What’s New in Astropy 5.3?

Overview

Astropy 5.3 is a major release that adds significant new functionality since the 5.2 release.

In particular, this release includes:

In addition to these major changes, Astropy v5.3 includes a large number of smaller improvements and bug fixes, which are described in the Full Changelog. By the numbers:

  • 984 commits have been added since 5.2

  • 156 issues have been closed since 5.2

  • 238 pull requests have been merged since 5.2

  • 46 people have contributed since 5.2

  • 16 of which are new contributors

New flat astropy.cosmology classes

Two new cosmologies have been added, FlatwpwaCDM and Flatw0wzCDM, which are the flat variants of wpwaCDM and w0wzCDM, respectively.

>>> from astropy.cosmology import Flatw0wzCDM
>>> cosmo = Flatw0wzCDM(H0=70, Om0=0.3, w0=-0.9, wz=0.2)
>>> cosmo.comoving_distance(0.5)  
<Quantity 1982.66012926 Mpc>

New union operators for Table

We have added support for dictionary-style merge (|) and update (|=) of columns in the Table class. This follows the behavior for dict defined in PEP 584. |= works the same way as update() and updates the table in place. | return the updated table:

>>> from astropy.table import Table, QTable
>>> t1 = Table({'a': ['foo', 'bar'], 'b': [0., 0.]})
>>> t2 = QTable({'b': [1., 2.], 'c': [7., 11.]})
>>> t3 = t1 | t2  # Create new table which merges columns from t1 and t2
>>> t3
<Table length=2>
a      b       c
str3 float64 float64
---- ------- -------
foo     1.0     7.0
bar     2.0    11.0

>>> t2 |= t1  # Update t2 columns in-place with t1 columns
>>> t2
<QTable length=2>
   b       c     a
float64 float64 str3
------- ------- ----
    0.0     7.0  foo
    0.0    11.0  bar

When using |=, the other object does not need to be a Table, it can be anything that can be used for Constructing a Table with a compatible number of rows.

Efficient data access for compressed FITS files

In previous astropy versions, when accessing data for a compressed FITS file via the data property of CompImageHDU, the whole data was read in and decompressed even if only a small part of the data was required. The CompImageHDU class now has a section property which can be used to access specific sections of the data and will result in as little data as possible being read in and decompressed. For a compressed image:

>>> hdu.section[300:400, 100:200]

will therefore return the same result as:

>>> hdu.data[300:400, 100:200]

but the former will be faster. The exact speedup will depend on the size of the data and the size of the tiles but could be 10-100x or more.

Added support for NOCOMPRESS for compressed FITS files

It is now possible to read and write compressed FITS files that make use of the NOCOMPRESS compression algorithm. This allows users to store data in uncompressed tiles by specifying compression_type='NOCOMPRESS' in CompImageHDU.

New fraction option for representing units as strings

A new formatting option is added to switch between using fractions or using negative powers directly, with the fraction option also allowing to switch between inline and multiline prettyprinting of units:

>>> import astropy.units as u
>>> unit = u.Unit('erg / (s cm2)')
>>> print(unit.to_string('console'))
erg s^-1 cm^-2
>>> print(unit.to_string('console', fraction='inline'))
erg / (s cm^2)
>>> print(unit.to_string('console', fraction='multiline'))
 erg
------
s cm^2
>>> print(unit.to_string('unicode'))
erg s⁻¹ cm⁻²
>>> print(unit.to_string('unicode', fraction='inline'))
erg / (s cm²)
>>> print(unit.to_string('unicode', fraction='multiline'))
 erg
─────
s cm²

Note that the 'console' and 'unicode' formats now use fraction=False by default, since this will more reliably produce readable results when printing quantities, table headers and cells, etc. For 'latex' the default remains fraction='display', for an unchanged experience with IPython notebook.

Change in order in unit string representations

In string representations of units, the order of bases now is by decreasing power first, then alphabetical, instead of alphabetical independent of power. This is also how unit bases are stored internally and helps particularly for units without fractions (such as FITS), where a unit like Jy/beam was typeset as beam-1 Jy instead of the more logical Jy beam-1.

For typesetting with fractions, there is usually less effect, but the string representations of complicated units will change (e.g., what previously was erg / (Angstrom cm2 s) will now be erg / (Angstrom s cm2)).

Unfortunately, this is a breaking change if you test for unit string downstream. To workaround a unit string comparison failure that you see, you can filter by astropy version either in the Python module or in setup.cfg. We provide some examples below but these are not exhaustive; please adapt them to your own use cases and refer to pytest-doctestplus documentation.

Example in a Python module that enables the same test for all supported astropy versions:

import astropy
from astropy.utils.introspection import minversion

ASTROPY_LT_5_3 = not minversion(astropy, "5.3.dev")

if ASTROPY_LT_5_3:
    flux_unit_str = "erg / (Angstrom cm2 s)"
else:
    flux_unit_str = "erg / (Angstrom s cm2)"
# Some code that compares against flux_unit_str here.

Example in a Python module that skips doctest for astropy 5.3 or later:

# ASTROPY_LT_5_3
__doctest_requires__ = {"class_or_function_name": ["astropy<5.3"]}

Example in setup.cfg:

doctest_subpackage_requires =
    docs/somedocpage.rst = astropy>=5.3  # units updated to new ordering
    package/somemodule.py = astropy<5.3  # TODO: update units to new ordering

Support for collapse operations on arbitrary axes in nddata

Take the sum, mean, maximum, or minimum along one or more axes, reducing the dimensions of the output, on NDData objects with appropriate propagation of uncertainties, masks, and units. For example, we can take the sum of ND masked quantities along the 1 axis like so:

>>> import numpy as np
>>> import astropy.units as u
>>> from astropy.nddata import NDDataArray, StdDevUncertainty
>>>
>>> data = [
...     [1, 2, 3],
...     [2, 3, 4]
... ]
>>> mask = [
...     [True, False, False],
...     [False, False, False]
... ]
>>> uncertainty = StdDevUncertainty(np.ones_like(data))
>>> nddata = NDDataArray(data=data, uncertainty=uncertainty, mask=mask, unit='m')
>>> sum_axis_1 = nddata.sum(axis=1)
>>> sum_axis_1, sum_axis_1.mask, sum_axis_1.uncertainty
(NDDataArray([6., 9.], unit='m'),
 array([ True, False]),
 StdDevUncertainty([1.41421356, 1.73205081]))

Refresh cached observatory site registry for EarthLocation methods

The EarthLocation convenience methods of_site() and get_site_names() use the observatory site registry from the astropy-data repository to return site data by name. Usually, the site registry is cached on the user’s computer for quick access. The online version of the registry, however, is updated from time to time to include new locations. The user may refresh their locally cached site registry by passing the new refresh_cache=True option to these two functions.

Propagation of measurement uncertainties into parameter covariances

Propagate measurement uncertainties into the best-fit parameter covariances via the weights keyword argument in non-linear fitters. Decreasing the weights will now increase the uncertainties on the best-fit parameters.

New LombScargleMultiband class for multiband datasets

LombScargleMultiband is a newly released extension of the LombScargle class. It enables the generation of periodograms for datasets with measurements taken in more than one photometric bands.

The code is adapted from the astroml package and the gatspy package, but conforms closely to the design paradigms established in LombScargle.

Two implementations of the Multiband Lomb-Scargle Periodogram are available within LombScargleMultiband, flexible and fast. flexible is a direct port of the LombScargleMultiband algorithm used in the gatspy gatspy package. flexible serves as a similar implementation to flexible LombScargleMultibandFast, but leverages LombScargle to do it’s independent band-by-band fits.

Full change log

To see a detailed list of all changes in version v5.3, including changes in API, please see the Full Changelog.

Contributors to the v5.3 release

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

  • Abdu Zoghbi *

  • Albert Y. Shih

  • Brett Graham *

  • Brett M. Morris *

  • Brigitta Sipőcz

  • Caden Gobat *

  • Chiara Marmo

  • David Stansby

  • Derek Homeier

  • Doug Branton *

    1. Rykoff

  • Eero Vaher

  • Felipe Cybis Pereira *

  • Jamie Kennea *

  • Larry Bradley

  • Manon Marchand *

  • Markus Demleitner

  • Marten van Kerkwijk

  • Maximilian Linhoff

  • Michael Brewer

  • Mihai Cara

  • Mubin17 *

  • Nabil Freij

  • Nathaniel Starkman

  • naveen *

  • Nick Murphy

  • Ole Streicher

      1. Lim

  • Paul Price

  • Roy Smart

  • Samruddhi Khandale *

  • Sandeep Desai *

  • Simon Alinder *

  • Simon Conseil

  • Stuart Mumford

  • Telomelonia *

  • Thomas J. Fan *

  • Thomas Robitaille

  • Tiago Gomes

  • Tiago Ribeiro *

  • Timothy P. Ellsworth Bowers

  • Tom Aldcroft

  • Tom Donaldson

  • William Jamieson

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