get_problem_data

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. This version uses the S7 object system for improved
performance and maintainability.

Anqi Fu

CVXR

Disciplined Convex Optimization

Balasubramanian Narasimhan

Steven Diamond

John Miller

Stephen Boyd

get_problem_data function

<dl><dt>x</dt>
<dd>A <code>Problem</code> object.</dd>
<dt>solver</dt>
<dd>Character string naming solver, or <code>NULL</code> for
automatic selection.</dd>
<dt>gp</dt>
<dd>Logical; if <code>TRUE</code>, parse the problem as a geometric program.</dd>
<dt>enforce_dpp</dt>
<dd>Logical; if <code>TRUE</code>, raise an error when a
parametrized problem is not DPP instead of compiling it as non-DPP.</dd>
<dt>ignore_dpp</dt>
<dd>Logical; if <code>TRUE</code>, treat a DPP problem as non-DPP
(skip the DPP fast path).</dd>
<dt>...</dt>
<dd>Additional solver options.</dd></dl>

Arguments

Get Problem Data for a Solver (deprecated) — get_problem_data

<dl>

<dt>x</dt>
<dd>A <code>Problem</code> object.</dd>


<dt>solver</dt>
<dd>Character string naming solver, or <code>NULL</code> for
automatic selection.</dd>


<dt>gp</dt>
<dd>Logical; if <code>TRUE</code>, parse the problem as a geometric program.</dd>


<dt>enforce_dpp</dt>
<dd>Logical; if <code>TRUE</code>, raise an error when a
parametrized problem is not DPP instead of compiling it as non-DPP.</dd>


<dt>ignore_dpp</dt>
<dd>Logical; if <code>TRUE</code>, treat a DPP problem as non-DPP
(skip the DPP fast path).</dd>


<dt>...</dt>
<dd>Additional solver options.</dd>

</dl>

get_problem_data: Get Problem Data for a Solver (deprecated)

Description

Usage

Value

Arguments

Details

See Also