This repository contains the code used to analyse the case studies and produce the figures for the paper Bianucci, T., Zechner, C. (2023 - in preparation). A local polynomial approximation method for compartmentalised biochemical systems.
This repository already contains Project.toml and Manifest.toml files specifying
is dependencies in the form of a Pkg environment.
To use it:
using Pkg
Pkg.activate(".")
Pkg.instantiate()
Pkg.precompile()or, in the Julia REPL:
] activate .
] instantiate
] precompileThis will download, install and precompile all the dependencies.
The code is structured as a main module LPAC which directly exposes
the main data structures and plotting features, together with the main
additional submodules Sim, Models and Figures.
The functions generating the figures for the paper are available in the
LPAC.Figures submodule.
They can be generated with the following:
julia --project
and
using LPAC
Figures.generateAllFigures()This uses the same serialized simulation results that we used for generating the paper figures,
that are stored in *.jser file within the ./Figures subfolder.
This ensures that the output is identical to the figures in the paper.
In order to run a new set of SSA trajectories and solve the moment equations again, it is enough to disable the loading of data from the serialized dump:
Figures.generateAllFigures(; loadFromDump=false)The new simulation results are again also serialized and saved into *.jser files, so that
tweaking of the plots does not require running the SSAs all over again.
To load the results from these saves, use the loadFromDump=true flag (which is the default):
Figures.generateAllFigures(; loadFromDump=true)Please note that any run with loadFromDump=false overwrites any existing *.jser files.
It is possible to revert to the original data from this repository by using the following command:
git checkout Figures