taffmat 0.4.0

Read and write Teac TAFFmat files.

A Python (2.7, 3.3, 3.4) module for reading and writing Teac TAFFmat files.

About the TAFFmat file format

TAFFmat is Teac’s proprietary file format used to store data from their LX series and other data recorders.

According to the Teac “LX Series Recording Unit Instruction Manual”:

TAFFmat (an acronym for Teac Data Acquisition File Format) is a file format composed of the following:

• a data file containing A/D (analog to digital) converted data. The file is binary format with the extension dat.

• a header file containing information such as recording conditions. The file is in text format with the extension hdr.

TAFFmat is a trademark of Teac Corporation.

Data Recorders Using TAFFmat

The following data recorders store their data in the TAFFmat file format:

• Teac LX-10/20

• Teac LX-110/120

• Teac WX-7000 Series

• Teac es8

Installation

You can install taffmat either via the Python Package Index (PyPI) or from source.

To install using pip:

$ pip install taffmat

Source: https://github.com/questrail/taffmat

Requirements

taffmat requires the following Python packages:

• numpy

Public API

The following functions are provided:

• change_slope(data_array, series, gain)

• read_taffmat(input_file)

• write_taffmat(data_array, header_data, output_base_filename)

• write_taffmat_slice(data_array, header_data, output_base_filename, starting_data_index, ending_data_index

Contributing

taffmat is developed using Scott Chacon’s GitHub Flow. To contribute, fork taffmat, create a feature branch, and then submit a pull request. GitHub Flow is summarized as:

• Anything in the master branch is deployable

• To work on something new, create a descriptively named branch off of master (e.g., new-oauth2-scopes)

• Commit to that branch locally and regularly push your work to the same named branch on the server

• When you need feedback or help, or you think the brnach is ready for merging, open a pull request.

• After someone else has reviewed and signed off on the feature, you can merge it into master.

• Once it is merged and pushed to master, you can and should deploy immediately.

License

taffmat is released under the MIT license. Please see the LICENSE.txt file for more information.