Added some comments and test example

src/DynamicsMethods/ClassicalMethods/diabatic_mdef.jl

@@ -14,7 +14,12 @@ end
 function DiabaticMDEF(masses::AbstractVector, DoFs::Integer, friction_method)
     DiabaticMDEF(get_mass_scale_matrix(masses, DoFs), friction_method)
 end
+"""
+    当你在生成 simulation 时, method 选择了 DiabaticMDEF
 
+    电脑会选择跑下面这段代码
+
+"""
 function NQCDynamics.Simulation{DiabaticMDEF}(atoms::Atoms, model::Model;
     friction_method, kwargs...
 )
@@ -136,17 +141,38 @@ function (friction_method::DirectQuadrature)(∂Hᵢ, ∂Hⱼ, eigenvalues, μ,
     return out
 end
 
+"""
+WideBandExact is a method to evaulate friction that is exact for a wide band limit.
+
+    The function contains mainly three parts/steps:
+        1.struct type WideBandExact
+        2.compute the integral in the friction kernel
+        3.fill the friction tensor to evaluate_friction!
+
+    Usage: (potential, ∂potentialᵢ, ∂potentialⱼ) should be given
+
+
+    1.friction_method = WideBandExact(ρ, β)
+
+    2.integral = friction_method(potential, ∂potentialᵢ, ∂potentialⱼ, μ, β)
+
+    3.fill_friction_tensor!(Λ, friction_method::WideBandExact, potential, derivative, r, μ)
+
+    The friction integral details is given in https://doi.org/10.1063/5.0137137 (Eq.33-34)
+
+"""
 struct WideBandExact{T} <: FrictionEvaluationMethod
     ρ::T
     β::T
 end
 function (friction_method::WideBandExact)(potential, ∂potentialᵢ, ∂potentialⱼ, μ, β)
+    # Read reference paper from the details
     h = potential[1,1]
     ∂hᵢ = ∂potentialᵢ[1,1]
     ∂hⱼ = ∂potentialⱼ[1,1]
 
     ρ = friction_method.ρ
-    Γ = 2π * potential[2,1]^2 * ρ
+    Γ = 2π * potential[2,1]^2 * ρ # hybridization function Γ = 2π * |V|^2 * ρ
     ∂Γ∂potential = sqrt(8π * ρ * Γ)
     ∂Γᵢ = ∂Γ∂potential * ∂potentialᵢ[2,1]
     ∂Γⱼ = ∂Γ∂potential * ∂potentialⱼ[2,1]

src/DynamicsMethods/DynamicsMethods.jl

@@ -32,6 +32,8 @@ export run_trajectory
 Each type of dynamics subtypes `Method` which is passed to
 the `AbstractSimulation` as a parameter to determine the type of
 dynamics desired.
+
+julia> ttree(DynamicsMethods.Method)
 """
 abstract type Method end
 

src/DynamicsMethods/IntegrationAlgorithms/IntegrationAlgorithms.jl

@@ -53,6 +53,14 @@ struct VerletwithElectronics <: OrdinaryDiffEq.OrdinaryDiffEqAlgorithm end
 struct MDEF_BAOAB <: StochasticDiffEq.StochasticDiffEqAlgorithm end
 struct BCOCB <: StochasticDiffEq.StochasticDiffEqAlgorithm end
 
+
+"""
+This block of code below is to select the algorithm for each type of simulation.
+
+
+
+"""
+
 DynamicsMethods.select_algorithm(::RingPolymerSimulation{<:DynamicsMethods.SurfaceHoppingMethods.SurfaceHopping}) = BCBwithTsit5(OrdinaryDiffEq.Tsit5())
 DynamicsMethods.select_algorithm(::RingPolymerSimulation{<:DynamicsMethods.EhrenfestMethods.AbstractEhrenfest}) = BCBwithTsit5(OrdinaryDiffEq.Tsit5())
 DynamicsMethods.select_algorithm(::Simulation{<:DynamicsMethods.ClassicalMethods.AbstractMDEF}) = MDEF_BAOAB()

src/Ensembles/selections.jl

@@ -1,6 +1,11 @@
 
 using NQCDistributions: DynamicalDistribution, ProductDistribution
 
+"""
+Check the tree structure of the type.
+julia> ttree(Ensembles.AbstractSelection)
+"""
+
 abstract type AbstractSelection end
 
 """

test/Hokseson_test/struct-function_same_name

@@ -0,0 +1,31 @@
+# Define a simple type named Point
+struct Point
+    x
+    y::Float64
+end
+
+
+
+# Constructor function for Point
+# 由于我们设置多了一个变量 t， 所以我们在call Point的时候
+# 多一个参数 t 就跑 function
+# 总结！定义 同名 function 用来 丰富 struct的功能
+function Point(x::Float64, y::Float64, t::Bool)
+    # This function is defined to convert x to Int64 if t is true otherwise leave it as Float64
+    if t == true
+        x = convert(Int64, x)
+    end
+
+    Point(x, y)
+end
+
+# Create an instance of Point using the constructor function
+my_point = Point(3.0, 4.0, true)
+
+# 直接跑 struct 创造 object
+# my_point = Point(3.0, 4.0)
+
+# Display the created instance
+println("Point Instance:")
+println("x: ", my_point.x)
+println("y: ", my_point.y)