power

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

power function

<dl><dt>x</dt>
<dd>An Expression (the base), OR a positive constant if <code>p</code> is a
variable (the identity <code>b^x = exp(x * log(b))</code> is used).</dd>
<dt>p</dt>
<dd>Numeric exponent, Parameter, or Expression. If <code>p</code> is a
non-constant Expression and <code>x</code> is a positive constant, dispatches to
<code>exp(p * log(x))</code>.</dd>
<dt>max_denom</dt>
<dd>Maximum denominator for rational approximation</dd>
<dt>approx</dt>
<dd>If TRUE (default), use SOC approximation. If FALSE, use exact power cone.</dd></dl>

Arguments

Create a Power atom — power

<dl>

<dt>x</dt>
<dd>An Expression (the base), OR a positive constant if <code>p</code> is a
variable (the identity <code>b^x = exp(x * log(b))</code> is used).</dd>


<dt>p</dt>
<dd>Numeric exponent, Parameter, or Expression. If <code>p</code> is a
non-constant Expression and <code>x</code> is a positive constant, dispatches to
<code>exp(p * log(x))</code>.</dd>


<dt>max_denom</dt>
<dd>Maximum denominator for rational approximation</dd>


<dt>approx</dt>
<dd>If TRUE (default), use SOC approximation. If FALSE, use exact power cone.</dd>

</dl>

Create a Power atom

power: Create a Power atom

Description

Usage

Value

Arguments