X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=mjo%2Fcone%2Fcone.py;h=507b6cea5c24d0a4eb745d9245c85a1fbf4ddb90;hb=494fe2e8517d40e3b71a54657e4a69a83cadf423;hp=23043381bca83acd6d7f17479ef4769980b9960f;hpb=012175f3a2591586099b4e955bb440958f2d63d7;p=sage.d.git diff --git a/mjo/cone/cone.py b/mjo/cone/cone.py index 2304338..507b6ce 100644 --- a/mjo/cone/cone.py +++ b/mjo/cone/cone.py @@ -8,6 +8,156 @@ addsitedir(abspath('../../')) from sage.all import * +def random_cone(min_dim=None, max_dim=None, min_rays=None, max_rays=None): + r""" + Generate a random rational convex polyhedral cone. + + Lower and upper bounds may be provided for both the dimension of the + ambient space and the number of generating rays of the cone. Any + parameters left unspecified will be chosen randomly. + + INPUT: + + - ``min_dim`` (default: random) -- The minimum dimension of the ambient + lattice. + + - ``max_dim`` (default: random) -- The maximum dimension of the ambient + lattice. + + - ``min_rays`` (default: random) -- The minimum number of generating rays + of the cone. + + - ``max_rays`` (default: random) -- The maximum number of generating rays + of the cone. + + OUTPUT: + + A new, randomly generated cone. + + TESTS: + + It's hard to test the output of a random process, but we can at + least make sure that we get a cone back:: + + sage: from sage.geometry.cone import is_Cone + sage: K = random_cone() + sage: is_Cone(K) # long time + True + + """ + + def random_min_max(l,u): + r""" + We need to handle four cases to prevent us from doing + something stupid like having an upper bound that's lower than + our lower bound. And we would need to repeat all of that logic + for the dimension/rays, so we consolidate it here. + """ + if l is None and u is None: + # They're both random, just return a random nonnegative + # integer. + return ZZ.random_element().abs() + + if l is not None and u is not None: + # Both were specified. Again, just make up a number and + # return it. If the user wants to give us u < l then he + # can have an exception. + return ZZ.random_element(l,u) + + if l is not None and u is None: + # In this case, we're generating the upper bound randomly + # GIVEN A LOWER BOUND. So we add a random nonnegative + # integer to the given lower bound. + u = l + ZZ.random_element().abs() + return ZZ.random_element(l,u) + + # Here we must be in the only remaining case, where we are + # given an upper bound but no lower bound. We might as well + # use zero. + return ZZ.random_element(0,u) + + d = random_min_max(min_dim, max_dim) + r = random_min_max(min_rays, max_rays) + + L = ToricLattice(d) + rays = [L.random_element() for i in range(0,r)] + + # We pass the lattice in case there are no rays. + return Cone(rays, lattice=L) + + +def discrete_complementarity_set(K): + r""" + Compute the discrete complementarity set of this cone. + + The complementarity set of this cone is the set of all orthogonal + pairs `(x,s)` such that `x` is in this cone, and `s` is in its + dual. The discrete complementarity set restricts `x` and `s` to be + generators of their respective cones. + + OUTPUT: + + A list of pairs `(x,s)` such that, + + * `x` is in this cone. + * `x` is a generator of this cone. + * `s` is in this cone's dual. + * `s` is a generator of this cone's dual. + * `x` and `s` are orthogonal. + + EXAMPLES: + + The discrete complementarity set of the nonnegative orthant consists + of pairs of standard basis vectors:: + + sage: K = Cone([(1,0),(0,1)]) + sage: discrete_complementarity_set(K) + [((1, 0), (0, 1)), ((0, 1), (1, 0))] + + If the cone consists of a single ray, the second components of the + discrete complementarity set should generate the orthogonal + complement of that ray:: + + sage: K = Cone([(1,0)]) + sage: discrete_complementarity_set(K) + [((1, 0), (0, 1)), ((1, 0), (0, -1))] + sage: K = Cone([(1,0,0)]) + sage: discrete_complementarity_set(K) + [((1, 0, 0), (0, 1, 0)), + ((1, 0, 0), (0, -1, 0)), + ((1, 0, 0), (0, 0, 1)), + ((1, 0, 0), (0, 0, -1))] + + When the cone is the entire space, its dual is the trivial cone, so + the discrete complementarity set is empty:: + + sage: K = Cone([(1,0),(-1,0),(0,1),(0,-1)]) + sage: discrete_complementarity_set(K) + [] + + TESTS: + + The complementarity set of the dual can be obtained by switching the + components of the complementarity set of the original cone:: + + sage: K1 = random_cone(0,10,0,10) + sage: K2 = K1.dual() + sage: expected = [(x,s) for (s,x) in discrete_complementarity_set(K2)] + sage: actual = discrete_complementarity_set(K1) + sage: actual == expected + True + + """ + V = K.lattice().vector_space() + + # Convert the rays to vectors so that we can compute inner + # products. + xs = [V(x) for x in K.rays()] + ss = [V(s) for s in K.dual().rays()] + + return [(x,s) for x in xs for s in ss if x.inner_product(s) == 0] + + def lyapunov_rank(K): r""" Compute the Lyapunov (or bilinearity) rank of this cone. @@ -108,17 +258,29 @@ def lyapunov_rank(K): sage: lyapunov_rank(K) == lyapunov_rank(K.dual()) True + TESTS: + + The Lyapunov rank should be additive on a product of cones:: + + sage: K1 = random_cone(0,10,0,10) + sage: K2 = random_cone(0,10,0,10) + sage: K = K1.cartesian_product(K2) + sage: lyapunov_rank(K) == lyapunov_rank(K1) + lyapunov_rank(K2) + True + + The dual cone `K^{*}` of ``K`` should have the same Lyapunov rank as ``K`` + itself:: + + sage: K = random_cone(0,10,0,10) + sage: lyapunov_rank(K) == lyapunov_rank(K.dual()) + True + """ V = K.lattice().vector_space() - xs = [V(x) for x in K.rays()] - ss = [V(s) for s in K.dual().rays()] - - # WARNING: This isn't really C(K), it only contains the pairs - # (x,s) in C(K) where x,s are extreme in their respective cones. - C_of_K = [(x,s) for x in xs for s in ss if x.inner_product(s) == 0] + C_of_K = discrete_complementarity_set(K) - matrices = [x.column() * s.row() for (x,s) in C_of_K] + matrices = [x.tensor_product(s) for (x,s) in C_of_K] # Sage doesn't think matrices are vectors, so we have to convert # our matrices to vectors explicitly before we can figure out how