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-rw-r--r--sumofsquares/__init__.py4
-rw-r--r--sumofsquares/constraints.py92
-rw-r--r--sumofsquares/problems.py77
3 files changed, 109 insertions, 64 deletions
diff --git a/sumofsquares/__init__.py b/sumofsquares/__init__.py
index 71aafde..99438d6 100644
--- a/sumofsquares/__init__.py
+++ b/sumofsquares/__init__.py
@@ -51,7 +51,7 @@ from polymatrix.expression.expression import Expression
from polymatrix.expressionstate.abc import ExpressionState
from .abc import Problem, Result, Set, Constraint, Solver
-from .constraints import ArchimedeanSet, NonNegative
+from .constraints import BasicSemialgebraicSet, NonNegative
from .problems import PutinarSOSProblem
from .utils import partition
from .variable import OptVariable, from_names
@@ -62,7 +62,7 @@ def make_sos_constraint(expr: Expression, domain: Set | None = None) -> NonNegat
def make_set(*polynomials: Iterable[Expression]):
- return ArchimedeanSet(polynomials)
+ return BasicSemialgebraicSet(polynomials)
def make_problem(
diff --git a/sumofsquares/constraints.py b/sumofsquares/constraints.py
index 61be087..4209ffe 100644
--- a/sumofsquares/constraints.py
+++ b/sumofsquares/constraints.py
@@ -1,15 +1,30 @@
+import math
+
from dataclasses import dataclass
from dataclassabc import dataclassabc
from typing_extensions import override
-from typing import NamedTuple
+from typing import Iterable
+
+import polymatrix as poly
from polymatrix.expression.expression import Expression
+from polymatrix.expressionstate.abc import ExpressionState
+from polymatrix.polymatrix.abc import PolyMatrix
+from polymatrix.statemonad.init import init_state_monad
+from polymatrix.variable.abc import Variable
from .abc import Set, Constraint
+from .error import AlgebraicError
+from .variable import OptVariable, from_name as opt_variable_from_name
+
+
+# ┏━┓┏━╸╺┳╸┏━┓
+# ┗━┓┣╸ ┃ ┗━┓
+# ┗━┛┗━╸ ╹ ┗━┛
@dataclass(frozen=True)
-class ArchimedeanSet(Set):
+class BasicSemialgebraicSet(Set):
r"""
A set that is described by the intersection of the positive loci of a
finite number of polynomials (under some conditions). Roughly speaking this
@@ -25,18 +40,19 @@ class ArchimedeanSet(Set):
\subseteq \mathbf{R}^q.
This tuple stores the :math:`g_i(x)`.
-
- **Important note:** this package does not check whether the set is actually
- Archimedean! It is assumed that the given :math:`g_i` make
- :math:`\mathbf{K}` Archimedean.
"""
- polynomials: tuple[Expression]
+ polynomials: tuple[Expression, ...]
def __str__(self):
polynomials = ', '.join(map(str, self.polynomials))
return f"{self.__class__.__qualname__}({polynomials})"
+# ┏━╸┏━┓┏┓╻┏━┓╺┳╸┏━┓┏━┓╻┏┓╻╺┳╸┏━┓
+# ┃ ┃ ┃┃┗┫┗━┓ ┃ ┣┳┛┣━┫┃┃┗┫ ┃ ┗━┓
+# ┗━╸┗━┛╹ ╹┗━┛ ╹ ╹┗╸╹ ╹╹╹ ╹ ╹ ┗━┛
+
+
@dataclassabc(frozen=True)
class EqualToZero(Constraint):
""" Constrain an expression to be equal to zero. """
@@ -60,7 +76,7 @@ class NonNegative(Constraint):
understood as `expression` being SOS.
"""
expression: Expression
- domain: ArchimedeanSet | None = None
+ domain: BasicSemialgebraicSet | None = None
@override
def __str__(self):
@@ -79,3 +95,63 @@ class PositiveSemiDefinite(Constraint):
@dataclassabc(frozen=True)
class ExponentialCone(Constraint):
expression: Expression
+
+
+# ┏━┓┏━┓┏━┓╻╺┳╸╻╻ ╻┏━┓╺┳╸┏━╸╻ ╻ ┏━╸┏┓╻┏━┓┏━┓┏━╸╺┳╸╺━┓┏━╸
+# ┣━┛┃ ┃┗━┓┃ ┃ ┃┃┏┛┗━┓ ┃ ┣╸ ┃ ┃ ┣╸ ┃┗┫┗━┓┣━┫┣╸ ┃ ┏━┛┣╸
+# ╹ ┗━┛┗━┛╹ ╹ ╹┗┛ ┗━┛ ╹ ┗━╸┗━╸┗━╸┗━╸╹ ╹┗━┛╹ ╹┗━╸ ╹ ┗━╸┗━╸
+
+def putinar_psatz(
+ constr: NonNegative,
+ variables: Iterable[OptVariable],
+ polynomial_variables: Iterable[Variable],
+ multiplier_name: str
+ ) -> Iterable[Constraint]:
+ """
+ Apply Putinar's positivstellensatz to a non-negativity constraint over an
+ archimedean domain.
+ """
+ if not constr.domain:
+ # TODO: maybe raise an exception to warn the user?
+ return (constr,)
+
+ # Number of variables in the original problem
+ q = sum(math.prod(v.shape) for v in variables)
+ x = poly.v_stack((1,) + tuple(polynomial_variables))
+
+ new_constraints = []
+ new_constr = constr.expression
+
+ for domain_poly in constr.domain.polynomials:
+ # To know the degree of the domain polynomial we need to evaluate the
+ # expression, hence we use a monad here
+ def make_multiplier( state: ExpressionState) -> tuple[ExpressionState, PolyMatrix]:
+ state, constr_pm = constr.expression.degree().apply(state)
+ state, domain_poly_pm = domain_poly.degree().apply(state)
+
+ constr_deg = constr_pm.at(0, 0).constant()
+ domain_poly_deg = domain_poly_pm.at(0, 0).constant()
+
+ # degree of multiplier
+ d = constr_deg - domain_poly_deg
+ if d < 0:
+ raise AlgebraicError("Cannot create Positivstellensatz multiplier because "
+ f"constraint polynomial has degree {constr_deg} and domain "
+ f"polynomial {domain_poly} has degree {domain_poly_deg}")
+
+ n = sum(math.comb(k + q - 1, k) for k in range(0, d+1))
+
+ # TODO: check that there is not a variable with this name already
+ # Coefficients of the multiplier polynomial
+ c = opt_variable_from_name(multiplier_name, shape=(1,n))
+ multiplier = c @ x.combinations(tuple(range(d +1)))
+
+ return multiplier.apply(state)
+
+ m = poly.from_statemonad(init_state_monad(make_multiplier))
+
+ # Subtract multiplier from expression and impose that it is also SOS
+ new_constr -= m * domain_poly
+ new_constraints.append(NonNegative(m))
+
+ return new_constraints
diff --git a/sumofsquares/problems.py b/sumofsquares/problems.py
index 3ec3f54..3105eae 100644
--- a/sumofsquares/problems.py
+++ b/sumofsquares/problems.py
@@ -14,11 +14,10 @@ from typing_extensions import override
from polymatrix.expression.expression import Expression, VariableExpression, init_expression
from polymatrix.expressionstate.abc import ExpressionState
-from polymatrix.statemonad.init import init_state_monad
from polymatrix.variable.abc import Variable
from .abc import Problem, Constraint, Solver, Result
-from .constraints import NonNegative
+from .constraints import NonNegative, putinar_psatz
from .error import AlgebraicError
from .solver.cvxopt import solve_sos_cone as cvxopt_solve_sos_cone
from .utils import partition
@@ -48,6 +47,22 @@ class SOSResult(Result):
@dataclassabc(frozen=True)
+class SchmuedgenSOSProblem(Problem):
+ r"""
+ SOS problem with quadratic cost, linear constraints and optinally with
+ positivity constraints over a basic closed semialgebraic set
+ :math:`\mathbf{K}`. To constrain the positivity over :math:`\mathbf{K}`
+ this problem uses Schmüdgen's Positivstellensatz.
+ """
+ cost: Expression
+ constraints: Sequence[Constraint]
+ variables: Sequence[OptVariable]
+ polynomial_variables: Sequence[Variable]
+ solver: Solver
+ state: ExpressionState
+
+
+@dataclassabc(frozen=True)
class PutinarSOSProblem(Problem):
r"""
SOS problem with quadratic cost, linear constraints and optinally with
@@ -72,60 +87,14 @@ class PutinarSOSProblem(Problem):
# Add langrange-multiplier-like polynomials to SOS constraints, while
# leaving the rest untouched.
- variables = tuple(self.variables)
constraints, to_process = partition(need_positivstellensatz, self.constraints)
+ new_constraints: list[Constraint] = []
+ for i, c in enumerate(to_process):
+ new_constraints.extend(putinar_psatz(c, self.variables, self.polynomial_variables, r"\gamma_{i}"))
- # New variables and constraints that will be introduced by the
- # positivstellensatz
- # new_variables = []
- new_constraints = []
-
- # Number of variables in the original problem
- q = len(self.variables)
- x = poly.v_stack((1,) + tuple(self.polynomial_variables))
-
- for i, constr in enumerate(to_process):
- # FIXME: this is not optimal, look into how to determine the
- # smallest degree needed to make the positivstellensatz work.
- new_constr = constr.expression
- for domain_poly in constr.domain.polynomials:
- # To know the degree of the polynomial we need to evaluate the
- # expression, hence we use a monad here
- def make_multiplier(state):
- state, constr_pm = constr.expression.degree().apply(state)
- state, domain_poly_pm = domain_poly.degree().apply(state)
-
- constr_deg = constr_pm.at(0, 0).constant()
- domain_poly_deg = domain_poly_pm.at(0, 0).constant()
-
- # degree of multiplier
- d = constr_deg - domain_poly_deg
- if d < 0:
- raise AlgebraicError("Cannot create Positivstellensatz multiplier because "
- f"constraint polynomial has degree {constr_deg} and domain "
- f"polynomial {domain_poly} has degree {domain_poly_deg}")
-
- n = sum(math.comb(k + q - 1, k) for k in range(0, d+1))
-
- # TODO: check that there is not a variable with this name already
- # Coefficients of the multiplier polynomial
- c = opt_variable_from_name(rf"\gamma_{i}", shape=(1,n))
- multiplier = c @ x.combinations(tuple(range(d +1)))
-
- return multiplier.apply(state)
-
- m = poly.from_statemonad(init_state_monad(make_multiplier))
-
- # Subtract multiplier from expression and impose that it is also SOS
- new_constr -= m * domain_poly
- new_constraints.append(NonNegative(m))
-
- new_constraints.append(NonNegative(new_constr))
-
- # FIXME: this is a dirty trick to make it work for now,
- # it is not efficient, replace with correct solution
-
- # Convert to polymatrix object to extract variables
+ # Convert to polymatrix object to extract variables created by p-satz
+ # FIXME: this is a dirty trick to make it work for now, it is not
+ # efficient, is there a better way?
new_state = self.state
for c in new_constraints:
new_state, _ = c.expression.apply(new_state)