Exp-class: The Exp class.

In CVXR: Disciplined Convex Optimization

The Exp class.

Description

This class represents the elementwise natural exponential e^x.

Usage

Exp(x)

## S4 method for signature 'Exp'
to_numeric(object, values)

## S4 method for signature 'Exp'
sign_from_args(object)

## S4 method for signature 'Exp'
is_atom_convex(object)

## S4 method for signature 'Exp'
is_atom_concave(object)

## S4 method for signature 'Exp'
is_atom_log_log_convex(object)

## S4 method for signature 'Exp'
is_atom_log_log_concave(object)

## S4 method for signature 'Exp'
is_incr(object, idx)

## S4 method for signature 'Exp'
is_decr(object, idx)

## S4 method for signature 'Exp'
.grad(object, values)

Arguments

x	An Expression object.
object	An Exp object.
values	A list of numeric values for the arguments
idx	An index into the atom.

Methods (by generic)

• to_numeric(Exp): The matrix with each element exponentiated.

• sign_from_args(Exp): The atom is positive.

• is_atom_convex(Exp): The atom is convex.

• is_atom_concave(Exp): The atom is not concave.

• is_atom_log_log_convex(Exp): Is the atom log-log convex?

• is_atom_log_log_concave(Exp): Is the atom log-log concave?

• is_incr(Exp): The atom is weakly increasing.

• is_decr(Exp): The atom is not weakly decreasing.

• .grad(Exp): Gives the (sub/super)gradient of the atom w.r.t. each variable

Slots

x

An Expression object.

CVXR documentation built on June 27, 2024, 5:11 p.m.