96 lines
3.1 KiB
Markdown
96 lines
3.1 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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- The core of the library takes care of the decoding by reinterpretation of the
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binary in the buffer as the required datatype implemented by
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```C++
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uint8_t *dfcast = reinterpret_cast<uint8_t*>(&df);
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for ( int i = 0; i < (int)sizeof(double); i++ )
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{
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dfcast[i] = (int)bych[i];
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}
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```
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where for instance df is the resulting float and bych contains the binary
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data as an array of chars.
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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. It is simply build by
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```Shell
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make
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```
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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. To build:
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```Shell
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make extall
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```
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For instance, the executable accepts the following arguments:
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```Shell
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./extract_all samples/SineData.tdm samples/SineData.tdx data/
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```
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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:
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```Shell
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python extract_all.py --help
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```
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- The same functionality may be obtained from an existing python script by
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importing the tdm_ripper module and calling the extract_all function. For
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instance
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```Python
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import tdm_ripper as td
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td.extract_all(b"samples/SineData.tdm",b"samples/SineData.tdx",b"data/",b"my_tdm")
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```
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where the arguments "data/" and "my_tdm" are optional. "data/" specifies the
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directory where all .csv output is dumped while "my_tdm" represents a name
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prefix for all csv. files.
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Note, that all string arguments must be converted to bytes before passing to
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the argument list by prepending "b".
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