Metadata-Version: 2.1
Name: petab
Version: 0.0.2
Summary: Parameter estimation tabular data
Home-page: https://github.com/icb-dcm/petab
Author: The PEtab developers
Author-email: daniel.weindl@helmholtz-muenchen.de
License: UNKNOWN
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        # PEtab --- a data format for specifying parameter estimation problems in systems biology
        
        ![Logo](doc/logo/PEtab.png)
        
        This repository describes *PEtab* --- a data format for specifying parameter 
        estimation problems in systems biology, provides a Python library for easy 
        access and validation of *PEtab* files. See 
        [doc/documentation_data_format.md](doc/documentation_data_format.md) for more 
        info.
        
        ## About PEtab
        
        PEtab is built around [SBML](http://sbml.org/) and based on tab-separated values 
        (TSV) files. It is meant as a standardized way to provide information for 
        parameter estimation which is out of the current scope of SBML. This includes
        for example:
        
          - Specifying and linking measurements to models
        
            - Defining model outputs
        
            - Specifying noise models
        
          - Specifying parameter bounds for optimization
        
          - Specifying multiple simulation condition with potentially shared parameters
         
        ## References
        
        Where PEtab is used / supported:
        
          - Within the systems biology optimization 
            [benchmark problem collection](https://github.com/LeonardSchmiester/Benchmark-Models)
        
          - A PEtab -> [COPASI](http://copasi.org/)
            [converter](https://github.com/copasi/python-petab-importer)
        
          - [pyPESTO](https://github.com/ICB-DCM/pyPESTO/)
        
          - [AMICI](https://github.com/ICB-DCM/AMICI/)
        
        PEtab support for [D2D](https://github.com/Data2Dynamics/d2d/) and
        [AMIGO2](https://sites.google.com/site/amigo2toolbox/) is under development.
        
        If your project or tool is using PEtab, and you would like to have it listed
        here, please let us know.
        
        ## Using PEtab
        
        If you would like to use PEtab yourself, please have a look at 
        [doc/documentation_data_format.md](doc/documentation_data_format.md) or at
        the example models provided in the 
        [benchmark problem collection](https://github.com/LoosC/Benchmark-Models).
        
        To convert your existing parameter estimation problem to the PEtab format, you 
        will have to:
        
        1. Specify your model in SBML
        
        1. Set up model outputs and noise model using `AssignmentRule`s as described in 
          the PEtab documentation
        
        1. Create a condition table, if appropriate
        
        1. Create a table of measurements
        
        1. Create a parameter table
        
        If you are using Python, some handy functions of the PEtab library can help 
        you with that. This include also a PEtab validator called `petablint.py` which
        you can use to check if your files adhere to the PEtab standard. If you have 
        further questions regarding PEtab, feel free to post an 
        [issue](https://github.com/ICB-DCM/PEtab/issues) at our github repository.
        
        ## PEtab Python library
        
        PEtab comes with a Python package for creating, checking, and working with 
        PEtab files. This library is available on pypi and the easiest way to install 
        it is running
        
            pip3 install petab
            
        It will require Python3.6 to run.
        
        Development versions of the PEtab library can be installed using
        
            pip3 install https://github.com/ICB-DCM/PEtab/archive/develop.zip
        
        (replace `develop` by the branch or commit you would like to install).
        
        When setting up a new parameter estimation problem, the most useful tools will
        be:
        
          - The **PEtab validator**, which is now automatically installed using Python
            entrypoints to be available as a shell command from anywhere called
            `petablint`
        
          - `petab.core.create_parameter_df` to create the parameter table, once you
            have set up the model, condition table and measurement table
        
          - Functions in `petab.sbml` to define observables and error model parameters
            in the SBML model
        
        ## Extending PEtab
        
        We are aware of the fact that PEtab may not serve everybody's needs. If you 
        have a suggestion of how to extend PEtab, feel free to post an issue at our 
        github repository.
        
Platform: UNKNOWN
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: reports
