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@pdp10 pdp10 released this 26 Jan 12:58
· 871 commits to master since this release
v3.0.0
c5bce5e

This release includes the following features / updates:

  • added prints to r plotting functions
  • pipeline analyses are executed on cluster (local, sge, lsf) using sbpipe parcomp module.
  • renamed option pp_cpus to local_cpus, after removal of parallel python.
  • renamed value pp to local for option cluster after removal of parallel python.
  • added support for Python 3. The code is now expected to work for Python 2.7+, 3.2, and 3.6.
  • replaced parallel python with python multiprocessing package. This should facilitate the transition to Python 3.
  • removed deprecated source code for manually randomising parameters before parameter estimation in Copasi files.
  • Copasi and PL-based simulators now share a large amount of code.
  • adapted programming language-based simulators to use ps1 and ps2 post-processing code. All simulators support all the pipelines.
  • moved post-processing code for ps1 and ps2 from Copasi to Simul.
  • improved code cohesion by moving utility code into Simul class().
  • improved output name consistency for report and plot files
  • improved sorting of plots in latex/pdf report for ps1 pipeline
  • added test case for stochastic double parameter scan.
  • double parameter scans can be executed in parallel as repeats.
  • added support for stochastic double parameter scans.
  • added test case for stochastic single parameter scan.
  • single parameter scans can be executed in parallel as repeats.
  • added support for stochastic single parameter scans.
  • modularised parallel computation within Copasi simulator
  • added heatmap plot representing stochastic repeats for the time course simulation.
  • moved R code from pipelines to R/
  • redesign of simulation plots. Improvements plus based on melt function.
  • removed remaining old gplots dependent code. Sbpipe only uses ggplot2 now.
  • added two new plots useful for stochastic simulation
  • improved reuse for all R plots.
  • added plots reproducing all the single simulations per species.
  • changed main script name from run_sbpipe.py to sbpipe.py.
  • Added support for parameter estimation using non-Copasi models. Test using R model.
  • Skip Java, Python, and R model tests if their dependencies are not satisfied.
  • Optimised Java, Python, and R simulators. Report file names are passed as input argument. Models do not need to be replicated.
  • Java models can be used for model simulation in addition to Copasi.
  • Python models can be used for model simulation in addition to Copasi.
  • R models can be used for model simulation in addition to Copasi.
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