| Line | Branch | Exec | Source |
|---|---|---|---|
| 1 | #pragma once | ||
| 2 | |||
| 3 | #ifndef REAL_TYPE | ||
| 4 | #define REAL_TYPE double | ||
| 5 | #endif | ||
| 6 | |||
| 7 | #ifndef DIM | ||
| 8 | #define DIM 3 | ||
| 9 | #endif | ||
| 10 | |||
| 11 | #include <eigen3/Eigen/Dense> | ||
| 12 | #include <yaml-cpp/yaml.h> | ||
| 13 | |||
| 14 | using Real = REAL_TYPE; | ||
| 15 | using Vec = Eigen::Matrix<Real, DIM, 1>; | ||
| 16 | using VecVec = Eigen::Matrix<Real, DIM, Eigen::Dynamic>; | ||
| 17 | using ArrayI = Eigen::Array<int, DIM, 1>; | ||
| 18 | |||
| 19 | /** | ||
| 20 | * Get the minimum image vector from position r1 to r2 with respect to a box of size L. | ||
| 21 | */ | ||
| 22 | 695206245 | inline Vec r_ij(const Vec &L, const Vec &r1, const Vec &r2) { | |
| 23 | 695206245 | Vec result; | |
| 24 | 695206245 | result = r2 - r1; | |
| 25 | 695206245 | result.array() -= (result.array() / L.array()).round() * L.array(); | |
| 26 | 695206245 | return result; | |
| 27 | } | ||
| 28 | |||
| 29 | namespace YAML { | ||
| 30 | |||
| 31 | // The following enables yaml-cpp to natively encode and decode Eigen matrices and arrays. | ||
| 32 | // For example, one can now use node[key].as<Vec>() | ||
| 33 | template <template <typename, int...> class EigenClass, typename Scalar, int d> | ||
| 34 | struct convert<EigenClass<Scalar, d, 1>> { | ||
| 35 | 20 | static Node encode(const EigenClass<Scalar, d, 1> &rhs) { | |
| 36 | 20 | Node node; | |
| 37 |
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80 | for (int i = 0; i < d; ++i) { |
| 38 |
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60 | node.push_back(rhs[i]); |
| 39 | } | ||
| 40 | 20 | return node; | |
| 41 | } | ||
| 42 | |||
| 43 | 110 | static bool decode(const Node &node, EigenClass<Scalar, d, 1> &rhs) { | |
| 44 |
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110 | if (!node.IsSequence() || node.size() != d) { |
| 45 | ✗ | return false; | |
| 46 | } | ||
| 47 | |||
| 48 |
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440 | for (int i = 0; i < d; ++i) { |
| 49 |
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330 | rhs[i] = node[i].as<Scalar>(); |
| 50 | } | ||
| 51 | 110 | return true; | |
| 52 | } | ||
| 53 | }; | ||
| 54 | |||
| 55 | // This helper class is needed because C++ forbids partial specialization of functions. | ||
| 56 | // In our case, we want to specialize the parse function to generic Eigen types. | ||
| 57 | template <typename ReturnT, typename DefaultT = ReturnT> struct ParseHelper { | ||
| 58 |
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946 | ReturnT operator()(const Node &node, const std::string &key) { return node[key].as<ReturnT>(); } |
| 59 | 1468 | ReturnT operator()(const Node &node, const std::string &key, DefaultT defaultValue) { | |
| 60 |
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1468 | return node[key] ? (*this)(node, key) : defaultValue; |
| 61 | } | ||
| 62 | }; | ||
| 63 | |||
| 64 | template <template <typename, int...> class EigenClass, typename Scalar1, int d, typename Scalar2> | ||
| 65 | struct ParseHelper<EigenClass<Scalar1, d, 1>, Scalar2> { | ||
| 66 | 274 | EigenClass<Scalar1, d, 1> operator()(const Node &node, const std::string &key) { | |
| 67 |
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822 | return node[key].IsScalar() ? EigenClass<Scalar1, d, 1>::Constant(node[key].as<Scalar1>()) |
| 68 |
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548 | : node[key].as<EigenClass<Scalar1, d, 1>>(); |
| 69 | } | ||
| 70 | 84 | EigenClass<Scalar1, d, 1> operator()(const Node &node, const std::string &key, | |
| 71 | Scalar2 defaultValue) { | ||
| 72 |
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113 | return node[key] ? (*this)(node, key) : EigenClass<Scalar1, d, 1>::Constant(defaultValue); |
| 73 | } | ||
| 74 | }; | ||
| 75 | |||
| 76 | // Two helper methods are provided for easy and consistent parsing of yaml nodes (with and without | ||
| 77 | // setting defaults) | ||
| 78 | 300 | template <typename ReturnT> auto parse(const Node &node, const std::string &key) { | |
| 79 | 300 | return ParseHelper<ReturnT>{}(node, key); | |
| 80 | } | ||
| 81 | |||
| 82 | template <typename ReturnT, typename DefaultT> | ||
| 83 | 818 | auto parse(const Node &node, const std::string &key, DefaultT defaultValue) { | |
| 84 | 818 | return ParseHelper<ReturnT, DefaultT>{}(node, key, defaultValue); | |
| 85 | } | ||
| 86 | |||
| 87 | } // namespace YAML | ||
| 88 |