problem_unpack_results

Inverts the reduction chain and unpacks the raw solver solution into
the original problem's variables and constraints. This is step 3 of
the decomposed solve pipeline:<ol>
<li><code>problem_data()</code> -- compile the problem</li>
<li><code>solve_via_data(chain, data)</code> -- call the solver</li>
<li><code>problem_unpack_results()</code> -- invert and unpack</li>
</ol>

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

problem_unpack_results function

<dl><dt>problem</dt>
<dd>A <code>Problem</code> object.</dd>
<dt>solution</dt>
<dd>The raw solver result from <code>solve_via_data()</code>.</dd>
<dt>chain</dt>
<dd>The <code>SolvingChain</code> from <code>problem_data()</code>.</dd>
<dt>inverse_data</dt>
<dd>The inverse data list from <code>problem_data()</code>.</dd></dl>

Arguments

Unpack Solver Results into a Problem — problem_unpack_results

<dl>

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


<dt>solution</dt>
<dd>The raw solver result from <code>solve_via_data()</code>.</dd>


<dt>chain</dt>
<dd>The <code>SolvingChain</code> from <code>problem_data()</code>.</dd>


<dt>inverse_data</dt>
<dd>The inverse data list from <code>problem_data()</code>.</dd>

</dl>

problem_unpack_results: Unpack Solver Results into a Problem

Description

Usage

Value

Arguments

Details

See Also