/**
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This file is part of the Basalt project.
https://gitlab.com/VladyslavUsenko/basalt-headers.git

Copyright (c) 2019, Vladyslav Usenko and Nikolaus Demmel.
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@file
@brief Common functions for B-spline evaluation
*/

#pragma once

#include <Eigen/Dense>
#include <cstdint>

namespace basalt {

/// @brief Compute binomial coefficient.
///
/// Computes number of combinations that include k objects out of n.
/// @param[in] n
/// @param[in] k
/// @return binomial coefficient
constexpr inline uint64_t binomialCoefficient(uint64_t n, uint64_t k) {
  if (k > n) {
    return 0;
  }
  uint64_t r = 1;
  for (uint64_t d = 1; d <= k; ++d) {
    r *= n--;
    r /= d;
  }
  return r;
}

/// @brief Compute blending matrix for uniform B-spline evaluation.
///
/// @param _N order of the spline
/// @param _Scalar scalar type to use
/// @param _Cumulative if the spline should be cumulative
template <int _N, typename _Scalar = double, bool _Cumulative = false>
Eigen::Matrix<_Scalar, _N, _N> computeBlendingMatrix() {
  Eigen::Matrix<double, _N, _N> m;
  m.setZero();

  for (int i = 0; i < _N; ++i) {
    for (int j = 0; j < _N; ++j) {
      double sum = 0;

      for (int s = j; s < _N; ++s) {
        sum += std::pow(-1.0, s - j) * binomialCoefficient(_N, s - j) *
               std::pow(_N - s - 1.0, _N - 1.0 - i);
      }
      m(j, i) = binomialCoefficient(_N - 1, _N - 1 - i) * sum;
    }
  }

  if (_Cumulative) {
    for (int i = 0; i < _N; i++) {
      for (int j = i + 1; j < _N; j++) {
        m.row(i) += m.row(j);
      }
    }
  }

  uint64_t factorial = 1;
  for (int i = 2; i < _N; ++i) {
    factorial *= i;
  }

  return (m / factorial).template cast<_Scalar>();
}

/// @brief Compute base coefficient matrix for polynomials of size N.
///
/// In each row starting from 0 contains the derivative coefficients of the
/// polynomial. For _N=5 we get the following matrix: \f[ \begin{bmatrix}
///   1 & 1 & 1 & 1 & 1
/// \\0 & 1 & 2 & 3 & 4
/// \\0 & 0 & 2 & 6 & 12
/// \\0 & 0 & 0 & 6 & 24
/// \\0 & 0 & 0 & 0 & 24
/// \\ \end{bmatrix}
/// \f]
/// Functions \ref RdSpline::baseCoeffsWithTime and \ref
/// So3Spline::baseCoeffsWithTime use this matrix to compute derivatives of the
/// time polynomial.
///
/// @param _N order of the polynomial
/// @param _Scalar scalar type to use
template <int _N, typename _Scalar = double>
Eigen::Matrix<_Scalar, _N, _N> computeBaseCoefficients() {
  Eigen::Matrix<double, _N, _N> base_coefficients;

  base_coefficients.setZero();
  base_coefficients.row(0).setOnes();

  constexpr int DEG = _N - 1;
  int order = DEG;
  for (int n = 1; n < _N; n++) {
    for (int i = DEG - order; i < _N; i++) {
      base_coefficients(n, i) = (order - DEG + i) * base_coefficients(n - 1, i);
    }
    order--;
  }
  return base_coefficients.template cast<_Scalar>();
}

}  // namespace basalt