// Copyright © 2016-2025 Thomas Nagler and Thibault Vatter
//
// This file is part of the vinecopulib library and licensed under the terms of
// the MIT license. For a copy, see the LICENSE file in the root directory of
// vinecopulib or https://vinecopulib.github.io/vinecopulib/.

#pragma once

#include <Eigen/Dense>
#include <limits>
#include <vinecopulib/misc/nlohmann_json.hpp>
#include <vinecopulib/misc/triangular_array.hpp>

namespace vinecopulib {

//! @brief A class for R-vine structures.
//!
//! RVineStructure objects encode the tree structure of the vine, i.e. the
//! conditioned/conditioning variables of each edge. It is represented by a
//! triangular array. An exemplary array is
//! 
//! ```
//! 4 4 4 4
//! 3 3 3
//! 2 2
//! 1
//! ```
//! 
//! which encodes the following pair-copulas:
//! 
//! ```
//! | tree | edge | pair-copulas |
//! |------|------|--------------|
//! | 0    | 0    | (1, 4)       |
//! |      | 1    | (2, 4)       |
//! |      | 2    | (3, 4)       |
//! | 1    | 0    | (1, 3; 4)    |
//! |      | 1    | (2, 3; 4)    |
//! | 2    | 0    | (1, 2; 3, 4) |
//! ```
//! 
//! Denoting by `M[i, j]` the array entry in row `i` and column `j`,
//! the pair-copula index for edge `e` in tree `t` of a `d` dimensional vine
//! is `(M[d - 1 - e, e], M[t, e]; M[t - 1, e], ..., M[0, e])`. Less
//! formally,
//!
//!   1. Start with the counter-diagonal element of column `e` 
//!      (first conditioned variable).
//!   2. Jump up to the element in row `t` (second conditioned variable).
//!   3. Gather all entries further up in column `e` (conditioning set).
//!
//! Internally, the diagonal is stored separately from the off-diagonal 
//! elements, which are stored as a triangular array. For instance, the 
//! off-diagonal elements off the structure above are stored as
//!
//! ```
//! 4 4 4
//! 3 3
//! 2
//! ```
//!
//! for the structure above. The reason is that it allows for parsimonious
//! representations of truncated models. For instance, the 2-truncated model is
//! represented by the same diagonal and the following truncated triangular
//! array:
//!
//! ```
//! 4 4 4
//! 3 3
//! ```
//! 
//! A valid R-vine array must satisfy several conditions which are checked
//! when `RVineStructure()` is called:
//! 
//!   1. It only contains numbers between 1 and d.
//!   2. The diagonal must contain the numbers 1, ..., d.
//!   3. The diagonal entry of a column must not be contained in any
//!      column further to the right.
//!   4. The entries of a column must be contained in all columns to the left.
//!   5. The proximity condition must hold: For all t = 1, ..., d - 2 and
//!      e = 0, ..., d - t - 1 there must exist an index j > d, such that
//!      `(M[t, e], {M[0, e], ..., M[t-1, e]})` equals either
//!      `(M[d-j-1, j], {M[0, j], ..., M[t-1, j]})` or
//!      `(M[t-1, j], {M[d-j-1, j], M[0, j], ..., M[t-2, j]})`.
//!
//! An R-vine array is said to be in natural order when the anti-diagonal
//! entries are \f$ 1, \dots, d \f$ (from left to right). The exemplary arrray
//! above is in natural order. Any R-vine array can be characterized by the
//! diagonal entries (called order) and the entries below the diagonal of the
//! corresponding R-vine array in natural order. Since most algorithms work
//! with the structure in natural order, this is how RVineStructure stores the
//! structure internally.
class RVineStructure
{
public:
  explicit RVineStructure(
    const size_t& d = static_cast<size_t>(1),
    const size_t& trunc_lvl = std::numeric_limits<size_t>::max());
  explicit RVineStructure(
    const Eigen::Matrix<size_t, Eigen::Dynamic, Eigen::Dynamic>& mat,
    bool check = true);
  explicit RVineStructure(
    const std::vector<size_t>& order,
    const size_t& trunc_lvl = std::numeric_limits<size_t>::max(),
    bool check = true);
  RVineStructure(const std::vector<size_t>& order,
                 const TriangularArray<size_t>& struct_array,
                 bool natural_order = false,
                 bool check = true);
  explicit RVineStructure(const std::string& filename, const bool check = true);
  explicit RVineStructure(const nlohmann::json& input, const bool check = true);

  nlohmann::json to_json() const;
  void to_file(const std::string& filename) const;

  size_t get_dim() const;
  size_t get_trunc_lvl() const;
  std::vector<size_t> get_order() const;
  TriangularArray<size_t> get_struct_array(bool natural_order = false) const;
  TriangularArray<size_t> get_min_array() const;
  TriangularArray<short unsigned> get_needed_hfunc1() const;
  TriangularArray<short unsigned> get_needed_hfunc2() const;
  Eigen::Matrix<size_t, Eigen::Dynamic, Eigen::Dynamic> get_matrix() const;

  size_t struct_array(size_t tree,
                      size_t edge,
                      bool natural_order = false) const;
  size_t min_array(size_t tree, size_t edge) const;
  bool needed_hfunc1(size_t tree, size_t edge) const;
  bool needed_hfunc2(size_t tree, size_t edge) const;

  void truncate(size_t trunc_lvl);
  std::string str() const;

  static RVineStructure simulate(size_t d,
                                 bool natural_order = false,
                                 std::vector<int> seeds = std::vector<int>());

protected:
  size_t find_trunc_lvl(
    const Eigen::Matrix<size_t, Eigen::Dynamic, Eigen::Dynamic>& mat) const;
  std::vector<size_t> get_order(
    const Eigen::Matrix<size_t, Eigen::Dynamic, Eigen::Dynamic>& mat) const;
  TriangularArray<size_t> to_rvine_array(
    const Eigen::Matrix<size_t, Eigen::Dynamic, Eigen::Dynamic>& mat) const;

  TriangularArray<size_t> to_natural_order() const;
  static TriangularArray<size_t> make_dvine_struct_array(size_t d,
                                                         size_t trunc_lvl);
  static TriangularArray<size_t> make_cvine_struct_array(size_t d,
                                                         size_t trunc_lvl);
  TriangularArray<size_t> compute_min_array() const;
  TriangularArray<short unsigned> compute_needed_hfunc1() const;
  TriangularArray<short unsigned> compute_needed_hfunc2() const;

  void check_if_quadratic(
    const Eigen::Matrix<size_t, Eigen::Dynamic, Eigen::Dynamic>& mat) const;
  void check_lower_tri(
    const Eigen::Matrix<size_t, Eigen::Dynamic, Eigen::Dynamic>& mat) const;
  void check_upper_tri() const;
  void check_columns() const;
  void check_antidiagonal() const;
  void check_proximity_condition() const;

  std::vector<size_t> order_;
  size_t d_;
  size_t trunc_lvl_;
  TriangularArray<size_t> struct_array_;
  TriangularArray<size_t> min_array_;
  // can't use bool b/c the comittee messed up std::vector<bool>
  TriangularArray<short unsigned> needed_hfunc1_;
  TriangularArray<short unsigned> needed_hfunc2_;
};

std::ostream&
operator<<(std::ostream& os, const RVineStructure& rvs);

//! @brief A class for D-vine structures.
//!
//! D-vines are a special class of R-vines where each tree is a path. A D-vine
//! structure is determined entirely by the order of variables. For example, if
//! the order is `(1, 2, 3, 4)`, the first tree in the vine is 1-2-3-4 and all
//! further trees are unique due to the proximity condition.
//!
//! Note that `DVineStructure` objects inherit the methods and attributes of
//! `RVineStructure` objects.
class DVineStructure : public RVineStructure
{
public:
  explicit DVineStructure(const std::vector<size_t>& order);
  DVineStructure(const std::vector<size_t>& order, size_t trunc_lvl);
};

//! @brief A class for C-vine structures.
//!
//! C-vines are a special class of R-vines where each tree is a star. A C-vine
//! structure is determined entirely by the order of variables. For example, if
//! the order is `{1, 2, 3, 4}`, the first tree in the vine connects variable
//! 4 with all others, the second tree connects variable 3 with all others,
//! etc.
//!
//! Note that `CVineStructure` objects inherit the methods and attributes of
//! `RVineStructure` objects.
class CVineStructure : public RVineStructure
{
public:
  explicit CVineStructure(const std::vector<size_t>& order);
  CVineStructure(const std::vector<size_t>& order, size_t trunc_lvl);
};
}

#include <vinecopulib/vinecop/implementation/rvine_structure.ipp>
