IERS data access (
iers package provides access to the tables provided by
the International Earth Rotation and Reference Systems (IERS) service, in
particular files allowing interpolation of published UT1-UTC and polar motion
values for given times. The UT1-UTC values are used in
provide UT1 values, and the polar motions are used in
determine Earth orientation for celestial-to-terrestrial coordinate
The package also provides machinery to track leap seconds. Since it
generally should not be necessary to deal with those by hand, this
is not discussed below. For details, see the documentation of
Starting with astropy 1.2, the latest IERS values (which include approximately
one year of predictive values) are automatically downloaded from the IERS
service when required. This happens when a time or coordinate transformation
needs a value which is not already available via the download cache. In most
cases there is no need for invoking the
iers classes oneself,
but it is useful to understand the situations when a download will occur
and how this can be controlled.
By default, the IERS data are managed via instances of the
IERS_Auto class. These instances are created
internally within the relevant time and coordinate objects during
transformations. If the astropy data cache does not have the required IERS
data file then astropy will request the file from the IERS service. This will
occur the first time such a transform is done for a new setup or on a new
machine. Here is an example that shows the typical download progress bar:
>>> from astropy.time import Time >>> t = Time('2016:001') >>> t.ut1 Downloading https://maia.usno.navy.mil/ser7/finals2000A.all |==================================================================| 3.0M/3.0M (100.00%) 6s <Time object: scale='ut1' format='yday' value=2016:001:00:00:00.082>
Note that you can forcibly clear the download cache as follows:
>>> from astropy.utils.data import clear_download_cache >>> clear_download_cache()
The default IERS data used automatically is updated by the service every 7 days and includes transforms dating back to 1973-01-01.
IERS_Auto class contains machinery
to ensure that the IERS table is kept up to date by auto-downloading the
latest version as needed. This means that the IERS table is assured of
having the state-of-the-art definitive and predictive values for Earth
rotation. As a user it is your responsibility to understand the
accuracy of IERS predictions if your science depends on that. If you
UT1-UTC or polar motions for times beyond the range of IERS
table data then the nearest available values will be provided.
There are a number of IERS configuration parameters in
that relate to automatic IERS downloading. Four of the most
important to consider are the following:
Enable auto-downloading of the latest IERS data. If set to
Falsethen the local IERS-B file will be used by default (even if the full IERS file with predictions was already downloaded and cached). This parameter also controls whether internet resources will be queried to update the leap second table if the installed version is out of date.
Maximum age of predictive data before auto-downloading (days). See next section for details. (default=30)
Remote timeout downloading IERS file data (seconds)
Some time conversions like UTC -> UT1 require IERS-A Earth rotation data for full accuracy. In cases where full accuracy is not required and downloading the IERS-A is not possible or desired (for instance running on a cluster) then this option can be set to either
'ignore'. The default is
'error'which will raise an exception if full accuracy is not possible for a time conversion,
'warn'will issue a warning, and
'ignore'will ignore the problem and use available IERS-B data.
Auto refresh behavior¶
The first time that one attempts a time or coordinate transformation that requires IERS data, the latest version of the IERS table (from 1973 through one year into the future) will be downloaded and stored in the astropy cache.
Transformations will then use the cached data file if possible. However, the
IERS_Auto table is automatically updated in place from the network if the
following two conditions a met when the table is queried for
polar motion values:
Any of the requested IERS values are predictive, meaning that they have been extrapolated into the future with a model that is fit to measured data. The IERS table contains approximately one year of predictive data from the time it is created.
The first predictive values in the table are at least
conf.auto_max_age daysold relative to the current actual time (i.e.
Time.now()). This means that the IERS table is out of date and a newer version can be found on the IERS service.
The IERS Service provides the default online table
astropy.utils.iers.IERS_A_URL) and updates the content
once each 7 days. The default value of
auto_max_age is 30 days to avoid
unnecessary network access, but one can reduce this to as low as 10 days.
If you are working without an internet connection and doing transformations that require IERS data, there are a couple of options.
Disable auto downloading
Here you can do:
>>> from astropy.utils import iers >>> iers.conf.auto_download = False
In this case any transforms will use the bundled IERS-B data which covers the time range from 1962 to just before the astropy release date. Any transforms outside of this range will not be allowed.
Set the auto-download max age parameter
Only do this if you understand what you are doing, THIS CAN GIVE INACCURATE ANSWERS! Assuming you have previously been connected to the internet and have downloaded and cached the IERS auto values previously, then do the following:
>>> iers.conf.auto_max_age = None
This disables the check of whether the IERS values are sufficiently recent, and all the transformations (even those outside the time range of available IERS data) will succeed with at most warnings.
Allow degraded accuracy
Only do this if you understand what you are doing, THIS CAN GIVE INACCURATE ANSWERS!
astropy.utils.iers.conf.iers_degraded_accuracy to either
'ignore'. These prevent the normal exception that occurs if a
time conversion falls outside the bounds of available local IERS-B data.
Direct table access¶
In most cases the automatic interface will suffice, but you may need to directly load and manipulate IERS tables. IERS-B values are provided as part of astropy and can be used to calculate time offsets and polar motion directly, or set up for internal use in further time and coordinate transformations. For example:
>>> from astropy.utils import iers >>> t = Time('2010:001') >>> iers_b = iers.IERS_B.open() >>> iers_b.ut1_utc(t) <Quantity 0.114033 s> >>> iers.earth_orientation_table.set(iers_b) <ScienceState earth_orientation_table: <IERS_B length=...>...> >>> t.ut1.iso '2010-01-01 00:00:00.114'
Instead of local copies of IERS files, one can also download them, using
and then use those for future time and coordinate transformations (in this
example, just for a single calculation, by using
earth_orientation_table as a context manager):
>>> iers_a = iers.IERS_A.open(iers.IERS_A_URL) >>> with iers.earth_orientation_table.set(iers_a): ... print(t.ut1.iso) 2010-01-01 00:00:00.114
To reset to the default, pass in
None (which is equivalent to passing in
>>> iers.earth_orientation_table.set(None) <ScienceState earth_orientation_table: <IERS...>...>
To see the internal IERS data that gets used in astropy you can do the following:
>>> dat = iers.earth_orientation_table.get() >>> type(dat) <class 'astropy.utils.iers.iers.IERS...'> >>> dat <IERS_Auto length=16196> year month day MJD PolPMFlag_A ... UT1Flag PM_x PM_y PolPMFlag d ... arcsec arcsec int64 int64 int64 float64 str1 ... unicode1 float64 float64 unicode1 ----- ----- ----- ------- ----------- ... -------- -------- -------- --------- 73 1 2 41684.0 I ... B 0.143 0.137 B 73 1 3 41685.0 I ... B 0.141 0.134 B 73 1 4 41686.0 I ... B 0.139 0.131 B 73 1 5 41687.0 I ... B 0.137 0.128 B ... ... ... ... ... ... ... ... ... ... 17 5 2 57875.0 P ... P 0.007211 0.44884 P 17 5 3 57876.0 P ... P 0.008757 0.450321 P 17 5 4 57877.0 P ... P 0.010328 0.451777 P 17 5 5 57878.0 P ... P 0.011924 0.453209 P 17 5 6 57879.0 P ... P 0.013544 0.454617 P
The explanation for most of the columns can be found in the file named
iers.IERS_A_README. The important columns of this table are MJD, UT1_UTC,
UT1Flag, PM_x, PM_y, PolPMFlag:
>>> dat['MJD', 'UT1_UTC', 'UT1Flag', 'PM_x', 'PM_y', 'PolPMFlag'] <IERS_Auto length=16196> MJD UT1_UTC UT1Flag PM_x PM_y PolPMFlag d s arcsec arcsec float64 float64 unicode1 float64 float64 unicode1 ------- ---------- -------- -------- -------- --------- 41684.0 0.8075 B 0.143 0.137 B 41685.0 0.8044 B 0.141 0.134 B 41686.0 0.8012 B 0.139 0.131 B 41687.0 0.7981 B 0.137 0.128 B ... ... ... ... ... ... 57875.0 -0.6545408 P 0.007211 0.44884 P 57876.0 -0.6559528 P 0.008757 0.450321 P 57877.0 -0.6573705 P 0.010328 0.451777 P 57878.0 -0.6587712 P 0.011924 0.453209 P 57879.0 -0.660187 P 0.013544 0.454617 P