mirror of
https://gitlab.rlp.net/mobitar/ReCo.jl.git
synced 2024-09-19 19:01:17 +00:00
Added radial distribution function
This commit is contained in:
Mo8it
parent
6cbc855e45
commit
3e02920067
10 changed files with 481 additions and 202 deletions
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@ -5,9 +5,11 @@ version = "0.2.0"
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[deps]
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BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
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CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
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CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0"
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CellListMap = "69e1c6dd-3888-40e6-b3c8-31ac5f578864"
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ColorSchemes = "35d6a980-a343-548e-a6ea-1d62b119f2f4"
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DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
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Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
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Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
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Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
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@ -9,6 +9,8 @@ using ProgressMeter: ProgressMeter
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using ReCo: ReCo
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includet("../graphics/common_CairoMakie.jl")
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# IMPORTANT: Disable the periodic boundary conditions
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# The arguments types have to match for the function to be overwritten!
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ReCo.push_to_verlet_list!(::Any, ::Any, ::Any) = nothing
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@ -26,20 +28,6 @@ ReCo.minimum_image(v::SVector{2,Float64}, ::Float64) = v
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const δt = 1e-4
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const Dₜ = ReCo.DEFAULT_Dₜ
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function fill_with_bundle_property!(
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v::Vector, property::Symbol, sim_dir::String, first_bundle::Int64=1
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)
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bundle_paths = ReCo.sorted_bundle_paths(sim_dir)
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for i in first_bundle:length(bundle_paths)
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bundle::ReCo.Bundle = JLD2.load_object(bundle_paths[i])
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append!(v, getproperty(bundle, property))
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end
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return nothing
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end
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function max_possible_displacement(T::Float64, v₀::Float64, δt::Float64=δt, Dₜ::Float64=Dₜ)
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return T * v₀ + T / δt * sqrt(2 * Dₜ * δt)
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end
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@ -52,6 +40,8 @@ function msd_simulation(
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parent_dir::String,
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comment::String="",
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)
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Random.seed!(42)
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dir = ReCo.init_sim(;
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n_particles=1,
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v₀=v₀,
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@ -72,10 +62,8 @@ function msd_simulation(
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end
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function mean_squared_displacement(;
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n_simulations::Int64, v₀s::AbstractVector{Float64}, T::Float64
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)
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Random.seed!(42)
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n_simulations::Int64, v₀s::NTuple{N,Float64}, T::Float64
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) where {N}
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n_v₀s = length(v₀s)
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main_parent_dir = "mean_squared_displacement_$(Dates.now())"
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@ -99,7 +87,9 @@ function mean_squared_displacement(;
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end
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ts = Float64[]
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fill_with_bundle_property!(ts, :t, sim_dirs[1, 1], 2) # Skip the first bundle to avoid t = 0
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ReCo.append_bundle_properties!(
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(ts,), (:t,), sim_dirs[1, 1]; particle_slice=1, snapshot_slice=:, first_bundle=2
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) # Skip the first bundle to avoid t = 0
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mean_sq_displacements = zeros((length(ts), n_v₀s))
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@ -137,42 +127,9 @@ function expected_mean_squared_displacement(t::Float64, v₀::Float64)
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return (4 * Dₜ + 2 * v₀^2 / Dᵣ) * t + 2 * v₀^2 * (exp(-Dᵣ * t) - 1) / (Dᵣ^2)
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end
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function init_cairomakie!()
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CairoMakie.activate!()
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set_theme!()
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return nothing
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end
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function gen_figure()
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text_width_in_pt = 405
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return Figure(;
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resolution=(text_width_in_pt, 0.55 * text_width_in_pt),
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fontsize=10,
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figure_padding=1,
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)
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end
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function set_gaps!(fig::Figure)
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colgap!(fig.layout, 5)
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rowgap!(fig.layout, 5)
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return nothing
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end
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function save_fig(filename::String, fig::Figure)
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parent_dir = "exports/graphics"
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mkpath(parent_dir)
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return save("$parent_dir/$filename", fig; pt_per_unit=1)
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end
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function plot_mean_sq_displacement_with_expectation(
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ts::Vector{Float64},
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mean_sq_displacements::Matrix{Float64},
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v₀s::AbstractVector{Float64},
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)
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ts::Vector{Float64}, mean_sq_displacements::Matrix{Float64}, v₀s::NTuple{N,Float64}
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) where {N}
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init_cairomakie!()
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fig = gen_figure()
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@ -205,7 +162,7 @@ function plot_mean_sq_displacement_with_expectation(
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end
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function run_msd_analysis()
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v₀s = SVector(0.0, 20.0, 40.0, 60.0, 80.0)
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v₀s = (0.0, 20.0, 40.0, 60.0, 80.0)
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ts, mean_sq_displacements = mean_squared_displacement(;
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n_simulations=200 * Threads.nthreads(), v₀s=v₀s, T=100.0
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@ -216,17 +173,17 @@ function run_msd_analysis()
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return nothing
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end
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function plot_random_walk(T::Float64, v₀::Float64, seed::Int64)
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function plot_random_walk(; T::Float64, v₀::Float64, seed::Int64)
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Random.seed!(seed)
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half_box_len = max_possible_displacement(T, v₀)
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dir = msd_simulation(v₀, half_box_len, T, 8.0, "random_walk_$(Dates.now())")
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ts = Float64[]
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fill_with_bundle_property!(ts, :t, dir)
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cs = SVector{2,Float64}[]
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fill_with_bundle_property!(cs, :c, dir)
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ReCo.append_bundle_properties!(
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(ts, cs), (:t, :c), dir; particle_slice=1, snapshot_slice=:
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)
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init_cairomakie!()
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@ -281,7 +238,7 @@ function plot_random_walk(T::Float64, v₀::Float64, seed::Int64)
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end
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function run_random_walk()
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plot_random_walk(100_000.0, 0.0, 12345)
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plot_random_walk(; T=100_000.0, v₀=0.0, seed=12345)
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return nothing
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end
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@ -1,28 +0,0 @@
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if splitdir(pwd())[2] == "analysis"
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cd("..")
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end
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if splitdir(pwd())[2] != "ReCo.jl"
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error("You have to be in the main directeory ReCo.jl!")
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else
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include("src/analysis/pair_correlation_function.jl")
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end
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##
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using JLD2: JLD2
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using CairoMakie
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CairoMakie.activate!()
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set_theme!(theme_black())
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##
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dirs = readdir("exports/2021_11_19"; join=true)
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##
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for dir in dirs
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data = JLD2.load("$dir/data.jld2")
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display(pair_correlation(data["sol"], data["variables"]).fig)
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end
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@ -0,0 +1,149 @@
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# Source: https://www.researchgate.net/publication/223333736_Reconstruction_of_Ross'_linear-mixing_model_for_the_equation_of_state_of_deuterium
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r_d_ratio,g_of_r_d_ratio
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0.99392,0.08604
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0.99388,0.18421
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0.99384,0.28847
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0.99382,0.34463
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0.99378,0.42994
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0.99372,0.52947
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0.99365,0.63441
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0.99361,0.68891
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0.99354,0.77406
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0.99344,0.87468
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0.99332,0.98013
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0.99325,1.03317
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0.99314,1.11822
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0.99297,1.21964
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0.99278,1.32539
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0.99267,1.37722
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0.99249,1.4622
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0.99224,1.56412
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0.99194,1.67
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0.99179,1.72089
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0.99152,1.8058
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0.99116,1.90793
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0.99074,2.01372
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0.99053,2.06399
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0.99015,2.1488
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0.98965,2.25086
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0.98909,2.35636
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0.98881,2.40637
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0.98831,2.49108
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0.98767,2.5925
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0.98699,2.69664
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0.98665,2.74669
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0.98607,2.83091
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0.98538,2.92885
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0.98467,3.02834
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0.98395,3.12761
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0.98362,3.17414
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0.98304,3.25677
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0.98242,3.34772
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0.98183,3.43776
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0.98129,3.52581
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0.98081,3.61118
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0.98043,3.69358
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0.98015,3.77322
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0.98,3.85156
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0.98014,3.95169
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0.98089,4.03823
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0.98357,4.10894
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0.9944,4.032
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1.00014,3.93792
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1.00441,3.85868
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1.00862,3.77571
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1.01272,3.69218
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1.01669,3.61072
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1.0216,3.51176
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1.02638,3.42062
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1.03128,3.33517
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1.03664,3.25085
|
||||
1.04281,3.16285
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1.04804,3.09295
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1.05614,2.98982
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1.06293,2.90588
|
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1.07039,2.81547
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1.07549,2.75441
|
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1.08352,2.65945
|
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1.09202,2.56047
|
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1.09758,2.49642
|
||||
1.10625,2.39796
|
||||
1.11214,2.33189
|
||||
1.12071,2.23742
|
||||
1.12939,2.14379
|
||||
1.13793,2.05435
|
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1.14612,1.97171
|
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1.15388,1.89756
|
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1.16359,1.81176
|
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1.17456,1.72585
|
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1.18615,1.64833
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1.19996,1.56268
|
||||
1.21169,1.47967
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1.22345,1.39143
|
||||
1.23543,1.30583
|
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1.24773,1.23043
|
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1.26375,1.14911
|
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1.28235,1.06205
|
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1.30026,0.97628
|
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1.32001,0.89731
|
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1.34607,0.8185
|
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1.38029,0.74139
|
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1.42373,0.67706
|
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1.47928,0.62965
|
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1.54985,0.64005
|
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1.60887,0.68208
|
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1.65956,0.742
|
||||
1.70693,0.80174
|
||||
1.75549,0.86677
|
||||
1.7997,0.93281
|
||||
1.8408,0.99879
|
||||
1.88278,1.07151
|
||||
1.92418,1.14479
|
||||
1.96069,1.20961
|
||||
2.00089,1.27998
|
||||
2.06624,1.29427
|
||||
2.12188,1.24296
|
||||
2.16454,1.1732
|
||||
2.20365,1.10578
|
||||
2.2468,1.03273
|
||||
2.28968,0.97094
|
||||
2.34711,0.92061
|
||||
2.40659,0.87706
|
||||
2.47617,0.86598
|
||||
2.54506,0.87775
|
||||
2.6091,0.91495
|
||||
2.67198,0.9548
|
||||
2.73415,0.99707
|
||||
2.79524,1.03776
|
||||
2.86004,1.06782
|
||||
2.92949,1.08716
|
||||
2.99726,1.09694
|
||||
3.06572,1.07401
|
||||
3.13305,1.0512
|
||||
3.20406,1.01975
|
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3.26722,0.99225
|
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3.33163,0.96833
|
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3.40415,0.95312
|
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3.46976,0.95561
|
||||
3.53944,0.96948
|
||||
3.61034,0.98695
|
||||
3.68191,1.00826
|
||||
3.74431,1.02656
|
||||
3.81351,1.04126
|
||||
3.88832,1.04634
|
||||
3.95948,1.04227
|
||||
4.02721,1.03357
|
||||
4.09307,1.02294
|
||||
4.16757,1.01022
|
||||
4.23256,0.99784
|
||||
4.30367,0.98757
|
||||
4.3786,0.98803
|
||||
4.44527,0.99118
|
||||
4.51289,0.99726
|
||||
4.58223,1.00774
|
||||
4.65288,1.01261
|
||||
4.72314,1.01386
|
||||
4.79174,1.02311
|
||||
4.86131,1.03134
|
||||
4.93191,1.0253
|
||||
4.98585,1.01943
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|
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@ -0,0 +1,216 @@
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using CairoMakie
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using LaTeXStrings: @L_str
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using StaticArrays: SVector
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using JLD2: JLD2
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using Dates: Dates
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using CSV: CSV
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using DataFrames: DataFrames
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using Random: Random
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using ReCo: ReCo
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includet("../../graphics/common_CairoMakie.jl")
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function radial_distribution_simulation(;
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n_particles::Int64, v₀s::NTuple{N,Float64}, T::Float64, packing_ratio::Float64
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) where {N}
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Random.seed!(42)
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n_v₀s = length(v₀s)
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sim_dirs = Vector{String}(undef, n_v₀s)
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parent_dir = "radial_distribution_$(Dates.now())"
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Threads.@threads for v₀_ind in 1:n_v₀s
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v₀ = v₀s[v₀_ind]
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dir = ReCo.init_sim(;
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n_particles=n_particles,
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v₀=v₀,
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packing_ratio=packing_ratio,
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parent_dir=parent_dir,
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comment="$v₀",
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)
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ReCo.run_sim(dir; duration=T, seed=v₀_ind)
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sim_dirs[v₀_ind] = dir
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end
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return sim_dirs
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end
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function circular_shell_volume(lower_radius, Δradius)
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return π * (2 * lower_radius * Δradius + Δradius^2)
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end
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function radial_distribution(;
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sim_dirs::Vector{String}, n_radii::Int64, n_last_snapshots::Int64, n_particles::Int64
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)
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sim_consts::ReCo.SimConsts = JLD2.load_object("$(sim_dirs[1])/sim_consts.jld2")
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particle_radius = sim_consts.particle_radius
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min_lower_radius = 0.0
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max_lower_radius = 5 * (2 * particle_radius)
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Δradius = (max_lower_radius - min_lower_radius) / n_radii
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lower_radii = LinRange(min_lower_radius, max_lower_radius, n_radii)
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box_volume = (2 * sim_consts.half_box_len)^2
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volume_per_particle = box_volume / n_particles
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n_sim_dirs = length(sim_dirs)
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gs = Vector{Vector{Float64}}(undef, n_sim_dirs)
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Threads.@threads for sim_dir_ind in 1:n_sim_dirs
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sim_dir = sim_dirs[sim_dir_ind]
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cs = Matrix{SVector{2,Float64}}(undef, (n_particles, n_last_snapshots))
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bundle_paths = ReCo.sorted_bundle_paths(sim_dir; rev=true)
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snapshot_conunter = 0
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break_bundle_path_loop = false
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for bundle_path in bundle_paths
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bundle::ReCo.Bundle = JLD2.load_object(bundle_path)
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for snapshot_ind in (bundle.n_snapshots):-1:1
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snapshot_conunter += 1
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@simd for particle_ind in 1:n_particles
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cs[particle_ind, snapshot_conunter] = bundle.c[
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particle_ind, snapshot_ind
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]
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end
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if snapshot_conunter == n_last_snapshots
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break_bundle_path_loop = true
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break
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end
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end
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if break_bundle_path_loop
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break
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end
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end
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if snapshot_conunter != n_last_snapshots
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error("snapshot_conunter != n_last_snapshots")
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end
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g = zeros(n_radii)
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|
||||
for snapshot_ind in 1:n_last_snapshots
|
||||
for p1_ind in 1:n_particles
|
||||
for p2_ind in (p1_ind + 1):n_particles
|
||||
c1 = cs[p1_ind, snapshot_ind]
|
||||
c2 = cs[p2_ind, snapshot_ind]
|
||||
|
||||
r⃗₁₂ = c2 - c1
|
||||
r⃗₁₂ = ReCo.minimum_image(r⃗₁₂, sim_consts.half_box_len)
|
||||
|
||||
distance = ReCo.norm2d(r⃗₁₂)
|
||||
|
||||
lower_radius_ind = ceil(Int64, distance / Δradius)
|
||||
|
||||
if lower_radius_ind <= n_radii
|
||||
g[lower_radius_ind] += 2
|
||||
end
|
||||
end
|
||||
end
|
||||
end
|
||||
|
||||
for (lower_radius_ind, lower_radius) in enumerate(lower_radii)
|
||||
g[lower_radius_ind] *=
|
||||
volume_per_particle / (
|
||||
n_last_snapshots *
|
||||
n_particles *
|
||||
circular_shell_volume(lower_radius, Δradius)
|
||||
)
|
||||
end
|
||||
|
||||
gs[sim_dir_ind] = g
|
||||
end
|
||||
|
||||
return (lower_radii, gs, particle_radius)
|
||||
end
|
||||
|
||||
function plot_radial_distributions(
|
||||
v₀s::NTuple{N,Float64},
|
||||
lower_radii::AbstractVector{Float64},
|
||||
gs::Vector{Vector{Float64}},
|
||||
particle_radius::Float64,
|
||||
) where {N}
|
||||
println("Plotting the radial distributions")
|
||||
|
||||
init_cairomakie!()
|
||||
|
||||
fig = gen_figure()
|
||||
|
||||
max_lower_radius = maximum(lower_radii)
|
||||
max_g = maximum(maximum.(gs))
|
||||
|
||||
ax = Axis(
|
||||
fig[1:2, 1:2];
|
||||
xticks=0:(2 * particle_radius):ceil(Int64, max_lower_radius),
|
||||
yticks=0:ceil(Int64, max_g),
|
||||
xlabel=L"r / d",
|
||||
ylabel=L"g",
|
||||
)
|
||||
|
||||
lines!(
|
||||
ax,
|
||||
SVector(0.0, max_lower_radius),
|
||||
SVector(1.0, 1.0);
|
||||
linestyle=:dash,
|
||||
color=:red,
|
||||
linewidth=1,
|
||||
)
|
||||
|
||||
expected = CSV.read(
|
||||
"analysis/g_of_r_d_ratio_with_0_45_packing_ratio.csv",
|
||||
DataFrames.DataFrame;
|
||||
header=2,
|
||||
)
|
||||
lines!(
|
||||
ax,
|
||||
expected.r_d_ratio,
|
||||
expected.g_of_r_d_ratio;
|
||||
label="Expectation for dense hard spheres",
|
||||
color=:green,
|
||||
)
|
||||
|
||||
for (g_ind, g) in enumerate(gs)
|
||||
scatterlines!(
|
||||
ax, lower_radii, g; markersize=3, linewidth=0.5, label=L"v_0 = %$(v₀s[g_ind])"
|
||||
)
|
||||
end
|
||||
|
||||
axislegend(ax; position=:rt, padding=3, rowgap=-3)
|
||||
|
||||
save_fig("radial_distribution.pdf", fig)
|
||||
|
||||
return nothing
|
||||
end
|
||||
|
||||
function run_radial_distribution_analysis()
|
||||
v₀s = (0.0, 80.0)
|
||||
|
||||
n_particles = 1000
|
||||
|
||||
sim_dirs = radial_distribution_simulation(;
|
||||
n_particles=n_particles, v₀s=v₀s, T=100.0, packing_ratio=0.45
|
||||
)
|
||||
|
||||
lower_radii, gs, particle_radius = radial_distribution(;
|
||||
sim_dirs=sim_dirs, n_radii=75, n_last_snapshots=200, n_particles=n_particles
|
||||
)
|
||||
|
||||
plot_radial_distributions(v₀s, lower_radii, gs, particle_radius)
|
||||
|
||||
return nothing
|
||||
end
|
||||
29
graphics/common_CairoMakie.jl
Normal file
29
graphics/common_CairoMakie.jl
Normal file
|
|
@ -0,0 +1,29 @@
|
|||
function init_cairomakie!()
|
||||
CairoMakie.activate!()
|
||||
set_theme!()
|
||||
|
||||
return nothing
|
||||
end
|
||||
|
||||
function gen_figure(; padding=4)
|
||||
text_width_in_pt = 405
|
||||
|
||||
return Figure(;
|
||||
resolution=(text_width_in_pt, 0.55 * text_width_in_pt),
|
||||
fontsize=10,
|
||||
figure_padding=padding,
|
||||
)
|
||||
end
|
||||
|
||||
function set_gaps!(fig::Figure)
|
||||
colgap!(fig.layout, 5)
|
||||
rowgap!(fig.layout, 5)
|
||||
|
||||
return nothing
|
||||
end
|
||||
|
||||
function save_fig(filename::String, fig::Figure, parent_dir="exports/graphics")
|
||||
mkpath(parent_dir)
|
||||
|
||||
return save("$parent_dir/$filename", fig; pt_per_unit=1)
|
||||
end
|
||||
|
|
@ -1,6 +1,8 @@
|
|||
using CairoMakie
|
||||
using LaTeXStrings: @L_str
|
||||
|
||||
includet("common_CairoMakie.jl")
|
||||
|
||||
const minimum_r_σ_ratio = 2^(1 / 6)
|
||||
|
||||
function U_LJ_ϵ_ratio(r_σ_ratio::Real)
|
||||
|
|
@ -16,11 +18,10 @@ function U_WCA_ϵ_ratio(r_σ_ratio::Real)
|
|||
end
|
||||
end
|
||||
|
||||
text_width_in_pt = 405
|
||||
function plot_potentials()
|
||||
init_cairomakie!()
|
||||
|
||||
fig = Figure(;
|
||||
resolution=(text_width_in_pt, 0.55 * text_width_in_pt), fontsize=10, figure_padding=1
|
||||
)
|
||||
fig = gen_figure()
|
||||
|
||||
max_x = 2.5
|
||||
|
||||
|
|
@ -36,7 +37,11 @@ LJ = lines!(ax, r_σ_ratio, U_LJ_ϵ_ratio.(r_σ_ratio))
|
|||
WCA = lines!(ax, r_σ_ratio, U_WCA_ϵ_ratio.(r_σ_ratio))
|
||||
|
||||
minimum_r_σ_ratio_line = lines!(
|
||||
ax, [minimum_r_σ_ratio, minimum_r_σ_ratio], [min_y, max_y]; linestyle=:dash, linewidth=1
|
||||
ax,
|
||||
[minimum_r_σ_ratio, minimum_r_σ_ratio],
|
||||
[min_y, max_y];
|
||||
linestyle=:dash,
|
||||
linewidth=1,
|
||||
)
|
||||
|
||||
Legend(
|
||||
|
|
@ -45,7 +50,9 @@ Legend(
|
|||
[L"U_{LJ}", L"U_{WCA}", L"\frac{r}{σ} = 2^{1/6}"],
|
||||
)
|
||||
|
||||
colgap!(fig.layout, 5)
|
||||
rowgap!(fig.layout, 5)
|
||||
set_gaps!(fig)
|
||||
|
||||
save("exports/graphics/potential.pdf", fig; pt_per_unit=1)
|
||||
save_fig("potential.pdf", fig)
|
||||
|
||||
return nothing
|
||||
end
|
||||
|
|
@ -124,12 +124,7 @@ function run_rl(;
|
|||
agent(PRE_EPISODE_STAGE, env)
|
||||
|
||||
# Episode
|
||||
ReCo.run_sim(
|
||||
dir;
|
||||
duration=episode_duration,
|
||||
seed=rand(1:typemax(Int64)),
|
||||
env_helper=env_helper,
|
||||
)
|
||||
ReCo.run_sim(dir; duration=episode_duration, seed=episode, env_helper=env_helper)
|
||||
|
||||
env.shared.terminated = true
|
||||
|
||||
|
|
|
|||
|
|
@ -1,83 +0,0 @@
|
|||
using CairoMakie, LaTeXStrings
|
||||
using LoopVectorization: @turbo
|
||||
|
||||
using ReCo: minimum_image, norm2d
|
||||
|
||||
function plot_g(radius, g, variables)
|
||||
fig = Figure()
|
||||
ax = Axis(
|
||||
fig[1, 1];
|
||||
xticks=0:ceil(Int64, maximum(radius)),
|
||||
yticks=0:ceil(Int64, maximum(g)),
|
||||
xlabel=L"r",
|
||||
ylabel=L"g(r)",
|
||||
title="v₀ = $(variables.v₀)",
|
||||
)
|
||||
|
||||
scatterlines!(ax, radius, g; color=:white, markercolor=:red)
|
||||
|
||||
return fig
|
||||
end
|
||||
|
||||
function pair_correlation(sol, variables)
|
||||
n_r = 100
|
||||
n_last_frames = 200
|
||||
min_radius = variables.particle_diameter / 2
|
||||
max_radius = 10.0 * variables.particle_diameter
|
||||
dr = (max_radius - min_radius) / n_r
|
||||
|
||||
radius = range(min_radius, max_radius; length=n_r)
|
||||
N_g = zeros(variables.n_particles, n_r)
|
||||
|
||||
Threads.@threads for r_ind in 1:n_r
|
||||
r = radius[r_ind]
|
||||
|
||||
@simd for i in 1:(variables.n_particles)
|
||||
for j in 1:(variables.n_particles)
|
||||
if i != j
|
||||
for k in 1:n_last_frames
|
||||
frame = variables.n_snapshots - k + 1
|
||||
c1 = sol.center[i, frame]
|
||||
c2 = sol.center[j, frame]
|
||||
|
||||
r⃗₁₂ = c1 - c2
|
||||
|
||||
r⃗₁₂ = minimum_image(r⃗₁₂, variables.half_box_len)
|
||||
|
||||
distance = norm2d(r⃗₁₂)
|
||||
|
||||
if (distance >= r) && (distance <= r + dr)
|
||||
N_g[i, r_ind] += 1
|
||||
end
|
||||
end
|
||||
end
|
||||
end
|
||||
end
|
||||
end
|
||||
|
||||
g = zeros(n_r)
|
||||
|
||||
@simd for r_ind in 1:n_r
|
||||
r = radius[r_ind]
|
||||
tmp_g = 0.0
|
||||
|
||||
@turbo for i in 1:(variables.n_particles)
|
||||
tmp_g += N_g[i, r_ind]
|
||||
end
|
||||
|
||||
tmp_g *=
|
||||
(2 * variables.half_box_len)^2 / (
|
||||
(variables.n_particles * n_last_frames) *
|
||||
variables.n_particles *
|
||||
2 *
|
||||
π *
|
||||
r *
|
||||
dr
|
||||
)
|
||||
g[r_ind] = tmp_g
|
||||
end
|
||||
|
||||
fig = plot_g(radius, g, variables)
|
||||
|
||||
return (; fig, radius, g)
|
||||
end
|
||||
41
src/data.jl
41
src/data.jl
|
|
@ -39,6 +39,9 @@ struct Bundle
|
|||
t::Vector{Float64}
|
||||
c::Matrix{SVector{2,Float64}}
|
||||
φ::Matrix{Float64}
|
||||
|
||||
n_particles::Int64
|
||||
n_snapshots::Int64
|
||||
end
|
||||
|
||||
function Bundle(n_particles::Int64, n_snapshots::Int64)
|
||||
|
|
@ -46,11 +49,13 @@ function Bundle(n_particles::Int64, n_snapshots::Int64)
|
|||
Vector{Float64}(undef, n_snapshots),
|
||||
Matrix{SVector{2,Float64}}(undef, (n_particles, n_snapshots)),
|
||||
Matrix{Float64}(undef, (n_particles, n_snapshots)),
|
||||
n_particles,
|
||||
n_snapshots,
|
||||
)
|
||||
end
|
||||
|
||||
function first_n_snapshots(bundle::Bundle, n::Int64)
|
||||
return Bundle(bundle.t[1:n], bundle.c[:, 1:n], bundle.φ[:, 1:n])
|
||||
return Bundle(bundle.t[1:n], bundle.c[:, 1:n], bundle.φ[:, 1:n], bundle.n_particles, n)
|
||||
end
|
||||
|
||||
function save_snapshot!(
|
||||
|
|
@ -78,7 +83,7 @@ function save_bundle(dir::String, bundle::Bundle, n_bundle::Int64, T::Float64)
|
|||
return nothing
|
||||
end
|
||||
|
||||
function sorted_bundle_paths(dir::String)
|
||||
function sorted_bundle_paths(dir::String; rev::Bool=false)
|
||||
bundle_paths = readdir("$dir/bundles"; join=true, sort=false)
|
||||
|
||||
n_bundles = length(bundle_paths)
|
||||
|
|
@ -93,7 +98,37 @@ function sorted_bundle_paths(dir::String)
|
|||
bundle_nums[i] = parse(Int64, bundle_num_string)
|
||||
end
|
||||
|
||||
sort_perm = sortperm(bundle_nums)
|
||||
sort_perm = sortperm(bundle_nums; rev=rev)
|
||||
|
||||
return bundle_paths[sort_perm]
|
||||
end
|
||||
|
||||
function append_bundle_properties!(
|
||||
vs::NTuple{N,Vector},
|
||||
properties::NTuple{N,Symbol},
|
||||
sim_dir::String;
|
||||
particle_slice=nothing,
|
||||
snapshot_slice,
|
||||
first_bundle::Int64=1,
|
||||
) where {N}
|
||||
bundle_paths = ReCo.sorted_bundle_paths(sim_dir)
|
||||
|
||||
for i in first_bundle:length(bundle_paths)
|
||||
bundle::ReCo.Bundle = JLD2.load_object(bundle_paths[i])
|
||||
|
||||
for (v_ind, v) in enumerat(vs)
|
||||
property = properties[v_ind]
|
||||
bundle_property = getproperty(bundle, property)
|
||||
|
||||
if !isnothing(particle_slice)
|
||||
bundle_property_view = view(bundle_property, particle_slice, snapshot_slice)
|
||||
else
|
||||
bundle_property_view = view(bundle_property, snapshot_slice)
|
||||
end
|
||||
|
||||
append!(v, bundle_property_view)
|
||||
end
|
||||
end
|
||||
|
||||
return nothing
|
||||
end
|
||||
Loading…
Reference in a new issue