/*
	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
	of the License, or (at your option) any later version.

	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.

	You should have received a copy of the GNU General Public License
	along with this program; if not, write to the Free Software
	Foundation, Inc., 51 Franklin Street, Fifth Floor,
	Boston, MA  02110-1301, USA.

	---
	Copyright (C) 2011 - 2015, Simon Hampe <simon.hampe@googlemail.com>

	---
	Copyright (c) 2016-2023
	Ewgenij Gawrilow, Michael Joswig, and the polymake team
	Technische Universität Berlin, Germany
	https://polymake.org

	Functions to compute the combinatorics of rational n-marked curves, e.g.
	the metric-to-tree algorithm by Buneman
	*/


#include "polymake/client.h"
#include "polymake/Rational.h"
#include "polymake/Matrix.h"
#include "polymake/Vector.h"
#include "polymake/Set.h"
#include "polymake/Map.h"
#include "polymake/PowerSet.h"
#include "polymake/Array.h"
#include "polymake/linalg.h"
#include "polymake/IncidenceMatrix.h"
#include "polymake/Graph.h"
#include "polymake/permutations.h"
#include "polymake/TropicalNumber.h"
#include "polymake/tropical/misc_tools.h"

namespace polymake { namespace tropical {

Int moduliDimensionFromLength(Int length)
{
  Int s = Int(sqrt(1 + 8*length));
  Int r = (1+s)/2;
  // Test for validity
  if ((r*(r-1)/2) != length) {
    throw std::runtime_error("Length is not of the form (n over 2)");
  }
  return r;
}

/**
   @brief Takes three rational values and checks whether two of them are equal and >= than the third
*/
bool fpcCheck(const Rational& a, const Rational& b, const Rational& c)
{
  if (a == b && a >= c) return true;
  if (a == c && a >= b) return true;
  if (b == c && b >= a) return true;
  return false;
}

///////////////////////////////////////////////////////////////////////////////////////

// Documentation see perl wrapper of wrapTestFourPointCondition (does the same except that it returns
// a vector of Int)
Vector<Int> testFourPointCondition(const Vector<Rational>& v)
{
  // Convert metric into map
  Int n = moduliDimensionFromLength(v.dim());
  Matrix<Rational> d(n+1,n+1);

  Int mindex = 0;
  for (Int i = 1; i < n; ++i) {
    for (Int j = i+1; j <= n; ++j) {
      d(i,j) = d(j,i) = v[mindex];
      ++mindex;
    }
  }

  // First we test all 4-element subsets
  const auto complete = sequence(1,n);
  if (n >= 4) {
    for (auto fours = entire(all_subsets_of_k(complete,4));  !fours.at_end(); ++fours) {
      const auto& l = *fours;
      Rational a = d(l[0],l[1]) + d(l[2],l[3]);
      Rational b = d(l[0],l[2]) + d(l[1],l[3]);
      Rational c = d(l[0],l[3]) + d(l[1],l[2]);
      // Check that two of a,b,c are equal and not less than the third
      if (!fpcCheck(a,b,c)) {
        Vector<Int> fault(l);
        return fault;
      }
    }
  }

  // Now we check all 3-element subsets
  for (auto threes = entire(all_subsets_of_k(complete,3));  !threes.at_end();  ++threes) {
    const auto& l = *threes;
    // Now check the three possibilities, where the fourth element is equal to any of the three
    for (Int t = 0; t < 3; ++t) {
      Rational a = d(l[0],l[1]) + d(l[2],l[t]);
      Rational b = d(l[0],l[2]) + d(l[1],l[t]);
      Rational c = d(l[0],l[t]) + d(l[1],l[2]);
      // Check that two of a,b,c are equal and not less than the third
      if (!fpcCheck(a,b,c)) {
        Vector<Int> fault(4);
        fault[0] = l[0];
        fault[1] = l[1];
        fault[2] = l[2];
        fault[3] = l[t];
        return fault;
      }
    }
  }

  // Now we check all 2-element subsets
  for (auto twos = entire(all_subsets_of_k(complete,2)); !twos.at_end(); ++twos) {
    const auto& l = *twos;
    // We have three possibilites for the other two z,t: t=x,z=y or t=z=x or t=z=y
    for (Int p = 1; p <= 3; ++p) {
      Int t = p < 3 ? l[0] : l[1];
      Int z = p != 2 ? l[1] : l[0];
      Rational a = d(l[0],l[1]) + d(z,t);
      Rational b = d(l[0],z) + d(l[1],t);
      Rational c = d(l[0],t) + d(l[1],z);
      // Check that two of a,b,c are equal and not less than the third
      if (!fpcCheck(a,b,c)) {
        Vector<Int> fault(4);
        fault[0] = l[0];
        fault[1] = l[1];
        fault[2] = z;
        fault[3] = t;
        return fault;
      }
    }
  }
  return Vector<Int>{};
}

///////////////////////////////////////////////////////////////////////////////////////

// Documentation see perl wrapper
ListReturn wrapTestFourPointCondition(const Vector<Rational>& v)
{
  Vector<Int> fault = testFourPointCondition(v);
  ListReturn result;
  // TODO: implement unroll for ListReturn
  for (Int i = 0; i < fault.dim(); ++i) {
    result << fault[i];
  }
  return result;
}

///////////////////////////////////////////////////////////////////////////////////////

/**
   @brief Computes a rational curve (in the v_I-representation) and its graph from a given metric (or more precisely a vector equivalent to a metric). It is wrapped by curveFromMetric and graphFromMetric, which should be called instead and whose documentation can be found in the corr. perl wrappers rational_curve_from_metric and curve_graph_from_metric. Note that the order of the [[EDGES]] of the graph object that do not contain leaf vertices is the same as the order of the corresponding [[SETS]] of the curve. Furthermore, the first n vertices of the graph are the end vertices of the leave edges (in order 1 .. n)
*/
BigObject curveAndGraphFromMetric(Vector<Rational> metric)
{
  // We prepare the metric by making sure, all entries are > 0
  const Int n = moduliDimensionFromLength(metric.dim());

  // We now add Phi(sum of unit vectors) to the metric until it fulfills the four-point-condition
  // and is positive
  // Then we add it once more to make sure every leaf has positive distance to its vertex
  // Note that adding Phi(..) is the same as adding 2 to every entry in the matrix
  bool hasBeenfpced = false;
  bool hasBeenStretched = false;
  Int tryCount = 0;
  while (!(hasBeenfpced && hasBeenStretched)) {
    // Since we cannot predict, how many tries we need to ensure 4-point-condition,
    // we insert a maximum bound to avoid endless looping on metrics that don't lie in M_n
    if (tryCount >= 1000000) {
      throw std::runtime_error("Cannot make metric four-point-condition-compatible: Maybe it's not in the moduli space?");
    }
    metric += 2*ones_vector<Rational>(metric.dim());
    // Check if everything is positive	
    if (accumulate(Set<Rational>(metric), operations::min()) <= 0) {
      continue;
    }
    // If it already had been 4-point-cond-compatible and positive, this was the stretching
    if (hasBeenfpced) hasBeenStretched = true;
    // Check if it fulfills the 4-pc
    if (testFourPointCondition(metric).dim() == 0)
      hasBeenfpced = true;
    else
      ++tryCount;
  }

  // For simplicity we ignore the first row and column and start counting at 1
  Matrix<Rational> d(n+1, n+1);
  Int mindex = 0;
  for (Int i = 1; i < n; ++i) {
    for (Int j = i+1; j <= n; ++j) {
      d(i,j) = metric[mindex];
      d(j,i) = metric[mindex];
      ++mindex;
    }
  }

  // For the graph case, we prepare a graph object
  Graph<> G(n);

  // To make the order of SETS/COEFFS agree with the order of the edges in graph,
  // we keep track of the original graph edge order.
  Vector<std::pair<Int, Int>> edge_order;

  // The algorithm possibly produces "double" vertices when creating a new vertex t
  // that has distance 0 to p or q. In this case we have to remember the original index p (or q)
  // to be able to create the graph correctly
  // So, at position i, it gives the number of the vertex (starting at 1), the virtual vertex i
  // actually represents. When creating a new vertex, this should be the maximum over the list + 1
  Vector<Int> orig(n+1);
  for (Int i = 1; i <= n; ++i)
    orig[i] = i;

  // Result variable
  Vector<Rational> coeffs;
  Vector<Set<Int>> sets;
  // Prepare vertex set, leaf map
  Set<Int> V = sequence(1, n);
  Map<Int, Set<Int>> leaves;
  for (Int i = 1; i <= n; ++i) {
    Set<Int> singleset; singleset += i;
    leaves[i] = singleset;
  }
  // These variables will contain the node data
  Vector<Set<Int>> nodes_by_leaves(n), nodes_by_sets(n);

  // Now inductively remove pairs of vertices until only 3 are left
  while (V.size() > 3) {
    // Find the triple (p,q,r) that maximizes the Buneman term
    Int p = 0, q = 0, r = 0;
    bool init = false;
    Rational max = 0;
    for (auto a = entire(V); !a.at_end(); ++a) {
      for (auto b = entire(V); !b.at_end(); ++b) {
        if (*b != *a) {
          for (auto c = entire(V); !c.at_end(); ++c) {
            if (*c != *b && *c != *a) {
              Rational newd = d(*a,*c) + d(*b,*c) - d(*a,*b);
              if (newd > max || !init) {
                max = newd;
                p = *a; q = *b; r = *c;
                init = true;
              }
            }
          }
        }
      }
    } // End find maximal triple

    // Compute distances to the new virtual element t
    Rational dtp = (d(p,q) + d(p,r) - d(q,r)) / 2;
    Vector<Rational> dtx(d.cols()); // Again, start counting from 1
    Int x = 0;
    for (auto i = entire(V); !i.at_end(); ++i) {
      if (*i != p) {
        dtx[*i] = d(*i,p) - dtp;
        if (*i != q && dtx[*i] == 0) {
          x = *i;
        }
      }
    }
    V -= p;
    V -= q;

    // Now 'add' the new vertex
    if (x> 0) {
      leaves[x] = leaves[x] + leaves[p] + leaves[q];
      if (leaves[p].size() > 1 && leaves[p].size() < n-1) {
        coeffs |= d(p,x);
        sets |= leaves[p];
        nodes_by_sets[orig[p]-1] += (sets.dim()-1);
        nodes_by_sets[orig[x]-1] += (sets.dim()-1);
      }
      if (leaves[q].size() > 1 && leaves[q].size() < n-1) {
        coeffs |= d(q,x);
        sets |= leaves[q];
        nodes_by_sets[orig[q]-1] += (sets.dim()-1);
        nodes_by_sets[orig[x]-1] += (sets.dim()-1);
      }
      // If p or q are leaves, add them to the node leaves of x
      if (leaves[p].size() == 1) nodes_by_leaves[orig[x]-1] += leaves[p];
      if (leaves[q].size() == 1) nodes_by_leaves[orig[x]-1] += leaves[q];
      // Graph case
      G.edge(orig[p]-1,orig[x]-1);
      G.edge(orig[q]-1,orig[x]-1);
      edge_order |= std::pair<Int, Int>(orig[p]-1,orig[x]-1);
      edge_order |= std::pair<Int, Int>(orig[q]-1,orig[x]-1);
    }
    else {
      // Note: It can not be possible that t=q and q is a leaf, since the removal
      // of p would then yield a disconnected graph
      // Graph case
      // If d(t,p) or d(t,q) = 0, identify t with p (or q)
      // Otherwise give t the next available node index
      if (dtp != 0 && dtx[q] != 0) {
        Int node_number = G.add_node();
        orig |= (node_number+1);
        nodes_by_leaves |= Set<Int>();
        nodes_by_sets |= Set<Int>();
      }
      if (dtp == 0) {
        orig |= orig[p];
      }
      if (dtx[q] == 0) {
        orig |= orig[q];
      }
      // We update the distance matrix, since we add a new element
      d = d | zero_vector<Rational>();
      d = d / zero_vector<Rational>();
      Int t = d.cols() -1;
      for (auto i = entire(V); !i.at_end(); i++) {
        d(*i,t) = d(t,*i) = dtx[*i];
      }

      // Now add the new vertex
      V += t;
      leaves[t] = leaves[p] + leaves[q];

      if (leaves[p].size() > 1 && leaves[p].size() < n-1) {
        if (dtp != 0) {
          coeffs |= dtp;
          sets |= leaves[p];
          nodes_by_sets[orig[p]-1] += (sets.dim()-1);
          nodes_by_sets[orig[t]-1] += (sets.dim()-1);
        }
      }
      if (leaves[q].size() > 1 && leaves[q].size() < n-1) {
        if (dtx[q] != 0) {
          coeffs |= dtx[q];
          sets |= leaves[q];
          nodes_by_sets[orig[q]-1] += (sets.dim()-1);
          nodes_by_sets[orig[t]-1] += (sets.dim()-1);
        }
      }

      // Now add the leaves
      if (leaves[p].size() == 1) nodes_by_leaves[orig[t]-1] += leaves[p];
      if (leaves[q].size() == 1) nodes_by_leaves[orig[t]-1] += leaves[q];

      if (dtp != 0) {
        G.edge(orig[t]-1,orig[p]-1);
        edge_order |= std::pair<Int, Int>(orig[t]-1,orig[p]-1);
      }
      if (dtx[q] != 0) {
        G.edge(orig[t]-1,orig[q]-1);
        edge_order |= std::pair<Int, Int>(orig[t]-1,orig[q]-1);
      }
    }
  } // End while(>3)

  // Now treat the basic cases of size 2 and 3
  Vector<Int> vAsList(V);
  if (V.size() == 3) {
    // Solve the linear system given by the pairwise distances
    Matrix<Rational> A(3,3);
    // Create the inverse matrix of the distance relation and multiply it with the distance vectors
    A(0,0) = A(0,1) = A(1,0) = A(1,2) = A(2,1) = A(2,2) = 0.5;
    A(0,2)  = A (1,1) = A(2,0) = -0.5;
    Vector<Rational> B(3);
    B[0] = d(vAsList[0],vAsList[1]);
    B[1] = d(vAsList[0],vAsList[2]);
    B[2] = d(vAsList[1],vAsList[2]);
    Vector<Rational> a = A * B;
    Int zeroa = -1;
    Array<Int> setsindices(3); //Indices of partitions in variable sets
    for (Int i = 0; i < 3; ++i) {
      setsindices[i] = -1;
      if (a[i] != 0) {
        if (leaves[vAsList[i]].size() > 1 && leaves[vAsList[i]].size() < n-1) {
          coeffs |= a[i];
          sets |= leaves[vAsList[i]];
          setsindices[i] = sets.dim()-1;
        }
      } else {
        zeroa = i;
      }
    }
    // Graph case
    // If all distances are nonzero, we add a vertex
    if (zeroa == -1) {
      Int t = G.add_node();
      nodes_by_leaves |= Set<Int>();
      nodes_by_sets |= Set<Int>();
      for (Int j = 0; j < 3; ++j) {
        G.edge(t,orig[vAsList[j]]-1);
        edge_order |= std::pair<Int, Int>(t,orig[vAsList[j]]-1);
        if (leaves[vAsList[j]].size() == 1) {
          nodes_by_leaves[t] += leaves[vAsList[j]];
        } else {
          nodes_by_sets[t] += setsindices[j];
          nodes_by_sets[orig[vAsList[j]]-1] += setsindices[j];
        }
      }	
    }
    // Otherwise we add the adjacencies of the two egdes
    else {
      for (Int j = 0; j < 3; ++j) {
        if (j != zeroa) {
          G.edge(orig[vAsList[j]]-1,orig[vAsList[zeroa]]-1);
          edge_order |= std::pair<Int, Int>(orig[vAsList[j]]-1,orig[vAsList[zeroa]]-1);
          if (leaves[vAsList[j]].size() == 1) {
            nodes_by_leaves[orig[vAsList[zeroa]]-1] += leaves[vAsList[j]];
          } else {
            nodes_by_sets[orig[vAsList[zeroa]]-1] += setsindices[j];
            nodes_by_sets[orig[vAsList[j]]-1] += setsindices[j];
          }
        }
      }
    }
  } // End case size == 3

  if (V.size() == 2) {
    // Two remaining nodes forming a tree cannot both be leaves of the original tree
    // If necessary, we swap the list, so that the first element is the non-leaf
    if (leaves[vAsList[0]].size() == 1) {
      std::swap(vAsList[0],vAsList[1]);
    }
    // We only have a bounded edge, if the second element is also not a leaf
    if (leaves[vAsList[1]].size() > 1 && leaves[vAsList[1]].size() < n-1) {
      coeffs |= d(vAsList[0],vAsList[1]);
      sets |= leaves[vAsList[0]];
      nodes_by_sets[orig[vAsList[0]]-1] += (sets.dim()-1);
      nodes_by_sets[orig[vAsList[1]]-1] += (sets.dim()-1);
    }
    // Otherwise we add a leaf at the first element
    else {
      nodes_by_leaves[orig[vAsList[0]]-1] += leaves[vAsList[1]];
    }
    // Graph case
    G.edge(orig[vAsList[0]]-1,orig[vAsList[1]]-1);
    edge_order |= std::pair<Int, Int>(orig[vAsList[0]]-1,orig[vAsList[1]]-1);
  }

  // Now we're done, so we create the result

  // Create node labels
  Array<std::string> labels(G.nodes());
  for (Int i = 0; i < n; ++i) {
    labels[i] = std::to_string(i+1);
  }

  // Compute node degrees
  nodes_by_leaves = nodes_by_leaves.slice(~sequence(0,n));
  nodes_by_sets = nodes_by_sets.slice(~sequence(0,n));
  Vector<Int> node_degrees(nodes_by_leaves.dim());
  for (Int nn = 0; nn < node_degrees.dim(); ++nn) {
    node_degrees[nn] = nodes_by_leaves[nn].size() + nodes_by_sets[nn].size();
  }

  BigObject graph("graph::Graph",
                  "N_NODES", G.nodes(),
                  "ADJACENCY", G,
                  "NODE_LABELS", labels);

  // The edges in G might now have a different order than the one in which we put it in
  // Hence we have to make sure, the order of SETS and COEFFS is compatible with the EDGES order
  // For this we have kept edge_order as a record of the original order of edges.
  const Array<Set<Int>> edge_list = graph.call_method("EDGES");
  // First we throw out all the edges in the original ordering that are actually leaves
  Set<Int> leaf_edges;
  for (Int oe = 0; oe < edge_order.dim(); ++oe) {
    if (edge_order[oe].first < n || edge_order[oe].second < n)
      leaf_edges += oe;
  }
  edge_order = edge_order.slice(~leaf_edges);

  // FIXME: misuse of Vector concatenation
  Vector<Set<Int>> ordered_sets;
  Vector<Rational> ordered_coeffs;
  for (const auto& edge : edge_list) {
    // First, see if it has an entry < n. Then its actually a leaf, not a bounded edge
    if (edge.front() >= n) {
      // Check which edge (in the original ordering) agrees with this one
      Int oeindex = -1;
      for (Int oe = 0; oe < edge_order.dim(); ++oe) {
        if (edge.contains(edge_order[oe].first) && edge.contains(edge_order[oe].second)) {
          oeindex = oe;
          break;
        }
      }
      ordered_sets |= sets[oeindex];
      ordered_coeffs |= coeffs[oeindex];
    }
  } // END re-order sets and coeffs

  if (sets.dim() == 0) {
    sets |= Set<Int>();
    coeffs |= 0;
  }

  return BigObject("RationalCurve",
                   "SETS", ordered_sets,
                   "COEFFS", ordered_coeffs,
                   "N_LEAVES", n,
                   "GRAPH", graph,
                   "GRAPH_EDGE_LENGTHS", ordered_coeffs,
                   "NODES_BY_LEAVES", nodes_by_leaves,
                   "NODES_BY_SETS", nodes_by_sets,
                   "NODE_DEGREES", node_degrees);
}

// Documentation see perl wrapper
BigObject curveFromMetric(const Vector<Rational>& metric)
{
  return curveAndGraphFromMetric(metric);
}


/*
 * @brief Takes a vector from Q^(n over 2) that describes an n-marked rational abstract
 * curve as a distance vector between its leaves. It then computes the
 * graph of the curve corresponding to this vector.
 * @param Vector<Rational> v A vector of length (n over 2). Its entries are
 * interpreted as the distances d(i,j) ordered lexicographically according to i,j. However, they need not be positive, as long as v is equivalent to a proper
 * metric modulo leaf lengths.
 * @return An array containing first the graph::Graph and then a Vector<Rational>, containing
 * the lengths of the bounded edges (in the order they appear in EDGES)
 */
ListReturn graphFromMetric(const Vector<Rational>& metric)
{
  BigObject curve = curveAndGraphFromMetric(metric);
  BigObject graph = curve.give("GRAPH");
  Vector<Rational> lengths = curve.give("COEFFS");
  ListReturn result;
  result << graph.copy();
  result << lengths;
  return result;
}


/**
   @brief Takes a linear combination of abstract n-marked curves with 1 bounded edge, described by their partitions and the corresponding edge length and computes the resulting metric
   @param IncidenceMatrix<> sets A list of partitions of {1,..,n}. May be redundant.
   @param Vector<Set<Int>> coeffs A list of arbitrary rational coefficients. Superfluous coefficients are ignored, missing ones replaced by 0.
   @param Int n The size of the leaf set
   @return Vector<Rational> A curve metric of length (n over 2)
*/
Vector<Rational> metricFromCurve(const IncidenceMatrix<>& sets, const Vector<Rational>& coeffs, Int n)
{
  // Create distance matrix (we count from 1 for simplicity)
  Matrix<Rational> d(n+1, n+1);
  const auto completeSet = sequence(1,n);
  // Go through all sets
  for (Int s = 0; s < sets.rows(); ++s) {
    // If we have no more coefficients, stop calculating
    if (s >= coeffs.dim()) break;
    // Otherwise add the coefficients to the appropriate distances
    Rational c = coeffs[s];
    const auto& sset = sets.row(s);
    Set<Int> complement = completeSet - sset;
    for (const Int selt : sset) {
      for (const Int celt : complement) {
        d(selt, celt) += c;
        d(celt, selt) += c;
      }
    }
  }

  // Now convert to a vector
  Vector<Rational> result;
  for (Int i = 1; i < n; ++i) {
    for (Int j = i+1; j <= n; j++) {
      result |= d(i,j);
    }
  }

  return result;
}


// Documentation see perl wrapper
template <typename Addition>
BigObject rational_curve_from_matroid_coordinates(Vector<Rational> matroidVector)
{
  matroidVector = matroidVector.slice(range_from(1));

  // Convert vector to a map
  Int n = moduliDimensionFromLength(matroidVector.dim())+1;
  Matrix<Rational> d(n, n);
  Int index = 0;
  for (Int i = 1; i < n-1; ++i) {
    for (Int j = i+1; j <= n-1; ++j) {
      // The isomorphism is rigged for max, so we need to insert a sign here
      d(i,j) = (-Addition::orientation())*matroidVector[index];
      ++index;
    }
  }

  // Now apply mapping
  Vector<Rational> metric;
  for (Int i = 1; i < n; ++i) {
    for (Int j = i+1; j <= n; ++j) {
      if (j == n) {
        metric |= 0;
      } else {
        metric |= (2* d(i,j));
      }
    }
  }

  return curveFromMetric(metric);
}

// Documentation see perl wrapper
template <typename Addition>
ListReturn rational_curve_list_from_matroid_coordinates(const Matrix<Rational>& m)
{
  ListReturn result;

  for (Int i = 0; i < m.rows(); ++i) {
    result << rational_curve_from_matroid_coordinates<Addition>(m.row(i));
  }

  return result;
}


/**
   @brief Takes a rational n-marked abstract curve and computes its representation in the matroid coordinates of the moduli space
   @param BigObject The rational curve
   @return Vector<Rational>
*/
template <typename Addition>
Vector<Rational> matroid_coordinates_from_curve(BigObject curve)
{
  // Extract values
  IncidenceMatrix<> sets = curve.give("SETS");
  Vector<Rational> coeffs = curve.give("COEFFS");
  const Int n = curve.give("N_LEAVES");

  // Create edge index map (i,j) -> vector index
  Matrix<Int> E(n, n);
  Int index = 0;
  for (Int i = 1; i < n-1; ++i) {
    for (Int j = i+1; j <= n-1; ++j) {
      E(i,j) = E(j,i) = index;
      ++index;
    }
  }

  // Compute ambient dimension of moduli space
  const Int raydim = (n*(n-3))/2 +1;
  const auto completeSet = sequence(1,n);

  Vector<Rational> result(raydim);

  // Map each set to matroid coordinates with appropriate coefficient
  for (Int s = 0; s < sets.rows(); ++s) {
    Set<Int> sset = sets.row(s);
    // Make sure the set does not contain n
    if (sset.contains(n)) sset = completeSet - sset;
    // Now create the flat vector for the complete graph on vertices in sset
    Vector<Int> slist(sset);
    for (Int i = 0; i < slist.dim(); ++i) {
      for (Int j = i+1; j < slist.dim(); ++j) {
        result[E(slist[i],slist[j])] += Addition::orientation() * coeffs[s];
      }
    }
  }

  result = (Rational(0) | result);
  return result;
}


// Documentation see perl wrapper
ListReturn curveFromMetricMatrix(const Matrix<Rational>& m)
{
  ListReturn result;

  for (Int i = 0; i < m.rows(); ++i) {
    result << curveFromMetric(m.row(i));
  }

  return result;
}


/**
   @brief This computes the properties [[NODES_BY_SETS]] and [[NODES_BY_LEAVES]] of a RationalCurve object
*/
void computeNodeData(BigObject curve)
{
  Vector<Rational> metric = curve.call_method("metric_vector");
  // We recompute the curve to make sure the graph edges have the same order
  // as the curve sets
  BigObject newcurve = curveAndGraphFromMetric(metric);

  // We might have to permute the column indices in the node matrices, since the sets might
  // be in a different order in the actual curve
  // For this we have to normalize both set descriptions to contain the element 1

  const Int n = newcurve.give("N_LEAVES");
  const auto all_leaves = sequence(1, n);
  IncidenceMatrix<> newsetsInc = newcurve.give("SETS");
  Vector<Set<Int>> newsets = incMatrixToVector(newsetsInc);
  for (Int ns = 0; ns < newsets.dim(); ++ns) {
    if (*(newsets[ns].begin()) != 1)
      newsets[ns] = all_leaves - newsets[ns];
  }
  IncidenceMatrix<> oldsetsInc = curve.give("SETS");
  Vector<Set<Int>> oldsets = incMatrixToVector(oldsetsInc);
  for (Int os = 0; os < oldsets.dim(); ++os) {
    if(*(oldsets[os].begin()) != 1)
      oldsets[os] = all_leaves - oldsets[os];
  }
  Array<Int> perm(newsets.dim());
  for (Int i = 0; i < perm.size(); ++i) {
    // Find equal set
    for (Int j = 0; j < perm.size(); ++j) {
      if (newsets[i] == oldsets[j]) {
        perm[i] = j; break;
      }
    }
  }

  IncidenceMatrix<> new_node_sets = newcurve.give("NODES_BY_SETS");
  IncidenceMatrix<> node_leaves = newcurve.give("NODES_BY_LEAVES");
  Vector<Int> node_degrees = newcurve.give("NODE_DEGREES");

  // Convert the node set matrix
  Vector<Set<Int>> old_node_sets;
  for (Int nns = 0; nns < new_node_sets.rows(); ++nns) {
    Set<Int> new_edge = new_node_sets.row(nns);
    Set<Int> old_edge;
    for (auto ne = entire(new_edge); !ne.at_end(); ++ne) {
      old_edge += perm[*ne];
    }
    old_node_sets |= old_edge;
  }

  curve.take("NODES_BY_LEAVES") << node_leaves;
  curve.take("NODES_BY_SETS") << old_node_sets;
  curve.take("NODE_DEGREES") << node_degrees;
}


UserFunction4perl("# @category Abstract rational curves"
                  "# Takes a vector from Q^(n over 2) that describes an n-marked rational abstract"
                  "# curve as a distance vector between its leaves. It then computes the "
                  "# curve corresponding to this vector."
                  "# @param Vector<Rational> v A vector of length (n over 2). Its entries are "
                  "# interpreted as the distances d(i,j) ordered lexicographically according to i,j. However, they need not be positive, as long as v is equivalent to a proper "
                  "# metric modulo leaf lengths."
                  "# @return RationalCurve",
                  &curveFromMetric,"rational_curve_from_metric(Vector<Rational>)");

UserFunctionTemplate4perl("# @category Abstract rational curves"
                          "# Takes a vector from $ Q^{(n-1) over 2} $ that lies in $ M_{0,n} $ (in its matroid coordinates) "
                          "# and computes the corresponding rational curve."
                          "# In the isomorphism of the metric curve space and the moduli coordinates"
                          "# the last leaf is considered as the special leaf"
                          "# @param Vector<Rational> v A vector in the moduli space (WITH leading coordinate)."
                          "# @tparam Addition Min or Max (i.e. what are the matroid coordinates using)"
                          "# @return RationalCurve",
                          "rational_curve_from_matroid_coordinates<Addition>(Vector<Rational>)");

UserFunctionTemplate4perl("# @category Abstract rational curves"
                          "# Takes a matrix whose rows are elements in the moduli space M_0,n in matroid "
                          "# coordinates. Returns a list, where the i-th element is the curve corr. to "
                          "# the i-th row in the matrix"
                          "# @param Matrix<Rational> m A list of vectors in the moduli space (with leading coordinate)."
                          "# @tparam Addition Mir or Max (i.e. what are the matroid coordinates using"
                          "# @return RationalCurve : An array of RationalCurves",
                          "rational_curve_list_from_matroid_coordinates<Addition>(Matrix<Rational>)");

UserFunction4perl("# @category Abstract rational curves"
                  "# Takes a matrix whose rows are metrics of rational n-marked curves."
                  "# Returns a list, where the i-th element is the curve corr. to "
                  "# the i-th row in the matrix"
                  "# @param Matrix<Rational> m"
                  "# @return RationalCurve : An array of RationalCurves",
                  &curveFromMetricMatrix, "rational_curve_list_from_metric(Matrix<Rational>)");

UserFunction4perl("# @category Abstract rational curves"
                  "# Takes a metric vector in Q^{(n over 2)} and checks whether it fulfills "
                  "# the four-point condition, i.e. whether it lies in M_0,n. More precisely "
                  "# it only needs to be equivalent to such a vector"
                  "# @param Vector<Rational> v The vector to be checked"
                  "# @return Int A quadruple (array) of indices, where the four-point condition "
                  "# is violated or an empty list, if the vector is indeed in M_0,n",
                  &wrapTestFourPointCondition, "testFourPointCondition(Vector<Rational>)");

UserFunctionTemplate4perl("# @category Abstract rational curves"
                          "# Takes a rational curve and converts it into the corresponding matroid coordinates"
                          "# in the moduli space of rational curves (including the leading 0 for a ray!)"
                          "# @param RationalCurve r A rational n-marked curve"
                          "# @tparam Addition Min or Max, i.e. which coordinates to use."
                          "# @return Vector<Rational> The matroid coordinates, tropically homogeneous and"
                          "# with leading coordinate",
                          "matroid_coordinates_from_curve<Addition>(RationalCurve)");

Function4perl(&graphFromMetric, "curve_graph_from_metric(Vector)");
Function4perl(&metricFromCurve, "metric_from_curve(IncidenceMatrix, Vector<Rational>, $)");
Function4perl(&computeNodeData, "compute_node_data(RationalCurve)");

} }
