is_dpp

Determines whether an expression or problem satisfies the rules of
Disciplined Parameterized Programming (DPP). A DPP-compliant problem
enables caching the compilation across parameter value changes.

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

is_dpp function

<dl><dt>x</dt>
<dd>An expression, constraint, or problem object.</dd>
<dt>context</dt>
<dd>Either <code>"dcp"</code> (default) or <code>"dgp"</code>: which
discipline to check parameterization against. Mirrors CVXPY's
<code>is_dpp(context=...)</code>.</dd></dl>

Arguments

Check DPP Compliance — is_dpp

<dl>

<dt>x</dt>
<dd>An expression, constraint, or problem object.</dd>


<dt>context</dt>
<dd>Either <code>"dcp"</code> (default) or <code>"dgp"</code>: which
discipline to check parameterization against. Mirrors CVXPY's
<code>is_dpp(context=...)</code>.</dd>

</dl>

is_dpp: Check DPP Compliance

Description

Usage

Value

Arguments