Faster sample! function (#858)

CHANGELOG.md

@@ -1,17 +1,14 @@
 # v6
+- The `@agent` macro now supports fields with default and const values (through the special `constants` field). Since now the macro supports these features, using `@agent` is the only supported way to create agent types for Agents.jl.
+- The `add_agent!` function supports adding an agent propagating keywords arguments.
 - Agent types in `ContinuousSpace` now require `SVector` for their `pos` and `vel` fields rather than `NTuple`. 
+- Two new functions `random_id_in_position` and `random_agent_in_position` can be used to select a random id/agent in a position in discrete spaces (even with filtering). 
+- A new argument `alloc` can be used to select a more performant version in relation to the expensiveness of the filtering for all random methods selecting ids/agents/positions.
+- The `sample!` function is up to 2x faster than before.
 
 ## BREAKING
 - `NTuple` in `ContinuousSpace` is officially deprecated, but backward compatibility is *mostly* maintained. Known breakages include the comparison of agent position and/or velocity with user-defined tuples (which will silently fail).
 
-# main
-
-- The `@agent` macro now supports fields with default and const values (through the special `constants` field). Since now the macro supports these features, using `@agent` is the only supported way to create agent types for Agents.jl.
-- The `add_agent!` function supports adding an agent propagating keywords arguments.
-- Two new functions `random_id_in_position` and `random_agent_in_position` can be used to select a random id/agent in a position in discrete spaces (even with filtering). 
-- A new argument `alloc` can be used to select a more performant version in relation to the expensiveness of the filtering for all 
-random methods selecting ids/agents/positions.
-
 # v5.17
 
 - New function `replicate!` allows to create a new instance of a given agent at the same position with the possibility to specify some

benchmark/sample.jl

@@ -0,0 +1,25 @@
+using Agents, BenchmarkTools
+
+@agent FakeAgent NoSpaceAgent begin end
+
+function fake_model(; nagents)
+    model = StandardABM(FakeAgent)
+    for i in 1:nagents
+        add_agent!(model)
+    end
+    return model
+end
+
+@benchmark sample!(model, 10^5) setup=(model = fake_model(; nagents = 10^2)) evals=1
+@benchmark sample!(model, 10^4) setup=(model = fake_model(; nagents = 10^2)) evals=1
+@benchmark sample!(model, 10^3) setup=(model = fake_model(; nagents = 10^2)) evals=1
+@benchmark sample!(model, 10^2) setup=(model = fake_model(; nagents = 10^2)) evals=1
+@benchmark sample!(model, 10^1) setup=(model = fake_model(; nagents = 10^2)) evals=1
+@benchmark sample!(model, 10^0) setup=(model = fake_model(; nagents = 10^2)) evals=1
+
+@benchmark sample!(model, 10^5) setup=(model = fake_model(; nagents = 10^5)) evals=1
+@benchmark sample!(model, 10^4) setup=(model = fake_model(; nagents = 10^5)) evals=1
+@benchmark sample!(model, 10^3) setup=(model = fake_model(; nagents = 10^5)) evals=1
+@benchmark sample!(model, 10^2) setup=(model = fake_model(; nagents = 10^5)) evals=1
+@benchmark sample!(model, 10^1) setup=(model = fake_model(; nagents = 10^5)) evals=1
+@benchmark sample!(model, 10^0) setup=(model = fake_model(; nagents = 10^5)) evals=1

src/Agents.jl

@@ -70,14 +70,26 @@ Welcome to this new update of Agents.jl!
 
 Breaking changes:
 
-- Agents in `ContinuousSpace` now require `SVector` for their `pos`
-  and `vel` fields instead of `NTuple`.
+- Agents.jl moved to Julia 1.9+, and now exports visualization
+  and interactive applications automatically once Makie (or Makie backends
+  such as GLMakie) come into scope, using the new package extension system.
+  The only downside of this is that now to visualize ABMs on open street
+  maps, the package OSMMakie.jl must be explicitly loaded as well.
+  InteractiveDynamics.jl is now obsolete.
+- We have created an objective fully automated framework for comparing open source
+  agent based modelling software. It shows that Agents.jl is much faster
+  than competing alternatives (MASON, NetLogo, Mesa).
+- The `@agent` macro is now THE way to create agent types for Agents.jl simulations since
+  now supports declaring default and constant fields. Directly creating structs by hand is 
+  no longer mentioned in the documentation at all. This will allow us in the future to utilize
+  additional fields that the user does not have to know about, which may bring new features or
+  performance gains by being part of the agent structures.
+- `ContinuousAgent{D}` is not a concrete type anymore. The new interface requires two parameters
+  `ContinuousAgent{D,T}` where `T` is any `AbstractFloat` type. If you want to use a type different
+  from `Float64`, you will also need to change the type of the `ContinuousSpace` extent accordingly. 
+  Agents in `ContinuousSpace` now require `SVector` for their `pos` and `vel` fields instead of `NTuple`. 
   Using `NTuple`s in `ContinuousSpace` is now deprecated.
-- `ContinuousAgent{D}` is not a concrete type anymore.
-  The new interface requires two parameters `ContinuousAgent{D,T}`
-  where `T` is any `AbstractFloat` type.
-  If you want to use a type different from `Float64`, you will also
-  need to change the type of the `ContinuousSpace` extent accordingly.
+- Several performance improvements all across the board.
 
 See the online documentation for more!
 """

src/simulations/sample.jl

@@ -28,28 +28,34 @@ function sample!(
     org_ids = collect(allids(model))
     if weight !== nothing
         weights = Weights([get_data(a, weight, identity) for a in allagents(model)])
-        newids = sample(abmrng(model), org_ids, weights, n, replace = replace)
+        new_ids = sample(abmrng(model), org_ids, weights, n, replace = replace)
     else
-        newids = sample(abmrng(model), org_ids, n, replace = replace)
+        new_ids = sample(abmrng(model), org_ids, n, replace = replace)
     end
-    add_newids!(model, org_ids, newids)
+    add_newids!(model, org_ids, new_ids)
 end
 
 #Used in sample!
-function add_newids!(model, org_ids, newids)
-    # `counter` counts the number of occurencies for each item, it comes from DataStructure.jl
-    count_newids = counter(newids)
+function add_newids!(model, org_ids, new_ids)
+    sort!(org_ids)
+    sort!(new_ids)
+    i, L = 1, length(new_ids)
+    sizehint!(agent_container(model), L)
+    id_new = new_ids[1]
     for id in org_ids
-        noccurances = count_newids[id]
         agent = model[id]
-        if noccurances == 0
+        if id_new != id
             remove_agent!(agent, model)
         else
-            for _ in 2:noccurances
+            i += 1
+            while i <= L && new_ids[i] == id
                 replicate!(agent, model)
+                i += 1
             end
+            i <= L && (id_new = new_ids[i])
         end
     end
+    return
 end
 
 """

test/randomness_tests.jl

@@ -22,6 +22,25 @@ using Agents, Test
 end
 
 @testset "sample!" begin
+    rng = StableRNG(50)
+    model4 = ABM(Agent1, GridSpace((2, 2)); rng = rng)
+    agents = model4.agents
+    add_agent_pos!(Agent1(1, (1,1)), model4)
+    add_agent_pos!(Agent1(2, (2,2)), model4)
+    sample!(model4, 4)
+    res = Dict{Int64, Agent1}(4 => Agent1(4, (2, 2)), 2 => Agent1(2, (2, 2)), 
+                              3 => Agent1(3, (2, 2)), 1 => Agent1(1, (1, 1)))
+    res_fields = [getfield(res[k], f) for f in fieldnames(Agent1) for k in keys(res)]
+    agents_fields = [getfield(agents[k], f) for f in fieldnames(Agent1) for k in keys(model4.agents)]
+    @test keys(model4.agents) == keys(res)
+    @test res_fields == agents_fields
+    sample!(model4, 2)
+    res = Dict{Int64, Agent1}(4 => Agent1(4, (2, 2)), 1 => Agent1(1, (1, 1)))
+    res_fields = [getfield(res[k], f) for f in fieldnames(Agent1) for k in keys(res)]
+    agents_fields = [getfield(agents[k], f) for f in fieldnames(Agent1) for k in keys(model4.agents)]
+    @test keys(model4.agents) == keys(res)
+    @test res_fields == agents_fields
+
     rng = StableRNG(42)
     model = ABM(Agent2; rng = rng)
     for i in 1:20