AtomTranslation 改为以超胞晶格矢为单位，而不是以埃为单位

一些小修改，应该不影响结果
fix build
2026-01-08 12:36:14 +08:00 · 2026-01-08 12:36:14 +08:00 · 2026-01-05 15:21:35 +08:00 · 2025-11-05 12:05:12 +08:00 · 2025-11-05 12:02:52 +08:00 · 2025-11-05 11:37:44 +08:00
104 changed files with 1750 additions and 2718 deletions
--- a/.envrc
+++ b/.envrc
@@ -1 +1 @@
-use flake
+use flake nixos#ufo
--- a/.gitattributes
+++ b/.gitattributes
@@ -0,0 +1,2 @@
+*.hdf5 filter=lfs diff=lfs merge=lfs -text
+*.zpp filter=lfs diff=lfs merge=lfs -text
--- a/.gitignore
+++ b/.gitignore
@@ -1,18 +1,4 @@
-.vscode
 .direnv
-main
-plot
-out.yaml
-.ccls-cache
+build
+.vscode
 .cache
-build/
-test/*
-!test/14.2.2.4.unfold.yaml
-!test/14.2.2.5.unfold.yaml
-!test/14.2.2.5.plot.yaml
-!test/14.2.4.4.unfold.yaml
-!test/14.2.4.4.plot.yaml
-!test/14.2.5.5.unfold.yaml
-!test/14.2.5.5.plot.yaml
-!test/14.2.6.4.unfold.yaml
-!test/14.2.6.4.plot.yaml
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -1,36 +1,51 @@
 cmake_minimum_required(VERSION 3.14)
-project(ufo VERSION 0.0.0 LANGUAGES CXX)
+project(ufo VERSION 0 LANGUAGES CXX)
 enable_testing()
 include(GNUInstallDirs)

-set_property(GLOBAL PROPERTY CXX_STANDARD 23)
-set_property(GLOBAL PROPERTY CXX_STANDARD_REQUIRED ON)
-set_property(GLOBAL PROPERTY CXX_EXTENSIONS OFF)
-
 if(NOT CMAKE_BUILD_TYPE AND NOT CMAKE_CONFIGURATION_TYPES)
  message("Setting build type to 'Release' as none was specified.")
  set(CMAKE_BUILD_TYPE Release CACHE STRING "Choose the type of build." FORCE)
  set_property(CACHE CMAKE_BUILD_TYPE PROPERTY STRINGS "Debug" "Release" "MinSizeRel" "RelWithDebInfo")
 endif()

-find_package(yaml-cpp REQUIRED)
-find_package(Eigen3 REQUIRED)
-find_package(fmt REQUIRED)
-find_package(concurrencpp REQUIRED)
-find_package(HighFive REQUIRED)
 find_package(TBB REQUIRED)
-find_package(glad REQUIRED)
-# find_package(Matplot++ REQUIRED COMPONENTS matplot_opengl)
 find_package(Matplot++ REQUIRED)
-find_path(ZPP_BITS_INCLUDE_DIR zpp_bits.h REQUIRED)
+find_package(biu REQUIRED)
+find_package(Threads REQUIRED)
+message("biu dir: ${biu_DIR}")

-add_executable(ufo src/solver.cpp src/fold.cpp src/unfold.cpp src/plot.cpp src/main.cpp)
-target_include_directories(ufo PRIVATE ${PROJECT_SOURCE_DIR}/include ${ZPP_BITS_INCLUDE_DIR})
-target_link_libraries(ufo PRIVATE
-  yaml-cpp Eigen3::Eigen fmt::fmt concurrencpp::concurrencpp HighFive_HighFive TBB::tbb Matplot++::matplot
-  Matplot++::matplot_opengl)
-# target_compile_definitions(ufo PRIVATE $<$<CONFIG:Debug>:_GLIBCXX_DEBUG>)
+add_executable(ufo src/fold.cpp src/unfold.cpp src/project-to-mode.cpp
+  src/plot.cpp src/raman.cpp src/project-to-atom.cpp src/main.cpp)
+target_include_directories(ufo PRIVATE ${PROJECT_SOURCE_DIR}/include)
+target_link_libraries(ufo PRIVATE TBB::tbb Matplot++::matplot biu::biu)
+target_compile_features(ufo PRIVATE cxx_std_23)
+target_compile_definitions(ufo PRIVATE BIU_LOGGER_SOURCE_ROOT="${CMAKE_SOURCE_DIR}")
+if (CMAKE_BUILD_TYPE STREQUAL "Debug")
+  target_compile_definitions(ufo PRIVATE BIU_LOGGER_DEBUG)
+  target_compile_options(ufo PRIVATE -ftemplate-backtrace-limit=0)
+endif()
+
+install(TARGETS ufo RUNTIME DESTINATION ${CMAKE_INSTALL_BINDIR})

 get_property(ImportedTargets DIRECTORY "${CMAKE_SOURCE_DIR}" PROPERTY IMPORTED_TARGETS)
 message("Imported targets: ${ImportedTargets}")
 message("List of compile features: ${CMAKE_CXX_COMPILE_FEATURES}")
+message("CMake build type: ${CMAKE_BUILD_TYPE}")
+
+include(CTest)
+
+add_test(NAME fold WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/test/fold COMMAND ufo fold config.yaml)
+add_test(NAME unfold WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/test/unfold COMMAND ufo unfold config.yaml)
+add_test(NAME zpp-to-yaml WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/test/zpp-to-yaml
+  COMMAND sh -c "${CMAKE_BINARY_DIR}/ufo zpp-to-yaml < data.zpp > data.yaml")
+add_test(NAME project-to-mode WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/test/project-to-mode
+  COMMAND ufo project-to-mode config.yaml)
+add_test(NAME project-to-atom WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/test/project-to-atom
+  COMMAND ufo project-to-atom config.yaml)
+add_test(NAME raman-create-displacement WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/test/raman-create-displacement
+  COMMAND ufo raman-create-displacement config.yaml)
+add_test(NAME raman-extract WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/test/raman-extract
+  COMMAND ufo raman-extract .)
+add_test(NAME raman-apply-contribution WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/test/raman-apply-contribution
+  COMMAND ufo raman-apply-contribution config.yaml)
--- a/README.md
+++ b/README.md
@@ -1,17 +0,0 @@
-This is a program to approximately unfold phonon spectra.
-
-Currently, there is no documentation, and some not core features are in other branches
-  and implemented in a temporary way, e.g., directly writing data in source file.
-
-I will finish the documentation and merge these features into main branch ASAP.
-
-The program is packaged in a standard way of cmake, so that you can build it just like other cmake projects:
-
-```bash
-mkdir build
-cd build
-cmake ..
-make
-```
-
-and view source files for input and output format.
--- a/default.nix
+++ b/default.nix
@@ -0,0 +1,11 @@
+{
+  stdenv, cmake, pkg-config, version ? null,
+  tbb, matplotplusplus, biu
+}: stdenv.mkDerivation
+{
+  name = "ufo";
+  src = ./.;
+  buildInputs = [ tbb matplotplusplus biu ];
+  nativeBuildInputs = [ cmake pkg-config ];
+  doCheck = true;
+}
--- a/doc/README.md
+++ b/doc/README.md
@@ -0,0 +1,45 @@
+分为几个功能：
+
+* fold：根据要计算的单胞的 q 点路径，计算超胞中对应的 q 点路径，生成的路径再交给 phonopy 计算。
+* unfold：根据 phonopy 计算的结果，将超胞的结果展开到单胞中。
+* plot：对计算结果画图。
+
+主要的输入输出格式均为 yaml。对于数据特别大的情况，也可以从 hdf5 中读取一部分数据或者将一部分数据写入到 hdf5 文件中。
+
+# fold
+
+## 输入
+
+```yaml
+# 三个整数组成的向量，表示从单胞到超胞，三个晶格矢量的倍数
+# 必写
+SuperCellMultiplier: [2, 2, 2]
+# 一个变换矩阵，表明超胞经历了怎样的扭曲。
+# 可选，默认值为单位矩阵
+SuperCellDeformation: [[1, 0, 0], [0, 1, 0], [0, 0, 1]]
+# 一个由三个浮点数组成的向量，表示考虑的 q 点
+# 必写
+Qpoints:
+  - [0, 0, 0]
+  - [0.1, 0, 0]
+  - [0.2, 0, 0]
+  - [0.3, 0, 0]
+  - [0.4, 0, 0]
+  - [0.5, 0, 0]
+# 一个 DataFile 类型的对象，表明输出结果到哪个文件
+# 必写
+OutputFile:
+```
+
+## 输出
+
+```yaml
+# 得到的 q 点坐标
+Qpoints:
+  - [0, 0, 0]
+  - [0.1, 0, 0]
+  - [0.2, 0, 0]
+  - [0.3, 0, 0]
+  - [0.4, 0, 0]
+  - [0.5, 0, 0]
+```
--- a/flake.lock
+++ b/flake.lock
--- a/flake.nix
+++ b/flake.nix
@@ -1,25 +0,0 @@
-{
-  inputs.nixos.url = "github:CHN-beta/nixos";
-  inputs.nixpkgs.url = "github:NixOS/nixpkgs/nixos-unstable";
-
-  outputs = inputs:
-    let
-      # pkgs = inputs.nixpkgs.legacyPackages.x86_64-linux;
-      pkgs = import inputs.nixpkgs
-      {
-        localSystem = { system = "x86_64-linux"; gcc = { arch = "alderlake"; tune = "alderlake"; }; };
-        config.allowUnfree = true;
-      };
-      localPackages = import "${inputs.nixos}/local/pkgs" { inherit pkgs; inherit (inputs.nixpkgs) lib; };
-    in
-    {
-      devShell.x86_64-linux = pkgs.mkShell.override { stdenv = pkgs.gcc13Stdenv; }
-      {
-        packages = with pkgs; [ pkg-config cmake ninja ];
-        buildInputs = (with pkgs; [ eigen yaml-cpp fmt highfive tbb_2021_8.dev glfw libGL ])
-          ++ (with localPackages; [ concurrencpp matplotplusplus zpp-bits glad ]);
-        hardeningDisable = [ "all" ];
-        # NIX_DEBUG = "1";
-      };
-    };
-}
--- a/include/ufo.hpp
+++ b/include/ufo.hpp
@@ -0,0 +1,104 @@
+# pragma once
+# include <biu.hpp>
+
+namespace ufo
+{
+  // 在相位中, 约定为使用 $\exp (2 \pi i \vec{q} \cdot \vec{r})$ 来表示原子的运动状态
+  //  (而不是 $\exp (-2 \pi i \vec{q} \cdot \vec{r})$)
+  // 一些书定义的倒格矢中包含了 $2 \pi$ 的部分, 我们这里约定不包含这部分.
+  //  也就是说, 正格子与倒格子的转置相乘, 得到单位矩阵.
+
+  using namespace biu::literals;
+  using namespace biu::stream_operators;
+
+  // 许多函数通用的一个结构体
+  struct CommonData
+  {
+    // 原胞相关信息，其中存储的信息是直接读入的，而不是反折叠后的结果
+    struct
+    {
+      // 晶胞，单位为埃，每行代表一个格矢
+      Eigen::Matrix3d Cell;
+      // 原子种类及其个数
+      std::vector<std::pair<std::string, std::size_t>> AtomType;
+      // 原子位置，单位为原胞格矢
+      Eigen::MatrixX3d AtomPosition;
+      // 单胞中每个 q 点的信息
+      struct QpointType
+      {
+        // q 点的坐标，单位为倒格矢
+        Eigen::Vector3d Qpoint;
+        struct ModeType
+        {
+          // 振动频率，单位为 THz
+          double Frequency;
+          // 振动模式，单位为埃
+          Eigen::MatrixX3cd EigenVector;
+          // 拉曼张量
+          // TODO: 单位是什么？
+          std::optional<double> WeightOnRaman;
+          // work around for fpr
+          std::optional<std::array<std::array<double, 3>, 3>> RamanTensor;
+          using serialize = zpp::bits::members<4>;
+        };
+        // 各个模式的的信息
+        std::vector<ModeType> Mode;
+        using serialize = zpp::bits::members<2>;
+      };
+      std::vector<QpointType> Qpoint;
+      using serialize = zpp::bits::members<4>;
+    } Primative;
+
+    // 超胞相关信息，包括反折叠后的信息
+    struct
+    {
+      // 超胞的晶胞，单位为埃，每行代表一个格矢
+      Eigen::Matrix3d Cell;
+      // 单胞与到超胞的变换
+      Eigen::Vector3i CellMultiplier;
+      Eigen::Matrix3d CellDeformation;
+      std::vector<std::pair<std::string, std::size_t>> AtomType;
+      Eigen::MatrixX3d AtomPosition;
+      std::optional<std::array<double, 3>> AtomTranslation;
+      struct QpointType
+      {
+        Eigen::Vector3d Qpoint;
+        std::vector<Eigen::Vector3d> SubQpoint;
+        struct ModeType
+        {
+          double Frequency;
+          Eigen::MatrixX3cd EigenVector;
+          std::vector<double> WeightOnUnfold;
+          std::optional<double> WeightOnSelectedAtom;
+          std::optional<double> WeightOnRaman;
+          std::optional<std::array<std::array<double, 3>, 3>> RamanTensor;
+          using serialize = zpp::bits::members<6>;
+        };
+        std::vector<ModeType> Mode;
+        using serialize = zpp::bits::members<3>;
+      };
+      std::vector<QpointType> Qpoint;
+      using serialize = zpp::bits::members<7>;
+    } Super;
+
+    // 选择的原子
+    std::optional<std::set<std::size_t>> SelectedAtom;
+
+    // 拉曼散射选择的偏振方向
+    std::optional<std::array<Eigen::Vector3d, 2>> RamanPolarization;
+
+    // 各种原子的质量
+    std::map<std::string, double> AtomMass;
+    using serialize = zpp::bits::members<5>;
+  };
+
+  void fold(std::string config_file);
+  void unfold(std::string config_file);
+  void project_to_atom(std::string config_file);
+  void project_to_mode(std::string config_file);
+  void plot_band(std::string config_file);
+  void plot_point(std::string config_file);
+  void raman_create_displacement(std::string config_file);
+  void raman_extract(std::string path);
+  void raman_apply_contribution(std::string config_file);
+}
--- a/include/ufo/fold.hpp
+++ b/include/ufo/fold.hpp
@@ -1,37 +0,0 @@
-# pragma once
-# include <ufo/solver.hpp>
-
-namespace ufo
-{
-  class FoldSolver : public Solver
-  {
-    public:
-      struct InputType
-      {
-        Eigen::Vector<unsigned, 3> SuperCellMultiplier;
-        std::optional<Eigen::Matrix<double, 3, 3>> SuperCellDeformation;
-        std::vector<Eigen::Vector3d> Qpoints;
-        DataFile OutputFile;
-
-        InputType(std::string config_file);
-      };
-      struct OutputType
-      {
-        std::vector<Eigen::Vector3d> Qpoints;
-        void write(std::string filename) const;
-      };
-    protected:
-      InputType Input_;
-      std::optional<OutputType> Output_;
-    public:
-      FoldSolver(std::string config_file);
-      FoldSolver& operator()() override;
-      // return value: QpointInReciprocalSuperCellByReciprocalSuperCell
-      static Eigen::Vector3d fold
-      (
-        Eigen::Vector3d qpoint_in_reciprocal_primitive_cell_by_reciprocal_primitive_cell,
-        Eigen::Vector<unsigned, 3> super_cell_multiplier,
-        std::optional<Eigen::Matrix<double, 3, 3>> super_cell_deformation
-      );
-  };
-}
--- a/include/ufo/plot.hpp
+++ b/include/ufo/plot.hpp
@@ -1,77 +0,0 @@
-# pragma once
-# include <ufo/unfold.hpp>
-
-namespace ufo
-{
-  class PlotSolver : public Solver
-  {
-    public:
-      struct InputType
-      {
-        Eigen::Matrix3d PrimativeCell;
-
-        struct FigureConfigType
-        {
-          std::vector<std::vector<Eigen::Vector3d>> Qpoints;
-          std::pair<unsigned, unsigned> Resolution;
-          std::pair<double, double> Range;
-          std::optional<std::vector<double>> YTicks;
-          DataFile PictureFile;
-          std::optional<std::vector<DataFile>> DataFiles;
-        };
-        std::vector<FigureConfigType> Figures;
-
-        struct UnfoldedDataType : public UnfoldSolver::OutputType
-        {
-          UnfoldedDataType(std::string filename);
-          UnfoldedDataType() = default;
-        };
-        DataFile UnfoldedDataFile;
-        UnfoldedDataType UnfoldedData;
-
-        InputType(std::string config_file);
-      };
-      struct OutputType
-      {
-        std::vector<std::vector<double>> Values;
-        std::vector<double> XTicks;
-        std::vector<double> YTicks;
-        std::pair<unsigned, unsigned> Resolution;
-        std::pair<double, double> Range;
-
-        OutputType() = default;
-        const OutputType& write(std::string filename, std::string format) const;
-        using serialize = zpp::bits::members<5>;
-      };
-    protected:
-      InputType Input_;
-      std::optional<std::vector<OutputType>> Output_;
-    public:
-      PlotSolver(std::string config_file);
-      PlotSolver& operator()() override;
-
-      // 根据 q 点路径, 搜索要使用的 q 点
-      static std::vector<std::reference_wrapper<const UnfoldSolver::OutputType::QpointDataType>> search_qpoints
-      (
-        const std::pair<Eigen::Vector3d, Eigen::Vector3d>& path,
-        const decltype(InputType::UnfoldedDataType::QpointData)& available_qpoints,
-        double threshold, bool exclude_endpoint = false
-      );
-      // 根据搜索到的 q 点, 计算每个点的数值
-      static std::tuple<std::vector<std::vector<double>>, std::vector<double>> calculate_values
-      (
-        const Eigen::Matrix3d primative_cell,
-        const std::vector<std::pair<Eigen::Vector3d, Eigen::Vector3d>>& path,
-        const std::vector<std::vector<std::reference_wrapper<const UnfoldSolver::OutputType::QpointDataType>>>& qpoints,
-        const decltype(InputType::FigureConfigType::Resolution)& resolution,
-        const decltype(InputType::FigureConfigType::Range)& range
-      );
-      // 根据数值, 画图
-      static void plot
-      (
-        const std::vector<std::vector<double>>& values,
-        const std::string& filename,
-        const std::vector<double>& x_ticks, const std::vector<double>& y_ticks
-      );
-  };
-}
--- a/include/ufo/solver.hpp
+++ b/include/ufo/solver.hpp
@@ -1,141 +0,0 @@
-# pragma once
-# include <iostream>
-# include <array>
-# include <numbers>
-# include <numeric>
-# include <fstream>
-# include <optional>
-# include <array>
-# include <utility>
-# include <execution>
-# include <syncstream>
-# include <any>
-# include <map>
-# include <vector>
-# include <span>
-# include <yaml-cpp/yaml.h>
-# include <Eigen/Dense>
-# include <concurrencpp/concurrencpp.h>
-# include <fmt/format.h>
-# include <fmt/std.h>
-# include <fmt/ranges.h>
-# include <highfive/H5File.hpp>
-# include <zpp_bits.h>
-# include <matplot/matplot.h>
-# include <matplot/backend/opengl.h>
-
-// 在相位中, 约定为使用 $\exp (2 \pi i \vec{q} \cdot \vec{r})$ 来表示原子的运动状态
-//  (而不是 $\exp (-2 \pi i \vec{q} \cdot \vec{r})$)
-// 一些书定义的倒格矢中包含了 $2 \pi$ 的部分, 我们这里约定不包含这部分.
-//  也就是说, 正格子与倒格子的转置相乘, 得到单位矩阵.
-
-namespace Eigen
-{
-  constexpr inline auto serialize(auto & archive, Eigen::Matrix3d& matrix)
-    { return archive(std::span(matrix.data(), matrix.size())); }
-  constexpr inline auto serialize(auto & archive, const Eigen::Matrix3d& matrix)
-    { return archive(std::span(matrix.data(), matrix.size())); }
-  constexpr inline auto serialize(auto & archive, Eigen::Vector3d& vector)
-    { return archive(std::span(vector.data(), vector.size())); }
-  constexpr inline auto serialize(auto & archive, const Eigen::Vector3d& vector)
-    { return archive(std::span(vector.data(), vector.size())); }
-}
-
-namespace ufo
-{
-  using namespace std::literals;
-  struct PhonopyComplex { double r, i; };
-  inline HighFive::CompoundType create_compound_complex()
-    { return {{ "r", HighFive::AtomicType<double>{}}, {"i", HighFive::AtomicType<double>{}}}; }
-
-	namespace detail_
-	{
-		template <typename T> struct SpecializationOfBitsMembersHelper : std::false_type {};
-		template <std::size_t N> struct SpecializationOfBitsMembersHelper<zpp::bits::members<N>> : std::true_type {};
-	}
-	template <typename T> concept ZppSerializable
-    = requires() { detail_::SpecializationOfBitsMembersHelper<T>::value == true; };
-
-  class Solver
-  {
-    public:
-      virtual Solver& operator()() = 0;
-      virtual ~Solver() = default;
-
-      static concurrencpp::generator<std::pair<Eigen::Vector<unsigned, 3>, unsigned>>
-        triplet_sequence(Eigen::Vector<unsigned, 3> range);
-
-      template <ZppSerializable T> inline static void zpp_write(const T& object, std::string filename)
-      {
-        auto [data, out] = zpp::bits::data_out();
-        out(object).or_throw();
-        static_assert(sizeof(char) == sizeof(std::byte));
-        std::ofstream file(filename, std::ios::binary | std::ios::out);
-        file.exceptions(std::ios::badbit | std::ios::failbit);
-        file.write(reinterpret_cast<const char*>(data.data()), data.size());
-      }
-      template <ZppSerializable T> inline static T zpp_read(std::string filename)
-      {
-        auto input = std::ifstream(filename, std::ios::binary | std::ios::in);
-        input.exceptions(std::ios::badbit | std::ios::failbit);
-        static_assert(sizeof(std::byte) == sizeof(char));
-        std::vector<std::byte> data;
-        {
-          std::vector<char> string(std::istreambuf_iterator<char>(input), {});
-          data.assign
-          (
-            reinterpret_cast<std::byte*>(string.data()),
-            reinterpret_cast<std::byte*>(string.data() + string.size())
-          );
-        }
-        auto in = zpp::bits::in(data);
-        T output;
-        in(output).or_throw();
-        return output;
-      }
-
-      class Hdf5file
-      {
-        public:
-          inline Hdf5file& open_for_read(std::string filename)
-          {
-            File_ = HighFive::File(filename, HighFive::File::ReadOnly);
-            return *this;
-          }
-          inline Hdf5file& open_for_write(std::string filename)
-          {
-            File_ = HighFive::File(filename, HighFive::File::ReadWrite | HighFive::File::Create
-              | HighFive::File::Truncate);
-            return *this;
-          }
-          template <typename T> inline Hdf5file& read(T& object, std::string name)
-          {
-            object = File_->getDataSet(name).read<std::remove_cvref_t<decltype(object)>>();
-            return *this;
-          }
-          template <typename T> inline Hdf5file& write(const T& object, std::string name)
-          {
-            File_->createDataSet(name, object);
-            return *this;
-          }
-        protected:
-          std::optional<HighFive::File> File_;
-      };
-
-      struct DataFile
-      {
-        std::string Filename;
-        std::string Format;
-        std::map<std::string, std::any> ExtraParameters;
-        inline DataFile() = default;
-        DataFile
-        (
-          YAML::Node node, std::set<std::string> supported_format,
-          std::string config_file, bool allow_same_as_config_file = false
-        );
-      };
-
-  };
-}
-
-HIGHFIVE_REGISTER_TYPE(ufo::PhonopyComplex, ufo::create_compound_complex)
--- a/include/ufo/unfold.hpp
+++ b/include/ufo/unfold.hpp
@@ -1,164 +0,0 @@
-# pragma once
-# include <ufo/solver.hpp>
-
-namespace ufo
-{
-  // 反折叠的原理: 将超胞中的原子运动状态, 投影到一组平面波构成的基矢中.
-  // 每一个平面波的波矢由两部分相加得到: 一部分是单胞倒格子的整数倍, 所取的个数有一定任意性, 论文中建议取大约单胞中原子个数那么多个;
-  //  对于没有缺陷的情况, 取一个应该就足够了.
-  // 另一部分是超胞倒格子的整数倍, 取 n 个, n 为超胞对应的单胞的倍数, 其实也就是倒空间中单胞对应倒格子中超胞的格点.
-  // 只要第一部分取得足够多, 那么单胞中原子的状态就可以完全被这些平面波描述.
-  // 将超胞中原子的运动状态投影到这些基矢上, 计算出投影的系数, 就可以将超胞的原子运动状态分解到单胞中的多个 q 点上.
-  class UnfoldSolver : public Solver
-  {
-    public:
-      struct InputType
-      {
-        // 单胞的三个格矢，每行表示一个格矢的坐标，单位为埃
-        Eigen::Matrix3d PrimativeCell;
-        // 单胞到超胞的格矢转换时用到的矩阵
-        // SuperCellMultiplier 是一个三维列向量且各个元素都是整数，表示单胞在各个方向扩大到多少倍之后，可以得到和超胞一样的体积
-        // SuperCsolver.hpp>mation 是一个行列式为 1 的矩阵，它表示经过 SuperCellMultiplier 扩大后，还需要怎样的变换才能得到超胞
-        // SuperCell = (SuperCellDeformation * SuperCellMultiplier.asDiagonal()) * PrimativeCell
-        // ReciprocalPrimativeCell = (SuperCellDeformation * SuperCellMultiplier.asDiagonal()).transpose()
-        //  * ReciprocalSuperCell
-        // Position = PositionToCell(line vector) * Cell
-        // InversePosition = InversePositionToCell(line vector) * ReciprocalCell
-        // PositionToSuperCell(line vector) * SuperCell = PositionToPrimativeCell(line vector) * PrimativeCell
-        // ReciprocalPositionToSuperCell(line vector) * ReciprocalSuperCell
-        //  = ReciprocalPositionToPrimativeCell(line vector) * ReciprocalPrimativeCell
-        Eigen::Vector<unsigned, 3> SuperCellMultiplier;
-        std::optional<Eigen::Matrix<double, 3, 3>> SuperCellDeformation;
-        // 在单胞内取几个平面波的基矢
-        Eigen::Vector<unsigned, 3> PrimativeCellBasisNumber;
-
-        // 从哪个文件读入 AtomPosition, 以及这个文件的格式, 格式可选值包括 "yaml"
-        DataFile AtomPositionInputFile;
-        // 从哪个文件读入 QpointData, 以及这个文件的格式, 格式可选值包括 "yaml" 和 "hdf5"
-        DataFile QpointDataInputFile;
-
-        // 超胞中原子的坐标，每行表示一个原子的坐标，单位为埃
-        Eigen::MatrixX3d AtomPosition;
-        // 关于各个 Q 点的数据
-        struct QpointDataType
-        {
-          // Q 点的坐标，单位为超胞的倒格矢
-          Eigen::Vector3d Qpoint;
-
-          // 关于这个 Q 点上各个模式的数据
-          struct ModeDataType
-          {
-            // 模式的频率，单位为 THz
-            double Frequency;
-            // 模式中各个原子的运动状态
-            // 这个数据是这样得到的: phonopy 输出的动态矩阵的 eigenvector 乘以 $\exp(-2 \pi i \vec q \cdot \vec r)$
-            // 这个数据可以认为是原子位移中, 关于超胞有周期性的那一部分, 再乘以原子质量的开方.
-            // 这个数据在读入后会被立即归一化.
-            Eigen::MatrixX3cd AtomMovement;
-          };
-          std::vector<ModeDataType> ModeData;
-        };
-        std::vector<QpointDataType> QpointData;
-
-        // 输出到哪些文件, 以及使用怎样的格式, 格式可选值包括:
-        // yaml: 使用 yaml 格式输出
-        // yaml-human-readable: 使用 yaml 格式输出, 但是输出的结果更适合人类阅读,
-        //  包括合并相近的模式, 去除权重过小的模式, 限制输出的小数位数.
-        // zpp: 使用 zpp-bits 序列化, 可以直接被 plot.cpp 读取
-        std::vector<DataFile> QpointDataOutputFile;
-
-        // 从文件中读取输入 (包括一个较小的配置文件, 和一个 hdf5 或者一个 yaml 文件), 文件中应当包含:
-        // 单胞的格矢: PrimativeCell 单位为埃 直接从 phonopy 的输出中复制
-        // 超胞的倍数: SuperCellMultiplier 手动输入, 为一个包含三个整数的数组
-        // 超胞的变形: SuperCellDeformation 手动输入, 为一个三阶方阵
-        // 平面波的基矢个数: PrimativeCellBasisNumber 手动输入, 为一个包含三个整数的数组
-        // 另外还有一个文件, 直接将 phonopy 的输出复制过来即可, 如果是 yaml, 应该包含下面的内容:
-        // 超胞中原子的坐标: points[*].coordinates 单位为超胞的格矢 直接从 phonopy 的输出中复制
-        // 各个 Q 点的坐标: phonon[*].q-position 单位为超胞的倒格子的格矢 直接从 phonopy 的输出中复制
-        // 各个模式的频率: phonon[*].band[*].frequency 单位为 THz 直接从 phonopy 的输出中复制
-        // 各个模式的原子运动状态: phonon[*].band[*].eigenvector 直接从 phonopy 的输出中复制
-        // 文件中可以有多余的项目, 多余的项目不管.
-        InputType(std::string filename);
-      };
-      struct OutputType
-      {
-        // 关于各个 Q 点的数据
-        struct QpointDataType
-        {
-          // Q 点的坐标，单位为单胞的倒格矢
-          Eigen::Vector3d Qpoint;
-
-          // 来源于哪个 Q 点, 单位为超胞的倒格矢
-          Eigen::Vector3d Source;
-          std::size_t SourceIndex_;
-
-          // 关于这个 Q 点上各个模式的数据
-          struct ModeDataType
-          {
-            // 模式的频率，单位为 THz
-            double Frequency;
-            // 模式的权重
-            double Weight;
-          };
-          std::vector<ModeDataType> ModeData;
-        };
-        std::vector<QpointDataType> QpointData;
-
-        void write(decltype(InputType::QpointDataOutputFile) output_files) const;
-        void write(std::string filename, std::string format, unsigned percision = 10) const;
-
-        using serialize = zpp::bits::members<1>;
-
-        virtual ~OutputType() = default;
-      };
-
-      // 第一层是不同的 sub qpoint, 第二层是单胞内不同的平面波
-      using BasisType = std::vector<std::vector<Eigen::VectorXcd>>;
-    protected:
-      InputType Input_;
-      std::optional<OutputType> Output_;
-      std::optional<BasisType> Basis_;
-
-      // 第一层是不同的模式, 第二层是不同的 sub qpoint
-      using ProjectionCoefficientType_ = std::vector<std::vector<double>>;
-
-    public:
-      UnfoldSolver(std::string config_file);
-      UnfoldSolver& operator()() override;
-
-      // 构建基
-      // 每个 q 点对应的一组 sub qpoint。不同的 q 点所对应的 sub qpoint 是不一样的，但 sub qpoint 与 q 点的相对位置一致。
-      // 这里 xyz_of_diff_of_sub_qpoint 即表示这个相对位置。
-      // 由于基只与这个相对位置有关（也就是说，不同 q 点的基是一样的），因此可以先计算出所有的基，这样降低计算量。
-      // 外层下标对应超胞倒格子的整数倍那部分(第二部分), 也就是不同的 sub qpoint
-      // 内层下标对应单胞倒格子的整数倍那部分(第一部分), 也就是 sub qpoint 上的不同平面波（取的数量越多，结果越精确）
-      static BasisType construct_basis
-      (
-        const decltype(InputType::PrimativeCell)& primative_cell,
-        const decltype(InputType::SuperCellMultiplier)& super_cell_multiplier,
-        const decltype(InputType::PrimativeCellBasisNumber)&
-          primative_cell_basis_number,
-        const decltype(InputType::AtomPosition)& atom_position
-      );
-
-      // 计算投影系数, 是反折叠的核心步骤
-      ProjectionCoefficientType_ construct_projection_coefficient
-      (
-        const BasisType& basis,
-        const std::vector<std::reference_wrapper<const decltype
-          (InputType::QpointDataType::ModeDataType::AtomMovement)>>& mode_data,
-        std::atomic<unsigned>& number_of_finished_modes
-      );
-
-      OutputType construct_output
-      (
-        const decltype(InputType::SuperCellMultiplier)& super_cell_multiplier,
-        const decltype(InputType::SuperCellDeformation)& super_cell_deformation,
-        const std::vector<std::reference_wrapper<const decltype
-          (InputType::QpointDataType::Qpoint)>>& meta_qpoint_by_reciprocal_super_cell,
-        const std::vector<std::vector<std::reference_wrapper<const decltype
-          (InputType::QpointDataType::ModeDataType::Frequency)>>>& frequency,
-        const ProjectionCoefficientType_& projection_coefficient
-      );
-  };
-}
--- a/src/fold.cpp
+++ b/src/fold.cpp
@@ -1,86 +1,56 @@
-# include <ufo/fold.hpp>
+# include <ufo.hpp>

-namespace ufo
+void ufo::fold(std::string config_file)
 {
-  FoldSolver::InputType::InputType(std::string config_file)
+  struct Config
  {
-    auto input = YAML::LoadFile(config_file);
-    for (unsigned i = 0; i < 3; i++)
-      SuperCellMultiplier(i) = input["SuperCellMultiplier"][i].as<unsigned>();
-    if (input["SuperCellDeformation"])
-    {
-      SuperCellDeformation.emplace();
-      for (unsigned i = 0; i < 3; i++)
-        for (unsigned j = 0; j < 3; j++)
-          (*SuperCellDeformation)(i, j) = input["SuperCellDeformation"][i][j].as<double>();
-    }
-    for (auto& qpoint : input["Qpoints"].as<std::vector<std::vector<double>>>())
-      Qpoints.push_back(Eigen::Vector3d
-        {{qpoint.at(0)}, {qpoint.at(1)}, {qpoint.at(2)}});
-    OutputFile = DataFile(input["OutputFile"], {"yaml"}, config_file);
-  }
-  void FoldSolver::OutputType::write(std::string filename) const
-  {
-    std::ofstream(filename) << [&]
-    {
-      std::stringstream print;
-      print << "Qpoints:\n";
-      for (auto& qpoint : Qpoints)
-        print << fmt::format("  - [ {:.8f}, {:.8f}, {:.8f} ]\n", qpoint(0), qpoint(1), qpoint(2));
-      return print.str();
-    }();
-  }
+    Eigen::Matrix3d SuperCellDeformation;
+    Eigen::Vector3i SuperCellMultiplier;
+    std::vector<Eigen::Vector3d> Qpoints;
+  };

-  FoldSolver::FoldSolver(std::string config_file) : Input_(config_file) {}
-  FoldSolver& FoldSolver::operator()()
-  {
-    if (!Output_)
-    {
-      Output_.emplace();
-      for (auto& qpoint : Input_.Qpoints)
-        Output_->Qpoints.push_back(fold
-        (
-          qpoint, Input_.SuperCellMultiplier,
-          Input_.SuperCellDeformation
-        ));
-    }
-    Output_->write(Input_.OutputFile.Filename);
-    return *this;
-  }
-
-  Eigen::Vector3d FoldSolver::fold
+  auto fold = []
  (
-    Eigen::Vector3d qpoint_in_reciprocal_primitive_cell_by_reciprocal_primitive_cell,
-    Eigen::Vector<unsigned, 3> super_cell_multiplier,
-    std::optional<Eigen::Matrix<double, 3, 3>> super_cell_deformation
-  )
+    Eigen::Matrix3d super_cell_deformation,
+    Eigen::Vector3i super_cell_multiplier,
+    Eigen::Vector3d qpoint_in_reciprocal_primitive_cell_by_reciprocal_primitive_cell
+  ) -> Eigen::Vector3d
  {
-    // 首先需要将 q 点转移到 ModifiedSuperCell 的倒格子中
-    // 将 q 点坐标扩大, 然后取小数部分, 就可以了
-    auto qpoint_by_reciprocal_modified_super_cell = super_cell_multiplier.cast<double>().asDiagonal()
-      * qpoint_in_reciprocal_primitive_cell_by_reciprocal_primitive_cell;
-    auto qpoint_in_reciprocal_modified_super_cell_by_reciprocal_modified_super_cell =
-      (qpoint_by_reciprocal_modified_super_cell.array() - qpoint_by_reciprocal_modified_super_cell.array().floor())
-        .matrix();
-    if (!super_cell_deformation)
-      return qpoint_in_reciprocal_modified_super_cell_by_reciprocal_modified_super_cell;
    /*
-      对 q 点平移数个 SupreCell, 直到它落在超胞的倒格子中
-      这等价于直接将 q 点坐标用 SuperCell 的倒格子表示, 然后取小数部分.
-      ModifiedSuperCell = SuperCellMultiplier * PrimativeCell
-      SuperCell = SuperCellDeformation * ModifiedSuperCell
-      ReciprocalModifiedSuperCell = ModifiedSuperCell.inverse().transpose()
-      ReciprocalSuperCell = SuperCell.inverse().transpose()
-      Qpoint = QpointByReciprocalModifiedSuperCell.transpose() * ReciprocalModifiedSuperCell
-      Qpoint = QpointByReciprocalSuperCell.transpose() * ReciprocalSuperCell
+      首先需要将 q 点坐标的单位转换为 ModifiedSuperCell 的格矢，可知：
+      QpointByReciprocalModifiedSuperCell =
+        SuperCellMultiplier.cast<double>().asDiagonal() * QpointByReciprocalPrimitiveCell;
+      接下来考虑将 q 点坐标的单位转换为 SuperCell 的格矢
+      ModifiedSuperCell = SuperCellMultiplier.transpose() * PrimativeCell;
+      SuperCell = SuperCellDeformation * ModifiedSuperCell;
+      ReciprocalModifiedSuperCell = ModifiedSuperCell.inverse().transpose();
+      ReciprocalSuperCell = SuperCell.inverse().transpose();
+      Qpoint = QpointByReciprocalModifiedSuperCell.transpose() * ReciprocalModifiedSuperCell;
+      Qpoint = QpointByReciprocalSuperCell.transpose() * ReciprocalSuperCell;
      整理可以得到:
-      QpointByReciprocalSuperCell = SuperCellDeformation * QpointByReciprocalModifiedSuperCell
+      QpointByReciprocalSuperCell = SuperCellDeformation * QpointByReciprocalModifiedSuperCell;
+      两个式子结合，可以得到：
+      QpointByReciprocalSuperCell =
+        SuperCellDeformation * SuperCellMultiplier.cast<double>().asDiagonal() * QpointByReciprocalPrimitiveCell;
    */
-    auto qpoint_in_reciprocal_modified_super_cell_by_reciprocal_super_cell =
-      (*super_cell_deformation * qpoint_in_reciprocal_modified_super_cell_by_reciprocal_modified_super_cell).eval();
-    auto qpoint_in_reciprocal_super_cell_by_reciprocal_super_cell =
-      qpoint_in_reciprocal_modified_super_cell_by_reciprocal_super_cell.array()
-      - qpoint_in_reciprocal_modified_super_cell_by_reciprocal_super_cell.array().floor();
-    return qpoint_in_reciprocal_super_cell_by_reciprocal_super_cell;
-  }
+    auto qpoint_in_reciprocal_primitive_cell_by_reciprocal_super_cell =
+    (
+      super_cell_deformation * super_cell_multiplier.cast<double>().asDiagonal()
+        * qpoint_in_reciprocal_primitive_cell_by_reciprocal_primitive_cell
+    ).eval();
+    /*
+      到目前为止，我们还没有移动过 q 点的坐标。现在，我们将它移动整数个 ReciprocalSuperCell，直到它落在超胞的倒格子中。
+      这等价于直接取 QpointByReciprocalSuperCell - QpointByReciprocalSuperCell.floor()。
+    */
+    return (qpoint_in_reciprocal_primitive_cell_by_reciprocal_super_cell.array()
+      - qpoint_in_reciprocal_primitive_cell_by_reciprocal_super_cell.array().floor()).matrix();
+  };
+
+  biu::Logger::Guard log(config_file);
+  auto input = YAML::LoadFile(config_file).as<Config>();
+  for (const auto& qpoint : input.Qpoints) log.info("{} -> {}"_f
+    (
+      qpoint,
+      fold(input.SuperCellDeformation, input.SuperCellMultiplier, qpoint)
+    ));
 }
--- a/src/main.cpp
+++ b/src/main.cpp
@@ -1,17 +1,18 @@
-# include <ufo/fold.hpp>
-# include <ufo/unfold.hpp>
-# include <ufo/plot.hpp>
+# include <ufo.hpp>

 int main(int argc, const char** argv)
 {
-  if (argc != 3)
-    throw std::runtime_error(fmt::format("Usage: {} task config.yaml", argv[0]));
-  if (argv[1] == std::string("fold"))
-    ufo::FoldSolver{argv[2]}();
-  else if (argv[1] == std::string("unfold"))
-    ufo::UnfoldSolver{argv[2]}();
-  else if (argv[1] == std::string("plot"))
-    ufo::PlotSolver{argv[2]}();
-  else
-    throw std::runtime_error(fmt::format("Unknown task: {}", argv[1]));
+  using namespace biu::literals;
+  if (argv[1] == "fold"s) ufo::fold(argv[2]);
+  else if (argv[1] == "unfold"s) ufo::unfold(argv[2]);
+  else if (argv[1] == "zpp-to-yaml"s) std::cout << YAML::Node(biu::deserialize<ufo::CommonData>
+    (biu::read<std::byte>(std::cin)));
+  else if (argv[1] == "project-to-atom"s) ufo::project_to_atom(argv[2]);
+  else if (argv[1] == "project-to-mode"s) ufo::project_to_mode(argv[2]);
+  else if (argv[1] == "raman-create-displacement"s) ufo::raman_create_displacement(argv[2]);
+  else if (argv[1] == "raman-extract"s) ufo::raman_extract(argv[2]);
+  else if (argv[1] == "raman-apply-contribution"s) ufo::raman_apply_contribution(argv[2]);
+  else if (argv[1] == "plot-band"s) ufo::plot_band(argv[2]);
+  else if (argv[1] == "plot-point"s) ufo::plot_point(argv[2]);
+  else throw std::runtime_error("Unknown task: {}"_f(argv[1]));
 }
--- a/src/plot.cpp
+++ b/src/plot.cpp
@@ -1,233 +1,179 @@
-# include <ufo/plot.hpp>
+# include <ufo.hpp>
+# include <matplot/matplot.h>
+# include <boost/container/flat_map.hpp>

-namespace ufo
+void ufo::plot_band(std::string config_file)
 {
-  PlotSolver::InputType::UnfoldedDataType::UnfoldedDataType(std::string filename)
+  struct Config
  {
-    static_cast<UnfoldSolver::OutputType&>(*this) = zpp_read<UnfoldSolver::OutputType>(filename);
-  }
+    std::string InputDataFile;
+    // 要画图的 q 点路径列表
+    // 内层表示一个路径上的 q 点，外层表示不同的路径
+    // 单位为倒格矢
+    std::vector<std::vector<Eigen::Vector3d>> Qpoints;
+    // 插值时使用的分辨率（不影响画出来图片的分辨率和横纵比）
+    std::array<std::size_t, 2> InterpolationResolution;
+    // 画图区域的y轴和x轴的比例。如果不指定，则由matplot++自动调整（通常调整为正方形，即 1）
+    std::optional<double> AspectRatio;
+    // 整张图片的分辨率
+    std::optional<std::array<std::size_t, 2>> PictureResolution;
+    // 画图的频率范围
+    std::array<double, 2> FrequencyRange;
+    // 搜索 q 点时的阈值，单位为埃^-1
+    std::optional<double> ThresholdWhenSearchingQpoints;
+    // 是否要在 y 轴上作一些标记
+    std::optional<std::vector<std::pair<double, std::string>>> YTicks;
+    // 是否输出图片
+    std::optional<std::string> OutputPictureFile;
+    // 是否输出数据，可以进一步使用 matplotlib 画图
+    std::optional<std::string> OutputDataFile;
+  };

-  PlotSolver::InputType::InputType(std::string config_file)
-  {
-    auto input = YAML::LoadFile(config_file);
-    for (unsigned i = 0; i < 3; i++)
-      for (unsigned j = 0; j < 3; j++)
-        PrimativeCell(i, j) = input["PrimativeCell"][i][j].as<double>();
-    for (auto& figure : input["Figures"].as<std::vector<YAML::Node>>())
-    {
-      Figures.emplace_back();
-      auto qpoints = figure["Qpoints"]
-        .as<std::vector<std::vector<std::vector<double>>>>();
-      for (auto& line : qpoints)
-      {
-        Figures.back().Qpoints.emplace_back();
-        for (auto& point : line)
-          Figures.back().Qpoints.back().emplace_back(point.at(0), point.at(1), point.at(2));
-        if (Figures.back().Qpoints.back().size() < 2)
-          throw std::runtime_error("Not enough points in a line");
-      }
-      if (Figures.back().Qpoints.size() < 1)
-        throw std::runtime_error("Not enough lines in a figure");
-      Figures.back().Resolution = figure["Resolution"].as<std::pair<unsigned, unsigned>>();
-      Figures.back().Range = figure["Range"].as<std::pair<double, double>>();
-      Figures.back().PictureFile
-        = DataFile(figure["PictureFile"], {"png"}, config_file);
-      if (figure["YTicks"])
-        Figures.back().YTicks = figure["YTicks"].as<std::vector<double>>();
-      if (figure["DataFiles"])
-      {
-        Figures.back().DataFiles.emplace();
-        for (auto& data_file : figure["DataFiles"].as<std::vector<YAML::Node>>())
-          Figures.back().DataFiles->emplace_back()
-            = DataFile(data_file, {"hdf5", "zpp"}, config_file);
-      }
-    }
-    UnfoldedDataFile = DataFile(input["UnfoldedDataFile"], {"zpp"}, config_file);
-    UnfoldedData = UnfoldedDataType(UnfoldedDataFile.Filename);
-  }
-  const PlotSolver::OutputType& PlotSolver::OutputType::write(std::string filename, std::string format) const
-  {
-    if (format == "zpp")
-      zpp_write(*this, filename);
-    else if (format == "hdf5")
-    {
-      std::vector resolution{ Resolution.first, Resolution.second };
-      std::vector range{ Range.first, Range.second };
-      Hdf5file{}.open_for_write(filename).write(Values, "Values")
-        .write(XTicks, "XTicks")
-        .write(YTicks, "YTicks")
-        .write(resolution, "Resolution")
-        .write(range, "Range");
-    }
-    return *this;
-  }
-
-  PlotSolver::PlotSolver(std::string config_file) : Input_(config_file) {}
-
-  PlotSolver& PlotSolver::operator()()
-  {
-    Output_.emplace();
-    for (auto& figure : Input_.Figures)
-    {
-      // 外层表示不同的线段的端点，内层表示这个线段上的 q 点
-      std::vector<std::vector<std::reference_wrapper<const UnfoldSolver::OutputType::QpointDataType>>> qpoints;
-      std::vector<std::pair<Eigen::Vector3d, Eigen::Vector3d>> lines;
-      for (auto& path : figure.Qpoints)
-        for (unsigned i = 0; i < path.size() - 1; i++)
-        {
-          lines.emplace_back(path[i], path[i + 1]);
-          qpoints.push_back(search_qpoints
-          (
-            lines.back(), Input_.UnfoldedData.QpointData,
-            0.001, i != path.size() - 2
-          ));
-        }
-      auto [values, x_ticks] = calculate_values
-      (
-        Input_.PrimativeCell, lines, qpoints, figure.Resolution, figure.Range
-      );
-      auto y_ticks = figure.YTicks.value_or(std::vector<double>{});
-      for (auto& _ : y_ticks)
-        _ = (_ - figure.Range.first) / (figure.Range.second - figure.Range.first) * figure.Resolution.second;
-      plot(values, figure.PictureFile.Filename, x_ticks, y_ticks);
-      Output_->emplace_back();
-      Output_->back().Values = std::move(values);
-      Output_->back().XTicks = std::move(x_ticks);
-      Output_->back().YTicks = std::move(y_ticks);
-      Output_->back().Resolution = figure.Resolution;
-      Output_->back().Range = figure.Range;
-      if (figure.DataFiles)
-        for (auto& data_file : *figure.DataFiles)
-          Output_->back().write(data_file.Filename, data_file.Format);
-    }
-    return *this;
-  }
-
-  std::vector<std::reference_wrapper<const UnfoldSolver::OutputType::QpointDataType>> PlotSolver::search_qpoints
+  // 根据 q 点路径, 搜索要使用的 q 点，返回的是超胞中 Qpint 的索引和 SubQpoint 的索引，以及到路径起点的距离，以及这段路径的总长度
+  auto search_qpoints = []
  (
+    const Eigen::Matrix3d& primative_cell,
    const std::pair<Eigen::Vector3d, Eigen::Vector3d>& path,
-    const decltype(InputType::UnfoldedDataType::QpointData)& available_qpoints,
-    double threshold, bool exclude_endpoint
+    const std::vector<std::vector<Eigen::Vector3d>>& qpoints,
+    double threshold, bool exclude_endpoint = false
  )
  {
-    std::multimap<double, std::reference_wrapper<const UnfoldSolver::OutputType::QpointDataType>> selected_qpoints;
    // 对于 output 中的每一个点, 检查这个点是否在路径上. 如果在, 把它加入到 selected_qpoints 中
-    for (auto& qpoint : available_qpoints)
-    {
-      // 计算三点围成的三角形的面积的两倍
-      auto area = (path.second - path.first).cross(qpoint.Qpoint - path.first).norm();
-      // 计算这个点到前两个点所在直线的距离
-      auto distance = area / (path.second - path.first).norm();
-      // 如果这个点到前两个点所在直线的距离小于阈值, 则认为这个点在路径上
-      if (distance < threshold)
+    // 键为这个点到起点的距离
+    boost::container::flat_map<double, std::pair<std::size_t, std::size_t>> selected_qpoints;
+    auto begin = (path.first.transpose() * primative_cell.reverse()).transpose().eval();
+    auto end = (path.second.transpose() * primative_cell.reverse()).transpose().eval();
+    for (std::size_t i = 0; i < qpoints.size(); i++) for (std::size_t j = 0; j < qpoints[i].size(); j++)
+      for (auto cell_shift
+        : biu::sequence(Eigen::Vector3i(-1, -1, -1), Eigen::Vector3i(2, 2, 2)))
      {
-        // 计算这个点到前两个点的距离, 两个距离都应该小于两点之间的距离
-        auto distance1 = (qpoint.Qpoint - path.first).norm();
-        auto distance2 = (qpoint.Qpoint - path.second).norm();
-        auto distance3 = (path.second - path.first).norm();
-        if (distance1 < distance3 + threshold && distance2 < distance3 + threshold)
-          // 如果这个点不在终点处, 或者不排除终点, 则加入
-          if (distance2 > threshold || !exclude_endpoint)
-            selected_qpoints.emplace(distance1, std::ref(qpoint));
+        Eigen::Vector3d qpoint
+          = primative_cell.reverse().transpose() * (qpoints[i][j] + cell_shift.first.cast<double>());
+        // 计算这个点到前两个点所在直线的距离
+        auto distance = (end - begin).cross(qpoint - begin).norm()
+          / (path.second - path.first).norm();
+        // 如果这个点到前两个点所在直线的距离小于阈值, 则认为这个点在这条直线上，但不一定在这两个点之间
+        if (distance < threshold)
+        {
+          // 计算这个点到前两个点的距离, 两个距离都应该小于两点之间的距离
+          auto distance1 = (qpoint - begin).norm();
+          auto distance2 = (qpoint - end).norm();
+          auto distance3 = (end - begin).norm();
+          if (distance1 < distance3 + threshold && distance2 < distance3 + threshold)
+            // 如果这个点不在终点处, 或者不排除终点, 则加入
+            if (distance2 > threshold || !exclude_endpoint)
+              selected_qpoints.emplace(distance1, std::pair{i, j});
+        }
      }
-    }
    // 去除非常接近的点
    for (auto it = selected_qpoints.begin(); it != selected_qpoints.end();)
    {
      auto next = std::next(it);
-      if (next == selected_qpoints.end())
-        break;
-      else if (next->first - it->first < threshold)
-        selected_qpoints.erase(next);
-      else
-        it = next;
+      if (next == selected_qpoints.end()) break;
+      else if (next->first - it->first < threshold) selected_qpoints.erase(next);
+      else it = next;
    }
-    if (selected_qpoints.empty())
-      throw std::runtime_error("No q points found");
-    std::vector<std::reference_wrapper<const UnfoldSolver::OutputType::QpointDataType>> result;
-    for (auto& qpoint : selected_qpoints)
-      result.push_back(qpoint.second);
-    return result;
-  }
+    if (selected_qpoints.empty()) throw std::runtime_error("No q points found");
+    return std::make_pair(selected_qpoints, (end - begin).norm());
+  };

-  std::tuple<std::vector<std::vector<double>>, std::vector<double>> PlotSolver::calculate_values
+  // 根据搜索到的 q 点, 计算图中每个点的值
+  auto calculate_values = []
  (
-    const Eigen::Matrix3d primative_cell,
-    const std::vector<std::pair<Eigen::Vector3d, Eigen::Vector3d>>& path,
-    const std::vector<std::vector<std::reference_wrapper<const UnfoldSolver::OutputType::QpointDataType>>>& qpoints,
-    const decltype(InputType::FigureConfigType::Resolution)& resolution,
-    const decltype(InputType::FigureConfigType::Range)& range
+    // search_qpoints 的第一个返回值
+    const boost::container::flat_map<double, std::pair<std::size_t, std::size_t>>& path,
+    // 每一条连续路径的第一个 q 点的索引
+    const std::set<std::size_t>& path_begin,
+    // 各个模式的频率和权重，几个维度分别为：MetaQpointIndex, ModeIndex
+    const std::vector<std::vector<double>>& frequency,
+    // 各个模式的权重，几个维度分别为：MetaQpointIndex, ModeIndex, SubQpointIndex
+    const std::vector<std::vector<std::vector<double>>>& weight,
+    // 用于插值的分辨率和范围
+    const std::array<std::size_t, 2>& resolution,
+    const std::array<double, 2>& frequency_range,
+    // 路径的总长度
+    double total_distance
  )
  {
-    // 整理输入
-    std::map<double, std::reference_wrapper<const UnfoldSolver::OutputType::QpointDataType>> qpoints_with_distance;
-    double total_distance = 0;
-    std::vector<double> x_ticks;
-    for (unsigned i = 0; i < path.size(); i++)
-    {
-      for (auto& _ : qpoints[i])
-        qpoints_with_distance.emplace
-        (
-          total_distance
-            + ((_.get().Qpoint - path[i].first).transpose() * primative_cell.inverse().transpose()).norm(),
-          _
-        );
-      total_distance += ((path[i].second - path[i].first).transpose() * primative_cell.inverse().transpose()).norm();
-      if (i != path.size() - 1)
-        x_ticks.push_back(total_distance);
-    }
-    for (auto& _ : x_ticks)
-      _ = _ / total_distance * resolution.first;
-
-    // 插值
-    std::vector<std::vector<double>> values;
-    auto blend = []
+    // 按比例混合两个 q 点的结果，得到可以用于画图的那一列数据
+    auto blend = [&]
    (
-      const UnfoldSolver::OutputType::QpointDataType& a,
-      const UnfoldSolver::OutputType::QpointDataType& b,
-      double ratio, unsigned resolution, std::pair<double, double> range
+      // 两个点的索引
+      std::pair<std::size_t, std::size_t> a, std::pair<std::size_t, std::size_t> b,
+      // 按照连续路径混合还是按照断开的路径混合
+      bool continuous,
+      // 第一个点占的比例
+      double ratio,
+      std::size_t resolution, std::array<double, 2> frequency_range
    ) -> std::vector<double>
    {
-      // 计算插值结果
-      std::vector<double> frequency, weight;
-      for (unsigned i = 0; i < a.ModeData.size(); i++)
+      // 混合得到的频率和权重
+      std::vector<double> frequency_result, weight_result;
+      // 如果是连续路径，将每个模式的频率和权重按照比例混合
+      if (continuous)
      {
-        frequency.push_back(a.ModeData[i].Frequency * ratio + b.ModeData[i].Frequency * (1 - ratio));
-        weight.push_back(a.ModeData[i].Weight * ratio + b.ModeData[i].Weight * (1 - ratio));
+        for (std::size_t i = 0; i < frequency[a.first].size(); i++)
+        {
+          frequency_result.push_back(frequency[a.first][i] * ratio + frequency[b.first][i] * (1 - ratio));
+          weight_result.push_back(weight[a.first][i][a.second] * ratio + weight[b.first][i][b.second] * (1 - ratio));
+        }
+      }
+      // 如果是不连续路径，将每个模式的权重乘以比例，最后相加
+      else
+      {
+        for (std::size_t i = 0; i < frequency[a.first].size(); i++)
+        {
+          frequency_result.push_back(frequency[a.first][i]);
+          weight_result.push_back(weight[a.first][i][a.second] * ratio);
+        }
+        for (std::size_t i = 0; i < frequency[b.first].size(); i++)
+        {
+          frequency_result.push_back(frequency[b.first][i]);
+          weight_result.push_back(weight[b.first][i][b.second] * (1 - ratio));
+        }
      }
      std::vector<double> result(resolution);
-      for (unsigned i = 0; i < frequency.size(); i++)
+      for (std::size_t i = 0; i < frequency_result.size(); i++)
      {
-        int index = (frequency[i] - range.first) / (range.second - range.first) * resolution;
-        if (index >= 0 && index < static_cast<int>(resolution))
-          result[index] += weight[i];
+        std::ptrdiff_t index = (frequency_result[i] - frequency_range[0]) / (frequency_range[1] - frequency_range[0])
+          * resolution;
+        if (index >= 0 && index < static_cast<std::ptrdiff_t>(resolution)) result[index] += weight_result[i];
      }
      return result;
    };
-    for (unsigned i = 0; i < resolution.first; i++)
+
+    std::vector<std::vector<double>> values;
+    for (std::size_t i = 0; i < resolution[0]; i++)
    {
-      auto current_distance = total_distance * i / resolution.first;
-      auto it = qpoints_with_distance.lower_bound(current_distance);
-      if (it == qpoints_with_distance.begin())
-        values.push_back(blend(it->second.get(), it->second.get(), 1, resolution.second, range));
-      else if (it == qpoints_with_distance.end())
-        values.push_back(blend(std::prev(it)->second.get(), std::prev(it)->second.get(), 1, resolution.second,
-          range));
-      else
-        values.push_back(blend
-        (
-          std::prev(it)->second.get(), it->second.get(),
-          (it->first - current_distance) / (it->first - std::prev(it)->first),
-          resolution.second, range)
-        );
+      auto current_distance = total_distance * i / resolution[0];
+      auto it = path.lower_bound(current_distance);
+      if (it == path.begin()) values.push_back(blend
+          (it->second, it->second, true, 1, resolution[1], frequency_range));
+      else if (it == path.end()) values.push_back(blend
+      (
+        std::prev(it)->second, std::prev(it)->second, true, 1,
+        resolution[1], frequency_range
+      ));
+      else values.push_back(blend
+      (
+        std::prev(it)->second, it->second,
+        !path_begin.contains(std::distance(path.begin(), it)),
+        (it->first - current_distance) / (it->first - std::prev(it)->first),
+        resolution[1], frequency_range
+      ));
    }
-    return {values, x_ticks};
-  }
-  void PlotSolver::plot
+    return values;
+  };
+
+  // 根据数值, 画图
+  auto plot = []
  (
    const std::vector<std::vector<double>>& values,
    const std::string& filename,
-    const std::vector<double>& x_ticks, const std::vector<double>& y_ticks
+    const std::vector<double>& x_ticks, const std::vector<double>& y_ticks,
+    const std::vector<std::string>& y_ticklabels,
+    const std::optional<double>& aspect_ratio,
+    const std::optional<std::array<std::size_t, 2>>& resolution
  )
  {
    std::vector<std::vector<double>>
@@ -235,32 +181,285 @@ namespace ufo
      g(values[0].size(), std::vector<double>(values.size(), 0)),
      b(values[0].size(), std::vector<double>(values.size(), 0)),
      a(values[0].size(), std::vector<double>(values.size(), 0));
-    for (unsigned i = 0; i < values[0].size(); i++)
-      for (unsigned j = 0; j < values.size(); j++)
+    for (std::size_t i = 0; i < values[0].size(); i++)
+      for (std::size_t j = 0; j < values.size(); j++)
      {
        auto v = values[j][i];
-        if (v < 0.05)
-          v = 0;
+        if (v < 0.05) v = 0;
        a[i][j] = v * 100 * 255;
-        if (a[i][j] > 255)
-          a[i][j] = 255;
+        if (a[i][j] > 255) a[i][j] = 255;
        r[i][j] = 255 - v * 2 * 255;
-        if (r[i][j] < 0)
-          r[i][j] = 0;
+        if (r[i][j] < 0) r[i][j] = 0;
        g[i][j] = 255 - v * 2 * 255;
-        if (g[i][j] < 0)
-          g[i][j] = 0;
+        if (g[i][j] < 0) g[i][j] = 0;
        b[i][j] = 255;
      }
-    auto f = matplot::figure<matplot::backend::gnuplot>(true);
+    auto f = matplot::figure(true);
    auto ax = f->current_axes();
    auto image = ax->image(std::tie(r, g, b));
    image->matrix_a(a);
    ax->y_axis().reverse(false);
    ax->x_axis().tick_values(x_ticks);
    ax->x_axis().tick_length(1);
+    ax->x_axis().ticklabels(std::vector<std::string>(x_ticks.size()));
    ax->y_axis().tick_values(y_ticks);
    ax->y_axis().tick_length(1);
+    ax->y_axis().ticklabels(y_ticklabels);
+    if (aspect_ratio)
+    {
+      ax->axes_aspect_ratio_auto(false);
+      ax->axes_aspect_ratio(*aspect_ratio);
+    }
+    if (resolution)
+    {
+      f->width((*resolution)[0]);
+      f->height((*resolution)[1]);
+    }
    f->save(filename, "png");
+  };
+
+  auto config = YAML::LoadFile(config_file).as<Config>();
+  auto input = biu::deserialize<CommonData>
+    (biu::read<std::byte>(config.InputDataFile));
+  
+  // 搜索画图需要用到的 q 点
+  // key 到起点的距离，value 为 q 点在 QpointData 中的索引
+  boost::container::flat_map<double, std::pair<std::size_t, std::size_t>> path;
+  // 每一条连续路径的第一个 q 点在 path 中的索引
+  std::set<std::size_t> path_begin;
+  // x 轴的刻度，为 path 中的索引
+  std::set<std::size_t> x_ticks_index;
+  double total_distance = 0;
+  for (auto& line : config.Qpoints)
+  {
+    assert(line.size() >= 2);
+    path_begin.insert(path.size());
+    for (std::size_t i = 0; i < line.size() - 1; i++)
+    {
+      x_ticks_index.insert(path.size());
+      auto [this_path, this_distance] = search_qpoints
+      (
+        input.Primative.Cell, {line[i], line[i + 1]},
+        input.Super.Qpoint
+          | ranges::views::transform([](auto& qpoint) { return qpoint.SubQpoint; })
+          | ranges::to_vector,
+        config.ThresholdWhenSearchingQpoints.value_or(0.001),
+        i != line.size() - 2
+      );
+      path.merge
+      (
+        this_path
+        | ranges::views::transform([&](auto& p)
+          { return std::make_pair(p.first + total_distance, p.second); })
+        | ranges::to<boost::container::flat_map>
+      );
+      total_distance += this_distance;
+    }
  }
+
+  // 计算画图的数据
+  auto values = calculate_values
+  (
+    path, path_begin,
+    input.Super.Qpoint
+      | ranges::views::transform([](auto& qpoint)
+      {
+        return qpoint.Mode | ranges::views::transform([](auto&& mode) { return mode.Frequency; }) | ranges::to_vector;
+      })
+      | ranges::to_vector,
+    input.Super.Qpoint
+      | ranges::views::transform([](auto& qpoint)
+      {
+        return qpoint.Mode
+          | ranges::views::transform([](auto&& mode)
+          {
+            return mode.WeightOnUnfold
+              | ranges::views::transform([&](auto&& weight)
+                { return weight * mode.WeightOnSelectedAtom.value_or(1) * mode.WeightOnRaman.value_or(1); })
+              | ranges::to_vector;
+          })
+          | ranges::to_vector;
+      })
+      | ranges::to_vector,
+    config.InterpolationResolution, config.FrequencyRange, total_distance
+  );
+  auto x_ticks = x_ticks_index | ranges::views::transform([&](auto i)
+    { return path.nth(i)->first / total_distance * config.InterpolationResolution[0]; }) | ranges::to_vector;
+  auto y_ticks = config.YTicks.value_or(std::vector<std::pair<double, std::string>>{})
+    | biu::toLvalue | ranges::views::keys
+    | ranges::views::transform([&](auto i)
+    {
+      return (i - config.FrequencyRange[0]) / (config.FrequencyRange[1] - config.FrequencyRange[0])
+        * config.InterpolationResolution[1];
+    })
+    | ranges::to_vector;
+  auto y_ticklabels = config.YTicks.value_or(std::vector<std::pair<double, std::string>>{})
+    | biu::toLvalue | ranges::views::values | ranges::to_vector;
+  if (config.OutputPictureFile) plot
+  (
+    values, config.OutputPictureFile.value(),
+    x_ticks, y_ticks, y_ticklabels, config.AspectRatio, config.PictureResolution
+  );
+  if (config.OutputDataFile)
+    biu::Hdf5file(config.OutputDataFile.value(), true)
+      .write("Values", values)
+      .write("XTicks", x_ticks)
+      .write("YTicks", y_ticks)
+      .write("YTickLabels", y_ticklabels)
+      .write("InterpolationResolution", config.InterpolationResolution)
+      .write("FrequencyRange", config.FrequencyRange);
+}
+
+void ufo::plot_point(std::string config_file)
+{
+  struct Config
+  {
+    std::string UnfoldedDataFile;
+    // 要画图的 q 点
+    Eigen::Vector3d Qpoint;
+    // 插值的分辨率
+    std::size_t InterpolationResolution;
+    std::optional<double> AspectRatio;
+    std::optional<std::array<std::size_t, 2>> PictureResolution;
+    // 画图的频率范围
+    std::array<double, 2> FrequencyRange;
+    // 搜索 q 点时的阈值，单位为埃^-1
+    std::optional<double> ThresholdWhenSearchingQpoints;
+    // 是否要在 z 轴上作一些标记
+    std::optional<std::vector<std::pair<double, std::string>>> XTicks;
+    // 是否输出图片
+    std::optional<std::string> OutputPictureFile;
+    // 是否输出插值后数据，可以进一步使用 matplotlib 画图
+    std::optional<std::string> OutputDataFile;
+    // 是否输出插值前数据，可以配合 phonopy 结果深入研究
+    std::optional<std::string> OutputRawDataFile;
+  };
+
+  // 根据 q 点路径, 搜索要使用的 q 点，返回的是 q 点在 QpointData 中的索引
+  auto search_qpoints = []
+  (
+    const Eigen::Matrix3d& primative_cell,
+    const Eigen::Vector3d& qpoint, const std::vector<std::vector<Eigen::Vector3d>>& qpoints,
+    double threshold
+  )
+  {
+    biu::Logger::Guard log(qpoint);
+    // 对于 output 中的每一个点, 检查这个点是否与所寻找的点足够近，如果足够近则返回
+    for (std::size_t i = 0; i < qpoints.size(); i++) for (std::size_t j = 0; j < qpoints[i].size(); j++)
+      for (auto cell_shift
+        : biu::sequence(Eigen::Vector3i(-1, -1, -1), Eigen::Vector3i(2, 2, 2)))
+      {
+        auto this_qpoint
+          = (primative_cell.reverse().transpose() * (qpoints[i][j] + cell_shift.first.cast<double>())).eval();
+        if ((this_qpoint - primative_cell.reverse().transpose() * qpoint).norm() < threshold)
+          return log.rtn(std::pair(i, j));
+      }
+    throw std::runtime_error("No q points found");
+  };
+
+  // 根据搜索到的 q 点, 计算图中每个点的值
+  auto calculate_values = []
+  (
+    // q 点的数据（需要用到它的频率和权重）
+    const std::vector<double>& frequency,
+    const std::vector<double>& weight,
+    // 用于插值的分辨率和范围
+    std::size_t resolution,
+    const std::array<double, 2>& frequency_range
+  )
+  {
+    biu::Logger::Guard log;
+    std::vector<double> result(resolution);
+    for (std::size_t i = 0; i < frequency.size(); i++)
+    {
+      double index_double = (frequency[i] - frequency_range[0]) / (frequency_range[1] - frequency_range[0])
+        * (resolution - 1);
+      std::ptrdiff_t index = std::round(index_double);
+      if (index >= 0 && index < static_cast<std::ptrdiff_t>(resolution)) result[index] += weight[i];
+    }
+    return log.rtn(result);
+  };
+
+  // 根据数值, 画图
+  auto plot = []
+  (
+    const std::vector<double>& values, const std::string& filename,
+    const std::vector<double>& x_ticks, const std::vector<std::string>& x_ticklabels,
+    const std::optional<double>& aspect_ratio, const std::optional<std::array<std::size_t, 2>>& resolution
+  )
+  {
+    biu::Logger::Guard log;
+    auto f = matplot::figure(true);
+    auto ax = f->current_axes();
+    auto image = ax->area(values, 0, false, "");
+    ax->y_axis().reverse(false);
+    ax->x_axis().tick_values(x_ticks);
+    ax->x_axis().tick_length(1);
+    ax->x_axis().ticklabels(x_ticklabels);
+    ax->y_axis().tick_values({});
+    if (aspect_ratio)
+    {
+      ax->axes_aspect_ratio_auto(false);
+      ax->axes_aspect_ratio(*aspect_ratio);
+    }
+    if (resolution)
+    {
+      f->width((*resolution)[0]);
+      f->height((*resolution)[1]);
+    }
+    f->save(filename, "png");
+  };
+
+  biu::Logger::Guard log;
+  auto config = YAML::LoadFile(config_file).as<Config>();
+  auto input = biu::deserialize<CommonData>
+    (biu::read<std::byte>(config.UnfoldedDataFile));
+  
+  auto qpoint_index = search_qpoints
+  (
+    input.Primative.Cell, config.Qpoint,
+    input.Super.Qpoint
+      | ranges::views::transform([](auto& qpoint) { return qpoint.SubQpoint; })
+      | ranges::to_vector,
+    config.ThresholdWhenSearchingQpoints.value_or(0.001)
+  );
+  auto values = calculate_values
+  (
+    input.Super.Qpoint[qpoint_index.first].Mode
+      | ranges::views::transform([](auto&& mode) { return mode.Frequency; })
+      | ranges::to_vector,
+    input.Super.Qpoint[qpoint_index.first].Mode
+      | ranges::views::transform([&](auto&& mode)
+      {
+        return mode.WeightOnUnfold[qpoint_index.second]
+          * mode.WeightOnSelectedAtom.value_or(1) * mode.WeightOnRaman.value_or(1);
+      })
+      | ranges::to_vector,
+    config.InterpolationResolution, config.FrequencyRange
+  );
+  auto x_ticks = config.XTicks.value_or(std::vector<std::pair<double, std::string>>{})
+    | biu::toLvalue | ranges::views::keys
+    | ranges::views::transform([&](auto i)
+    {
+      return (i - config.FrequencyRange[0]) / (config.FrequencyRange[1] - config.FrequencyRange[0])
+        * config.InterpolationResolution;
+    })
+    | ranges::to_vector;
+  auto x_ticklabels = config.XTicks.value_or(std::vector<std::pair<double, std::string>>{})
+    | biu::toLvalue | ranges::views::values | ranges::to_vector;
+  if (config.OutputPictureFile) plot
+  (
+    values, config.OutputPictureFile.value(),
+    x_ticks, x_ticklabels, config.AspectRatio, config.PictureResolution
+  );
+  if (config.OutputDataFile)
+    biu::Hdf5file(config.OutputDataFile.value(), true)
+      .write("Values", values)
+      .write("XTicks", x_ticks)
+      .write("XTickLabels", x_ticklabels)
+      .write("InterpolationResolution", config.InterpolationResolution)
+      .write("FrequencyRange", config.FrequencyRange);
+  // TODO: pfr + optional + Eigen Matrix = failed
+  if (config.OutputRawDataFile)
+    std::ofstream(*config.OutputRawDataFile) << YAML::Node(values);
 }
--- a/src/project-to-atom.cpp
+++ b/src/project-to-atom.cpp
@@ -0,0 +1,36 @@
+# include <ufo.hpp>
+# include <ranges>
+
+void ufo::project_to_atom(std::string config_file)
+{
+  struct Config
+  {
+    std::set<std::size_t> SelectedAtom;
+    std::string InputFile;
+    std::string OutputFile;
+  };
+
+  biu::Logger::Guard log(config_file);
+  auto config = YAML::LoadFile(config_file).as<Config>();
+  auto input = biu::deserialize<CommonData>(biu::read<std::byte>(config.InputFile));
+  input.SelectedAtom = config.SelectedAtom;
+  for (auto& qpoint : input.Super.Qpoint) for (auto& mode : qpoint.Mode)
+    mode.WeightOnSelectedAtom = mode.EigenVector.rowwise().squaredNorm().cwiseProduct
+    (
+      ranges::views::iota(0ul, input.Super.AtomPosition.rows() * 1ul)
+        | ranges::views::transform([&](auto i)
+          { return config.SelectedAtom.contains(i) ? 1. : 0.; })
+        | ranges::to_vector | biu::toEigen<>
+    ).sum() * (input.Super.AtomPosition.rows() * 1. / config.SelectedAtom.size());
+  std::ofstream(config.OutputFile, std::ios::binary) << biu::serialize<char>(input);
+  log.info("Summary:");
+  for (auto i_of_qpoint : std::views::iota(0ul, input.Super.Qpoint.size()))
+    for (auto i_of_mode : std::views::iota(0ul, input.Super.Qpoint[i_of_qpoint].Mode.size()))
+      if (*input.Super.Qpoint[i_of_qpoint].Mode[i_of_mode].WeightOnSelectedAtom > 0.1)
+        log.info("{}:{:.2f}:{}:{:.2f}"_f
+        (
+          i_of_qpoint, fmt::join(input.Super.Qpoint[i_of_qpoint].Qpoint, ", "),
+          i_of_mode, input.Super.Qpoint[i_of_qpoint].Mode[i_of_mode].Frequency,
+          *input.Super.Qpoint[i_of_qpoint].Mode[i_of_mode].WeightOnSelectedAtom
+        ));
+}
--- a/src/project-to-mode.cpp
+++ b/src/project-to-mode.cpp
@@ -0,0 +1,133 @@
+# include <ufo.hpp>
+
+void ufo::project_to_mode(std::string config_file)
+{
+  // 将选定的超胞中的某一个 q 点上的每一个模式到反折叠后的某个 q 点的投影，投射到单胞中的对应 q 点的模式上
+
+  struct Config
+  {
+    // 在单胞内取几个平面波的基矢
+    Eigen::Vector<std::size_t, 3> PrimativeCellBasisNumber;
+    // 要选定的超胞中的 q 点，sub qpoint，以及单胞中的 q 点
+    std::size_t SuperQpointIndex, SubQpointIndex, PrimativeQpointIndex;
+    // 输入输出文件的路径，直接输出 yaml，因为这些数据不再需要后处理
+    std::string InputDataFile, OutputFile;
+  };
+  struct Output
+  {
+    Eigen::Vector3d SuperQpoint, SubQpoint, PrimativeQpoint;
+    std::vector<std::vector<double>> Coefficient;
+  };
+
+  biu::Logger::Guard log(config_file);
+  auto config = YAML::LoadFile(config_file).as<Config>();
+  auto input = biu::deserialize<CommonData>
+    (biu::read<std::byte>(config.InputDataFile));
+  Output output
+  {
+    .SuperQpoint = input.Super.Qpoint[config.SuperQpointIndex].Qpoint,
+    .SubQpoint = input.Super.Qpoint[config.SuperQpointIndex].SubQpoint[config.SubQpointIndex],
+    .PrimativeQpoint = input.Primative.Qpoint[config.PrimativeQpointIndex].Qpoint,
+    .Coefficient = std::vector<std::vector<double>>(input.Super.Qpoint[config.SuperQpointIndex].Mode.size(),
+      std::vector<double>(input.Primative.Qpoint[config.PrimativeQpointIndex].Mode.size()))
+  };
+  if ((output.SubQpoint - output.PrimativeQpoint).norm() > 0.01)
+    log.error("sub qpoint {} != primative qpoint {}"_f(output.SubQpoint, output.PrimativeQpoint));
+
+  // 基在原胞中的表示
+  auto primative_basis = [&]
+  {
+    biu::Logger::Guard log;
+    std::vector<Eigen::VectorXcd> basis(config.PrimativeCellBasisNumber.array().prod());
+    for (auto [xyz_of_basis, i_of_basis]
+      : biu::sequence(config.PrimativeCellBasisNumber))
+    {
+      // 波矢就是 xyz_of_basis, 单位为单胞的倒格矢
+      // 将它的单位转换成埃^-1
+      auto wavevector =
+        (xyz_of_basis.transpose().cast<double>() * input.Primative.Cell.inverse().transpose()).transpose().eval();
+      log.debug("xyz_of_basis: {}"_f(xyz_of_basis));
+      log.debug("wavevector: {:.3f}"_f(fmt::join(wavevector, ", ")));
+      // 将原子坐标单位也转换为埃
+      auto atom_position = (input.Primative.AtomPosition * input.Primative.Cell).eval();
+      // 计算基矢
+      basis[i_of_basis] = (2i * std::numbers::pi_v<double> * (atom_position * wavevector)).array().exp();
+    }
+    return basis;
+  }();
+  // 基在超胞中的表示
+  auto super_basis = [&]
+  {
+    biu::Logger::Guard log;
+    std::vector<Eigen::VectorXcd> basis(config.PrimativeCellBasisNumber.array().prod());
+    auto diff_of_sub_qpoint_by_reciprocal_modified_super_cell = [&]
+    {
+      for
+      (
+        auto [diff_of_sub_qpoint_by_reciprocal_modified_super_cell, i_of_sub_qpoint]
+          : biu::sequence(input.Super.CellMultiplier)
+      )
+        if (i_of_sub_qpoint == config.SubQpointIndex) return diff_of_sub_qpoint_by_reciprocal_modified_super_cell;
+      std::unreachable();
+    }();
+    log.debug("diff_of_sub_qpoint_by_reciprocal_modified_super_cell: {}"_f
+      (diff_of_sub_qpoint_by_reciprocal_modified_super_cell));
+    for (auto [xyz_of_basis, i_of_basis]
+      : biu::sequence(config.PrimativeCellBasisNumber.cast<int>().eval()))
+    {
+      // 计算波矢, 单位为单胞的倒格矢
+      auto wavevector_by_reciprocal_primative_cell = xyz_of_basis.cast<double>()
+        + input.Super.CellMultiplier.cast<double>().cwiseInverse().asDiagonal()
+        * diff_of_sub_qpoint_by_reciprocal_modified_super_cell.cast<double>();
+      // 将单位转换为埃^-1
+      auto wavevector = input.Primative.Cell.inverse() * wavevector_by_reciprocal_primative_cell;
+      log.debug("wavevector: {}"_f(wavevector));
+      // 将原子坐标单位也转换为埃
+      auto atom_translation =
+        (input.Super.AtomTranslation.value_or(std::array{0., 0., 0.}) | biu::toEigen<>)
+        .transpose().replicate(input.Super.AtomPosition.rows(), 1).eval();
+      Eigen::MatrixX3d atom_position = (input.Super.AtomPosition - atom_translation)
+        * (input.Super.CellDeformation * input.Super.CellMultiplier.cast<double>().asDiagonal() * input.Primative.Cell);
+      // 计算基矢
+      basis[i_of_basis] = (2i * std::numbers::pi_v<double> * (atom_position * wavevector)).array().exp();
+    }
+    return basis;
+  }();
+  // 将所有模式投影到基矢上
+  auto primative_projection_coefficient =
+    input.Primative.Qpoint[config.PrimativeQpointIndex].Mode
+      | ranges::views::transform([&](const auto& mode)
+        {
+          return primative_basis
+            | ranges::views::transform([&](const auto& basis)
+              { return (basis.transpose().conjugate() * mode.EigenVector).eval() | biu::fromEigen; })
+            | ranges::to_vector
+            | biu::toEigen<>;
+        })
+      | ranges::to_vector;
+  auto super_projection_coefficient =
+    input.Super.Qpoint[config.SuperQpointIndex].Mode
+      | ranges::views::transform([&](const auto& mode)
+        {
+          return super_basis
+            | ranges::views::transform([&](const auto& basis)
+              { return (basis.transpose().conjugate() * mode.EigenVector).eval() | biu::fromEigen; })
+            | ranges::to_vector
+            | biu::toEigen<>;
+        })
+      | ranges::to_vector;
+  // 将它们互相投影，得到结果
+  for (auto [i_of_super_mode, super_mode] : ranges::views::enumerate(super_projection_coefficient))
+  {
+    for (auto [i_of_primative_mode, primative_mode]
+      : ranges::views::enumerate(primative_projection_coefficient))
+      output.Coefficient[i_of_super_mode][i_of_primative_mode] =
+        std::norm((super_mode.transpose().conjugate() * primative_mode).trace());
+    auto sum = ranges::accumulate(output.Coefficient[i_of_super_mode], 0.);
+    for (auto& coefficient : output.Coefficient[i_of_super_mode])
+      coefficient *=
+        input.Super.Qpoint[config.SuperQpointIndex].Mode[i_of_super_mode].WeightOnUnfold[config.SubQpointIndex] / sum;
+  }
+  // 输出
+  std::ofstream(config.OutputFile) << YAML::Node(output);
+}
--- a/src/raman.cpp
+++ b/src/raman.cpp
@@ -0,0 +1,197 @@
+# include <ufo.hpp>
+
+namespace ufo
+{
+  struct RamanData
+  {
+    std::map<std::pair<std::size_t, std::size_t>, double> ModeRatio;
+    double MaxDisplacement;
+    enum { Primative, Super } Cell;
+    using serialize = zpp::bits::members<3>;
+  };
+
+  void raman_create_displacement(std::string config_file)
+  {
+    struct Config
+    {
+      // 要计算的是原胞还是超胞
+      decltype(RamanData::Cell) Cell;
+      // 要计算哪个 q 点的哪些模式，总是假定是 gamma 点的模式
+      std::map<std::size_t, std::set<std::size_t>> SelectedModes;
+      // 原子最大位移大小，单位为埃
+      double MaxDisplacement;
+      // 输出的POSCAR所在的目录
+      std::string OutputPoscarDirectory;
+      // 输入的数据文件名
+      std::string InputDataFile;
+      std::string OutputDataFile;
+    };
+
+    auto generate_poscar = []
+    (
+      Eigen::Matrix3d SuperCell, Eigen::MatrixX3d AtomPosition,
+      std::vector<std::pair<std::string, std::size_t>> AtomType
+    )
+    {
+      std::stringstream ss;
+      ss << "some random comment to make VASP happy\n1.0\n";
+      for (std::size_t i = 0; i < 3; i++)
+      {
+        for (std::size_t j = 0; j < 3; j++) ss << SuperCell(i, j) << " ";
+        ss << std::endl;
+      }
+      ss << "{}\n"_f(ranges::accumulate
+      (
+        AtomType | ranges::views::transform([](auto&& atom) { return atom.first; }),
+        ""s, [](auto&& a, auto&& b) { return a + " " + b; }
+      ));
+      ss << "{}\n"_f(ranges::accumulate
+      (
+        AtomType | ranges::views::transform([](auto&& atom) { return atom.second; }),
+        ""s, [](auto&& a, auto&& b) { return a + " " + std::to_string(b); }
+      ));
+      ss << "Direct\n";
+      for (const auto& position : AtomPosition.rowwise())
+      {
+        for (std::size_t i = 0; i < 3; i++) ss << position(i) << " ";
+        ss << std::endl;
+      }
+      return ss.str();
+    };
+
+    biu::Logger::Guard log(config_file);
+    auto config = YAML::LoadFile(config_file).as<Config>();
+    auto input = biu::deserialize<CommonData>
+      (biu::read<std::byte>(config.InputDataFile));
+    RamanData output;
+    output.MaxDisplacement = config.MaxDisplacement;
+    output.Cell = config.Cell;
+
+    auto process = [&](auto& cell)
+    {
+      auto mass = cell.AtomType
+        | ranges::views::transform([&](auto&& atom)
+          { return ranges::views::repeat_n(input.AtomMass[atom.first], atom.second); })
+        | ranges::views::join | ranges::to_vector | biu::toEigen<>;
+      for (auto i_of_qpoint : config.SelectedModes | ranges::views::keys)
+        for (auto i_of_mode : config.SelectedModes[i_of_qpoint])
+        {
+          // 假定虚部总是为零
+          auto move_eigenvector = cell.Qpoint[i_of_qpoint].Mode[i_of_mode].EigenVector.real()
+            .cwiseProduct(mass.cwiseSqrt().cwiseInverse().rowwise().replicate(3)).eval();
+          // 归一化
+          auto ratio = config.MaxDisplacement / move_eigenvector.rowwise().norm().maxCoeff();
+          auto atom_movement = (move_eigenvector * ratio).eval();
+          // 输出
+          for (auto direction : {1, -1})
+          {
+            auto path = "{}/{}/{}/{}"_f
+              (config.OutputPoscarDirectory, i_of_qpoint, i_of_mode, direction > 0 ? "+" : "-");
+            std::filesystem::create_directories(path);
+            std::ofstream("{}/POSCAR"_f(path)) << generate_poscar
+              (cell.Cell, cell.AtomPosition + atom_movement * cell.Cell.inverse() * direction, cell.AtomType);
+          }
+          output.ModeRatio[{i_of_qpoint, i_of_mode}] = ratio;
+          log.debug("Write mode {} {} {}"_f(i_of_qpoint, i_of_mode, atom_movement.rowwise().norm().eval()));
+        }
+    };
+    if (config.Cell == RamanData::Primative) process(input.Primative);
+    else process(input.Super);
+
+    std::filesystem::create_directories("{}/{}"_f(config.OutputPoscarDirectory, "origin"));
+    std::ofstream("{}/origin/POSCAR"_f(config.OutputPoscarDirectory)) << generate_poscar
+      (input.Super.Cell, input.Super.AtomPosition, input.Super.AtomType);
+    std::ofstream(config.OutputDataFile, std::ios::binary) << biu::serialize<char>(output);
+  }
+
+  void raman_extract(std::string path)
+  {
+    biu::Logger::Guard log(path);
+    auto get_dielectric_tensor = [](std::filesystem::path file)
+    {
+      biu::Logger::Guard log(file);
+      auto in_stream = std::ifstream(file);
+      std::string line;
+      // search line containing: MACROSCOPIC STATIC DIELECTRIC TENSOR
+      while (std::getline(in_stream, line))
+      {
+        if (line.find("MACROSCOPIC STATIC DIELECTRIC TENSOR") != std::string::npos)
+        {
+          log.debug("find in {}"_f(file));
+          // skip 1 line
+          std::getline(in_stream, line);
+          Eigen::Matrix3d dielectric_tensor;
+          for (std::size_t i = 0; i < 3; i++) for (std::size_t j = 0; j < 3; j++)
+            in_stream >> dielectric_tensor(i, j);
+          log.debug("read tensor {}"_f(dielectric_tensor));
+          return dielectric_tensor;
+        }
+      }
+      // test if the file is read correctly
+      throw std::runtime_error("Error reading file: {}"_f(file));
+    };
+    auto search_path = [&](this auto self, std::size_t indent, std::string path) -> void
+    {
+      if (std::filesystem::exists(path + "/OUTCAR"))
+      {
+        auto e = get_dielectric_tensor(path + "/OUTCAR");
+        for (std::size_t i = 0; i < 3; i++) std::cout << "{}- [ {}, {}, {} ]\n"_f
+          (std::string(indent * 2, ' '), e(i, 0), e(i, 1), e(i, 2));
+      }
+      else for (auto entry : std::filesystem::directory_iterator(path)) if (entry.is_directory())
+      {
+        std::cout << "{}{}:\n"_f
+        (
+          std::string(indent * 2, ' '),
+          (std::set{"+"s, "-"s}.contains(entry.path().filename()))
+            ? "\"{}\""_f(entry.path().filename()) : entry.path().filename().string()
+        );
+        self(indent + 1, entry.path());
+      }
+    };
+    search_path(0, path);
+  }
+
+  void raman_apply_contribution(std::string config_file)
+  {
+    struct Config
+    {
+      Eigen::Matrix3d OriginalSusceptibility;
+      std::map<std::size_t, std::map<std::size_t, std::map<std::string, Eigen::Matrix3d>>> Susceptibility;
+      std::array<Eigen::Vector3d, 2> Polarization;
+      std::string InputDataFile;
+      std::string RamanInputDataFile;
+      std::string OutputDataFile;
+    };
+
+    biu::Logger::Guard log(config_file);
+    auto config = YAML::LoadFile(config_file).as<Config>();
+    auto input = biu::deserialize<CommonData>
+      (biu::read<std::byte>(config.InputDataFile));
+    auto raman_input = biu::deserialize<RamanData>
+      (biu::read<std::byte>(config.RamanInputDataFile));
+
+    input.RamanPolarization = config.Polarization;
+    auto process = [&](auto& cell)
+    {
+      for (auto&& [i, ratio] : raman_input.ModeRatio)
+      {
+        auto&& [i_of_qpoint, i_of_mode] = i;
+        auto&& _ = cell.Qpoint[i_of_qpoint].Mode[i_of_mode];
+        auto&& susceptibility = config.Susceptibility[i_of_qpoint][i_of_mode];
+        Eigen::Matrix3d raman_tensor = (susceptibility["+"] - susceptibility["-"]) / 2 / ratio;
+        _.RamanTensor = raman_tensor | biu::fromEigen;
+        _.WeightOnRaman = config.Polarization[0].transpose() * raman_tensor * config.Polarization[1];
+        log.info("{}:{:.2f}:{}:{:.2f} {}"_f
+        (
+          i_of_qpoint, fmt::join(cell.Qpoint[i_of_qpoint].Qpoint, ", "),
+          i_of_mode, _.Frequency, *_.WeightOnRaman
+        ));
+      }
+    };
+    if (raman_input.Cell == RamanData::Primative) process(input.Primative);
+    else process(input.Super);
+
+    std::ofstream(config.OutputDataFile, std::ios::binary) << biu::serialize<char>(input);
+  }
+}
--- a/src/solver.cpp
+++ b/src/solver.cpp
@@ -1,47 +0,0 @@
-# include <ufo/solver.hpp>
-
-namespace ufo
-{
-  concurrencpp::generator<std::pair<Eigen::Vector<unsigned, 3>, unsigned>> Solver::triplet_sequence
-    (Eigen::Vector<unsigned, 3> range)
-  {
-    for (unsigned x = 0; x < range[0]; x++)
-      for (unsigned y = 0; y < range[1]; y++)
-        for (unsigned z = 0; z < range[2]; z++)
-          co_yield
-          {
-            Eigen::Vector<unsigned, 3>{{x}, {y}, {z}},
-            x * range[1] * range[2] + y * range[2] + z
-          };
-  }
-
-  Solver::DataFile::DataFile
-    (YAML::Node node, std::set<std::string> supported_format, std::string config_file, bool allow_same_as_config_file)
-  {
-    if (auto _ = node["SameAsConfigFile"])
-    {
-      auto __ = _.as<bool>();
-      if (__ && !allow_same_as_config_file)
-        throw std::runtime_error("\"SameAsConfigFile: true\" is not allowed here.");
-      ExtraParameters["SameAsConfigFile"] = __;
-      if (__)
-      {
-        Filename = config_file;
-        Format = "yaml";
-        return;
-      }
-    }
-    Filename = node["Filename"].as<std::string>();
-    Format = node["Format"].as<std::string>();
-    if (!supported_format.contains(Format))
-      throw std::runtime_error(fmt::format("Unsupported format: \"{}\"", Format));
-    if (auto _ = node["RelativeToConfigFile"])
-    {
-      auto __ = _.as<bool>();
-      ExtraParameters["RelativeToConfigFile"] = __;
-      if (__)
-        Filename = std::filesystem::path(config_file).parent_path() / Filename;
-    }
-  };
-
-}
--- a/src/unfold.cpp
+++ b/src/unfold.cpp
@@ -1,429 +1,310 @@
-# include <ufo/unfold.hpp>
+# include <ufo.hpp>
+# include <thread>
+# include <syncstream>
+# include <execution>
+# include <ranges>

-namespace ufo
+void ufo::unfold(std::string config_file)
 {
-  UnfoldSolver::InputType::InputType(std::string filename)
+  // 反折叠的原理: 将超胞中的原子运动状态, 投影到一组平面波构成的基矢中.
+  // 每一个平面波的波矢由两部分相加得到: 一部分是单胞倒格子的整数倍, 所取的个数有一定任意性, 论文中建议取大约单胞中原子个数那么多个，
+  // 但我觉得可以多取一些；这些平面波以原胞为周期，它用于尽可能描述
+  // 另一部分是超胞倒格子的整数倍, 取 n 个, n 为超胞对应的单胞的倍数, 其实也就是倒空间中单胞对应倒格子中超胞的格点.
+  // 只要第一部分取得足够多, 那么单胞中原子的状态就可以完全被这些平面波描述.
+  // 将超胞中原子的运动状态投影到这些基矢上, 计算出投影的系数, 就可以将超胞的原子运动状态分解到单胞中的多个 q 点上.
+
+  struct Config
  {
-    // read main input file
+    // 单胞到超胞的格矢转换时用到的矩阵
+    // SuperCellMultiplier 是一个三维列向量且各个元素都是整数，表示单胞在各个方向扩大到多少倍之后，可以得到和超胞一样的体积
+    // SuperCellDeformation 是一个行列式为 1 的矩阵，它表示经过 SuperCellMultiplier 扩大后，还需要怎样的变换才能得到超胞
+    // SuperCell = (SuperCellDeformation * SuperCellMultiplier.asDiagonal()) * PrimativeCell
+    // ReciprocalPrimativeCell = (SuperCellDeformation * SuperCellMultiplier.asDiagonal()).transpose()
+    //  * ReciprocalSuperCell
+    // Position = PositionToCell(line vector) * Cell
+    // InversePosition = InversePositionToCell(line vector) * ReciprocalCell
+    // PositionToSuperCell(line vector) * SuperCell = PositionToPrimativeCell(line vector) * PrimativeCell
+    // ReciprocalPositionToSuperCell(line vector) * ReciprocalSuperCell
+    //  = ReciprocalPositionToPrimativeCell(line vector) * ReciprocalPrimativeCell
+    Eigen::Vector3i SuperCellMultiplier;
+    Eigen::Matrix3d SuperCellDeformation;
+    std::optional<std::array<double, 3>> AtomTranslation;
+
+    // 在单胞内取几个平面波的基矢
+    Eigen::Vector<std::size_t, 3> PrimativeCellBasisNumber;
+
+    // 单胞的 phonopy 输出的 phonopy.yaml，用来读入单胞的晶格、原子坐标、原子类型、原子质量
+    std::string PrimativePhonopy;
+    // 单胞的 phonopy 输出的 band.hdf5 或 qpoint.hdf5，用来读入 q 点和振动模式
+    std::string PrimativeQpoint;
+    // 同上，但是是超胞里的结果
+    std::string SuperPhonopy;
+    std::string SuperQpoint;
+
+    std::string OutputFile;
+  };
+
+  // 从文件中读取 q 点数据
+  // data 为 CommonData::Primative 或 CommonData::Super
+  // 返回值为原子类型和原子质量的对应关系
+  auto read_qpoint = [](std::string phonopy_file, std::string qpoint_file, auto& data)
+  {
+    biu::Logger::Guard log(phonopy_file, qpoint_file, data);
+
+    // phonopy 的输出有两种可能。
+    // 直接指定计算的 q 点时，frequency 是 2 维，这时第一个维度是 q 点，第二个维度是不同模式。
+    // 计算能带时，frequency 是 3 维，相比于二维的情况多了第一个维度，表示 q 点所在路径。
+    // qpoint 或 path，以及 eigenvector 也有类似的变化。
+    // 除此以外，eigenvector 后两个维度分别指示模式的特征向量的各个维度和各个模式（而不是各个模式和特征向量的各个维度），
+    // 因为后两个维度的尺寸总是一样的（模式个数等于原子坐标个数），非常容易搞错。
+    std::vector<std::array<double, 3>> qpoint;
+    std::vector<std::vector<double>> frequency;
+    std::vector<std::vector<std::vector<std::complex<double>>>> eigenvector_vector;
+    auto file = biu::Hdf5file(qpoint_file);
+
+    if (file.File.getDataSet("/frequency").getDimensions().size() == 2)
+      file.read("/frequency", frequency)
+        .read("/eigenvector", eigenvector_vector)
+        .read("/qpoint", qpoint);
+    else
    {
-      auto node = YAML::LoadFile(filename);
-        for (unsigned i = 0; i < 3; i++)
-          for (unsigned j = 0; j < 3; j++)
-            PrimativeCell(i, j) = node["PrimativeCell"][i][j].as<double>();
+      std::vector<std::vector<std::array<double, 3>>> temp_path;
+      std::vector<std::vector<std::vector<double>>> temp_frequency;
+      std::vector<std::vector<std::vector<std::vector<std::complex<double>>>>> temp_eigenvector_vector;
+      file.read("/frequency", temp_frequency)
+        .read("/eigenvector", temp_eigenvector_vector)
+        .read("/path", temp_path);
+      frequency = temp_frequency | ranges::views::join | ranges::to_vector;
+      qpoint = temp_path | ranges::views::join | ranges::to_vector;
+      eigenvector_vector = temp_eigenvector_vector | ranges::views::join | ranges::to_vector;
+    }

-      for (unsigned i = 0; i < 3; i++)
-        SuperCellMultiplier(i) = node["SuperCellMultiplier"][i].as<int>();
-
-      if (auto value = node["SuperCellDeformation"])
+    // 整理并写入得到结果
+    auto number_of_qpoints = frequency.size(), number_of_modes = frequency[0].size();
+    data.Qpoint.resize(number_of_qpoints);
+    for (auto i : std::views::iota(0u, number_of_qpoints)) 
+    {
+      data.Qpoint[i].Qpoint = qpoint[i] | biu::toEigen<>;
+      data.Qpoint[i].Mode.resize(number_of_modes);
+      for (auto j : std::views::iota(0u, number_of_modes)) 
      {
-        SuperCellDeformation.emplace();
-        for (unsigned i = 0; i < 3; i++)
-          for (unsigned j = 0; j < 3; j++)
-            (*SuperCellDeformation)(i, j) = value[i][j].as<double>();
-      }
-
-      for (unsigned i = 0; i < 3; i++)
-        PrimativeCellBasisNumber(i) = node["PrimativeCellBasisNumber"][i].as<int>();
-
-      AtomPositionInputFile = DataFile
-      (
-        node["AtomPositionInputFile"], {"yaml"},
-        filename, true
-      );
-      QpointDataInputFile = DataFile
-      (
-        node["QpointDataInputFile"], {"yaml", "hdf5"},
-        filename, true
-      );
-      if (auto value = node["QpointDataOutputFile"])
-      {
-        QpointDataOutputFile.resize(value.size());
-        for (unsigned i = 0; i < value.size(); i++)
-          QpointDataOutputFile[i] = DataFile
-          (
-            value[i], {"yaml", "yaml-human-readable", "zpp", "hdf5"},
-            filename, false
-          );
+        data.Qpoint[i].Mode[j].Frequency = frequency[i][j];
+        auto number_of_atoms = number_of_modes / 3;
+        Eigen::MatrixX3cd eigenvector(number_of_atoms, 3);
+        for (auto k : std::views::iota(0u, number_of_atoms))
+          for (auto l : std::views::iota(0u, 3u))
+            eigenvector(k, l) = eigenvector_vector[i][k * 3 + l][j];
+        // 原则上讲，需要对读入的原子运动状态作相位转换, 使得它们与我们的约定一致(对超胞周期性重复)，但这个转换 phonopy 已经做了
+        // 这里还要需要做归一化处理 (指将数据简单地作为向量处理的归一化)
+        data.Qpoint[i].Mode[j].EigenVector = eigenvector / eigenvector.norm();
      }
    }

-    if (AtomPositionInputFile.Format == "yaml")
-    {
-      auto node = YAML::LoadFile(AtomPositionInputFile.Filename);
-      std::vector<YAML::Node> points;
-      if (auto _ = node["points"])
-        points = _.as<std::vector<YAML::Node>>();
-      else
-        points = node["unit_cell"]["points"].as<std::vector<YAML::Node>>();
-      auto atom_position_to_super_cell = Eigen::MatrixX3d(points.size(), 3);
-      for (unsigned i = 0; i < points.size(); i++)
-        for (unsigned j = 0; j < 3; j++)
-          atom_position_to_super_cell(i, j) = points[i]["coordinates"][j].as<double>();
-      auto super_cell = (SuperCellDeformation.value_or(Eigen::Matrix3d::Identity())
-        * SuperCellMultiplier.cast<double>().asDiagonal() * PrimativeCell).eval();
-      AtomPosition = atom_position_to_super_cell * super_cell;
-    }
-    if (QpointDataInputFile.Format == "yaml")
-    {
-      auto node = YAML::LoadFile(QpointDataInputFile.Filename);
-      auto phonon = node["phonon"].as<std::vector<YAML::Node>>();
-      QpointData.resize(phonon.size());
-      for (unsigned i = 0; i < phonon.size(); i++)
-      {
-        for (unsigned j = 0; j < 3; j++)
-          QpointData[i].Qpoint(j) = phonon[i]["q-position"][j].as<double>();
-        auto band = phonon[i]["band"].as<std::vector<YAML::Node>>();
-        QpointData[i].ModeData.resize(band.size());
-        for (unsigned j = 0; j < band.size(); j++)
-        {
-          QpointData[i].ModeData[j].Frequency = band[j]["frequency"].as<double>();
-          auto eigenvector_vectors = band[j]["eigenvector"]
-            .as<std::vector<std::vector<std::vector<double>>>>();
-          Eigen::MatrixX3cd eigenvectors(AtomPosition.rows(), 3);
-          for (unsigned k = 0; k < AtomPosition.rows(); k++)
-            for (unsigned l = 0; l < 3; l++)
-              eigenvectors(k, l)
-                = eigenvector_vectors[k][l][0] + 1i * eigenvector_vectors[k][l][1];
-          // 需要对读入的原子运动状态作相位转换, 使得它们与我们的约定一致(对超胞周期性重复)
-          // 这里还要需要做归一化处理 (指将数据简单地作为向量处理的归一化)
-          auto& AtomMovement = QpointData[i].ModeData[j].AtomMovement;
-          // AtomMovement = eigenvectors.array().colwise() * (-2 * std::numbers::pi_v<double> * 1i
-          //   * (atom_position_to_super_cell * input.QpointData[i].Qpoint)).array().exp();
-          // AtomMovement /= AtomMovement.norm();
-          // phonopy 似乎已经进行了相位的转换！为什么？
-          AtomMovement = eigenvectors / eigenvectors.norm();
-        }
-      }
-    }
-    else if (QpointDataInputFile.Format == "hdf5")
-    {
-      std::vector<std::vector<std::vector<double>>> frequency, path;
-      std::vector<std::vector<std::vector<std::vector<PhonopyComplex>>>> eigenvector_vector;
-      Hdf5file{}.open_for_read(QpointDataInputFile.Filename).read(frequency, "/frequency")
-        .read(eigenvector_vector, "/eigenvector")
-        .read(path, "/path");
-      std::vector size = { frequency.size(), frequency[0].size(), frequency[0][0].size() };
-      QpointData.resize(size[0] * size[1]);
-      for (unsigned i = 0; i < size[0]; i++)
-        for (unsigned j = 0; j < size[1]; j++)
-        {
-          QpointData[i * size[1] + j].Qpoint = Eigen::Vector3d(path[i][j].data());
-          QpointData[i * size[1] + j].ModeData.resize(size[2]);
-          for (unsigned k = 0; k < size[2]; k++)
-          {
-            QpointData[i * size[1] + j].ModeData[k].Frequency = frequency[i][j][k];
-            Eigen::MatrixX3cd eigenvectors(AtomPosition.rows(), 3);
-            for (unsigned l = 0; l < AtomPosition.rows(); l++)
-              for (unsigned m = 0; m < 3; m++)
-                eigenvectors(l, m)
-                  = eigenvector_vector[i][j][l * 3 + m][k].r + eigenvector_vector[i][j][l * 3 + m][k].i * 1i;
-            QpointData[i * size[1] + j].ModeData[k].AtomMovement = eigenvectors / eigenvectors.norm();
-          }
-        }
-    }
-  }
+    // 读取并写入其它数据
+    YAML::Node phonopy = YAML::LoadFile(phonopy_file);
+    data.Cell = phonopy["unit_cell"]["lattice"].as<Eigen::Matrix3d>();
+    auto points = phonopy["unit_cell"]["points"].as<std::vector<YAML::Node>>();
+    data.AtomType = points
+      | ranges::views::transform([](const YAML::Node& point) { return point["symbol"].as<std::string>(); })
+      | ranges::views::chunk_by(std::ranges::equal_to{})
+      | ranges::views::transform([](const auto& chunk) { return std::pair{chunk[0], chunk.size()}; })
+      | ranges::to_vector;
+    data.AtomPosition = points
+      | ranges::views::transform([](const YAML::Node& point)
+        { return point["coordinates"].as<std::array<double, 3>>(); })
+      | ranges::to_vector
+      | biu::toEigen<>;
+    return points
+      | ranges::views::transform([](const YAML::Node& point)
+        { return std::pair(point["symbol"].as<std::string>(), point["mass"].as<double>()); })
+      | ranges::views::chunk_by(std::ranges::equal_to{})
+      | ranges::views::transform([](const auto& chunk) { return chunk[0]; })
+      | ranges::to<std::map<std::string, double>>;
+  };

-  void UnfoldSolver::OutputType::write
-    (decltype(InputType::QpointDataOutputFile) output_files) const
-  {
-    for (auto& output_file : output_files)
-      write(output_file.Filename, output_file.Format);
-  }
-  void UnfoldSolver::OutputType::write(std::string filename, std::string format, unsigned percision) const
-  {
-    if (format == "yaml")
-      std::ofstream(filename) << [&]
-      {
-        std::stringstream print;
-        print << "QpointData:\n";
-        for (auto& qpoint: QpointData)
-        {
-          print << fmt::format("  - Qpoint: [ {1:.{0}f}, {2:.{0}f}, {3:.{0}f} ]\n",
-            percision, qpoint.Qpoint[0], qpoint.Qpoint[1], qpoint.Qpoint[2]);
-          print << fmt::format("    Source: [ {1:.{0}f}, {2:.{0}f}, {3:.{0}f} ]\n",
-            percision, qpoint.Source[0], qpoint.Source[1], qpoint.Source[2]);
-          print << "    ModeData:\n";
-          for (auto& mode: qpoint.ModeData)
-            print << fmt::format("      - {{ Frequency: {1:.{0}f}, Weight: {2:.{0}f} }}\n",
-              percision, mode.Frequency, mode.Weight);
-        }
-        return print.str();
-      }();
-    else if (format == "yaml-human-readable")
-    {
-      std::remove_cvref_t<decltype(*this)> output;
-      std::map<unsigned, std::vector<decltype(QpointData)::const_iterator>>
-        meta_qpoint_to_sub_qpoint_iterators;
-      for (auto it = QpointData.begin(); it != QpointData.end(); it++)
-        meta_qpoint_to_sub_qpoint_iterators[it->SourceIndex_].push_back(it);
-      for (auto [meta_qpoint_index, sub_qpoint_iterators] : meta_qpoint_to_sub_qpoint_iterators)
-        for (auto& qpoint : sub_qpoint_iterators)
-        {
-          std::map<double, double> frequency_to_weight;
-          for (unsigned i_of_mode = 0; i_of_mode < qpoint->ModeData.size(); i_of_mode++)
-          {
-            auto frequency = qpoint->ModeData[i_of_mode].Frequency;
-            auto weight = qpoint->ModeData[i_of_mode].Weight;
-            auto it_lower = frequency_to_weight.lower_bound(frequency - 0.1);
-            auto it_upper = frequency_to_weight.upper_bound(frequency + 0.1);
-            if (it_lower == it_upper)
-              frequency_to_weight[frequency] = weight;
-            else
-            {
-              auto frequency_sum = std::accumulate(it_lower, it_upper, 0.,
-                [](const auto& a, const auto& b) { return a + b.first * b.second; });
-              auto weight_sum = std::accumulate(it_lower, it_upper, 0.,
-                [](const auto& a, const auto& b) { return a + b.second; });
-              frequency_sum += frequency * weight;
-              weight_sum += weight;
-              frequency_to_weight.erase(it_lower, it_upper);
-              frequency_to_weight[frequency_sum / weight_sum] = weight_sum;
-            }
-          }
-          auto& _ = output.QpointData.emplace_back();
-          _.Qpoint = qpoint->Qpoint;
-          _.Source = qpoint->Source;
-          _.SourceIndex_ = qpoint->SourceIndex_;
-          for (auto [frequency, weight] : frequency_to_weight)
-            if (weight > 0.1)
-            {
-              auto& __ = _.ModeData.emplace_back();
-              __.Frequency = frequency;
-              __.Weight = weight;
-            }
-        }
-      output.write(filename, "yaml", 3);
-    }
-    else if (format == "zpp")
-      zpp_write(*this, filename);
-    else if (format == "hdf5")
-    {
-      std::vector<std::vector<double>> Qpoint, Source, Frequency, Weight;
-      for (auto& qpoint : QpointData)
-      {
-        Qpoint.emplace_back(qpoint.Qpoint.data(), qpoint.Qpoint.data() + 3);
-        Source.emplace_back(qpoint.Source.data(), qpoint.Source.data() + 3);
-        Frequency.emplace_back();
-        Weight.emplace_back();
-        for (auto& mode : qpoint.ModeData)
-        {
-          Frequency.back().push_back(mode.Frequency);
-          Weight.back().push_back(mode.Weight);
-        }
-      }
-      Hdf5file{}.open_for_write(filename).write(Qpoint, "/Qpoint")
-        .write(Source, "/Source")
-        .write(Frequency, "/Frequency")
-        .write(Weight, "/Weight");
-    }
-  }
-
-  UnfoldSolver::UnfoldSolver(std::string config_file) : Input_([&]
-  {
-    std::clog << "Reading input file... " << std::flush;
-    return config_file;
-  }())
-  {
-    std::clog << "Done." << std::endl;
-  }
-
-  UnfoldSolver& UnfoldSolver::operator()()
-  {
-    if (!Basis_)
-    {
-      std::clog << "Constructing basis... " << std::flush;
-      Basis_ = construct_basis
-      (
-        Input_.PrimativeCell, Input_.SuperCellMultiplier,
-        Input_.PrimativeCellBasisNumber, Input_.AtomPosition
-      );
-      std::clog << "Done." << std::endl;
-    }
-    if (!Output_)
-    {
-      std::clog << "Calculating projection coefficient... " << std::flush;
-      std::vector<std::reference_wrapper<const decltype
-        (InputType::QpointDataType::ModeDataType::AtomMovement)>> mode_data;
-      for (auto& qpoint : Input_.QpointData)
-        for (auto& mode : qpoint.ModeData)
-          mode_data.emplace_back(mode.AtomMovement);
-      std::atomic<unsigned> number_of_finished_modes(0);
-      std::thread print_thread([&]
-      {
-        unsigned n;
-        while ((n = number_of_finished_modes) < mode_data.size())
-        {
-          std::osyncstream(std::cerr) << fmt::format("\rCalculating projection coefficient... ({}/{})",
-            number_of_finished_modes, mode_data.size()) << std::flush;
-          std::this_thread::sleep_for(100ms);
-          number_of_finished_modes.wait(n);
-        }
-      });
-      auto projection_coefficient = construct_projection_coefficient
-        (*Basis_, mode_data, number_of_finished_modes);
-      number_of_finished_modes = mode_data.size();
-      print_thread.join();
-      std::clog << "\33[2K\rCalculating projection coefficient... Done." << std::endl;
-
-      std::clog << "Constructing output... " << std::flush;
-      std::vector<std::reference_wrapper<const decltype(InputType::QpointDataType::Qpoint)>> qpoint;
-      std::vector<std::vector<std::reference_wrapper<const
-        decltype(InputType::QpointDataType::ModeDataType::Frequency)>>> frequency;
-      for (auto& qpoint_data : Input_.QpointData)
-      {
-        qpoint.emplace_back(qpoint_data.Qpoint);
-        frequency.emplace_back();
-        for (auto& mode_data : qpoint_data.ModeData)
-          frequency.back().emplace_back(mode_data.Frequency);
-      }
-      Output_ = construct_output
-      (
-        Input_.SuperCellMultiplier,
-        Input_.SuperCellDeformation, qpoint, frequency, projection_coefficient
-      );
-      std::clog << "Done." << std::endl;
-    }
-    std::clog << "Writing output... " << std::flush;
-    Output_->write(Input_.QpointDataOutputFile);
-    std::clog << "Done." << std::endl;
-    return *this;
-  }
-
-  UnfoldSolver::BasisType UnfoldSolver::construct_basis
+  // 构建基
+  // 每个 q 点对应一组 sub qpoint。不同的 q 点所对应的 sub qpoint 是不一样的，但 sub qpoint 与 q 点的相对位移在不同 q 点之间是相同的。
+  // 由于基只与这个相对位置有关（也就是说，不同 q 点的基是一样的），因此可以先计算出所有的基，这样降低计算量。
+  // 外层下标对应超胞倒格子的整数倍那部分(第二部分), 也就是不同的 sub qpoint
+  // 内层下标对应单胞倒格子的整数倍那部分(第一部分), 也就是 sub qpoint 上的不同平面波（取的数量越多，结果越精确）
+  auto construct_basis = []
  (
-    const decltype(InputType::PrimativeCell)& primative_cell,
-    const decltype(InputType::SuperCellMultiplier)& super_cell_multiplier,
-    const decltype(InputType::PrimativeCellBasisNumber)& primative_cell_basis_number,
-    const decltype(InputType::AtomPosition)& atom_position
+    Eigen::Matrix3d primative_cell, Eigen::Vector3i super_cell_multiplier,
+    Eigen::Vector<std::size_t, 3> primative_cell_basis_number, Eigen::MatrixX3d atom_position
  )
  {
-    BasisType basis(super_cell_multiplier.prod());
-    // 每个 q 点对应的一组 sub qpoint。不同的 q 点所对应的 sub qpoint 是不一样的，但 sub qpoint 与 q 点的相对位置一致。
-    // 这里 xyz_of_diff_of_sub_qpoint 即表示这个相对位置，单位为超胞的倒格矢
-    for (auto [xyz_of_diff_of_sub_qpoint_by_reciprocal_modified_super_cell, i_of_sub_qpoint]
-      : triplet_sequence(super_cell_multiplier))
+    biu::Logger::Guard log;
+    std::vector<std::vector<Eigen::VectorXcd>> basis(super_cell_multiplier.prod());
+    // diff_of_sub_qpoint 表示 sub qpoint 与 qpoint 的相对位置，单位为超胞的倒格矢
+    for (auto [diff_of_sub_qpoint_by_reciprocal_modified_super_cell, i_of_sub_qpoint]
+      : biu::sequence(super_cell_multiplier))
    {
      basis[i_of_sub_qpoint].resize(primative_cell_basis_number.prod());
-      for (auto [xyz_of_basis, i_of_basis] : triplet_sequence(primative_cell_basis_number))
+      for (auto [xyz_of_basis, i_of_basis]
+        : biu::sequence(primative_cell_basis_number))
      {
-        // 计算 q 点的坐标, 单位为单胞的倒格矢
-        auto diff_of_sub_qpoint_by_reciprocal_primative_cell = xyz_of_basis.cast<double>()
+        // 计算波矢, 单位为单胞的倒格矢
+        auto wavevector_by_reciprocal_primative_cell = xyz_of_basis.cast<double>()
          + super_cell_multiplier.cast<double>().cwiseInverse().asDiagonal()
-          * xyz_of_diff_of_sub_qpoint_by_reciprocal_modified_super_cell.cast<double>();
-        // 将 q 点坐标转换为埃^-1
-        auto qpoint = (diff_of_sub_qpoint_by_reciprocal_primative_cell.transpose()
-          * (primative_cell.transpose().inverse())).transpose();
+          * diff_of_sub_qpoint_by_reciprocal_modified_super_cell.cast<double>();
+        // 将单位转换为埃^-1
+        auto wavevector = primative_cell.inverse() * wavevector_by_reciprocal_primative_cell;
        // 计算基矢
        basis[i_of_sub_qpoint][i_of_basis]
-          = (2i * std::numbers::pi_v<double> * (atom_position * qpoint)).array().exp();
+          = (2i * std::numbers::pi_v<double> * (atom_position * wavevector)).array().exp();
      }
    }
    return basis;
-  }
+  };

-  std::vector<std::vector<double>> UnfoldSolver::construct_projection_coefficient
+  // 计算从超胞到原胞的投影系数（不是分原子的投影系数），是反折叠的核心步骤
+  // 返回的投影系数是一个三维数组，第一维对应不同的 q 点，第二维对应不同的模式，第三维对应不同的 sub qpoint
+  auto construct_projection_coefficient = []
  (
-    const BasisType& basis,
-    const std::vector<std::reference_wrapper<const decltype
-      (InputType::QpointDataType::ModeDataType::AtomMovement)>>& mode_data,
-    std::atomic<unsigned>& number_of_finished_modes
+    const std::vector<std::vector<Eigen::VectorXcd>>& basis,
+    const std::vector<std::reference_wrapper<const Eigen::MatrixX3cd>>& modes,
+    std::atomic<std::size_t>& number_of_finished_modes
  )
  {
    // 第一层下标对应不同模式, 第二层下标对应这个模式在反折叠后的 q 点(sub qpoint)
-    std::vector<std::vector<double>> projection_coefficient(mode_data.size());
+    std::vector<std::vector<double>> projection_coefficient(modes.size());
    // 对每个模式并行
    std::transform
    (
-      std::execution::par, mode_data.begin(), mode_data.end(),
+      std::execution::par, modes.begin(), modes.end(),
      projection_coefficient.begin(), [&](const auto& mode_data)
      {
        // 这里, mode_data 和 projection_coefficient 均指对应于一个模式的数据
        std::vector<double> projection_coefficient(basis.size());
-        for (unsigned i_of_sub_qpoint = 0; i_of_sub_qpoint < basis.size(); i_of_sub_qpoint++)
+        for (auto i_of_sub_qpoint : std::views::iota(0u, basis.size()))
          // 对于 basis 中, 对应于单胞倒格子的部分, 以及对应于不同方向的部分, 分别求内积, 然后求模方和
-          for (unsigned i_of_basis = 0; i_of_basis < basis[i_of_sub_qpoint].size(); i_of_basis++)
+          for (auto i_of_basis : std::views::iota(0u, basis[i_of_sub_qpoint].size()))
            projection_coefficient[i_of_sub_qpoint] +=
-              (basis[i_of_sub_qpoint][i_of_basis].transpose().conjugate() * mode_data.get())
-                .array().abs2().sum();
+              (basis[i_of_sub_qpoint][i_of_basis].transpose().conjugate() * mode_data.get()).array().abs2().sum();
        // 如果是严格地将向量分解到一组完备的基矢上, 那么不需要对计算得到的权重再做归一化处理
        // 但这里并不是这样一个严格的概念. 因此对分解到各个 sub qpoint 上的权重做归一化处理
-        auto sum = std::accumulate
-          (projection_coefficient.begin(), projection_coefficient.end(), 0.);
-        for (auto& _ : projection_coefficient)
-          _ /= sum;
+        auto sum = ranges::accumulate(projection_coefficient, 0.);
+        for (auto& _ : projection_coefficient) _ /= sum;
        number_of_finished_modes++;
        return projection_coefficient;
      }
    );
    return projection_coefficient;
-  }
+  };

-  UnfoldSolver::OutputType UnfoldSolver::construct_output
-  (
-    const decltype(InputType::SuperCellMultiplier)& super_cell_multiplier,
-    const decltype(InputType::SuperCellDeformation)& super_cell_deformation,
-    const std::vector<std::reference_wrapper<const decltype
-      (InputType::QpointDataType::Qpoint)>>& meta_qpoint_by_reciprocal_super_cell,
-    const std::vector<std::vector<std::reference_wrapper<const decltype
-      (InputType::QpointDataType::ModeDataType::Frequency)>>>& frequency,
-    const ProjectionCoefficientType_& projection_coefficient
-  )
-  {
-    OutputType output;
+  biu::Logger::Guard log;
+
+  log.info("Reading input file...");
+  auto config = YAML::LoadFile(config_file).as<Config>();
+  CommonData output;
+  output.AtomMass = read_qpoint
+    (config.PrimativePhonopy, config.PrimativeQpoint, output.Primative);
+  output.AtomMass.merge(read_qpoint
+    (config.SuperPhonopy, config.SuperQpoint, output.Super));
+  output.Super.CellDeformation = config.SuperCellDeformation;
+  output.Super.CellMultiplier = config.SuperCellMultiplier;
+  output.Super.AtomTranslation = config.AtomTranslation;
+  // 填充 SubQpoint
+  for (auto i_of_super_qpoint : std::views::iota(0u, output.Super.Qpoint.size()))
    for
    (
-      unsigned i_of_meta_qpoint = 0, num_of_mode_manipulated = 0;
-      i_of_meta_qpoint < meta_qpoint_by_reciprocal_super_cell.size();
-      i_of_meta_qpoint++
+      auto [diff_of_sub_qpoint_by_reciprocal_modified_super_cell, i_of_sub_qpoint]
+        : biu::sequence(config.SuperCellMultiplier)
    )
    {
-      for (auto [xyz_of_diff_of_sub_qpoint_by_reciprocal_modified_super_cell, i_of_sub_qpoint]
-        : triplet_sequence(super_cell_multiplier))
-      {
-        auto& _ = output.QpointData.emplace_back();
-        /*
-          SubQpointByReciprocalModifiedSuperCell = XyzOfDiffOfSubQpointByReciprocalModifiedSuperCell +
-            MetaQpointByReciprocalModifiedSuperCell;
-          SubQpoint = SubQpointByReciprocalModifiedSuperCell.transpose() * ReciprocalModifiedSuperCell;
-          SubQpoint = SubQpointByReciprocalPrimativeCell.transpose() * ReciprocalPrimativeCell;
-          ReciprocalModifiedSuperCell = ModifiedSuperCell.inverse().transpose();
-          ReciprocalPrimativeCell = PrimativeCell.inverse().transpose();
-          ModifiedSuperCell = SuperCellMultiplier.asDiagonal() * PrimativeCell;
-          MetaQpoint = MetaQpointByReciprocalModifiedSuperCell.transpose() * ReciprocalModifiedSuperCell;
-          MetaQpoint = MetaQpointByReciprocalSuperCell.transpose() * ReciprocalSuperCell;
-          ReciprocalSuperCell = SuperCell.inverse().transpose();
-          ModifiedSuperCell = SuperCellDeformation * SuperCell;
-          SuperCell = SuperCellMultiplier.asDiagonal() * PrimativeCell;
-          整理可以得到:
-          SubQpointByReciprocalPrimativeCell = SuperCellMultiplier.asDiagonal().inverse() *
-            (XyzOfDiffOfSubQpointByReciprocalModifiedSuperCell +
-              SuperCellDeformation.inverse() * MetaQpointByReciprocalSuperCell);
-          但注意到, 这样得到的 SubQpoint 可能不在 ReciprocalPrimativeCell 中
-            (当 SuperCellDeformation 不是单位矩阵时, 边界附近的一两条 SubQpoint 会出现这种情况).
-          解决办法是, 在赋值时, 仅取 SubQpointByReciprocalPrimativeCell 的小数部分.
-        */
-        auto sub_qpoint_by_reciprocal_primative_cell =
-        (
-          super_cell_multiplier.cast<double>().cwiseInverse().asDiagonal()
-          * (
-            xyz_of_diff_of_sub_qpoint_by_reciprocal_modified_super_cell.cast<double>()
-            + super_cell_deformation.value_or(Eigen::Matrix3d::Identity()).inverse()
-              * meta_qpoint_by_reciprocal_super_cell[i_of_meta_qpoint].get().cast<double>()
-          )
-        ).eval();
-        _.Qpoint = sub_qpoint_by_reciprocal_primative_cell.array()
-          - sub_qpoint_by_reciprocal_primative_cell.array().floor();
-        _.Source = meta_qpoint_by_reciprocal_super_cell[i_of_meta_qpoint];
-        _.SourceIndex_ = i_of_meta_qpoint;
-        for (unsigned i_of_mode = 0; i_of_mode < frequency[i_of_meta_qpoint].size(); i_of_mode++)
-        {
-          auto& __ = _.ModeData.emplace_back();
-          __.Frequency = frequency[i_of_meta_qpoint][i_of_mode];
-          __.Weight = projection_coefficient[num_of_mode_manipulated + i_of_mode][i_of_sub_qpoint];
-        }
-      }
-      num_of_mode_manipulated += frequency[i_of_meta_qpoint].size();
+      /*
+        SubQpointByReciprocalModifiedSuperCell = XyzOfDiffOfSubQpointByReciprocalModifiedSuperCell +
+          MetaQpointByReciprocalModifiedSuperCell;
+        SubQpoint = SubQpointByReciprocalModifiedSuperCell.transpose() * ReciprocalModifiedSuperCell;
+        SubQpoint = SubQpointByReciprocalPrimativeCell.transpose() * ReciprocalPrimativeCell;
+        ReciprocalModifiedSuperCell = ModifiedSuperCell.inverse().transpose();
+        ReciprocalPrimativeCell = PrimativeCell.inverse().transpose();
+        ModifiedSuperCell = SuperCellMultiplier.asDiagonal() * PrimativeCell;
+        MetaQpoint = MetaQpointByReciprocalModifiedSuperCell.transpose() * ReciprocalModifiedSuperCell;
+        MetaQpoint = MetaQpointByReciprocalSuperCell.transpose() * ReciprocalSuperCell;
+        ReciprocalSuperCell = SuperCell.inverse().transpose();
+        ModifiedSuperCell = SuperCellDeformation * SuperCell;
+        SuperCell = SuperCellMultiplier.asDiagonal() * PrimativeCell;
+        整理可以得到:
+        SubQpointByReciprocalPrimativeCell = SuperCellMultiplier.asDiagonal().inverse() *
+          (XyzOfDiffOfSubQpointByReciprocalModifiedSuperCell +
+            SuperCellDeformation.inverse() * MetaQpointByReciprocalSuperCell);
+        但注意到, 这样得到的 SubQpoint 可能不在 ReciprocalPrimativeCell 中
+          (当 SuperCellDeformation 不是单位矩阵时, 边界附近的一两条 SubQpoint 会出现这种情况).
+        解决办法是, 在赋值时, 仅取 SubQpointByReciprocalPrimativeCell 的小数部分.
+      */
+      auto sub_qpoint_by_reciprocal_primative_cell =
+      (
+        config.SuperCellMultiplier.cast<double>().cwiseInverse().asDiagonal()
+        * (
+          diff_of_sub_qpoint_by_reciprocal_modified_super_cell.cast<double>()
+            + config.SuperCellDeformation.inverse() * output.Super.Qpoint[i_of_super_qpoint].Qpoint
+        )
+      ).eval();
+      output.Super.Qpoint[i_of_super_qpoint].SubQpoint.push_back(sub_qpoint_by_reciprocal_primative_cell.array()
+        - sub_qpoint_by_reciprocal_primative_cell.array().floor());
    }
-    return output;
+  log.info("Done.");
+
+  log.info("Constructing basis...");
+  auto basis = construct_basis
+  (
+    output.Primative.Cell, output.Super.CellMultiplier,
+    config.PrimativeCellBasisNumber,
+    output.Super.AtomPosition
+      * (output.Super.CellDeformation * output.Super.CellMultiplier.cast<double>().asDiagonal() * output.Primative.Cell)
+  );
+  log.info("Done.");
+
+  std::clog << "Calculating projection coefficient... " << std::flush;
+  // 将所有模式放到一维来处理
+  {
+    auto modes = output.Super.Qpoint
+      | ranges::views::transform([](const auto& qpoint)
+        { return qpoint.Mode | ranges::views::transform([](const auto& mode)
+          { return std::cref(mode.EigenVector); }); })
+      | ranges::views::join
+      | ranges::to_vector;
+    std::atomic<std::size_t> number_of_finished_modes(0);
+    std::thread print_thread([&]
+    {
+      while (true)
+      {
+        std::osyncstream(std::clog)
+          << "\rCalculating projection coefficient... ({}/{})"_f(number_of_finished_modes, modes.size())
+          << std::flush;
+        std::this_thread::sleep_for(100ms);
+        if (number_of_finished_modes == modes.size()) break;
+      }
+    });
+    auto projection_coefficient = construct_projection_coefficient
+      (basis, modes, number_of_finished_modes);
+    std::size_t i_of_modes = 0;
+    for (auto& qpoint : output.Super.Qpoint) for (auto& mode : qpoint.Mode)
+      mode.WeightOnUnfold = projection_coefficient[i_of_modes++];
+    print_thread.join();
  }
+  std::clog << "\33[2K\rCalculating projection coefficient... Done." << std::endl;
+
+  log.info("Writing data... ");
+  std::ofstream(config.OutputFile, std::ios::binary) << biu::serialize<char>(output);
+  log.info("Done.");
+
+  log.info("Summary:");
+
+  for (auto i_of_qpoint : std::views::iota(0u, output.Super.Qpoint.size()))
+    for (auto i_of_mode : std::views::iota(0u, output.Super.Qpoint[i_of_qpoint].Mode.size()))
+      for
+      (
+        auto i_of_sub_qpoint
+          : std::views::iota(0u, output.Super.Qpoint[i_of_qpoint].SubQpoint.size())
+      )
+      if (output.Super.Qpoint[i_of_qpoint].Mode[i_of_mode].WeightOnUnfold[i_of_sub_qpoint] > 0.01)
+        log.info("{}:{:.2f}:{}:{:.2f} -> {:.2f} {:.2f}"_f
+        (
+          i_of_qpoint, fmt::join(output.Super.Qpoint[i_of_qpoint].Qpoint, ", "),
+          i_of_mode, output.Super.Qpoint[i_of_qpoint].Mode[i_of_mode].Frequency,
+          fmt::join(output.Super.Qpoint[i_of_qpoint].SubQpoint[i_of_sub_qpoint], ", "),
+          output.Super.Qpoint[i_of_qpoint].Mode[i_of_mode].WeightOnUnfold[i_of_sub_qpoint]
+        ));
 }
--- a/test/14.2.2.4.unfold.yaml
+++ b/test/14.2.2.4.unfold.yaml
@@ -1,12 +0,0 @@
-PrimativeCell:
- [     1.548010265167714,    -2.681232429908652,     0.000000000000000 ] # a
- [     1.548010265167714,     2.681232429908652,     0.000000000000000 ] # b
- [     0.000000000000000,     0.000000000000000,     5.061224103556595 ] # c
-SuperCellMultiplier: [ 3, 1, 1 ]
-PrimativeCellBasisNumber: [ 8, 8, 8 ]
-AtomPositionInputFile: { FileName: "/home/chn/Documents/lammps-SiC/14/14.2/14.2.2/14.2.2.4/band.yaml", Format: "yaml" }
-QpointDataInputFile: { FileName: "/home/chn/Documents/lammps-SiC/14/14.2/14.2.2/14.2.2.4/band.yaml", Format: "yaml" }
-QpointDataOutputFile:
- { FileName: "test/14.2.2.4.result.yaml", Format: "yaml" }
- { FileName: "test/14.2.2.4.result.human-readable.yaml", Format: "yaml-human-readable" }
- { FileName: "test/14.2.2.4.result.zpp", Format: "zpp" }
--- a/test/14.2.2.5.plot.yaml
+++ b/test/14.2.2.5.plot.yaml
@@ -1,14 +0,0 @@
-PrimativeCell:
- [     1.548010265167714,    -2.681232429908652,     0.000000000000000 ] # a
- [     1.548010265167714,     2.681232429908652,     0.000000000000000 ] # b
- [     0.000000000000000,     0.000000000000000,     5.061224103556595 ] # c
-SourceFilename: ./test/14.2.2.5.result.zpp
-Figures:
- Qpoints:
-  - - [ 0, 0, 0 ]
-    - [ 0.5, 0, 0 ]
-    - [ 0.3333333, 0.3333333, 0 ]
-    - [ 0, 0, 0 ]
-  Resolution: [ 1024, 400 ]
-  Range: [ -5, 35 ]
-  Filename: ./test/14.2.2.5.png
--- a/test/14.2.2.5.unfold.yaml
+++ b/test/14.2.2.5.unfold.yaml
@@ -1,12 +0,0 @@
-PrimativeCell:
- [     1.548010265167714,    -2.681232429908652,     0.000000000000000 ] # a
- [     1.548010265167714,     2.681232429908652,     0.000000000000000 ] # b
- [     0.000000000000000,     0.000000000000000,     5.061224103556595 ] # c
-SuperCellMultiplier: [ 3, 1, 1 ]
-PrimativeCellBasisNumber: [ 8, 8, 8 ]
-AtomPositionInputFile: { FileName: "/home/chn/Documents/lammps-SiC/14/14.2/14.2.2/14.2.2.5/band.yaml", Format: "yaml" }
-QpointDataInputFile: { FileName: "/home/chn/Documents/lammps-SiC/14/14.2/14.2.2/14.2.2.5/band.yaml", Format: "yaml" }
-QpointDataOutputFile:
- { FileName: "test/14.2.2.5.result.yaml", Format: "yaml" }
- { FileName: "test/14.2.2.5.result.human-readable.yaml", Format: "yaml-human-readable" }
- { FileName: "test/14.2.2.5.result.zpp", Format: "zpp" }
--- a/test/14.2.4.4.plot.yaml
+++ b/test/14.2.4.4.plot.yaml
@@ -1,14 +0,0 @@
-PrimativeCell:
- [     1.548010265167714,    -2.681232429908652,     0.000000000000000 ] # a
- [     1.548010265167714,     2.681232429908652,     0.000000000000000 ] # b
- [     0.000000000000000,     0.000000000000000,     5.061224103556595 ] # c
-SourceFilename: ./test/14.2.4.4.result.zpp
-Figures:
- Qpoints:
-  - - [ 0, 0, 0 ]
-    - [ 0.5, 0, 0 ]
-    - [ 0.3333333, 0.3333333, 0 ]
-    - [ 0, 0, 0 ]
-  Resolution: [ 1024, 400 ]
-  Range: [ -5, 35 ]
-  Filename: ./test/14.2.4.4.png
--- a/test/14.2.4.4.unfold.yaml
+++ b/test/14.2.4.4.unfold.yaml
@@ -1,14 +0,0 @@
-PrimativeCell:
- [     1.548010265167714,    -2.681232429908652,     0.000000000000000 ] # a
- [     1.548010265167714,     2.681232429908652,     0.000000000000000 ] # b
- [     0.000000000000000,     0.000000000000000,     5.061224103556595 ] # c
-SuperCellMultiplier: [ 2, 2, 1 ]
-PrimativeCellBasisNumber: [ 8, 8, 8 ]
-AtomPositionInputFile: 
-  FileName: "/home/chn/Documents/lammps-SiC/14/14.2/14.2.4/14.2.4.4/phonopy.yaml"
-  Format: "yaml"
-QpointDataInputFile: { FileName: "/home/chn/Documents/lammps-SiC/14/14.2/14.2.4/14.2.4.4/band.hdf5", Format: "hdf5" }
-QpointDataOutputFile:
- { FileName: "test/14.2.4.4.result.yaml", Format: "yaml" }
- { FileName: "test/14.2.4.4.result.human-readable.yaml", Format: "yaml-human-readable" }
- { FileName: "test/14.2.4.4.result.zpp", Format: "zpp" }
--- a/test/14.2.5.5.plot.yaml
+++ b/test/14.2.5.5.plot.yaml
@@ -1,14 +0,0 @@
-PrimativeCell:
- [     1.548010265167714,    -2.681232429908652,     0.000000000000000 ] # a
- [     1.548010265167714,     2.681232429908652,     0.000000000000000 ] # b
- [     0.000000000000000,     0.000000000000000,     5.061224103556595 ] # c
-SourceFilename: ./test/14.2.5.5.result.zpp
-Figures:
- Qpoints:
-  - - [ 0, 0, 0 ]
-    - [ 0.5, 0, 0 ]
-    - [ 0.3333333, 0.3333333, 0 ]
-    - [ 0, 0, 0 ]
-  Resolution: [ 1024, 400 ]
-  Range: [ -5, 35 ]
-  Filename: ./test/14.2.5.5.png
--- a/test/14.2.5.5.unfold.yaml
+++ b/test/14.2.5.5.unfold.yaml
@@ -1,18 +0,0 @@
-PrimativeCell:
- [     1.548010265167714,    -2.681232429908652,     0.000000000000000 ] # a
- [     1.548010265167714,     2.681232429908652,     0.000000000000000 ] # b
- [     0.000000000000000,     0.000000000000000,     5.061224103556595 ] # c
-SuperCellMultiplier: [ 1, 2, 1 ]
-SuperCellDeformation:
- [ 1, 0, 0]
- [ 1, 1, 0]
- [ 0, 0, 1]
-PrimativeCellBasisNumber: [ 8, 8, 8 ]
-AtomPositionInputFile:
-  FileName: "/home/chn/Documents/lammps-SiC/14/14.2/14.2.5/14.2.5.5/phonopy.yaml"
-  Format: "yaml"
-QpointDataInputFile: { FileName: "/home/chn/Documents/lammps-SiC/14/14.2/14.2.5/14.2.5.5/band.hdf5", Format: "hdf5" }
-QpointDataOutputFile:
- { FileName: "test/14.2.5.5.result.yaml", Format: "yaml" }
- { FileName: "test/14.2.5.5.result.human-readable.yaml", Format: "yaml-human-readable" }
- { FileName: "test/14.2.5.5.result.zpp", Format: "zpp" }
--- a/test/14.2.6.4.plot.yaml
+++ b/test/14.2.6.4.plot.yaml
@@ -1,15 +0,0 @@
-PrimativeCell:
- [     1.548010265167714,    -2.681232429908652,     0.000000000000000 ] # a
- [     1.548010265167714,     2.681232429908652,     0.000000000000000 ] # b
- [     0.000000000000000,     0.000000000000000,     5.061224103556595 ] # c
-SourceFilename: ./test/14.2.6.4.result.zpp
-Figures:
- Qpoints:
-  - - [ 0, 0, 0 ]
-    - [ 0.5, 0, 0 ]
-    - [ 0.3333333, 0.3333333, 0 ]
-    - [ 0, 0, 0 ]
-  Resolution: [ 1024, 1024 ]
-  Range: [ -5, 35 ]
-  Filename: ./test/14.2.6.4.png
-  YTicks: [ 0, 5, 10, 15, 20, 25, 30 ]
--- a/test/14.2.6.4.unfold.yaml
+++ b/test/14.2.6.4.unfold.yaml
@@ -1,18 +0,0 @@
-PrimativeCell:
- [     1.548010265167714,    -2.681232429908652,     0.000000000000000 ] # a
- [     1.548010265167714,     2.681232429908652,     0.000000000000000 ] # b
- [     0.000000000000000,     0.000000000000000,     5.061224103556595 ] # c
-SuperCellMultiplier: [ 4, 8, 1 ]
-SuperCellDeformation:
- [ 1, 0, 0]
- [ 1, 1, 0]
- [ 0, 0, 1]
-PrimativeCellBasisNumber: [ 8, 8, 8 ]
-AtomPositionInputFile:
-  FileName: "/home/chn/Documents/lammps-SiC/14/14.2/14.2.6/14.2.6.4/phonopy.yaml"
-  Format: "yaml"
-QpointDataInputFile: { FileName: "/home/chn/Documents/lammps-SiC/14/14.2/14.2.6/14.2.6.4/band.hdf5", Format: "hdf5" }
-QpointDataOutputFile:
- { FileName: "test/14.2.6.4.result.yaml", Format: "yaml" }
- { FileName: "test/14.2.6.4.result.human-readable.yaml", Format: "yaml-human-readable" }
- { FileName: "test/14.2.6.4.result.zpp", Format: "zpp" }
--- a/test/fold/config.yaml
+++ b/test/fold/config.yaml
@@ -0,0 +1,18 @@
+SuperCellMultiplier: [3, 4, 1]
+SuperCellDeformation:
+  - [ 1, 0, 0 ]
+  - [ 0.6666, 1, 0 ]
+  - [ 0, 0, 1 ]
+Qpoints:
+  - [0, 0, 0]
+  - [0.05, 0, 0]
+  - [0.1, 0, 0]
+  - [0.15, 0, 0]
+  - [0.2, 0, 0]
+  - [0.25, 0, 0]
+  - [0.3, 0, 0]
+  - [0.35, 0, 0]
+  - [0.4, 0, 0]
+  - [0.45, 0, 0]
+  - [0.5, 0, 0]
+OutputFile: fold-output.yaml
--- a/test/project-to-atom/.gitignore
+++ b/test/project-to-atom/.gitignore
@@ -0,0 +1 @@
+output.zpp
--- a/test/project-to-atom/config.yaml
+++ b/test/project-to-atom/config.yaml
@@ -0,0 +1,3 @@
+SelectedAtom: [0, 2, 4]
+InputFile: input.zpp
+OutputFile: output.zpp
--- a/test/project-to-atom/input.zpp
+++ b/test/project-to-atom/input.zpp
--- a/test/project-to-mode/.gitignore
+++ b/test/project-to-mode/.gitignore
@@ -0,0 +1 @@
+output.yaml
--- a/test/project-to-mode/config.yaml
+++ b/test/project-to-mode/config.yaml
@@ -0,0 +1,6 @@
+PrimativeCellBasisNumber: [ 8, 8, 8 ]
+SuperQpointIndex: 0
+SubQpointIndex: 0
+PrimativeQpointIndex: 0
+InputDataFile: data.zpp
+OutputFile: output.yaml
--- a/test/project-to-mode/data.zpp
+++ b/test/project-to-mode/data.zpp
--- a/test/raman-apply-contribution/.gitignore
+++ b/test/raman-apply-contribution/.gitignore
@@ -0,0 +1 @@
+output.zpp
--- a/test/raman-apply-contribution/config.yaml
+++ b/test/raman-apply-contribution/config.yaml
@@ -0,0 +1,228 @@
+OriginalSusceptibility:
+  - [ 7.006328, -3.3e-05, -2e-06 ]
+  - [ -3.4e-05, 7.002539, -2.4e-05 ]
+  - [ -3e-06, -1.2e-05, 7.303458 ]
+Susceptibility:
+  0:
+    0:
+      "+":
+        - [ 7.006379, -5e-06, -2e-06 ]
+        - [ -1.6e-05, 7.002547, -3e-05 ]
+        - [ -1.1e-05, -6e-06, 7.303627 ]
+      "-":
+        - [ 7.006463, 4e-06, -4.5e-05 ]
+        - [ 1e-06, 7.002729, -1.7e-05 ]
+        - [ -4.9e-05, 6e-06, 7.303617 ]
+    1:
+      "+":
+        - [ 7.006331, 7e-06, 1.6e-05 ]
+        - [ 2e-06, 7.002539, -1.9e-05 ]
+        - [ 1.7e-05, -3e-06, 7.303612 ]
+      "-":
+        - [ 7.006366, -8e-06, 1.5e-05 ]
+        - [ -1.1e-05, 7.002548, -8e-06 ]
+        - [ 1.3e-05, 1.1e-05, 7.303606 ]
+    10:
+      "+":
+        - [ 7.00768, 0.004054, 1e-06 ]
+        - [ 0.004046, 7.003291, -4e-05 ]
+        - [ -1e-06, -1.7e-05, 7.305554 ]
+      "-":
+        - [ 7.007955, -0.004016, -1e-06 ]
+        - [ -0.004015, 7.003451, -9e-06 ]
+        - [ -4e-06, 7e-06, 7.305848 ]
+    107:
+      "+":
+        - [ 7.007532, -4.7e-05, -6e-06 ]
+        - [ -4.8e-05, 7.003828, -9e-06 ]
+        - [ -4e-06, 4e-06, 7.307759 ]
+      "-":
+        - [ 7.0076, -5e-06, -1.2e-05 ]
+        - [ -5e-06, 7.003875, -8e-06 ]
+        - [ -1e-05, 2e-06, 7.307945 ]
+    115:
+      "+":
+        - [ 7.007683, 5e-06, -5.3e-05 ]
+        - [ -0, 7.003913, 5e-06 ]
+        - [ -4e-05, 2.8e-05, 7.307388 ]
+      "-":
+        - [ 7.007917, 5e-06, -3e-06 ]
+        - [ 4e-06, 7.004128, -3e-06 ]
+        - [ -2e-06, 1.1e-05, 7.307671 ]
+    15:
+      "+":
+        - [ 7.010948, -8.3e-05, -0.007718 ]
+        - [ -8e-05, 7.004814, -3.4e-05 ]
+        - [ -0.00772, -1.5e-05, 7.3101 ]
+      "-":
+        - [ 7.011174, 3e-06, 0.00773 ]
+        - [ -5e-06, 7.005176, -7e-06 ]
+        - [ 0.007728, 1e-05, 7.3104 ]
+    16:
+      "+":
+        - [ 7.008787, 7.2e-05, -1.8e-05 ]
+        - [ 7.4e-05, 7.007313, 0.007694 ]
+        - [ -2.4e-05, 0.007696, 7.310191 ]
+      "-":
+        - [ 7.008947, -1.3e-05, -7e-06 ]
+        - [ -2.1e-05, 7.007438, -0.007742 ]
+        - [ -7e-06, -0.007727, 7.310434 ]
+    185:
+      "+":
+        - [ 7.018886, 1.8e-05, -5e-05 ]
+        - [ 2.7e-05, 7.015141, -3e-05 ]
+        - [ -5e-05, -1.7e-05, 7.307471 ]
+      "-":
+        - [ 7.003657, 1e-06, 9e-06 ]
+        - [ -1e-06, 6.999828, -1.4e-05 ]
+        - [ 1e-05, 5e-06, 7.326057 ]
+    2:
+      "+":
+        - [ 7.006421, -8e-06, -4e-05 ]
+        - [ -1.5e-05, 7.002682, -6.7e-05 ]
+        - [ -3.9e-05, -4.5e-05, 7.303477 ]
+      "-":
+        - [ 7.00633, 2.4e-05, -7.4e-05 ]
+        - [ 2.2e-05, 7.00253, -9.1e-05 ]
+        - [ -7.7e-05, -7.2e-05, 7.303417 ]
+    251:
+      "+":
+        - [ 7.008862, 4.9e-05, -8.8e-05 ]
+        - [ 4.8e-05, 7.011172, -0.00086 ]
+        - [ -7.8e-05, -0.000845, 7.305162 ]
+      "-":
+        - [ 7.009107, -5e-06, -2e-06 ]
+        - [ -8e-06, 7.011587, 0.000791 ]
+        - [ 3e-06, 0.000809, 7.305493 ]
+    252:
+      "+":
+        - [ 7.015066, -4.3e-05, -0.000838 ]
+        - [ -4.5e-05, 7.005147, -2.9e-05 ]
+        - [ -0.000841, -9e-06, 7.305197 ]
+      "-":
+        - [ 7.015285, -4e-06, 0.000833 ]
+        - [ -2e-06, 7.005368, -4e-06 ]
+        - [ 0.000824, 1.2e-05, 7.305474 ]
+    281:
+      "+":
+        - [ 6.981143, 1.4e-05, -5.8e-05 ]
+        - [ 1.1e-05, 7.038724, 4.3e-05 ]
+        - [ -5.7e-05, 5.9e-05, 7.306158 ]
+      "-":
+        - [ 7.037206, 2e-06, 0 ]
+        - [ 3e-06, 6.983191, -1e-05 ]
+        - [ 2e-06, 0, 7.306576 ]
+    282:
+      "+":
+        - [ 7.014582, -0.027613, 1.6e-05 ]
+        - [ -0.027632, 7.005279, -7.1e-05 ]
+        - [ 4e-06, -6.7e-05, 7.306158 ]
+      "-":
+        - [ 7.014711, 0.027632, -2e-06 ]
+        - [ 0.027633, 7.005478, -1.1e-05 ]
+        - [ -3e-06, 4e-06, 7.306578 ]
+    287:
+      "+":
+        - [ 7.032791, 2.6e-05, -4.1e-05 ]
+        - [ 3.2e-05, 7.028882, -1.7e-05 ]
+        - [ -3.6e-05, -2e-06, 7.250185 ]
+      "-":
+        - [ 6.985897, -3e-06, 4e-06 ]
+        - [ 5e-06, 6.982421, -1.4e-05 ]
+        - [ 2e-06, -3e-06, 7.382705 ]
+    292:
+      "+":
+        - [ 7.007262, 1.3e-05, 1.3e-05 ]
+        - [ 9e-06, 7.013971, -5.9e-05 ]
+        - [ 7e-06, -4.6e-05, 7.305084 ]
+      "-":
+        - [ 7.011688, 0, 2e-06 ]
+        - [ -2e-06, 7.009318, -7e-06 ]
+        - [ 4e-06, 9e-06, 7.306455 ]
+    293:
+      "+":
+        - [ 7.015281, 0.002384, -0 ]
+        - [ 0.002373, 7.005685, -4.4e-05 ]
+        - [ -4e-06, -2.8e-05, 7.3058 ]
+      "-":
+        - [ 7.015423, -0.002375, -9e-06 ]
+        - [ -0.00237, 7.005799, -7e-06 ]
+        - [ -8e-06, 1.1e-05, 7.305927 ]
+    311:
+      "+":
+        - [ 7.017108, 0.000122, -0.023832 ]
+        - [ 0.00013, 7.006382, -5.6e-05 ]
+        - [ -0.02384, -3.4e-05, 7.306937 ]
+      "-":
+        - [ 7.017506, 5e-06, 0.023741 ]
+        - [ -6e-06, 7.006811, -2e-06 ]
+        - [ 0.023733, 1.6e-05, 7.307537 ]
+    312:
+      "+":
+        - [ 7.010335, 7.8e-05, -4.6e-05 ]
+        - [ 8.4e-05, 7.013598, 0.023664 ]
+        - [ -4.1e-05, 0.023683, 7.307236 ]
+      "-":
+        - [ 7.010567, -1e-06, -3e-06 ]
+        - [ -9e-06, 7.013715, -0.023726 ]
+        - [ -4e-06, -0.023709, 7.307591 ]
+    327:
+      "+":
+        - [ 7.008517, 2.9e-05, -1.6e-05 ]
+        - [ 2.5e-05, 7.004613, -9.3e-05 ]
+        - [ -1.8e-05, -7.1e-05, 7.324773 ]
+      "-":
+        - [ 7.012664, -1e-05, 1e-06 ]
+        - [ -8e-06, 7.008951, -1.2e-05 ]
+        - [ 5e-06, 7e-06, 7.306262 ]
+    378:
+      "+":
+        - [ 7.012128, 1e-05, 1.8e-05 ]
+        - [ 1e-06, 7.008401, -1e-05 ]
+        - [ 1.3e-05, -1e-06, 7.322152 ]
+      "-":
+        - [ 7.012153, 1e-06, -1.3e-05 ]
+        - [ 9e-06, 7.008396, -1.4e-05 ]
+        - [ -1.9e-05, 3e-06, 7.322317 ]
+    379:
+      "+":
+        - [ 7.010873, -5.9e-05, -3.8e-05 ]
+        - [ -7.8e-05, 7.007166, -3.6e-05 ]
+        - [ -4.3e-05, -2.5e-05, 7.319279 ]
+      "-":
+        - [ 7.011186, -5e-06, -1.4e-05 ]
+        - [ 6e-06, 7.007443, -1e-06 ]
+        - [ -1.9e-05, 1.4e-05, 7.319705 ]
+    5:
+      "+":
+        - [ 7.007563, -0.001516, 5e-06 ]
+        - [ -0.001515, 7.00316, -5.5e-05 ]
+        - [ 0, -2.9e-05, 7.305665 ]
+      "-":
+        - [ 7.007833, 0.001555, -9e-06 ]
+        - [ 0.001554, 7.003468, -1.1e-05 ]
+        - [ -1.2e-05, 1e-05, 7.306111 ]
+    6:
+      "+":
+        - [ 7.005528, 1.8e-05, 4.1e-05 ]
+        - [ 1.2e-05, 7.005511, -3.7e-05 ]
+        - [ 3.7e-05, -1.5e-05, 7.30606 ]
+      "-":
+        - [ 7.008811, -2e-06, 4e-06 ]
+        - [ -5e-06, 7.002567, -3e-06 ]
+        - [ 7e-06, 1.7e-05, 7.306146 ]
+    9:
+      "+":
+        - [ 7.011048, 8e-05, -2.7e-05 ]
+        - [ 8.6e-05, 7.000001, 6e-06 ]
+        - [ -2.6e-05, 4.1e-05, 7.30555 ]
+      "-":
+        - [ 7.003087, -6e-06, 3e-06 ]
+        - [ -3e-06, 7.008199, -1e-06 ]
+        - [ 5e-06, 1.8e-05, 7.305867 ]
+Polarization:
+  - [ 0, 1, 0 ]
+  - [ 0, 1, 0 ]
+InputDataFile: data.zpp
+RamanInputDataFile: raman.zpp
+OutputDataFile: output.zpp
--- a/test/raman-apply-contribution/data.zpp
+++ b/test/raman-apply-contribution/data.zpp
--- a/test/raman-apply-contribution/raman.zpp
+++ b/test/raman-apply-contribution/raman.zpp
--- a/test/raman-create-displacement/.gitignore
+++ b/test/raman-create-displacement/.gitignore
@@ -0,0 +1,2 @@
+POSCAR
+output.zpp
--- a/test/raman-create-displacement/config.yaml
+++ b/test/raman-create-displacement/config.yaml
@@ -0,0 +1,7 @@
+Cell: Super
+SelectedModes: 
+  0: [ 0, 1, 2, 5, 6, 9, 10, 15, 16, 107, 115, 185, 251, 252, 281, 282, 287, 292, 293, 311, 312, 327, 378, 379 ]
+MaxDisplacement: 0.02
+OutputPoscarDirectory: POSCAR
+InputDataFile: data.zpp
+OutputDataFile: output.zpp
--- a/test/raman-create-displacement/data.zpp
+++ b/test/raman-create-displacement/data.zpp
--- a/test/raman-extract/.gitattributes
+++ b/test/raman-extract/.gitattributes
@@ -0,0 +1 @@
+OUTCAR filter=lfs diff=lfs merge=lfs -text
--- a/test/raman-extract/0/0/+/OUTCAR
+++ b/test/raman-extract/0/0/+/OUTCAR
--- a/test/raman-extract/0/0/-/OUTCAR
+++ b/test/raman-extract/0/0/-/OUTCAR
--- a/test/raman-extract/0/1/+/OUTCAR
+++ b/test/raman-extract/0/1/+/OUTCAR
--- a/test/raman-extract/0/1/-/OUTCAR
+++ b/test/raman-extract/0/1/-/OUTCAR
--- a/test/raman-extract/0/10/+/OUTCAR
+++ b/test/raman-extract/0/10/+/OUTCAR
--- a/test/raman-extract/0/10/-/OUTCAR
+++ b/test/raman-extract/0/10/-/OUTCAR
--- a/test/raman-extract/0/107/+/OUTCAR
+++ b/test/raman-extract/0/107/+/OUTCAR
--- a/test/raman-extract/0/107/-/OUTCAR
+++ b/test/raman-extract/0/107/-/OUTCAR
--- a/test/raman-extract/0/115/+/OUTCAR
+++ b/test/raman-extract/0/115/+/OUTCAR
--- a/test/raman-extract/0/115/-/OUTCAR
+++ b/test/raman-extract/0/115/-/OUTCAR
--- a/test/raman-extract/0/15/+/OUTCAR
+++ b/test/raman-extract/0/15/+/OUTCAR
--- a/test/raman-extract/0/15/-/OUTCAR
+++ b/test/raman-extract/0/15/-/OUTCAR
--- a/test/raman-extract/0/16/+/OUTCAR
+++ b/test/raman-extract/0/16/+/OUTCAR
--- a/test/raman-extract/0/16/-/OUTCAR
+++ b/test/raman-extract/0/16/-/OUTCAR
--- a/test/raman-extract/0/185/+/OUTCAR
+++ b/test/raman-extract/0/185/+/OUTCAR
--- a/test/raman-extract/0/185/-/OUTCAR
+++ b/test/raman-extract/0/185/-/OUTCAR
--- a/test/raman-extract/0/2/+/OUTCAR
+++ b/test/raman-extract/0/2/+/OUTCAR
--- a/test/raman-extract/0/2/-/OUTCAR
+++ b/test/raman-extract/0/2/-/OUTCAR
--- a/test/raman-extract/0/251/+/OUTCAR
+++ b/test/raman-extract/0/251/+/OUTCAR
--- a/test/raman-extract/0/251/-/OUTCAR
+++ b/test/raman-extract/0/251/-/OUTCAR
--- a/test/raman-extract/0/252/+/OUTCAR
+++ b/test/raman-extract/0/252/+/OUTCAR
--- a/test/raman-extract/0/252/-/OUTCAR
+++ b/test/raman-extract/0/252/-/OUTCAR
--- a/test/raman-extract/0/281/+/OUTCAR
+++ b/test/raman-extract/0/281/+/OUTCAR
--- a/test/raman-extract/0/281/-/OUTCAR
+++ b/test/raman-extract/0/281/-/OUTCAR
--- a/test/raman-extract/0/282/+/OUTCAR
+++ b/test/raman-extract/0/282/+/OUTCAR
--- a/test/raman-extract/0/282/-/OUTCAR
+++ b/test/raman-extract/0/282/-/OUTCAR
--- a/test/raman-extract/0/287/+/OUTCAR
+++ b/test/raman-extract/0/287/+/OUTCAR
--- a/test/raman-extract/0/287/-/OUTCAR
+++ b/test/raman-extract/0/287/-/OUTCAR
--- a/test/raman-extract/0/292/+/OUTCAR
+++ b/test/raman-extract/0/292/+/OUTCAR
--- a/test/raman-extract/0/292/-/OUTCAR
+++ b/test/raman-extract/0/292/-/OUTCAR
--- a/test/raman-extract/0/293/+/OUTCAR
+++ b/test/raman-extract/0/293/+/OUTCAR
--- a/test/raman-extract/0/293/-/OUTCAR
+++ b/test/raman-extract/0/293/-/OUTCAR
--- a/test/raman-extract/0/311/+/OUTCAR
+++ b/test/raman-extract/0/311/+/OUTCAR
--- a/test/raman-extract/0/311/-/OUTCAR
+++ b/test/raman-extract/0/311/-/OUTCAR
--- a/test/raman-extract/0/312/+/OUTCAR
+++ b/test/raman-extract/0/312/+/OUTCAR
--- a/test/raman-extract/0/312/-/OUTCAR
+++ b/test/raman-extract/0/312/-/OUTCAR
--- a/test/raman-extract/0/327/+/OUTCAR
+++ b/test/raman-extract/0/327/+/OUTCAR
--- a/test/raman-extract/0/327/-/OUTCAR
+++ b/test/raman-extract/0/327/-/OUTCAR
--- a/test/raman-extract/0/378/+/OUTCAR
+++ b/test/raman-extract/0/378/+/OUTCAR
--- a/test/raman-extract/0/378/-/OUTCAR
+++ b/test/raman-extract/0/378/-/OUTCAR
--- a/test/raman-extract/0/379/+/OUTCAR
+++ b/test/raman-extract/0/379/+/OUTCAR
--- a/test/raman-extract/0/379/-/OUTCAR
+++ b/test/raman-extract/0/379/-/OUTCAR
--- a/test/raman-extract/0/5/+/OUTCAR
+++ b/test/raman-extract/0/5/+/OUTCAR
--- a/test/raman-extract/0/5/-/OUTCAR
+++ b/test/raman-extract/0/5/-/OUTCAR
--- a/test/raman-extract/0/6/+/OUTCAR
+++ b/test/raman-extract/0/6/+/OUTCAR
--- a/test/raman-extract/0/6/-/OUTCAR
+++ b/test/raman-extract/0/6/-/OUTCAR
--- a/test/raman-extract/0/9/+/OUTCAR
+++ b/test/raman-extract/0/9/+/OUTCAR
--- a/test/raman-extract/0/9/-/OUTCAR
+++ b/test/raman-extract/0/9/-/OUTCAR
--- a/test/raman-extract/origin/OUTCAR
+++ b/test/raman-extract/origin/OUTCAR
--- a/test/unfold/.gitattributes
+++ b/test/unfold/.gitattributes
@@ -0,0 +1 @@
+*phonopy.yaml filter=lfs diff=lfs merge=lfs -text
--- a/test/unfold/.gitignore
+++ b/test/unfold/.gitignore
@@ -0,0 +1 @@
+unfold-output.zpp
--- a/test/unfold/config.yaml
+++ b/test/unfold/config.yaml
@@ -0,0 +1,13 @@
+SuperCellMultiplier: [4, 4, 1]
+SuperCellDeformation:
+  - [ 1, 0, 0 ]
+  - [ 0.5, 1, 0 ]
+  - [ 0, 0, 1 ]
+AtomTranslation: [ 0, 0, 0.5 ]
+PrimativeCellBasisNumber: [ 8, 8, 8 ]
+PrimativePhonopy: primitive-phonopy.yaml
+PrimativeQpoint: primitive-band.hdf5
+SuperPhonopy: super-phonopy.yaml
+SuperQpoint: super-qpoints.hdf5
+OutputFile: unfold-output.zpp
+
--- a/test/unfold/primitive-band.hdf5
+++ b/test/unfold/primitive-band.hdf5
--- a/test/unfold/primitive-phonopy.yaml
+++ b/test/unfold/primitive-phonopy.yaml
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
Haonan Chen	82ad565448	AtomTranslation 改为以超胞晶格矢为单位，而不是以埃为单位	2026-01-08 12:36:14 +08:00
Haonan Chen	cb7dd54e7f	一些小修改，应该不影响结果	2026-01-08 12:36:14 +08:00
Haonan Chen	19736049c9	fix build	2026-01-05 15:21:35 +08:00
chn	dc6b431bf9	fix raman tensor scaling	2025-11-05 12:05:12 +08:00
chn	32febb2843	Revert "fix raman tensor calculation scaling" This reverts commit `a54e769b24`.	2025-11-05 12:02:52 +08:00
chn	a54e769b24	fix raman tensor calculation scaling	2025-11-05 11:37:44 +08:00
chn	8a137d5342	a little improvement in code (should not change result)	2025-10-11 14:45:59 +08:00
chn	b21a8fb198	Revert "fix raman" This reverts commit `2ddfca800a`.	2025-10-11 10:18:55 +08:00
chn	2ddfca800a	fix raman	2025-10-10 16:29:16 +08:00
chn	745353d089	project-to-atom: fix	2025-04-01 18:15:43 +08:00
chn	c4c549c669	project-to-atom: add test	2025-04-01 17:30:01 +08:00
chn	388c77db5f	remove unused config	2025-04-01 17:22:26 +08:00
chn	d4578c7991	fix	2024-12-24 17:47:02 +08:00
chn	f871c28768	修改拉曼输出文件布局	2024-12-22 15:53:11 +08:00
chn	d584951fd7	fix raman, add test	2024-12-04 15:21:09 +08:00
chn	6e64054ffc	fix	2024-12-03 19:11:48 +08:00
chn	0c073b73b5	clean up	2024-12-03 18:15:28 +08:00
chn	bf3c8430ed	解决bug	2024-12-03 17:56:22 +08:00
chn	eb6b903417	写了 project_to_mode 但还没调试好	2024-12-03 16:25:17 +08:00
chn	3f98ce8378	add zpp-to-yaml test	2024-12-02 18:51:17 +08:00
chn	7b4ea3bbf3	add unfold test	2024-12-02 18:27:40 +08:00
chn	db1d3befd6	重构	2024-12-02 15:47:33 +08:00
chn	b94823f8aa	add raman support	2024-11-24 22:13:29 +08:00
chn	28e4d29f2c	init	2024-11-21 16:18:06 +08:00
				`@@ -0,0 +1 @@`
				`*phonopy.yaml filter=lfs diff=lfs merge=lfs -text`