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neworder: a dynamic microsimulation framework for Python

Authors: Andrew P Smith;

neworder: a dynamic microsimulation framework for Python

Abstract

neworder 1.0.0 Release to coincide with publication in the Journal of Open Source Software Breaking changes Model.timeline and Model.mc are now class attributes where they were previously methods. (Change e.g. model.mc().ustream(10) to model.mc.ustream(10)) Functional changes Add initial spatial domain support (neworder.Domain, neworder.Space): continuous rectangular domain in n dimensions domain edges can be wrapped, contrained, mirrored or unbounded calculate positions, distances, proximity and movement for points in the domain New example using the domain functionality: boids flocking Migrate existing examples to use new domain functionality, where appropriate Fixes for wolf-sheep predation example Other Various minor improvements resulting from JOSS reviewer comments. Internals add a virtual clone method to Timeline, simplifying model construction. migration of most CI builds to github workflows.

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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