Metadata-Version: 2.1
Name: petab
Version: 0.1.12
Summary: Parameter estimation tabular data
Home-page: https://github.com/PEtab-dev/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](https://raw.githubusercontent.com/petab-dev/petab/master/doc/logo/PEtab.png)
        
        *PEtab* is a data format for specifying parameter estimation problems in systems biology.
        This repository provides extensive documentation and a Python library for easy
        access and validation of *PEtab* files.
        
        ## 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
        
        ![PEtab files](https://raw.githubusercontent.com/petab-dev/petab/master/doc/gfx/petab_files.png)
        
        ## Documentation
        
        Documentation of the PEtab data format and Python library is available at
        [https://petab.readthedocs.io/en/latest/](https://petab.readthedocs.io/en/latest/).
        
        ## Examples
        
        A wide range of PEtab examples can be found in the systems biology parameter estimation
        [benchmark problem collection](https://github.com/Benchmarking-Initiative/Benchmark-Models-PEtab).
        
        
        ## PEtab support in systems biology tools
        
        Where PEtab is supported (in alphabetical order):
        
        
          - [AMICI](https://github.com/ICB-DCM/AMICI/)
            ([Example](https://github.com/ICB-DCM/AMICI/blob/master/python/examples/example_petab/petab.ipynb))
        
          - A PEtab -> [COPASI](http://copasi.org/)
            [converter](https://github.com/copasi/python-petab-importer)
        
          - [d2d](https://github.com/Data2Dynamics/d2d/)
            ([HOWTO](https://github.com/Data2Dynamics/d2d/wiki/Support-for-PEtab))
        
          - [dMod](https://github.com/dkaschek/dMod/)
            ([HOWTO](https://github.com/dkaschek/dMod/wiki/Support-for-PEtab))
        
          - [MEIGO](https://github.com/gingproc-IIM-CSIC/MEIGO64)
            ([HOWTO](https://github.com/gingproc-IIM-CSIC/MEIGO64/tree/master/MEIGO/PEtabMEIGO))
        
          - [parPE](https://github.com/ICB-DCM/parPE/)
        
          - [pyABC](https://github.com/ICB-DCM/pyABC/) ([Example](https://pyabc.readthedocs.io/en/latest/examples/petab.html))
        
          - [pyPESTO](https://github.com/ICB-DCM/pyPESTO/)
            ([Example](https://pypesto.readthedocs.io/en/latest/example/petab_import.html))
        
          - [SBML2Julia](https://github.com/paulflang/SBML2Julia)
            ([Tutorial](https://sbml2julia.readthedocs.io/en/latest/python_api.html))
        
        If your project or tool is using PEtab, and you would like to have it listed
        here, please [let us know](https://github.com/PEtab-dev/PEtab/issues).
        
        ### PEtab features supported in different tools
        
        The following list provides an overview of supported PEtab features in
        different tools, based on passed test cases of the
        [PEtab test suite](https://github.com/PEtab-dev/petab_test_suite):
        
        
        | ID | Test                                                           | AMICI<br>`>=0.10.20` | Copasi | D2D | dMod | MEIGO | parPE<br>`develop`  | pyABC<br>`>=0.10.1` | pyPESTO<br>`>=0.0.11` | SBML2Julia |
        |----|----------------------------------------------------------------|----------------------|--------|-----|------|-------|-----------------------|-------|------------------------|------------|
        | 1  | Basic simulation                                               | +++                  | +--    | +++ | +++  | +++   | --+                   | +++   | +++                    | +++        |
        | 2  | Multiple simulation conditions                                 | +++                  | +--    | +++ | +++  | +++   | --+                   | +++   | +++                    | +++        |
        | 3  | Numeric observable parameter overrides in measurement table    | +++                  | +--    | +++ | +++  | +++   | --+                   | +++   | +++                    | +++        |
        | 4  | Parametric observable parameter overrides in measurement table | +++                  | +--    | +++ | +++  | +++   | --+                   | +++   | +++                    | +++        |
        | 5  | Parametric overrides in condition table                        | +++                  | +--    | +++ | +++  | +++   | --+                   | +++   | +++                    | +++        |
        | 6  | Time-point specific overrides in the measurement table         | ---                  | ---    | +++ | +++  | +++   | ---                   | ---   | ---                    | +++        |
        | 7  | Observable transformations to log10 scale                      | +-+                  | +--    | +++ | ++-  | +++   | --+                   | +-+   | +-+                    | +++        |
        | 8  | Replicate measurements                                         | +++                  | +--    | +++ | +++  | +++   | --+                   | +++   | +++                    | +++        |
        | 9  | Pre-equilibration                                              | +++                  | +--    | +++ | +++  | +++   | --+                   | +++   | +++                    | +++        |
        | 10 | Partial pre-equilibration                                      | +++                  | ---    | +++ | +++  | +++   | --+                   | +++   | +++                    | +++        |
        | 11 | Numeric initial concentration in condition table               | +++                  | +--    | +++ | +++  | +++   | --+                   | +++   | +++                    | +++        |
        | 12 | Numeric initial compartment sizes in condition table           | ---                  | +--    | +++ | +++  | +++   | ---                   | ---   | ---                    | +++        |
        | 13 | Parametric initial concentrations in condition table           | +++                  | +--    | +++ | +++  | +++   | --+                   | +++   | +++                    | +++        |
        | 14 | Numeric noise parameter overrides in measurement table         | +++                  | +--    | +++ | +++  | +++   | --+                   | +++   | +++                    | +++        |
        | 15 | Parametric noise parameter overrides in measurement table      | +++                  | +--    | +++ | +++  | +++   | --+                   | +++   | +++                    | +++        |
        | 16 | Observable transformations to log scale                        | +-+                  | +--    | +++ | ++-  | +++   | --+                   | +-+   | +-+                    | +++        |
        
        Legend:
        * First character indicates whether computing simulated data is supported and simulations are correct (+) or not (-).
        * Second character indicates whether computing chi2 values of residuals are supported and correct (+) or not (-).
        * Third character indicates whether computing likelihoods is supported and correct (+) or not (-).
        
        ## Using PEtab
        
        If you would like to use PEtab yourself, please have a look at:
        
        * [a PEtab tutorial](https://petab.readthedocs.io/en/latest/tutorial.html)
          going through the individual steps of setting up a parameter estimation
          problem in PEtab, independently of any specific software
        * [the PEtab format reference](https://petab.readthedocs.io/en/stable/documentation_data_format.html)
        * the example models provided in the
          [benchmark collection](https://github.com/Benchmarking-Initiative/Benchmark-Models-PEtab).
        * the tutorials provided with each of the softwares supporting PEtab
        
        To convert your existing parameter estimation problem to the PEtab format, you 
        will have to:
        
        1. Specify your model in SBML.
        
        1. Create a condition table.
        
        1. Create a table of observables.
        
        1. Create a table of measurements.
        
        1. Create a parameter table.
        
        If you are using Python, some handy functions of the
        [PEtab library](https://petab.readthedocs.io/en/latest/modules.html) can help
        you with that. This include also a PEtab validator called `petablint` 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/PEtab-dev/PEtab/issues) at our github repository.
        
        ## PEtab Python library
        
        PEtab comes with a Python package for creating, checking, visualizing and
        working with PEtab files. This library is available on
        [pypi](https://pypi.org/project/petab/) and the easiest way to install
        it is running
        
            pip3 install petab
            
        It will require Python>=3.6 to run.
        
        Development versions of the PEtab library can be installed using
        
            pip3 install https://github.com/PEtab-dev/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.create_parameter_df` to create the parameter table, once you
            have set up the model, condition table, observable table and measurement
            table
        
          - `petab.create_combine_archive` to create a
            [COMBINE Archive](https://combinearchive.org/index/) from PEtab files
        
        ### Library examples
        
        Examples for PEtab Python library usage:
        
        * [Validation](https://github.com/PEtab-dev/PEtab/blob/master/doc/example/example_petablint.ipynb)
        * [Visualization](https://github.com/PEtab-dev/PEtab/blob/master/doc/example/example_visualization.ipynb)
        
        
        ## Getting help
        
        If you have any question or problems with PEtab, feel free to post them at
        our GitHub [issue tracker](https://github.com/PEtab-dev/PEtab/issues/).
        
        ## Contributing to PEtab
        
        Contributions and feedback to PEtab are very welcome, see our
        [contribution guide](https://github.com/petab-dev/petab/tree/master/CONTRIBUTING.md).
        
Platform: UNKNOWN
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: combine
Provides-Extra: reports
