The astropy.io.ascii subpackage allows reading and writing of table data in ASCII format. A number of improvements have been made to this package, some of which break compatibility with the original asciitable package.
The biggest change is full integration with the Table class so that table and column metadata (e.g. keywords, units, description, formatting) are directly available in the output table object. The CDS, DAOphot, and IPAC format readers now provide this type of integrated metadata. Missing value support is now provided using masked tables instead of NumPy masked arrays.
There is an important change in way that input data are parsed in the write() function. In version 0.1 of astropy, a list of lists was interpreted to be a list of data rows, corresponding to the behavior in asciitable. Starting from version 0.2, a list of lists is interpreted as a list of data columns. This corresponds to the behavior of the Table class.
Finally, a reader class to read SExtractor table outputs is now available.
The astropy.coordinates subpackage was added in Astropy 0.2, and adds a framework for defining celestial and other astronomical coordinate systems, as well as transformations between them. A few simple usage examples include:
>>> import astropy.coordinates as coord >>> c = coord.ICRSCoordinates(ra=10.68458, dec=41.26917, unit=(u.degree, u.degree)) >>> c.ra <RA 10.68458 deg> >>> c.galactic <GalacticCoordinates l=121.17430 deg, b=-21.57280 deg>
Currently a limited set of standard coordinate systems are included, but more will be added in the next release. There is also an example of creating a custom coordinate system in the documentation.
The package also includes a representation of angles (Angle) that may be useful in other contexts. It also supports distances in celestial coordinates, which allows a complete mapping to 3D coordinates:
>>> c = coord.ICRSCoordinates('00h42m44.3s +41d16m9s', distance=Distance(770, u.kpc)) >>> c.cartesian <CartesianPoints (568.712888217, 107.300935969, 507.889909249) kpc>
>>> c = coord.ICRSCoordinates.from_name("M42") >>> c.ra, c.dec (<RA 83.82208 deg>, <Dec -5.39111 deg>) >>> c = coord.GalacticCoordinates.from_name("M42") >>> c.l, c.b (<Angle -150.98622 deg>, <Angle -19.38162 deg>)
Note that this subpackage is still under heavy development, and likely will undergo significant changes in the next few versions.
There have been several improvements to astropy.cosmology subpackage, some of which required minor API changes. Contributions to the energy density from photons and neutrinos are now taken into account, and so cosmological quantities should be accurate all the way up to z ~ 1100, corresponding to the CMB surface of last scattering. There are also new classes to represent flat cosmologies, optionally with a time-varying dark energy parameter w using the popular parameterisations by Linder 2003.
There are two API changes:
- Previously the Om, Ol and Ok attributes of a Cosmology class referred to densities at z = 0. These have been renamed to Om0, Ol0, and Ok0. Om, Ol and Ok are now methods that give the relevant density as a function of redshift. This change makes their behaviour consistent with that of the Hubble parameter attribute and method (H0 and H).
- The FLRWCosmology class has been renamed to FLRW.
So while in version 0.1 you could define a flat cosmology in following way:
>>> from astropy.cosmology import FLRWCosmology >>> cosmo = FLRWCosmology(H0=70, Om=0.3, Ol=0.7)
Now you would do the same thing using:
>>> from astropy.cosmology import FlatLambdaCDM >>> cosmo = FlatLambdaCDM(H0=70, Om0=0.3)
Finally, a new set of cosmological parameters from the 9 year WMAP results (astropy.cosmology.WMAP9) has been added from the recently submitted paper by Hinshaw et al.. Since this paper has not yet been refereed, convenience functions still use the 7 year WMAP results if you don’t explicitly specify a cosmology.
The astropy.table subpackage was first introduced for preview in Astropy 0.1 and provides functionality for storing and manipulating heterogenous tables of data in a way that is familiar to numpy users. Some key features include:
Astropy 0.2 brings the addition of integrated support for missing values via the Numpy masked array class. This feature requires Numpy version 1.5 or greater because of issues with masked arrays in previous versions.
The Table class now connects to the new I/O framework read and write methods. For example, assume you have a table of magnitudes called mags with columns B and V. You can add a new column B-V and write out to an ASCII table with:
>>> BV = Column(data=mags['B'] - mags['V'], name='B-V') >>> mags.add_column(BV) >>> mags.write('mags_BV.dat', format='ascii')
>>> from astropy.table import Table >>> t = Table.read('my_table.xml', format='vo') >>> t.write('my_table.hdf5')
At this time, this framework supports ASCII tables, HDF5 tables, and VO tables, and will be extended to support FITS tables and datasets in the next version. Users can also register their own file formats directly, in case these are not present in Astropy. More information about how to read/write Table objects using the built-in formats is available in Reading and writing Table objects, and more information about the I/O framework and how to register new file formats can be found in I/O Registry (astropy.io.registry).
The astropy.time package is new in Astropy 0.2 and provides functionality for manipulating times and dates. Specific emphasis is placed on supporting time scales (e.g. UTC, TAI, UT1) and time representations (e.g. JD, MJD, ISO 8601) that are used in astronomy. The underlying computations are mostly done with the C language SOFA time and calendar routines. A simple example follows:
>>> from astropy.time import Time >>> times = ['1999-01-01 00:00:00.123456789', '2010-01-01 00:00:00'] >>> t = Time(times, format='iso', scale='utc')
The format argument specifies how to interpret Time Format of the input values, e.g. ISO or JD or Unix time. The scale argument specifies the Time Scale for the values, e.g. UTC or TT or UT1. Converting to another time format or time scale is a snap:
>>> t.jd # Get an array of JD times array([ 2451179.50000143, 2455197.5 ]) >>> t.tt # Get a new Time object with values in the TT time scale <Time object: scale='tt' format='iso' vals=['1999-01-01 00:01:04.307' '2010-01-01 00:01:06.184']>
Units (astropy.units) handles defining and converting between physical units, and performing arithmetic with physical quantities (numbers with associated units).
Units can be converted to one another:
>>> from astropy import units as u >>> # Convert from parsec to meter >>> u.pc.to(u.m) 3.0856776e+16
It also handles equivalencies that hold true in certain contexts, such as that between wavelength and frequency:
# Wavelength to frequency doesn't normally work >>> u.nm.to(u.Hz, [1000, 2000]) UnitsException: 'nm' (length) and 'Hz' (frequency) are not convertible # ...but by passing an equivalency unit (spectral()), it does... >>> u.nm.to(u.Hz, [1000, 2000], equivalencies=u.spectral()) array([ 2.99792458e+14, 1.49896229e+14])
Also included in the astropy.units package is the Quantity object, which represents a numerical value with an associated unit. These objects support arithmetic with other numbers and Quantity objects and preserve units:
>>> from astropy import units as u >>> 15.1*u.meter / (32.0*u.second) <Quantity 0.471875 m / (s)> >>> 3.0*u.kilometer / (130.51*u.meter/u.second) <Quantity 0.0229867443108 km s / (m)> >>> (3.0*u.kilometer / (130.51*u.meter/u.second)).simplify_units() <Quantity 22.9867443108 s>
The name of the VOTable XML handling package has changed from astropy.io.vo to astropy.io.votable.
The unit attribute is now an astropy.units.Unit object, so unit conversions can easily be supported. The CDS unit format used by VOTable XML is now fully supported as a result.
Masked values are now handled by a single array, rather than a pair of arrays.
The precision and width attributes of each field are now handled correctly as per the VOTable XML specification. This may result in the output changing.
Each TABLE section of a VOTable XML file can be converted to/from an astropy.table.Table object, which allows much easier editing of the columns than a regular Numpy structured array.
A standalone volint script is available to validate the contents of VOTable XML files.
The default setting for pedantic mode can be set using a configuration parameter (astropy.io.vo.PEDANTIC).
When reading FITS headers, the default value of relax is True, in order to accept all non-standard keywords that wcslib understands. This should make astropy.wcs handle more FITS files by default, but may introduce a change in behavior in some edge cases. Likewise for writing FITS headers, the default value of relax is WCSHDO_safe, meaning it will write all non-standard exceptions that are considered safe and unambiguous. This should make the FITS files produced by astropy.wcs supported by a larger range of third-party tools, but may introduce changes in behavior in some edge cases.
The WCS transformation functions, when provided for a separate array for each input axis, will now broadcast the arrays correctly and return the output in the broadcasted shape. This makes using a constant for one of the axes possible.
The units in a WCS object (CUNITij) are now astropy.units.Unit objects, so operations on those units may be performed.
The included version of wcslib has been upgraded to version 4.16.