#  Copyright (c) 1997-2015
#  Ewgenij Gawrilow, Michael Joswig (Technische Universitaet Berlin, Germany)
#  http://www.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.
#-------------------------------------------------------------------------------

INCLUDE
   morse_matching.rules

# convert Int {+1,0,-1} to Bool {true,false,undef} to capture heuristical approaches
sub ternary_to_bool($) {
  my ($truth_value)=@_;
  if ($truth_value>=0) { # arrived at a decision
    return $truth_value;
  } else {
    return undef; # heuristics unsuccessful
  }
}

object SimplicialComplex {

rule FACETS, VERTEX_INDICES, N_VERTICES : INPUT_FACES {
   faces_to_facets($this, $this->INPUT_FACES);
}

rule FACETS : HASSE_DIAGRAM.ADJACENCY, HASSE_DIAGRAM.DECORATION, HASSE_DIAGRAM.INVERSE_RANK_MAP, HASSE_DIAGRAM.TOP_NODE, HASSE_DIAGRAM.BOTTOM_NODE {
   $this->FACETS=facets_from_hasse_diagram($this->HASSE_DIAGRAM);
}

rule PURE, DIM : FACETS {
    my $n=$this->FACETS->size;
    my $pure=1; # let's be optimistic
    my $sz=0;   # simplicial complex may be empty
    if ($n) {
	$sz=$this->FACETS->[0]->size;
	for (my $i=1; $i<$n; ++$i) {
	    my $s=$this->FACETS->[$i]->size();
	    $pure= 0 if $sz!=$s;
	    assign_max($sz,$s);
	}
    }
    $this->PURE= $pure;
    $this->DIM=  $sz-1;
}
weight 1.10;

rule N_FACETS : FACETS {
   $this->N_FACETS=$this->FACETS->size();
}
weight 0.1;

rule N_MINIMAL_NON_FACES : MINIMAL_NON_FACES {
   $this->N_MINIMAL_NON_FACES=$this->MINIMAL_NON_FACES->size();
}
weight 0.1;

rule DIM : FACETS {
   $this->DIM=$this->FACETS->[0]->size()-1;
}
precondition : PURE;
weight 0.1;

rule GRAPH.ADJACENCY : FACETS {
   $this->GRAPH->ADJACENCY=vertex_graph($this->FACETS);
}
weight 2.10;

rule DUAL_GRAPH.ADJACENCY : FACETS {
   $this->DUAL_GRAPH->ADJACENCY=dual_graph($this->FACETS);
}

rule GRAPH.NODE_LABELS = VERTEX_LABELS;

# methods for backward compatibility

# @category Combinatorics
# Degrees of the vertices in the [[GRAPH]].
# @return Array<Int>
user_method VERTEX_DEGREES = GRAPH.NODE_DEGREES;

# @category Topology
# True if the [[GRAPH]] is a connected graph.
# @return Bool
user_method CONNECTED = GRAPH.CONNECTED;

# @category Topology
# True if the [[DUAL_GRAPH]] is a connected graph.
# @return Bool
user_method DUAL_CONNECTED = DUAL_GRAPH.CONNECTED;

# @category Combinatorics
# The connected components of the [[GRAPH]], encoded as node sets. 
# @return PowerSet<Int>
user_method CONNECTED_COMPONENTS = GRAPH.CONNECTED_COMPONENTS;

# @category Combinatorics
# The connected components of the [[DUAL_GRAPH]], encoded as node sets. 
# @return PowerSet<Int>
user_method DUAL_CONNECTED_COMPONENTS = DUAL_GRAPH.DUAL_CONNECTED_COMPONENTS;

# @category Topology
# Number of connected components of the [[GRAPH]].
# @return Int
user_method N_CONNECTED_COMPONENTS = GRAPH.N_CONNECTED_COMPONENTS;

# @category Combinatorics
# The maximal cliques of the [[GRAPH]], encoded as node sets.
# @return PowerSet<Int>
user_method MAX_CLIQUES = GRAPH.MAX_CLIQUES;

# @category Combinatorics
# The maximal cliques of the [[DUAL_GRAPH]], encoded as node sets.
# @return PowerSet<Int>
user_method DUAL_MAX_CLIQUES = DUAL_GRAPH.MAX_CLIQUES;

# @category Combinatorics
# Node connectivity of the [[GRAPH]], that is, the minimal number of nodes to be removed from the graph such that the result is disconnected.
# @return Int
user_method CONNECTIVITY = GRAPH.CONNECTIVITY;

# @category Combinatorics
# Node connectivity of the [[DUAL_GRAPH]]. Dual to [[CONNECTIVITY]].
# @return PowerSet<Int>
user_method DUAL_CONNECTIVITY = DUAL_GRAPH.CONNECTIVITY;

# @category Combinatorics
# True if [[GRAPH]] is a __bipartite__. 
# @return Bool
user_method BIPARTITE = GRAPH.BIPARTITE;

# @category Combinatorics
# True if [[DUAL_GRAPH]] is a __bipartite__.
# @return Bool
user_method DUAL_BIPARTITE = DUAL_GRAPH.BIPARTITE;

# @category Combinatorics
# Difference of the black and white nodes if the [[GRAPH]] is [[BIPARTITE]]. Otherwise -1.
# @return Int
user_method GRAPH_SIGNATURE = GRAPH.SIGNATURE;

# @category Combinatorics
# Difference of the black and white nodes if the [[DUAL_GRAPH]] is [[BIPARTITE]]. Otherwise -1. 
# @return Int
user_method DUAL_GRAPH_SIGNATURE = DUAL_GRAPH.SIGNATURE;


rule FOLDABLE : PROJ_ORBITS, DIM {
    $this->FOLDABLE = ($this->PROJ_ORBITS->size() == $this->DIM+1);
}
precondition : DUAL_GRAPH.CONNECTED;
weight 0.1;

rule F_VECTOR : FACETS, DIM, PURE {
  $this->F_VECTOR=f_vector($this->FACETS,$this->DIM,$this->PURE);
}
weight 3.20;

rule H_VECTOR : F_VECTOR {
  $this->H_VECTOR=h_vector($this->F_VECTOR);
}
weight 1.00;

rule SHELLING : H_VECTOR {
  $this->SHELLING=shelling($this);
}
precondition : PURE;
weight 5.00;

rule SHELLABLE : SHELLING {
  my @shell = @{$this->SHELLING};
  my $firstface = $shell[0];
  $this->SHELLABLE=@$firstface != 0;
}
precondition : PURE;

rule F_VECTOR, F2_VECTOR : HASSE_DIAGRAM.ADJACENCY, HASSE_DIAGRAM.DECORATION, HASSE_DIAGRAM.INVERSE_RANK_MAP, HASSE_DIAGRAM.TOP_NODE, HASSE_DIAGRAM.BOTTOM_NODE {
   $this->F2_VECTOR=f2_vector($this->HASSE_DIAGRAM);
   $this->F_VECTOR=$this->F2_VECTOR->diagonal;
}

rule EULER_CHARACTERISTIC : F_VECTOR {
   my $euler_char = -1;
   my $sign = 1;
   my $d = $this->F_VECTOR->size();
   for (my $i=0; $i<$d; ++$i) {
       my $f=$this->F_VECTOR->[$i];
       $euler_char += $sign*$f;
       $sign = -$sign
   }
   $this->EULER_CHARACTERISTIC=$euler_char;
}
weight 0.40;

rule N_VERTICES : FACETS {
   my $n=0;
   foreach my $f (@{$this->FACETS}) {
      assign_max($n, $f->[-1]+1) if @$f;
   }
   $this->N_VERTICES=$n;
}
weight 1.10;


rule default.homology: HOMOLOGY : FACETS {
   $this->HOMOLOGY=homology($this->FACETS, 0);
}
weight 4.10;
precondition : DIM { $this->DIM>=0 }

rule COHOMOLOGY : FACETS {
   $this->COHOMOLOGY=homology($this->FACETS, 1);
}
weight 4.10;
precondition : DIM { $this->DIM>=0 }

rule default.homology: HOMOLOGY, CYCLES : FACETS {
   ($this->HOMOLOGY, $this->CYCLES) = homology_and_cycles($this->FACETS, 0);
}
weight 4.50;
precondition : DIM { $this->DIM>=0 }

rule COHOMOLOGY, COCYCLES : FACETS {
   ($this->COHOMOLOGY, $this->COCYCLES) = homology_and_cycles($this->FACETS, 1);
}
weight 4.50;
precondition : DIM { $this->DIM>=0 }

rule INTERSECTION_FORM : CYCLES, COCYCLES {
   intersection_form($this);
}

rule STIEFEL_WHITNEY : FACETS {
   $this->STIEFEL_WHITNEY=stiefel_whitney($this->FACETS);
}
precondition : CLOSED_PSEUDO_MANIFOLD;
weight 5.10;

rule ODD_SUBCOMPLEX.FACETS : FACETS {
   odd_complex($this);
}
precondition : PURE;
weight 3.10;

rule ODD_SUBCOMPLEX.INPUT_FACES : FACETS, BOUNDARY.FACETS, BOUNDARY.VERTEX_MAP {
   odd_complex_of_manifold($this);
}
precondition : MANIFOLD;
weight 2.10;

rule SURFACE : DIM, GRAPH.CONNECTED, MANIFOLD {
   $this->SURFACE= $this->GRAPH->CONNECTED && $this->MANIFOLD && $this->DIM==2;
}
weight 0.1;

rule GENUS : ORIENTED_PSEUDO_MANIFOLD, EULER_CHARACTERISTIC {
  my $euler_char = $this->EULER_CHARACTERISTIC;
  if ($this->ORIENTED_PSEUDO_MANIFOLD) {
    $this->GENUS = (1-$euler_char)/2;
  } else {
    $this->GENUS = 1-$euler_char;
  }
}
precondition : SURFACE;
precondition : CLOSED_PSEUDO_MANIFOLD;
weight 0.20;

rule MANIFOLD : { $this->MANIFOLD=1; }
precondition : BALL;
weight 0.1;

rule MANIFOLD : { $this->MANIFOLD=1; }
precondition : SPHERE;
weight 0.1;

# deterministic
rule MANIFOLD : FACETS, DIM, N_VERTICES {
   $this->MANIFOLD=ternary_to_bool(is_manifold($this));
}
precondition : PURE;
precondition : DIM { $this->DIM < 4 }
weight 4.10;

# heuristics
rule MANIFOLD : HASSE_DIAGRAM.ADJACENCY, HASSE_DIAGRAM.DECORATION, HASSE_DIAGRAM.INVERSE_RANK_MAP, HASSE_DIAGRAM.TOP_NODE, HASSE_DIAGRAM.BOTTOM_NODE, CLOSED_PSEUDO_MANIFOLD {
   $this->MANIFOLD=ternary_to_bool(is_manifold_h($this));
}
precondition : PSEUDO_MANIFOLD;
weight 4.50;

rule PSEUDO_MANIFOLD : {  $this->PSEUDO_MANIFOLD=1; }
precondition : MANIFOLD;
weight 0.1;

rule PSEUDO_MANIFOLD : {  $this->PSEUDO_MANIFOLD=1; }
precondition : CLOSED_PSEUDO_MANIFOLD;
weight 0.1;

rule PSEUDO_MANIFOLD : {  $this->PSEUDO_MANIFOLD=1; }
precondition : ORIENTED_PSEUDO_MANIFOLD;
weight 0.1;

rule PSEUDO_MANIFOLD : HASSE_DIAGRAM.ADJACENCY, HASSE_DIAGRAM.DECORATION, HASSE_DIAGRAM.INVERSE_RANK_MAP, HASSE_DIAGRAM.TOP_NODE, HASSE_DIAGRAM.BOTTOM_NODE {
   is_pseudo_manifold($this);
}
precondition : PURE;
weight 1.50;

rule MANIFOLD, PSEUDO_MANIFOLD : {
   $this->MANIFOLD=0;
   $this->PSEUDO_MANIFOLD=0;
}
precondition : !PURE;
weight 0.1;

rule CLOSED_PSEUDO_MANIFOLD : HASSE_DIAGRAM.ADJACENCY, HASSE_DIAGRAM.DECORATION, HASSE_DIAGRAM.INVERSE_RANK_MAP, HASSE_DIAGRAM.TOP_NODE, HASSE_DIAGRAM.BOTTOM_NODE {
   is_closed_pseudo_manifold($this);
}
precondition : PURE;
weight 1.50;

rule CLOSED_PSEUDO_MANIFOLD : {
   $this->CLOSED_PSEUDO_MANIFOLD=0;
}
precondition : !PURE;
weight 0.1;

rule ORIENTED_PSEUDO_MANIFOLD, ORIENTATION : FACETS, DUAL_GRAPH, PSEUDO_MANIFOLD {
   orientation($this);
}

rule BALL : FACETS, DIM, N_VERTICES, HASSE_DIAGRAM.ADJACENCY, HASSE_DIAGRAM.DECORATION, HASSE_DIAGRAM.INVERSE_RANK_MAP, HASSE_DIAGRAM.TOP_NODE, HASSE_DIAGRAM.BOTTOM_NODE {
   $this->BALL=ternary_to_bool(is_ball_or_sphere($this,0));
}
precondition : PSEUDO_MANIFOLD;
precondition : !CLOSED_PSEUDO_MANIFOLD;
weight 4.10;

rule BALL : {
   $this->BALL=0;
}
precondition : CLOSED_PSEUDO_MANIFOLD;
weight 0.1;

rule SPHERE : FACETS, DIM, N_VERTICES, HASSE_DIAGRAM.ADJACENCY, HASSE_DIAGRAM.DECORATION, HASSE_DIAGRAM.INVERSE_RANK_MAP, HASSE_DIAGRAM.TOP_NODE, HASSE_DIAGRAM.BOTTOM_NODE {
   $this->SPHERE=ternary_to_bool(is_ball_or_sphere($this,1));
}
precondition : CLOSED_PSEUDO_MANIFOLD;
weight 4.10;

rule SPHERE : {
   $this->SPHERE=0;
}
precondition : !CLOSED_PSEUDO_MANIFOLD;
weight 0.1;


rule HASSE_DIAGRAM.ADJACENCY, HASSE_DIAGRAM.DECORATION, HASSE_DIAGRAM.INVERSE_RANK_MAP, HASSE_DIAGRAM.TOP_NODE, HASSE_DIAGRAM.BOTTOM_NODE : FACETS {
   $this->HASSE_DIAGRAM = hasse_diagram($this);
}
weight 4.10;


rule MINIMAL_NON_FACES : HASSE_DIAGRAM.ADJACENCY, HASSE_DIAGRAM.DECORATION, HASSE_DIAGRAM.INVERSE_RANK_MAP, HASSE_DIAGRAM.TOP_NODE, HASSE_DIAGRAM.BOTTOM_NODE {
   $this->MINIMAL_NON_FACES=minimal_non_faces($this->HASSE_DIAGRAM);
}
weight 4.10 : DIM { $this->DIM <= 10 ? [0,0] : [4,10] }


# This implements an old algorithm described by Lawler:
# "Covering problems: duality relations and a new method of solution"
# SIAM J. Appl. Math., Vol. 14, No. 5, 1966
#
# See also Chapter 2 of "Hypergraphs", C. Berge, North-Holland, Amsterdam, 1989

rule MINIMAL_NON_FACES : FACETS, DIM, N_VERTICES {
   $this->MINIMAL_NON_FACES=lawler_minimal_non_faces($this->FACETS, $this->N_VERTICES);
}
weight 4.10 : DIM { $this->DIM > 10 ? [0,0] : [4,10] }


rule LOCALLY_STRONGLY_CONNECTED : {
   $this->LOCALLY_STRONGLY_CONNECTED=1;
}
precondition : MANIFOLD;
weight 0.1;

rule LOCALLY_STRONGLY_CONNECTED : HASSE_DIAGRAM.ADJACENCY, HASSE_DIAGRAM.DECORATION, HASSE_DIAGRAM.INVERSE_RANK_MAP, HASSE_DIAGRAM.TOP_NODE, HASSE_DIAGRAM.BOTTOM_NODE {
   $this->LOCALLY_STRONGLY_CONNECTED=is_locally_strongly_connected($this);
}
weight 2.10;

#compute boundary complex
rule BOUNDARY.FACETS, BOUNDARY.VERTEX_MAP : HASSE_DIAGRAM.ADJACENCY, HASSE_DIAGRAM.DECORATION, HASSE_DIAGRAM.INVERSE_RANK_MAP, HASSE_DIAGRAM.TOP_NODE, HASSE_DIAGRAM.BOTTOM_NODE {
   ($this->BOUNDARY->FACETS, $this->BOUNDARY->VERTEX_MAP) =  boundary_of_pseudo_manifold($this);
}
precondition : PSEUDO_MANIFOLD;
weight 1.10;

rule VERTEX_LABELS : N_VERTICES {
   my @labels = (0..$this->N_VERTICES-1);
   $this->VERTEX_LABELS="@labels";
}
weight 0.10;

rule PROJ_ORBITS, PROJ_DICTIONARY : N_VERTICES, FACETS, DUAL_GRAPH.ADJACENCY {
   ($this->PROJ_ORBITS, $this->PROJ_DICTIONARY)=projectivities($this);
}
precondition : DUAL_GRAPH.CONNECTED;
weight 1.10;


}

declare property_type Cell : c++ (include => "polymake/topaz/Filtration.h", operators => '==') {

   # Construct a filtration cell.
   # @param Int deg Filtration degree of the cell.
   # @param Int dim Dimension of the cell.
   # @param Int idx Row number of the cell in the boundary matrix belonging to the Filtration.
   method construct(*, *, *) : c++;

}

# A filtration of chain complexes.
# @tparam MatrixType
declare property_type Filtration<MatrixType> : c++ (include => "polymake/topaz/Filtration.h", operators => '=='){

   # Construct a Filtration.
   # @param Array<Cell> C An array containing all cells in the filtration.
   # @param Array<MatrixType> bd The boundary matrices of the last frame of the filtration, indexed by dimension.
   # @optional Bool s Indicates whether the cell array is already sorted by degree first and dimension second, default: 0
   method construct(Array<Cell>:lvalue,Array<MatrixType>;$=0) : c++;

   # Construct a Filtration from a HasseDiagram and an integer array.
   # @param Lattice The last frame of the filtration.
   # @param Array<Int> degs The degrees of the simplices in the input complex.
   #                        Indexing after sorting them first by dimension, second lexicographically (like in the HasseDiagram)
    method construct(Lattice<BasicDecoration>,Array<Int>) : c++;

   # Returns the dimension of the maximal cells in the last frame of the filtration.
   # @return Int
   user_method dim() : c++;

   # Returns the number of frames in of the filtration.
   # @return Int
   user_method n_frames() : c++;

   # Returns the number of cells in the last frame of the filtration.
   # @return Int
   user_method n_cells() : c++;

   # Returns the cells of the filtration, given as array of 3-tuples containing degree, dimension and
   # boundary matrix row number of the cell.
   # @return Array<Cell>
   user_method cells() : c++;

   # Returns the d-boundary matrix of the t-th frame of the filtration.
   # @param Int d
   # @param Int t
   user_method boundary_matrix(Int, Int) : non_const : c++;
}

# A finite chain complex, represented as its boundary matrices.
# Check out the tutorial on the polymake homepage for examples on constructing ChainComplexes and computing their homology.
#
# @example You can create a new ChainComplex by passing the Array of differential matrices (as maps via _left_ multiplication):
# > $cc = new ChainComplex(new Array<SparseMatrix<Integer>>([[[2,0]]]));
#
# Note that this creates a ChainComplex consisting three differential matrices -- the trivial zeroth and last ones
# are omitted in the constructor.
#
# You can look at the boundary matrices:
# > print $cc->boundary_matrix(1);
# | 2 0
#
# The functions ''homology'', ''homology_and_cycles'' and ''betti_numbers'' can be used to analyse your complex.
# > print homology($cc,0);
# | ({(2 1)} 1)
# | ({} 0)
# @tparam MatrixType The type of the differential matrices. default: SparseMatrix<Integer>
declare property_type ChainComplex<MatrixType = SparseMatrix<Integer>> : c++ (include => "polymake/topaz/ChainComplex.h", operators => '=='){

   # Construct a Chain Complex.
   # @param Array<MatrixType> bd The boundary matrices of the chain complex, NOT including the trivial zeroth and last matrices. Indexed by dimension. The matrices are maps via left multiplication.
   # @optional Bool sanity_check Indicates whether to test if the input matrices' dimensions match and the maps satisfy the differential condition. default: 0
   method construct(Array<MatrixType>; $=0) : c++;

   # Returns the number of non-empty modules in the complex.
   # @return Int
   user_method dim() : c++;

   # Returns the d-boundary matrix of the chain complex.
   # @param Int d
   # @return MatrixType
   user_method boundary_matrix(*) : c++;
}

# @category Producing a new simplicial complex from others
# Computes the __barycentric subdivision__ of //complex//.
# @param SimplicialComplex complex
# @option String pin_hasse_section default: HASSE_DIAGRAM
# @option String label_section default: VERTEX_LABELS
# @option String coord_section default: VERTICES
# @option Bool geometric_realization set to 1 to obtain a [[GeometricSimplicialComplex]], default: 0
# @return SimplicialComplex (or [[GeometricSimplicialComplex]])
# @example To subdivide a triangle into six new triangles, do this:
# > $b = barycentric_subdivision(simplex(2));
user_function barycentric_subdivision($ { relabel => 1, pin_hasse_section=>"HASSE_DIAGRAM", label_section=>"VERTEX_LABELS", geometric_realization=>0, coord_section=>"VERTICES"}) {
    barycentric_subdivision_impl(@_);
}

# @category Producing a new simplicial complex from others
# Computes the //k//-th __barycentric subdivision__ of //complex// by iteratively calling [[barycentric_subdivision]].
# @param SimplicialComplex complex
# @param Int k
# @option String pin_hasse_section default: HASSE_DIAGRAM
# @option String label_section default: VERTEX_LABELS
# @option String coord_section default: VERTICES
# @option Bool geometric_realization set to 1 to obtain a [[GeometricSimplicialComplex]], default: 0
# @return SimplicialComplex (or [[GeometricSimplicialComplex]])
user_function iterated_barycentric_subdivision(SimplicialComplex $ { relabel => 1, pin_hasse_section=>"HASSE_DIAGRAM", label_section=>"VERTEX_LABELS", geometric_realization=>0, coord_section=>"VERTICES"}) {
  iterated_barycentric_subdivision_impl(@_);
}

# Local Variables:
# mode: perl
# c-basic-offset:3
# End:
