pyuvdata defines a pythonic interface to interferometric data sets. Currently pyuvdata supports reading and writing of miriad, uvfits, CASA measurement sets and uvh5 files and reading of FHD (Fast Holographic Deconvolution) visibility save files, SMA Mir files and MWA correlator FITS files.
Documentation of the API, conventions used throughout the package, and a tutorial is hosted on ReadTheDocs.
The main goals are:
pyuvdata has four major user classes:
importuvfits task does not seem to support >255 antennas. Because of this and other limitations to CASA's importuvfits task, we reccommend that users planning to work in CASA avoid using importuvfits and use the measurement set writer instead.cotter), ALMA, and SMA (filled using the importuvfits task). Extensive loopback testing has been done to verify that pyuvdata written measurement sets are compatible with CASA.See our issue log for a full list.
Contributions to this package to add new file formats or address any of the issues in the issue log are very welcome, as are bug reports and feature requests. Please see our guide on contributing
pyuvdata has been used with data from the following telescopes. If you use it on data from a telescope we don't have listed here please let us know how it went via an issue! We would like to make pyuvdata generally useful to the community for as many telescopes as possible.
We use a generation.major.minor version number format. We use the generation number for very significant improvements or major rewrites, the major number to indicate substantial package changes (intended to be released every 3-4 months) and the minor number to release smaller incremental updates (intended to be released approximately monthly and which usually do not include breaking API changes). We do our best to provide a significant period (usually 2 major generations) of deprecation warnings for all breaking changes to the API. We track all changes in our changelog.
pyuvdata was originally developed in the low frequency 21cm community to support the development of and interchange of data between calibration and foreground subtraction pipelines. Particular focus has been paid to supporting drift and phased array modes.
Please cite both of our JOSS papers:
Keating et al., (2025). pyuvdata v3: an interface for astronomical interferometric data sets in Python. Journal of Open Source Software, 10(109), 7482, https://doi.org/10.21105/joss.07482 [ADS Link]
Hazelton et al, (2017), pyuvdata: an interface for astronomical interferometeric datasets in python, Journal of Open Source Software, 2(10), 140, doi:10.21105/joss.00140 [ADS Link]
Simple installation via conda is available for users, developers should follow the directions under Developer Installation below.
For simple installation, the latest stable version is available via conda (preferred: conda install -c conda-forge pyuvdata) or pip (pip install pyuvdata).
There are some optional dependencies that are required for specific functionality, which will not be installed automatically by conda or pip. See Dependencies for details on installing optional dependencies.
Required:
Optional:
The numpy and astropy versions are important, so make sure these are up to date.
We suggest using conda to install all the dependencies. If you want to install python-casacore and astropy-healpix, you'll need to add conda-forge as a channel (conda config --add channels conda-forge).
If you do not want to use conda, the packages are also available on PyPI (python-casacore may require more effort, see details for that package below). You can install the optional dependencies via pip by specifying an option when you install pyuvdata, as in pip install pyuvdata[healpix] which will install all the required packages for using the HEALPix functionality in pyuvdata. The options that can be passed in this way are:
astroquerycasahdf5_compressionhealpixlunarnovasalltutorialtestdocdevThe first set (astroquery, casa, hdf5_compression, healpix, lunar, and novas) enable various specific functionality while all will install all of the above to enable all functionality. The last three (test, doc and dev) include everything installed with all plus packages for testing and building the docs which may be useful for developers of pyuvdata.
python-casacore requires the casacore c++ libraries. It can be installed easily using conda (python-casacore on conda-forge).
If you do not want to use conda, the casacore c++ libraries are available for ubuntu through the kern suite. On OSX, casacore is available through the ska-sa brew tap. The python-casacore library (with manual install instructions) is available at https://github.com/casacore/python-casacore
Clone the repository using git clone https://github.com/RadioAstronomySoftwareGroup/pyuvdata.git
Navigate into the pyuvdata directory and run pip install . (note that python setup.py install does not work). Note that this will attempt to automatically install any missing dependencies. If you use conda or another package manager you might prefer to first install the dependencies as described in Dependencies.
To install without dependencies, run pip install --no-deps .
To compile the binary extension modules such that you can successfully run import pyuvdata from the top-level directory of your Git checkout, run: python setup.py build_ext --inplace
If you want to do development on pyuvdata, in addition to the other dependencies you will need the following packages:
We manage our test data using pooch, which will download the file the first time it's needed and save it in a cache folder, subsequent calls to fetch that data will not re-download it. The test data are hosted in the RASG datasets repo, organized by data type and telescope. In the tests this data is downloaded and cached using pooch via the pyuvdata.datasets.fetch_data function. For more details and directions on adding test data see the developer docs
One other package, pytest-xdist, is not required, but can be used to speed up running the test suite by running tests in parallel. To use it call pytest with the -n auto option.
One way to ensure you have all the needed packages is to use the included environment.yaml file to create a new environment that will contain all the optional dependencies along with dependencies required for testing and development (conda env create -f environment.yaml). Alternatively, you can specify test, doc, or dev when installing pyuvdata (as in pip install pyuvdata[dev]) to install the packages needed for testing (including coverage and linting) and documentation development; dev includes everything in test and doc.
To use pre-commit to prevent committing code that does not follow our style, you'll need to run pre-commit install in the top level pyuvdata directory.
Uses the pytest package to execute test suite. From the source pyuvdata directory run pytest or python -m pytest.
Testing of UVFlag module requires the pytest-cases plug-in.
pyuvdata is organized around objects that contain all the data and metadata required to represent and work with interferometric data, calibration solutions, flags, antenna beams and telescope layouts. Each object has the data and metadata as attributes along with many useful methods for importing and exporting files and manipulating and transforming the data in useful ways. Please see our extensive documentation on ReadTheDocs for tutorials and complete API details.
pyuvdata is maintained by the RASG Managers, which currently include:
Please use the channels discussed in the guide on contributing for code-related discussions. You can contact us privately if needed at rasgmanagers@gmail.com.
Support for pyuvdata was provided by NSF awards #1835421 and #1835120.
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