48 lines
1.8 KiB
Markdown
48 lines
1.8 KiB
Markdown
# tdm_ripper
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The tdm_ripper provides convenient access to the TDM/TDMS data format employed by
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National Instruments LabView and DIAdem.
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## Data Format
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Datasets encoded in the TDM/TDMS format come along in pairs comprised of a
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.tdm and .tdx file. While the .tdm file is a human-readable document providing
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meta information about the dataset, the .tdx is a binary containing the actual data.
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The .tdm is represented in XML format and basically reveals what data the .tdx
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contains and how to read it. The XML tree is usually made up of several groups,
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each containing an arbitrary amount of channels.
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## Usage
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Although the package is built upon a C++ core, which decodes the data, it may be
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used as a Python module, as well, by interfacing the C++ library with a Cython
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wrapper.
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### C++ core
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- In order to parse the XML tree of the .tdm file, the library employs pugixml:
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https://pugixml.org/ and https://github.com/zeux/pugixml
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- The package currently supports the following datatypes:
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- eInt8Usi: 8 byte
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- eInt16Usi: 16 byte
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- eInt32Usi: 32 byte
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- eInt64Usi: 64 byte
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- eUInt8Usi: 8 byte
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- eUInt16Usi: 16 byte
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- eUInt32Usi: 32 byte
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- eUInt64Usi: 64 byte
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- eFloat32Usi: 32 byte
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- eFloat64Usi: 64 byte
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- main.cpp contains an example of how the C++ library might be used to provide
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the channels and groups of the dataset.
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- extract_all.cpp takes the .tdm, the .tdx file and some output directory as arguments
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to provide all given information in .csv format without any logging.
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### Python module
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- The library may also be used as a Python module and supports the use of
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group channels in NumPy arrays as shown in example.py .
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- To extract all available information and data in the TDM files without any
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further interaction, the use of extract_all.py is recommended. To exhibit the
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required arguments call $ python extract_all.py --help .
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