Skip to main content

Python interface to Telescope Pointing Machine C library.

Project description

Python interface to the TPM C library


PyTPM is a Python interface to the Telescope Pointing Machine (TPM) library. TPM is a C library written by Jeffrey W Percival, for performing coordinate conversions between several astronomical coordinate systems.

TPM was designed with the aim of incorporating it into telescope control systems. To meet this design goal, TPM offers control over calculations carried out during coordinate conversions. Some of these calculations must be performed frequently, for example time related calculations. Others need to be performed only once per night, for example nutation and precession matrices. TPM allows the user to select the exact calculations to be performed. This enables the user to control the computational load, which is important in telescope control systems. TPM C library is used by the KPNO WIYN observatory and the WHAM projects.

PyTPM is not a complete astrometry package. The aim is to provide access to the TPM C code from Python. TPM machinery can be directly accessed using the pytpm.tpm sub-module. The sub-module pytpm.convert has several convenience functions that can be used for performing coordinate conversions. The latter is sufficient for most, but not all, calculations. You should read the TPM manual before attempting to use the pytpm.tpm module. The manual is present in the source code repository and is also included with the PyTPM documentation

Python interface to TPM C code is written using Cython.

Installing PyTPM

PyTPM requires the following:

  • Python 2.6, 2.7 or 3.2.
  • GCC.
  • The Distribute package.
  • Nose for running tests.
  • Cython, only if the Cython output needs to be regenerated.

To build the documentation Sphinx and the numpydoc Sphinx extension is required.

PyTPM was tested on Ubuntu 10.10 and 11.04.



The file src/tpm/delta_AT.c must be updated when Delta-AT is changed by the IERS, and PyTPM Cython code must re-compiled. Update the file and just run again. A new version of PyTPM will be released when this change occurs.

If you don’t have Distribute, then install it. Then do one of the following:

  • pip or easy_install

    Install pip and then run pip install pytpm.

    If easy_install is available then easy_install pytpm will also work. Distribute comes with easy_install. pip itself can be installed using the command easy_install pip.


  • Manual installation.

    Download the distribution from the pypi page for the project. Then run python install. Use the –prefix <dest> or –user arguments to change the installation location.

With both these methods, virtualenv and virtualenvwrapper can be used. These tools enable easy installation and maintenance of Python packages.

To run tests, and to build documentation, the manual installation method has to be followed. Run python test and then run python install. To build documentation, run make html in the doc directory.


Detailed documentation is available at Documentation in HTML format can also be downloaded from the pypi page for the project. Documentation in ReST format is available in the doc directory of the distribution.

PyTPM can be used to convert positions and velocities in a given astronomical coordinate system into another. Examples of doing this are in the examples folder of the source code repository and is also included with the HTML documentation.

You should read the TPM manual before attempting to use the pytpm.tpm module. The manual is also available in the source code repository and the HTML documentation.

In the following examples coordinates of M100 is converted between different systems.

The following examples use the convenience function pytpm.convert.convertv6, instead of directly using the underlying TPM functions. The documentation has examples of using the latter.

The convertv6 function takes the following arguments. Not all of these need to be specified for a given conversion.

Parameter Description
v6 one V6C vector or a list of V6C vectors.
s1 start state
s2 end state
epoch epoch of the coordinates as a Julian date
equinox equinox of the coordinates as Julian date
utc time of “observation” as a Julian date; exact meaning depends on the type of conversion; defaults to the epoch J2000.0
delta_ut UT1 - UTC in seconds.
delta_at TAI - UTC in seconds.
lon geodetic longitude in degrees
lat geodetic latitude in degrees
alt altitude in meters
xpole ploar motion in radians
ypole ploar motion in radians
T temperature in kelvin
P pressure in milli-bars
H relative humidity (0-1)
wavelength wavelength of observation in microns

A V6C object is a 6-D vector that stores positions and velocities in Cartesian coordinates. The function pytpm.convert.v62cat can be used to create a V6C object from catalog data. This function will accept scalar or list of coordinates. Function pytpm.convert.v62cat can convert V6C objects to catalog coordinates. The coordinates are returned as a dictionary. This function will also take a list of V6C objects and will return a list of dictionaries.

Coordinate systems are specified using integers or integer constants. These are referred to as states.The following are some of the important states.

State Description
3 IAU 1980 Ecliptic system
4 IAU 1958 Galactic system
5 Heliocentric mean FK4 system, B1950 equinox
6 Heliocentric mean FK5 system, J2000 equinox
11 Geocentric apparent FK5, current equinox
16 Topocentric apparent FK5, current equinox
17 Topocentric apparent (Hour Angle, Declination)
18 Topocentric apparent (Azimuth, Elevation)
19 Topocentric observed (Azimuth, Elevation)
20 Topocentric observed (Hour Angle, Declination)

FK5 equinox and epoch J2000.0, to FK4 equinox and epoch B1950.0

First obtain the FK5 equinox J2000.0 and epoch J2000.0 RA and Dec coordinates in radians.

>>> ra_j2000 = tpm.HMS(hh=12, mm=22, ss=54.899).to_radians()
>>> dec_j2000 = tpm.DMS(dd=15, mm=49, ss=20.57).to_radians()

Create a V6C vector for the object. Note that pytpm.convert.cat2v6 will accept a list of coordinates as well.

>>> v6 = convert.cat2v6(ra_j2000, dec_j2000)

Now convert to FK4 equinox B1950.0 but remaining at epoch J2000.0. In the following 6 stands for FK5 equinox and epoch J2000.0 coordinates and 5 stands for FK4 equinox and epoch B1950.0. The epoch and equinox are specified using epoch and equinox keywords. But they can be interpreted in different ways depending on the exact conversion requested. In this case, they are applicable to the input coordinates.

>>> v6_fk4 = convert.convertv6(v6, s1=6, s2=5, epoch=tpm.J2000,
   ...: equinox=tpm.J2000)

Convert V6C to catalog data and print results. Function pytpm.convert.v62cat will also accept a list of V6C objects.

>>> d = convert.v62cat(v6_fk4, C=tpm.CB)
>>> print tpm.HMS(r=d['alpha'])
 12H 20M 22.935S
>>> print tpm.DMS(r=d['delta'])
+16D 05' 58.024"

The parameter C is the number of days in a century. The velocities in AU/day must be converted into “/century. In the Besselian system, a century has approximately 36524.22 days, where as in the Julian system a century has 36525.0 days. The former is used in FK4 and the latter is used in FK5. The default value is set to 36525.0.

Note that the results above do not agree with the FK4 values given by SIMBAD. This is because the results are for the epoch J2000.0. Even though the object doesn’t have proper motion, the FK4 system is rotating with respect to FK5. This results in a fictitious proper motion in the FK4 system. We must apply proper motion from epoch J2000.0 to epoch B1950.0 to get the final result.

>>> v6_fk4_ep1950 = convert.proper_motion(v6_fk4, tpm.B1950, tpm.J2000)

Finally convert V6C to catalog data and print results. The final result is in FK4 equinox and epoch B1950.0. The final results agree with the values given by SIMBAD.

>>> d = convert.v62cat(v6_fk4_ep1950, C=tpm.CB)
>>> print tpm.HMS(r=d['alpha'])
 12H 20M 22.943S
>>> print tpm.DMS(r=d['delta'])
+16D 05' 58.241"

FK5 equinox and epoch J2000 to IAU 1958 Galactic System

The IAU 1958 galactic system is represented using state 4. The result below is for the epoch J2000.0. The epoch of the Galactic coordinates given by SIMBAD is J2000.0. So the result obtained below is what we need, i.e., we don’t need to apply any proper motion corrections.

>>> ra_j2000 = tpm.HMS(hh=12, mm=22, ss=54.899).to_radians()
>>> dec_j2000 = tpm.DMS(dd=15, mm=49, ss=20.57).to_radians()
>>> v6 = convert.cat2v6(ra_j2000, dec_j2000)

>>> v6_gal = convert.convertv6(v6, s1=6, s2=4, epoch=tpm.J2000,
   ...: equinox=tpm.J2000)

>>> d = convert.v62cat(v6_gal)
>>> print tpm.r2d(d['alpha'])
>>> print tpm.r2d(d['delta'])

IAU 1958 Galactic to FK5 equinox and epoch J2000.0

Here we set the starting state to galactic i.e., 4 and the end state to FK5 equinox. Since the input coordinates are at epoch J2000.0, the final results will also be at epoch J2000.0, i.e., FK5 equinox and epoch J2000.0.

>>> gal_lon = tpm.d2r(271.1361)
>>> gal_lat = tpm.d2r(76.8989)
>>> v6 = convert.cat2v6(gal_lon, gal_lat)

>>> v6_fk5 = convert.convertv6(v6, s1=4, s2=6, epoch=tpm.J2000)

>>> d = convert.v62cat(v6_fk5)
>>> print tpm.HMS(r=d['alpha'])
 12H 22M 54.900S
>>> print tpm.DMS(r=d['delta'])
+15D 49' 20.683"

The results are consistent with the accuracy of the input galactic coordinates.

FK5 equinox and epoch J2000 to IAU 1980 Ecliptic system

The ecliptic system is indicated using the state 3. Here the epoch of the output ecliptic coordinates will be J2000.0.

>>> ra_j2000 = tpm.HMS(hh=12, mm=22, ss=54.899).to_radians()
>>> dec_j2000 = tpm.DMS(dd=15, mm=49, ss=20.57).to_radians()
>>> v6 = convert.cat2v6(ra_j2000, dec_j2000)

>>> v6_ecl = convert.convertv6(v6, s1=6, s2=3, epoch=tpm.J2000,
   ...: equinox=tpm.J2000)

>>> d = convert.v62cat(v6_ecl)
>>> print tpm.r2d(d['alpha'])
>>> print tpm.r2d(d['delta'])

The results agree with the results form the SLALIB (pyslalib) routine sla_eqecl.

IAU 1980 Ecliptic system to FK5 equinox and epoch J2000.0

The starting state is set to 3 for ecliptic and the end state is set to 6 for FK5 equinox and epoch J2000.0.

>>> ecl_lon = tpm.d2r(178.78256462)
>>> ecl_lat = tpm.d2r(16.7597002513)
>>> v6 = convert.cat2v6(ecl_lon, ecl_lat)

>>> v6_fk5 = convert.convertv6(v6, s1=3, s2=6, epoch=tpm.J2000)

>>> d = convert.v62cat(v6_fk5)
>>> print tpm.HMS(r=d['alpha'])
 12H 22M 54.898S
>>> print tpm.DMS(r=d['delta'])
+15D 49' 20.570"

FK5 equinox and epoch J2000 to Geocentric apparent

Geocentric apparent RA & Dec. for midnight of 2010/1/1 is calculated as shown below. The state identification number for geocentric apparent position is 11.

Obtain UTC and TDB time for the time of observation.

>>> utc = tpm.gcal2j(2010, 1, 1) - 0.5  # midnight
>>> tdb = tpm.utc2tdb(utc)

Obtain coordinates and V6C vector.

>>> ra_j2000 = tpm.HMS(hh=12, mm=22, ss=54.899).to_radians()
>>> dec_j2000 = tpm.DMS(dd=15, mm=49, ss=20.57).to_radians()
>>> v6 = convert.cat2v6(ra_j2000, dec_j2000)

Apply proper motion from epoch J2000.0 to epoch of observation. In this example, this is not needed since proper motion is zero. But we do this for completeness. The result is FK5 J2000 current epoch.

>>> v6 = convert.proper_motion(v6, tt, tpm.J2000)

Convert coordinates from FK5 equinox J2000, current epoch to FK5 equinox and epoch of date.

>>> v6_gc = convert.convertv6(v6, s1=6, s2=11, utc=utc)
>>> d = convert.v62cat(v6_gc)
>>> print tpm.r2d(d['alpha'])
>>> print tpm.r2d(d['delta'])

The result from SLALIB (pyslalib) for the equivalent conversion, using the sla_map function is given below.

>>> utc = slalib.sla_caldj(2010, 1, 1)[0]  # midnight
>>> tt = slalib.sla_dtt(utc) / 86400.0 + utc

>>> r, d = slalib.sla_map(ra_j2000, dec_j2000, 0, 0, 0, 0.0, 2000.0,
   ...: tt)

>>> tpm.r2d(r)
>>> tpm.r2d(d)

The difference is about 0.06 arc-sec in RA and about 0.03 arc-sec in Dec.:

>>> (tpm.r2d(r) - 185.860038856) * 3600.0
>>> (tpm.r2d(d) - 15.7631353482) * 3600.0

FK5 equinox and epoch J2000 to topocentric observed

Topocentric observed azimuth and elevation (and zenith distance) for an observer at the default location (KPNO) is calculated for 2010/1/1 mid-day. The final state i.e., apparent topocentric Az & El, is 19.

For midnight 2010/1/1 this object is below the horizon and hence the refraction calculations are not reliable. So we use mid-day for the following example.

>>> utc = tpm.gcal2j(2010, 1, 1)  # mid-day
>>> tt = tpm.utc2tdb(utc)

>>> ra_j2000 = tpm.HMS(hh=12, mm=22, ss=54.899).to_radians()
>>> dec_j2000 = tpm.DMS(dd=15, mm=49, ss=20.57).to_radians()
>>> v6 = convert.cat2v6(ra_j2000, dec_j2000)

>>> v6 = convert.proper_motion(v6, tt, tpm.J2000)

>>> v6_app = convert.convertv6(v6, s1=6, s2=19, utc=utc)

>>> d = convert.v62cat(v6_app)
>>> print tpm.r2d(d['alpha']), 90 - tpm.r2d(d['delta'])
133.49820871 22.0162437585

To calculate the observed hour angle and declination the v6_app vector obtained above can be used as input. We don’t need to go back to the FK5 equinox and epoch J2000.0 values. The input state is now 19 and the output, i.e., topocentric observed HA & Dec, is 20.

>>> v6_hadec = convert.convertv6(v6_app, s1=19, s2=20, utc=utc)

>>> d = convert.v62cat(v6_hadec)
>>> print tpm.r2d(d['alpha'])
>>> print tpm.r2d(d['delta'])

To calculate the observed RA we need to find the LAST, since TPM only provides apparent RA. The observed RA can be found by subtracting hour angle from LAST. This is one situation where we need to access the underlying TPM machinery provided in pytpm.tpm. Please consult the TPM manual and the PyTPM documentation for more information.

>>> tstate = tpm.TSTATE()
>>> tpm.tpm_data(tstate, tpm.TPM_INIT)
>>> tstate.utc = utc
>>> tstate.delta_ut = tpm.delta_UT(utc)
>>> tstate.delta_at = tpm.delta_AT(utc)
>>> tstate.lon = tpm.d2r(-111.598333)
>>> = tpm.d2r(31.956389)
>>> tpm.tpm_data(tstate, tpm.TPM_ALL)
>>> last = tpm.r2d(tpm.r2r(tstate.last))
>>> last - tpm.r2d(d['alpha']) + 360.0

The same calculation with SLALIB, using sla_aop produces results that agree with PyTPM.

>>> dut = tpm.delta_UT(tpm.gcal2j(2010, 1, 1))  # DUT for mid-day.
>>> utc = slalib.sla_caldj(2010, 1, 1)[0] + 0.5  # mid-day.
>>> tt = slalib.sla_dtt(utc) / 86400.0 + utc

>>> r, d = slalib.sla_map(ra_j2000, dec_j2000, 0, 0, 0, 0.0, 2000.0,
   ...: tt)

>>> lon = tpm.d2r(-111.598333)
>>> lat = tpm.d2r(31.956389)

>>> az, zd, ha, dec, ra = slalib.sla_aop(r, d, utc, dut, lon, lat,
   ...: 2093.093, 0, 0, 273.15, 1013.25, 0, 0.550, 0.0065)

>>> tpm.r2d(tpm.r2r(az)), tpm.r2d(tpm.r2r(zd))
133.498195532 22.0162383595

The hour angle, declination and right ascension are:

>>> print tpm.r2d(tpm.r2r(ha))
>>> print tpm.r2d(tpm.r2r(dec))
>>> print tpm.r2d(tpm.r2r(ra))

Consult the appropriate section of the PyTPM documentation for a detailed comparison between PyTPM and SLALIB.

Converting positions and velocities

Converting positions and velocities follow exactly the same procedure as the examples shown above. The convert.cat2v6 function will take proper motions, radial velocity and parallax in addition to position. The returned dictionary will have appropriate fields for final proper motions, radial velocity and parallax.

See the file doc/examples/ for a full example. The file is also included with the HTML documentation and with the source distribution.

For example if tab is a table that contains full 6-D coordinates with keys ra, dec, pma, pmd, px and rv, then a full V6C vector can be constructed as:

>>> v6 = convert.cat2v6(tab['ra'], tab['dec'], tab['pma'],
   ...: tab['pmd'], tab['px'], rv, tpm.CJ)

See docstring of the convert.convertv6 function for the required units for each of these.

To convert this from, say FK5 to Ecliptic, at the same epoch, we can use:

>>> v6o = convert.convertv6(v6, s1=6, s2=3)
>>> cat = convert.v62cat(v6o)

The variable cat will contain a dictionary, or a list of dictionaries, with the relevant catalog quantities. See the docstring of this convert.v62cat for units of output quantities.

Credits and license

Jeffrey W Percival wrote the TPM C library. See src/tpm/TPM_LICENSE.txt for TPM license.

The version used here was obtained from the coords package (version 0.36) of the astrolib library. Some C source files missing from the above source were provided by Jeff Percival.

Python and Cython code for PyTPM is released under the BSD license; see LICENSE.txt.

Please send email to prasanthhn, at the domain, for reporting errors, and for comments and suggestions.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for PyTPM, version 0.7.1
Filename, size File type Python version Upload date Hashes
Filename, size PyTPM-0.7.1.tar.gz (1.7 MB) File type Source Python version None Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page