fix: index properly into multi-type propensities (#1072)

* fix: index properly into multi-type propensities * Fix the fix * Update Project.toml --------- Co-authored-by: Adriano Meligrana <[email protected]>
JuliaDynamics · Sep 2, 2024 · 932d75f · 932d75f
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commit 932d75f
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Showing 2 changed files with 7 additions and 5 deletions.
diff --git a/Project.toml b/Project.toml
@@ -1,7 +1,7 @@
 name = "Agents"
 uuid = "46ada45e-f475-11e8-01d0-f70cc89e6671"
 authors = ["George Datseris", "Tim DuBois", "Aayush Sabharwal", "Ali Vahdati", "Adriano Meligrana"]
-version = "6.1.4"
+version = "6.1.5"
 
 [deps]
 CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
@@ -10,8 +10,8 @@ DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
 Distributed = "8ba89e20-285c-5b6f-9357-94700520ee1b"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
-DynamicSumTypes = "5fcdbb90-de43-509e-b9a6-c4d43f29cf26"
 Downloads = "f43a241f-c20a-4ad4-852c-f6b1247861c6"
+DynamicSumTypes = "5fcdbb90-de43-509e-b9a6-c4d43f29cf26"
 Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
 JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819"
 LazyArtifacts = "4af54fe1-eca0-43a8-85a7-787d91b784e3"
@@ -47,8 +47,8 @@ DataFrames = "0.21, 0.22, 1"
 DataStructures = "0.18"
 Distributed = "1"
 Distributions = "0.25"
-DynamicSumTypes = "3"
 Downloads = "1"
+DynamicSumTypes = "3"
 GraphMakie = "0.5"
 Graphs = "1.4"
 JLD2 = "0.4"

diff --git a/src/core/model_event_queue.jl b/src/core/model_event_queue.jl
@@ -256,9 +256,11 @@ function add_event!(agent, model) # TODO: Study type stability of this function
         propensities_type[i] = p
     end
     # Then, select an event based on propensities
-    event_idx = events_type[sample_propensity(abmrng(model), propensities_type)]    # The time to the event is generated from the selected event
+    # The time to the event is generated from the selected event
+    prop_idx = sample_propensity(abmrng(model), propensities_type)
+    event_idx = events_type[prop_idx] 
     selected_event = events[event_idx]
-    selected_prop = propensities_type[event_idx]
+    selected_prop = propensities_type[prop_idx]
     t = selected_event.timing(agent, model, selected_prop)
     # we then propagate to the direct function
     add_event!(agent, event_idx, t, model)