| .. _utils-iers: |
|
|
| ************************************************ |
| IERS data access (`astropy.utils.iers`) |
| ************************************************ |
|
|
| Introduction |
| ============ |
|
|
| The `~astropy.utils.iers` package provides access to the tables provided by |
| the International Earth Rotation and Reference Systems (IERS) service, in |
| particular allowing interpolation of published UT1-UTC values for given |
| times. These are used in `astropy.time` to provide UT1 values. The polar |
| motions are also used for determining Earth orientation for |
| celestial-to-terrestrial coordinate transformations |
| (in `astropy.coordinates`). |
|
|
| Getting started |
| =============== |
|
|
| 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 `~astropy.utils.iers` classes oneself, |
| but it is useful to understand the situations when a download will occur |
| and how this can be controlled. |
|
|
| Basic usage |
| ----------- |
|
|
| The IERS data are managed via a instances of the |
| :class:`~astropy.utils.iers.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 # doctest: +SKIP |
| Downloading http://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. |
|
|
| .. note:: The :class:`~astropy.utils.iers.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 |
| request ``UT1-UTC`` or polar motions for times beyond the range of IERS |
| table data then the nearest available values will be provided. |
|
|
|
|
| Configuration parameters |
| ------------------------ |
|
|
| There are three configuration parameters that control the behavior |
| of the automatic IERS downloading: |
|
|
| auto_download: |
| Enable auto-downloading of the latest IERS data. If set to ``False`` then |
| the local IERS-B file will be used by default (even if the full IERS file |
| with predictions was already downloaded and cached). This replicates the |
| behavior prior to astropy 1.2. (default=True) |
|
|
| auto_max_age: |
| Maximum age of predictive data before auto-downloading (days). See |
| next section for details. (default=30) |
|
|
| iers_auto_url: |
| URL for auto-downloading IERS file data |
|
|
| iers_auto_url_mirror: |
| Mirror URL for auto-downloading IERS file data. |
|
|
| remote_timeout: |
| Remote timeout downloading IERS file data (seconds) |
|
|
| 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 ``UT1-UTC`` or |
| 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 |
| days`` old 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 |
| (`<http://maia.usno.navy.mil/ser7/finals2000A.all>`_) 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. |
| |
| Working offline |
| --------------- |
|
|
| 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 # doctest: +SKIP |
|
|
| 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 # doctest: +SKIP |
|
|
| 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. |
|
|
| 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 for transformations. For example:: |
| |
| >>> from astropy.utils import iers |
| >>> t = Time('2010:001') |
| >>> iers_b = iers.IERS_B.open() |
| >>> iers_b.ut1_utc(t) # doctest: +FLOAT_CMP |
| <Quantity 0.1140827 s> |
| >>> t.delta_ut1_utc = iers_b.ut1_utc(t) |
| >>> t.ut1.iso |
| '2010-01-01 00:00:00.114' |
|
|
| Instead of local copies of IERS files, one can also download them, using |
| ``iers.IERS_A_URL`` (or ``iers.IERS_A_URL_MIRROR``) and ``iers.IERS_B_URL``:: |
| |
| >>> iers_a = iers.IERS_A.open(iers.IERS_A_URL) # doctest: +SKIP |
|
|
| For coordinate transformations that require IERS polar motion values, |
| setting the values manually can be done as follows (where one could also |
| select IERS_B):: |
| |
| >>> iers.conf.auto_download = False |
| >>> iers.IERS.iers_table = iers.IERS_A.open(iers.IERS_A_URL) # doctest: +SKIP |
|
|
| To see the internal IERS data that gets used in astropy you can do the |
| following:: |
| |
| >>> dat = iers.IERS_Auto.open() # doctest: +SKIP |
| >>> dat # doctest: +SKIP |
| <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'] # doctest: +SKIP |
| <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 |
|
|
