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@ -10,9 +10,9 @@
</p>
_TDMtermite_ is a C++ based library that decodes (encodes) the proprietary
file format _TDM/TDX_ for measurement data, which relies upon the
_technical data management_ data model. The TDM format was introduced by
[National Instruments](https://www.ni.com) and is employed by
file format _TDM/TDX_ for measurement data. First introduced by
[National Instruments](https://www.ni.com), the TDM format relies on the
_technical data management_ data model and is employed by
[LabVIEW](https://www.ni.com/de-de/shop/labview.html), LabWindows™/CVI™,
Measurement Studio, SignalExpress, and [DIAdem](https://www.ni.com/de-de/shop/data-acquisition-and-control/application-software-for-data-acquisition-and-control-category/what-is-diadem.html).
@ -25,18 +25,18 @@ Measurement Studio, SignalExpress, and [DIAdem](https://www.ni.com/de-de/shop/da
## Dataformat
Datasets encoded in the TDM/TDX format come along in pairs comprised of a
.tdm (header) and a .tdx (data) file. While the .tdm file is a human-readable
file providing meta information about the data set, the .tdx is a binary
Datasets encoded in the TDM/TDX format come in pairs comprised of a
.tdm (header) file and a .tdx (data) file. While the .tdm file is a human-readable
file providing meta information about the dataset, the .tdx file is a binary file
containing the actual data. The .tdm based on the _technical data management_
model is an XML file and basically describes what data the .tdx contains and how
model is an XML file. It describes what data the .tdx file contains and how
to read it. The
[TDM data model](https://www.ni.com/de-de/support/documentation/supplemental/10/ni-tdm-data-model.html)
structures the data hierarchically with respect to _file_, (channel) _groups_ and
_channels_. The file level XML may contain any number of (channel) groups each
structures the data hierarchically with respect to _file_, _(channel)_ _groups_ and
_channels_. The file-level XML may contain any number of (channel) groups, each
of which is made up of an arbitrary number of channels. Thus, the XML tree in
the [TDM header file](https://zone.ni.com/reference/de-XX/help/370858P-0113/tdmdatamodel/tdmdatamodel/tdm_headerfile/)
looks basically like this:
looks like this:
```xml
<?xml version="1.0" encoding="UTF-8" standalone="no" ?>
@ -67,14 +67,14 @@ looks basically like this:
</usi:tdm>
```
and is comprised of _four_ main XML elements: `usi:documentation`, `usi:model`,
The XML tree is comprised of _four_ main XML elements: `usi:documentation`, `usi:model`,
`usi:include` and `usi:data`. The element `usi:include` references the data file
`example.tdx` and reveals one of _two_ possible orderings of the mass data (.tdx):
1. either _channel wise_ (`<block>`) - all values of a specific channel follow subsequently -
1. or _block wise_ (`<block_bm>`) - all values of a specific measurement time follow subsequently -
1. either _channel-wise_ (`<block>`) - all values of a specific channel follow subsequently
1. or _block-wise_ (`<block_bm>`) - all values of a specific measurement time follow subsequently.
ordering. The supported _numerical data types_ are
The supported _numerical data types_ are:
| datatype | channel datatype | numeric | value sequence | size | description |
|-------------|------------------|---------|-----------------|-------|-------------------------|
@ -87,10 +87,10 @@ ordering. The supported _numerical data types_ are
| eFloat64Usi | DT_DOUBLE | 7 | double_sequence | 8byte | 64 Bit double |
| eStringUsi | DT_STRING | 1 | string_sequence | | text |
The XML element `<usi:data>` is basically comprised of _five_ different types of
The XML element `<usi:data>` is comprised of _five_ different types of
elements that are `<tdm_root>`, `<tdm_channelgroup>`, `<tdm_channel>`, `<localcolumn>`
and `<submatrix>`. The root element `<tdm_root>` describes the general properties
of the dataset and lists the _id's_ of all channel groups that belong to
of the dataset and lists the _ids_ of all channel groups that belong to
the dataset. The element `<tdm_channelgroup>` divides the _channels_ into groups
and has a unique _id_ that is referenced by its root element. The `<channels>`
element in `<tdm_channelgroup>` lists the unique ids of all channels that belong
@ -110,7 +110,7 @@ actual data including its datatype. The remaining element types are
</localcolumn>
```
with a unique id, the `<measurement_quantity>` refering to one specific channel,
with a unique id, the `<measurement_quantity>` referring to one specific channel,
the `<submatrix>` and its id respectively, the type of representation in
`<sequence_representation>` - being one of _explicit_, _implicit linear_ or
_rawlinear_ - and the `<values>` element, which refers to one _value sequence_,
@ -125,49 +125,49 @@ and the element `<submatrix>`
</submatrix>
```
that references the channel group in `<measurement>` it belongs to and provides
that references the channel group in `<measurement>` to which it belongs and provides
the _number of rows_ in the channels listed in `<local_columns>`.
## Installation
The library can be used both as a _CLI_ based tool and as a _Python_ module.
The library can be used both as a _CLI_-based tool and as a _Python_ module.
### CLI tool
To install the CLI tool _tdmtermite_ do
To install the CLI tool _TDMtermite_, do
```Shell
make install
```
which uses `/usr/local/bin` as installation directory. On _macOSX_ please first
which uses `/usr/local/bin` as an installation directory. On _macOSX_, please first
build the binary locally with `make` and install it in your preferred location.
### Python
In order to build a _Python module_ from the _C++_ code base the
In order to build a _Python module_ from the _C++_ code base, the
[Cython](https://cython.readthedocs.io/en/latest/index.html) package must be
available, which may be installed via `python3 -m pip install cython` .
Furthermore, the [Numpy](https://numpy.org) package is recommended to be able
available. It may be installed via `python3 -m pip install cython` .
The [Numpy](https://numpy.org) package is recommended
to pass arrays of data from the C++ kernel to Python. The _makefile_ provides
the target `make cython-requirements` to install all required Python modules.
Finally, to build the Python extension _tdm_termite_ either locally or install
it the targets `make cython-build` and `make cython-install` are provided.
Hence, to install the Python module on the system simply do
Finally, to build the Python extension _tdm_termite_ locally or install
it, the targets `make cython-build` and `make cython-install` are provided.
To install the Python module on the system, simply do
```Shell
make cython-requirements
make cython-install
```
that makes the module available to be imported as `import tdm_termite` .
That makes the module available for import as a `import tdm_termite` .
## Usage
### CLI tool
The usage of the CLI tool is sufficiently clarified by its help message displayed
by `tdmtermite --help`. For instance, to extract the data decoded in the pair of
by `tdmtermite --help`. To extract the data decoded in the pair of
files `samples/SineData.tdm` and `samples/SineData.tdx` into the directory
`/home/jack/data/`:
@ -176,7 +176,7 @@ tdmtermite samples/SineData.tdm samples/SineData.tdx --output /home/jack/data
```
The tool can also be used to list the available objects in the TDM dataset, which
are i.a. _channels_, _channelgroups_ and TDX _blocks_. For instance, to list
are i.a. _channels_, _channelgroups_ and TDX _blocks_. To list
all channels and channelgroups (without writing any file output):
```Shell
@ -184,37 +184,37 @@ tdmtermite samples/SineData.tdm samples/SineData.tdx --listgroups --listchannels
```
The user may also submit a _filenaming rule_ to control the names of the files the
channel(-group)s are written to. To this end, the _magic flags_ `%G` `%g`, `%C`
channel(group)s are written to. To this end, the _magic flags_ `%G` `%g`, `%C`
and `%c` representing the group id, group name, channel index and channel name
are defined. The default filenaming option is
are defined. The default filenaming option is:
```Shell
tdmtermite samples/SineData.tdm samples/SineData.tdx --output /home/jack/data --filenames channelgroup_%G.csv
```
which makes the tool write _all channels_ grouped into files according to their
group association, while all channelgroup filenames obey the pattern `channelgroup_%G.csv`
This makes the tool write _all channels_ grouped into files according to their
group association, while all channelgroup filenames obey the pattern `channelgroup_%G.csv`,
with `%G` being replaced by the group id. The filenaming rule also enables the user
to extract only a single channel(group) by providing a particular channel(-group)
to extract only a single channel(group) by providing a particular channel(group)
id in the filenaming flag. For example,
```Shell
tdmtermite samples/SineData.tdm samples/SineData.tdx --output /home/jack/data -f channel_usi16_%c.csv --includemeta
```
will write the single channel with id `usi16` to the file
`/home/jack/data/channel_usi16_A4.csv` including its meta-data as a file header.
This will write the single channel with the id `usi16` to the file
`/home/jack/data/channel_usi16_A4.csv`, including its meta-data as a file header.
### Python
To be able to use the Python module _tdm_termite_ it first has to be build locally
or installed on the system. In the Python interpreter simply do:
To be able to use the Python module _tdm_termite_, it first has to be built locally
or installed on the system. In the Python interpreter, simply do:
```Python
import tdm_termite
```
to import the module. The TDM files are provided by creating an instance of
This will import the module. The TDM files are provided by creating an instance of
the _tdm_termite_ class:
```Python
@ -225,7 +225,7 @@ except RuntimeError as e:
print("failed to load/decode TDM files: " + str(e))
```
After initializing the _tdm_termite_ object it can be used to extract any of the
After initializing the _tdm_termite_ object, it can be used to extract any of the
available data. For instance, to list the included channelgroups and channels:
```Python
@ -274,7 +274,7 @@ for grp in grpids :
print("failed to print channelgroup: " + str(grp) + " : " + str(e))
```
For a full example including more details see the [extensive example](python/usage.py)
For details, see this [extensive example](python/usage.py)
and the absolute minimal example [minimal usage](python/minimal.py). In order
to simply extract all data of the TDM datatset and dump it to files in a given
(existing!) directory, do
@ -285,8 +285,8 @@ jack = tdm_termite.tdmtermite(b'samples/SineData.tdm',b'samples/SineData.tdx')
jack.write_all(b"./my_tdm_data_directory/")
```
The interface allows to construct customized file/column headers from any
meta-data and provide these headers for usage in file output (see the
The interface allows you to construct customized file/column headers from any
meta-data and provide these headers for usage in file output (see this
[example](python/custom.py)).
## References