README: update python usage

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Mario Fink 2021-01-26 13:28:04 +01:00
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README.md
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@ -200,110 +200,38 @@ will write the single channel with id `usi16` to the file
### Python
...tbc...
To be able to use the Python module _tdm_reaper_ it first has to be build locally
or installed on the system. In the Python interpreter simply do:
## !!! Deprecated !!!
The makefile provides targets for using the library both as native C++ extension
and as Python module. The package supports usage on Linux and MacOSX.
The tdm_ripper module is built on these platforms by
```Shell
# Linux
pip install Cython
make install
```Python
import tdm_reaper
```
and
to import the module. The TDM files are provided by creating an instance of
the _tdm_reaper_ class:
```Shell
# macOS
pip install Cython
make install_osx
```Python
# create 'tdm_reaper' instance object
try :
jack = tdm_reaper.tdmreaper(b'samples/SineData.tdm',b'samples/SineData.tdx')
except RuntimeError as e:
print("failed to load/decode TDM files: " + str(e))
```
## Usage
After initializing the _tdm_reaper_ object it can be used to extract any of the
available data. For instance, to list the included channelgroups and channels:
Although the package is built upon a C++ core, which decodes the data, it may be
used as a Python module, as well, by interfacing the C++ library with a Cython
wrapper.
```Python
# list ids of channelgroups
grpids = jack.get_channelgroup_ids()
### C++ core
- In order to parse the XML tree of the .tdm file, the library employs pugixml:
https://pugixml.org/ and https://github.com/zeux/pugixml
- The package currently supports the following datatypes:
- eInt8Usi: 8 byte
- eInt16Usi: 16 byte
- eInt32Usi: 32 byte
- eInt64Usi: 64 byte
- eUInt8Usi: 8 byte
- eUInt16Usi: 16 byte
- eUInt32Usi: 32 byte
- eUInt64Usi: 64 byte
- eFloat32Usi: 32 byte
- eFloat64Usi: 64 byte
- The core of the library takes care of the decoding by reinterpretation of the
binary in the buffer as the required datatype implemented by
# list ids of channels
chnids = jack.get_channel_ids()
```
```C++
uint8_t *dfcast = reinterpret_cast<uint8_t*>(&df);
for ( int i = 0; i < (int)sizeof(double); i++ )
{
dfcast[i] = (int)bych[i];
}
```
where for instance df is the resulting float and bych contains the binary
data as an array of chars.
- main.cpp contains an example of how the C++ library might be used to provide
the channels and groups of the dataset. It is simply build by
```Shell
make
```
- extract_all.cpp takes the .tdm, the .tdx file and some output directory as arguments
to provide all given information in .csv format without any logging. To build:
```Shell
make extall
```
For instance, the executable accepts the following arguments:
```Shell
./extract_all samples/SineData.tdm samples/SineData.tdx data/
```
### Python module
- The library may also be used as a Python module and supports the use of
group channels in NumPy arrays as shown in example.py .
- To extract all available information and data in the TDM files without any
further interaction, the use of extract_all.py is recommended. To exhibit the
required arguments:
```Shell
python extract_all.py --help
```
- The same functionality may be obtained from an existing python script by
importing the tdm_ripper module and calling the extract_all function. For
instance
```Python
import tdm_ripper as td
files = td.extract_all(b"samples/SineData.tdm",b"samples/SineData.tdx",b"data/",b"my_tdm")
```
where the arguments "data/" and "my_tdm" are optional. "data/" specifies the
directory where all .csv output is dumped while "my_tdm" represents a name
prefix for all csv. files.
Note, that all string arguments must be converted to bytes before passing to
the argument list by prepending "b".
For a full example and to see how the actual data is extracted see the example
`python/usage.py`.
## References