.. include:: references.txt .. We call EarthLocation.of_site here first to force the downloading .. of sites.json so that future doctest output isn't clutted with .. "Downloading ... [done]". This can be removed once we have a better .. way of ignoring output lines based on pattern-matching, e.g.: .. https://github.com/astropy/pytest-doctestplus/issues/11 .. testsetup:: >>> from astropy.coordinates import EarthLocation >>> EarthLocation.of_site('greenwich') # doctest: +IGNORE_OUTPUT .. _astropy-coordinates: ******************************************************* Astronomical Coordinate Systems (`astropy.coordinates`) ******************************************************* Introduction ============ The `~astropy.coordinates` package provides classes for representing a variety of celestial/spatial coordinates and their velocity components, as well as tools for converting between common coordinate systems in a uniform way. Getting Started =============== The simplest way to use `~astropy.coordinates` is to use the |skycoord| class. |skycoord| objects are instantiated by passing in positions (and optional velocities) with specified units and a coordinate frame. Commonly sky positions are passed in as `~astropy.units.Quantity` objects and the frame is specified with the string name. As an example of creating a |skycoord| to represent an ICRS (Right ascension [RA], Declination [Dec]) sky position:: >>> from astropy import units as u >>> from astropy.coordinates import SkyCoord >>> c = SkyCoord(ra=10.625*u.degree, dec=41.2*u.degree, frame='icrs') The initializer for |skycoord| is very flexible and supports inputs provided in a number of convenient formats. The following ways of initializing a coordinate are all equivalent to the above:: >>> c = SkyCoord(10.625, 41.2, frame='icrs', unit='deg') >>> c = SkyCoord('00h42m30s', '+41d12m00s', frame='icrs') >>> c = SkyCoord('00h42.5m', '+41d12m') >>> c = SkyCoord('00 42 30 +41 12 00', unit=(u.hourangle, u.deg)) >>> c = SkyCoord('00:42.5 +41:12', unit=(u.hourangle, u.deg)) >>> c # doctest: +FLOAT_CMP The examples above illustrate a few simple rules to follow when creating a coordinate object: - Coordinate values can be provided either as unnamed positional arguments or via keyword arguments like ``ra`` and ``dec``, or ``l`` and ``b`` (depending on the frame). - The coordinate ``frame`` keyword is optional because it defaults to `~astropy.coordinates.ICRS`. - Angle units must be specified for all components, either by passing in a `~astropy.units.Quantity` object (e.g., ``10.5*u.degree``), by including them in the value (e.g., ``'+41d12m00s'``), or via the ``unit`` keyword. |skycoord| and all other `~astropy.coordinates` objects also support array coordinates. These work the same as single-value coordinates, but they store multiple coordinates in a single object. When you're going to apply the same operation to many different coordinates (say, from a catalog), this is a better choice than a list of |skycoord| objects, because it will be *much* faster than applying the operation to each |skycoord| in a ``for`` loop. Like the underlying `~numpy.ndarray` instances that contain the data, |skycoord| objects can be sliced, reshaped, etc.:: >>> c = SkyCoord(ra=[10, 11, 12, 13]*u.degree, dec=[41, -5, 42, 0]*u.degree) >>> c # doctest: +FLOAT_CMP >>> c[1] # doctest: +FLOAT_CMP >>> c.reshape(2, 2) # doctest: +FLOAT_CMP Coordinate access ----------------- Once you have a coordinate object you can access the components of that coordinate (e.g., RA, Dec) and get string representations of the full coordinate. The component values are accessed using (typically lower-case) named attributes that depend on the coordinate frame (e.g., ICRS, Galactic, etc.). For the default, ICRS, the coordinate component names are ``ra`` and ``dec``:: >>> c = SkyCoord(ra=10.68458*u.degree, dec=41.26917*u.degree) >>> c.ra # doctest: +FLOAT_CMP >>> c.ra.hour # doctest: +FLOAT_CMP 0.7123053333333335 >>> c.ra.hms # doctest: +FLOAT_CMP hms_tuple(h=0.0, m=42.0, s=44.299200000000525) >>> c.dec # doctest: +FLOAT_CMP >>> c.dec.degree # doctest: +FLOAT_CMP 41.26917 >>> c.dec.radian # doctest: +FLOAT_CMP 0.7202828960652683 Coordinates can be converted to strings using the :meth:`~astropy.coordinates.SkyCoord.to_string` method:: >>> c = SkyCoord(ra=10.68458*u.degree, dec=41.26917*u.degree) >>> c.to_string('decimal') '10.6846 41.2692' >>> c.to_string('dms') '10d41m04.488s 41d16m09.012s' >>> c.to_string('hmsdms') '00h42m44.2992s +41d16m09.012s' For additional information see the section on :ref:`working_with_angles`. Transformation -------------- The simplest way to transform to a new coordinate frame is by accessing the appropriately-named attribute. For instance to get the coordinate in the `~astropy.coordinates.Galactic` frame use:: >>> c_icrs = SkyCoord(ra=10.68458*u.degree, dec=41.26917*u.degree, frame='icrs') >>> c_icrs.galactic # doctest: +FLOAT_CMP For more control, you can use the `~astropy.coordinates.SkyCoord.transform_to` method, which accepts a frame name, frame class, or frame instance:: >>> c_fk5 = c_icrs.transform_to('fk5') # c_icrs.fk5 does the same thing >>> c_fk5 # doctest: +FLOAT_CMP >>> from astropy.coordinates import FK5 >>> c_fk5.transform_to(FK5(equinox='J1975')) # precess to a different equinox # doctest: +FLOAT_CMP This form of `~astropy.coordinates.SkyCoord.transform_to` also makes it straightforward to convert from celestial coordinates to `~astropy.coordinates.AltAz` coordinates, allowing the use of |skycoord| as a tool for planning observations. For a more complete example of this, see :ref:`sphx_glr_generated_examples_coordinates_plot_obs-planning.py`. Some coordinate frames such as `~astropy.coordinates.AltAz` require Earth rotation information (UT1-UTC offset and/or polar motion) when transforming to/from other frames. These Earth rotation values are automatically downloaded from the International Earth Rotation and Reference Systems (IERS) service when required. See :ref:`utils-iers` for details of this process. Representation -------------- So far we have been using a spherical coordinate representation in the all the examples, and this is the default for the built-in frames. Frequently it is convenient to initialize or work with a coordinate using a different representation such as cartesian or cylindrical. This can be done by setting the ``representation_type`` for either |skycoord| objects or low-level frame coordinate objects:: >>> c = SkyCoord(x=1, y=2, z=3, unit='kpc', representation_type='cartesian') >>> c # doctest: +FLOAT_CMP >>> c.x, c.y, c.z # doctest: +FLOAT_CMP (, , ) >>> c.representation_type = 'cylindrical' >>> c # doctest: +FLOAT_CMP For all the details see :ref:`astropy-skycoord-representations`. Distance -------- |skycoord| and the individual frame classes also support specifying a distance from the frame origin. The origin depends on the particular coordinate frame; this can be, e.g., centered on the earth, centered on the solar system barycenter, etc. Two angles and a distance specify a unique point in 3D space, which also allows converting the coordinates to a Cartesian representation:: >>> c = SkyCoord(ra=10.68458*u.degree, dec=41.26917*u.degree, distance=770*u.kpc) >>> c.cartesian.x # doctest: +FLOAT_CMP >>> c.cartesian.y # doctest: +FLOAT_CMP >>> c.cartesian.z # doctest: +FLOAT_CMP With distances assigned, |skycoord| convenience methods are more powerful, as they can make use of the 3D information. For example, to compute the physical, 3D separation between two points in space:: >>> c1 = SkyCoord(ra=10*u.degree, dec=9*u.degree, distance=10*u.pc, frame='icrs') >>> c2 = SkyCoord(ra=11*u.degree, dec=10*u.degree, distance=11.5*u.pc, frame='icrs') >>> c1.separation_3d(c2) # doctest: +FLOAT_CMP Convenience methods ------------------- |skycoord| defines a number of convenience methods that support, for example, computing on-sky (i.e. angular) and 3D separations between two coordinates:: >>> c1 = SkyCoord(ra=10*u.degree, dec=9*u.degree, frame='icrs') >>> c2 = SkyCoord(ra=11*u.degree, dec=10*u.degree, frame='fk5') >>> c1.separation(c2) # Differing frames handled correctly # doctest: +FLOAT_CMP cross-matching catalog coordinates (detailed in :ref:`astropy-coordinates-matching`):: >>> target_c = SkyCoord(ra=10*u.degree, dec=9*u.degree, frame='icrs') >>> # read in coordinates from a catalog... >>> catalog_c = ... # doctest: +SKIP >>> idx, sep, _ = target_c.match_to_catalog_sky(catalog_c) # doctest: +SKIP The `astropy.coordinates` subpackage also provides a quick way to get coordinates for named objects assuming you have an active internet connection. The `~astropy.coordinates.SkyCoord.from_name` method of |skycoord| uses `Sesame `_ to retrieve coordinates for a particular named object:: >>> SkyCoord.from_name("PSR J1012+5307") # doctest: +REMOTE_DATA +FLOAT_CMP In some cases, the coordinates are embedded in the catalogue name of the object. For such object names, `~astropy.coordinates.SkyCoord.from_name` is able to parse the coordinates from the name if given the ``parse=True`` option. For slow connections, this may be much faster than a sesame query for the same object name. It's worth noting, however, that the coordinates extracted in this way may differ from the database coordinates by a few deci-arcseconds, so only use this option if you do not need sub-arcsecond accuracy for your coordinates:: >>> SkyCoord.from_name("CRTS SSS100805 J194428-420209", parse=True) # doctest: +FLOAT_CMP For sites (primarily observatories) on the Earth, `astropy.coordinates` provides a quick way to get an `~astropy.coordinates.EarthLocation` - the `~astropy.coordinates.EarthLocation.of_site` method:: >>> from astropy.coordinates import EarthLocation >>> EarthLocation.of_site('Apache Point Observatory') # doctest: +REMOTE_DATA +FLOAT_CMP To see the list of site names available, use :func:`astropy.coordinates.EarthLocation.get_site_names`. For arbitrary Earth addresses (e.g., not observatory sites), use the `~astropy.coordinates.EarthLocation.of_address` classmethod. Any address passed to this function uses Google maps to retrieve the latitude and longitude and can also (optionally) query Google maps to get the height of the location. As with Google maps, this works with fully specified addresses, location names, city names, and etc.: .. doctest-skip:: >>> EarthLocation.of_address('1002 Holy Grail Court, St. Louis, MO') >>> EarthLocation.of_address('1002 Holy Grail Court, St. Louis, MO', ... get_height=True) >>> EarthLocation.of_address('Danbury, CT') .. note:: `~astropy.coordinates.SkyCoord.from_name`, `~astropy.coordinates.EarthLocation.of_site`, and `~astropy.coordinates.EarthLocation.of_address` are for convenience, and hence are by design rather simple. If you need precise coordinates for an object you should find the appropriate reference and input the coordinates manually, or use more specialized functionality like that in the `astroquery `_ or `astroplan `_ affiliated packages. Also note that these methods retrieve data from the internet to determine the celestial or Earth coordinates. The online data may be updated, so if you need to guarantee that your scripts are reproducible in the long term, see the :doc:`remote_methods` section. This functionality can be combined to do more complicated tasks like computing barycentric corrections to radial velocity observations (also a supported high-level |skycoord| method - see :ref:`astropy-coordinates-rv-corrs`):: >>> from astropy.time import Time >>> obstime = Time('2017-2-14') >>> target = SkyCoord.from_name('M31') # doctest: +REMOTE_DATA >>> keck = EarthLocation.of_site('Keck') # doctest: +REMOTE_DATA >>> target.radial_velocity_correction(obstime=obstime, location=keck).to('km/s') # doctest: +REMOTE_DATA +FLOAT_CMP Velocities (Proper Motions and Radial Velocities) ------------------------------------------------- In addition to positional coordinates, `~astropy.coordinates` supports storing and transforming velocities. These are available both via the lower-level :doc:`coordinate frame classes `, and (new in v3.0) via |skycoord| objects:: >>> sc = SkyCoord(1*u.deg, 2*u.deg, radial_velocity=20*u.km/u.s) >>> sc # doctest: +SKIP .. the SKIP above in the ``sc`` line is because numpy has a subtly different output in versions < 12 - the trailing comma is missing. If a NPY_LT_1_12 comes in to being this can switch to that. But don't forget to *also* change this in the velocities.rst file For more details on velocity support (and limitations), see the :doc:`velocities` page. .. _astropy-coordinates-overview: Overview of `astropy.coordinates` concepts ========================================== .. note :: The `~astropy.coordinates` package from v0.4 onward builds from previous versions of the package, and more detailed information and justification of the design is available in `APE (Astropy Proposal for Enhancement) 5 `_. Here we provide an overview of the package and associated framework. This background information is not necessary for simply using `~astropy.coordinates`, particularly if you use the |skycoord| high- level class, but it is helpful for more advanced usage, particularly creating your own frame, transformations, or representations. Another useful piece of background information are some :ref:`astropy-coordinates-definitions` as they are used in `~astropy.coordinates`. `~astropy.coordinates` is built on a three-tiered system of objects: representations, frames, and a high-level class. Representations classes are a particular way of storing a three-dimensional data point (or points), such as Cartesian coordinates or spherical polar coordinates. Frames are particular reference frames like FK5 or ICRS, which may store their data in different representations, but have well- defined transformations between each other. These transformations are all stored in the ``astropy.coordinates.frame_transform_graph``, and new transformations can be created by users. Finally, the high-level class (|skycoord|) uses the frame classes, but provides a more accessible interface to these objects as well as various convenience methods and more string-parsing capabilities. Separating these concepts makes it easier to extend the functionality of `~astropy.coordinates`. It allows representations, frames, and transformations to be defined or extended separately, while still preserving the high-level capabilities and simplicity of the |skycoord| class. .. topic:: Examples: See :ref:`sphx_glr_generated_examples_coordinates_plot_obs-planning.py` for an example of using the `~astropy.coordinates` functionality to prepare for an observing run. Using `astropy.coordinates` =========================== More detailed information on using the package is provided on separate pages, listed below. .. toctree:: :maxdepth: 1 angles skycoord transforming solarsystem formatting matchsep representations frames velocities apply_space_motion galactocentric remote_methods definitions inplace In addition, another resource for the capabilities of this package is the ``astropy.coordinates.tests.test_api_ape5`` testing file. It showcases most of the major capabilities of the package, and hence is a useful supplement to this document. You can see it by either looking at it directly if you downloaded a copy of the astropy source code, or typing the following in an IPython session:: In [1]: from astropy.coordinates.tests import test_api_ape5 In [2]: test_api_ape5?? .. note that if this section gets too long, it should be moved to a separate doc page - see the top of performance.inc.rst for the instructions on how to do that .. include:: performance.inc.rst .. _astropy-coordinates-seealso: See Also ======== Some references particularly useful in understanding subtleties of the coordinate systems implemented here include: * `USNO Circular 179 `_ A useful guide to the IAU 2000/2003 work surrounding ICRS/IERS/CIRS and related problems in precision coordinate system work. * `Standards Of Fundamental Astronomy `_ The definitive implementation of IAU-defined algorithms. The "SOFA Tools for Earth Attitude" document is particularly valuable for understanding the latest IAU standards in detail. * `IERS Conventions (2010) `_ An exhaustive reference covering the ITRS, the IAU2000 celestial coordinates framework, and other related details of modern coordinate conventions. * Meeus, J. "Astronomical Algorithms" A valuable text describing details of a wide range of coordinate-related problems and concepts. .. _astropy-coordinates-api: Reference/API ============= .. automodapi:: astropy.coordinates