What’s New in Astropy 5.2?


Astropy 5.2 is a major release that adds significant new functionality since the 5.1 release.

In particular, this release includes:

In addition to these major changes, Astropy 5.2 includes a large number of smaller improvements and bug fixes, which are described in the Full change log. By the numbers:

  • 1065 commits have been added since 5.1

  • 157 issues have been closed since 5.1

  • 320 pull requests have been merged since 5.1

  • 50 people have contributed since 5.1

  • 18 of which are new contributors

Quantity data types

The default dtype argument for Quantity has been changed, so that one can now explicitly give dtype=None to get the same behaviour as numpy. Without an explicit argument, any integer values are still upcast to floating point, since that makes more sense for physical quantities.

Updates to astropy.cosmology

A new comparison function has been added – astropy.cosmology.cosmology_equal() – that mirrors its numpy counterparts but allows for the arguments to be converted to a Cosmology and to compare flat cosmologies with their non-flat equivalents.

>>> from astropy.cosmology import cosmology_equal
>>> from astropy.cosmology import FlatLambdaCDM, LambdaCDM
>>> cosmo1 = FlatLambdaCDM(70, 0.3)
>>> cosmo2 = LambdaCDM(70, 0.3, 0.7)
>>> cosmology_equal(cosmo1.to_format("mapping"), cosmo2,
...                 format=("mapping", None), allow_equivalent=True)

A cosmology can be parsed from or converted to a HTML table using the new HTML methods in Cosmology’s to/from_format I/O.

>>> from astropy.cosmology import Planck18
>>> Planck18.write("planck18.html")

The columns can be latex/mathjax formatted using the flag latex_names=True; then if the following is added to the file’s header, the column names will render nicely.:

<script type="text/javascript" id="MathJax-script" async

Topocentric ITRS Frame

A topocentric ITRS frame has been added that makes dealing with near-Earth objects easier and more intuitive.:

>>> from astropy.coordinates import EarthLocation, AltAz, ITRS
>>> from astropy.time import Time
>>> from astropy import units as u

>>> t = Time('J2010')
>>> obj = EarthLocation(-1*u.deg, 52*u.deg, height=10.*u.km)
>>> home = EarthLocation(-1*u.deg, 52*u.deg, height=0.*u.km)

>>> # Direction of object from GEOCENTER
>>> itrs_geo = obj.get_itrs(t).cartesian

>>> # now get the Geocentric ITRS position of observatory
>>> obsrepr = home.get_itrs(t).cartesian

>>> # topocentric ITRS position of a straight overhead object
>>> itrs_repr = itrs_geo - obsrepr

>>> # create an ITRS object that appears straight overhead for a TOPOCENTRIC OBSERVER
>>> itrs_topo = ITRS(itrs_repr, obstime=t, location=home)

>>> # convert to AltAz
>>> aa = itrs_topo.transform_to(AltAz(obstime=t, location=home))

Performance Improvements

To help speed up coordinate transformations, several performance improvements were implemented, mainly concerning validity checks in Angle and how FrameAttributes are accessed. Performance improvements will vary between different tasks, e.g., the speedup of transforming AltAz coordinates to ICRS is 5-10 % depending on the number of coordinates.

Enhanced Fixed Width ASCII Tables

It is now possible to read and write a fixed width ASCII table that includes additional header rows specifying any or all of the column dtype, unit, format, and description. This is available in the fixed_width and fixed_width_two_line formats via the new header_rows keyword argument:

>>> from astropy.io import ascii
>>> from astropy.table.table_helpers import simple_table
>>> dat = simple_table(size=3, cols=4)
>>> dat["b"].info.unit = "m"
>>> dat["d"].info.unit = "m/s"
>>> dat["b"].info.format = ".2f"
>>> ascii.write(
...     dat,
...     format="fixed_width_two_line",
...     header_rows=["name", "unit", "format"]
... )
a    b c     d
     m   m / s
- ---- - -----
1 1.00 c     4
2 2.00 d     5
3 3.00 e     6

Accessing cloud-hosted FITS files

A use_fsspec argument has been added to astropy.io.fits.open which enables users to seamlessly extract data from FITS files stored on a web server or in the cloud without downloading the entire file to local storage. This feature uses a new optional dependency, fsspec, which supports a range of remote and distributed storage backends including Amazon and Google Cloud Storage. For example, you can now access a Hubble Space Telescope image located in Hubble’s public Amazon S3 bucket as follows:

>>> from astropy.io import fits
>>> uri = "s3://stpubdata/hst/public/j8pu/j8pu0y010/j8pu0y010_drc.fits"
>>> with fits.open(uri, fsspec_kwargs={"anon": True}) as hdul:  
...     # Download a single header
...     header = hdul[1].header
...     # Download a single image
...     mydata = hdul[1].data
...     # Download a small cutout
...     cutout = hdul[1].section[10:20, 30:50]

Note that the example above obtains a cutout image using the section attribute rather than the traditional data attribute. The use of .section ensures that only the necessary parts of the FITS image are transferred from the server, rather than downloading the entire data array. This trick can significantly speed up your code if you require small subsets of large FITS files located on slow (remote) storage systems. See Obtaining subsets from cloud-hosted FITS files for additional information on working with FITS files in this way.

Drawing the instrument beam and a physical scale bar on celestial images

Two functions have been added to wcsaxes: add_beam() and add_scalebar(). These functions allow to draw the shape of the instrument beam (e.g.for radio observations) and a physical scale bar on celestial images:

>>> from astropy.io import fits
>>> from astropy.wcs import WCS
>>> from astropy import units as u
>>> from astropy.visualization.wcsaxes import add_beam, add_scalebar
>>> import matplotlib.pyplot as plt
>>> uri = "https://cdsarc.cds.unistra.fr/ftp/J/A+A/610/A24/fits/as209_sc_flagged_cont.image.pbcor_uniform.fits"
>>> with fits.open(uri, fsspec_kwargs={"anon": True}) as hdul:  
...    header = hdul[0].header
...    wcs = WCS(header, naxis=(1,2))
...    data = hdul[0].data.squeeze()
...    ax = plt.subplot(projection=wcs, xlim=(442, 582), ylim=(442, 582))
...    ax.imshow(data)
...    # Draw the beam shape (from the header)
...    add_beam(ax, header=header, frame=True)
...    # Draw a scale bar corresponding to 100 au at a distance of 126 pc
...    add_scalebar(ax, 100./126. * u.arcsec, label="100 au", color="white")

Interior ticks and tick labels

The default locations of ticks and tick labels for a WCSAxes rectangular plot are the edges of the frame. It is now possible to place ticks or tick labels in the interior of the plot by using add_tickable_gridline() to define a new “tickable” gridline. Here is an example plot that uses this new functionality:

glon, glat = ax.get_coords_overlay('galactic')

glat.add_tickable_gridline('const-glat', 0*u.deg)
glon.add_tickable_gridline('const-glon', 0*u.deg)

glon.set_axislabel('Galactic Longitude', color='magenta')

glat.set_ticklabel_position(('const-glon', 'r'))
glat.set_axislabel('Galactic Latitude', color='blue')

(png, svg, pdf)


Support for tilde-prefixed paths

This release finishes adding support for tilde-prefixed paths, which began in 5.1. These are paths of the form ~/data/file.fits or ~<username>/data/file.fits. The single tilde refers to the current user’s home directory, while a tilde followed by a valid username refers to that user’s home directory (e.g. /home/<username> on Linux or /Users/<username> on macOS). This syntax is common in command-line oriented applications, especially on Unix-based systems. It serves as a convenient shortcut, and it also allows code to be shared and run by multiple people without having to update file paths if each person keeps data in the same directory structure relative to their home directory.

This support has been added throughout the astropy.io module. This feature is also supported within the I/O functionality of astropy.table and the FITS-file functionality in astropy.nddata.

CCDData PSF Image representation

The NDData/CCDData objects now have a specific attribute for an image representation of the point spread function (PSF) at the image center. This was added to support the Rubin Observatory/LSST alert packets, which will be distributed as CCDData objects.

Full change log

To see a detailed list of all changes in version v5.2, including changes in API, please see the Full Changelog.

Contributors to the v5.2 release

The people who have contributed to the code for this release are:

  • Adrian Price-Whelan

  • Albert Y. Shih

  • Bharath Saiguhan *

  • Brett Woltz *

  • Brigitta Sipőcz

  • Chiara Marmo

  • Conor MacBride

  • David Paz *

  • David Stansby

  • Derek Homeier

  • Eero Vaher

  • Erik Tollerud

  • Frazer McLean *

  • Gabe Brammer *

  • Gabriel Brammer

  • Geert Barentsen

  • Hans Moritz Günther

  • Hood Chatham *

  • Jero Bado

  • John Parejko

  • Kunam Balaram Reddy *

  • Larry Bradley

  • Lily Fahey *

  • Lu Xu *

  • Marten van Kerkwijk

  • Martin Dyer *

  • Matthew Craig

  • Matthew Pitkin *

  • Max Mahlke *

  • Maximilian Nöthe

  • Michael Brewer

  • Mihai Cara

  • Nadia Dencheva

  • Nathaniel Starkman

  • Pey Lian Lim

  • Roland Weber *

  • Roy Smart

  • Sam Lee

  • Sam Van Kooten

  • Simon Conseil

  • Stuart Mumford

  • Sébastien Maret *

  • T. E. Pickering *

  • Thomas Robitaille

  • Timothy P. Ellsworth Bowers *

  • Tom Aldcroft

  • William Jamieson

  • Yash Nandwana *

Where a * indicates that this release contains their first contribution to astropy.