# ------------------------------------------------------------------------------
# Copyright (C) 2019 Maximilian Stahlberg
# Based on the original picos.expressions module by Guillaume Sagnol.
#
# This file is part of PICOS.
#
# PICOS is free software: you can redistribute it and/or modify it under the
# terms of the GNU General Public License as published by the Free Software
# Foundation, either version 3 of the License, or (at your option) any later
# version.
#
# PICOS is distributed in the hope that it will be useful, but WITHOUT ANY
# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
# A PARTICULAR PURPOSE. See the GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License along with
# this program. If not, see <http://www.gnu.org/licenses/>.
# ------------------------------------------------------------------------------
"""Implements :class:`GeometricMean`."""
import operator
from collections import namedtuple
import cvxopt
import numpy
from .. import glyphs
from ..apidoc import api_end, api_start
from ..constraints import GeometricMeanConstraint
from .data import convert_and_refine_arguments, convert_operands, cvx2np
from .exp_affine import AffineExpression
from .expression import Expression, refine_operands, validate_prediction
_API_START = api_start(globals())
# -------------------------------
[docs]class GeometricMean(Expression):
r"""Geometric mean of an affine expression.
:Definition:
For an :math:`n`-dimensional affine expression :math:`x` with
:math:`x \geq 0`, the geometric mean is given as
.. math::
\left(\prod_{i = 1}^n x_i \right)^{\frac{1}{n}}.
.. warning::
When you pose a lower bound on a geometric mean, then PICOS enforces
:math:`x \geq 0` through an auxiliary constraint during solution search.
"""
# --------------------------------------------------------------------------
# Initialization and factory methods.
# --------------------------------------------------------------------------
[docs] @convert_and_refine_arguments("x")
def __init__(self, x):
"""Construct a :class:`GeometricMean`.
:param x: The affine expression to form the geometric mean of.
:type x: ~picos.expressions.AffineExpression
"""
if not isinstance(x, AffineExpression):
raise TypeError("Can only form the geometrtic mean of a real affine"
" expression, not of {}.".format(type(x).__name__))
self._x = x
Expression.__init__(
self, "Geometric Mean", glyphs.make_function("geomean")(x.string))
# --------------------------------------------------------------------------
# Abstract method implementations and method overridings, except _predict.
# --------------------------------------------------------------------------
def _get_refined(self):
if self._x.constant:
return AffineExpression.from_constant(self.value, 1, self._symbStr)
elif len(self._x) == 1:
return self._x.renamed(self._symbStr)
else:
return self
Subtype = namedtuple("Subtype", ("argdim"))
def _get_subtype(self):
return self.Subtype(len(self._x))
def _get_value(self):
value = self._x._get_value()
value = numpy.prod(cvx2np(value))**(1.0 / len(self._x))
return cvxopt.matrix(value)
def _get_mutables(self):
return self._x._get_mutables()
def _is_convex(self):
return False
def _is_concave(self):
return True # Only for nonnegative x.
def _replace_mutables(self, mapping):
return self.__class__(self._x._replace_mutables(mapping))
def _freeze_mutables(self, freeze):
return self.__class__(self._x._freeze_mutables(freeze))
# --------------------------------------------------------------------------
# Python special method implementations, except constraint-creating ones.
# --------------------------------------------------------------------------
@classmethod
def _mul(cls, self, other, forward):
if isinstance(other, AffineExpression) and other.constant:
factor = other.safe_value
if not factor:
return AffineExpression.zero()
elif factor == 1:
return self
elif factor > 0:
if forward:
string = glyphs.clever_mul(self.string, other.string)
else:
string = glyphs.clever_mul(other.string, self.string)
product = cls(other*self._x)
product._typeStr = "Scaled " + product._typeStr
product._symbStr = string
return product
if forward:
return Expression.__mul__(self, other)
else:
return Expression.__rmul__(self, other)
[docs] @convert_operands(scalarRHS=True)
@refine_operands()
def __mul__(self, other):
return GeometricMean._mul(self, other, True)
[docs] @convert_operands(scalarRHS=True)
@refine_operands()
def __rmul__(self, other):
return GeometricMean._mul(self, other, False)
# --------------------------------------------------------------------------
# Methods and properties that return modified copies.
# --------------------------------------------------------------------------
@property
def x(self):
"""The expression under the mean."""
return self._x
# --------------------------------------------------------------------------
# Constraint-creating operators, and _predict.
# --------------------------------------------------------------------------
@classmethod
def _predict(cls, subtype, relation, other):
assert isinstance(subtype, cls.Subtype)
if relation == operator.__ge__:
if issubclass(other.clstype, AffineExpression) \
and other.subtype.dim == 1:
return GeometricMeanConstraint.make_type(subtype.argdim)
return NotImplemented
[docs] @convert_operands(scalarRHS=True)
@validate_prediction
@refine_operands()
def __ge__(self, other):
if isinstance(other, AffineExpression):
return GeometricMeanConstraint(self, other)
else:
return NotImplemented
# --------------------------------------
__all__ = api_end(_API_START, globals())