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# Copyright (c) 1997-2024
# Ewgenij Gawrilow, Michael Joswig, and the polymake team
# Technische Universität Berlin, Germany
# https://polymake.org
#
# This program 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 2, or (at your option) any
# later version: http://www.gnu.org/licenses/gpl.txt.
#
# This program 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.
#-------------------------------------------------------------------------------
object Polytope {
# @category Combinatorics
# A lower bound for the minimal number of simplices in a triangulation
property SIMPLEXITY_LOWER_BOUND : Int;
# @category Combinatorics
# An upper bound for the maximal signature of a foldable triangulation of a polytope
# The signature is the absolute difference of the normalized volumes of black minus white maximal simplices,
# where only odd normalized volumes are taken into account.
property FOLDABLE_MAX_SIGNATURE_UPPER_BOUND : Int;
rule SIMPLEXITY_LOWER_BOUND : COMBINATORIAL_DIM, VERTICES, MAX_INTERIOR_SIMPLICES, VOLUME, COCIRCUIT_EQUATIONS {
$this->SIMPLEXITY_LOWER_BOUND = simplexity_lower_bound($this->COMBINATORIAL_DIM, $this->VERTICES, $this->MAX_INTERIOR_SIMPLICES, $this->VOLUME, $this->COCIRCUIT_EQUATIONS);
}
rule FOLDABLE_MAX_SIGNATURE_UPPER_BOUND : COMBINATORIAL_DIM, VERTICES, MAX_INTERIOR_SIMPLICES, VOLUME, FOLDABLE_COCIRCUIT_EQUATIONS {
$this->FOLDABLE_MAX_SIGNATURE_UPPER_BOUND = foldable_max_signature_upper_bound($this->COMBINATORIAL_DIM, $this->VERTICES, $this->MAX_INTERIOR_SIMPLICES, $this->VOLUME, $this->FOLDABLE_COCIRCUIT_EQUATIONS);
}
# @category Combinatorics
# The symmetrized version of SIMPLEXITY_LOWER_BOUND
rule GROUP.SIMPLEXITY_LOWER_BOUND : VOLUME, VERTICES, COMBINATORIAL_DIM, GROUP.REPRESENTATIVE_MAX_INTERIOR_SIMPLICES, GROUP.VERTICES_ACTION.SYMMETRIZED_COCIRCUIT_EQUATIONS.PROJECTED_EQUATIONS {
$this->GROUP->SIMPLEXITY_LOWER_BOUND = simplexity_lower_bound($this->COMBINATORIAL_DIM, $this->VERTICES, $this->GROUP->REPRESENTATIVE_MAX_INTERIOR_SIMPLICES, $this->VOLUME, $this->GROUP->VERTICES_ACTION->SYMMETRIZED_COCIRCUIT_EQUATIONS->PROJECTED_EQUATIONS);
}
} # end Polytope
object PointConfiguration {
# @category Symmetry
# The symmetrized version of SIMPLEXITY_LOWER_BOUND
rule GROUP.SIMPLEXITY_LOWER_BOUND : CONVEX_HULL.COMBINATORIAL_DIM, CONVEX_HULL.VOLUME, POINTS, GROUP.REPRESENTATIVE_MAX_INTERIOR_SIMPLICES, GROUP.POINTS_ACTION.SYMMETRIZED_COCIRCUIT_EQUATIONS.ISOTYPIC_COMPONENTS, GROUP.POINTS_ACTION.SYMMETRIZED_COCIRCUIT_EQUATIONS.RIDGES, GROUP.POINTS_ACTION.SYMMETRIZED_COCIRCUIT_EQUATIONS.PROJECTED_EQUATIONS {
$this->GROUP->SIMPLEXITY_LOWER_BOUND = simplexity_lower_bound($this->CONVEX_HULL->COMBINATORIAL_DIM, $this->POINTS, $this->GROUP->REPRESENTATIVE_MAX_INTERIOR_SIMPLICES, $this->CONVEX_HULL->VOLUME, $this->GROUP->POINTS_ACTION->SYMMETRIZED_COCIRCUIT_EQUATIONS->PROJECTED_EQUATIONS);
}
} # end PointConfiguration
# @category Triangulations, subdivisions and volume
# Calculate the universal polytope //U(P)// of an input polytope //P//.
# If //P// has //n// vertices and dimension //d//, then //U(P)// is a
# 0/1-polytope in dimension binomial(//n//,//d//+1) whose vertices
# correspond to the full triangulations of //P//. Each coordinate of a
# particular vertex //v// indicates the presence or absence of a
# particular simplex in the triangulation corresponding to //v//, and
# the order of the simplices (and hence the interpretation of each
# coordinate of //v//) is the one given by the property
# MAX_INTERIOR_SIMPLICES. Because the number of triangulations of
# //P// is typically very large, the polytope U(P) is not constructed
# by enumerating triangulations, but instead in the inequality
# description afforded by the cocircuit equations, a volume equality,
# and non-negativity constraints for the coordinates.
# @param Polytope P the input polytope
# @return Polytope
# @example
# Since the 2-dimensional cube (i.e., the square) has just two
# triangulations, its universal polytope is a segment embedded in dimension
# binomial(4,3) = 4. The cocircuit equations read as follows:
# > print universal_polytope(cube(2))->EQUATIONS;
# | -8 4 4 4 4
# | (5) (2 -1) (3 1)
# | (5) (1 -1) (4 1)
user_function universal_polytope<Scalar>(Polytope<Scalar>) {
my $p = shift;
return universal_polytope_impl($p->COMBINATORIAL_DIM, $p->VERTICES, $p->MAX_INTERIOR_SIMPLICES, $p->VOLUME, $p->COCIRCUIT_EQUATIONS);
}
# @category Triangulations, subdivisions and volume
# Calculate the universal polytope of a polytope, point configuration or quotient manifold
# @param Polytope P the input polytope
# @param Array<Set> reps the representatives of maximal interior simplices
# @param SparseMatrix cocircuit_equations the matrix of cocircuit equations
# @return Polytope
user_function universal_polytope<Scalar>(Polytope<Scalar>, Array<Set>, SparseMatrix) {
my ($p, $simplices, $cocircuit_equations) = @_;
return universal_polytope_impl($p->COMBINATORIAL_DIM, $p->VERTICES, $simplices, $p->VOLUME, new SparseMatrix<Rational>($cocircuit_equations));
}
# @category Optimization
# construct a linear program whose optimal value is a lower bound for the minimal number of simplices
# in a triangulation of P.
# @param Polytope P
# @option String outfile_name. If the string is '-' (as is the default), the linear program is printed to STDOUT.
# @example
# To print the linear program for the 2-dimensional cube, write
# > write_simplexity_ilp(cube(2));
# | MINIMIZE
# | obj: +1 x1 +1 x2 +1 x3 +1 x4
# | Subject To
# | ie0: +1 x1 >= 0
# | ie1: +1 x2 >= 0
# | ie2: +1 x3 >= 0
# | ie3: +1 x4 >= 0
# | eq0: +4 x1 +4 x2 +4 x3 +4 x4 = 8
# | eq1: -1 x2 +1 x3 = 0
# | eq2: -1 x1 +1 x4 = 0
# | BOUNDS
# | x1 free
# | x2 free
# | x3 free
# | x4 free
# | GENERAL
# | x1
# | x2
# | x3
# | x4
# | END
user_function write_simplexity_ilp<Scalar>(Polytope<Scalar>; $='-') {
my ($p, $outfilename) = @_;
my $rmis = new Array<Set>($p->MAX_INTERIOR_SIMPLICES);
my $q = simplexity_ilp($p->COMBINATORIAL_DIM, $p->VERTICES, $rmis, $p->VOLUME, $p->COCIRCUIT_EQUATIONS);
poly2lp($q, $q->LP, 0, $outfilename);
}
# @category Optimization
# construct a linear program whose optimal value is a lower bound for the minimal number of simplices
# in a triangulation of P, and that takes into account the angle constraint around codimension 2 faces.
# The first set of variables correspond to possible maximal internal simplices, the second set to the
# simplices of codimension 2. See the source file polytope/src/symmetrized_codim_2_angle_sums.cc for details.
# @param Polytope P
# @param String outfile_name
# @example
# To print the linear program for the 2-dimensional cube, write
# > write_simplexity_ilp_with_angles(cube(2));
# | MINIMIZE
# | obj: +1 x1 +1 x2 +1 x3 +1 x4
# | Subject To
# | ie0: +1 x1 >= 0
# | ie1: +1 x2 >= 0
# | ie2: +1 x3 >= 0
# | ie3: +1 x4 >= 0
# | ie4: +1 x5 >= 0
# | ie5: +1 x6 >= 0
# | ie6: +1 x7 >= 0
# | ie7: +1 x8 >= 0
# | eq0: -1 x2 +1 x3 = 0
# | eq1: -1 x1 +1 x4 = 0
# | eq2: +0.5 x1 +0.25 x2 +0.2500000000000001 x3 -0.5 x5 = 0
# | eq3: +0.25 x1 +0.5 x3 +0.2500000000000001 x4 -0.5 x6 = 0
# | eq4: +0.25 x1 +0.5 x2 +0.2500000000000001 x4 -0.5 x7 = 0
# | eq5: +0.25 x2 +0.2500000000000001 x3 +0.5 x4 -0.5 x8 = 0
# | eq6: +1 x5 = 1
# | eq7: +1 x6 = 1
# | eq8: +1 x7 = 1
# | eq9: +1 x8 = 1
# | eq10: +4 x1 +4 x2 +4 x3 +4 x4 = 8
# | BOUNDS
# | x1 free
# | x2 free
# | x3 free
# | x4 free
# | x5 free
# | x6 free
# | x7 free
# | x8 free
# | GENERAL
# | x1
# | x2
# | x3
# | x4
# | x5
# | x6
# | x7
# | x8
# | END
# |
user_function write_simplexity_ilp_with_angles<Scalar>(Polytope<Scalar>; $="-") {
my ($p, $outfilename) = @_;
my $rmis = new Array<Set>($p->MAX_INTERIOR_SIMPLICES);
my $trivial_gens = new Array<Array<Int>>();
my $V = new Matrix<Scalar>($p->VERTICES);
my $F = new Matrix<Scalar>($p->FACETS);
my $q = simplexity_ilp_with_angles($p->COMBINATORIAL_DIM, $V, $F, $p->VERTICES_IN_FACETS, $p->VERTICES_IN_RIDGES, $trivial_gens, $rmis, $p->VOLUME, $p->COCIRCUIT_EQUATIONS);
poly2lp($q, $q->LP, 0, $outfilename);
}
# @category Optimization
# construct a linear program whose optimal value is a lower bound for
# the minimal number of simplices in a triangulation of P.
# The symmetry group of P is taken into account, in that the
# variables in the linear program are projections of the indicator
# variables of the maximal interior simplices to a given direct sum of
# isotypic components of the symmetry group of P acting on these simplices.
# @param Polytope P
# @param Set<Int> isotypic_components the set of indices of isotypic components to project to; default [0]
# @param String outfile_name. Setting this to '-' (as is the default) prints the LP to stdout.
# @example
# For the 3-cube, the symmetrized LP for isotypic component 0 reads as follows:
# > write_symmetrized_simplexity_ilp(cube(3,group=>1));
# | MINIMIZE
# | obj: +1 x1 +1 x2 +1 x3 +1 x4
# | Subject To
# | ie0: +1 x1 >= 0
# | ie1: +1 x2 >= 0
# | ie2: +1 x3 >= 0
# | ie3: +1 x4 >= 0
# | eq0: +8 x1 +8 x2 +8 x3 +16 x4 = 48
# | eq1: -6 x1 +6 x3 +24 x4 = 0
# | BOUNDS
# | x1 free
# | x2 free
# | x3 free
# | x4 free
# | GENERAL
# | x1
# | x2
# | x3
# | x4
# | END
# The interpretation is as follows: The variables x1,...,x4 correspond to the representatives of interior simplices:
# > print cube(3,group=>1)->GROUP->REPRESENTATIVE_MAX_INTERIOR_SIMPLICES;
# | {0 1 2 4}
# | {0 1 2 5}
# | {0 1 2 7}
# | {0 3 5 6}
# The solution (x1,x2,x3,x4) = (4,0,0,1) of the LP says that in a minimal triangulation of the 3-cube,
# there are 4 simplices in the same symmetry class as {0,1,2,4}, and one in the class of {0,3,5,6}.
user_function write_symmetrized_simplexity_ilp<Scalar>(Polytope<Scalar>; $=[0], $="-") {
my ($p, $isotypic_components_ref, $outfilename) = @_;
my $isotypic_components = new Set<Int>($isotypic_components_ref);
my $q = simplexity_ilp($p->COMBINATORIAL_DIM, $p->VERTICES, $p->GROUP->REPRESENTATIVE_MAX_INTERIOR_SIMPLICES, $p->VOLUME, symmetrized_cocircuit_equations($p, $isotypic_components)->PROJECTED_EQUATIONS);
poly2lp($q, $q->LP, 0, $outfilename);
}
# @category Optimization
# construct a linear program whose optimal value is an upper bound for the algebraic signature of
# a triangulation of P. This is the absolute value of the difference of normalized volumes of black
# minus white simplices (counting only those with odd normalized volume) in a triangulation of P
# whose dual graph is bipartite.
# If P has a GROUP, it will be used to construct the linear program.
# @param Polytope P
# @param String outfile_name
# @example
# For the 0/1 2-cube without a GROUP, the foldable max signature lp is computed as follows:
# > write_foldable_max_signature_ilp(cube(2,0));
# | MINIMIZE
# | obj: +1 x1 -1 x2 +1 x3 -1 x4 +1 x5 -1 x6 +1 x7 -1 x8
# | Subject To
# | ie0: +1 x1 >= 0
# | ie1: +1 x2 >= 0
# | ie2: +1 x3 >= 0
# | ie3: +1 x4 >= 0
# | ie4: +1 x5 >= 0
# | ie5: +1 x6 >= 0
# | ie6: +1 x7 >= 0
# | ie7: +1 x8 >= 0
# | ie8: -1 x1 -1 x2 >= -1
# | ie9: -1 x3 -1 x4 >= -1
# | ie10: -1 x5 -1 x6 >= -1
# | ie11: -1 x7 -1 x8 >= -1
# | eq0: -1 x4 +1 x5 = 0
# | eq1: +1 x3 -1 x6 = 0
# | eq2: -1 x2 +1 x7 = 0
# | eq3: +1 x1 -1 x8 = 0
# | eq4: +1 x1 +1 x2 +1 x3 +1 x4 +1 x5 +1 x6 +1 x7 +1 x8 = 2
# | BOUNDS
# | x1 free
# | x2 free
# | x3 free
# | x4 free
# | x5 free
# | x6 free
# | x7 free
# | x8 free
# | GENERAL
# | x1
# | x2
# | x3
# | x4
# | x5
# | x6
# | x7
# | x8
# | END
# There are eight variables, one for each possible black or white maximal interior simplex. The optimal value of this LP is zero, because any triangulation
# has exactly one black and one white simplex of odd normalized volume. Notice that the objective function becomes empty for cube(2), because in the +1/-1 cube,
# each simplex has even volume.
# @example
# For the 0/1 3-cube, we use a GROUP property:
# > write_foldable_max_signature_ilp(cube(3,0,group=>1));
# | MINIMIZE
# | obj: +1 x1 -1 x2 +1 x3 -1 x4 +1 x5 -1 x6
# | Subject To
# | ie0: +1 x1 >= 0
# | ie1: +1 x2 >= 0
# | ie2: +1 x3 >= 0
# | ie3: +1 x4 >= 0
# | ie4: +1 x5 >= 0
# | ie5: +1 x6 >= 0
# | ie6: +1 x7 >= 0
# | ie7: +1 x8 >= 0
# | ie8: -1 x1 -1 x2 >= -8
# | ie9: -1 x3 -1 x4 >= -24
# | ie10: -1 x5 -1 x6 >= -24
# | ie11: -1 x7 -1 x8 >= -2
# | eq0: +2 x3 -2 x4 +2 x5 -2 x6 = 0
# | eq1: -2 x3 +2 x4 -2 x5 +2 x6 = 0
# | eq2: -6 x2 +6 x5 +24 x7 = 0
# | eq3: -6 x1 +6 x6 +24 x8 = 0
# | eq4: +1 x1 +1 x2 +1 x3 +1 x4 +1 x5 +1 x6 +2 x7 +2 x8 = 6
# | BOUNDS
# | x1 free
# | x2 free
# | x3 free
# | x4 free
# | x5 free
# | x6 free
# | x7 free
# | x8 free
# | GENERAL
# | x1
# | x2
# | x3
# | x4
# | x5
# | x6
# | x7
# | x8
# | END
# There are again 8 variables, but now they correspond to the black and white representatives of the four symmetry classes of maximal interior simplices.
# The optimal value of this linear program is 4, because the most imbalanced triangulation is the one with 5 simplices, in which the volume of the big interior
# simplex is even and doesn't get counted in the objective function.
user_function write_foldable_max_signature_ilp<Scalar>(Polytope<Scalar>; $="-") {
my $p = shift;
my $outfilename = shift;
if (!$p->LATTICE) {
die "need the polytope to be a lattice polytope, ie, all vertices must be integral";
}
my $q;
if ($p->lookup("GROUP")) {
my $max_simplices = $p->GROUP->REPRESENTATIVE_MAX_INTERIOR_SIMPLICES;
my $foldable_cocircuit_equations = symmetrized_foldable_cocircuit_equations_0($p->COMBINATORIAL_DIM, $p->VERTICES, $p->VERTICES_IN_FACETS, $p->GROUP->VERTICES_ACTION->GENERATORS, $p->GROUP->REPRESENTATIVE_INTERIOR_RIDGE_SIMPLICES, $max_simplices);
$q = symmetrized_foldable_max_signature_ilp($p->COMBINATORIAL_DIM, $p->VERTICES, $max_simplices, $p->VOLUME, $p->GROUP->VERTICES_ACTION->GENERATORS, $foldable_cocircuit_equations);
} else {
my $max_simplices = $p->MAX_INTERIOR_SIMPLICES;
my $foldable_cocircuit_equations = $p->FOLDABLE_COCIRCUIT_EQUATIONS;
$q = foldable_max_signature_ilp($p->COMBINATORIAL_DIM, $p->VERTICES, $max_simplices, $p->VOLUME, $foldable_cocircuit_equations);
}
poly2lp($q, $q->LP, 0, $outfilename);
}
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