From b7a84c85d1140dc4a8af08edd77d672e582bc0c5 Mon Sep 17 00:00:00 2001
From: Daniel Vedder <daniel.vedder@idiv.de>
Date: Mon, 5 Aug 2024 11:03:27 +0200
Subject: [PATCH] Profiled a run, turned off flocking behaviour in skylarks
Searching for neighbours turned out to consume ~80% of processing time...
---
Makefile | 8 ++++----
runprofile.jl | 4 ++--
src/nature/species/skylark.jl | 9 +++++++--
3 files changed, 13 insertions(+), 8 deletions(-)
diff --git a/Makefile b/Makefile
index 91edc67..2a26fec 100644
--- a/Makefile
+++ b/Makefile
@@ -23,16 +23,16 @@ docs:
profile:
# run and profile an example simulation
- if [ -d "example_results" ]; then rm -r example_results; fi
- ./runprofile.jl -o example_results
+ if [ -d "profile_results" ]; then rm -r profile_results; fi
+ ./runprofile.jl -o profile_results
container:
#TODO create a Singularity container
- echo "Not yet implemented (#43)"
+ echo "Not yet implemented (#43)."
release:
echo "Not yet implemented."
install:
#TODO install Julia and/or package dependencies?
- echo "Not yet implemented."
+ echo "Not yet implemented (#67)."
diff --git a/runprofile.jl b/runprofile.jl
index a223bfd..ff21e0f 100755
--- a/runprofile.jl
+++ b/runprofile.jl
@@ -11,11 +11,11 @@ Profile.clear()
@profile simulate()
-open("profile_flat.txt", "w") do s
+open("profile_results/profile_flat.txt", "w") do s
Profile.print(IOContext(s, :displaysize=>(300,145)), format=:flat, mincount=10, sortedby=:count)
end
-open("profile_tree.txt", "w") do s
+open("profile_results/profile_tree.txt", "w") do s
Profile.print(IOContext(s, :displaysize=>(300,300)), mincount=10)
end
diff --git a/src/nature/species/skylark.jl b/src/nature/species/skylark.jl
index 94c3bd1..87ac542 100644
--- a/src/nature/species/skylark.jl
+++ b/src/nature/species/skylark.jl
@@ -88,9 +88,14 @@ end
Non-breeding adults move around with other individuals and check for migration.
"""
@phase Skylark nonbreeding begin
- #XXX is flocking behaviour important? It may be quite computationally expensive...
+ #FIXME searching for neighbours is *the* performance bottleneck!!
+ # Two options:
+ # (a) ignore flocking, simply move randomly (scientifically OK, doesn't look as good)
+ # (b) select a random neighbour once, then keep following that individual
+
# flocking behaviour - follow a random neighbour or move randomly
- neighbours = @neighbours(self.visionrange) #XXX check for the closest neighbour(s)?
+ neighbours = ()
+ #neighbours = @neighbours(self.visionrange) #XXX check for the closest neighbour(s)?
isempty(neighbours) ?
@walk("random", self.movementrange) :
@follow(@rand(neighbours), 30m) #XXX magic number
--
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