To help you get started, we've collected the most common ways that npTDMS is being used within popular public projects.

adamreeve / npTDMS / nptdms / types.py View on Github

@tds_data_type(8, np.uint64)
class Uint64(StructType):
    size = 8
    struct_declaration = "Q"


@tds_data_type(9, np.single)
class SingleFloat(StructType):
    size = 4
    struct_declaration = "f"


@tds_data_type(10, np.double)
class DoubleFloat(StructType):
    size = 8
    struct_declaration = "d"


@tds_data_type(11, None)
class ExtendedFloat(TdmsType):
    pass


@tds_data_type(0x19, np.single, set_np_type=False)
class SingleFloatWithUnit(StructType):
    size = 4
    struct_declaration = "f"


@tds_data_type(0x1A, np.double, set_np_type=False)

View more ways to use npTDMS

npTDMS

npTDMS is a cross-platform Python package for reading and writing TDMS files as produced by LabVIEW, and is built on top of the numpy package. Data is read from TDMS files as numpy arrays, and npTDMS also allows writing numpy arrays to TDMS files.

TDMS files are structured in a hierarchy of groups and channels. A TDMS file can contain multiple groups, which may each contain multiple channels. A file, group and channel may all have properties associated with them, but only channels have array data.

Typical usage when reading a TDMS file might look like:

from nptdms import TdmsFile

tdms_file = TdmsFile.read("path_to_file.tdms")
group = tdms_file['group name']
channel = group['channel name']
channel_data = channel[:]
channel_properties = channel.properties

The TdmsFile.read method reads all data into memory immediately. When you are working with large TDMS files or don't need to read all channel data, you can instead use TdmsFile.open. This is more memory efficient but accessing data can be slower:

with TdmsFile.open("path_to_file.tdms") as tdms_file:
    group = tdms_file['group name']
    channel = group['channel name']
    channel_data = channel[:]

npTDMS also has rudimentary support for writing TDMS files. Using npTDMS to write a TDMS file looks like:

from nptdms import TdmsWriter, ChannelObject
import numpy

with TdmsWriter("path_to_file.tdms") as tdms_writer:
    data_array = numpy.linspace(0, 1, 10)
    channel = ChannelObject('group name', 'channel name', data_array)
    tdms_writer.write_segment([channel])

For more detailed documentation on reading and writing TDMS files, see the npTDMS documentation.

Installation

npTDMS is available from the Python Package Index, so the easiest way to install it is by running:

pip install npTDMS

There are optional features available that require additional dependencies. These are hdf for hdf export, pandas for pandas DataFrame export, and thermocouple_scaling for using thermocouple scalings. You can specify these extra features when installing npTDMS to also install the dependencies they require:

pip install npTDMS[hdf,pandas,thermocouple_scaling]

Alternatively, after downloading the source code you can extract it and change into the new directory, then run:

python setup.py install

Links

Source code lives at and any issues can be reported at . Documentation is available at .

Limitations

This module doesn't support TDMS files with XML headers or with extended precision floating point data.

Contributors/Thanks

Thanks to Floris van Vugt who wrote the pyTDMS module, which helped when writing this module.

Thanks to Tony Perkins, Ruben De Smet, Martin Hochwallner and Peter Duncan for contributing support for converting to Pandas DataFrames.

Thanks to nmgeek and jshridha for implementing support for DAQmx raw data files.