Welcome to the murefi documentation!

murefi is a Python package for multi replicate fitting, mostly for building ordinary differential equation (ODE) models.

You can download the latest version from GitHub or install it via pip install murefi.

In the following examples, we introduce the data structures, basic concepts and modeling API. Here you can learn how a murefi-driven modeling workflow looks like:

Examples

• Data structures in murefi
  • Creating mock data for testing
  • Creating murefi data structures
  • Using the data structures
  • Saving and loading datasets
• The ParameterMapping
  • Creating a ParameterMapping
  • Properties of the ParameterMapping
  • The repmap Method
• Example: Modelling an enzymatic reaction with Michaelis-Menten kinetics
  • Overview: Fitting with calibr8 and murefi
  • Preparing Data & Models
  • Estimation of model parameters
  • Visualizing the optimization result
• Differentiable ODE models with murefi and sunode
  • Preparing Data & Models
  • Objective function and gradients
  • Building a Bayesian ODE model with murefi, calibr8, sunode and pymc

You can find autogenerated API documentation below:

API Reference

• murefi.datastructures
  • Dataset
  • DtypeError
  • Replicate
  • ShapeError
  • Timeseries
  • load_dataset()
  • save_dataset()
• murefi.core
  • ParameterMapping
• murefi.ode
  • BaseODEModel
• murefi.symbolic
  • IntegrationOp
  • make_hash_sha256()
  • make_hashable()
  • named_with_shapes_dict()
  • solve_sunode()
• murefi.objectives
  • for_dataset()