Welcome to TLE-tools’s documentation!

TLE-tools is a small library to work with two-line element set files.

Purpose

The purpose of the library is to parse TLE sets them into convenient TLE objects, load entire TLE set files into pandas.DataFrame’s, convert TLE objects into poliastro.twobody.Orbit’s, and more.

From Wikipedia:

A two-line element set (TLE) is a data format encoding a list of orbital elements of an Earth-orbiting object for a given point in time, the epoch. The TLE data representation is specific to the simplified perturbations models (SGP, SGP4, SDP4, SGP8 and SDP8), so any algorithm using a TLE as a data source must implement one of the SGP models to correctly compute the state at a time of interest. TLEs can describe the trajectories only of Earth-orbiting objects.

Example:

ISS (ZARYA)
1 25544U 98067A   19249.04864348  .00001909  00000-0  40858-4 0  9990
2 25544  51.6464 320.1755 0007999  10.9066  53.2893 15.50437522187805

Installation

Install and update using pip:

pip install -U TLE-tools

Indices and tables

API Documentation

If you are looking for information on a specific function, class, or method, this part of the documentation is for you.

API Documentation

This parto of the documentation covers all the interfaces of tle. For guides on how to use them, pleas consult the tutorials.

TLE Classes

The library offers two classes to represent a single TLE. There is the unitless version TLE, whose attributes are expressed in the same units that are used in the TLE format, and there is the unitful version TLEu, whose attributes are quantities (astropy.units.Quantity), a type able to represent a value with an associated unit taken from astropy.units.

TLE-tools is a small library to work with two-line element set files.

class tle.TLE(name, norad, classification, int_desig, epoch_year, epoch_day, dn_o2, ddn_o6, bstar, set_num, inc, raan, ecc, argp, M, n, rev_num)

Data class representing a single TLE.

A two-line element set (TLE) is a data format encoding a list of orbital elements of an Earth-orbiting object for a given point in time, the epoch.

All the attributes parsed from the TLE are expressed in the same units that are used in the TLE format.

Variables:
  • name (str) – name of the satellite
  • norad (str) – NORAD catalog number (https://en.wikipedia.org/wiki/Satellite_Catalog_Number)
  • classification (str) – ‘U’, ‘C’, ‘S’ for unclassified, classified, secret
  • int_desig (str) – international designator (https://en.wikipedia.org/wiki/International_Designator)
  • epoch_year (int) – year of the epoch
  • epoch_day (float) – day of the year plus fraction of the day
  • dn_o2 (float) – first time derivative of the mean motion divided by 2
  • ddn_o6 (float) – second time derivative of the mean motion divided by 6
  • bstar (float) – BSTAR coefficient (https://en.wikipedia.org/wiki/BSTAR)
  • set_num (int) – element set number
  • inc (float) – inclination
  • raan (float) – right ascension of the ascending node
  • ecc (float) – eccentricity
  • argp (float) – argument of perigee
  • M (float) – mean anomaly
  • n (float) – mean motion
  • rev_num (int) – revolution number
class tle.TLEu(name, norad, classification, int_desig, epoch_year, epoch_day, dn_o2, ddn_o6, bstar, set_num, inc, raan, ecc, argp, M, n, rev_num)

Unitful data class representing a single TLE.

This is a subclass of TLE, so refer to that class for a description of the attributes and properties.

The only difference here is that all the attributes are quantities (astropy.units.Quantity), a type able to represent a value with an associated unit taken from astropy.units.

Module functions

tle.load_dataframe(filename, *, epoch=True)

Load multiple TLEs from one or more files and return a pandas.DataFrame.

Convenience functions
tle.partition(iterable, n)

Partition an iterable into tuples.

The iterable iterable is progressively consumed n items at a time in order to produce tuples of length n.

Parameters:
  • iterable (iterable) – The iterable to partition.
  • n (int) – Length of the desired tuples.
Returns:

A generator which yields subsequent n-uples from the original iterable.
tle.add_epoch(df)

Add a column 'epoch' to a dataframe.

df must have columns 'epoch_year' and 'epoch_day', from which the column 'epoch' is computed.

Parameters:df (pandas.DataFrame) – pandas.DataFrame instance to modify.