ConeMatrixStuffing-class

ConeMatrixStuffing

accepts,ConeMatrixStuffing,Problem-method

stuffed_objective,ConeMatrixStuffing,Problem,CoeffExtractor-method

Linear cone problems are assumed to have a linear objective and cone constraints,
which may have zero or more arguments, all of which must be affine.

An object-oriented modeling language for disciplined
convex programming (DCP) as described in Fu, Narasimhan, and Boyd
(2020, <doi:10.18637/jss.v094.i14>). It allows the user to
formulate convex optimization problems in a natural way following
mathematical convention and DCP rules. The system analyzes the
problem, verifies its convexity, converts it into a canonical
form, and hands it off to an appropriate solver to obtain the
solution. Interfaces to solvers on CRAN and elsewhere are
provided, both commercial and open source.

Anqi Fu

CVXR

Disciplined Convex Optimization

Balasubramanian Narasimhan

David W Kang

Steven Diamond

John Miller

Stephen Boyd

Paul Kunsberg Rosenfield

ConeMatrixStuffing-class function

<dl><dt>object</dt>
<dd>A ConeMatrixStuffing object.</dd>
<dt>problem</dt>
<dd>A Problem object.</dd>
<dt>extractor</dt>
<dd>Used to extract the affine coefficients of the objective.</dd></dl>

Arguments

<ul>
<li><code>accepts(object = ConeMatrixStuffing, problem = Problem)</code>: Is the solver accepted?</li>
<li><code>stuffed_objective(
 object = ConeMatrixStuffing,
 problem = Problem,
 extractor = CoeffExtractor
)</code>: Returns a list of the stuffed matrices</li>
</ul>

Methods (by generic)

Construct Matrices for Linear Cone Problems — ConeMatrixStuffing-class

<dl>

<dt>object</dt>
<dd>A ConeMatrixStuffing object.</dd>


<dt>problem</dt>
<dd>A Problem object.</dd>


<dt>extractor</dt>
<dd>Used to extract the affine coefficients of the objective.</dd>

</dl>

ConeMatrixStuffing-class: Construct Matrices for Linear Cone Problems

Description

Usage

Arguments

Methods (by generic)

Details