{ "info": { "author": "Matthew Rankin", "author_email": "matthew@questrail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Topic :: Software Development :: Libraries :: Python Modules" ], "description": "taffmat\n=======\n\n|PyPi Version| |Build Status| |Coverage Status| |License Badge|\n\nA Python 3.4+ module for reading and writing Teac TAFFmat files.\n\nAbout the TAFFmat file format\n-----------------------------\n\nTAFFmat is Teac\u2019s proprietary file format used to store data from their\nLX series and other data recorders.\n\nAccording to the Teac \u201cLX Series Recording Unit Instruction Manual\u201d:\n\n TAFFmat (an acronym for Teac Data Acquisition File Format) is a file\n format composed of the following:\n\n - a data file containing A/D (analog to digital) converted data.\n The file is binary format with the extension dat.\n - a header file containing information such as recording\n conditions. The file is in text format with the extension hdr.\n\nTAFFmat is a trademark of Teac Corporation.\n\nData Recorders Using TAFFmat\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nThe following data recorders store their data in the TAFFmat file\nformat:\n\n- Teac\n `LX-10/20 `__\n- Teac `LX-110/120 `__\n- Teac `WX-7000 Series `__\n- Teac `es8 `__\n\nInstallation\n------------\n\nYou can install `taffmat `__\neither via the Python Package Index (PyPI) or from source.\n\nTo install using pip:\n\n.. code:: bash\n\n $ pip install taffmat\n\n**Source:** https://github.com/questrail/taffmat\n\nRequirements\n------------\n\n`taffmat `__ requires the\nfollowing Python packages:\n\n- `numpy `__\n\nPublic API\n----------\n\nThe following functions are provided:\n\n- ``change_slope(data_array, series, gain)``\n- ``read_taffmat(input_file)``\n- ``write_taffmat(data_array, header_data, output_base_filename)``\n- ``write_taffmat_slice(data_array, header_data, output_base_filename, starting_data_index, ending_data_index``\n\nContributing\n------------\n\n`taffmat `__ is developed using\n`Scott Chacon `__\\ \u2019s `GitHub\nFlow `__. To\ncontribute, fork `taffmat `__,\ncreate a feature branch, and then submit a pull request. `GitHub\nFlow `__ is\nsummarized as:\n\n- Anything in the ``master`` branch is deployable\n- To work on something new, create a descriptively named branch off of\n ``master`` (e.g., ``new-oauth2-scopes``)\n- Commit to that branch locally and regularly push your work to the\n same named branch on the server\n- When you need feedback or help, or you think the brnach is ready for\n merging, open a `pull\n request `__.\n- After someone else has reviewed and signed off on the feature, you\n can merge it into master.\n- Once it is merged and pushed to ``master``, you can and *should*\n deploy immediately.\n\nLicense\n-------\n\n`taffmat `__ is released under the\nMIT license. 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