MEANS

MEANS is python package for Moment Expansion Approximation, iNference and Simulation.

We present a free, user-friendly tool implementing an efficient moment expansion approximation with parametric closures that integrates well with the IPython interactive environment. Our package enables the analysis of complex stochastic systems without any constraints on the number of species and moments studied and the type of rate laws in the system. In addition to the approximation method our package provides numerous tools to help non-expert users in stochastic analysis.

Installation

Please follow detailed instructions in Github.

Tutorial

An interactive tutorial on getting started with MEANS can be found on our Github page. We recommend trying it out directly using Jupyter interactive environment.

API Reference

• means.approximation package
  • Subpackages
    • means.approximation.lna package
      • Submodules
      • Module contents
        • Linear Noise Approximation
    • means.approximation.mea package
      • Submodules
        • Gamma moment closure
        • Log-normal moment closure
        • Normal moment closure
        • Scalar moment closure
        • MEA helper functions.
      • Module contents
        • Moment Expansion Approximation
  • Submodules
  • Module contents
• means.core package
  • Submodules
    • Descriptors
    • Model
    • Problems
  • Module contents
• means.examples package
  • Submodules
  • Module contents
• means.inference package
  • Submodules
    • Distances
    • Parameter Inference Parallelisation
    • Inference Results
  • Module contents
    • Parameter Inference
• means.io package
  • Submodules
  • Module contents
    • Module for Input/Output operations.
      • Human Readable Serialisation
      • Binary Serialisation
      • SBML
• means.simulation package
  • Submodules
    • Simulation Descriptors
    • Simulate
    • Solvers
    • Gillespie Stochastic Simulation Algorithm
    • Trajectories
  • Module contents
• means.util package
  • Submodules
    • MEANS Helpers
    • Sympy Helpers
  • Module contents
    • Utilities