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mean squared displacement

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Mo8it 2022-01-23 03:05:05 +01:00
parent e471c4072c
commit c5d92348f8

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using CairoMakie
using LaTeXStrings: @L_str
using Dates: Dates
using Random: Random
using StaticArrays: SVector
using JLD2: JLD2
using ReCo: ReCo
# Disable the periodic boundary conditions
ReCo.update_verlet_lists!(args...) = nothing
ReCo.gen_cell_list(args...) = nothing
ReCo.gen_cell_list_box(args...) = nothing
ReCo.push_to_verlet_list!(args...) = nothing
ReCo.restrict_coordinate(value::Float64, args...) = value
ReCo.restrict_coordinates(v::SVector{2,Float64}, args...) = v
ReCo.restrict_coordinates!(args...) = nothing
ReCo.minimum_image_coordinate(value::Float64, args...) = value
ReCo.minimum_image(v::SVector{2,Float64}, args...) = v
function mean_squared_displacement(;
n_simulations::Int64, v₀s::AbstractVector{Float64}, T::Float64
)
Random.seed!(42)
n_v₀s = length(v₀s)
δt = ReCo.DEFAULT_δt
Dₜ = ReCo.DEFAULT_Dₜ
main_parent_dir = "mean_squared_displacement_$(Dates.now())"
mkpath(main_parent_dir)
sim_dirs = Matrix{String}(undef, (n_simulations, n_v₀s))
for (v₀_ind, v₀) in enumerate(v₀s)
max_possible_displacement = T * v₀ + T / δt * sqrt(2 * Dₜ * δt)
parent_dir = main_parent_dir * "/$v₀"
Threads.@threads for sim_ind in 1:n_simulations
dir = ReCo.init_sim(;
n_particles=1,
v₀=v₀,
parent_dir=parent_dir,
comment="$sim_ind",
half_box_len=max_possible_displacement,
)
sim_dirs[sim_ind, v₀_ind] = dir
ReCo.run_sim(dir; duration=T, seed=rand(1:typemax(Int64)), snapshot_at=0.01)
end
end
ts = Float64[]
bundle_paths = ReCo.sorted_bundle_paths(sim_dirs[1, 1])
for i in 2:length(bundle_paths) # Skip the first bundle to avoid t = 0
bundle::ReCo.Bundle = JLD2.load_object(bundle_paths[i])
append!(ts, bundle.t)
end
mean_sq_displacements = zeros((length(ts), n_v₀s))
@simd for v₀_ind in 1:n_v₀s
for sim_ind in 1:n_simulations
sim_dir = sim_dirs[sim_ind, v₀_ind]
bundle_paths = ReCo.sorted_bundle_paths(sim_dir)
snapshot_ind = 1
for i in 2:length(bundle_paths)
bundle::ReCo.Bundle = JLD2.load_object(bundle_paths[i])
for c in bundle.c
sq_displacement = ReCo.sq_norm2d(c)
mean_sq_displacements[snapshot_ind, v₀_ind] += sq_displacement
snapshot_ind += 1
end
end
end
end
mean_sq_displacements ./= n_simulations
return (ts, mean_sq_displacements)
end
function expected_mean_squared_displacement(t::Float64, v₀::Float64)
Dₜ = ReCo.DEFAULT_Dₜ
particle_radius = ReCo.DEFAULT_PARTICLE_RADIUS
Dᵣ = 3 * Dₜ / ((2 * particle_radius)^2)
return (4 * Dₜ + 2 * v₀^2 / Dᵣ) * t + 2 * v₀^2 * (exp(-Dᵣ * t) - 1) / (Dᵣ^2)
end
function plot_mean_sq_displacement_with_expectation(
ts::Vector{Float64},
mean_sq_displacements::Matrix{Float64},
v₀s::AbstractVector{Float64},
)
CairoMakie.activate!()
set_theme!()
text_width_in_pt = 405
fig = Figure(;
resolution=(text_width_in_pt, 0.55 * text_width_in_pt),
fontsize=10,
figure_padding=1,
)
ax = Axis(fig[1, 1]; xlabel=L"t", ylabel=L"\mathbf{MSD}", xscale=log10, yscale=log10)
t_linrange = LinRange(ts[1], ts[end], 1000)
v₀_scatter_plots = []
for (v₀_ind, v₀) in enumerate(v₀s)
scatter_plot = scatter!(
ax, ts, view(mean_sq_displacements, :, v₀_ind); markersize=4
)
push!(v₀_scatter_plots, scatter_plot)
expected_mean_sq_displacements = expected_mean_squared_displacement.(t_linrange, v₀)
lines!(ax, t_linrange, expected_mean_sq_displacements)
end
Legend(fig[1, 2], v₀_scatter_plots, [L"v₀ = %$v₀" for v₀ in v₀s])
colgap!(fig.layout, 5)
rowgap!(fig.layout, 5)
parent_dir = "exports/graphics/"
mkpath(parent_dir)
save("$parent_dir/mean_squared_displacement.pdf", fig; pt_per_unit=1)
return nothing
end
function run_analysis()
v₀s = SVector(0.0, 20.0, 40.0, 60.0, 80.0)
ts, mean_sq_displacements = mean_squared_displacement(;
n_simulations=3 * Threads.nthreads(), v₀s=v₀s, T=10.0
)
plot_mean_sq_displacement_with_expectation(ts, mean_sq_displacements, v₀s)
return nothing
end
# run_analysis()