344 lines
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ReStructuredText
344 lines
11 KiB
ReStructuredText
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===========================
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Stars and Distant Objects
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===========================
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.. currentmodule:: skyfield.starlib
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Skyfield can generate positions for stars or and other distant objects
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that you either load from a star catalog, or else for which you can
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provide barycentric ICRS coordinates.
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The Hipparcos Catalog
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=====================
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One of the most popular star catalogs is the Hipparcos catalog, compiled
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from the observations of a 1989–1993 European Space Agency satellite
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telescope. The spelling is deliberate; the ancient Greek astronomer’s
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name was “Hipparchus” but the name of the observatory and resulting
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catalog are an acronym for “High Precision Parallax Collecting
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Satellite.”
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To load this large star catalog with Skyfield requires the `Pandas
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<https://pandas.pydata.org/>`_ data library. If you use the Anaconda
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scientific Python distribution, you can install Pandas with::
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conda install pandas
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Otherwise you can try installing it with either the standard ``pip``
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Python package installation tool::
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pip install pandas
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Whichever way you install it, the Pandas library gives Skyfield the
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ability to load the Hipparcos catalog as a 118,218 row Pandas dataframe.
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You can filter individual stars out of the dataframe using the Pandas
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``loc[]`` operation with the star’s Hipparcos catalog number. For
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example, Barnard’s Star — the star moving fastest across our sky — has
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the Hipparcos designation “HIP 87937” and would be accessed like this:
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.. testsetup::
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__import__('skyfield.tests.fixes').tests.fixes.setup(
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(2014, 1, 18, 23, 10, 9))
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import matplotlib
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matplotlib.use('Agg') # to avoid “no display name” error on Travis CI
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.. testcode::
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from skyfield.api import Star, load
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from skyfield.data import hipparcos
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with load.open(hipparcos.URL) as f:
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df = hipparcos.load_dataframe(f)
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barnards_star = Star.from_dataframe(df.loc[87937])
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To generate the position of a star in the Earth’s sky on a given date,
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compute the Earth’s position in the Solar System and then ``observe()``
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the star:
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.. testcode::
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planets = load('de421.bsp')
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earth = planets['earth']
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ts = load.timescale(builtin=True)
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t = ts.now()
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astrometric = earth.at(t).observe(barnards_star)
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ra, dec, distance = astrometric.radec()
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print(ra)
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print(dec)
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.. testoutput::
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17h 57m 47.77s
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+04deg 44' 01.1"
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The position will properly reflect the star’s proper motion as measured
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by the HIPPARCOS mission.
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Stars with “nan” positions
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==========================
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The Hipparcos catalog, as pointed out in its official publication `The
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Hipparcos and Tycho Catalogues`_, includes 263 target stars for which no
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reliable position could be computed. These stars have blanks for their
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right ascension and declination in the text of the catalog itself. In
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Skyfield they will always return coordinates with the value ``nan`` (the
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floating point value “not a number”).
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If you want to avoid ``nan`` coordinates, you can filter them out of
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your dataframe with:
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.. testcode::
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df = df[df['ra_degrees'].notnull()]
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The result will be the same if you filter by the ``dec_degrees`` column
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instead.
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.. _The Hipparcos and Tycho Catalogues: https://www.cosmos.esa.int/documents/532822/552851/vol1_all.pdf/99adf6e3-6893-4824-8fc2-8d3c9cbba2b5
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Filtering the star catalog
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==========================
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In addition to selecting individual stars using their HIP number, you
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can build a :class:`~skyfield.starlib.Star` object that contains all of
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the stars in a dataframe. You can combine this with the standard Pandas
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dataframe filtering techniques to select only stars above a certain
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brightness.
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For example, let’s imagine that we wanted to plot the stars in the
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constellation Orion — but only stars that are at least magnitude 2.5.
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Pandas will let us filter the Hipparcos catalog dataframe in a single
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line of code:
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.. testcode::
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df = df[df['magnitude'] <= 2.5]
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print('After filtering, there are {} stars'.format(len(df)))
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.. testoutput::
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After filtering, there are 93 stars
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You can use this dataframe to build a :class:`~skyfield.starlib.Star`
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object that will compute the positions of all 93 stars at once.
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.. testcode::
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bright_stars = Star.from_dataframe(df)
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t = ts.utc(2018, 9, 3)
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astrometric = earth.at(t).observe(bright_stars)
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ra, dec, distance = astrometric.radec()
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print('There are {} right ascensions'.format(len(ra.hours)))
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print('and {} declinations'.format(len(dec.degrees)))
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.. testoutput::
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There are 93 right ascensions
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and 93 declinations
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Each element of the right ascension array and the declination array
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corresponds to one of the 93 selected stars. Their position can be
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combined with their magnitude to produce a plot.
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.. testcode::
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from matplotlib import pyplot as plt
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fig, ax = plt.subplots()
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ax.scatter(ra.hours, dec.degrees, 8 - df['magnitude'], 'k')
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ax.set_xlim(7.0, 4.0)
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ax.set_ylim(-20, 20)
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ax.grid(True)
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ax.set(title='The brightest stars in Orion')
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fig.savefig('bright_stars.png')
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The result of the simple filtering and plotting is an (admittedly
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primitive) rendering of Orion!
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.. image:: bright_stars.png
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Skyfield does not yet offer star chart routines, but hopefully they will
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appear before the end of the year. For now you can peek at the Skyfield
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file ``charting.py`` and experiment on your own.
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Building a single star from its coordinates
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===========================================
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If instead of loading up a whole star catalog you have the coordinates
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for one particular star you are interested in, you can instantiate a
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:class:`~skyfield.starlib.Star` directly using keyword arguments. Right
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ascension and declination can be specified as traditional base-60
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coordinates, where the fractions are “minutes” and “seconds”, if you
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pass tuples instead of floats:
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.. testcode::
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from skyfield.api import Star, load
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planets = load('de421.bsp')
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earth = planets['earth']
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barnard = Star(ra_hours=(17, 57, 48.49803),
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dec_degrees=(4, 41, 36.2072))
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ts = load.timescale(builtin=True)
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t = ts.now()
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astrometric = earth.at(t).observe(barnard)
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ra, dec, distance = astrometric.radec()
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print(ra)
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print(dec)
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.. testoutput::
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17h 57m 48.50s
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+04deg 41' 36.2"
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Of course, this has simply returned the same position. More interesting
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is that we can ask for the position to be expressed in the dynamical
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reference system of the moving Earth instead of in the same fixed ICRS
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system in which we provided it:
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.. testcode::
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ra, dec, distance = astrometric.radec(epoch=ts.now())
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print(ra)
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print(dec)
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.. testoutput::
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17h 58m 30.80s
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+04deg 41' 41.9"
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Distances to stars
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==================
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The distance that Skyfield computes to a particular star
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might or might not be meaningful,
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depending both on which star catalog you are using
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and on which particular star you observe.
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Skyfield has no way to even guess the distance to a star
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if it has only been given its right ascension and declination,
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as is the case for Barnard’s Star as we defined it above.
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To represent this vector of unknown length,
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Skyfield generates a vector exactly one gigaparsec long:
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.. testcode::
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print(distance) # exactly 1 gigaparsec
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.. testoutput::
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2.06265e+14 au
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This is so very far outside of our galaxy
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that such positions should be easy
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for you to tell apart from real distances to stars.
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Real distances will all be within a few hundred parsecs or less,
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because our telescopes cannot currently measure the parallax of stars
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that are any further away than that.
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In the next section,
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we will redefine Barnard’s Star
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and this time supply a real value for its parallax
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from a recent star catalog.
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You will see in that its ``distance``
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switches to a realistic estimate.
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Proper motion and parallax
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==========================
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There are other ways that a :class:`Star` object can generate a position
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different than the plain old ICRS right ascension and declination with
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which it is initialized. First, Skyfield will recognize that an object
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should change position over the years if we specify its proper motion in
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milliarcseconds (“mas”) per year. Second, Skyfield will shift its
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apparent position relative to the location from which you observe it if
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you provide a parallax indicating that the star is close enough to the
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Solar System that we have been able to measure its distance. Finally,
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there is even a tiny effect from its radial velocity if it is known.
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Here are all three effects applied to Barnard’s star:
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.. testcode::
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from skyfield.api import T0
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barnard = Star(ra_hours=(17, 57, 48.49803),
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dec_degrees=(4, 41, 36.2072),
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ra_mas_per_year=-798.71,
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dec_mas_per_year=+10337.77,
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parallax_mas=545.4,
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radial_km_per_s=-110.6)
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astrometric = earth.at(t).observe(barnard)
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ra, dec, distance = astrometric.radec()
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print(ra)
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print(dec)
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print(distance)
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.. testoutput::
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17h 57m 47.76s
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+04deg 44' 01.3"
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3.77863e+05 au
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Note that the above position is different than the input right ascension
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and declination but not because we have asked for dynamic coordinates.
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This position is in fixed ICRS coordinates and indicates real motion on
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the part of Barnard’s star across our sky.
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See the guide to :doc:`positions` to learn the operations that you can
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perform with these astrometric positions after using a :class:`Star`
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object to generate them.
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Position at an epoch besides J2000
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==================================
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Some star catalogs provide positions at an epoch besides J2000.
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For example, the catalog of stars observed by the Hipparcos space telescope
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provides their positions as of J1991.25.
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The epoch can be provided as an argument ``epoch`` to :class:`Star`.
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Here are the right ascension and declination given for Barnard’s Star
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in the Hipparcos catalog:
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.. testcode::
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hipparcos_epoch = ts.tt(1991.25)
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barnard2 = Star(ra_hours=(17, 57, 48.97),
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dec_degrees=(4, 40, 5.8),
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ra_mas_per_year=-797.84,
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dec_mas_per_year=+10326.93,
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epoch=hipparcos_epoch)
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ra, dec, distance = earth.at(t).observe(barnard2).radec()
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print(ra)
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print(dec)
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.. testoutput::
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17h 57m 47.75s
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+04deg 44' 01.3"
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As you can see, the position returned for the date ``t`` is the same,
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even though we initialized this :class:`Star` object
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with a position for Barnard’s Star more than 8 years earlier
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than the position we used in our first example.
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.. testcleanup::
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__import__('skyfield.tests.fixes').tests.fixes.teardown()
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.. The tiny hip_main.dat.gz file in this directory that powers these
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examples was generated by running the following in the main Skyfield
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source directory:
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zless hip_main.dat.gz | awk -F\| '$6 <= 3.2 || $2 == 87937' |gzip -9c > skyfield/documentation/hip_main.dat.gz
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