mut i32 ) -> Result<(), String>
Obtains information about a matrix from the symmetric matrix storage.
§Arguments
-
idx_Index of the matrix for which information is requested. -
dim_Returns the dimension of the requested matrix. -
nz_Returns the number of non-zeros in the requested matrix. -
mattype_Returns the type of the requested matrix.See Symmattype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getsymmatinfo
sourcepub fn get_task_name(&self) -> Result<String, String>
pub fn get_task_name(&self) -> Result<String, String>
Obtains the task name.
§Returns
tasknameReturns the task name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.gettaskname
sourcepub fn get_task_name_len(&self) -> Result<i32, String>
pub fn get_task_name_len(&self) -> Result<i32, String>
Obtains the length the task name.
§Returns
lenReturns the length of the task name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.gettasknamelen
sourcepub fn get_var_bound(
&self,
i_: i32,
bk_: &mut i32,
bl_: &mut f64,
bu_: &mut f64
) -> Result<(), String>
pub fn get_var_bound( &self, i_: i32, bk_: &mut i32, bl_: &mut f64, bu_: &mut f64 ) -> Result<(), String>
Obtains bound information for one variable.
§Arguments
-
i_Index of the variable for which the bound information should be obtained. -
bk_Bound keys.See Boundkey
-
bl_Values for lower bounds. -
bu_Values for upper bounds.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getvarbound
sourcepub fn get_var_bound_slice(
&self,
first_: i32,
last_: i32,
bk_: &mut [i32],
bl_: &mut [f64],
bu_: &mut [f64]
) -> Result<(), String>
pub fn get_var_bound_slice( &self, first_: i32, last_: i32, bk_: &mut [i32], bl_: &mut [f64], bu_: &mut [f64] ) -> Result<(), String>
Obtains bounds information for a slice of the variables.
§Arguments
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
bk_Bound keys.See Boundkey
-
bl_Values for lower bounds. -
bu_Values for upper bounds.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getvarboundslice
sourcepub fn get_var_name(&self, j_: i32) -> Result<String, String>
pub fn get_var_name(&self, j_: i32) -> Result<String, String>
Obtains the name of a variable.
§Arguments
j_Index of a variable.
§Returns
nameReturns the required name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getvarname
sourcepub fn get_var_name_index(
&self,
somename_: &str,
asgn_: &mut i32
) -> Result<i32, String>
pub fn get_var_name_index( &self, somename_: &str, asgn_: &mut i32 ) -> Result<i32, String>
Checks whether the name has been assigned to any variable.
§Arguments
somename_The name which should be checked.asgn_Is non-zero if the name somename is assigned to a variable.
§Returns
indexIf the name somename is assigned to a variable, then return the index of the variable.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getvarnameindex
sourcepub fn get_var_name_len(&self, i_: i32) -> Result<i32, String>
pub fn get_var_name_len(&self, i_: i32) -> Result<i32, String>
Obtains the length of the name of a variable.
§Arguments
i_Index of a variable.
§Returns
lenReturns the length of the indicated name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getvarnamelen
sourcepub fn get_var_type(&self, j_: i32) -> Result<i32, String>
pub fn get_var_type(&self, j_: i32) -> Result<i32, String>
Gets the variable type of one variable.
§Arguments
j_Index of the variable.
§Returns
vartypeVariable type of variable index j.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getvartype
sourcepub fn get_var_type_list(
&self,
subj_: &[i32],
vartype_: &mut [i32]
) -> Result<(), String>
pub fn get_var_type_list( &self, subj_: &[i32], vartype_: &mut [i32] ) -> Result<(), String>
Obtains the variable type for one or more variables.
§Arguments
-
subj_A list of variable indexes. -
vartype_Returns the variables types corresponding the variable indexes requested.See Variabletype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getvartypelist
sourcepub fn get_xc(&self, whichsol_: i32, xc_: &mut [f64]) -> Result<(), String>
pub fn get_xc(&self, whichsol_: i32, xc_: &mut [f64]) -> Result<(), String>
Obtains the xc vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
xc_Primal constraint solution.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getxc
sourcepub fn get_xc_slice(
&self,
whichsol_: i32,
first_: i32,
last_: i32,
xc_: &mut [f64]
) -> Result<(), String>
pub fn get_xc_slice( &self, whichsol_: i32, first_: i32, last_: i32, xc_: &mut [f64] ) -> Result<(), String>
Obtains a slice of the xc vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
xc_Primal constraint solution.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getxcslice
sourcepub fn get_xx(&self, whichsol_: i32, xx_: &mut [f64]) -> Result<(), String>
pub fn get_xx(&self, whichsol_: i32, xx_: &mut [f64]) -> Result<(), String>
Obtains the xx vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
xx_Primal variable solution.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getxx
Examples found in repository?
examples/helloworld.rs (line 28)
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fn main() -> Result<(),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
task.append_vars(1)?; // 1 variable x
task.put_c_j(0, 1.0)?; // c_0 = 1.0
task.put_var_bound(0, Boundkey::RA, 2.0, 3.0)?; // 2.0 <= x <= 3.0
task.put_obj_sense(Objsense::MINIMIZE)?; // minimize
task.optimize()?; // Optimize
let mut x = vec![0.0; 1];
task.get_xx(Soltype::ITR, x.as_mut_slice())?; // Get solution
println!("Solution x = {}", x[0]); // Print solution
return Result::Ok(());
}More examples
examples/portfolio_2_frontier.rs (line 107)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}examples/ceo1.rs (line 92)
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fn main() -> Result<(),String> {
let numcon = 1;
let numvar = 3;
let bkc = mosek::Boundkey::FX;
let blc = 1.0;
let buc = 1.0;
let bkx = vec![ Boundkey::FR,
Boundkey::FR,
Boundkey::FR ];
let blx = vec![ -INF, -INF, -INF ];
let bux = vec![ INF, INF, INF ];
let c = vec![ 1.0, 1.0, 0.0 ];
let a = vec![ 1.0, 1.0, 1.0 ];
let asub = vec![0, 1, 2];
//let csub = new int[numvar];
//double[] xx = new double[numvar];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|task| task.with_callback(
&mut |caller| { println!("caller = {}",caller); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
/* Define the linear part of the problem */
task.put_c_slice(0, numvar, c.as_slice())?;
task.put_a_row(0, asub.as_slice(), a.as_slice())?;
task.put_con_bound(0, bkc, blc, buc)?;
task.put_var_bound_slice(0, numvar, bkx.as_slice(), blx.as_slice(), bux.as_slice())?;
/* Add a conic constraint */
task.append_afes(3)?;
let afeidxs = vec![0, 1, 2 ];
let b = vec![0.0,0.0,0.0];
let domidx = task.append_primal_exp_cone_domain()?;
task.put_afe_f_row_list(afeidxs.as_slice(),
vec![1,1,1].as_slice(),
vec![0,1,2].as_slice(),
vec![0,1,2].as_slice(),
vec![1.0,1.0,1.0].as_slice())?;
task.append_acc(domidx,afeidxs.as_slice(),b.as_slice())?;
task.put_obj_sense(Objsense::MINIMIZE)?;
println!("optimize");
/* Solve the problem */
task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
/* Get status information about the solution */
let solsta = task.get_sol_sta(Soltype::ITR)?;
assert!(solsta == Solsta::OPTIMAL);
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITR, & mut xx[..])?;
println!("Optimal primal solution");
for j in 0..numvar as usize {
println!("x[{}]: {:.4}",j,xx[j]);
}
Ok(())
}))
}examples/reoptimization.rs (lines 85-86)
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fn main() -> Result<(),String> {
let numcon = 3;
let numvar = 3;
let c = &[1.5, 2.5, 3.0 ];
let bkc = &[ Boundkey::UP,
Boundkey::UP,
Boundkey::UP ];
let blc = &[ -INF,
-INF,
-INF ];
let buc = &[ 100000.0,
50000.0,
60000.0 ];
let bkx = &[ Boundkey::LO,
Boundkey::LO,
Boundkey::LO
];
let blx = &[ 0.0, 0.0, 0.0 ];
let bux = &[ INF,
INF,
INF ];
let asub = &[
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ] ];
let aval = &[
&[ 2.0, 3.0, 2.0 ],
&[ 4.0, 2.0, 3.0 ],
&[ 3.0, 3.0, 2.0 ] ];
let mut task = Task::new().unwrap();
/* Append the constraints. */
task.append_cons(numcon)?;
/* Append the variables. */
task.append_vars(numvar)?;
/* Put C. */
for (j,&cj) in (0..numvar).zip(c.iter()) {
task.put_c_j(j,cj)?;
}
/* Put constraint bounds. */
for (i,&bki,&bli,&bui) in izip!(0..numcon,bkc,blc,buc) {
task.put_con_bound(i, bki, bli, bui)?;
}
/* Put variable bounds. */
for (j,&bki,&bli,&bui) in izip!(0..numvar,bkx,blx,bux) {
task.put_var_bound(j, bki, bli, bui)?;
}
/* Put A. */
if numcon > 0 {
for (j,&asubj,&avalj) in izip!(0..numvar,asub,aval) {
task.put_a_col(j,
asubj,
avalj)?;
}
}
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/****************** Make a change to the A matrix ******************/
task.put_aij(0, 0, 3.0)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/***************** Add a new variable ******************************/
/* Get index of new variable. */
let varidx = task.get_num_var()?;
/* Append a new variable x_3 to the problem */
task.append_vars(1)?;
let numvar = numvar + 1;
/* Set bounds on new varaible */
task.put_var_bound(varidx, Boundkey::LO, 0.0, INF)?;
/* Change objective */
task.put_c_j(varidx, 1.0)?;
/* Put new values in the A matrix */
let acolsub = &[0i32, 2];
let acolval = &[4.0, 1.0];
task.put_a_col(varidx, /* column index */
acolsub,
acolval)?;
/* Change optimizer to simplex free and reoptimize */
task.put_int_param(mosek::Iparam::OPTIMIZER, mosek::Optimizertype::FREE_SIMPLEX)?;
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Add a new constraint ***************************/
/* Get index of new constraint. */
let conidx = task.get_num_con()?;
/* Append a new constraint */
task.append_cons(1)?;
let numcon = numcon + 1;
/* Set bounds on new constraint */
task.put_con_bound(conidx,
Boundkey::UP,
-INF,
30000.0)?;
/* Put new values in the A matrix */
let arowsub = &[0i32, 1, 2, 3 ];
let arowval = &[1.0, 2.0, 1.0, 1.0 ];
task.put_a_row(conidx, /* row index */
arowsub,
arowval)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Change constraint bounds ********************/
let newbkc = &[Boundkey::UP,
Boundkey::UP,
Boundkey::UP,
Boundkey::UP];
let newblc = &[-INF,
-INF,
-INF,
-INF];
let newbuc = &[ 80000.0, 40000.0, 50000.0, 22000.0 ];
task.put_con_bound_slice(0, numcon, newbkc, newblc, newbuc)?;
let _ = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
Ok(())
}examples/milo1.rs (line 87)
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fn main() -> Result<(),String> {
let numcon : i32 = 2;
let numvar : i32 = 2;
let infinity = 0.0; // only for symbolic purposes, value never used
let bkc = vec![Boundkey::UP, Boundkey::LO];
let blc = vec![ -infinity, -4.0 ];
let buc = vec![ 250.0, infinity ];
let bkx = vec![ Boundkey::LO, Boundkey::LO ];
let blx = vec![ 0.0, 0.0 ];
let bux = vec![ infinity, infinity ];
let c = vec![1.0, 0.64];
let asub = vec![0, 1,
0, 1];
let aval = vec![50.0, 3.0, 31.0, -2.0];
let ptrb : Vec<usize> = vec![ 0, 2 ];
let ptre : Vec<usize> = vec![ 2, 4 ];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| task.with_itg_sol_callback(
&mut |xx| { println!("Found a new solution = {:?}",xx); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
for ((((j,cj),bk),bl),bu) in (0..numvar).zip(c.iter()).zip(bkx.iter()).zip(blx.iter()).zip(bux.iter()) {
/* Set the linear term c_j in the objective.*/
task.put_c_j(j, *cj)?;
/* Set the bounds on variable j.
blx[j] <= x_j <= bux[j] */
task.put_var_bound(j, *bk, *bl, *bu)?;
/* Input column j of A */
task.put_a_col(j, /* Variable (column) index.*/
&asub[ptrb[j as usize]..ptre[j as usize]], /* Row index of non-zeros in column j.*/
&aval[ptrb[j as usize]..ptre[j as usize]])?; /* Non-zero Values of column j. */
}
// Set the bounds on constraints.
// for i=1, ...,numcon : blc[i] <= constraint i <= buc[i]
for (((i,bk),bl),bu) in (0..numcon).zip(bkc.iter()).zip(blc.iter()).zip(buc.iter()) {
task.put_con_bound(i, *bk, *bl, *bu)?;
}
/* Specify integer variables. */
for j in 0..numvar {
task.put_var_type(j, Variabletype::TYPE_INT)?;
}
/* Set max solution time */
task.put_dou_param(Dparam::MIO_MAX_TIME, 60.0)?;
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITG, xx.as_mut_slice())?;
/* Get status information about the solution */
match task.get_sol_sta(Soltype::ITG)? {
Solsta::INTEGER_OPTIMAL => {
println!("Optimal solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::PRIM_FEAS => {
println!("Feasible solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::UNKNOWN => {
match task.get_pro_sta(Soltype::ITG)? {
Prosta::PRIM_INFEAS_OR_UNBOUNDED => {
println!("Problem status Infeasible or unbounded");
}
Prosta::PRIM_INFEAS => {
println!("Problem status Infeasible.");
}
Prosta::UNKNOWN => {
println!("Problem status unknown.");
}
_ => {
println!("Other problem status.");
}
}
}
_ => {
println!("Other solution status");
}
}
Ok(())
}))
}sourcepub fn get_xx_slice(
&self,
whichsol_: i32,
first_: i32,
last_: i32,
xx_: &mut [f64]
) -> Result<(), String>
pub fn get_xx_slice( &self, whichsol_: i32, first_: i32, last_: i32, xx_: &mut [f64] ) -> Result<(), String>
Obtains a slice of the xx vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
xx_Primal variable solution.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getxxslice
Examples found in repository?
examples/portfolio_5_card.rs (line 175)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}sourcepub fn get_y(&self, whichsol_: i32, y_: &mut [f64]) -> Result<(), String>
pub fn get_y(&self, whichsol_: i32, y_: &mut [f64]) -> Result<(), String>
Obtains the y vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
y_Vector of dual variables corresponding to the constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.gety
sourcepub fn get_y_slice(
&self,
whichsol_: i32,
first_: i32,
last_: i32,
y_: &mut [f64]
) -> Result<(), String>
pub fn get_y_slice( &self, whichsol_: i32, first_: i32, last_: i32, y_: &mut [f64] ) -> Result<(), String>
Obtains a slice of the y vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
y_Vector of dual variables corresponding to the constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.getyslice
sourcepub fn infeasibility_report(
&mut self,
whichstream_: i32,
whichsol_: i32
) -> Result<(), String>
pub fn infeasibility_report( &mut self, whichstream_: i32, whichsol_: i32 ) -> Result<(), String>
Prints the infeasibility report to an output stream.
§Arguments
-
whichstream_Index of the stream.See Streamtype
-
whichsol_Selects a solution.See Soltype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.infeasibilityreport
sourcepub fn init_basis_solve(&mut self, basis_: &mut [i32]) -> Result<(), String>
pub fn init_basis_solve(&mut self, basis_: &mut [i32]) -> Result<(), String>
Prepare a task for basis solver.
§Arguments
basis_The array of basis indexes to use.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.initbasissolve
Examples found in repository?
examples/solvelinear.rs (line 57)
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fn setup(task : & mut mosek::Task,
aval : &[f64],
asub : &[i32],
ptrb : &[i64],
ptre : &[i64],
numvar : i32) -> Result<Vec<i32>,String> {
// mosek.stakey[] skx = new mosek.stakey [numvar];
// mosek.stakey[] skc = new mosek.stakey [numvar];
// for (int i = 0; i < numvar ; ++i) {
// skx[i] = mosek.stakey.bas;
// skc[i] = mosek.stakey.fix;
// }
task.append_vars(numvar)?;
task.append_cons(numvar)?;
task.put_a_col_slice(0,numvar,ptrb,ptre,asub,aval)?;
task.put_con_bound_slice_const(0,numvar,Boundkey::FX,0.0,0.0)?;
task.put_var_bound_slice_const(0,numvar,Boundkey::FR,-INF,INF)?;
/* Define a basic solution by specifying
status keys for variables & constraints. */
task.delete_solution(Soltype::BAS)?;
task.put_skc_slice(Soltype::BAS, 0, numvar, vec![Stakey::FIX; numvar as usize].as_slice())?;
task.put_skx_slice(Soltype::BAS, 0, numvar, vec![Stakey::BAS; numvar as usize].as_slice())?;
let mut basis = vec![0; numvar as usize];
task.init_basis_solve(basis.as_mut_slice())?;
Ok(basis)
}sourcepub fn input_data(
&mut self,
maxnumcon_: i32,
maxnumvar_: i32,
c_: &[f64],
cfix_: f64,
aptrb_: &[i64],
aptre_: &[i64],
asub_: &[i32],
aval_: &[f64],
bkc_: &[i32],
blc_: &[f64],
buc_: &[f64],
bkx_: &[i32],
blx_: &[f64],
bux_: &[f64]
) -> Result<(), String>
pub fn input_data( &mut self, maxnumcon_: i32, maxnumvar_: i32, c_: &[f64], cfix_: f64, aptrb_: &[i64], aptre_: &[i64], asub_: &[i32], aval_: &[f64], bkc_: &[i32], blc_: &[f64], buc_: &[f64], bkx_: &[i32], blx_: &[f64], bux_: &[f64] ) -> Result<(), String>
Input the linear part of an optimization task in one function call.
§Arguments
-
maxnumcon_Number of preallocated constraints in the optimization task. -
maxnumvar_Number of preallocated variables in the optimization task. -
c_Linear terms of the objective as a dense vector. The length is the number of variables. -
cfix_Fixed term in the objective. -
aptrb_Row or column start pointers. -
aptre_Row or column end pointers. -
asub_Coefficient subscripts. -
aval_Coefficient values. -
bkc_Bound keys for the constraints.See Boundkey
-
blc_Lower bounds for the constraints. -
buc_Upper bounds for the constraints. -
bkx_Bound keys for the variables.See Boundkey
-
blx_Lower bounds for the variables. -
bux_Upper bounds for the variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.inputdata64
sourcepub fn is_dou_par_name(
&self,
parname_: &str,
param_: &mut i32
) -> Result<(), String>
pub fn is_dou_par_name( &self, parname_: &str, param_: &mut i32 ) -> Result<(), String>
Checks a double parameter name.
§Arguments
-
parname_Parameter name. -
param_Returns the parameter corresponding to the name, if one exists.See Dparam
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.isdouparname
sourcepub fn is_int_par_name(
&self,
parname_: &str,
param_: &mut i32
) -> Result<(), String>
pub fn is_int_par_name( &self, parname_: &str, param_: &mut i32 ) -> Result<(), String>
Checks an integer parameter name.
§Arguments
-
parname_Parameter name. -
param_Returns the parameter corresponding to the name, if one exists.See Iparam
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.isintparname
sourcepub fn is_str_par_name(
&self,
parname_: &str,
param_: &mut i32
) -> Result<(), String>
pub fn is_str_par_name( &self, parname_: &str, param_: &mut i32 ) -> Result<(), String>
Checks a string parameter name.
§Arguments
-
parname_Parameter name. -
param_Returns the parameter corresponding to the name, if one exists.See Sparam
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.isstrparname
sourcepub fn link_file_to_stream(
&mut self,
whichstream_: i32,
filename_: &str,
append_: i32
) -> Result<(), String>
pub fn link_file_to_stream( &mut self, whichstream_: i32, filename_: &str, append_: i32 ) -> Result<(), String>
Directs all output from a task stream to a file.
§Arguments
-
whichstream_Index of the stream.See Streamtype
-
filename_A valid file name. -
append_If this argument is 0 the output file will be overwritten, otherwise it will be appended to.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.linkfiletotaskstream
sourcepub fn one_solution_summary(
&self,
whichstream_: i32,
whichsol_: i32
) -> Result<(), String>
pub fn one_solution_summary( &self, whichstream_: i32, whichsol_: i32 ) -> Result<(), String>
Prints a short summary of a specified solution.
§Arguments
-
whichstream_Index of the stream.See Streamtype
-
whichsol_Selects a solution.See Soltype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.onesolutionsummary
sourcepub fn optimize_rmt(
&mut self,
address_: &str,
accesstoken_: &str,
trmcode_: &mut i32
) -> Result<(), String>
pub fn optimize_rmt( &mut self, address_: &str, accesstoken_: &str, trmcode_: &mut i32 ) -> Result<(), String>
Offload the optimization task to a solver server and wait for the solution.
§Arguments
-
address_Address of the OptServer. -
accesstoken_Access token. -
trmcode_Is either OK or a termination response code.See Rescode
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.optimizermt
sourcepub fn optimizer_summary(&self, whichstream_: i32) -> Result<(), String>
pub fn optimizer_summary(&self, whichstream_: i32) -> Result<(), String>
Prints a short summary with optimizer statistics from last optimization.
§Arguments
-
whichstream_Index of the stream.See Streamtype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.optimizersummary
Examples found in repository?
examples/concurrent1.rs (line 167)
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fn concurrent1(data : FileOrText, timelimit : Option<String>) -> Result<(),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
match data {
FileOrText::File(fname) => task.read_data(fname.as_str())?,
FileOrText::Text(text) => task.read_ptf_string(text.as_str())?
}
if let Some(timelimit) = timelimit {
task.put_dou_param(mosek::Dparam::OPTIMIZER_MAX_TIME, timelimit.parse().unwrap())?;
}
let numintvar = task.get_num_int_var()?;
let r = if numintvar == 0 {
let optimizers = &[mosek::Optimizertype::CONIC,
mosek::Optimizertype::DUAL_SIMPLEX,
mosek::Optimizertype::PRIMAL_SIMPLEX];
optimize_concurrent(& mut task, optimizers)
}
else {
let seeds = &[ 42, 13, 71749373 ];
optimize_concurrent_mio(& mut task, seeds)
};
let sense = task.get_obj_sense()?;
// Pick the feasible result. For non-integer problems all
// solutions should be the same if more than one is returned, but
// for integer problems tasks may have hit the time limit and
// returned non-optimal solutions.
let n = r.len();
if n == 0 {
println!("All optimizers failed.");
}
else if numintvar > 0 {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
ii.iter().zip(tasks.iter()).enumerate()
.filter_map(|(k,(_i,t))|
match (*t).solution_def(Soltype::ITG) {
Ok(true) => match t.get_sol_sta(Soltype::ITG).unwrap() {
Solsta::PRIM_FEAS|Solsta::INTEGER_OPTIMAL => Some((k,t.get_primal_obj(Soltype::ITG).unwrap())),
_ => None
},
_ => None
})
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
else {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
tasks.iter().enumerate()
.filter_map(|(k,t)|
match t.get_sol_sta(Soltype::BAS) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::BAS).unwrap())),
_ => None
}.or_else(|| match t.get_sol_sta(Soltype::ITR) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::ITR).unwrap())),
_ => None
}))
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
Result::Ok(())
}sourcepub fn optimize(&mut self) -> Result<i32, String>
pub fn optimize(&mut self) -> Result<i32, String>
Optimizes the problem.
§Returns
trmcodeIs either OK or a termination response code.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.optimizetrm
Examples found in repository?
examples/concurrent1.rs (line 28)
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fn optimize(mut t : mosek::Task, stop : Arc<Mutex<bool>>) -> Option<(i32,mosek::Task)> {
let cbstop = Arc::clone(&stop);
if let Some(trm) = t.with_callback(
&mut |_| cbstop.lock().and_then(|p| Ok(*p)).unwrap_or(false),
|task|
if let Ok(trm) = task.optimize() {
let mut st = stop.lock().unwrap();
*st = true;
Some(trm)
} else {
None
}) {
Some((trm,t))
}
else {
None
}
}More examples
examples/helloworld.rs (line 25)
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fn main() -> Result<(),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
task.append_vars(1)?; // 1 variable x
task.put_c_j(0, 1.0)?; // c_0 = 1.0
task.put_var_bound(0, Boundkey::RA, 2.0, 3.0)?; // 2.0 <= x <= 3.0
task.put_obj_sense(Objsense::MINIMIZE)?; // minimize
task.optimize()?; // Optimize
let mut x = vec![0.0; 1];
task.get_xx(Soltype::ITR, x.as_mut_slice())?; // Get solution
println!("Solution x = {}", x[0]); // Print solution
return Result::Ok(());
}examples/callback.rs (line 132)
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fn callbackmain(which : &str, data : FileOrText) -> Result<(),String> {
/* Create the optimization task. */
let mut task = Task::new().unwrap();
match data {
FileOrText::Text(data) => { task.read_ptf_string(data)? },
FileOrText::File(fname) => { task.read_data(fname)? }
}
task.write_data("callback.ptf")?;
match which {
"psim" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::PRIMAL_SIMPLEX)?,
"dsim" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::DUAL_SIMPLEX)?,
"intpnt" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::INTPNT)?,
s => return Err(format!("Invalid argument '{}'",s))
}
/* Directs the log task stream to the 'printstr' function. */
task.with_stream_callback(
Streamtype::LOG,
& mut |msg| print!("{}",msg),
|task|
task.with_info_callback(
& mut callback,
|task|
task.optimize()
)
)?;
Result::Ok(())
}examples/portfolio_2_frontier.rs (line 100)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}examples/ceo1.rs (line 81)
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fn main() -> Result<(),String> {
let numcon = 1;
let numvar = 3;
let bkc = mosek::Boundkey::FX;
let blc = 1.0;
let buc = 1.0;
let bkx = vec![ Boundkey::FR,
Boundkey::FR,
Boundkey::FR ];
let blx = vec![ -INF, -INF, -INF ];
let bux = vec![ INF, INF, INF ];
let c = vec![ 1.0, 1.0, 0.0 ];
let a = vec![ 1.0, 1.0, 1.0 ];
let asub = vec![0, 1, 2];
//let csub = new int[numvar];
//double[] xx = new double[numvar];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|task| task.with_callback(
&mut |caller| { println!("caller = {}",caller); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
/* Define the linear part of the problem */
task.put_c_slice(0, numvar, c.as_slice())?;
task.put_a_row(0, asub.as_slice(), a.as_slice())?;
task.put_con_bound(0, bkc, blc, buc)?;
task.put_var_bound_slice(0, numvar, bkx.as_slice(), blx.as_slice(), bux.as_slice())?;
/* Add a conic constraint */
task.append_afes(3)?;
let afeidxs = vec![0, 1, 2 ];
let b = vec![0.0,0.0,0.0];
let domidx = task.append_primal_exp_cone_domain()?;
task.put_afe_f_row_list(afeidxs.as_slice(),
vec![1,1,1].as_slice(),
vec![0,1,2].as_slice(),
vec![0,1,2].as_slice(),
vec![1.0,1.0,1.0].as_slice())?;
task.append_acc(domidx,afeidxs.as_slice(),b.as_slice())?;
task.put_obj_sense(Objsense::MINIMIZE)?;
println!("optimize");
/* Solve the problem */
task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
/* Get status information about the solution */
let solsta = task.get_sol_sta(Soltype::ITR)?;
assert!(solsta == Solsta::OPTIMAL);
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITR, & mut xx[..])?;
println!("Optimal primal solution");
for j in 0..numvar as usize {
println!("x[{}]: {:.4}",j,xx[j]);
}
Ok(())
}))
}examples/reoptimization.rs (line 82)
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fn main() -> Result<(),String> {
let numcon = 3;
let numvar = 3;
let c = &[1.5, 2.5, 3.0 ];
let bkc = &[ Boundkey::UP,
Boundkey::UP,
Boundkey::UP ];
let blc = &[ -INF,
-INF,
-INF ];
let buc = &[ 100000.0,
50000.0,
60000.0 ];
let bkx = &[ Boundkey::LO,
Boundkey::LO,
Boundkey::LO
];
let blx = &[ 0.0, 0.0, 0.0 ];
let bux = &[ INF,
INF,
INF ];
let asub = &[
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ] ];
let aval = &[
&[ 2.0, 3.0, 2.0 ],
&[ 4.0, 2.0, 3.0 ],
&[ 3.0, 3.0, 2.0 ] ];
let mut task = Task::new().unwrap();
/* Append the constraints. */
task.append_cons(numcon)?;
/* Append the variables. */
task.append_vars(numvar)?;
/* Put C. */
for (j,&cj) in (0..numvar).zip(c.iter()) {
task.put_c_j(j,cj)?;
}
/* Put constraint bounds. */
for (i,&bki,&bli,&bui) in izip!(0..numcon,bkc,blc,buc) {
task.put_con_bound(i, bki, bli, bui)?;
}
/* Put variable bounds. */
for (j,&bki,&bli,&bui) in izip!(0..numvar,bkx,blx,bux) {
task.put_var_bound(j, bki, bli, bui)?;
}
/* Put A. */
if numcon > 0 {
for (j,&asubj,&avalj) in izip!(0..numvar,asub,aval) {
task.put_a_col(j,
asubj,
avalj)?;
}
}
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/****************** Make a change to the A matrix ******************/
task.put_aij(0, 0, 3.0)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/***************** Add a new variable ******************************/
/* Get index of new variable. */
let varidx = task.get_num_var()?;
/* Append a new variable x_3 to the problem */
task.append_vars(1)?;
let numvar = numvar + 1;
/* Set bounds on new varaible */
task.put_var_bound(varidx, Boundkey::LO, 0.0, INF)?;
/* Change objective */
task.put_c_j(varidx, 1.0)?;
/* Put new values in the A matrix */
let acolsub = &[0i32, 2];
let acolval = &[4.0, 1.0];
task.put_a_col(varidx, /* column index */
acolsub,
acolval)?;
/* Change optimizer to simplex free and reoptimize */
task.put_int_param(mosek::Iparam::OPTIMIZER, mosek::Optimizertype::FREE_SIMPLEX)?;
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Add a new constraint ***************************/
/* Get index of new constraint. */
let conidx = task.get_num_con()?;
/* Append a new constraint */
task.append_cons(1)?;
let numcon = numcon + 1;
/* Set bounds on new constraint */
task.put_con_bound(conidx,
Boundkey::UP,
-INF,
30000.0)?;
/* Put new values in the A matrix */
let arowsub = &[0i32, 1, 2, 3 ];
let arowval = &[1.0, 2.0, 1.0, 1.0 ];
task.put_a_row(conidx, /* row index */
arowsub,
arowval)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Change constraint bounds ********************/
let newbkc = &[Boundkey::UP,
Boundkey::UP,
Boundkey::UP,
Boundkey::UP];
let newblc = &[-INF,
-INF,
-INF,
-INF];
let newbuc = &[ 80000.0, 40000.0, 50000.0, 22000.0 ];
task.put_con_bound_slice(0, numcon, newbkc, newblc, newbuc)?;
let _ = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
Ok(())
}Additional examples can be found in:
sourcepub fn primal_repair(
&mut self,
wlc_: &[f64],
wuc_: &[f64],
wlx_: &[f64],
wux_: &[f64]
) -> Result<(), String>
pub fn primal_repair( &mut self, wlc_: &[f64], wuc_: &[f64], wlx_: &[f64], wux_: &[f64] ) -> Result<(), String>
Repairs a primal infeasible optimization problem by adjusting the bounds on the constraints and variables.
§Arguments
wlc_Weights associated with relaxing lower bounds on the constraints.wuc_Weights associated with relaxing the upper bound on the constraints.wlx_Weights associated with relaxing the lower bounds of the variables.wux_Weights associated with relaxing the upper bounds of variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.primalrepair
sourcepub fn primal_sensitivity(
&mut self,
subi_: &[i32],
marki_: &[i32],
subj_: &[i32],
markj_: &[i32],
leftpricei_: &mut [f64],
rightpricei_: &mut [f64],
leftrangei_: &mut [f64],
rightrangei_: &mut [f64],
leftpricej_: &mut [f64],
rightpricej_: &mut [f64],
leftrangej_: &mut [f64],
rightrangej_: &mut [f64]
) -> Result<(), String>
pub fn primal_sensitivity( &mut self, subi_: &[i32], marki_: &[i32], subj_: &[i32], markj_: &[i32], leftpricei_: &mut [f64], rightpricei_: &mut [f64], leftrangei_: &mut [f64], rightrangei_: &mut [f64], leftpricej_: &mut [f64], rightpricej_: &mut [f64], leftrangej_: &mut [f64], rightrangej_: &mut [f64] ) -> Result<(), String>
Perform sensitivity analysis on bounds.
§Arguments
-
subi_Indexes of constraints to analyze. -
marki_Mark which constraint bounds to analyze.See Mark
-
subj_Indexes of variables to analyze. -
markj_Mark which variable bounds to analyze.See Mark
-
leftpricei_Left shadow price for constraints. -
rightpricei_Right shadow price for constraints. -
leftrangei_Left range for constraints. -
rightrangei_Right range for constraints. -
leftpricej_Left shadow price for variables. -
rightpricej_Right shadow price for variables. -
leftrangej_Left range for variables. -
rightrangej_Right range for variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.primalsensitivity
sourcepub fn print_param(&self) -> Result<(), String>
pub fn print_param(&self) -> Result<(), String>
Prints the current parameter settings.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.printparam
sourcepub fn put_acc(
&mut self,
accidx_: i64,
domidx_: i64,
afeidxlist_: &[i64],
b_: &[f64]
) -> Result<(), String>
pub fn put_acc( &mut self, accidx_: i64, domidx_: i64, afeidxlist_: &[i64], b_: &[f64] ) -> Result<(), String>
Puts an affine conic constraint.
§Arguments
accidx_Affine conic constraint index.domidx_Domain index.afeidxlist_List of affine expression indexes.b_The vector of constant terms modifying affine expressions. Optional.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putacc
sourcepub fn put_acc_b(&mut self, accidx_: i64, b_: &[f64]) -> Result<(), String>
pub fn put_acc_b(&mut self, accidx_: i64, b_: &[f64]) -> Result<(), String>
Puts the constant vector b in an affine conic constraint.
§Arguments
accidx_Affine conic constraint index.b_The vector of constant terms modifying affine expressions. Optional.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putaccb
sourcepub fn put_acc_b_j(
&mut self,
accidx_: i64,
j_: i64,
bj_: f64
) -> Result<(), String>
pub fn put_acc_b_j( &mut self, accidx_: i64, j_: i64, bj_: f64 ) -> Result<(), String>
Sets one element in the b vector of an affine conic constraint.
§Arguments
accidx_Affine conic constraint index.j_The index of an element in b to change.bj_The new value of b[j].
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putaccbj
sourcepub fn put_acc_dot_y(
&self,
whichsol_: i32,
accidx_: i64,
doty_: &mut [f64]
) -> Result<(), String>
pub fn put_acc_dot_y( &self, whichsol_: i32, accidx_: i64, doty_: &mut [f64] ) -> Result<(), String>
Puts the doty vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
accidx_The index of the affine conic constraint. -
doty_The dual values for this affine conic constraint. The array should have length equal to the dimension of the constraint.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putaccdoty
sourcepub fn put_acc_list(
&mut self,
accidxs_: &[i64],
domidxs_: &[i64],
afeidxlist_: &[i64],
b_: &[f64]
) -> Result<(), String>
pub fn put_acc_list( &mut self, accidxs_: &[i64], domidxs_: &[i64], afeidxlist_: &[i64], b_: &[f64] ) -> Result<(), String>
Puts a number of affine conic constraints.
§Arguments
accidxs_Affine conic constraint indices.domidxs_Domain indices.afeidxlist_List of affine expression indexes.b_The vector of constant terms modifying affine expressions. Optional.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putacclist
sourcepub fn put_acc_name(&mut self, accidx_: i64, name_: &str) -> Result<(), String>
pub fn put_acc_name(&mut self, accidx_: i64, name_: &str) -> Result<(), String>
Sets the name of an affine conic constraint.
§Arguments
accidx_Index of the affine conic constraint.name_The name of the affine conic constraint.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putaccname
Examples found in repository?
examples/portfolio_2_frontier.rs (line 88)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}More examples
examples/portfolio_5_card.rs (line 141)
46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177
fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}sourcepub fn put_a_col(
&mut self,
j_: i32,
subj_: &[i32],
valj_: &[f64]
) -> Result<(), String>
pub fn put_a_col( &mut self, j_: i32, subj_: &[i32], valj_: &[f64] ) -> Result<(), String>
Replaces all elements in one column of the linear constraint matrix.
§Arguments
j_Column index.subj_Row indexes of non-zero values in column.valj_New non-zero values of column.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putacol
Examples found in repository?
examples/reoptimization.rs (lines 73-75)
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fn main() -> Result<(),String> {
let numcon = 3;
let numvar = 3;
let c = &[1.5, 2.5, 3.0 ];
let bkc = &[ Boundkey::UP,
Boundkey::UP,
Boundkey::UP ];
let blc = &[ -INF,
-INF,
-INF ];
let buc = &[ 100000.0,
50000.0,
60000.0 ];
let bkx = &[ Boundkey::LO,
Boundkey::LO,
Boundkey::LO
];
let blx = &[ 0.0, 0.0, 0.0 ];
let bux = &[ INF,
INF,
INF ];
let asub = &[
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ] ];
let aval = &[
&[ 2.0, 3.0, 2.0 ],
&[ 4.0, 2.0, 3.0 ],
&[ 3.0, 3.0, 2.0 ] ];
let mut task = Task::new().unwrap();
/* Append the constraints. */
task.append_cons(numcon)?;
/* Append the variables. */
task.append_vars(numvar)?;
/* Put C. */
for (j,&cj) in (0..numvar).zip(c.iter()) {
task.put_c_j(j,cj)?;
}
/* Put constraint bounds. */
for (i,&bki,&bli,&bui) in izip!(0..numcon,bkc,blc,buc) {
task.put_con_bound(i, bki, bli, bui)?;
}
/* Put variable bounds. */
for (j,&bki,&bli,&bui) in izip!(0..numvar,bkx,blx,bux) {
task.put_var_bound(j, bki, bli, bui)?;
}
/* Put A. */
if numcon > 0 {
for (j,&asubj,&avalj) in izip!(0..numvar,asub,aval) {
task.put_a_col(j,
asubj,
avalj)?;
}
}
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/****************** Make a change to the A matrix ******************/
task.put_aij(0, 0, 3.0)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/***************** Add a new variable ******************************/
/* Get index of new variable. */
let varidx = task.get_num_var()?;
/* Append a new variable x_3 to the problem */
task.append_vars(1)?;
let numvar = numvar + 1;
/* Set bounds on new varaible */
task.put_var_bound(varidx, Boundkey::LO, 0.0, INF)?;
/* Change objective */
task.put_c_j(varidx, 1.0)?;
/* Put new values in the A matrix */
let acolsub = &[0i32, 2];
let acolval = &[4.0, 1.0];
task.put_a_col(varidx, /* column index */
acolsub,
acolval)?;
/* Change optimizer to simplex free and reoptimize */
task.put_int_param(mosek::Iparam::OPTIMIZER, mosek::Optimizertype::FREE_SIMPLEX)?;
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Add a new constraint ***************************/
/* Get index of new constraint. */
let conidx = task.get_num_con()?;
/* Append a new constraint */
task.append_cons(1)?;
let numcon = numcon + 1;
/* Set bounds on new constraint */
task.put_con_bound(conidx,
Boundkey::UP,
-INF,
30000.0)?;
/* Put new values in the A matrix */
let arowsub = &[0i32, 1, 2, 3 ];
let arowval = &[1.0, 2.0, 1.0, 1.0 ];
task.put_a_row(conidx, /* row index */
arowsub,
arowval)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Change constraint bounds ********************/
let newbkc = &[Boundkey::UP,
Boundkey::UP,
Boundkey::UP,
Boundkey::UP];
let newblc = &[-INF,
-INF,
-INF,
-INF];
let newbuc = &[ 80000.0, 40000.0, 50000.0, 22000.0 ];
task.put_con_bound_slice(0, numcon, newbkc, newblc, newbuc)?;
let _ = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
Ok(())
}More examples
examples/milo1.rs (lines 59-61)
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fn main() -> Result<(),String> {
let numcon : i32 = 2;
let numvar : i32 = 2;
let infinity = 0.0; // only for symbolic purposes, value never used
let bkc = vec![Boundkey::UP, Boundkey::LO];
let blc = vec![ -infinity, -4.0 ];
let buc = vec![ 250.0, infinity ];
let bkx = vec![ Boundkey::LO, Boundkey::LO ];
let blx = vec![ 0.0, 0.0 ];
let bux = vec![ infinity, infinity ];
let c = vec![1.0, 0.64];
let asub = vec![0, 1,
0, 1];
let aval = vec![50.0, 3.0, 31.0, -2.0];
let ptrb : Vec<usize> = vec![ 0, 2 ];
let ptre : Vec<usize> = vec![ 2, 4 ];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| task.with_itg_sol_callback(
&mut |xx| { println!("Found a new solution = {:?}",xx); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
for ((((j,cj),bk),bl),bu) in (0..numvar).zip(c.iter()).zip(bkx.iter()).zip(blx.iter()).zip(bux.iter()) {
/* Set the linear term c_j in the objective.*/
task.put_c_j(j, *cj)?;
/* Set the bounds on variable j.
blx[j] <= x_j <= bux[j] */
task.put_var_bound(j, *bk, *bl, *bu)?;
/* Input column j of A */
task.put_a_col(j, /* Variable (column) index.*/
&asub[ptrb[j as usize]..ptre[j as usize]], /* Row index of non-zeros in column j.*/
&aval[ptrb[j as usize]..ptre[j as usize]])?; /* Non-zero Values of column j. */
}
// Set the bounds on constraints.
// for i=1, ...,numcon : blc[i] <= constraint i <= buc[i]
for (((i,bk),bl),bu) in (0..numcon).zip(bkc.iter()).zip(blc.iter()).zip(buc.iter()) {
task.put_con_bound(i, *bk, *bl, *bu)?;
}
/* Specify integer variables. */
for j in 0..numvar {
task.put_var_type(j, Variabletype::TYPE_INT)?;
}
/* Set max solution time */
task.put_dou_param(Dparam::MIO_MAX_TIME, 60.0)?;
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITG, xx.as_mut_slice())?;
/* Get status information about the solution */
match task.get_sol_sta(Soltype::ITG)? {
Solsta::INTEGER_OPTIMAL => {
println!("Optimal solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::PRIM_FEAS => {
println!("Feasible solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::UNKNOWN => {
match task.get_pro_sta(Soltype::ITG)? {
Prosta::PRIM_INFEAS_OR_UNBOUNDED => {
println!("Problem status Infeasible or unbounded");
}
Prosta::PRIM_INFEAS => {
println!("Problem status Infeasible.");
}
Prosta::UNKNOWN => {
println!("Problem status unknown.");
}
_ => {
println!("Other problem status.");
}
}
}
_ => {
println!("Other solution status");
}
}
Ok(())
}))
}sourcepub fn put_a_col_list(
&mut self,
sub_: &[i32],
ptrb_: &[i64],
ptre_: &[i64],
asub_: &[i32],
aval_: &[f64]
) -> Result<(), String>
pub fn put_a_col_list( &mut self, sub_: &[i32], ptrb_: &[i64], ptre_: &[i64], asub_: &[i32], aval_: &[f64] ) -> Result<(), String>
Replaces all elements in several columns the linear constraint matrix.
§Arguments
sub_Indexes of columns that should be replaced.ptrb_Array of pointers to the first element in the columns.ptre_Array of pointers to the last element plus one in the columns.asub_Row indexesaval_Coefficient values.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putacollist64
sourcepub fn put_a_col_slice(
&mut self,
first_: i32,
last_: i32,
ptrb_: &[i64],
ptre_: &[i64],
asub_: &[i32],
aval_: &[f64]
) -> Result<(), String>
pub fn put_a_col_slice( &mut self, first_: i32, last_: i32, ptrb_: &[i64], ptre_: &[i64], asub_: &[i32], aval_: &[f64] ) -> Result<(), String>
Replaces all elements in a sequence of columns the linear constraint matrix.
§Arguments
first_First column in the slice.last_Last column plus one in the slice.ptrb_Array of pointers to the first element in the columns.ptre_Array of pointers to the last element plus one in the columns.asub_Row indexesaval_Coefficient values.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putacolslice64
Examples found in repository?
examples/solvelinear.rs (line 44)
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fn setup(task : & mut mosek::Task,
aval : &[f64],
asub : &[i32],
ptrb : &[i64],
ptre : &[i64],
numvar : i32) -> Result<Vec<i32>,String> {
// mosek.stakey[] skx = new mosek.stakey [numvar];
// mosek.stakey[] skc = new mosek.stakey [numvar];
// for (int i = 0; i < numvar ; ++i) {
// skx[i] = mosek.stakey.bas;
// skc[i] = mosek.stakey.fix;
// }
task.append_vars(numvar)?;
task.append_cons(numvar)?;
task.put_a_col_slice(0,numvar,ptrb,ptre,asub,aval)?;
task.put_con_bound_slice_const(0,numvar,Boundkey::FX,0.0,0.0)?;
task.put_var_bound_slice_const(0,numvar,Boundkey::FR,-INF,INF)?;
/* Define a basic solution by specifying
status keys for variables & constraints. */
task.delete_solution(Soltype::BAS)?;
task.put_skc_slice(Soltype::BAS, 0, numvar, vec![Stakey::FIX; numvar as usize].as_slice())?;
task.put_skx_slice(Soltype::BAS, 0, numvar, vec![Stakey::BAS; numvar as usize].as_slice())?;
let mut basis = vec![0; numvar as usize];
task.init_basis_solve(basis.as_mut_slice())?;
Ok(basis)
}sourcepub fn put_afe_barf_block_triplet(
&mut self,
afeidx_: &[i64],
barvaridx_: &[i32],
subk_: &[i32],
subl_: &[i32],
valkl_: &[f64]
) -> Result<(), String>
pub fn put_afe_barf_block_triplet( &mut self, afeidx_: &[i64], barvaridx_: &[i32], subk_: &[i32], subl_: &[i32], valkl_: &[f64] ) -> Result<(), String>
Inputs barF in block triplet form.
§Arguments
afeidx_Constraint index.barvaridx_Symmetric matrix variable index.subk_Block row index.subl_Block column index.valkl_The numerical value associated with each block triplet.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putafebarfblocktriplet
sourcepub fn put_afe_barf_entry(
&mut self,
afeidx_: i64,
barvaridx_: i32,
termidx_: &[i64],
termweight_: &[f64]
) -> Result<(), String>
pub fn put_afe_barf_entry( &mut self, afeidx_: i64, barvaridx_: i32, termidx_: &[i64], termweight_: &[f64] ) -> Result<(), String>
Inputs one entry in barF.
§Arguments
afeidx_Row index of barF.barvaridx_Semidefinite variable index.termidx_Element indices in matrix storage.termweight_Weights in the weighted sum.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putafebarfentry
sourcepub fn put_afe_barf_entry_list(
&mut self,
afeidx_: &[i64],
barvaridx_: &[i32],
numterm_: &[i64],
ptrterm_: &[i64],
termidx_: &[i64],
termweight_: &[f64]
) -> Result<(), String>
pub fn put_afe_barf_entry_list( &mut self, afeidx_: &[i64], barvaridx_: &[i32], numterm_: &[i64], ptrterm_: &[i64], termidx_: &[i64], termweight_: &[f64] ) -> Result<(), String>
Inputs a list of entries in barF.
§Arguments
afeidx_Row indexes of barF.barvaridx_Semidefinite variable indexes.numterm_Number of terms in the weighted sums.ptrterm_Pointer to the terms forming each entry.termidx_Concatenated element indexes in matrix storage.termweight_Concatenated weights in the weighted sum.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putafebarfentrylist
sourcepub fn put_afe_barf_row(
&mut self,
afeidx_: i64,
barvaridx_: &[i32],
numterm_: &[i64],
ptrterm_: &[i64],
termidx_: &[i64],
termweight_: &[f64]
) -> Result<(), String>
pub fn put_afe_barf_row( &mut self, afeidx_: i64, barvaridx_: &[i32], numterm_: &[i64], ptrterm_: &[i64], termidx_: &[i64], termweight_: &[f64] ) -> Result<(), String>
Inputs a row of barF.
§Arguments
afeidx_Row index of barF.barvaridx_Semidefinite variable indexes.numterm_Number of terms in the weighted sums.ptrterm_Pointer to the terms forming each entry.termidx_Concatenated element indexes in matrix storage.termweight_Concatenated weights in the weighted sum.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putafebarfrow
sourcepub fn put_afe_f_col(
&mut self,
varidx_: i32,
afeidx_: &[i64],
val_: &[f64]
) -> Result<(), String>
pub fn put_afe_f_col( &mut self, varidx_: i32, afeidx_: &[i64], val_: &[f64] ) -> Result<(), String>
Replaces all elements in one column of the F matrix in the affine expressions.
§Arguments
varidx_Column index.afeidx_Row indexes of non-zero values in the column.val_New non-zero values in the column.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putafefcol
sourcepub fn put_afe_f_entry(
&mut self,
afeidx_: i64,
varidx_: i32,
value_: f64
) -> Result<(), String>
pub fn put_afe_f_entry( &mut self, afeidx_: i64, varidx_: i32, value_: f64 ) -> Result<(), String>
Replaces one entry in F.
§Arguments
afeidx_Row index in F.varidx_Column index in F.value_Value of the entry.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putafefentry
Examples found in repository?
examples/portfolio_2_frontier.rs (line 89)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}More examples
examples/portfolio_5_card.rs (line 145)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}sourcepub fn put_afe_f_entry_list(
&mut self,
afeidx_: &[i64],
varidx_: &[i32],
val_: &[f64]
) -> Result<(), String>
pub fn put_afe_f_entry_list( &mut self, afeidx_: &[i64], varidx_: &[i32], val_: &[f64] ) -> Result<(), String>
Replaces a list of entries in F.
§Arguments
afeidx_Row indices in F.varidx_Column indices in F.val_Values of the entries in F.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putafefentrylist
sourcepub fn put_afe_f_row(
&mut self,
afeidx_: i64,
varidx_: &[i32],
val_: &[f64]
) -> Result<(), String>
pub fn put_afe_f_row( &mut self, afeidx_: i64, varidx_: &[i32], val_: &[f64] ) -> Result<(), String>
Replaces all elements in one row of the F matrix in the affine expressions.
§Arguments
afeidx_Row index.varidx_Column indexes of non-zero values in the row.val_New non-zero values in the row.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putafefrow
sourcepub fn put_afe_f_row_list(
&mut self,
afeidx_: &[i64],
numnzrow_: &[i32],
ptrrow_: &[i64],
varidx_: &[i32],
val_: &[f64]
) -> Result<(), String>
pub fn put_afe_f_row_list( &mut self, afeidx_: &[i64], numnzrow_: &[i32], ptrrow_: &[i64], varidx_: &[i32], val_: &[f64] ) -> Result<(), String>
Replaces all elements in a number of rows of the F matrix in the affine expressions.
§Arguments
afeidx_Row indices.numnzrow_Number of non-zeros in each row.ptrrow_Pointer to the first nonzero in each row.varidx_Column indexes of non-zero values.val_New non-zero values in the rows.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putafefrowlist
Examples found in repository?
examples/ceo1.rs (lines 70-74)
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fn main() -> Result<(),String> {
let numcon = 1;
let numvar = 3;
let bkc = mosek::Boundkey::FX;
let blc = 1.0;
let buc = 1.0;
let bkx = vec![ Boundkey::FR,
Boundkey::FR,
Boundkey::FR ];
let blx = vec![ -INF, -INF, -INF ];
let bux = vec![ INF, INF, INF ];
let c = vec![ 1.0, 1.0, 0.0 ];
let a = vec![ 1.0, 1.0, 1.0 ];
let asub = vec![0, 1, 2];
//let csub = new int[numvar];
//double[] xx = new double[numvar];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|task| task.with_callback(
&mut |caller| { println!("caller = {}",caller); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
/* Define the linear part of the problem */
task.put_c_slice(0, numvar, c.as_slice())?;
task.put_a_row(0, asub.as_slice(), a.as_slice())?;
task.put_con_bound(0, bkc, blc, buc)?;
task.put_var_bound_slice(0, numvar, bkx.as_slice(), blx.as_slice(), bux.as_slice())?;
/* Add a conic constraint */
task.append_afes(3)?;
let afeidxs = vec![0, 1, 2 ];
let b = vec![0.0,0.0,0.0];
let domidx = task.append_primal_exp_cone_domain()?;
task.put_afe_f_row_list(afeidxs.as_slice(),
vec![1,1,1].as_slice(),
vec![0,1,2].as_slice(),
vec![0,1,2].as_slice(),
vec![1.0,1.0,1.0].as_slice())?;
task.append_acc(domidx,afeidxs.as_slice(),b.as_slice())?;
task.put_obj_sense(Objsense::MINIMIZE)?;
println!("optimize");
/* Solve the problem */
task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
/* Get status information about the solution */
let solsta = task.get_sol_sta(Soltype::ITR)?;
assert!(solsta == Solsta::OPTIMAL);
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITR, & mut xx[..])?;
println!("Optimal primal solution");
for j in 0..numvar as usize {
println!("x[{}]: {:.4}",j,xx[j]);
}
Ok(())
}))
}sourcepub fn put_afe_g(&mut self, afeidx_: i64, g_: f64) -> Result<(), String>
pub fn put_afe_g(&mut self, afeidx_: i64, g_: f64) -> Result<(), String>
Replaces one element in the g vector in the affine expressions.
§Arguments
afeidx_Row index.g_New value for the element of g.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putafeg
Examples found in repository?
examples/portfolio_2_frontier.rs (line 90)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}More examples
examples/portfolio_5_card.rs (line 142)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}sourcepub fn put_afe_g_list(
&mut self,
afeidx_: &[i64],
g_: &[f64]
) -> Result<(), String>
pub fn put_afe_g_list( &mut self, afeidx_: &[i64], g_: &[f64] ) -> Result<(), String>
Replaces a list of elements in the g vector in the affine expressions.
§Arguments
afeidx_Indices of entries in g.g_New values for the elements of g.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putafeglist
sourcepub fn put_afe_g_slice(
&mut self,
first_: i64,
last_: i64,
slice_: &[f64]
) -> Result<(), String>
pub fn put_afe_g_slice( &mut self, first_: i64, last_: i64, slice_: &[f64] ) -> Result<(), String>
Modifies a slice of the vector g.
§Arguments
first_First index in the sequence.last_Last index plus 1 in the sequence.slice_The slice of g as a dense vector.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putafegslice
sourcepub fn put_aij(&mut self, i_: i32, j_: i32, aij_: f64) -> Result<(), String>
pub fn put_aij(&mut self, i_: i32, j_: i32, aij_: f64) -> Result<(), String>
Changes a single value in the linear coefficient matrix.
§Arguments
i_Constraint (row) index.j_Variable (column) index.aij_New coefficient.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putaij
Examples found in repository?
examples/portfolio_2_frontier.rs (line 69)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}More examples
examples/reoptimization.rs (line 93)
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fn main() -> Result<(),String> {
let numcon = 3;
let numvar = 3;
let c = &[1.5, 2.5, 3.0 ];
let bkc = &[ Boundkey::UP,
Boundkey::UP,
Boundkey::UP ];
let blc = &[ -INF,
-INF,
-INF ];
let buc = &[ 100000.0,
50000.0,
60000.0 ];
let bkx = &[ Boundkey::LO,
Boundkey::LO,
Boundkey::LO
];
let blx = &[ 0.0, 0.0, 0.0 ];
let bux = &[ INF,
INF,
INF ];
let asub = &[
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ] ];
let aval = &[
&[ 2.0, 3.0, 2.0 ],
&[ 4.0, 2.0, 3.0 ],
&[ 3.0, 3.0, 2.0 ] ];
let mut task = Task::new().unwrap();
/* Append the constraints. */
task.append_cons(numcon)?;
/* Append the variables. */
task.append_vars(numvar)?;
/* Put C. */
for (j,&cj) in (0..numvar).zip(c.iter()) {
task.put_c_j(j,cj)?;
}
/* Put constraint bounds. */
for (i,&bki,&bli,&bui) in izip!(0..numcon,bkc,blc,buc) {
task.put_con_bound(i, bki, bli, bui)?;
}
/* Put variable bounds. */
for (j,&bki,&bli,&bui) in izip!(0..numvar,bkx,blx,bux) {
task.put_var_bound(j, bki, bli, bui)?;
}
/* Put A. */
if numcon > 0 {
for (j,&asubj,&avalj) in izip!(0..numvar,asub,aval) {
task.put_a_col(j,
asubj,
avalj)?;
}
}
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/****************** Make a change to the A matrix ******************/
task.put_aij(0, 0, 3.0)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/***************** Add a new variable ******************************/
/* Get index of new variable. */
let varidx = task.get_num_var()?;
/* Append a new variable x_3 to the problem */
task.append_vars(1)?;
let numvar = numvar + 1;
/* Set bounds on new varaible */
task.put_var_bound(varidx, Boundkey::LO, 0.0, INF)?;
/* Change objective */
task.put_c_j(varidx, 1.0)?;
/* Put new values in the A matrix */
let acolsub = &[0i32, 2];
let acolval = &[4.0, 1.0];
task.put_a_col(varidx, /* column index */
acolsub,
acolval)?;
/* Change optimizer to simplex free and reoptimize */
task.put_int_param(mosek::Iparam::OPTIMIZER, mosek::Optimizertype::FREE_SIMPLEX)?;
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Add a new constraint ***************************/
/* Get index of new constraint. */
let conidx = task.get_num_con()?;
/* Append a new constraint */
task.append_cons(1)?;
let numcon = numcon + 1;
/* Set bounds on new constraint */
task.put_con_bound(conidx,
Boundkey::UP,
-INF,
30000.0)?;
/* Put new values in the A matrix */
let arowsub = &[0i32, 1, 2, 3 ];
let arowval = &[1.0, 2.0, 1.0, 1.0 ];
task.put_a_row(conidx, /* row index */
arowsub,
arowval)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Change constraint bounds ********************/
let newbkc = &[Boundkey::UP,
Boundkey::UP,
Boundkey::UP,
Boundkey::UP];
let newblc = &[-INF,
-INF,
-INF,
-INF];
let newbuc = &[ 80000.0, 40000.0, 50000.0, 22000.0 ];
task.put_con_bound_slice(0, numcon, newbkc, newblc, newbuc)?;
let _ = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
Ok(())
}sourcepub fn put_aij_list(
&mut self,
subi_: &[i32],
subj_: &[i32],
valij_: &[f64]
) -> Result<(), String>
pub fn put_aij_list( &mut self, subi_: &[i32], subj_: &[i32], valij_: &[f64] ) -> Result<(), String>
Changes one or more coefficients in the linear constraint matrix.
§Arguments
subi_Constraint (row) indices.subj_Variable (column) indices.valij_New coefficient values.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putaijlist64
Examples found in repository?
examples/pinfeas.rs (lines 21-23)
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
fn test_problem() -> Result<mosek::Task,String> {
let mut task = mosek::Task::new().unwrap();
task.append_vars(7)?;
task.append_cons(7)?;
task.put_c_list(&[0,1,2,3,4,5,6],
&[1.0,2.0,5.0,2.0,1.0,2.0,1.0])?;
task.put_aij_list(&[0,0,1,1,2,2,2,3,3,4,5,5,6,6],
&[0,1,2,3,4,5,6,0,4,1,2,5,3,6],
&[1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0])?;
task.put_con_bound_slice(0, 7,
&[Boundkey::UP,Boundkey::UP,Boundkey::UP,Boundkey::FX,Boundkey::FX,Boundkey::FX,Boundkey::FX],
&[-INF, -INF, -INF, 1100.0, 200.0, 500.0, 500.0],
&[200.0, 1000.0, 1000.0, 1100.0, 200.0, 500.0, 500.0])?;
task.put_var_bound_slice_const(0, 7, Boundkey::UP, 0.0, INF)?;
Ok(task)
}More examples
examples/portfolio_5_card.rs (line 114)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}sourcepub fn put_a_row(
&mut self,
i_: i32,
subi_: &[i32],
vali_: &[f64]
) -> Result<(), String>
pub fn put_a_row( &mut self, i_: i32, subi_: &[i32], vali_: &[f64] ) -> Result<(), String>
Replaces all elements in one row of the linear constraint matrix.
§Arguments
i_Row index.subi_Column indexes of non-zero values in row.vali_New non-zero values of row.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putarow
Examples found in repository?
examples/ceo1.rs (line 61)
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fn main() -> Result<(),String> {
let numcon = 1;
let numvar = 3;
let bkc = mosek::Boundkey::FX;
let blc = 1.0;
let buc = 1.0;
let bkx = vec![ Boundkey::FR,
Boundkey::FR,
Boundkey::FR ];
let blx = vec![ -INF, -INF, -INF ];
let bux = vec![ INF, INF, INF ];
let c = vec![ 1.0, 1.0, 0.0 ];
let a = vec![ 1.0, 1.0, 1.0 ];
let asub = vec![0, 1, 2];
//let csub = new int[numvar];
//double[] xx = new double[numvar];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|task| task.with_callback(
&mut |caller| { println!("caller = {}",caller); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
/* Define the linear part of the problem */
task.put_c_slice(0, numvar, c.as_slice())?;
task.put_a_row(0, asub.as_slice(), a.as_slice())?;
task.put_con_bound(0, bkc, blc, buc)?;
task.put_var_bound_slice(0, numvar, bkx.as_slice(), blx.as_slice(), bux.as_slice())?;
/* Add a conic constraint */
task.append_afes(3)?;
let afeidxs = vec![0, 1, 2 ];
let b = vec![0.0,0.0,0.0];
let domidx = task.append_primal_exp_cone_domain()?;
task.put_afe_f_row_list(afeidxs.as_slice(),
vec![1,1,1].as_slice(),
vec![0,1,2].as_slice(),
vec![0,1,2].as_slice(),
vec![1.0,1.0,1.0].as_slice())?;
task.append_acc(domidx,afeidxs.as_slice(),b.as_slice())?;
task.put_obj_sense(Objsense::MINIMIZE)?;
println!("optimize");
/* Solve the problem */
task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
/* Get status information about the solution */
let solsta = task.get_sol_sta(Soltype::ITR)?;
assert!(solsta == Solsta::OPTIMAL);
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITR, & mut xx[..])?;
println!("Optimal primal solution");
for j in 0..numvar as usize {
println!("x[{}]: {:.4}",j,xx[j]);
}
Ok(())
}))
}More examples
examples/reoptimization.rs (lines 154-156)
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fn main() -> Result<(),String> {
let numcon = 3;
let numvar = 3;
let c = &[1.5, 2.5, 3.0 ];
let bkc = &[ Boundkey::UP,
Boundkey::UP,
Boundkey::UP ];
let blc = &[ -INF,
-INF,
-INF ];
let buc = &[ 100000.0,
50000.0,
60000.0 ];
let bkx = &[ Boundkey::LO,
Boundkey::LO,
Boundkey::LO
];
let blx = &[ 0.0, 0.0, 0.0 ];
let bux = &[ INF,
INF,
INF ];
let asub = &[
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ] ];
let aval = &[
&[ 2.0, 3.0, 2.0 ],
&[ 4.0, 2.0, 3.0 ],
&[ 3.0, 3.0, 2.0 ] ];
let mut task = Task::new().unwrap();
/* Append the constraints. */
task.append_cons(numcon)?;
/* Append the variables. */
task.append_vars(numvar)?;
/* Put C. */
for (j,&cj) in (0..numvar).zip(c.iter()) {
task.put_c_j(j,cj)?;
}
/* Put constraint bounds. */
for (i,&bki,&bli,&bui) in izip!(0..numcon,bkc,blc,buc) {
task.put_con_bound(i, bki, bli, bui)?;
}
/* Put variable bounds. */
for (j,&bki,&bli,&bui) in izip!(0..numvar,bkx,blx,bux) {
task.put_var_bound(j, bki, bli, bui)?;
}
/* Put A. */
if numcon > 0 {
for (j,&asubj,&avalj) in izip!(0..numvar,asub,aval) {
task.put_a_col(j,
asubj,
avalj)?;
}
}
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/****************** Make a change to the A matrix ******************/
task.put_aij(0, 0, 3.0)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/***************** Add a new variable ******************************/
/* Get index of new variable. */
let varidx = task.get_num_var()?;
/* Append a new variable x_3 to the problem */
task.append_vars(1)?;
let numvar = numvar + 1;
/* Set bounds on new varaible */
task.put_var_bound(varidx, Boundkey::LO, 0.0, INF)?;
/* Change objective */
task.put_c_j(varidx, 1.0)?;
/* Put new values in the A matrix */
let acolsub = &[0i32, 2];
let acolval = &[4.0, 1.0];
task.put_a_col(varidx, /* column index */
acolsub,
acolval)?;
/* Change optimizer to simplex free and reoptimize */
task.put_int_param(mosek::Iparam::OPTIMIZER, mosek::Optimizertype::FREE_SIMPLEX)?;
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Add a new constraint ***************************/
/* Get index of new constraint. */
let conidx = task.get_num_con()?;
/* Append a new constraint */
task.append_cons(1)?;
let numcon = numcon + 1;
/* Set bounds on new constraint */
task.put_con_bound(conidx,
Boundkey::UP,
-INF,
30000.0)?;
/* Put new values in the A matrix */
let arowsub = &[0i32, 1, 2, 3 ];
let arowval = &[1.0, 2.0, 1.0, 1.0 ];
task.put_a_row(conidx, /* row index */
arowsub,
arowval)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Change constraint bounds ********************/
let newbkc = &[Boundkey::UP,
Boundkey::UP,
Boundkey::UP,
Boundkey::UP];
let newblc = &[-INF,
-INF,
-INF,
-INF];
let newbuc = &[ 80000.0, 40000.0, 50000.0, 22000.0 ];
task.put_con_bound_slice(0, numcon, newbkc, newblc, newbuc)?;
let _ = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
Ok(())
}examples/portfolio_5_card.rs (lines 96-98)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}sourcepub fn put_a_row_list(
&mut self,
sub_: &[i32],
ptrb_: &[i64],
ptre_: &[i64],
asub_: &[i32],
aval_: &[f64]
) -> Result<(), String>
pub fn put_a_row_list( &mut self, sub_: &[i32], ptrb_: &[i64], ptre_: &[i64], asub_: &[i32], aval_: &[f64] ) -> Result<(), String>
Replaces all elements in several rows of the linear constraint matrix.
§Arguments
sub_Indexes of rows or columns that should be replaced.ptrb_Array of pointers to the first element in the rows.ptre_Array of pointers to the last element plus one in the rows.asub_Variable indexes.aval_Coefficient values.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putarowlist64
sourcepub fn put_a_row_slice(
&mut self,
first_: i32,
last_: i32,
ptrb_: &[i64],
ptre_: &[i64],
asub_: &[i32],
aval_: &[f64]
) -> Result<(), String>
pub fn put_a_row_slice( &mut self, first_: i32, last_: i32, ptrb_: &[i64], ptre_: &[i64], asub_: &[i32], aval_: &[f64] ) -> Result<(), String>
Replaces all elements in several rows the linear constraint matrix.
§Arguments
first_First row in the slice.last_Last row plus one in the slice.ptrb_Array of pointers to the first element in the rows.ptre_Array of pointers to the last element plus one in the rows.asub_Column indexes of new elements.aval_Coefficient values.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putarowslice64
sourcepub fn put_a_truncate_tol(&mut self, tolzero_: f64) -> Result<(), String>
pub fn put_a_truncate_tol(&mut self, tolzero_: f64) -> Result<(), String>
Truncates all elements in A below a certain tolerance to zero.
§Arguments
tolzero_Truncation tolerance.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putatruncatetol
sourcepub fn put_bara_block_triplet(
&mut self,
subi_: &[i32],
subj_: &[i32],
subk_: &[i32],
subl_: &[i32],
valijkl_: &[f64]
) -> Result<(), String>
pub fn put_bara_block_triplet( &mut self, subi_: &[i32], subj_: &[i32], subk_: &[i32], subl_: &[i32], valijkl_: &[f64] ) -> Result<(), String>
Inputs barA in block triplet form.
§Arguments
subi_Constraint index.subj_Symmetric matrix variable index.subk_Block row index.subl_Block column index.valijkl_The numerical value associated with each block triplet.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putbarablocktriplet
sourcepub fn put_bara_ij(
&mut self,
i_: i32,
j_: i32,
sub_: &[i64],
weights_: &[f64]
) -> Result<(), String>
pub fn put_bara_ij( &mut self, i_: i32, j_: i32, sub_: &[i64], weights_: &[f64] ) -> Result<(), String>
Inputs an element of barA.
§Arguments
i_Row index of barA.j_Column index of barA.sub_Element indexes in matrix storage.weights_Weights in the weighted sum.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putbaraij
sourcepub fn put_bara_ij_list(
&mut self,
subi_: &[i32],
subj_: &[i32],
alphaptrb_: &[i64],
alphaptre_: &[i64],
matidx_: &[i64],
weights_: &[f64]
) -> Result<(), String>
pub fn put_bara_ij_list( &mut self, subi_: &[i32], subj_: &[i32], alphaptrb_: &[i64], alphaptre_: &[i64], matidx_: &[i64], weights_: &[f64] ) -> Result<(), String>
Inputs list of elements of barA.
§Arguments
subi_Row index of barA.subj_Column index of barA.alphaptrb_Start entries for terms in the weighted sum.alphaptre_End entries for terms in the weighted sum.matidx_Element indexes in matrix storage.weights_Weights in the weighted sum.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putbaraijlist
sourcepub fn put_bara_row_list(
&mut self,
subi_: &[i32],
ptrb_: &[i64],
ptre_: &[i64],
subj_: &[i32],
nummat_: &[i64],
matidx_: &[i64],
weights_: &[f64]
) -> Result<(), String>
pub fn put_bara_row_list( &mut self, subi_: &[i32], ptrb_: &[i64], ptre_: &[i64], subj_: &[i32], nummat_: &[i64], matidx_: &[i64], weights_: &[f64] ) -> Result<(), String>
Replace a set of rows of barA
§Arguments
subi_Row indexes of barA.ptrb_Start of rows in barA.ptre_End of rows in barA.subj_Column index of barA.nummat_Number of entries in weighted sum of matrixes.matidx_Matrix indexes for weighted sum of matrixes.weights_Weights for weighted sum of matrixes.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putbararowlist
sourcepub fn put_barc_block_triplet(
&mut self,
subj_: &[i32],
subk_: &[i32],
subl_: &[i32],
valjkl_: &[f64]
) -> Result<(), String>
pub fn put_barc_block_triplet( &mut self, subj_: &[i32], subk_: &[i32], subl_: &[i32], valjkl_: &[f64] ) -> Result<(), String>
Inputs barC in block triplet form.
§Arguments
subj_Symmetric matrix variable index.subk_Block row index.subl_Block column index.valjkl_The numerical value associated with each block triplet.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putbarcblocktriplet
sourcepub fn put_barc_j(
&mut self,
j_: i32,
sub_: &[i64],
weights_: &[f64]
) -> Result<(), String>
pub fn put_barc_j( &mut self, j_: i32, sub_: &[i64], weights_: &[f64] ) -> Result<(), String>
Changes one element in barc.
§Arguments
j_Index of the element in barc` that should be changed.sub_sub is list of indexes of those symmetric matrices appearing in sum.weights_The weights of the terms in the weighted sum.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putbarcj
sourcepub fn put_bars_j(
&mut self,
whichsol_: i32,
j_: i32,
barsj_: &[f64]
) -> Result<(), String>
pub fn put_bars_j( &mut self, whichsol_: i32, j_: i32, barsj_: &[f64] ) -> Result<(), String>
Sets the dual solution for a semidefinite variable.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
j_Index of the semidefinite variable. -
barsj_Value of the j’th variable of barx.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putbarsj
sourcepub fn put_barvar_name(&mut self, j_: i32, name_: &str) -> Result<(), String>
pub fn put_barvar_name(&mut self, j_: i32, name_: &str) -> Result<(), String>
Sets the name of a semidefinite variable.
§Arguments
j_Index of the variable.name_The variable name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putbarvarname
sourcepub fn put_barx_j(
&mut self,
whichsol_: i32,
j_: i32,
barxj_: &[f64]
) -> Result<(), String>
pub fn put_barx_j( &mut self, whichsol_: i32, j_: i32, barxj_: &[f64] ) -> Result<(), String>
Sets the primal solution for a semidefinite variable.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
j_Index of the semidefinite variable. -
barxj_Value of the j’th variable of barx.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putbarxj
sourcepub fn put_cfix(&mut self, cfix_: f64) -> Result<(), String>
pub fn put_cfix(&mut self, cfix_: f64) -> Result<(), String>
Replaces the fixed term in the objective.
§Arguments
cfix_Fixed term in the objective.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putcfix
sourcepub fn put_c_j(&mut self, j_: i32, cj_: f64) -> Result<(), String>
pub fn put_c_j(&mut self, j_: i32, cj_: f64) -> Result<(), String>
Modifies one linear coefficient in the objective.
§Arguments
j_Index of the variable whose objective coefficient should be changed.cj_New coefficient value.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putcj
Examples found in repository?
examples/helloworld.rs (line 21)
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fn main() -> Result<(),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
task.append_vars(1)?; // 1 variable x
task.put_c_j(0, 1.0)?; // c_0 = 1.0
task.put_var_bound(0, Boundkey::RA, 2.0, 3.0)?; // 2.0 <= x <= 3.0
task.put_obj_sense(Objsense::MINIMIZE)?; // minimize
task.optimize()?; // Optimize
let mut x = vec![0.0; 1];
task.get_xx(Soltype::ITR, x.as_mut_slice())?; // Get solution
println!("Solution x = {}", x[0]); // Print solution
return Result::Ok(());
}More examples
examples/portfolio_2_frontier.rs (line 99)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}examples/reoptimization.rs (line 58)
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fn main() -> Result<(),String> {
let numcon = 3;
let numvar = 3;
let c = &[1.5, 2.5, 3.0 ];
let bkc = &[ Boundkey::UP,
Boundkey::UP,
Boundkey::UP ];
let blc = &[ -INF,
-INF,
-INF ];
let buc = &[ 100000.0,
50000.0,
60000.0 ];
let bkx = &[ Boundkey::LO,
Boundkey::LO,
Boundkey::LO
];
let blx = &[ 0.0, 0.0, 0.0 ];
let bux = &[ INF,
INF,
INF ];
let asub = &[
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ] ];
let aval = &[
&[ 2.0, 3.0, 2.0 ],
&[ 4.0, 2.0, 3.0 ],
&[ 3.0, 3.0, 2.0 ] ];
let mut task = Task::new().unwrap();
/* Append the constraints. */
task.append_cons(numcon)?;
/* Append the variables. */
task.append_vars(numvar)?;
/* Put C. */
for (j,&cj) in (0..numvar).zip(c.iter()) {
task.put_c_j(j,cj)?;
}
/* Put constraint bounds. */
for (i,&bki,&bli,&bui) in izip!(0..numcon,bkc,blc,buc) {
task.put_con_bound(i, bki, bli, bui)?;
}
/* Put variable bounds. */
for (j,&bki,&bli,&bui) in izip!(0..numvar,bkx,blx,bux) {
task.put_var_bound(j, bki, bli, bui)?;
}
/* Put A. */
if numcon > 0 {
for (j,&asubj,&avalj) in izip!(0..numvar,asub,aval) {
task.put_a_col(j,
asubj,
avalj)?;
}
}
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/****************** Make a change to the A matrix ******************/
task.put_aij(0, 0, 3.0)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/***************** Add a new variable ******************************/
/* Get index of new variable. */
let varidx = task.get_num_var()?;
/* Append a new variable x_3 to the problem */
task.append_vars(1)?;
let numvar = numvar + 1;
/* Set bounds on new varaible */
task.put_var_bound(varidx, Boundkey::LO, 0.0, INF)?;
/* Change objective */
task.put_c_j(varidx, 1.0)?;
/* Put new values in the A matrix */
let acolsub = &[0i32, 2];
let acolval = &[4.0, 1.0];
task.put_a_col(varidx, /* column index */
acolsub,
acolval)?;
/* Change optimizer to simplex free and reoptimize */
task.put_int_param(mosek::Iparam::OPTIMIZER, mosek::Optimizertype::FREE_SIMPLEX)?;
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Add a new constraint ***************************/
/* Get index of new constraint. */
let conidx = task.get_num_con()?;
/* Append a new constraint */
task.append_cons(1)?;
let numcon = numcon + 1;
/* Set bounds on new constraint */
task.put_con_bound(conidx,
Boundkey::UP,
-INF,
30000.0)?;
/* Put new values in the A matrix */
let arowsub = &[0i32, 1, 2, 3 ];
let arowval = &[1.0, 2.0, 1.0, 1.0 ];
task.put_a_row(conidx, /* row index */
arowsub,
arowval)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Change constraint bounds ********************/
let newbkc = &[Boundkey::UP,
Boundkey::UP,
Boundkey::UP,
Boundkey::UP];
let newblc = &[-INF,
-INF,
-INF,
-INF];
let newbuc = &[ 80000.0, 40000.0, 50000.0, 22000.0 ];
task.put_con_bound_slice(0, numcon, newbkc, newblc, newbuc)?;
let _ = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
Ok(())
}examples/portfolio_5_card.rs (line 87)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}examples/milo1.rs (line 54)
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fn main() -> Result<(),String> {
let numcon : i32 = 2;
let numvar : i32 = 2;
let infinity = 0.0; // only for symbolic purposes, value never used
let bkc = vec![Boundkey::UP, Boundkey::LO];
let blc = vec![ -infinity, -4.0 ];
let buc = vec![ 250.0, infinity ];
let bkx = vec![ Boundkey::LO, Boundkey::LO ];
let blx = vec![ 0.0, 0.0 ];
let bux = vec![ infinity, infinity ];
let c = vec![1.0, 0.64];
let asub = vec![0, 1,
0, 1];
let aval = vec![50.0, 3.0, 31.0, -2.0];
let ptrb : Vec<usize> = vec![ 0, 2 ];
let ptre : Vec<usize> = vec![ 2, 4 ];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| task.with_itg_sol_callback(
&mut |xx| { println!("Found a new solution = {:?}",xx); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
for ((((j,cj),bk),bl),bu) in (0..numvar).zip(c.iter()).zip(bkx.iter()).zip(blx.iter()).zip(bux.iter()) {
/* Set the linear term c_j in the objective.*/
task.put_c_j(j, *cj)?;
/* Set the bounds on variable j.
blx[j] <= x_j <= bux[j] */
task.put_var_bound(j, *bk, *bl, *bu)?;
/* Input column j of A */
task.put_a_col(j, /* Variable (column) index.*/
&asub[ptrb[j as usize]..ptre[j as usize]], /* Row index of non-zeros in column j.*/
&aval[ptrb[j as usize]..ptre[j as usize]])?; /* Non-zero Values of column j. */
}
// Set the bounds on constraints.
// for i=1, ...,numcon : blc[i] <= constraint i <= buc[i]
for (((i,bk),bl),bu) in (0..numcon).zip(bkc.iter()).zip(blc.iter()).zip(buc.iter()) {
task.put_con_bound(i, *bk, *bl, *bu)?;
}
/* Specify integer variables. */
for j in 0..numvar {
task.put_var_type(j, Variabletype::TYPE_INT)?;
}
/* Set max solution time */
task.put_dou_param(Dparam::MIO_MAX_TIME, 60.0)?;
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITG, xx.as_mut_slice())?;
/* Get status information about the solution */
match task.get_sol_sta(Soltype::ITG)? {
Solsta::INTEGER_OPTIMAL => {
println!("Optimal solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::PRIM_FEAS => {
println!("Feasible solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::UNKNOWN => {
match task.get_pro_sta(Soltype::ITG)? {
Prosta::PRIM_INFEAS_OR_UNBOUNDED => {
println!("Problem status Infeasible or unbounded");
}
Prosta::PRIM_INFEAS => {
println!("Problem status Infeasible.");
}
Prosta::UNKNOWN => {
println!("Problem status unknown.");
}
_ => {
println!("Other problem status.");
}
}
}
_ => {
println!("Other solution status");
}
}
Ok(())
}))
}sourcepub fn put_c_list(&mut self, subj_: &[i32], val_: &[f64]) -> Result<(), String>
pub fn put_c_list(&mut self, subj_: &[i32], val_: &[f64]) -> Result<(), String>
Modifies a part of the linear objective coefficients.
§Arguments
subj_Indices of variables for which objective coefficients should be changed.val_New numerical values for the objective coefficients that should be modified.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putclist
Examples found in repository?
examples/pinfeas.rs (lines 19-20)
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fn test_problem() -> Result<mosek::Task,String> {
let mut task = mosek::Task::new().unwrap();
task.append_vars(7)?;
task.append_cons(7)?;
task.put_c_list(&[0,1,2,3,4,5,6],
&[1.0,2.0,5.0,2.0,1.0,2.0,1.0])?;
task.put_aij_list(&[0,0,1,1,2,2,2,3,3,4,5,5,6,6],
&[0,1,2,3,4,5,6,0,4,1,2,5,3,6],
&[1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0])?;
task.put_con_bound_slice(0, 7,
&[Boundkey::UP,Boundkey::UP,Boundkey::UP,Boundkey::FX,Boundkey::FX,Boundkey::FX,Boundkey::FX],
&[-INF, -INF, -INF, 1100.0, 200.0, 500.0, 500.0],
&[200.0, 1000.0, 1000.0, 1100.0, 200.0, 500.0, 500.0])?;
task.put_var_bound_slice_const(0, 7, Boundkey::UP, 0.0, INF)?;
Ok(task)
}sourcepub fn put_con_bound(
&mut self,
i_: i32,
bkc_: i32,
blc_: f64,
buc_: f64
) -> Result<(), String>
pub fn put_con_bound( &mut self, i_: i32, bkc_: i32, blc_: f64, buc_: f64 ) -> Result<(), String>
Changes the bound for one constraint.
§Arguments
-
i_Index of the constraint. -
bkc_New bound key.See Boundkey
-
blc_New lower bound. -
buc_New upper bound.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putconbound
Examples found in repository?
examples/portfolio_2_frontier.rs (line 62)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}More examples
examples/ceo1.rs (line 62)
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fn main() -> Result<(),String> {
let numcon = 1;
let numvar = 3;
let bkc = mosek::Boundkey::FX;
let blc = 1.0;
let buc = 1.0;
let bkx = vec![ Boundkey::FR,
Boundkey::FR,
Boundkey::FR ];
let blx = vec![ -INF, -INF, -INF ];
let bux = vec![ INF, INF, INF ];
let c = vec![ 1.0, 1.0, 0.0 ];
let a = vec![ 1.0, 1.0, 1.0 ];
let asub = vec![0, 1, 2];
//let csub = new int[numvar];
//double[] xx = new double[numvar];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|task| task.with_callback(
&mut |caller| { println!("caller = {}",caller); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
/* Define the linear part of the problem */
task.put_c_slice(0, numvar, c.as_slice())?;
task.put_a_row(0, asub.as_slice(), a.as_slice())?;
task.put_con_bound(0, bkc, blc, buc)?;
task.put_var_bound_slice(0, numvar, bkx.as_slice(), blx.as_slice(), bux.as_slice())?;
/* Add a conic constraint */
task.append_afes(3)?;
let afeidxs = vec![0, 1, 2 ];
let b = vec![0.0,0.0,0.0];
let domidx = task.append_primal_exp_cone_domain()?;
task.put_afe_f_row_list(afeidxs.as_slice(),
vec![1,1,1].as_slice(),
vec![0,1,2].as_slice(),
vec![0,1,2].as_slice(),
vec![1.0,1.0,1.0].as_slice())?;
task.append_acc(domidx,afeidxs.as_slice(),b.as_slice())?;
task.put_obj_sense(Objsense::MINIMIZE)?;
println!("optimize");
/* Solve the problem */
task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
/* Get status information about the solution */
let solsta = task.get_sol_sta(Soltype::ITR)?;
assert!(solsta == Solsta::OPTIMAL);
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITR, & mut xx[..])?;
println!("Optimal primal solution");
for j in 0..numvar as usize {
println!("x[{}]: {:.4}",j,xx[j]);
}
Ok(())
}))
}examples/reoptimization.rs (line 62)
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fn main() -> Result<(),String> {
let numcon = 3;
let numvar = 3;
let c = &[1.5, 2.5, 3.0 ];
let bkc = &[ Boundkey::UP,
Boundkey::UP,
Boundkey::UP ];
let blc = &[ -INF,
-INF,
-INF ];
let buc = &[ 100000.0,
50000.0,
60000.0 ];
let bkx = &[ Boundkey::LO,
Boundkey::LO,
Boundkey::LO
];
let blx = &[ 0.0, 0.0, 0.0 ];
let bux = &[ INF,
INF,
INF ];
let asub = &[
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ] ];
let aval = &[
&[ 2.0, 3.0, 2.0 ],
&[ 4.0, 2.0, 3.0 ],
&[ 3.0, 3.0, 2.0 ] ];
let mut task = Task::new().unwrap();
/* Append the constraints. */
task.append_cons(numcon)?;
/* Append the variables. */
task.append_vars(numvar)?;
/* Put C. */
for (j,&cj) in (0..numvar).zip(c.iter()) {
task.put_c_j(j,cj)?;
}
/* Put constraint bounds. */
for (i,&bki,&bli,&bui) in izip!(0..numcon,bkc,blc,buc) {
task.put_con_bound(i, bki, bli, bui)?;
}
/* Put variable bounds. */
for (j,&bki,&bli,&bui) in izip!(0..numvar,bkx,blx,bux) {
task.put_var_bound(j, bki, bli, bui)?;
}
/* Put A. */
if numcon > 0 {
for (j,&asubj,&avalj) in izip!(0..numvar,asub,aval) {
task.put_a_col(j,
asubj,
avalj)?;
}
}
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/****************** Make a change to the A matrix ******************/
task.put_aij(0, 0, 3.0)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/***************** Add a new variable ******************************/
/* Get index of new variable. */
let varidx = task.get_num_var()?;
/* Append a new variable x_3 to the problem */
task.append_vars(1)?;
let numvar = numvar + 1;
/* Set bounds on new varaible */
task.put_var_bound(varidx, Boundkey::LO, 0.0, INF)?;
/* Change objective */
task.put_c_j(varidx, 1.0)?;
/* Put new values in the A matrix */
let acolsub = &[0i32, 2];
let acolval = &[4.0, 1.0];
task.put_a_col(varidx, /* column index */
acolsub,
acolval)?;
/* Change optimizer to simplex free and reoptimize */
task.put_int_param(mosek::Iparam::OPTIMIZER, mosek::Optimizertype::FREE_SIMPLEX)?;
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Add a new constraint ***************************/
/* Get index of new constraint. */
let conidx = task.get_num_con()?;
/* Append a new constraint */
task.append_cons(1)?;
let numcon = numcon + 1;
/* Set bounds on new constraint */
task.put_con_bound(conidx,
Boundkey::UP,
-INF,
30000.0)?;
/* Put new values in the A matrix */
let arowsub = &[0i32, 1, 2, 3 ];
let arowval = &[1.0, 2.0, 1.0, 1.0 ];
task.put_a_row(conidx, /* row index */
arowsub,
arowval)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Change constraint bounds ********************/
let newbkc = &[Boundkey::UP,
Boundkey::UP,
Boundkey::UP,
Boundkey::UP];
let newblc = &[-INF,
-INF,
-INF,
-INF];
let newbuc = &[ 80000.0, 40000.0, 50000.0, 22000.0 ];
task.put_con_bound_slice(0, numcon, newbkc, newblc, newbuc)?;
let _ = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
Ok(())
}examples/portfolio_5_card.rs (line 99)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}examples/milo1.rs (line 66)
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fn main() -> Result<(),String> {
let numcon : i32 = 2;
let numvar : i32 = 2;
let infinity = 0.0; // only for symbolic purposes, value never used
let bkc = vec![Boundkey::UP, Boundkey::LO];
let blc = vec![ -infinity, -4.0 ];
let buc = vec![ 250.0, infinity ];
let bkx = vec![ Boundkey::LO, Boundkey::LO ];
let blx = vec![ 0.0, 0.0 ];
let bux = vec![ infinity, infinity ];
let c = vec![1.0, 0.64];
let asub = vec![0, 1,
0, 1];
let aval = vec![50.0, 3.0, 31.0, -2.0];
let ptrb : Vec<usize> = vec![ 0, 2 ];
let ptre : Vec<usize> = vec![ 2, 4 ];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| task.with_itg_sol_callback(
&mut |xx| { println!("Found a new solution = {:?}",xx); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
for ((((j,cj),bk),bl),bu) in (0..numvar).zip(c.iter()).zip(bkx.iter()).zip(blx.iter()).zip(bux.iter()) {
/* Set the linear term c_j in the objective.*/
task.put_c_j(j, *cj)?;
/* Set the bounds on variable j.
blx[j] <= x_j <= bux[j] */
task.put_var_bound(j, *bk, *bl, *bu)?;
/* Input column j of A */
task.put_a_col(j, /* Variable (column) index.*/
&asub[ptrb[j as usize]..ptre[j as usize]], /* Row index of non-zeros in column j.*/
&aval[ptrb[j as usize]..ptre[j as usize]])?; /* Non-zero Values of column j. */
}
// Set the bounds on constraints.
// for i=1, ...,numcon : blc[i] <= constraint i <= buc[i]
for (((i,bk),bl),bu) in (0..numcon).zip(bkc.iter()).zip(blc.iter()).zip(buc.iter()) {
task.put_con_bound(i, *bk, *bl, *bu)?;
}
/* Specify integer variables. */
for j in 0..numvar {
task.put_var_type(j, Variabletype::TYPE_INT)?;
}
/* Set max solution time */
task.put_dou_param(Dparam::MIO_MAX_TIME, 60.0)?;
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITG, xx.as_mut_slice())?;
/* Get status information about the solution */
match task.get_sol_sta(Soltype::ITG)? {
Solsta::INTEGER_OPTIMAL => {
println!("Optimal solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::PRIM_FEAS => {
println!("Feasible solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::UNKNOWN => {
match task.get_pro_sta(Soltype::ITG)? {
Prosta::PRIM_INFEAS_OR_UNBOUNDED => {
println!("Problem status Infeasible or unbounded");
}
Prosta::PRIM_INFEAS => {
println!("Problem status Infeasible.");
}
Prosta::UNKNOWN => {
println!("Problem status unknown.");
}
_ => {
println!("Other problem status.");
}
}
}
_ => {
println!("Other solution status");
}
}
Ok(())
}))
}sourcepub fn put_con_bound_list(
&mut self,
sub_: &[i32],
bkc_: &[i32],
blc_: &[f64],
buc_: &[f64]
) -> Result<(), String>
pub fn put_con_bound_list( &mut self, sub_: &[i32], bkc_: &[i32], blc_: &[f64], buc_: &[f64] ) -> Result<(), String>
Changes the bounds of a list of constraints.
§Arguments
-
sub_List of constraint indexes. -
bkc_Bound keys for the constraints.See Boundkey
-
blc_Lower bounds for the constraints. -
buc_Upper bounds for the constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putconboundlist
sourcepub fn put_con_bound_list_const(
&mut self,
sub_: &[i32],
bkc_: i32,
blc_: f64,
buc_: f64
) -> Result<(), String>
pub fn put_con_bound_list_const( &mut self, sub_: &[i32], bkc_: i32, blc_: f64, buc_: f64 ) -> Result<(), String>
Changes the bounds of a list of constraints.
§Arguments
-
sub_List of constraint indexes. -
bkc_New bound key for all constraints in the list.See Boundkey
-
blc_New lower bound for all constraints in the list. -
buc_New upper bound for all constraints in the list.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putconboundlistconst
sourcepub fn put_con_bound_slice(
&mut self,
first_: i32,
last_: i32,
bkc_: &[i32],
blc_: &[f64],
buc_: &[f64]
) -> Result<(), String>
pub fn put_con_bound_slice( &mut self, first_: i32, last_: i32, bkc_: &[i32], blc_: &[f64], buc_: &[f64] ) -> Result<(), String>
Changes the bounds for a slice of the constraints.
§Arguments
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
bkc_Bound keys for the constraints.See Boundkey
-
blc_Lower bounds for the constraints. -
buc_Upper bounds for the constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putconboundslice
Examples found in repository?
examples/pinfeas.rs (lines 24-27)
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fn test_problem() -> Result<mosek::Task,String> {
let mut task = mosek::Task::new().unwrap();
task.append_vars(7)?;
task.append_cons(7)?;
task.put_c_list(&[0,1,2,3,4,5,6],
&[1.0,2.0,5.0,2.0,1.0,2.0,1.0])?;
task.put_aij_list(&[0,0,1,1,2,2,2,3,3,4,5,5,6,6],
&[0,1,2,3,4,5,6,0,4,1,2,5,3,6],
&[1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0])?;
task.put_con_bound_slice(0, 7,
&[Boundkey::UP,Boundkey::UP,Boundkey::UP,Boundkey::FX,Boundkey::FX,Boundkey::FX,Boundkey::FX],
&[-INF, -INF, -INF, 1100.0, 200.0, 500.0, 500.0],
&[200.0, 1000.0, 1000.0, 1100.0, 200.0, 500.0, 500.0])?;
task.put_var_bound_slice_const(0, 7, Boundkey::UP, 0.0, INF)?;
Ok(task)
}More examples
examples/reoptimization.rs (line 178)
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fn main() -> Result<(),String> {
let numcon = 3;
let numvar = 3;
let c = &[1.5, 2.5, 3.0 ];
let bkc = &[ Boundkey::UP,
Boundkey::UP,
Boundkey::UP ];
let blc = &[ -INF,
-INF,
-INF ];
let buc = &[ 100000.0,
50000.0,
60000.0 ];
let bkx = &[ Boundkey::LO,
Boundkey::LO,
Boundkey::LO
];
let blx = &[ 0.0, 0.0, 0.0 ];
let bux = &[ INF,
INF,
INF ];
let asub = &[
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ] ];
let aval = &[
&[ 2.0, 3.0, 2.0 ],
&[ 4.0, 2.0, 3.0 ],
&[ 3.0, 3.0, 2.0 ] ];
let mut task = Task::new().unwrap();
/* Append the constraints. */
task.append_cons(numcon)?;
/* Append the variables. */
task.append_vars(numvar)?;
/* Put C. */
for (j,&cj) in (0..numvar).zip(c.iter()) {
task.put_c_j(j,cj)?;
}
/* Put constraint bounds. */
for (i,&bki,&bli,&bui) in izip!(0..numcon,bkc,blc,buc) {
task.put_con_bound(i, bki, bli, bui)?;
}
/* Put variable bounds. */
for (j,&bki,&bli,&bui) in izip!(0..numvar,bkx,blx,bux) {
task.put_var_bound(j, bki, bli, bui)?;
}
/* Put A. */
if numcon > 0 {
for (j,&asubj,&avalj) in izip!(0..numvar,asub,aval) {
task.put_a_col(j,
asubj,
avalj)?;
}
}
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/****************** Make a change to the A matrix ******************/
task.put_aij(0, 0, 3.0)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/***************** Add a new variable ******************************/
/* Get index of new variable. */
let varidx = task.get_num_var()?;
/* Append a new variable x_3 to the problem */
task.append_vars(1)?;
let numvar = numvar + 1;
/* Set bounds on new varaible */
task.put_var_bound(varidx, Boundkey::LO, 0.0, INF)?;
/* Change objective */
task.put_c_j(varidx, 1.0)?;
/* Put new values in the A matrix */
let acolsub = &[0i32, 2];
let acolval = &[4.0, 1.0];
task.put_a_col(varidx, /* column index */
acolsub,
acolval)?;
/* Change optimizer to simplex free and reoptimize */
task.put_int_param(mosek::Iparam::OPTIMIZER, mosek::Optimizertype::FREE_SIMPLEX)?;
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Add a new constraint ***************************/
/* Get index of new constraint. */
let conidx = task.get_num_con()?;
/* Append a new constraint */
task.append_cons(1)?;
let numcon = numcon + 1;
/* Set bounds on new constraint */
task.put_con_bound(conidx,
Boundkey::UP,
-INF,
30000.0)?;
/* Put new values in the A matrix */
let arowsub = &[0i32, 1, 2, 3 ];
let arowval = &[1.0, 2.0, 1.0, 1.0 ];
task.put_a_row(conidx, /* row index */
arowsub,
arowval)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Change constraint bounds ********************/
let newbkc = &[Boundkey::UP,
Boundkey::UP,
Boundkey::UP,
Boundkey::UP];
let newblc = &[-INF,
-INF,
-INF,
-INF];
let newbuc = &[ 80000.0, 40000.0, 50000.0, 22000.0 ];
task.put_con_bound_slice(0, numcon, newbkc, newblc, newbuc)?;
let _ = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
Ok(())
}examples/portfolio_5_card.rs (line 116)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}sourcepub fn put_con_bound_slice_const(
&mut self,
first_: i32,
last_: i32,
bkc_: i32,
blc_: f64,
buc_: f64
) -> Result<(), String>
pub fn put_con_bound_slice_const( &mut self, first_: i32, last_: i32, bkc_: i32, blc_: f64, buc_: f64 ) -> Result<(), String>
Changes the bounds for a slice of the constraints.
§Arguments
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
bkc_New bound key for all constraints in the slice.See Boundkey
-
blc_New lower bound for all constraints in the slice. -
buc_New upper bound for all constraints in the slice.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putconboundsliceconst
Examples found in repository?
examples/solvelinear.rs (line 46)
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fn setup(task : & mut mosek::Task,
aval : &[f64],
asub : &[i32],
ptrb : &[i64],
ptre : &[i64],
numvar : i32) -> Result<Vec<i32>,String> {
// mosek.stakey[] skx = new mosek.stakey [numvar];
// mosek.stakey[] skc = new mosek.stakey [numvar];
// for (int i = 0; i < numvar ; ++i) {
// skx[i] = mosek.stakey.bas;
// skc[i] = mosek.stakey.fix;
// }
task.append_vars(numvar)?;
task.append_cons(numvar)?;
task.put_a_col_slice(0,numvar,ptrb,ptre,asub,aval)?;
task.put_con_bound_slice_const(0,numvar,Boundkey::FX,0.0,0.0)?;
task.put_var_bound_slice_const(0,numvar,Boundkey::FR,-INF,INF)?;
/* Define a basic solution by specifying
status keys for variables & constraints. */
task.delete_solution(Soltype::BAS)?;
task.put_skc_slice(Soltype::BAS, 0, numvar, vec![Stakey::FIX; numvar as usize].as_slice())?;
task.put_skx_slice(Soltype::BAS, 0, numvar, vec![Stakey::BAS; numvar as usize].as_slice())?;
let mut basis = vec![0; numvar as usize];
task.init_basis_solve(basis.as_mut_slice())?;
Ok(basis)
}More examples
examples/portfolio_5_card.rs (line 161)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}sourcepub fn put_cone(
&mut self,
k_: i32,
ct_: i32,
conepar_: f64,
submem_: &[i32]
) -> Result<(), String>
pub fn put_cone( &mut self, k_: i32, ct_: i32, conepar_: f64, submem_: &[i32] ) -> Result<(), String>
Replaces a conic constraint.
§Arguments
-
k_Index of the cone. -
ct_Specifies the type of the cone.See Conetype
-
conepar_For the power cone it denotes the exponent alpha. For other cone types it is unused and can be set to 0. -
submem_Variable subscripts of the members in the cone.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putcone
sourcepub fn put_cone_name(&mut self, j_: i32, name_: &str) -> Result<(), String>
pub fn put_cone_name(&mut self, j_: i32, name_: &str) -> Result<(), String>
Sets the name of a cone.
§Arguments
j_Index of the cone.name_The name of the cone.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putconename
sourcepub fn put_con_name(&mut self, i_: i32, name_: &str) -> Result<(), String>
pub fn put_con_name(&mut self, i_: i32, name_: &str) -> Result<(), String>
Sets the name of a constraint.
§Arguments
i_Index of the constraint.name_The name of the constraint.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putconname
Examples found in repository?
examples/portfolio_2_frontier.rs (line 63)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}More examples
examples/portfolio_5_card.rs (line 95)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}sourcepub fn put_con_solution_i(
&mut self,
i_: i32,
whichsol_: i32,
sk_: i32,
x_: f64,
sl_: f64,
su_: f64
) -> Result<(), String>
pub fn put_con_solution_i( &mut self, i_: i32, whichsol_: i32, sk_: i32, x_: f64, sl_: f64, su_: f64 ) -> Result<(), String>
Sets the primal and dual solution information for a single constraint.
§Arguments
-
i_Index of the constraint. -
whichsol_Selects a solution.See Soltype
-
sk_Status key of the constraint.See Stakey
-
x_Primal solution value of the constraint. -
sl_Solution value of the dual variable associated with the lower bound. -
su_Solution value of the dual variable associated with the upper bound.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putconsolutioni
sourcepub fn put_c_slice(
&mut self,
first_: i32,
last_: i32,
slice_: &[f64]
) -> Result<(), String>
pub fn put_c_slice( &mut self, first_: i32, last_: i32, slice_: &[f64] ) -> Result<(), String>
Modifies a slice of the linear objective coefficients.
§Arguments
first_First element in the slice of c.last_Last element plus 1 of the slice in c to be changed.slice_New numerical values for the objective coefficients that should be modified.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putcslice
Examples found in repository?
examples/portfolio_2_frontier.rs (line 64)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}More examples
examples/ceo1.rs (line 60)
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fn main() -> Result<(),String> {
let numcon = 1;
let numvar = 3;
let bkc = mosek::Boundkey::FX;
let blc = 1.0;
let buc = 1.0;
let bkx = vec![ Boundkey::FR,
Boundkey::FR,
Boundkey::FR ];
let blx = vec![ -INF, -INF, -INF ];
let bux = vec![ INF, INF, INF ];
let c = vec![ 1.0, 1.0, 0.0 ];
let a = vec![ 1.0, 1.0, 1.0 ];
let asub = vec![0, 1, 2];
//let csub = new int[numvar];
//double[] xx = new double[numvar];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|task| task.with_callback(
&mut |caller| { println!("caller = {}",caller); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
/* Define the linear part of the problem */
task.put_c_slice(0, numvar, c.as_slice())?;
task.put_a_row(0, asub.as_slice(), a.as_slice())?;
task.put_con_bound(0, bkc, blc, buc)?;
task.put_var_bound_slice(0, numvar, bkx.as_slice(), blx.as_slice(), bux.as_slice())?;
/* Add a conic constraint */
task.append_afes(3)?;
let afeidxs = vec![0, 1, 2 ];
let b = vec![0.0,0.0,0.0];
let domidx = task.append_primal_exp_cone_domain()?;
task.put_afe_f_row_list(afeidxs.as_slice(),
vec![1,1,1].as_slice(),
vec![0,1,2].as_slice(),
vec![0,1,2].as_slice(),
vec![1.0,1.0,1.0].as_slice())?;
task.append_acc(domidx,afeidxs.as_slice(),b.as_slice())?;
task.put_obj_sense(Objsense::MINIMIZE)?;
println!("optimize");
/* Solve the problem */
task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
/* Get status information about the solution */
let solsta = task.get_sol_sta(Soltype::ITR)?;
assert!(solsta == Solsta::OPTIMAL);
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITR, & mut xx[..])?;
println!("Optimal primal solution");
for j in 0..numvar as usize {
println!("x[{}]: {:.4}",j,xx[j]);
}
Ok(())
}))
}sourcepub fn put_djc(
&mut self,
djcidx_: i64,
domidxlist_: &[i64],
afeidxlist_: &[i64],
b_: &[f64],
termsizelist_: &[i64]
) -> Result<(), String>
pub fn put_djc( &mut self, djcidx_: i64, domidxlist_: &[i64], afeidxlist_: &[i64], b_: &[f64], termsizelist_: &[i64] ) -> Result<(), String>
Inputs a disjunctive constraint.
§Arguments
djcidx_Index of the disjunctive constraint.domidxlist_List of domain indexes.afeidxlist_List of affine expression indexes.b_The vector of constant terms modifying affine expressions.termsizelist_List of term sizes.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putdjc
sourcepub fn put_djc_name(&mut self, djcidx_: i64, name_: &str) -> Result<(), String>
pub fn put_djc_name(&mut self, djcidx_: i64, name_: &str) -> Result<(), String>
Sets the name of a disjunctive constraint.
§Arguments
djcidx_Index of the disjunctive constraint.name_The name of the disjunctive constraint.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putdjcname
sourcepub fn put_djc_slice(
&mut self,
idxfirst_: i64,
idxlast_: i64,
domidxlist_: &[i64],
afeidxlist_: &[i64],
b_: &[f64],
termsizelist_: &[i64],
termsindjc_: &[i64]
) -> Result<(), String>
pub fn put_djc_slice( &mut self, idxfirst_: i64, idxlast_: i64, domidxlist_: &[i64], afeidxlist_: &[i64], b_: &[f64], termsizelist_: &[i64], termsindjc_: &[i64] ) -> Result<(), String>
Inputs a slice of disjunctive constraints.
§Arguments
idxfirst_Index of the first disjunctive constraint in the slice.idxlast_Index of the last disjunctive constraint in the slice plus 1.domidxlist_List of domain indexes.afeidxlist_List of affine expression indexes.b_The vector of constant terms modifying affine expressions. Optional.termsizelist_List of term sizes.termsindjc_Number of terms in each of the disjunctive constraints in the slice.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putdjcslice
sourcepub fn put_domain_name(
&mut self,
domidx_: i64,
name_: &str
) -> Result<(), String>
pub fn put_domain_name( &mut self, domidx_: i64, name_: &str ) -> Result<(), String>
Sets the name of a domain.
§Arguments
domidx_Index of the domain.name_The name of the domain.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putdomainname
sourcepub fn put_dou_param(
&mut self,
param_: i32,
parvalue_: f64
) -> Result<(), String>
pub fn put_dou_param( &mut self, param_: i32, parvalue_: f64 ) -> Result<(), String>
Sets a double parameter.
§Arguments
-
param_Which parameter.See Dparam
-
parvalue_Parameter value.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putdouparam
Examples found in repository?
examples/parameters.rs (line 25)
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fn main() -> Result<(),String> {
let mut task = Task::new().unwrap();
println!("Test MOSEK parameter get/set functions");
// Set log level (integer parameter)
task.put_int_param(Iparam::LOG, 1)?;
// Select interior-point optimizer... (integer parameter)
task.put_int_param(Iparam::OPTIMIZER, Optimizertype::INTPNT)?;
// ... without basis identification (integer parameter)
task.put_int_param(Iparam::INTPNT_BASIS,Basindtype::NEVER)?;
// Set relative gap tolerance (double parameter)
task.put_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP, 1.0e-7)?;
// The same using explicit string names
task.put_param("MSK_DPAR_INTPNT_CO_TOL_REL_GAP", "1.0e-7")?;
task.put_na_dou_param("MSK_DPAR_INTPNT_CO_TOL_REL_GAP", 1.0e-7 )?;
// Incorrect value
if let Err(_) = task.put_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP, -1.0) {
println!("Wrong parameter value");
}
let param = task.get_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP)?;
println!("Current value for parameter intpnt_co_tol_rel_gap = $param");
// Define and solve an optimization problem here
// optimize(task,)
// After optimization:
println!("Get MOSEK information items");
let tm = task.get_dou_inf(Dinfitem::OPTIMIZER_TIME)?;
let iter = task.get_int_inf(Iinfitem::INTPNT_ITER)?;
println!("Time: {}",tm);
println!("Iterations: {}",iter);
Ok(())
}More examples
examples/concurrent1.rs (line 112)
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fn concurrent1(data : FileOrText, timelimit : Option<String>) -> Result<(),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
match data {
FileOrText::File(fname) => task.read_data(fname.as_str())?,
FileOrText::Text(text) => task.read_ptf_string(text.as_str())?
}
if let Some(timelimit) = timelimit {
task.put_dou_param(mosek::Dparam::OPTIMIZER_MAX_TIME, timelimit.parse().unwrap())?;
}
let numintvar = task.get_num_int_var()?;
let r = if numintvar == 0 {
let optimizers = &[mosek::Optimizertype::CONIC,
mosek::Optimizertype::DUAL_SIMPLEX,
mosek::Optimizertype::PRIMAL_SIMPLEX];
optimize_concurrent(& mut task, optimizers)
}
else {
let seeds = &[ 42, 13, 71749373 ];
optimize_concurrent_mio(& mut task, seeds)
};
let sense = task.get_obj_sense()?;
// Pick the feasible result. For non-integer problems all
// solutions should be the same if more than one is returned, but
// for integer problems tasks may have hit the time limit and
// returned non-optimal solutions.
let n = r.len();
if n == 0 {
println!("All optimizers failed.");
}
else if numintvar > 0 {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
ii.iter().zip(tasks.iter()).enumerate()
.filter_map(|(k,(_i,t))|
match (*t).solution_def(Soltype::ITG) {
Ok(true) => match t.get_sol_sta(Soltype::ITG).unwrap() {
Solsta::PRIM_FEAS|Solsta::INTEGER_OPTIMAL => Some((k,t.get_primal_obj(Soltype::ITG).unwrap())),
_ => None
},
_ => None
})
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
else {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
tasks.iter().enumerate()
.filter_map(|(k,t)|
match t.get_sol_sta(Soltype::BAS) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::BAS).unwrap())),
_ => None
}.or_else(|| match t.get_sol_sta(Soltype::ITR) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::ITR).unwrap())),
_ => None
}))
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
Result::Ok(())
}examples/milo1.rs (line 74)
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fn main() -> Result<(),String> {
let numcon : i32 = 2;
let numvar : i32 = 2;
let infinity = 0.0; // only for symbolic purposes, value never used
let bkc = vec![Boundkey::UP, Boundkey::LO];
let blc = vec![ -infinity, -4.0 ];
let buc = vec![ 250.0, infinity ];
let bkx = vec![ Boundkey::LO, Boundkey::LO ];
let blx = vec![ 0.0, 0.0 ];
let bux = vec![ infinity, infinity ];
let c = vec![1.0, 0.64];
let asub = vec![0, 1,
0, 1];
let aval = vec![50.0, 3.0, 31.0, -2.0];
let ptrb : Vec<usize> = vec![ 0, 2 ];
let ptre : Vec<usize> = vec![ 2, 4 ];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| task.with_itg_sol_callback(
&mut |xx| { println!("Found a new solution = {:?}",xx); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
for ((((j,cj),bk),bl),bu) in (0..numvar).zip(c.iter()).zip(bkx.iter()).zip(blx.iter()).zip(bux.iter()) {
/* Set the linear term c_j in the objective.*/
task.put_c_j(j, *cj)?;
/* Set the bounds on variable j.
blx[j] <= x_j <= bux[j] */
task.put_var_bound(j, *bk, *bl, *bu)?;
/* Input column j of A */
task.put_a_col(j, /* Variable (column) index.*/
&asub[ptrb[j as usize]..ptre[j as usize]], /* Row index of non-zeros in column j.*/
&aval[ptrb[j as usize]..ptre[j as usize]])?; /* Non-zero Values of column j. */
}
// Set the bounds on constraints.
// for i=1, ...,numcon : blc[i] <= constraint i <= buc[i]
for (((i,bk),bl),bu) in (0..numcon).zip(bkc.iter()).zip(blc.iter()).zip(buc.iter()) {
task.put_con_bound(i, *bk, *bl, *bu)?;
}
/* Specify integer variables. */
for j in 0..numvar {
task.put_var_type(j, Variabletype::TYPE_INT)?;
}
/* Set max solution time */
task.put_dou_param(Dparam::MIO_MAX_TIME, 60.0)?;
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITG, xx.as_mut_slice())?;
/* Get status information about the solution */
match task.get_sol_sta(Soltype::ITG)? {
Solsta::INTEGER_OPTIMAL => {
println!("Optimal solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::PRIM_FEAS => {
println!("Feasible solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::UNKNOWN => {
match task.get_pro_sta(Soltype::ITG)? {
Prosta::PRIM_INFEAS_OR_UNBOUNDED => {
println!("Problem status Infeasible or unbounded");
}
Prosta::PRIM_INFEAS => {
println!("Problem status Infeasible.");
}
Prosta::UNKNOWN => {
println!("Problem status unknown.");
}
_ => {
println!("Other problem status.");
}
}
}
_ => {
println!("Other solution status");
}
}
Ok(())
}))
}sourcepub fn put_int_param(
&mut self,
param_: i32,
parvalue_: i32
) -> Result<(), String>
pub fn put_int_param( &mut self, param_: i32, parvalue_: i32 ) -> Result<(), String>
Sets an integer parameter.
§Arguments
-
param_Which parameter.See Iparam
-
parvalue_Parameter value.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putintparam
Examples found in repository?
examples/concurrent1.rs (line 48)
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fn optimize_concurrent(task : &mut mosek::Task,
optimizers : &[i32]) -> Vec<(usize,i32,mosek::Task)> {
let stop = Arc::new(Mutex::new(false));
optimizers.iter().enumerate()
.filter_map(|(i,&ot)|
if let Some(mut t) = task.clone() {
if let Err(_) = t.put_int_param(mosek::Iparam::OPTIMIZER, ot as i32) { None }
else {
let stopopt = Arc::clone(&stop);
Some((i,thread::spawn(move || optimize(t,stopopt))))
}
}
else { None })
.filter_map(|(i,th)|
match th.join().unwrap() {
None => None,
Some((r,t)) => Some((i,r,t)) } )
.collect()
}
fn optimize_concurrent_mio(task : & mut mosek::Task,
seeds : &[i32]) -> Vec<(usize,i32,mosek::Task)> {
let stop = Arc::new(Mutex::new(false));
seeds.iter().enumerate()
.filter_map(|(i,&seed)| {
if let Some(mut t) = task.clone() {
if let Err(_) = t.put_int_param(mosek::Iparam::MIO_SEED, seed) { None }
else {
let stopopt = Arc::clone(&stop);
Some((i,thread::spawn(move || optimize(t,stopopt))))
}
}
else { None }})
.filter_map(|(i,th)|
match th.join().unwrap() {
None => None,
Some((r,t)) => Some((i,r,t)) } )
.collect()
}More examples
examples/callback.rs (line 118)
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fn callbackmain(which : &str, data : FileOrText) -> Result<(),String> {
/* Create the optimization task. */
let mut task = Task::new().unwrap();
match data {
FileOrText::Text(data) => { task.read_ptf_string(data)? },
FileOrText::File(fname) => { task.read_data(fname)? }
}
task.write_data("callback.ptf")?;
match which {
"psim" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::PRIMAL_SIMPLEX)?,
"dsim" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::DUAL_SIMPLEX)?,
"intpnt" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::INTPNT)?,
s => return Err(format!("Invalid argument '{}'",s))
}
/* Directs the log task stream to the 'printstr' function. */
task.with_stream_callback(
Streamtype::LOG,
& mut |msg| print!("{}",msg),
|task|
task.with_info_callback(
& mut callback,
|task|
task.optimize()
)
)?;
Result::Ok(())
}examples/parameters.rs (line 19)
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fn main() -> Result<(),String> {
let mut task = Task::new().unwrap();
println!("Test MOSEK parameter get/set functions");
// Set log level (integer parameter)
task.put_int_param(Iparam::LOG, 1)?;
// Select interior-point optimizer... (integer parameter)
task.put_int_param(Iparam::OPTIMIZER, Optimizertype::INTPNT)?;
// ... without basis identification (integer parameter)
task.put_int_param(Iparam::INTPNT_BASIS,Basindtype::NEVER)?;
// Set relative gap tolerance (double parameter)
task.put_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP, 1.0e-7)?;
// The same using explicit string names
task.put_param("MSK_DPAR_INTPNT_CO_TOL_REL_GAP", "1.0e-7")?;
task.put_na_dou_param("MSK_DPAR_INTPNT_CO_TOL_REL_GAP", 1.0e-7 )?;
// Incorrect value
if let Err(_) = task.put_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP, -1.0) {
println!("Wrong parameter value");
}
let param = task.get_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP)?;
println!("Current value for parameter intpnt_co_tol_rel_gap = $param");
// Define and solve an optimization problem here
// optimize(task,)
// After optimization:
println!("Get MOSEK information items");
let tm = task.get_dou_inf(Dinfitem::OPTIMIZER_TIME)?;
let iter = task.get_int_inf(Iinfitem::INTPNT_ITER)?;
println!("Time: {}",tm);
println!("Iterations: {}",iter);
Ok(())
}examples/parallel.rs (line 40)
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fn parallel(files : Vec<FileOrText>) -> Result<(),String> {
// Create an example list of tasks to optimize
let mut tasks : Vec<(String,Task)> = files.iter().filter_map(|fname| {
let mut t = Task::new().unwrap();
match fname {
FileOrText::File(fname) => {
if let Err(_) = t.read_data(fname.as_str()) { None }
else {
t.put_int_param(mosek::Iparam::NUM_THREADS, 2).unwrap();
Some((fname.as_str().to_string(),t))
}
},
FileOrText::Text(data) => {
if let Err(_) = t.read_ptf_string(data.as_str()) { None }
else {
t.put_int_param(mosek::Iparam::NUM_THREADS, 2).unwrap();
Some(("-".to_string(),t))
}
}
}
}).collect();
let mut res = vec![0i32; tasks.len()];
let mut trm = vec![0i32; tasks.len()];
{
let taskrs : Vec<& mut Task> = tasks.iter_mut().map(|(_a,b)| b).collect();
// Size of thread pool available for all tasks
let threadpoolsize : i32 = 6;
// Optimize all the given tasks in parallel
mosek::optimize_batch(false, // No race
-1.0, // No time limit
threadpoolsize,
taskrs.as_slice(), // Array of tasks to optimize
trm.as_mut_slice(),
res.as_mut_slice())?;
}
for (resi,trmi,(fname,ti)) in izip!(res,trm,tasks.iter()) {
println!("Task {} res {} trm {} obj_val {} time {}",
fname,
resi,
trmi,
ti.get_dou_inf(mosek::Dinfitem::INTPNT_PRIMAL_OBJ)?,
ti.get_dou_inf(mosek::Dinfitem::OPTIMIZER_TIME)?);
}
Ok(())
}examples/reoptimization.rs (line 126)
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fn main() -> Result<(),String> {
let numcon = 3;
let numvar = 3;
let c = &[1.5, 2.5, 3.0 ];
let bkc = &[ Boundkey::UP,
Boundkey::UP,
Boundkey::UP ];
let blc = &[ -INF,
-INF,
-INF ];
let buc = &[ 100000.0,
50000.0,
60000.0 ];
let bkx = &[ Boundkey::LO,
Boundkey::LO,
Boundkey::LO
];
let blx = &[ 0.0, 0.0, 0.0 ];
let bux = &[ INF,
INF,
INF ];
let asub = &[
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ] ];
let aval = &[
&[ 2.0, 3.0, 2.0 ],
&[ 4.0, 2.0, 3.0 ],
&[ 3.0, 3.0, 2.0 ] ];
let mut task = Task::new().unwrap();
/* Append the constraints. */
task.append_cons(numcon)?;
/* Append the variables. */
task.append_vars(numvar)?;
/* Put C. */
for (j,&cj) in (0..numvar).zip(c.iter()) {
task.put_c_j(j,cj)?;
}
/* Put constraint bounds. */
for (i,&bki,&bli,&bui) in izip!(0..numcon,bkc,blc,buc) {
task.put_con_bound(i, bki, bli, bui)?;
}
/* Put variable bounds. */
for (j,&bki,&bli,&bui) in izip!(0..numvar,bkx,blx,bux) {
task.put_var_bound(j, bki, bli, bui)?;
}
/* Put A. */
if numcon > 0 {
for (j,&asubj,&avalj) in izip!(0..numvar,asub,aval) {
task.put_a_col(j,
asubj,
avalj)?;
}
}
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/****************** Make a change to the A matrix ******************/
task.put_aij(0, 0, 3.0)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/***************** Add a new variable ******************************/
/* Get index of new variable. */
let varidx = task.get_num_var()?;
/* Append a new variable x_3 to the problem */
task.append_vars(1)?;
let numvar = numvar + 1;
/* Set bounds on new varaible */
task.put_var_bound(varidx, Boundkey::LO, 0.0, INF)?;
/* Change objective */
task.put_c_j(varidx, 1.0)?;
/* Put new values in the A matrix */
let acolsub = &[0i32, 2];
let acolval = &[4.0, 1.0];
task.put_a_col(varidx, /* column index */
acolsub,
acolval)?;
/* Change optimizer to simplex free and reoptimize */
task.put_int_param(mosek::Iparam::OPTIMIZER, mosek::Optimizertype::FREE_SIMPLEX)?;
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Add a new constraint ***************************/
/* Get index of new constraint. */
let conidx = task.get_num_con()?;
/* Append a new constraint */
task.append_cons(1)?;
let numcon = numcon + 1;
/* Set bounds on new constraint */
task.put_con_bound(conidx,
Boundkey::UP,
-INF,
30000.0)?;
/* Put new values in the A matrix */
let arowsub = &[0i32, 1, 2, 3 ];
let arowval = &[1.0, 2.0, 1.0, 1.0 ];
task.put_a_row(conidx, /* row index */
arowsub,
arowval)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Change constraint bounds ********************/
let newbkc = &[Boundkey::UP,
Boundkey::UP,
Boundkey::UP,
Boundkey::UP];
let newblc = &[-INF,
-INF,
-INF,
-INF];
let newbuc = &[ 80000.0, 40000.0, 50000.0, 22000.0 ];
task.put_con_bound_slice(0, numcon, newbkc, newblc, newbuc)?;
let _ = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
Ok(())
}sourcepub fn put_max_num_acc(&mut self, maxnumacc_: i64) -> Result<(), String>
pub fn put_max_num_acc(&mut self, maxnumacc_: i64) -> Result<(), String>
Sets the number of preallocated affine conic constraints.
§Arguments
maxnumacc_Number of preallocated affine conic constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putmaxnumacc
sourcepub fn put_max_num_afe(&mut self, maxnumafe_: i64) -> Result<(), String>
pub fn put_max_num_afe(&mut self, maxnumafe_: i64) -> Result<(), String>
Sets the number of preallocated affine expressions in the optimization task.
§Arguments
maxnumafe_Number of preallocated affine expressions.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putmaxnumafe
sourcepub fn put_max_num_a_nz(&mut self, maxnumanz_: i64) -> Result<(), String>
pub fn put_max_num_a_nz(&mut self, maxnumanz_: i64) -> Result<(), String>
Sets the number of preallocated non-zero entries in the linear coefficient matrix.
§Arguments
maxnumanz_New size of the storage reserved for storing the linear coefficient matrix.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putmaxnumanz
sourcepub fn put_max_num_barvar(&mut self, maxnumbarvar_: i32) -> Result<(), String>
pub fn put_max_num_barvar(&mut self, maxnumbarvar_: i32) -> Result<(), String>
Sets the number of preallocated symmetric matrix variables.
§Arguments
maxnumbarvar_Number of preallocated symmetric matrix variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putmaxnumbarvar
sourcepub fn put_max_num_con(&mut self, maxnumcon_: i32) -> Result<(), String>
pub fn put_max_num_con(&mut self, maxnumcon_: i32) -> Result<(), String>
Sets the number of preallocated constraints in the optimization task.
§Arguments
maxnumcon_Number of preallocated constraints in the optimization task.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putmaxnumcon
sourcepub fn put_max_num_cone(&mut self, maxnumcone_: i32) -> Result<(), String>
pub fn put_max_num_cone(&mut self, maxnumcone_: i32) -> Result<(), String>
Sets the number of preallocated conic constraints in the optimization task.
§Arguments
maxnumcone_Number of preallocated conic constraints in the optimization task.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putmaxnumcone
sourcepub fn put_max_num_djc(&mut self, maxnumdjc_: i64) -> Result<(), String>
pub fn put_max_num_djc(&mut self, maxnumdjc_: i64) -> Result<(), String>
Sets the number of preallocated disjunctive constraints.
§Arguments
maxnumdjc_Number of preallocated disjunctive constraints in the task.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putmaxnumdjc
sourcepub fn put_max_num_domain(&mut self, maxnumdomain_: i64) -> Result<(), String>
pub fn put_max_num_domain(&mut self, maxnumdomain_: i64) -> Result<(), String>
Sets the number of preallocated domains in the optimization task.
§Arguments
maxnumdomain_Number of preallocated domains.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putmaxnumdomain
sourcepub fn put_max_num_q_nz(&mut self, maxnumqnz_: i64) -> Result<(), String>
pub fn put_max_num_q_nz(&mut self, maxnumqnz_: i64) -> Result<(), String>
Sets the number of preallocated non-zero entries in quadratic terms.
§Arguments
maxnumqnz_Number of non-zero elements preallocated in quadratic coefficient matrices.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putmaxnumqnz
sourcepub fn put_max_num_var(&mut self, maxnumvar_: i32) -> Result<(), String>
pub fn put_max_num_var(&mut self, maxnumvar_: i32) -> Result<(), String>
Sets the number of preallocated variables in the optimization task.
§Arguments
maxnumvar_Number of preallocated variables in the optimization task.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putmaxnumvar
sourcepub fn put_na_dou_param(
&mut self,
paramname_: &str,
parvalue_: f64
) -> Result<(), String>
pub fn put_na_dou_param( &mut self, paramname_: &str, parvalue_: f64 ) -> Result<(), String>
Sets a double parameter.
§Arguments
paramname_Name of a parameter.parvalue_Parameter value.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putnadouparam
Examples found in repository?
examples/parameters.rs (line 29)
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fn main() -> Result<(),String> {
let mut task = Task::new().unwrap();
println!("Test MOSEK parameter get/set functions");
// Set log level (integer parameter)
task.put_int_param(Iparam::LOG, 1)?;
// Select interior-point optimizer... (integer parameter)
task.put_int_param(Iparam::OPTIMIZER, Optimizertype::INTPNT)?;
// ... without basis identification (integer parameter)
task.put_int_param(Iparam::INTPNT_BASIS,Basindtype::NEVER)?;
// Set relative gap tolerance (double parameter)
task.put_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP, 1.0e-7)?;
// The same using explicit string names
task.put_param("MSK_DPAR_INTPNT_CO_TOL_REL_GAP", "1.0e-7")?;
task.put_na_dou_param("MSK_DPAR_INTPNT_CO_TOL_REL_GAP", 1.0e-7 )?;
// Incorrect value
if let Err(_) = task.put_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP, -1.0) {
println!("Wrong parameter value");
}
let param = task.get_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP)?;
println!("Current value for parameter intpnt_co_tol_rel_gap = $param");
// Define and solve an optimization problem here
// optimize(task,)
// After optimization:
println!("Get MOSEK information items");
let tm = task.get_dou_inf(Dinfitem::OPTIMIZER_TIME)?;
let iter = task.get_int_inf(Iinfitem::INTPNT_ITER)?;
println!("Time: {}",tm);
println!("Iterations: {}",iter);
Ok(())
}sourcepub fn put_na_int_param(
&mut self,
paramname_: &str,
parvalue_: i32
) -> Result<(), String>
pub fn put_na_int_param( &mut self, paramname_: &str, parvalue_: i32 ) -> Result<(), String>
Sets an integer parameter.
§Arguments
paramname_Name of a parameter.parvalue_Parameter value.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putnaintparam
sourcepub fn put_na_str_param(
&mut self,
paramname_: &str,
parvalue_: &str
) -> Result<(), String>
pub fn put_na_str_param( &mut self, paramname_: &str, parvalue_: &str ) -> Result<(), String>
Sets a string parameter.
§Arguments
paramname_Name of a parameter.parvalue_Parameter value.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putnastrparam
sourcepub fn put_obj_name(&mut self, objname_: &str) -> Result<(), String>
pub fn put_obj_name(&mut self, objname_: &str) -> Result<(), String>
Assigns a new name to the objective.
§Arguments
objname_Name of the objective.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putobjname
sourcepub fn put_obj_sense(&mut self, sense_: i32) -> Result<(), String>
pub fn put_obj_sense(&mut self, sense_: i32) -> Result<(), String>
Sets the objective sense.
§Arguments
-
sense_The objective sense of the taskSee Objsense
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putobjsense
Examples found in repository?
examples/helloworld.rs (line 23)
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fn main() -> Result<(),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
task.append_vars(1)?; // 1 variable x
task.put_c_j(0, 1.0)?; // c_0 = 1.0
task.put_var_bound(0, Boundkey::RA, 2.0, 3.0)?; // 2.0 <= x <= 3.0
task.put_obj_sense(Objsense::MINIMIZE)?; // minimize
task.optimize()?; // Optimize
let mut x = vec![0.0; 1];
task.get_xx(Soltype::ITR, x.as_mut_slice())?; // Get solution
println!("Solution x = {}", x[0]); // Print solution
return Result::Ok(());
}More examples
examples/portfolio_2_frontier.rs (line 53)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}examples/ceo1.rs (line 77)
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fn main() -> Result<(),String> {
let numcon = 1;
let numvar = 3;
let bkc = mosek::Boundkey::FX;
let blc = 1.0;
let buc = 1.0;
let bkx = vec![ Boundkey::FR,
Boundkey::FR,
Boundkey::FR ];
let blx = vec![ -INF, -INF, -INF ];
let bux = vec![ INF, INF, INF ];
let c = vec![ 1.0, 1.0, 0.0 ];
let a = vec![ 1.0, 1.0, 1.0 ];
let asub = vec![0, 1, 2];
//let csub = new int[numvar];
//double[] xx = new double[numvar];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|task| task.with_callback(
&mut |caller| { println!("caller = {}",caller); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
/* Define the linear part of the problem */
task.put_c_slice(0, numvar, c.as_slice())?;
task.put_a_row(0, asub.as_slice(), a.as_slice())?;
task.put_con_bound(0, bkc, blc, buc)?;
task.put_var_bound_slice(0, numvar, bkx.as_slice(), blx.as_slice(), bux.as_slice())?;
/* Add a conic constraint */
task.append_afes(3)?;
let afeidxs = vec![0, 1, 2 ];
let b = vec![0.0,0.0,0.0];
let domidx = task.append_primal_exp_cone_domain()?;
task.put_afe_f_row_list(afeidxs.as_slice(),
vec![1,1,1].as_slice(),
vec![0,1,2].as_slice(),
vec![0,1,2].as_slice(),
vec![1.0,1.0,1.0].as_slice())?;
task.append_acc(domidx,afeidxs.as_slice(),b.as_slice())?;
task.put_obj_sense(Objsense::MINIMIZE)?;
println!("optimize");
/* Solve the problem */
task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
/* Get status information about the solution */
let solsta = task.get_sol_sta(Soltype::ITR)?;
assert!(solsta == Solsta::OPTIMAL);
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITR, & mut xx[..])?;
println!("Optimal primal solution");
for j in 0..numvar as usize {
println!("x[{}]: {:.4}",j,xx[j]);
}
Ok(())
}))
}examples/reoptimization.rs (line 80)
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fn main() -> Result<(),String> {
let numcon = 3;
let numvar = 3;
let c = &[1.5, 2.5, 3.0 ];
let bkc = &[ Boundkey::UP,
Boundkey::UP,
Boundkey::UP ];
let blc = &[ -INF,
-INF,
-INF ];
let buc = &[ 100000.0,
50000.0,
60000.0 ];
let bkx = &[ Boundkey::LO,
Boundkey::LO,
Boundkey::LO
];
let blx = &[ 0.0, 0.0, 0.0 ];
let bux = &[ INF,
INF,
INF ];
let asub = &[
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ] ];
let aval = &[
&[ 2.0, 3.0, 2.0 ],
&[ 4.0, 2.0, 3.0 ],
&[ 3.0, 3.0, 2.0 ] ];
let mut task = Task::new().unwrap();
/* Append the constraints. */
task.append_cons(numcon)?;
/* Append the variables. */
task.append_vars(numvar)?;
/* Put C. */
for (j,&cj) in (0..numvar).zip(c.iter()) {
task.put_c_j(j,cj)?;
}
/* Put constraint bounds. */
for (i,&bki,&bli,&bui) in izip!(0..numcon,bkc,blc,buc) {
task.put_con_bound(i, bki, bli, bui)?;
}
/* Put variable bounds. */
for (j,&bki,&bli,&bui) in izip!(0..numvar,bkx,blx,bux) {
task.put_var_bound(j, bki, bli, bui)?;
}
/* Put A. */
if numcon > 0 {
for (j,&asubj,&avalj) in izip!(0..numvar,asub,aval) {
task.put_a_col(j,
asubj,
avalj)?;
}
}
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/****************** Make a change to the A matrix ******************/
task.put_aij(0, 0, 3.0)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/***************** Add a new variable ******************************/
/* Get index of new variable. */
let varidx = task.get_num_var()?;
/* Append a new variable x_3 to the problem */
task.append_vars(1)?;
let numvar = numvar + 1;
/* Set bounds on new varaible */
task.put_var_bound(varidx, Boundkey::LO, 0.0, INF)?;
/* Change objective */
task.put_c_j(varidx, 1.0)?;
/* Put new values in the A matrix */
let acolsub = &[0i32, 2];
let acolval = &[4.0, 1.0];
task.put_a_col(varidx, /* column index */
acolsub,
acolval)?;
/* Change optimizer to simplex free and reoptimize */
task.put_int_param(mosek::Iparam::OPTIMIZER, mosek::Optimizertype::FREE_SIMPLEX)?;
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Add a new constraint ***************************/
/* Get index of new constraint. */
let conidx = task.get_num_con()?;
/* Append a new constraint */
task.append_cons(1)?;
let numcon = numcon + 1;
/* Set bounds on new constraint */
task.put_con_bound(conidx,
Boundkey::UP,
-INF,
30000.0)?;
/* Put new values in the A matrix */
let arowsub = &[0i32, 1, 2, 3 ];
let arowval = &[1.0, 2.0, 1.0, 1.0 ];
task.put_a_row(conidx, /* row index */
arowsub,
arowval)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Change constraint bounds ********************/
let newbkc = &[Boundkey::UP,
Boundkey::UP,
Boundkey::UP,
Boundkey::UP];
let newblc = &[-INF,
-INF,
-INF,
-INF];
let newbuc = &[ 80000.0, 40000.0, 50000.0, 22000.0 ];
task.put_con_bound_slice(0, numcon, newbkc, newblc, newbuc)?;
let _ = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
Ok(())
}examples/portfolio_5_card.rs (line 85)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}examples/milo1.rs (line 77)
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fn main() -> Result<(),String> {
let numcon : i32 = 2;
let numvar : i32 = 2;
let infinity = 0.0; // only for symbolic purposes, value never used
let bkc = vec![Boundkey::UP, Boundkey::LO];
let blc = vec![ -infinity, -4.0 ];
let buc = vec![ 250.0, infinity ];
let bkx = vec![ Boundkey::LO, Boundkey::LO ];
let blx = vec![ 0.0, 0.0 ];
let bux = vec![ infinity, infinity ];
let c = vec![1.0, 0.64];
let asub = vec![0, 1,
0, 1];
let aval = vec![50.0, 3.0, 31.0, -2.0];
let ptrb : Vec<usize> = vec![ 0, 2 ];
let ptre : Vec<usize> = vec![ 2, 4 ];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| task.with_itg_sol_callback(
&mut |xx| { println!("Found a new solution = {:?}",xx); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
for ((((j,cj),bk),bl),bu) in (0..numvar).zip(c.iter()).zip(bkx.iter()).zip(blx.iter()).zip(bux.iter()) {
/* Set the linear term c_j in the objective.*/
task.put_c_j(j, *cj)?;
/* Set the bounds on variable j.
blx[j] <= x_j <= bux[j] */
task.put_var_bound(j, *bk, *bl, *bu)?;
/* Input column j of A */
task.put_a_col(j, /* Variable (column) index.*/
&asub[ptrb[j as usize]..ptre[j as usize]], /* Row index of non-zeros in column j.*/
&aval[ptrb[j as usize]..ptre[j as usize]])?; /* Non-zero Values of column j. */
}
// Set the bounds on constraints.
// for i=1, ...,numcon : blc[i] <= constraint i <= buc[i]
for (((i,bk),bl),bu) in (0..numcon).zip(bkc.iter()).zip(blc.iter()).zip(buc.iter()) {
task.put_con_bound(i, *bk, *bl, *bu)?;
}
/* Specify integer variables. */
for j in 0..numvar {
task.put_var_type(j, Variabletype::TYPE_INT)?;
}
/* Set max solution time */
task.put_dou_param(Dparam::MIO_MAX_TIME, 60.0)?;
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITG, xx.as_mut_slice())?;
/* Get status information about the solution */
match task.get_sol_sta(Soltype::ITG)? {
Solsta::INTEGER_OPTIMAL => {
println!("Optimal solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::PRIM_FEAS => {
println!("Feasible solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::UNKNOWN => {
match task.get_pro_sta(Soltype::ITG)? {
Prosta::PRIM_INFEAS_OR_UNBOUNDED => {
println!("Problem status Infeasible or unbounded");
}
Prosta::PRIM_INFEAS => {
println!("Problem status Infeasible.");
}
Prosta::UNKNOWN => {
println!("Problem status unknown.");
}
_ => {
println!("Other problem status.");
}
}
}
_ => {
println!("Other solution status");
}
}
Ok(())
}))
}sourcepub fn put_optserver_host(&mut self, host_: &str) -> Result<(), String>
pub fn put_optserver_host(&mut self, host_: &str) -> Result<(), String>
Specify an OptServer for remote calls.
§Arguments
host_A URL specifying the optimization server to be used.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putoptserverhost
sourcepub fn put_param(
&mut self,
parname_: &str,
parvalue_: &str
) -> Result<(), String>
pub fn put_param( &mut self, parname_: &str, parvalue_: &str ) -> Result<(), String>
Modifies the value of parameter.
§Arguments
parname_Parameter name.parvalue_Parameter value.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putparam
Examples found in repository?
examples/parameters.rs (line 28)
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fn main() -> Result<(),String> {
let mut task = Task::new().unwrap();
println!("Test MOSEK parameter get/set functions");
// Set log level (integer parameter)
task.put_int_param(Iparam::LOG, 1)?;
// Select interior-point optimizer... (integer parameter)
task.put_int_param(Iparam::OPTIMIZER, Optimizertype::INTPNT)?;
// ... without basis identification (integer parameter)
task.put_int_param(Iparam::INTPNT_BASIS,Basindtype::NEVER)?;
// Set relative gap tolerance (double parameter)
task.put_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP, 1.0e-7)?;
// The same using explicit string names
task.put_param("MSK_DPAR_INTPNT_CO_TOL_REL_GAP", "1.0e-7")?;
task.put_na_dou_param("MSK_DPAR_INTPNT_CO_TOL_REL_GAP", 1.0e-7 )?;
// Incorrect value
if let Err(_) = task.put_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP, -1.0) {
println!("Wrong parameter value");
}
let param = task.get_dou_param(Dparam::INTPNT_CO_TOL_REL_GAP)?;
println!("Current value for parameter intpnt_co_tol_rel_gap = $param");
// Define and solve an optimization problem here
// optimize(task,)
// After optimization:
println!("Get MOSEK information items");
let tm = task.get_dou_inf(Dinfitem::OPTIMIZER_TIME)?;
let iter = task.get_int_inf(Iinfitem::INTPNT_ITER)?;
println!("Time: {}",tm);
println!("Iterations: {}",iter);
Ok(())
}sourcepub fn put_q_con(
&mut self,
qcsubk_: &[i32],
qcsubi_: &[i32],
qcsubj_: &[i32],
qcval_: &[f64]
) -> Result<(), String>
pub fn put_q_con( &mut self, qcsubk_: &[i32], qcsubi_: &[i32], qcsubj_: &[i32], qcval_: &[f64] ) -> Result<(), String>
Replaces all quadratic terms in constraints.
§Arguments
qcsubk_Constraint subscripts for quadratic coefficients.qcsubi_Row subscripts for quadratic constraint matrix.qcsubj_Column subscripts for quadratic constraint matrix.qcval_Quadratic constraint coefficient values.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putqcon
sourcepub fn put_q_con_k(
&mut self,
k_: i32,
qcsubi_: &[i32],
qcsubj_: &[i32],
qcval_: &[f64]
) -> Result<(), String>
pub fn put_q_con_k( &mut self, k_: i32, qcsubi_: &[i32], qcsubj_: &[i32], qcval_: &[f64] ) -> Result<(), String>
Replaces all quadratic terms in a single constraint.
§Arguments
k_The constraint in which the new quadratic elements are inserted.qcsubi_Row subscripts for quadratic constraint matrix.qcsubj_Column subscripts for quadratic constraint matrix.qcval_Quadratic constraint coefficient values.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putqconk
sourcepub fn put_q_obj(
&mut self,
qosubi_: &[i32],
qosubj_: &[i32],
qoval_: &[f64]
) -> Result<(), String>
pub fn put_q_obj( &mut self, qosubi_: &[i32], qosubj_: &[i32], qoval_: &[f64] ) -> Result<(), String>
Replaces all quadratic terms in the objective.
§Arguments
qosubi_Row subscripts for quadratic objective coefficients.qosubj_Column subscripts for quadratic objective coefficients.qoval_Quadratic objective coefficient values.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putqobj
sourcepub fn put_q_obj_i_j(
&mut self,
i_: i32,
j_: i32,
qoij_: f64
) -> Result<(), String>
pub fn put_q_obj_i_j( &mut self, i_: i32, j_: i32, qoij_: f64 ) -> Result<(), String>
Replaces one coefficient in the quadratic term in the objective.
§Arguments
i_Row index for the coefficient to be replaced.j_Column index for the coefficient to be replaced.qoij_The new coefficient value.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putqobjij
sourcepub fn put_skc(&mut self, whichsol_: i32, skc_: &[i32]) -> Result<(), String>
pub fn put_skc(&mut self, whichsol_: i32, skc_: &[i32]) -> Result<(), String>
Sets the status keys for the constraints.
§Arguments
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putskc
sourcepub fn put_skc_slice(
&mut self,
whichsol_: i32,
first_: i32,
last_: i32,
skc_: &[i32]
) -> Result<(), String>
pub fn put_skc_slice( &mut self, whichsol_: i32, first_: i32, last_: i32, skc_: &[i32] ) -> Result<(), String>
Sets the status keys for a slice of the constraints.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
skc_Status keys for the constraints.See Stakey
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putskcslice
Examples found in repository?
examples/solvelinear.rs (line 53)
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fn setup(task : & mut mosek::Task,
aval : &[f64],
asub : &[i32],
ptrb : &[i64],
ptre : &[i64],
numvar : i32) -> Result<Vec<i32>,String> {
// mosek.stakey[] skx = new mosek.stakey [numvar];
// mosek.stakey[] skc = new mosek.stakey [numvar];
// for (int i = 0; i < numvar ; ++i) {
// skx[i] = mosek.stakey.bas;
// skc[i] = mosek.stakey.fix;
// }
task.append_vars(numvar)?;
task.append_cons(numvar)?;
task.put_a_col_slice(0,numvar,ptrb,ptre,asub,aval)?;
task.put_con_bound_slice_const(0,numvar,Boundkey::FX,0.0,0.0)?;
task.put_var_bound_slice_const(0,numvar,Boundkey::FR,-INF,INF)?;
/* Define a basic solution by specifying
status keys for variables & constraints. */
task.delete_solution(Soltype::BAS)?;
task.put_skc_slice(Soltype::BAS, 0, numvar, vec![Stakey::FIX; numvar as usize].as_slice())?;
task.put_skx_slice(Soltype::BAS, 0, numvar, vec![Stakey::BAS; numvar as usize].as_slice())?;
let mut basis = vec![0; numvar as usize];
task.init_basis_solve(basis.as_mut_slice())?;
Ok(basis)
}sourcepub fn put_skx(&mut self, whichsol_: i32, skx_: &[i32]) -> Result<(), String>
pub fn put_skx(&mut self, whichsol_: i32, skx_: &[i32]) -> Result<(), String>
Sets the status keys for the scalar variables.
§Arguments
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putskx
sourcepub fn put_skx_slice(
&mut self,
whichsol_: i32,
first_: i32,
last_: i32,
skx_: &[i32]
) -> Result<(), String>
pub fn put_skx_slice( &mut self, whichsol_: i32, first_: i32, last_: i32, skx_: &[i32] ) -> Result<(), String>
Sets the status keys for a slice of the variables.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
skx_Status keys for the variables.See Stakey
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putskxslice
Examples found in repository?
examples/solvelinear.rs (line 54)
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fn setup(task : & mut mosek::Task,
aval : &[f64],
asub : &[i32],
ptrb : &[i64],
ptre : &[i64],
numvar : i32) -> Result<Vec<i32>,String> {
// mosek.stakey[] skx = new mosek.stakey [numvar];
// mosek.stakey[] skc = new mosek.stakey [numvar];
// for (int i = 0; i < numvar ; ++i) {
// skx[i] = mosek.stakey.bas;
// skc[i] = mosek.stakey.fix;
// }
task.append_vars(numvar)?;
task.append_cons(numvar)?;
task.put_a_col_slice(0,numvar,ptrb,ptre,asub,aval)?;
task.put_con_bound_slice_const(0,numvar,Boundkey::FX,0.0,0.0)?;
task.put_var_bound_slice_const(0,numvar,Boundkey::FR,-INF,INF)?;
/* Define a basic solution by specifying
status keys for variables & constraints. */
task.delete_solution(Soltype::BAS)?;
task.put_skc_slice(Soltype::BAS, 0, numvar, vec![Stakey::FIX; numvar as usize].as_slice())?;
task.put_skx_slice(Soltype::BAS, 0, numvar, vec![Stakey::BAS; numvar as usize].as_slice())?;
let mut basis = vec![0; numvar as usize];
task.init_basis_solve(basis.as_mut_slice())?;
Ok(basis)
}sourcepub fn put_slc(&mut self, whichsol_: i32, slc_: &[f64]) -> Result<(), String>
pub fn put_slc(&mut self, whichsol_: i32, slc_: &[f64]) -> Result<(), String>
Sets the slc vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
slc_Dual variables corresponding to the lower bounds on the constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putslc
sourcepub fn put_slc_slice(
&mut self,
whichsol_: i32,
first_: i32,
last_: i32,
slc_: &[f64]
) -> Result<(), String>
pub fn put_slc_slice( &mut self, whichsol_: i32, first_: i32, last_: i32, slc_: &[f64] ) -> Result<(), String>
Sets a slice of the slc vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
slc_Dual variables corresponding to the lower bounds on the constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putslcslice
sourcepub fn put_slx(&mut self, whichsol_: i32, slx_: &[f64]) -> Result<(), String>
pub fn put_slx(&mut self, whichsol_: i32, slx_: &[f64]) -> Result<(), String>
Sets the slx vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
slx_Dual variables corresponding to the lower bounds on the variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putslx
sourcepub fn put_slx_slice(
&mut self,
whichsol_: i32,
first_: i32,
last_: i32,
slx_: &[f64]
) -> Result<(), String>
pub fn put_slx_slice( &mut self, whichsol_: i32, first_: i32, last_: i32, slx_: &[f64] ) -> Result<(), String>
Sets a slice of the slx vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
slx_Dual variables corresponding to the lower bounds on the variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putslxslice
sourcepub fn put_snx(&mut self, whichsol_: i32, sux_: &[f64]) -> Result<(), String>
pub fn put_snx(&mut self, whichsol_: i32, sux_: &[f64]) -> Result<(), String>
Sets the snx vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
sux_Dual variables corresponding to the upper bounds on the variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putsnx
sourcepub fn put_snx_slice(
&mut self,
whichsol_: i32,
first_: i32,
last_: i32,
snx_: &[f64]
) -> Result<(), String>
pub fn put_snx_slice( &mut self, whichsol_: i32, first_: i32, last_: i32, snx_: &[f64] ) -> Result<(), String>
Sets a slice of the snx vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
snx_Dual variables corresponding to the conic constraints on the variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putsnxslice
sourcepub fn put_solution(
&mut self,
whichsol_: i32,
skc_: &[i32],
skx_: &[i32],
skn_: &[i32],
xc_: &[f64],
xx_: &[f64],
y_: &[f64],
slc_: &[f64],
suc_: &[f64],
slx_: &[f64],
sux_: &[f64],
snx_: &[f64]
) -> Result<(), String>
pub fn put_solution( &mut self, whichsol_: i32, skc_: &[i32], skx_: &[i32], skn_: &[i32], xc_: &[f64], xx_: &[f64], y_: &[f64], slc_: &[f64], suc_: &[f64], slx_: &[f64], sux_: &[f64], snx_: &[f64] ) -> Result<(), String>
Inserts a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
skc_Status keys for the constraints.See Stakey
-
skx_Status keys for the variables.See Stakey
-
skn_Status keys for the conic constraints.See Stakey
-
xc_Primal constraint solution. -
xx_Primal variable solution. -
y_Vector of dual variables corresponding to the constraints. -
slc_Dual variables corresponding to the lower bounds on the constraints. -
suc_Dual variables corresponding to the upper bounds on the constraints. -
slx_Dual variables corresponding to the lower bounds on the variables. -
sux_Dual variables corresponding to the upper bounds on the variables. -
snx_Dual variables corresponding to the conic constraints on the variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putsolution
sourcepub fn put_solution_new(
&mut self,
whichsol_: i32,
skc_: &[i32],
skx_: &[i32],
skn_: &[i32],
xc_: &[f64],
xx_: &[f64],
y_: &[f64],
slc_: &[f64],
suc_: &[f64],
slx_: &[f64],
sux_: &[f64],
snx_: &[f64],
doty_: &[f64]
) -> Result<(), String>
pub fn put_solution_new( &mut self, whichsol_: i32, skc_: &[i32], skx_: &[i32], skn_: &[i32], xc_: &[f64], xx_: &[f64], y_: &[f64], slc_: &[f64], suc_: &[f64], slx_: &[f64], sux_: &[f64], snx_: &[f64], doty_: &[f64] ) -> Result<(), String>
Inserts a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
skc_Status keys for the constraints.See Stakey
-
skx_Status keys for the variables.See Stakey
-
skn_Status keys for the conic constraints.See Stakey
-
xc_Primal constraint solution. -
xx_Primal variable solution. -
y_Vector of dual variables corresponding to the constraints. -
slc_Dual variables corresponding to the lower bounds on the constraints. -
suc_Dual variables corresponding to the upper bounds on the constraints. -
slx_Dual variables corresponding to the lower bounds on the variables. -
sux_Dual variables corresponding to the upper bounds on the variables. -
snx_Dual variables corresponding to the conic constraints on the variables. -
doty_Dual variables corresponding to affine conic constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putsolutionnew
sourcepub fn put_solution_y_i(
&mut self,
i_: i32,
whichsol_: i32,
y_: f64
) -> Result<(), String>
pub fn put_solution_y_i( &mut self, i_: i32, whichsol_: i32, y_: f64 ) -> Result<(), String>
Inputs the dual variable of a solution.
§Arguments
-
i_Index of the dual variable. -
whichsol_Selects a solution.See Soltype
-
y_Solution value of the dual variable.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putsolutionyi
sourcepub fn put_str_param(
&mut self,
param_: i32,
parvalue_: &str
) -> Result<(), String>
pub fn put_str_param( &mut self, param_: i32, parvalue_: &str ) -> Result<(), String>
Sets a string parameter.
§Arguments
-
param_Which parameter.See Sparam
-
parvalue_Parameter value.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putstrparam
Examples found in repository?
examples/opt_server_async.rs (line 48)
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fn opt_server_async(inputfile : FileOrText, addr : String, numpolls : usize, cert : Option<String>) -> Result<(),String> {
// Path to certificate, if any
let token = {
Task::new().unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| {
match inputfile {
FileOrText::File(ref filename) => task.read_data(filename.as_str()).unwrap(),
FileOrText::Text(ref data) => task.read_ptf_string(data.as_str()).unwrap()
}
if let Some(ref cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH,cert.as_str())?;
}
task.async_optimize(addr.as_str(),"")
}).expect("Failed to submit async optimization")
};
println!("Task token = '{}'", token);
println!("Setting log stream...");
Task::new().unwrap().with_stream_callback(
Streamtype::LOG,
& mut |msg| print!("{}",msg),
|task| task.with_callback(
&mut|caller| { println!("caller = {}",caller); false },
|task| {
println!("Reading input file '{:?}'...",inputfile);
match inputfile {
FileOrText::File(ref filename) => task.read_data(filename.as_str()).unwrap(),
FileOrText::Text(ref data) => task.read_ptf_string(data.as_str()).unwrap()
}
if let Some(ref cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH,cert.as_str())?;
}
println!("Starting polling loop...");
for i in 0..numpolls {
sleep(Duration::new(1,0));
println!("\tpoll {}...", i);
let mut trm : i32 = 0;
let mut resp : i32 = 0;
let respavailable = task.async_poll(addr.as_str(),
"",
token.as_str(),
& mut resp,
& mut trm)?;
if respavailable {
println!("solution available!");
task.async_get_result(addr.as_str(),
"",
token.as_str(),
& mut resp,
& mut trm)?;
task.solution_summary (Streamtype::LOG)?;
return Ok(());
}
}
println!("max num polls reached, stopping host.");
task.async_stop (addr.as_str(), "", token.as_str())?;
Err("Max num polls".to_string())
}))
}sourcepub fn put_suc(&mut self, whichsol_: i32, suc_: &[f64]) -> Result<(), String>
pub fn put_suc(&mut self, whichsol_: i32, suc_: &[f64]) -> Result<(), String>
Sets the suc vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
suc_Dual variables corresponding to the upper bounds on the constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putsuc
sourcepub fn put_suc_slice(
&mut self,
whichsol_: i32,
first_: i32,
last_: i32,
suc_: &[f64]
) -> Result<(), String>
pub fn put_suc_slice( &mut self, whichsol_: i32, first_: i32, last_: i32, suc_: &[f64] ) -> Result<(), String>
Sets a slice of the suc vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
suc_Dual variables corresponding to the upper bounds on the constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putsucslice
sourcepub fn put_sux(&mut self, whichsol_: i32, sux_: &[f64]) -> Result<(), String>
pub fn put_sux(&mut self, whichsol_: i32, sux_: &[f64]) -> Result<(), String>
Sets the sux vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
sux_Dual variables corresponding to the upper bounds on the variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putsux
sourcepub fn put_sux_slice(
&mut self,
whichsol_: i32,
first_: i32,
last_: i32,
sux_: &[f64]
) -> Result<(), String>
pub fn put_sux_slice( &mut self, whichsol_: i32, first_: i32, last_: i32, sux_: &[f64] ) -> Result<(), String>
Sets a slice of the sux vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
sux_Dual variables corresponding to the upper bounds on the variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putsuxslice
sourcepub fn put_task_name(&mut self, taskname_: &str) -> Result<(), String>
pub fn put_task_name(&mut self, taskname_: &str) -> Result<(), String>
Assigns a new name to the task.
§Arguments
taskname_Name assigned to the task.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.puttaskname
sourcepub fn put_var_bound(
&mut self,
j_: i32,
bkx_: i32,
blx_: f64,
bux_: f64
) -> Result<(), String>
pub fn put_var_bound( &mut self, j_: i32, bkx_: i32, blx_: f64, bux_: f64 ) -> Result<(), String>
Changes the bounds for one variable.
§Arguments
-
j_Index of the variable. -
bkx_New bound key.See Boundkey
-
blx_New lower bound. -
bux_New upper bound.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putvarbound
Examples found in repository?
examples/helloworld.rs (line 22)
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fn main() -> Result<(),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
task.append_vars(1)?; // 1 variable x
task.put_c_j(0, 1.0)?; // c_0 = 1.0
task.put_var_bound(0, Boundkey::RA, 2.0, 3.0)?; // 2.0 <= x <= 3.0
task.put_obj_sense(Objsense::MINIMIZE)?; // minimize
task.optimize()?; // Optimize
let mut x = vec![0.0; 1];
task.get_xx(Soltype::ITR, x.as_mut_slice())?; // Get solution
println!("Solution x = {}", x[0]); // Print solution
return Result::Ok(());
}More examples
examples/portfolio_2_frontier.rs (line 71)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}examples/reoptimization.rs (line 67)
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fn main() -> Result<(),String> {
let numcon = 3;
let numvar = 3;
let c = &[1.5, 2.5, 3.0 ];
let bkc = &[ Boundkey::UP,
Boundkey::UP,
Boundkey::UP ];
let blc = &[ -INF,
-INF,
-INF ];
let buc = &[ 100000.0,
50000.0,
60000.0 ];
let bkx = &[ Boundkey::LO,
Boundkey::LO,
Boundkey::LO
];
let blx = &[ 0.0, 0.0, 0.0 ];
let bux = &[ INF,
INF,
INF ];
let asub = &[
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ],
&[ 0i32, 1, 2 ] ];
let aval = &[
&[ 2.0, 3.0, 2.0 ],
&[ 4.0, 2.0, 3.0 ],
&[ 3.0, 3.0, 2.0 ] ];
let mut task = Task::new().unwrap();
/* Append the constraints. */
task.append_cons(numcon)?;
/* Append the variables. */
task.append_vars(numvar)?;
/* Put C. */
for (j,&cj) in (0..numvar).zip(c.iter()) {
task.put_c_j(j,cj)?;
}
/* Put constraint bounds. */
for (i,&bki,&bli,&bui) in izip!(0..numcon,bkc,blc,buc) {
task.put_con_bound(i, bki, bli, bui)?;
}
/* Put variable bounds. */
for (j,&bki,&bli,&bui) in izip!(0..numvar,bkx,blx,bux) {
task.put_var_bound(j, bki, bli, bui)?;
}
/* Put A. */
if numcon > 0 {
for (j,&asubj,&avalj) in izip!(0..numvar,asub,aval) {
task.put_a_col(j,
asubj,
avalj)?;
}
}
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/****************** Make a change to the A matrix ******************/
task.put_aij(0, 0, 3.0)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in xx.iter().enumerate() {
println!("x[{}]: {}",j,xj);
}
/***************** Add a new variable ******************************/
/* Get index of new variable. */
let varidx = task.get_num_var()?;
/* Append a new variable x_3 to the problem */
task.append_vars(1)?;
let numvar = numvar + 1;
/* Set bounds on new varaible */
task.put_var_bound(varidx, Boundkey::LO, 0.0, INF)?;
/* Change objective */
task.put_c_j(varidx, 1.0)?;
/* Put new values in the A matrix */
let acolsub = &[0i32, 2];
let acolval = &[4.0, 1.0];
task.put_a_col(varidx, /* column index */
acolsub,
acolval)?;
/* Change optimizer to simplex free and reoptimize */
task.put_int_param(mosek::Iparam::OPTIMIZER, mosek::Optimizertype::FREE_SIMPLEX)?;
let _trm = task.optimize()?;
let mut xx = vec![0.0; task.get_num_var()? as usize];
task.get_xx(Soltype::BAS, xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Add a new constraint ***************************/
/* Get index of new constraint. */
let conidx = task.get_num_con()?;
/* Append a new constraint */
task.append_cons(1)?;
let numcon = numcon + 1;
/* Set bounds on new constraint */
task.put_con_bound(conidx,
Boundkey::UP,
-INF,
30000.0)?;
/* Put new values in the A matrix */
let arowsub = &[0i32, 1, 2, 3 ];
let arowval = &[1.0, 2.0, 1.0, 1.0 ];
task.put_a_row(conidx, /* row index */
arowsub,
arowval)?;
let _trm = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
/********************** Change constraint bounds ********************/
let newbkc = &[Boundkey::UP,
Boundkey::UP,
Boundkey::UP,
Boundkey::UP];
let newblc = &[-INF,
-INF,
-INF,
-INF];
let newbuc = &[ 80000.0, 40000.0, 50000.0, 22000.0 ];
task.put_con_bound_slice(0, numcon, newbkc, newblc, newbuc)?;
let _ = task.optimize()?;
task.get_xx(Soltype::BAS, // Request the basic solution.
xx.as_mut_slice())?;
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}",j,xj);
}
Ok(())
}examples/milo1.rs (line 57)
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fn main() -> Result<(),String> {
let numcon : i32 = 2;
let numvar : i32 = 2;
let infinity = 0.0; // only for symbolic purposes, value never used
let bkc = vec![Boundkey::UP, Boundkey::LO];
let blc = vec![ -infinity, -4.0 ];
let buc = vec![ 250.0, infinity ];
let bkx = vec![ Boundkey::LO, Boundkey::LO ];
let blx = vec![ 0.0, 0.0 ];
let bux = vec![ infinity, infinity ];
let c = vec![1.0, 0.64];
let asub = vec![0, 1,
0, 1];
let aval = vec![50.0, 3.0, 31.0, -2.0];
let ptrb : Vec<usize> = vec![ 0, 2 ];
let ptre : Vec<usize> = vec![ 2, 4 ];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| task.with_itg_sol_callback(
&mut |xx| { println!("Found a new solution = {:?}",xx); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
for ((((j,cj),bk),bl),bu) in (0..numvar).zip(c.iter()).zip(bkx.iter()).zip(blx.iter()).zip(bux.iter()) {
/* Set the linear term c_j in the objective.*/
task.put_c_j(j, *cj)?;
/* Set the bounds on variable j.
blx[j] <= x_j <= bux[j] */
task.put_var_bound(j, *bk, *bl, *bu)?;
/* Input column j of A */
task.put_a_col(j, /* Variable (column) index.*/
&asub[ptrb[j as usize]..ptre[j as usize]], /* Row index of non-zeros in column j.*/
&aval[ptrb[j as usize]..ptre[j as usize]])?; /* Non-zero Values of column j. */
}
// Set the bounds on constraints.
// for i=1, ...,numcon : blc[i] <= constraint i <= buc[i]
for (((i,bk),bl),bu) in (0..numcon).zip(bkc.iter()).zip(blc.iter()).zip(buc.iter()) {
task.put_con_bound(i, *bk, *bl, *bu)?;
}
/* Specify integer variables. */
for j in 0..numvar {
task.put_var_type(j, Variabletype::TYPE_INT)?;
}
/* Set max solution time */
task.put_dou_param(Dparam::MIO_MAX_TIME, 60.0)?;
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITG, xx.as_mut_slice())?;
/* Get status information about the solution */
match task.get_sol_sta(Soltype::ITG)? {
Solsta::INTEGER_OPTIMAL => {
println!("Optimal solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::PRIM_FEAS => {
println!("Feasible solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::UNKNOWN => {
match task.get_pro_sta(Soltype::ITG)? {
Prosta::PRIM_INFEAS_OR_UNBOUNDED => {
println!("Problem status Infeasible or unbounded");
}
Prosta::PRIM_INFEAS => {
println!("Problem status Infeasible.");
}
Prosta::UNKNOWN => {
println!("Problem status unknown.");
}
_ => {
println!("Other problem status.");
}
}
}
_ => {
println!("Other solution status");
}
}
Ok(())
}))
}sourcepub fn put_var_bound_list(
&mut self,
sub_: &[i32],
bkx_: &[i32],
blx_: &[f64],
bux_: &[f64]
) -> Result<(), String>
pub fn put_var_bound_list( &mut self, sub_: &[i32], bkx_: &[i32], blx_: &[f64], bux_: &[f64] ) -> Result<(), String>
Changes the bounds of a list of variables.
§Arguments
-
sub_List of variable indexes. -
bkx_Bound keys for the variables.See Boundkey
-
blx_Lower bounds for the variables. -
bux_Upper bounds for the variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putvarboundlist
sourcepub fn put_var_bound_list_const(
&mut self,
sub_: &[i32],
bkx_: i32,
blx_: f64,
bux_: f64
) -> Result<(), String>
pub fn put_var_bound_list_const( &mut self, sub_: &[i32], bkx_: i32, blx_: f64, bux_: f64 ) -> Result<(), String>
Changes the bounds of a list of variables.
§Arguments
-
sub_List of variable indexes. -
bkx_New bound key for all variables in the list.See Boundkey
-
blx_New lower bound for all variables in the list. -
bux_New upper bound for all variables in the list.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putvarboundlistconst
sourcepub fn put_var_bound_slice(
&mut self,
first_: i32,
last_: i32,
bkx_: &[i32],
blx_: &[f64],
bux_: &[f64]
) -> Result<(), String>
pub fn put_var_bound_slice( &mut self, first_: i32, last_: i32, bkx_: &[i32], blx_: &[f64], bux_: &[f64] ) -> Result<(), String>
Changes the bounds for a slice of the variables.
§Arguments
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
bkx_Bound keys for the variables.See Boundkey
-
blx_Lower bounds for the variables. -
bux_Upper bounds for the variables.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putvarboundslice
Examples found in repository?
examples/ceo1.rs (line 63)
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fn main() -> Result<(),String> {
let numcon = 1;
let numvar = 3;
let bkc = mosek::Boundkey::FX;
let blc = 1.0;
let buc = 1.0;
let bkx = vec![ Boundkey::FR,
Boundkey::FR,
Boundkey::FR ];
let blx = vec![ -INF, -INF, -INF ];
let bux = vec![ INF, INF, INF ];
let c = vec![ 1.0, 1.0, 0.0 ];
let a = vec![ 1.0, 1.0, 1.0 ];
let asub = vec![0, 1, 2];
//let csub = new int[numvar];
//double[] xx = new double[numvar];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|task| task.with_callback(
&mut |caller| { println!("caller = {}",caller); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
/* Define the linear part of the problem */
task.put_c_slice(0, numvar, c.as_slice())?;
task.put_a_row(0, asub.as_slice(), a.as_slice())?;
task.put_con_bound(0, bkc, blc, buc)?;
task.put_var_bound_slice(0, numvar, bkx.as_slice(), blx.as_slice(), bux.as_slice())?;
/* Add a conic constraint */
task.append_afes(3)?;
let afeidxs = vec![0, 1, 2 ];
let b = vec![0.0,0.0,0.0];
let domidx = task.append_primal_exp_cone_domain()?;
task.put_afe_f_row_list(afeidxs.as_slice(),
vec![1,1,1].as_slice(),
vec![0,1,2].as_slice(),
vec![0,1,2].as_slice(),
vec![1.0,1.0,1.0].as_slice())?;
task.append_acc(domidx,afeidxs.as_slice(),b.as_slice())?;
task.put_obj_sense(Objsense::MINIMIZE)?;
println!("optimize");
/* Solve the problem */
task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
/* Get status information about the solution */
let solsta = task.get_sol_sta(Soltype::ITR)?;
assert!(solsta == Solsta::OPTIMAL);
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITR, & mut xx[..])?;
println!("Optimal primal solution");
for j in 0..numvar as usize {
println!("x[{}]: {:.4}",j,xx[j]);
}
Ok(())
}))
}sourcepub fn put_var_bound_slice_const(
&mut self,
first_: i32,
last_: i32,
bkx_: i32,
blx_: f64,
bux_: f64
) -> Result<(), String>
pub fn put_var_bound_slice_const( &mut self, first_: i32, last_: i32, bkx_: i32, blx_: f64, bux_: f64 ) -> Result<(), String>
Changes the bounds for a slice of the variables.
§Arguments
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
bkx_New bound key for all variables in the slice.See Boundkey
-
blx_New lower bound for all variables in the slice. -
bux_New upper bound for all variables in the slice.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putvarboundsliceconst
Examples found in repository?
examples/pinfeas.rs (line 28)
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fn test_problem() -> Result<mosek::Task,String> {
let mut task = mosek::Task::new().unwrap();
task.append_vars(7)?;
task.append_cons(7)?;
task.put_c_list(&[0,1,2,3,4,5,6],
&[1.0,2.0,5.0,2.0,1.0,2.0,1.0])?;
task.put_aij_list(&[0,0,1,1,2,2,2,3,3,4,5,5,6,6],
&[0,1,2,3,4,5,6,0,4,1,2,5,3,6],
&[1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0])?;
task.put_con_bound_slice(0, 7,
&[Boundkey::UP,Boundkey::UP,Boundkey::UP,Boundkey::FX,Boundkey::FX,Boundkey::FX,Boundkey::FX],
&[-INF, -INF, -INF, 1100.0, 200.0, 500.0, 500.0],
&[200.0, 1000.0, 1000.0, 1100.0, 200.0, 500.0, 500.0])?;
task.put_var_bound_slice_const(0, 7, Boundkey::UP, 0.0, INF)?;
Ok(task)
}More examples
examples/solvelinear.rs (line 47)
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fn setup(task : & mut mosek::Task,
aval : &[f64],
asub : &[i32],
ptrb : &[i64],
ptre : &[i64],
numvar : i32) -> Result<Vec<i32>,String> {
// mosek.stakey[] skx = new mosek.stakey [numvar];
// mosek.stakey[] skc = new mosek.stakey [numvar];
// for (int i = 0; i < numvar ; ++i) {
// skx[i] = mosek.stakey.bas;
// skc[i] = mosek.stakey.fix;
// }
task.append_vars(numvar)?;
task.append_cons(numvar)?;
task.put_a_col_slice(0,numvar,ptrb,ptre,asub,aval)?;
task.put_con_bound_slice_const(0,numvar,Boundkey::FX,0.0,0.0)?;
task.put_var_bound_slice_const(0,numvar,Boundkey::FR,-INF,INF)?;
/* Define a basic solution by specifying
status keys for variables & constraints. */
task.delete_solution(Soltype::BAS)?;
task.put_skc_slice(Soltype::BAS, 0, numvar, vec![Stakey::FIX; numvar as usize].as_slice())?;
task.put_skx_slice(Soltype::BAS, 0, numvar, vec![Stakey::BAS; numvar as usize].as_slice())?;
let mut basis = vec![0; numvar as usize];
task.init_basis_solve(basis.as_mut_slice())?;
Ok(basis)
}examples/portfolio_5_card.rs (line 73)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}sourcepub fn put_var_name(&mut self, j_: i32, name_: &str) -> Result<(), String>
pub fn put_var_name(&mut self, j_: i32, name_: &str) -> Result<(), String>
Sets the name of a variable.
§Arguments
j_Index of the variable.name_The variable name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putvarname
Examples found in repository?
examples/portfolio_2_frontier.rs (line 72)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}More examples
examples/portfolio_5_card.rs (line 78)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}sourcepub fn put_var_solution_j(
&mut self,
j_: i32,
whichsol_: i32,
sk_: i32,
x_: f64,
sl_: f64,
su_: f64,
sn_: f64
) -> Result<(), String>
pub fn put_var_solution_j( &mut self, j_: i32, whichsol_: i32, sk_: i32, x_: f64, sl_: f64, su_: f64, sn_: f64 ) -> Result<(), String>
Sets the primal and dual solution information for a single variable.
§Arguments
-
j_Index of the variable. -
whichsol_Selects a solution.See Soltype
-
sk_Status key of the variable.See Stakey
-
x_Primal solution value of the variable. -
sl_Solution value of the dual variable associated with the lower bound. -
su_Solution value of the dual variable associated with the upper bound. -
sn_Solution value of the dual variable associated with the conic constraint.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putvarsolutionj
sourcepub fn put_var_type(&mut self, j_: i32, vartype_: i32) -> Result<(), String>
pub fn put_var_type(&mut self, j_: i32, vartype_: i32) -> Result<(), String>
Sets the variable type of one variable.
§Arguments
-
j_Index of the variable. -
vartype_The new variable type.See Variabletype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putvartype
Examples found in repository?
examples/portfolio_5_card.rs (line 81)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}More examples
examples/milo1.rs (line 71)
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fn main() -> Result<(),String> {
let numcon : i32 = 2;
let numvar : i32 = 2;
let infinity = 0.0; // only for symbolic purposes, value never used
let bkc = vec![Boundkey::UP, Boundkey::LO];
let blc = vec![ -infinity, -4.0 ];
let buc = vec![ 250.0, infinity ];
let bkx = vec![ Boundkey::LO, Boundkey::LO ];
let blx = vec![ 0.0, 0.0 ];
let bux = vec![ infinity, infinity ];
let c = vec![1.0, 0.64];
let asub = vec![0, 1,
0, 1];
let aval = vec![50.0, 3.0, 31.0, -2.0];
let ptrb : Vec<usize> = vec![ 0, 2 ];
let ptre : Vec<usize> = vec![ 2, 4 ];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| task.with_itg_sol_callback(
&mut |xx| { println!("Found a new solution = {:?}",xx); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
for ((((j,cj),bk),bl),bu) in (0..numvar).zip(c.iter()).zip(bkx.iter()).zip(blx.iter()).zip(bux.iter()) {
/* Set the linear term c_j in the objective.*/
task.put_c_j(j, *cj)?;
/* Set the bounds on variable j.
blx[j] <= x_j <= bux[j] */
task.put_var_bound(j, *bk, *bl, *bu)?;
/* Input column j of A */
task.put_a_col(j, /* Variable (column) index.*/
&asub[ptrb[j as usize]..ptre[j as usize]], /* Row index of non-zeros in column j.*/
&aval[ptrb[j as usize]..ptre[j as usize]])?; /* Non-zero Values of column j. */
}
// Set the bounds on constraints.
// for i=1, ...,numcon : blc[i] <= constraint i <= buc[i]
for (((i,bk),bl),bu) in (0..numcon).zip(bkc.iter()).zip(blc.iter()).zip(buc.iter()) {
task.put_con_bound(i, *bk, *bl, *bu)?;
}
/* Specify integer variables. */
for j in 0..numvar {
task.put_var_type(j, Variabletype::TYPE_INT)?;
}
/* Set max solution time */
task.put_dou_param(Dparam::MIO_MAX_TIME, 60.0)?;
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITG, xx.as_mut_slice())?;
/* Get status information about the solution */
match task.get_sol_sta(Soltype::ITG)? {
Solsta::INTEGER_OPTIMAL => {
println!("Optimal solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::PRIM_FEAS => {
println!("Feasible solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::UNKNOWN => {
match task.get_pro_sta(Soltype::ITG)? {
Prosta::PRIM_INFEAS_OR_UNBOUNDED => {
println!("Problem status Infeasible or unbounded");
}
Prosta::PRIM_INFEAS => {
println!("Problem status Infeasible.");
}
Prosta::UNKNOWN => {
println!("Problem status unknown.");
}
_ => {
println!("Other problem status.");
}
}
}
_ => {
println!("Other solution status");
}
}
Ok(())
}))
}sourcepub fn put_var_type_list(
&mut self,
subj_: &[i32],
vartype_: &[i32]
) -> Result<(), String>
pub fn put_var_type_list( &mut self, subj_: &[i32], vartype_: &[i32] ) -> Result<(), String>
Sets the variable type for one or more variables.
§Arguments
-
subj_A list of variable indexes for which the variable type should be changed. -
vartype_A list of variable types.See Variabletype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putvartypelist
sourcepub fn put_xc(&mut self, whichsol_: i32, xc_: &mut [f64]) -> Result<(), String>
pub fn put_xc(&mut self, whichsol_: i32, xc_: &mut [f64]) -> Result<(), String>
Sets the xc vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
xc_Primal constraint solution.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putxc
sourcepub fn put_xc_slice(
&mut self,
whichsol_: i32,
first_: i32,
last_: i32,
xc_: &[f64]
) -> Result<(), String>
pub fn put_xc_slice( &mut self, whichsol_: i32, first_: i32, last_: i32, xc_: &[f64] ) -> Result<(), String>
Sets a slice of the xc vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
xc_Primal constraint solution.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putxcslice
sourcepub fn put_xx(&mut self, whichsol_: i32, xx_: &[f64]) -> Result<(), String>
pub fn put_xx(&mut self, whichsol_: i32, xx_: &[f64]) -> Result<(), String>
Sets the xx vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
xx_Primal variable solution.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putxx
sourcepub fn put_xx_slice(
&mut self,
whichsol_: i32,
first_: i32,
last_: i32,
xx_: &[f64]
) -> Result<(), String>
pub fn put_xx_slice( &mut self, whichsol_: i32, first_: i32, last_: i32, xx_: &[f64] ) -> Result<(), String>
Sets a slice of the xx vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
xx_Primal variable solution.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putxxslice
sourcepub fn put_y(&mut self, whichsol_: i32, y_: &[f64]) -> Result<(), String>
pub fn put_y(&mut self, whichsol_: i32, y_: &[f64]) -> Result<(), String>
Sets the y vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
y_Vector of dual variables corresponding to the constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.puty
sourcepub fn put_y_slice(
&mut self,
whichsol_: i32,
first_: i32,
last_: i32,
y_: &[f64]
) -> Result<(), String>
pub fn put_y_slice( &mut self, whichsol_: i32, first_: i32, last_: i32, y_: &[f64] ) -> Result<(), String>
Sets a slice of the y vector for a solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
first_First index in the sequence. -
last_Last index plus 1 in the sequence. -
y_Vector of dual variables corresponding to the constraints.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.putyslice
sourcepub fn read_b_solution(
&self,
filename_: &str,
compress_: i32
) -> Result<(), String>
pub fn read_b_solution( &self, filename_: &str, compress_: i32 ) -> Result<(), String>
Read a binary dump of the task solution and information items.
§Arguments
-
filename_A valid file name. -
compress_Data compression type.See Compresstype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.readbsolution
sourcepub fn read_data(&mut self, filename_: &str) -> Result<(), String>
pub fn read_data(&mut self, filename_: &str) -> Result<(), String>
Reads problem data from a file.
§Arguments
filename_A valid file name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.readdataautoformat
Examples found in repository?
examples/callback.rs (line 112)
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fn callbackmain(which : &str, data : FileOrText) -> Result<(),String> {
/* Create the optimization task. */
let mut task = Task::new().unwrap();
match data {
FileOrText::Text(data) => { task.read_ptf_string(data)? },
FileOrText::File(fname) => { task.read_data(fname)? }
}
task.write_data("callback.ptf")?;
match which {
"psim" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::PRIMAL_SIMPLEX)?,
"dsim" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::DUAL_SIMPLEX)?,
"intpnt" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::INTPNT)?,
s => return Err(format!("Invalid argument '{}'",s))
}
/* Directs the log task stream to the 'printstr' function. */
task.with_stream_callback(
Streamtype::LOG,
& mut |msg| print!("{}",msg),
|task|
task.with_info_callback(
& mut callback,
|task|
task.optimize()
)
)?;
Result::Ok(())
}More examples
examples/parallel.rs (line 38)
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fn parallel(files : Vec<FileOrText>) -> Result<(),String> {
// Create an example list of tasks to optimize
let mut tasks : Vec<(String,Task)> = files.iter().filter_map(|fname| {
let mut t = Task::new().unwrap();
match fname {
FileOrText::File(fname) => {
if let Err(_) = t.read_data(fname.as_str()) { None }
else {
t.put_int_param(mosek::Iparam::NUM_THREADS, 2).unwrap();
Some((fname.as_str().to_string(),t))
}
},
FileOrText::Text(data) => {
if let Err(_) = t.read_ptf_string(data.as_str()) { None }
else {
t.put_int_param(mosek::Iparam::NUM_THREADS, 2).unwrap();
Some(("-".to_string(),t))
}
}
}
}).collect();
let mut res = vec![0i32; tasks.len()];
let mut trm = vec![0i32; tasks.len()];
{
let taskrs : Vec<& mut Task> = tasks.iter_mut().map(|(_a,b)| b).collect();
// Size of thread pool available for all tasks
let threadpoolsize : i32 = 6;
// Optimize all the given tasks in parallel
mosek::optimize_batch(false, // No race
-1.0, // No time limit
threadpoolsize,
taskrs.as_slice(), // Array of tasks to optimize
trm.as_mut_slice(),
res.as_mut_slice())?;
}
for (resi,trmi,(fname,ti)) in izip!(res,trm,tasks.iter()) {
println!("Task {} res {} trm {} obj_val {} time {}",
fname,
resi,
trmi,
ti.get_dou_inf(mosek::Dinfitem::INTPNT_PRIMAL_OBJ)?,
ti.get_dou_inf(mosek::Dinfitem::OPTIMIZER_TIME)?);
}
Ok(())
}examples/opt_server_async.rs (line 44)
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fn opt_server_async(inputfile : FileOrText, addr : String, numpolls : usize, cert : Option<String>) -> Result<(),String> {
// Path to certificate, if any
let token = {
Task::new().unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| {
match inputfile {
FileOrText::File(ref filename) => task.read_data(filename.as_str()).unwrap(),
FileOrText::Text(ref data) => task.read_ptf_string(data.as_str()).unwrap()
}
if let Some(ref cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH,cert.as_str())?;
}
task.async_optimize(addr.as_str(),"")
}).expect("Failed to submit async optimization")
};
println!("Task token = '{}'", token);
println!("Setting log stream...");
Task::new().unwrap().with_stream_callback(
Streamtype::LOG,
& mut |msg| print!("{}",msg),
|task| task.with_callback(
&mut|caller| { println!("caller = {}",caller); false },
|task| {
println!("Reading input file '{:?}'...",inputfile);
match inputfile {
FileOrText::File(ref filename) => task.read_data(filename.as_str()).unwrap(),
FileOrText::Text(ref data) => task.read_ptf_string(data.as_str()).unwrap()
}
if let Some(ref cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH,cert.as_str())?;
}
println!("Starting polling loop...");
for i in 0..numpolls {
sleep(Duration::new(1,0));
println!("\tpoll {}...", i);
let mut trm : i32 = 0;
let mut resp : i32 = 0;
let respavailable = task.async_poll(addr.as_str(),
"",
token.as_str(),
& mut resp,
& mut trm)?;
if respavailable {
println!("solution available!");
task.async_get_result(addr.as_str(),
"",
token.as_str(),
& mut resp,
& mut trm)?;
task.solution_summary (Streamtype::LOG)?;
return Ok(());
}
}
println!("max num polls reached, stopping host.");
task.async_stop (addr.as_str(), "", token.as_str())?;
Err("Max num polls".to_string())
}))
}examples/concurrent1.rs (line 108)
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fn concurrent1(data : FileOrText, timelimit : Option<String>) -> Result<(),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
match data {
FileOrText::File(fname) => task.read_data(fname.as_str())?,
FileOrText::Text(text) => task.read_ptf_string(text.as_str())?
}
if let Some(timelimit) = timelimit {
task.put_dou_param(mosek::Dparam::OPTIMIZER_MAX_TIME, timelimit.parse().unwrap())?;
}
let numintvar = task.get_num_int_var()?;
let r = if numintvar == 0 {
let optimizers = &[mosek::Optimizertype::CONIC,
mosek::Optimizertype::DUAL_SIMPLEX,
mosek::Optimizertype::PRIMAL_SIMPLEX];
optimize_concurrent(& mut task, optimizers)
}
else {
let seeds = &[ 42, 13, 71749373 ];
optimize_concurrent_mio(& mut task, seeds)
};
let sense = task.get_obj_sense()?;
// Pick the feasible result. For non-integer problems all
// solutions should be the same if more than one is returned, but
// for integer problems tasks may have hit the time limit and
// returned non-optimal solutions.
let n = r.len();
if n == 0 {
println!("All optimizers failed.");
}
else if numintvar > 0 {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
ii.iter().zip(tasks.iter()).enumerate()
.filter_map(|(k,(_i,t))|
match (*t).solution_def(Soltype::ITG) {
Ok(true) => match t.get_sol_sta(Soltype::ITG).unwrap() {
Solsta::PRIM_FEAS|Solsta::INTEGER_OPTIMAL => Some((k,t.get_primal_obj(Soltype::ITG).unwrap())),
_ => None
},
_ => None
})
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
else {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
tasks.iter().enumerate()
.filter_map(|(k,t)|
match t.get_sol_sta(Soltype::BAS) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::BAS).unwrap())),
_ => None
}.or_else(|| match t.get_sol_sta(Soltype::ITR) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::ITR).unwrap())),
_ => None
}))
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
Result::Ok(())
}sourcepub fn read_data_format(
&mut self,
filename_: &str,
format_: i32,
compress_: i32
) -> Result<(), String>
pub fn read_data_format( &mut self, filename_: &str, format_: i32, compress_: i32 ) -> Result<(), String>
Reads problem data from a file.
§Arguments
-
filename_A valid file name. -
format_File data format.See Dataformat
-
compress_File compression type.See Compresstype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.readdataformat
sourcepub fn read_json_sol(&mut self, filename_: &str) -> Result<(), String>
pub fn read_json_sol(&mut self, filename_: &str) -> Result<(), String>
Reads a solution from a JSOL file.
§Arguments
filename_A valid file name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.readjsonsol
sourcepub fn read_json_string(&mut self, data_: &str) -> Result<(), String>
pub fn read_json_string(&mut self, data_: &str) -> Result<(), String>
Load task data from a string in JSON format.
§Arguments
data_Problem data in text format.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.readjsonstring
sourcepub fn read_lp_string(&mut self, data_: &str) -> Result<(), String>
pub fn read_lp_string(&mut self, data_: &str) -> Result<(), String>
Load task data from a string in LP format.
§Arguments
data_Problem data in text format.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.readlpstring
sourcepub fn read_opf_string(&mut self, data_: &str) -> Result<(), String>
pub fn read_opf_string(&mut self, data_: &str) -> Result<(), String>
Load task data from a string in OPF format.
§Arguments
data_Problem data in text format.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.readopfstring
sourcepub fn read_param_file(&mut self, filename_: &str) -> Result<(), String>
pub fn read_param_file(&mut self, filename_: &str) -> Result<(), String>
Reads a parameter file.
§Arguments
filename_A valid file name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.readparamfile
sourcepub fn read_ptf_string(&mut self, data_: &str) -> Result<(), String>
pub fn read_ptf_string(&mut self, data_: &str) -> Result<(), String>
Load task data from a string in PTF format.
§Arguments
data_Problem data in text format.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.readptfstring
Examples found in repository?
More examples
examples/callback.rs (line 111)
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fn callbackmain(which : &str, data : FileOrText) -> Result<(),String> {
/* Create the optimization task. */
let mut task = Task::new().unwrap();
match data {
FileOrText::Text(data) => { task.read_ptf_string(data)? },
FileOrText::File(fname) => { task.read_data(fname)? }
}
task.write_data("callback.ptf")?;
match which {
"psim" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::PRIMAL_SIMPLEX)?,
"dsim" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::DUAL_SIMPLEX)?,
"intpnt" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::INTPNT)?,
s => return Err(format!("Invalid argument '{}'",s))
}
/* Directs the log task stream to the 'printstr' function. */
task.with_stream_callback(
Streamtype::LOG,
& mut |msg| print!("{}",msg),
|task|
task.with_info_callback(
& mut callback,
|task|
task.optimize()
)
)?;
Result::Ok(())
}examples/parallel.rs (line 45)
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fn parallel(files : Vec<FileOrText>) -> Result<(),String> {
// Create an example list of tasks to optimize
let mut tasks : Vec<(String,Task)> = files.iter().filter_map(|fname| {
let mut t = Task::new().unwrap();
match fname {
FileOrText::File(fname) => {
if let Err(_) = t.read_data(fname.as_str()) { None }
else {
t.put_int_param(mosek::Iparam::NUM_THREADS, 2).unwrap();
Some((fname.as_str().to_string(),t))
}
},
FileOrText::Text(data) => {
if let Err(_) = t.read_ptf_string(data.as_str()) { None }
else {
t.put_int_param(mosek::Iparam::NUM_THREADS, 2).unwrap();
Some(("-".to_string(),t))
}
}
}
}).collect();
let mut res = vec![0i32; tasks.len()];
let mut trm = vec![0i32; tasks.len()];
{
let taskrs : Vec<& mut Task> = tasks.iter_mut().map(|(_a,b)| b).collect();
// Size of thread pool available for all tasks
let threadpoolsize : i32 = 6;
// Optimize all the given tasks in parallel
mosek::optimize_batch(false, // No race
-1.0, // No time limit
threadpoolsize,
taskrs.as_slice(), // Array of tasks to optimize
trm.as_mut_slice(),
res.as_mut_slice())?;
}
for (resi,trmi,(fname,ti)) in izip!(res,trm,tasks.iter()) {
println!("Task {} res {} trm {} obj_val {} time {}",
fname,
resi,
trmi,
ti.get_dou_inf(mosek::Dinfitem::INTPNT_PRIMAL_OBJ)?,
ti.get_dou_inf(mosek::Dinfitem::OPTIMIZER_TIME)?);
}
Ok(())
}examples/opt_server_async.rs (line 45)
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fn opt_server_async(inputfile : FileOrText, addr : String, numpolls : usize, cert : Option<String>) -> Result<(),String> {
// Path to certificate, if any
let token = {
Task::new().unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| {
match inputfile {
FileOrText::File(ref filename) => task.read_data(filename.as_str()).unwrap(),
FileOrText::Text(ref data) => task.read_ptf_string(data.as_str()).unwrap()
}
if let Some(ref cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH,cert.as_str())?;
}
task.async_optimize(addr.as_str(),"")
}).expect("Failed to submit async optimization")
};
println!("Task token = '{}'", token);
println!("Setting log stream...");
Task::new().unwrap().with_stream_callback(
Streamtype::LOG,
& mut |msg| print!("{}",msg),
|task| task.with_callback(
&mut|caller| { println!("caller = {}",caller); false },
|task| {
println!("Reading input file '{:?}'...",inputfile);
match inputfile {
FileOrText::File(ref filename) => task.read_data(filename.as_str()).unwrap(),
FileOrText::Text(ref data) => task.read_ptf_string(data.as_str()).unwrap()
}
if let Some(ref cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH,cert.as_str())?;
}
println!("Starting polling loop...");
for i in 0..numpolls {
sleep(Duration::new(1,0));
println!("\tpoll {}...", i);
let mut trm : i32 = 0;
let mut resp : i32 = 0;
let respavailable = task.async_poll(addr.as_str(),
"",
token.as_str(),
& mut resp,
& mut trm)?;
if respavailable {
println!("solution available!");
task.async_get_result(addr.as_str(),
"",
token.as_str(),
& mut resp,
& mut trm)?;
task.solution_summary (Streamtype::LOG)?;
return Ok(());
}
}
println!("max num polls reached, stopping host.");
task.async_stop (addr.as_str(), "", token.as_str())?;
Err("Max num polls".to_string())
}))
}examples/concurrent1.rs (line 109)
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fn concurrent1(data : FileOrText, timelimit : Option<String>) -> Result<(),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
match data {
FileOrText::File(fname) => task.read_data(fname.as_str())?,
FileOrText::Text(text) => task.read_ptf_string(text.as_str())?
}
if let Some(timelimit) = timelimit {
task.put_dou_param(mosek::Dparam::OPTIMIZER_MAX_TIME, timelimit.parse().unwrap())?;
}
let numintvar = task.get_num_int_var()?;
let r = if numintvar == 0 {
let optimizers = &[mosek::Optimizertype::CONIC,
mosek::Optimizertype::DUAL_SIMPLEX,
mosek::Optimizertype::PRIMAL_SIMPLEX];
optimize_concurrent(& mut task, optimizers)
}
else {
let seeds = &[ 42, 13, 71749373 ];
optimize_concurrent_mio(& mut task, seeds)
};
let sense = task.get_obj_sense()?;
// Pick the feasible result. For non-integer problems all
// solutions should be the same if more than one is returned, but
// for integer problems tasks may have hit the time limit and
// returned non-optimal solutions.
let n = r.len();
if n == 0 {
println!("All optimizers failed.");
}
else if numintvar > 0 {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
ii.iter().zip(tasks.iter()).enumerate()
.filter_map(|(k,(_i,t))|
match (*t).solution_def(Soltype::ITG) {
Ok(true) => match t.get_sol_sta(Soltype::ITG).unwrap() {
Solsta::PRIM_FEAS|Solsta::INTEGER_OPTIMAL => Some((k,t.get_primal_obj(Soltype::ITG).unwrap())),
_ => None
},
_ => None
})
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
else {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
tasks.iter().enumerate()
.filter_map(|(k,t)|
match t.get_sol_sta(Soltype::BAS) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::BAS).unwrap())),
_ => None
}.or_else(|| match t.get_sol_sta(Soltype::ITR) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::ITR).unwrap())),
_ => None
}))
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
Result::Ok(())
}sourcepub fn read_solution(
&mut self,
whichsol_: i32,
filename_: &str
) -> Result<(), String>
pub fn read_solution( &mut self, whichsol_: i32, filename_: &str ) -> Result<(), String>
Reads a solution from a file.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
filename_A valid file name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.readsolution
sourcepub fn read_solution_file(&self, filename_: &str) -> Result<(), String>
pub fn read_solution_file(&self, filename_: &str) -> Result<(), String>
Read solution file in format determined by the filename
§Arguments
filename_A valid file name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.readsolutionfile
sourcepub fn read_summary(&mut self, whichstream_: i32) -> Result<(), String>
pub fn read_summary(&mut self, whichstream_: i32) -> Result<(), String>
Prints information about last file read.
§Arguments
-
whichstream_Index of the stream.See Streamtype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.readsummary
sourcepub fn read_task(&mut self, filename_: &str) -> Result<(), String>
pub fn read_task(&mut self, filename_: &str) -> Result<(), String>
Load task data from a file.
§Arguments
filename_A valid file name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.readtask
sourcepub fn remove_barvars(&mut self, subset_: &[i32]) -> Result<(), String>
pub fn remove_barvars(&mut self, subset_: &[i32]) -> Result<(), String>
Removes a number of symmetric matrices.
§Arguments
subset_Indexes of symmetric matrices which should be removed.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.removebarvars
sourcepub fn remove_cones(&mut self, subset_: &[i32]) -> Result<(), String>
pub fn remove_cones(&mut self, subset_: &[i32]) -> Result<(), String>
Removes a number of conic constraints from the problem.
§Arguments
subset_Indexes of cones which should be removed.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.removecones
sourcepub fn remove_cons(&mut self, subset_: &[i32]) -> Result<(), String>
pub fn remove_cons(&mut self, subset_: &[i32]) -> Result<(), String>
Removes a number of constraints.
§Arguments
subset_Indexes of constraints which should be removed.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.removecons
sourcepub fn remove_vars(&mut self, subset_: &[i32]) -> Result<(), String>
pub fn remove_vars(&mut self, subset_: &[i32]) -> Result<(), String>
Removes a number of variables.
§Arguments
subset_Indexes of variables which should be removed.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.removevars
sourcepub fn resize_task(
&mut self,
maxnumcon_: i32,
maxnumvar_: i32,
maxnumcone_: i32,
maxnumanz_: i64,
maxnumqnz_: i64
) -> Result<(), String>
pub fn resize_task( &mut self, maxnumcon_: i32, maxnumvar_: i32, maxnumcone_: i32, maxnumanz_: i64, maxnumqnz_: i64 ) -> Result<(), String>
Resizes an optimization task.
§Arguments
maxnumcon_New maximum number of constraints.maxnumvar_New maximum number of variables.maxnumcone_New maximum number of cones.maxnumanz_New maximum number of linear non-zero elements.maxnumqnz_New maximum number of quadratic non-zeros elements.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.resizetask
sourcepub fn sensitivity_report(&self, whichstream_: i32) -> Result<(), String>
pub fn sensitivity_report(&self, whichstream_: i32) -> Result<(), String>
Creates a sensitivity report.
§Arguments
-
whichstream_Index of the stream.See Streamtype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.sensitivityreport
sourcepub fn set_defaults(&mut self) -> Result<(), String>
pub fn set_defaults(&mut self) -> Result<(), String>
Resets all parameter values.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.setdefaults
sourcepub fn solution_def(&self, whichsol_: i32) -> Result<bool, String>
pub fn solution_def(&self, whichsol_: i32) -> Result<bool, String>
Checks whether a solution is defined.
§Arguments
-
whichsol_Selects a solution.See Soltype
§Returns
isdefIs non-zero if the requested solution is defined.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.solutiondef
Examples found in repository?
examples/concurrent1.rs (line 146)
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fn concurrent1(data : FileOrText, timelimit : Option<String>) -> Result<(),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
match data {
FileOrText::File(fname) => task.read_data(fname.as_str())?,
FileOrText::Text(text) => task.read_ptf_string(text.as_str())?
}
if let Some(timelimit) = timelimit {
task.put_dou_param(mosek::Dparam::OPTIMIZER_MAX_TIME, timelimit.parse().unwrap())?;
}
let numintvar = task.get_num_int_var()?;
let r = if numintvar == 0 {
let optimizers = &[mosek::Optimizertype::CONIC,
mosek::Optimizertype::DUAL_SIMPLEX,
mosek::Optimizertype::PRIMAL_SIMPLEX];
optimize_concurrent(& mut task, optimizers)
}
else {
let seeds = &[ 42, 13, 71749373 ];
optimize_concurrent_mio(& mut task, seeds)
};
let sense = task.get_obj_sense()?;
// Pick the feasible result. For non-integer problems all
// solutions should be the same if more than one is returned, but
// for integer problems tasks may have hit the time limit and
// returned non-optimal solutions.
let n = r.len();
if n == 0 {
println!("All optimizers failed.");
}
else if numintvar > 0 {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
ii.iter().zip(tasks.iter()).enumerate()
.filter_map(|(k,(_i,t))|
match (*t).solution_def(Soltype::ITG) {
Ok(true) => match t.get_sol_sta(Soltype::ITG).unwrap() {
Solsta::PRIM_FEAS|Solsta::INTEGER_OPTIMAL => Some((k,t.get_primal_obj(Soltype::ITG).unwrap())),
_ => None
},
_ => None
})
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
else {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
tasks.iter().enumerate()
.filter_map(|(k,t)|
match t.get_sol_sta(Soltype::BAS) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::BAS).unwrap())),
_ => None
}.or_else(|| match t.get_sol_sta(Soltype::ITR) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::ITR).unwrap())),
_ => None
}))
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
Result::Ok(())
}sourcepub fn solution_summary(&self, whichstream_: i32) -> Result<(), String>
pub fn solution_summary(&self, whichstream_: i32) -> Result<(), String>
Prints a short summary of the current solutions.
§Arguments
-
whichstream_Index of the stream.See Streamtype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.solutionsummary
Examples found in repository?
examples/opt_server_async.rs (line 96)
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fn opt_server_async(inputfile : FileOrText, addr : String, numpolls : usize, cert : Option<String>) -> Result<(),String> {
// Path to certificate, if any
let token = {
Task::new().unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| {
match inputfile {
FileOrText::File(ref filename) => task.read_data(filename.as_str()).unwrap(),
FileOrText::Text(ref data) => task.read_ptf_string(data.as_str()).unwrap()
}
if let Some(ref cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH,cert.as_str())?;
}
task.async_optimize(addr.as_str(),"")
}).expect("Failed to submit async optimization")
};
println!("Task token = '{}'", token);
println!("Setting log stream...");
Task::new().unwrap().with_stream_callback(
Streamtype::LOG,
& mut |msg| print!("{}",msg),
|task| task.with_callback(
&mut|caller| { println!("caller = {}",caller); false },
|task| {
println!("Reading input file '{:?}'...",inputfile);
match inputfile {
FileOrText::File(ref filename) => task.read_data(filename.as_str()).unwrap(),
FileOrText::Text(ref data) => task.read_ptf_string(data.as_str()).unwrap()
}
if let Some(ref cert) = cert {
task.put_str_param(Sparam::REMOTE_TLS_CERT_PATH,cert.as_str())?;
}
println!("Starting polling loop...");
for i in 0..numpolls {
sleep(Duration::new(1,0));
println!("\tpoll {}...", i);
let mut trm : i32 = 0;
let mut resp : i32 = 0;
let respavailable = task.async_poll(addr.as_str(),
"",
token.as_str(),
& mut resp,
& mut trm)?;
if respavailable {
println!("solution available!");
task.async_get_result(addr.as_str(),
"",
token.as_str(),
& mut resp,
& mut trm)?;
task.solution_summary (Streamtype::LOG)?;
return Ok(());
}
}
println!("max num polls reached, stopping host.");
task.async_stop (addr.as_str(), "", token.as_str())?;
Err("Max num polls".to_string())
}))
}More examples
examples/ceo1.rs (line 84)
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fn main() -> Result<(),String> {
let numcon = 1;
let numvar = 3;
let bkc = mosek::Boundkey::FX;
let blc = 1.0;
let buc = 1.0;
let bkx = vec![ Boundkey::FR,
Boundkey::FR,
Boundkey::FR ];
let blx = vec![ -INF, -INF, -INF ];
let bux = vec![ INF, INF, INF ];
let c = vec![ 1.0, 1.0, 0.0 ];
let a = vec![ 1.0, 1.0, 1.0 ];
let asub = vec![0, 1, 2];
//let csub = new int[numvar];
//double[] xx = new double[numvar];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|task| task.with_callback(
&mut |caller| { println!("caller = {}",caller); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
/* Define the linear part of the problem */
task.put_c_slice(0, numvar, c.as_slice())?;
task.put_a_row(0, asub.as_slice(), a.as_slice())?;
task.put_con_bound(0, bkc, blc, buc)?;
task.put_var_bound_slice(0, numvar, bkx.as_slice(), blx.as_slice(), bux.as_slice())?;
/* Add a conic constraint */
task.append_afes(3)?;
let afeidxs = vec![0, 1, 2 ];
let b = vec![0.0,0.0,0.0];
let domidx = task.append_primal_exp_cone_domain()?;
task.put_afe_f_row_list(afeidxs.as_slice(),
vec![1,1,1].as_slice(),
vec![0,1,2].as_slice(),
vec![0,1,2].as_slice(),
vec![1.0,1.0,1.0].as_slice())?;
task.append_acc(domidx,afeidxs.as_slice(),b.as_slice())?;
task.put_obj_sense(Objsense::MINIMIZE)?;
println!("optimize");
/* Solve the problem */
task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
/* Get status information about the solution */
let solsta = task.get_sol_sta(Soltype::ITR)?;
assert!(solsta == Solsta::OPTIMAL);
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITR, & mut xx[..])?;
println!("Optimal primal solution");
for j in 0..numvar as usize {
println!("x[{}]: {:.4}",j,xx[j]);
}
Ok(())
}))
}examples/concurrent1.rs (line 168)
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fn concurrent1(data : FileOrText, timelimit : Option<String>) -> Result<(),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
match data {
FileOrText::File(fname) => task.read_data(fname.as_str())?,
FileOrText::Text(text) => task.read_ptf_string(text.as_str())?
}
if let Some(timelimit) = timelimit {
task.put_dou_param(mosek::Dparam::OPTIMIZER_MAX_TIME, timelimit.parse().unwrap())?;
}
let numintvar = task.get_num_int_var()?;
let r = if numintvar == 0 {
let optimizers = &[mosek::Optimizertype::CONIC,
mosek::Optimizertype::DUAL_SIMPLEX,
mosek::Optimizertype::PRIMAL_SIMPLEX];
optimize_concurrent(& mut task, optimizers)
}
else {
let seeds = &[ 42, 13, 71749373 ];
optimize_concurrent_mio(& mut task, seeds)
};
let sense = task.get_obj_sense()?;
// Pick the feasible result. For non-integer problems all
// solutions should be the same if more than one is returned, but
// for integer problems tasks may have hit the time limit and
// returned non-optimal solutions.
let n = r.len();
if n == 0 {
println!("All optimizers failed.");
}
else if numintvar > 0 {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
ii.iter().zip(tasks.iter()).enumerate()
.filter_map(|(k,(_i,t))|
match (*t).solution_def(Soltype::ITG) {
Ok(true) => match t.get_sol_sta(Soltype::ITG).unwrap() {
Solsta::PRIM_FEAS|Solsta::INTEGER_OPTIMAL => Some((k,t.get_primal_obj(Soltype::ITG).unwrap())),
_ => None
},
_ => None
})
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
else {
let (ii,_,tasks) = split3vec(r);
let pobjs : Vec<(usize,f64)> =
tasks.iter().enumerate()
.filter_map(|(k,t)|
match t.get_sol_sta(Soltype::BAS) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::BAS).unwrap())),
_ => None
}.or_else(|| match t.get_sol_sta(Soltype::ITR) {
Ok(Solsta::PRIM_FEAS)|Ok(Solsta::OPTIMAL) => Some((k,t.get_primal_obj(Soltype::ITR).unwrap())),
_ => None
}))
.collect();
let &(besti,bestobj) = pobjs.iter()
.max_by(|(_,o1),(_,o2)|
match sense {
Objsense::MAXIMIZE => if o1 < o2 {Ordering::Less} else if o2 < o1 {Ordering::Greater} else {Ordering::Equal},
_ => if o1 > o2 {Ordering::Less} else if o2 > o1 {Ordering::Greater} else {Ordering::Equal}
}).unwrap();
drop_except(tasks,besti).unwrap()
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|t| {
t.optimizer_summary(mosek::Streamtype::LOG)?;
t.solution_summary(mosek::Streamtype::LOG)?;
Ok::<(),String>(())
})?;
println!("{} optimizers succeeded:",pobjs.len());
for &(k,v) in pobjs.iter() {
println!("Optimizer with seed #{} produced result : {:.5e}",ii[k],v);
}
println!("\tBest solution is #{}: {:.5e}",ii[besti],bestobj);
}
Result::Ok(())
}examples/milo1.rs (line 84)
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fn main() -> Result<(),String> {
let numcon : i32 = 2;
let numvar : i32 = 2;
let infinity = 0.0; // only for symbolic purposes, value never used
let bkc = vec![Boundkey::UP, Boundkey::LO];
let blc = vec![ -infinity, -4.0 ];
let buc = vec![ 250.0, infinity ];
let bkx = vec![ Boundkey::LO, Boundkey::LO ];
let blx = vec![ 0.0, 0.0 ];
let bux = vec![ infinity, infinity ];
let c = vec![1.0, 0.64];
let asub = vec![0, 1,
0, 1];
let aval = vec![50.0, 3.0, 31.0, -2.0];
let ptrb : Vec<usize> = vec![ 0, 2 ];
let ptre : Vec<usize> = vec![ 2, 4 ];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| task.with_itg_sol_callback(
&mut |xx| { println!("Found a new solution = {:?}",xx); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
for ((((j,cj),bk),bl),bu) in (0..numvar).zip(c.iter()).zip(bkx.iter()).zip(blx.iter()).zip(bux.iter()) {
/* Set the linear term c_j in the objective.*/
task.put_c_j(j, *cj)?;
/* Set the bounds on variable j.
blx[j] <= x_j <= bux[j] */
task.put_var_bound(j, *bk, *bl, *bu)?;
/* Input column j of A */
task.put_a_col(j, /* Variable (column) index.*/
&asub[ptrb[j as usize]..ptre[j as usize]], /* Row index of non-zeros in column j.*/
&aval[ptrb[j as usize]..ptre[j as usize]])?; /* Non-zero Values of column j. */
}
// Set the bounds on constraints.
// for i=1, ...,numcon : blc[i] <= constraint i <= buc[i]
for (((i,bk),bl),bu) in (0..numcon).zip(bkc.iter()).zip(blc.iter()).zip(buc.iter()) {
task.put_con_bound(i, *bk, *bl, *bu)?;
}
/* Specify integer variables. */
for j in 0..numvar {
task.put_var_type(j, Variabletype::TYPE_INT)?;
}
/* Set max solution time */
task.put_dou_param(Dparam::MIO_MAX_TIME, 60.0)?;
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITG, xx.as_mut_slice())?;
/* Get status information about the solution */
match task.get_sol_sta(Soltype::ITG)? {
Solsta::INTEGER_OPTIMAL => {
println!("Optimal solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::PRIM_FEAS => {
println!("Feasible solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::UNKNOWN => {
match task.get_pro_sta(Soltype::ITG)? {
Prosta::PRIM_INFEAS_OR_UNBOUNDED => {
println!("Problem status Infeasible or unbounded");
}
Prosta::PRIM_INFEAS => {
println!("Problem status Infeasible.");
}
Prosta::UNKNOWN => {
println!("Problem status unknown.");
}
_ => {
println!("Other problem status.");
}
}
}
_ => {
println!("Other solution status");
}
}
Ok(())
}))
}sourcepub fn solve_with_basis(
&mut self,
transp_: bool,
numnz_: i32,
sub_: &mut [i32],
val_: &mut [f64]
) -> Result<i32, String>
pub fn solve_with_basis( &mut self, transp_: bool, numnz_: i32, sub_: &mut [i32], val_: &mut [f64] ) -> Result<i32, String>
Solve a linear equation system involving a basis matrix.
§Arguments
transp_Controls which problem formulation is solved.numnz_Input (number of non-zeros in right-hand side).sub_Input (indexes of non-zeros in right-hand side) and output (indexes of non-zeros in solution vector).val_Input (right-hand side values) and output (solution vector values).
§Returns
numnzoutOutput (number of non-zeros in solution vector).
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.solvewithbasis
sourcepub fn str_to_cone_type(
&self,
str_: &str,
conetype_: &mut i32
) -> Result<(), String>
pub fn str_to_cone_type( &self, str_: &str, conetype_: &mut i32 ) -> Result<(), String>
Obtains a cone type code.
§Arguments
-
str_String corresponding to the cone type code. -
conetype_The cone type corresponding to str.See Conetype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.strtoconetype
sourcepub fn str_to_sk(&self, str_: &str, sk_: &mut i32) -> Result<(), String>
pub fn str_to_sk(&self, str_: &str, sk_: &mut i32) -> Result<(), String>
Obtains a status key.
§Arguments
-
str_A status key abbreviation string. -
sk_Status key corresponding to the string.See Stakey
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.strtosk
sourcepub fn toconic(&mut self) -> Result<(), String>
pub fn toconic(&mut self) -> Result<(), String>
In-place reformulation of a QCQO to a conic quadratic problem.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.toconic
sourcepub fn unlink_func_from_stream(
&mut self,
whichstream_: i32
) -> Result<(), String>
pub fn unlink_func_from_stream( &mut self, whichstream_: i32 ) -> Result<(), String>
Disconnects a user-defined function from a task stream.
§Arguments
-
whichstream_Index of the stream.See Streamtype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.unlinkfuncfromtaskstream
sourcepub fn update_solution_info(&mut self, whichsol_: i32) -> Result<(), String>
pub fn update_solution_info(&mut self, whichsol_: i32) -> Result<(), String>
Update the information items related to the solution.
§Arguments
-
whichsol_Selects a solution.See Soltype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.updatesolutioninfo
sourcepub fn which_param(
&self,
parname_: &str,
partype_: &mut i32,
param_: &mut i32
) -> Result<(), String>
pub fn which_param( &self, parname_: &str, partype_: &mut i32, param_: &mut i32 ) -> Result<(), String>
Checks a parameter name.
§Arguments
-
parname_Parameter name. -
partype_Parameter type.See Parametertype
-
param_Which parameter.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.whichparam
sourcepub fn write_b_solution(
&self,
filename_: &str,
compress_: i32
) -> Result<(), String>
pub fn write_b_solution( &self, filename_: &str, compress_: i32 ) -> Result<(), String>
Write a binary dump of the task solution and information items.
§Arguments
-
filename_A valid file name. -
compress_Data compression type.See Compresstype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.writebsolution
sourcepub fn write_data(&self, filename_: &str) -> Result<(), String>
pub fn write_data(&self, filename_: &str) -> Result<(), String>
Writes problem data to a file.
§Arguments
filename_A valid file name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.writedata
Examples found in repository?
examples/callback.rs (line 115)
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fn callbackmain(which : &str, data : FileOrText) -> Result<(),String> {
/* Create the optimization task. */
let mut task = Task::new().unwrap();
match data {
FileOrText::Text(data) => { task.read_ptf_string(data)? },
FileOrText::File(fname) => { task.read_data(fname)? }
}
task.write_data("callback.ptf")?;
match which {
"psim" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::PRIMAL_SIMPLEX)?,
"dsim" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::DUAL_SIMPLEX)?,
"intpnt" => task.put_int_param(Iparam::OPTIMIZER,Optimizertype::INTPNT)?,
s => return Err(format!("Invalid argument '{}'",s))
}
/* Directs the log task stream to the 'printstr' function. */
task.with_stream_callback(
Streamtype::LOG,
& mut |msg| print!("{}",msg),
|task|
task.with_info_callback(
& mut callback,
|task|
task.optimize()
)
)?;
Result::Ok(())
}More examples
examples/portfolio_2_frontier.rs (line 101)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
alphas : &[f64],
w : f64) -> Result<Vec<(f64,f64)>,String> {
let k = (GT.len() / n as usize) as i32;
/* Create the optimization task. */
let mut task = match Task::new() {
Some(t) => t,
None => return Err("Failed to create task".to_string()),
};
//task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
task.append_vars(n+1)?;
task.append_cons(1)?;
/* Objective */
task.put_obj_sense(Objsense::MAXIMIZE)?;
let x : Vec<i32> = (0i32..n).collect();
let s = n;
/* Total budget */
let total_budget = w + x0.iter().sum::<f64>();
/* Total budget constraint - set bounds l^c = u^c */
task.put_con_bound(0i32, mosek::Boundkey::FX, total_budget, total_budget)?;
task.put_con_name(0i32,"budget")?;
task.put_c_slice(0,n,mu)?;
/* x variables. */
for (j,xj) in x.iter().enumerate() {
/* Coefficients in the first row of A */
task.put_aij(0, *xj, 1.0)?;
/* No short-selling - x^l = 0, x^u = inf */
task.put_var_bound(*xj, mosek::Boundkey::LO, 0.0, 0.0)?;
task.put_var_name(*xj, format!("x[{}]",j+1).as_str())?;
}
task.put_var_name(s, "s")?;
task.put_var_bound(s, mosek::Boundkey::FR, 0.0, 0.0)?;
// risk bound
// (s,0.5,GT * x) in Q_r
{
let acci = task.get_num_acc()?;
let afei = task.get_num_afe()?;
task.append_afes(k as i64 + 2)?;
let dom = task.append_r_quadratic_cone_domain(k as i64+2)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 2].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_f_entry(afei,s,1.0)?;
task.put_afe_g(afei+1,0.5)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 2, j as i32, *v)?;
}
}
let frontier : Vec<(f64,f64)> = alphas.iter().filter_map(|alpha| {
/* Sets the objective function coefficient for s. */
if let Err(_) = task.put_c_j(s, - *alpha) { None }
else if let Err(_) = task.optimize() { None }
else if let Err(_) = task.write_data(format!("portfolio_2_frontier-{}.ptf",alpha).as_str()) { None }
else if let Ok(solsta) = task.get_sol_sta(Soltype::ITR) {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
match solsta {
Solsta::OPTIMAL => {
let mut xx = vec![0.0; n as usize+1];
if let Err(_) = task.get_xx(Soltype::ITR,xx.as_mut_slice()) { None }
else {
Some((*alpha,mu.iter().zip(xx.iter()).map(|(m,x)| m * x).sum::<f64>()))
}
}
_ => None
}
}
else {
None
}
}).collect();
Ok(frontier)
}examples/portfolio_5_card.rs (line 165)
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fn portfolio(n : i32,
mu : &[f64],
GT : &[f64],
x0 : &[f64],
gamma : f64,
p : i32,
w : f64) -> Result<(Vec<f64>,f64),String> {
/* Create the optimization task. */
let mut task = match Task::new() {
Some(e) => e,
None => return Err("Failed to create task".to_string()),
};
let k = (GT.len() / n as usize) as i32;
// task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;
/* Compute total wealth */
let w0 = w + x0.iter().sum::<f64>();
task.append_vars(3*n)?;
let all_vars : Vec<i32> = (0..3*n).collect();
let x = &all_vars[0..n as usize];
let y = &all_vars[n as usize..2*n as usize];
let z = &all_vars[2*n as usize..3*n as usize];
task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;
for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
task.put_var_type(*yj, Variabletype::TYPE_INT)?;
}
// objective
task.put_obj_sense(Objsense::MAXIMIZE)?;
for (j,mui) in x.iter().zip(mu.iter()) {
task.put_c_j(*j, *mui)?;
}
let n_ones = vec![1.0; n as usize];
// budget constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"budget")?;
task.put_a_row(coni,
x,
n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
}
// |x-x0| <= z
{
let coni = task.get_num_con()?;
task.append_cons(2 * n)?;
for i in 0..n {
task.put_con_name(coni+i, format!("zabs1[{}]",1 + i).as_str())?;
task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
}
let ones = vec![1.0; n as usize];
let minusones = vec![-1.0; n as usize];
let con_abs1 : Vec<i32> = (coni..coni+n).collect();
let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
}
// cardinality constraint
{
let coni = task.get_num_con()?;
task.append_cons(1)?;
task.put_con_name(coni,"cardinality")?;
task.put_a_row(coni, y, n_ones.as_slice())?;
task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
}
// (gamma,G'x) in Q
{
let afei = task.get_num_afe()?;
let acci = task.get_num_acc()?;
task.append_afes(k as i64+1)?;
let dom = task.append_quadratic_cone_domain(k as i64+1)?;
task.append_acc_seq(dom,
afei,
vec![0.0; k as usize + 1].as_slice())?;
task.put_acc_name(acci,"risk")?;
task.put_afe_g(afei,gamma)?;
for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
}
}
// Switch
{
let coni = task.get_num_con()?;
task.append_cons(n)?;
for i in 0..n {
task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
}
let conlist : Vec<i32> = (coni..coni+n).collect();
task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;
task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
}
let _ = task.optimize()?;
task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;
// Check if the integer solution is an optimal point
if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
// See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
eprintln!("Solution not optimal!");
std::process::exit(1);
}
let mut xx = vec![0.0;n as usize];
task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}sourcepub fn write_json_sol(&self, filename_: &str) -> Result<(), String>
pub fn write_json_sol(&self, filename_: &str) -> Result<(), String>
Writes a solution to a JSON file.
§Arguments
filename_A valid file name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.writejsonsol
sourcepub fn write_param_file(&self, filename_: &str) -> Result<(), String>
pub fn write_param_file(&self, filename_: &str) -> Result<(), String>
Writes all the parameters to a parameter file.
§Arguments
filename_A valid file name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.writeparamfile
sourcepub fn write_solution(
&self,
whichsol_: i32,
filename_: &str
) -> Result<(), String>
pub fn write_solution( &self, whichsol_: i32, filename_: &str ) -> Result<(), String>
Write a solution to a file.
§Arguments
-
whichsol_Selects a solution.See Soltype
-
filename_A valid file name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.writesolution
sourcepub fn write_solution_file(&self, filename_: &str) -> Result<(), String>
pub fn write_solution_file(&self, filename_: &str) -> Result<(), String>
Write solution file in format determined by the filename
§Arguments
filename_A valid file name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.writesolutionfile
sourcepub fn write_stat(&mut self, filename_: &str) -> Result<(), String>
pub fn write_stat(&mut self, filename_: &str) -> Result<(), String>
Appends a record to the statistics file.
§Arguments
filename_A valid file name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.writestat
sourcepub fn write_task(&self, filename_: &str) -> Result<(), String>
pub fn write_task(&self, filename_: &str) -> Result<(), String>
Write a complete binary dump of the task data.
§Arguments
filename_A valid file name.
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.writetask
sourcepub fn write_task_solver_result_file(
&self,
filename_: &str,
compress_: i32
) -> Result<(), String>
pub fn write_task_solver_result_file( &self, filename_: &str, compress_: i32 ) -> Result<(), String>
Internal
§Arguments
-
filename_A valid file name. -
compress_Data compression type.See Compresstype
Full documentation: https://docs.mosek.com/latest/capi/alphabetic-functionalities.html#mosek.env.writetasksolverresult_file
Trait Implementations§
Auto Trait Implementations§
Blanket Implementations§
source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more