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# pyuvdata


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.

API documentation and a tutorial is hosted on [ReadTheDocs](

# Motivation
The main goals are:

1. To provide a high quality, well documented path to convert between data formats
2. Support the direct use of datasets from python with minimal software
3. Provide precise data definition via both human readable code and high quality online documentation

# Package Details
pyuvdata has four major user classes:

* UVData: supports interferometric data (visibilities) and associated metadata
* UVCal: supports interferometric calibration solutions (antenna-based) and
associated metadata (Note that this is a fairly new object, consider it to be a beta version)
* UVBeam: supports primary beams (E-field or power) and associated metadata
(Note that this is a fairly new object, consider it to be a beta version)
* UVFlag: A class to handle the manipulation and combination of flags for data sets.
Also can convert raw data quality metrics into flags using thresholding.
(This object is very new and experimental. Consider it to be a beta version)

## UVData File standard notes
* miriad has been thoroughly tested with aipy-style miriad files and minimally
tested with ATCA files
* uvfits conforms to AIPS memo 117 (as of March 2020).  It is tested against
FHD, CASA, and AIPS. However AIPS is limited to <80 antennas and CASA uvfits
import does not seem to support >255 antennas. Users with data sets containing > 255
antennas should use the measurement set writer instead.
* CASA measurement sets, primarily conforming to [CASA Memo 229](, with some elements taken from the proposed v3.0 format documented in [CASA Memo 264]( Measurement sets are tested against
VLA and MWA data sets, (the latter filled via cotter), with some manual verification
haven been performed against ALMA and SMA data sets, the latter filled using the `importuvfits` task of CASA.
tested against ALMA-filled datasets and with SMA datasets
* uvh5 is an HDF5-based file format defined by the HERA collaboration,
details in the [uvh5 memo](docs/references/uvh5_memo.pdf). Note that this is a
somewhat new format, so it may evolve a bit
but we will strive to make future versions backwards compatible with the current format.
It is probably not compatible with other interferometric HDF5 files defined by other groups.
* FHD (read-only support, tested against MWA and PAPER data)
* MIR (read-only support, tested against SMA data)
* MWA correlator FITS files (read-only support, tested against Cotter outputs and FHD)

## UVCal file formats
* calfits: a new format defined in pyuvdata, details in the [calfits_memo](docs/references/calfits_memo.pdf).
Note that this format was recently defined and may change in coming versions,
based on user needs. Consider it to be a beta version, but we will strive to
make future versions backwards compatible with the current format.
* FHD calibration files (read-only support)

## UVBeam file formats
* regularly gridded fits for both E-field and power beams
* non-standard HEALPix fits for both E-field and power beams (in an ImageHDU
rather than a binary table to support frequency, polarization and E-field vector axes)
* read support for CST beam text files, with a defined yaml file format for
metadata, details here: [cst settings file](docs/cst_settings_yaml.rst)

## Under Development
* UVCal: object and calfits file format (beta version)
* UVBeam: object and beamfits file format (beta version)
* UVFlag: object and HDF5 file format. (beta version)
* Mir: object (part of UVData class) (beta version)
* MirParser: object and python interface for MIR file format (beta version)

## Known Issues and Planned Improvements
* UVBeam: support phased-array antenna beams (e.g. MWA beams).
* UVFlag: Adding requires a high level knowledge of individual objects. (see [issue #653](

For details see the [issue log](

## Community Guidelines
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](.github/

# Telescopes
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.


# Versioning
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](

# History
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.

# Citation
Please cite pyuvdata by citing our JOSS paper:

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](;
[Bibtex entry](

# Installation
Simple installation via conda is available for users, developers should follow
the directions under [Developer Installation](#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](#dependencies) for details on installing optional dependencies.

Note that as of v2.2, `pyuvdata` is only supported on python 3.7+.

## Dependencies


* astropy >= 4.2.1
* h5py >= 3.0
* numpy >= 1.18
* pyerfa >= 2.0
* scipy
* setuptools_scm


* python-casacore >= 3.1.0 (for working with CASA measurement sets)
* astropy-healpix (for working with beams in HEALPix formats)
* pyyaml (for working with settings files for CST beam files)
* novas and novas_de405 (for using the NOVAS library for astrometry)
* astroquery >= 0.4.4 (for enabling lookup functionality with JPL-Horizons)

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:
[`casa`, `healpix`, `cst`, `all`, `test`, `doc`, `dev`]. The first three (`casa`, `healpix`, `cst`)
enable various specific functionality while `all` will install all optional
dependencies. The last three (`test`, `doc`, `dev`) may be useful for developers
of pyuvdata.

### Installing python-casacore
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

## Developer Installation
Clone the repository using
```git clone```

Navigate into the pyuvdata directory and run `pip install .`
(note that `python install` does not work).
Note that this will attempt to automatically install any missing dependencies.
If you use anaconda or another package manager you might prefer to first install
the dependencies as described in [Dependencies](#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 build_ext --inplace```

If you want to do development on pyuvdata, in addition to the other dependencies
you will need the following packages:

* pytest >= 6.2
* pytest-cases >= 3.6.9
* pytest-cov
* cython >=0.23  (This is necessary for coverage reporting of cython extensions)
* coverage
* pre-commit
* sphinx
* pypandoc

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.

## Tests
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.

The primary interface to data from python is via the UVData object. It provides
import functionality from all supported file formats (UVFITS, Miriad, UVH5, FHD,
CASA measurement sets, SMA Mir, MWA correlator FITS) and export to UVFITS, Miriad,
CASA measurement sets and UVH5 formats and can
be interacted with directly. Similarly, the primary calibration, beam, and flag
interfaces are via the UVCal, UVBeam, and UVflag objects. The attributes of the UVData,
UVCal, UVBeam, and UVFlag objects are described in the UVData Parameters, UVCal Parameters,
UVBeam Parameters and UVFlag Parameters pages on [ReadTheDocs](

# Maintainers
pyuvdata is maintained by the RASG Managers, which currently include:

 - Adam Beardsley (Winona State University)
 - Bryna Hazelton (University of Washington)
 - Daniel Jacobs (Arizona State University)
 - Matt Kolopanis (Arizona State University)
 - Paul La Plante (University of California, Berkeley)
 - Jonathan Pober (Brown University)

Please use the channels discussed in the [guide on contributing](.github/
for code-related discussions. You can contact us privately if needed at
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