Fix typos

.gitignore

@@ -6,3 +6,6 @@ exports
 
 # Profiling
 *.mem
+
+# VSCodium
+.vscode

analysis/radial_distribution_function/radial_distribution_function.jl

@@ -72,22 +72,22 @@ function radial_distribution(;
 
         bundle_paths = ReCo.sorted_bundle_paths(sim_dir; rev=true)
 
-        snapshot_conunter = 0
+        snapshot_counter = 0
         break_bundle_path_loop = false
 
         for bundle_path in bundle_paths
             bundle::ReCo.Bundle = JLD2.load_object(bundle_path)
 
             for snapshot_ind in (bundle.n_snapshots):-1:1
-                snapshot_conunter += 1
+                snapshot_counter += 1
 
                 @simd for particle_ind in 1:n_particles
-                    cs[particle_ind, snapshot_conunter] = bundle.c[
+                    cs[particle_ind, snapshot_counter] = bundle.c[
                         particle_ind, snapshot_ind
                     ]
                 end
 
-                if snapshot_conunter == n_last_snapshots
+                if snapshot_counter == n_last_snapshots
                     break_bundle_path_loop = true
                     break
                 end
@@ -98,8 +98,8 @@ function radial_distribution(;
             end
         end
 
-        if snapshot_conunter != n_last_snapshots
-            error("snapshot_conunter != n_last_snapshots")
+        if snapshot_counter != n_last_snapshots
+            error("snapshot_counter != n_last_snapshots")
         end
 
         g = zeros(Float64, n_radii)

graphics/center_of_mass.jl

@@ -82,7 +82,7 @@ function gen_COM_graphics()
 
     ##
 
-    Drawing(box_length, box_height, "$graphics_export_dir/circular_projectiong.pdf")
+    Drawing(box_length, box_height, "$graphics_export_dir/circular_projection.pdf")
     origin()
     fontsize(5)
 

graphics/periodic_boundary_conditions.jl

@@ -7,20 +7,20 @@ using ReCo: ReCo
 function gen_periodic_boundary_conditions_graphics()
     Random.seed!(23)
 
-    drwaing_box_length = 300
+    drawing_box_length = 300
 
     graphics_export_dir = "exports/graphics"
     mkpath(graphics_export_dir)
 
     Drawing(
-        drwaing_box_length,
-        drwaing_box_length,
+        drawing_box_length,
+        drawing_box_length,
         "$graphics_export_dir/periodic_boundary_conditions.pdf",
     )
     origin()
 
     particle_radius = 10
-    box_len = drwaing_box_length / 3
+    box_len = drawing_box_length / 3
     half_box_len = box_len / 2
 
     N_in_one_box = 5
@@ -79,13 +79,13 @@ function gen_periodic_boundary_conditions_graphics()
     setline(1.0)
     for line_factor in (-3, -1, 1, 3)
         line(
-            Point(line_factor * drwaing_box_length / 6, drwaing_box_length / 2),
-            Point(line_factor * drwaing_box_length / 6, -drwaing_box_length / 2),
+            Point(line_factor * drawing_box_length / 6, drawing_box_length / 2),
+            Point(line_factor * drawing_box_length / 6, -drawing_box_length / 2),
             :stroke,
         )
         line(
-            Point(drwaing_box_length / 2, line_factor * drwaing_box_length / 6),
-            Point(-drwaing_box_length / 2, line_factor * drwaing_box_length / 6),
+            Point(drawing_box_length / 2, line_factor * drawing_box_length / 6),
+            Point(-drawing_box_length / 2, line_factor * drawing_box_length / 6),
             :stroke,
         )
     end

src/RL/Envs/LocalCOMEnv.jl

@@ -39,8 +39,8 @@ end
 mutable struct LocalCOMEnvHelper <: EnvHelper
     shared::EnvHelperSharedProps
 
-    vec_to_neighbour_sums::Vector{SVector{2,Float64}}
-    n_neighbours::Vector{Int64}
+    vec_to_neighbor_sums::Vector{SVector{2,Float64}}
+    n_neighbors::Vector{Int64}
 
     distances_to_local_center_of_mass::Vector{Float64}
     max_distance_to_local_center_of_mass::Float64
@@ -69,8 +69,8 @@ end
 
 function pre_integration_hook!(env_helper::LocalCOMEnvHelper)
     @simd for id in 1:(env_helper.shared.n_particles)
-        env_helper.vec_to_neighbour_sums[id] = SVector(0.0, 0.0)
-        env_helper.n_neighbours[id] = 0
+        env_helper.vec_to_neighbor_sums[id] = SVector(0.0, 0.0)
+        env_helper.n_neighbors[id] = 0
     end
 
     return nothing
@@ -83,11 +83,11 @@ function state_update_helper_hook!(
     r⃗₁₂::SVector{2,Float64},
     distance²::Float64,
 )
-    env_helper.vec_to_neighbour_sums[id1] += r⃗₁₂
-    env_helper.vec_to_neighbour_sums[id2] -= r⃗₁₂
+    env_helper.vec_to_neighbor_sums[id1] += r⃗₁₂
+    env_helper.vec_to_neighbor_sums[id2] -= r⃗₁₂
 
-    env_helper.n_neighbours[id1] += 1
-    env_helper.n_neighbours[id2] += 1
+    env_helper.n_neighbors[id1] += 1
+    env_helper.n_neighbors[id2] += 1
 
     return nothing
 end
@@ -98,13 +98,13 @@ function state_update_hook!(env_helper::LocalCOMEnvHelper, particles::Vector{ReC
     env = env_helper.shared.env
 
     for particle_id in 1:n_particles
-        n_neighbours = env_helper.n_neighbours[particle_id]
+        n_neighbors = env_helper.n_neighbors[particle_id]
 
-        if n_neighbours == 0
+        if n_neighbors == 0
             state_id = env.shared.n_states
         else
             vec_to_local_center_of_mass =
-                env_helper.vec_to_neighbour_sums[particle_id] / n_neighbours
+                env_helper.vec_to_neighbor_sums[particle_id] / n_neighbors
             distance = ReCo.norm2d(vec_to_local_center_of_mass)
             env_helper.distances_to_local_center_of_mass[particle_id] = distance
             distance_state_ind = find_state_ind(distance, env.distance_state_space)
@@ -127,9 +127,9 @@ end
 function update_reward!(
     env::LocalCOMEnv, env_helper::LocalCOMEnvHelper, particle::ReCo.Particle
 )
-    n_neighbours = env_helper.n_neighbours[particle.id]
+    n_neighbors = env_helper.n_neighbors[particle.id]
 
-    if n_neighbours == 0
+    if n_neighbors == 0
         env.shared.reward = 0.0
     else
         reward = minimizing_reward(

src/RL/Envs/LocalCOMWithAdditionalShapeRewardEnv.jl

@@ -39,8 +39,8 @@ end
 mutable struct LocalCOMWithAdditionalShapeRewardEnvHelper <: EnvHelper
     shared::EnvHelperSharedProps
 
-    vec_to_neighbour_sums::Vector{SVector{2,Float64}}
-    n_neighbours::Vector{Int64}
+    vec_to_neighbor_sums::Vector{SVector{2,Float64}}
+    n_neighbors::Vector{Int64}
 
     distances_to_local_center_of_mass::Vector{Float64}
     max_distance_to_local_center_of_mass::Float64
@@ -89,8 +89,8 @@ end
 
 function pre_integration_hook!(env_helper::LocalCOMWithAdditionalShapeRewardEnvHelper)
     @simd for id in 1:(env_helper.shared.n_particles)
-        env_helper.vec_to_neighbour_sums[id] = SVector(0.0, 0.0)
-        env_helper.n_neighbours[id] = 0
+        env_helper.vec_to_neighbor_sums[id] = SVector(0.0, 0.0)
+        env_helper.n_neighbors[id] = 0
     end
 
     return nothing
@@ -103,11 +103,11 @@ function state_update_helper_hook!(
     r⃗₁₂::SVector{2,Float64},
     distance²::Float64,
 )
-    env_helper.vec_to_neighbour_sums[id1] += r⃗₁₂
-    env_helper.vec_to_neighbour_sums[id2] -= r⃗₁₂
+    env_helper.vec_to_neighbor_sums[id1] += r⃗₁₂
+    env_helper.vec_to_neighbor_sums[id2] -= r⃗₁₂
 
-    env_helper.n_neighbours[id1] += 1
-    env_helper.n_neighbours[id2] += 1
+    env_helper.n_neighbors[id1] += 1
+    env_helper.n_neighbors[id2] += 1
 
     return nothing
 end
@@ -122,16 +122,16 @@ function state_update_hook!(
     distance_to_local_center_of_mass_sum = 0.0
 
     for particle_id in 1:n_particles
-        n_neighbours = env_helper.n_neighbours[particle_id]
+        n_neighbors = env_helper.n_neighbors[particle_id]
 
-        if n_neighbours == 0
+        if n_neighbors == 0
             state_id = env.shared.n_states
 
             distance_to_local_center_of_mass_sum +=
                 env_helper.max_distance_to_local_center_of_mass
         else
             vec_to_local_center_of_mass =
-                env_helper.vec_to_neighbour_sums[particle_id] / n_neighbours
+                env_helper.vec_to_neighbor_sums[particle_id] / n_neighbors
             distance = ReCo.norm2d(vec_to_local_center_of_mass)
             env_helper.distances_to_local_center_of_mass[particle_id] = distance
             distance_to_local_center_of_mass_sum += distance
@@ -172,9 +172,9 @@ function update_reward!(
     env_helper::LocalCOMWithAdditionalShapeRewardEnvHelper,
     particle::ReCo.Particle,
 )
-    n_neighbours = env_helper.n_neighbours[particle.id]
+    n_neighbors = env_helper.n_neighbors[particle.id]
 
-    if n_neighbours == 0
+    if n_neighbors == 0
         env.shared.reward = 0.0
     else
         reward = minimizing_reward(

src/RL/Envs/LocalCOMWithAdditionalShapeRewardEnv2.jl

@@ -39,8 +39,8 @@ end
 mutable struct LocalCOMWithAdditionalShapeRewardEnv2Helper <: EnvHelper
     shared::EnvHelperSharedProps
 
-    vec_to_neighbour_sums::Vector{SVector{2,Float64}}
-    n_neighbours::Vector{Int64}
+    vec_to_neighbor_sums::Vector{SVector{2,Float64}}
+    n_neighbors::Vector{Int64}
 
     distances_to_local_center_of_mass::Vector{Float64}
     max_distance_to_local_center_of_mass::Float64
@@ -86,8 +86,8 @@ end
 
 function pre_integration_hook!(env_helper::LocalCOMWithAdditionalShapeRewardEnv2Helper)
     @simd for id in 1:(env_helper.shared.n_particles)
-        env_helper.vec_to_neighbour_sums[id] = SVector(0.0, 0.0)
-        env_helper.n_neighbours[id] = 0
+        env_helper.vec_to_neighbor_sums[id] = SVector(0.0, 0.0)
+        env_helper.n_neighbors[id] = 0
     end
 
     return nothing
@@ -100,11 +100,11 @@ function state_update_helper_hook!(
     r⃗₁₂::SVector{2,Float64},
     distance²::Float64,
 )
-    env_helper.vec_to_neighbour_sums[id1] += r⃗₁₂
-    env_helper.vec_to_neighbour_sums[id2] -= r⃗₁₂
+    env_helper.vec_to_neighbor_sums[id1] += r⃗₁₂
+    env_helper.vec_to_neighbor_sums[id2] -= r⃗₁₂
 
-    env_helper.n_neighbours[id1] += 1
-    env_helper.n_neighbours[id2] += 1
+    env_helper.n_neighbors[id1] += 1
+    env_helper.n_neighbors[id2] += 1
 
     return nothing
 end
@@ -120,16 +120,16 @@ function state_update_hook!(
     distance_to_local_center_of_mass_sum = 0.0
 
     for particle_id in 1:n_particles
-        n_neighbours = env_helper.n_neighbours[particle_id]
+        n_neighbors = env_helper.n_neighbors[particle_id]
 
-        if n_neighbours == 0
+        if n_neighbors == 0
             state_id = env.shared.n_states
 
             distance_to_local_center_of_mass_sum +=
                 env_helper.max_distance_to_local_center_of_mass
         else
             vec_to_local_center_of_mass =
-                env_helper.vec_to_neighbour_sums[particle_id] / n_neighbours
+                env_helper.vec_to_neighbor_sums[particle_id] / n_neighbors
             distance = ReCo.norm2d(vec_to_local_center_of_mass)
             env_helper.distances_to_local_center_of_mass[particle_id] = distance
             distance_to_local_center_of_mass_sum += distance
@@ -161,9 +161,9 @@ function update_reward!(
     env_helper::LocalCOMWithAdditionalShapeRewardEnv2Helper,
     particle::ReCo.Particle,
 )
-    n_neighbours = env_helper.n_neighbours[particle.id]
+    n_neighbors = env_helper.n_neighbors[particle.id]
 
-    if n_neighbours == 0
+    if n_neighbors == 0
         env.shared.reward = 0.0
     else
         reward = minimizing_reward(

src/RL/Envs/NearestNeighborEnv.jl

@@ -1,12 +1,12 @@
 using ..ReCo: ReCo
 
-struct NearestNeighbourEnv <: Env
+struct NearestNeighborEnv <: Env
     shared::EnvSharedProps
 
     distance_state_space::Vector{Interval}
     direction_angle_state_space::Vector{Interval}
 
-    function NearestNeighbourEnv(;
+    function NearestNeighborEnv(;
         n_distance_states::Int64=3, n_direction_angle_states::Int64=3, args
     )
         @assert n_distance_states > 1
@@ -36,11 +36,11 @@ struct NearestNeighbourEnv <: Env
     end
 end
 
-mutable struct NearestNeighbourEnvHelper <: EnvHelper
+mutable struct NearestNeighborEnvHelper <: EnvHelper
     shared::EnvHelperSharedProps
 
-    vecs_to_neighbour::Vector{SVector{2,Float64}}
-    sq_distances_to_neighbour::Vector{Float64}
+    vecs_to_neighbor::Vector{SVector{2,Float64}}
+    sq_distances_to_neighbor::Vector{Float64}
 
     current_κ::Float64
     goal_κ::Float64
@@ -48,7 +48,7 @@ mutable struct NearestNeighbourEnvHelper <: EnvHelper
 
     half_box_len::Float64
 
-    function NearestNeighbourEnvHelper(shared::EnvHelperSharedProps, half_box_len::Float64)
+    function NearestNeighborEnvHelper(shared::EnvHelperSharedProps, half_box_len::Float64)
         goal_κ = 0.4
         max_distance_to_goal_κ = max(1 - goal_κ, goal_κ)
 
@@ -64,49 +64,47 @@ mutable struct NearestNeighbourEnvHelper <: EnvHelper
     end
 end
 
-function gen_env_helper(
-    ::NearestNeighbourEnv, env_helper_shared::EnvHelperSharedProps; args
-)
-    return NearestNeighbourEnvHelper(env_helper_shared, args.half_box_len)
+function gen_env_helper(::NearestNeighborEnv, env_helper_shared::EnvHelperSharedProps; args)
+    return NearestNeighborEnvHelper(env_helper_shared, args.half_box_len)
 end
 
-function pre_integration_hook!(env_helper::NearestNeighbourEnvHelper)
+function pre_integration_hook!(env_helper::NearestNeighborEnvHelper)
     @simd for particle_id in 1:(env_helper.shared.n_particles)
-        env_helper.sq_distances_to_neighbour[particle_id] = Inf64
+        env_helper.sq_distances_to_neighbor[particle_id] = Inf64
     end
 
     return nothing
 end
 
 function state_update_helper_hook!(
-    env_helper::NearestNeighbourEnvHelper,
+    env_helper::NearestNeighborEnvHelper,
     id1::Int64,
     id2::Int64,
     r⃗₁₂::SVector{2,Float64},
     distance²::Float64,
 )
-    if distance² < env_helper.sq_distances_to_neighbour[id1]
-        env_helper.vecs_to_neighbour[id1] = r⃗₁₂
-        env_helper.sq_distances_to_neighbour[id1] = distance²
+    if distance² < env_helper.sq_distances_to_neighbor[id1]
+        env_helper.vecs_to_neighbor[id1] = r⃗₁₂
+        env_helper.sq_distances_to_neighbor[id1] = distance²
     end
 
-    if distance² < env_helper.sq_distances_to_neighbour[id2]
-        env_helper.vecs_to_neighbour[id2] = -r⃗₁₂
-        env_helper.sq_distances_to_neighbour[id2] = distance²
+    if distance² < env_helper.sq_distances_to_neighbor[id2]
+        env_helper.vecs_to_neighbor[id2] = -r⃗₁₂
+        env_helper.sq_distances_to_neighbor[id2] = distance²
     end
 
     return nothing
 end
 
 function state_update_hook!(
-    env_helper::NearestNeighbourEnvHelper, particles::Vector{ReCo.Particle}
+    env_helper::NearestNeighborEnvHelper, particles::Vector{ReCo.Particle}
 )
     n_particles = env_helper.shared.n_particles
 
     env = env_helper.shared.env
 
     for particle_id in 1:n_particles
-        sq_distance = env_helper.sq_distances_to_neighbour[particle_id]
+        sq_distance = env_helper.sq_distances_to_neighbor[particle_id]
 
         if sq_distance == Inf64
             state_id = env.shared.n_states
@@ -116,7 +114,7 @@ function state_update_hook!(
 
             si, co = sincos(particles[particle_id].φ)
             direction_angle = ReCo.angle2(
-                SVector(co, si), env_helper.vecs_to_neighbour[particle_id]
+                SVector(co, si), env_helper.vecs_to_neighbor[particle_id]
             )
             direction_state_ind = find_state_ind(
                 direction_angle, env.direction_angle_state_space
@@ -136,7 +134,7 @@ function state_update_hook!(
 end
 
 function update_reward!(
-    env::NearestNeighbourEnv, env_helper::NearestNeighbourEnvHelper, particle::ReCo.Particle
+    env::NearestNeighborEnv, env_helper::NearestNeighborEnvHelper, particle::ReCo.Particle
 )
     reward = minimizing_reward(
         abs(env_helper.current_κ - env_helper.goal_κ), env_helper.max_distance_to_goal_κ

src/RL/RL.jl

@@ -4,7 +4,7 @@ export run_rl,
     LocalCOMWithAdditionalShapeRewardEnv,
     LocalCOMWithAdditionalShapeRewardEnv2,
     OriginEnv,
-    NearestNeighbourEnv,
+    NearestNeighborEnv,
     LocalCOMEnv,
     OriginCompassEnv,
     COMCompassEnv
@@ -77,7 +77,7 @@ function gen_agent(
 end
 
 """
-    run_rl(EnvType; <keyword arguments>)
+    run_rl(EnvType::Type{<:Env}; <keyword arguments>)
 
 Run a reinforcement learning process and return the tuple (`env_helper`, `rl_dir`). `env_helper` is the environment helper and `rl_dir` is the path of the process directory relative to the directory `ReCo.jl`.
 
@@ -178,7 +178,7 @@ function run_rl(
         # Reset
         reset!(env)
 
-        # Pre espisode
+        # Pre episode
         hook(PRE_EPISODE_STAGE, agent, env)
         agent(PRE_EPISODE_STAGE, env)
 
@@ -234,7 +234,7 @@ end
 include("Envs/LocalCOMWithAdditionalShapeRewardEnv.jl")
 include("Envs/LocalCOMWithAdditionalShapeRewardEnv2.jl")
 include("Envs/OriginEnv.jl")
-include("Envs/NearestNeighbourEnv.jl")
+include("Envs/NearestNeighborEnv.jl")
 include("Envs/LocalCOMEnv.jl")
 include("Envs/OriginCompassEnv.jl")
 include("Envs/COMCompassEnv.jl")

src/ReCo.jl

@@ -9,7 +9,7 @@ export init_sim,
     LocalCOMWithAdditionalShapeRewardEnv,
     LocalCOMWithAdditionalShapeRewardEnv2,
     OriginEnv,
-    NearestNeighbourEnv,
+    NearestNeighborEnv,
     LocalCOMEnv,
     OriginCompassEnv,
     COMCompassEnv

src/Shape.jl

@@ -28,7 +28,7 @@ function center_of_mass_from_proj_sums(
     digits = 5
 
     # No need for 1/n_particles with atan
-    # If proj is (0, 0) then COM is 0 or L or -L. Here, 0 is choosen with θ = π
+    # If proj is (0, 0) then COM is 0 or L or -L. Here, 0 is chosen with θ = π
     if round(x_proj_sum[1]; digits=digits) == round(x_proj_sum[2]; digits=digits) == 0
         x_θ = π
     else

src/run.jl

@@ -25,7 +25,7 @@ Some of the last snapshots might be lost if the simulations is stopped (see the
 - `duration::Float64`: Duration of the simulation.
 - `snapshot_at::Float64=$DEFAULT_SNAPSHOT_AT`: Snapshot time interval.
 - `seed::Int64=$DEFAULT_SEED`: Random number generator seed.
-- `n_bundle_snapshots::Int64=$DEFAULT_N_BUNDLE_SNAPSHOTS`: Number of snapshots in a bundle. This number is relevant for long simulations that can be stopped while running. A simulation can be continued from the last bundle of snapshots. If the number of snapshots in a bundle is too high and the simulation is stopped, many of the last snapshots can be lost. A low number results in high IO since snapshots are then bundled and stored more often. For example, setting this number to 1 results in saving every snapshot immidiately without bundeling it with other snapshots which would be more efficient. Setting the number to 1000 could mean loosing 999 snapshots in the worst case if the simulation is stopped before having 1000 snapshots to bundle and save.
+- `n_bundle_snapshots::Int64=$DEFAULT_N_BUNDLE_SNAPSHOTS`: Number of snapshots in a bundle. This number is relevant for long simulations that can be stopped while running. A simulation can be continued from the last bundle of snapshots. If the number of snapshots in a bundle is too high and the simulation is stopped, many of the last snapshots can be lost. A low number results in high IO since snapshots are then bundled and stored more often. For example, setting this number to 1 results in saving every snapshot immediately without bundeling it with other snapshots which would be more efficient. Setting the number to 1000 could mean loosing 999 snapshots in the worst case if the simulation is stopped before having 1000 snapshots to bundle and save.
 - `env_helper::Union{RL.EnvHelper,Nothing}=nothing`: Environment helper. It should be left as the default `nothing` unless this method is used internally for reinforcement learning.
 - `show_progress::Bool=$DEFAULT_SHOW_PROGRESS`: Show simulation progress bar.
 """