Skip to main content

Python wrapper for efmtool.

Project description

Python wrapper for efmtool

efmtool is a Java software for the enumeration of Elementary Flux Modes (EFMs) developed by Marco Terzer at ETH Zurich. This package provides a simple Python wrapper.

Installation

pip install efmtool

Usage

The wrapper provides two ways of calling efmtool:

  1. Through a simplified interface:

    efms = efmtool.calculate_efms(
        stoichiometry : np.array,
        reversibilities : List[int],
        reaction_names : List[str],
        metabolite_names : List[str],
        options : Dict = None,
        jvm_options : List[str] = None)
    

    This function directly returns a NumPy array containing all the EFMs of the specified network (example). reversibilities is a list indicating whether a reaction is reversible (1) or not (0). Note that irreversibilities are assumed to be in forward directions. If a reaction is irreversible in the backward direction, it should be reversed before calling efmtool. Default options can be obtained through get_default_options().

  2. Through a generic wrapper:

    efmtool.call_efmtool(
        args : List[str],
        jvm_options : List[str] = None)
    

    The wrapper simply calls efmtool passing the specified arguments. Specifying, writing and reading input/output temporary files is responsibility of the user.

See config/metabolic-efm.xml, the documentation, or run java -cp lib/metabolic-efm-all.jar ch.javasoft.metabolic.efm.main.CalculateFluxModes --help for more information about the available options.

Cite us

If you use efmtool in a scientific publication, please cite our paper:

Terzer, M., Stelling, J., 2008. "Large-​scale computation of elementary flux modes with bit pattern trees". Bioinformatics. - link

Credits

efmtool is a software written by Marco Terzer (ETH Zurich).

Python wrapper by Mattia Gollub (ETH Zurich).

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

efmtool-0.1.5.tar.gz (5.6 MB view details)

Uploaded Source

Built Distribution

efmtool-0.1.5-py2.py3-none-any.whl (5.6 MB view details)

Uploaded Python 2 Python 3

File details

Details for the file efmtool-0.1.5.tar.gz.

File metadata

  • Download URL: efmtool-0.1.5.tar.gz
  • Upload date:
  • Size: 5.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.0 requests/2.24.0 setuptools/50.3.0.post20201006 requests-toolbelt/0.9.1 tqdm/4.50.2 CPython/3.8.5

File hashes

Hashes for efmtool-0.1.5.tar.gz
Algorithm Hash digest
SHA256 c21fd2d35ecd31845db3ea52b6867771445725a2a0b35e2b9b04c92354a80839
MD5 c44fd78a0a196e7431045117a6fc0816
BLAKE2b-256 b58afe8c8913ab29aed7b199b12e5f6247ed4597c52ebfc5898f919c4f2109a6

See more details on using hashes here.

Provenance

File details

Details for the file efmtool-0.1.5-py2.py3-none-any.whl.

File metadata

  • Download URL: efmtool-0.1.5-py2.py3-none-any.whl
  • Upload date:
  • Size: 5.6 MB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.0 requests/2.24.0 setuptools/50.3.0.post20201006 requests-toolbelt/0.9.1 tqdm/4.50.2 CPython/3.8.5

File hashes

Hashes for efmtool-0.1.5-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 33e05c1295eeb8bcae5d8c022d59c223abbced855368aff622735bc8bd90ab66
MD5 11b062923c152cba121c1af8bc365311
BLAKE2b-256 df8e8ad8a7e46bf2c0628bcc6566b78fa414468211fc83028018521a21b73040

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page