from sage.all import *
-from sage.geometry.cone import is_Cone
-
-def is_positive_on(L,K):
- r"""
- Determine whether or not ``L`` is positive on ``K``.
-
- We say that ``L`` is positive on a closed convex cone ``K`` if
- `L\left\lparen x \right\rparen` belongs to ``K`` for all `x` in
- ``K``. This property need only be checked for generators of ``K``.
-
- To reliably check whether or not ``L`` is positive, its base ring
- must be either exact (for example, the rationals) or ``SR``. An
- exact ring is more reliable, but in some cases a matrix whose
- entries contain symbolic constants like ``e`` and ``pi`` will work.
-
- INPUT:
-
- - ``L`` -- A matrix over either an exact ring or ``SR``.
-
- - ``K`` -- A polyhedral closed convex cone.
-
- OUTPUT:
-
- If the base ring of ``L`` is exact, then ``True`` will be returned if
- and only if ``L`` is positive on ``K``.
-
- If the base ring of ``L`` is ``SR``, then the situation is more
- complicated:
-
- - ``True`` will be returned if it can be proven that ``L``
- is positive on ``K``.
- - ``False`` will be returned if it can be proven that ``L``
- is not positive on ``K``.
- - ``False`` will also be returned if we can't decide; specifically
- if we arrive at a symbolic inequality that cannot be resolved.
-
- EXAMPLES:
-
- Nonnegative matrices are positive operators on the nonnegative
- orthant::
-
- sage: K = Cone([(1,0,0),(0,1,0),(0,0,1)])
- sage: L = random_matrix(QQ,3).apply_map(abs)
- sage: is_positive_on(L,K)
- True
-
- TESTS:
-
- The identity operator is always positive::
-
- sage: set_random_seed()
- sage: K = random_cone(max_ambient_dim=8)
- sage: L = identity_matrix(K.lattice_dim())
- sage: is_positive_on(L,K)
- True
-
- The "zero" operator is always positive::
-
- sage: K = random_cone(max_ambient_dim=8)
- sage: R = K.lattice().vector_space().base_ring()
- sage: L = zero_matrix(R, K.lattice_dim())
- sage: is_positive_on(L,K)
- True
-
- Everything in ``K.positive_operators_gens()`` should be
- positive on ``K``::
-
- sage: K = random_cone(max_ambient_dim=5)
- sage: all([ is_positive_on(L,K) # long time
- ....: for L in K.positive_operators_gens() ]) # long time
- True
- sage: all([ is_positive_on(L.change_ring(SR),K) # long time
- ....: for L in K.positive_operators_gens() ]) # long time
- True
-
- """
- if not is_Cone(K):
- raise TypeError('K must be a Cone')
- if not L.base_ring().is_exact() and not L.base_ring() is SR:
- raise ValueError('base ring of operator L is neither SR nor exact')
-
- if L.base_ring().is_exact():
- # This should be way faster than computing the dual and
- # checking a bunch of inequalities, but it doesn't work if
- # ``L*x`` is symbolic. For example, ``e in Cone([(1,)])``
- # is true, but returns ``False``.
- return all([ L*x in K for x in K ])
- else:
- # Fall back to inequality-checking when the entries of ``L``
- # might be symbolic.
- return all([ s*(L*x) >= 0 for x in K for s in K.dual() ])
-
-
-def is_cross_positive_on(L,K):
- r"""
- Determine whether or not ``L`` is cross-positive on ``K``.
-
- We say that ``L`` is cross-positive on a closed convex cone``K`` if
- `\left\langle L\left\lparenx\right\rparen,s\right\rangle \ge 0` for
- all pairs `\left\langle x,s \right\rangle` in the complementarity
- set of ``K``. This property need only be checked for generators of
- ``K`` and its dual.
-
- To reliably check whether or not ``L`` is cross-positive, its base
- ring must be either exact (for example, the rationals) or ``SR``. An
- exact ring is more reliable, but in some cases a matrix whose
- entries contain symbolic constants like ``e`` and ``pi`` will work.
-
- INPUT:
-
- - ``L`` -- A matrix over either an exact ring or ``SR``.
-
- - ``K`` -- A polyhedral closed convex cone.
-
- OUTPUT:
-
- If the base ring of ``L`` is exact, then ``True`` will be returned if
- and only if ``L`` is cross-positive on ``K``.
-
- If the base ring of ``L`` is ``SR``, then the situation is more
- complicated:
-
- - ``True`` will be returned if it can be proven that ``L``
- is cross-positive on ``K``.
- - ``False`` will be returned if it can be proven that ``L``
- is not cross-positive on ``K``.
- - ``False`` will also be returned if we can't decide; specifically
- if we arrive at a symbolic inequality that cannot be resolved.
-
- EXAMPLES:
-
- The identity operator is always cross-positive::
-
- sage: set_random_seed()
- sage: K = random_cone(max_ambient_dim=8)
- sage: L = identity_matrix(K.lattice_dim())
- sage: is_cross_positive_on(L,K)
- True
-
- The "zero" operator is always cross-positive::
-
- sage: K = random_cone(max_ambient_dim=8)
- sage: R = K.lattice().vector_space().base_ring()
- sage: L = zero_matrix(R, K.lattice_dim())
- sage: is_cross_positive_on(L,K)
- True
-
- TESTS:
-
- Everything in ``K.cross_positive_operators_gens()`` should be
- cross-positive on ``K``::
-
- sage: K = random_cone(max_ambient_dim=5)
- sage: all([ is_cross_positive_on(L,K) # long time
- ....: for L in K.cross_positive_operators_gens() ]) # long time
- True
- sage: all([ is_cross_positive_on(L.change_ring(SR),K) # long time
- ....: for L in K.cross_positive_operators_gens() ]) # long time
- True
-
- """
- if not is_Cone(K):
- raise TypeError('K must be a Cone')
- if not L.base_ring().is_exact() and not L.base_ring() is SR:
- raise ValueError('base ring of operator L is neither SR nor exact')
-
- return all([ s*(L*x) >= 0
- for (x,s) in K.discrete_complementarity_set() ])
-
-def is_Z_on(L,K):
- r"""
- Determine whether or not ``L`` is a Z-operator on ``K``.
-
- We say that ``L`` is a Z-operator on a closed convex cone``K`` if
- `\left\langle L\left\lparenx\right\rparen,s\right\rangle \le 0` for
- all pairs `\left\langle x,s \right\rangle` in the complementarity
- set of ``K``. It is known that this property need only be checked
- for generators of ``K`` and its dual.
-
- A matrix is a Z-operator on ``K`` if and only if its negation is a
- cross-positive operator on ``K``.
-
- To reliably check whether or not ``L`` is a Z operator, its base
- ring must be either exact (for example, the rationals) or ``SR``. An
- exact ring is more reliable, but in some cases a matrix whose
- entries contain symbolic constants like ``e`` and ``pi`` will work.
-
- INPUT:
-
- - ``L`` -- A matrix over either an exact ring or ``SR``.
-
- - ``K`` -- A polyhedral closed convex cone.
-
- OUTPUT:
-
- If the base ring of ``L`` is exact, then ``True`` will be returned if
- and only if ``L`` is a Z-operator on ``K``.
-
- If the base ring of ``L`` is ``SR``, then the situation is more
- complicated:
-
- - ``True`` will be returned if it can be proven that ``L``
- is a Z-operator on ``K``.
- - ``False`` will be returned if it can be proven that ``L``
- is not a Z-operator on ``K``.
- - ``False`` will also be returned if we can't decide; specifically
- if we arrive at a symbolic inequality that cannot be resolved.
-
- EXAMPLES:
-
- The identity operator is always a Z-operator::
-
- sage: set_random_seed()
- sage: K = random_cone(max_ambient_dim=8)
- sage: L = identity_matrix(K.lattice_dim())
- sage: is_Z_on(L,K)
- True
-
- The "zero" operator is always a Z-operator::
-
- sage: K = random_cone(max_ambient_dim=8)
- sage: R = K.lattice().vector_space().base_ring()
- sage: L = zero_matrix(R, K.lattice_dim())
- sage: is_Z_on(L,K)
- True
-
- TESTS:
-
- Everything in ``K.Z_operators_gens()`` should be a Z-operator
- on ``K``::
-
- sage: K = random_cone(max_ambient_dim=5)
- sage: all([ is_Z_on(L,K) # long time
- ....: for L in K.Z_operators_gens() ]) # long time
- True
- sage: all([ is_Z_on(L.change_ring(SR),K) # long time
- ....: for L in K.Z_operators_gens() ]) # long time
- True
-
- """
- return is_cross_positive_on(-L,K)
-
-
-def is_lyapunov_like_on(L,K):
- r"""
- Determine whether or not ``L`` is Lyapunov-like on ``K``.
-
- We say that ``L`` is Lyapunov-like on a closed convex cone ``K`` if
- `\left\langle L\left\lparenx\right\rparen,s\right\rangle = 0` for
- all pairs `\left\langle x,s \right\rangle` in the complementarity
- set of ``K``. This property need only be checked for generators of
- ``K`` and its dual.
-
- To reliably check whether or not ``L`` is Lyapunov-like, its base
- ring must be either exact (for example, the rationals) or ``SR``. An
- exact ring is more reliable, but in some cases a matrix whose
- entries contain symbolic constants like ``e`` and ``pi`` will work.
-
- INPUT:
-
- - ``L`` -- A matrix over either an exact ring or ``SR``.
-
- - ``K`` -- A polyhedral closed convex cone.
-
- OUTPUT:
-
- If the base ring of ``L`` is exact, then ``True`` will be returned if
- and only if ``L`` is Lyapunov-like on ``K``.
-
- If the base ring of ``L`` is ``SR``, then the situation is more
- complicated:
-
- - ``True`` will be returned if it can be proven that ``L``
- is Lyapunov-like on ``K``.
- - ``False`` will be returned if it can be proven that ``L``
- is not Lyapunov-like on ``K``.
- - ``False`` will also be returned if we can't decide; specifically
- if we arrive at a symbolic inequality that cannot be resolved.
-
- EXAMPLES:
-
- Diagonal matrices are Lyapunov-like operators on the nonnegative
- orthant::
-
- sage: K = Cone([(1,0,0),(0,1,0),(0,0,1)])
- sage: L = diagonal_matrix(random_vector(QQ,3))
- sage: is_lyapunov_like_on(L,K)
- True
-
- TESTS:
-
- The identity operator is always Lyapunov-like::
-
- sage: set_random_seed()
- sage: K = random_cone(max_ambient_dim=8)
- sage: L = identity_matrix(K.lattice_dim())
- sage: is_lyapunov_like_on(L,K)
- True
-
- The "zero" operator is always Lyapunov-like::
-
- sage: K = random_cone(max_ambient_dim=8)
- sage: R = K.lattice().vector_space().base_ring()
- sage: L = zero_matrix(R, K.lattice_dim())
- sage: is_lyapunov_like_on(L,K)
- True
-
- Everything in ``K.lyapunov_like_basis()`` should be Lyapunov-like
- on ``K``::
-
- sage: K = random_cone(max_ambient_dim=5)
- sage: all([ is_lyapunov_like_on(L,K) # long time
- ....: for L in K.lyapunov_like_basis() ]) # long time
- True
- sage: all([ is_lyapunov_like_on(L.change_ring(SR),K) # long time
- ....: for L in K.lyapunov_like_basis() ]) # long time
- True
-
- """
- if not is_Cone(K):
- raise TypeError('K must be a Cone')
- if not L.base_ring().is_exact() and not L.base_ring() is SR:
- raise ValueError('base ring of operator L is neither SR nor exact')
-
- return all([ s*(L*x) == 0
- for (x,s) in K.discrete_complementarity_set() ])
-
def LL_cone(K):
gens = K.lyapunov_like_basis()
L = ToricLattice(K.lattice_dim()**2)
- return Cone([ g.list() for g in gens ], lattice=L, check=False)
+ return Cone(( g.list() for g in gens ), lattice=L, check=False)
def Sigma_cone(K):
gens = K.cross_positive_operators_gens()
L = ToricLattice(K.lattice_dim()**2)
- return Cone([ g.list() for g in gens ], lattice=L, check=False)
+ return Cone(( g.list() for g in gens ), lattice=L, check=False)
def Z_cone(K):
gens = K.Z_operators_gens()
L = ToricLattice(K.lattice_dim()**2)
- return Cone([ g.list() for g in gens ], lattice=L, check=False)
+ return Cone(( g.list() for g in gens ), lattice=L, check=False)
def pi_cone(K1, K2=None):
if K2 is None:
K2 = K1
gens = K1.positive_operators_gens(K2)
L = ToricLattice(K1.lattice_dim()*K2.lattice_dim())
- return Cone([ g.list() for g in gens ], lattice=L, check=False)
+ return Cone(( g.list() for g in gens ), lattice=L, check=False)
projects / sage.d.git / blobdiff