Package: pypredict
PyPredictNOTE: To preserve compatibility withpredict, pypredict usesnorthlatitude andwestlongitude for terrestrial coordinates.Do you want accurate and time-tested satellite tracking and pass prediction in a convenient python wrapper?
You're in the right place.PyPredict is a C Python extension directly adapted from the ubiquitouspredictsatellite tracking command line application.
Originally written for the commodore 64, predict has a proven pedigree; We just aim to provide a convenient API.
PyPredict is a port of the predict codebase and should yield identical results.If you think you've found an error inpypredict, please include output frompredicton same inputs to the bug report.If you think you've found a bug in predict, please report and we'll coordinate with upstream.Installationsudoapt-getinstallpython-dev
sudopythonsetup.pyinstallUsageObserve a satellite (relative to a position on earth)importpredicttle="""0 LEMUR 11 40044U 14033AL  15013.74135905  .00002013  00000-0  31503-3 0  61192 40044 097.9584 269.2923 0059425 258.2447 101.2095 14.72707190 30443"""qth=(37.771034,122.413815,7)# lat (N), long (W), alt (meters)predict.observe(tle,qth)# optional time argument defaults to time.time()# => {'altitude': 676.8782276657903,#     'azimuth': 96.04762045174824,#     'beta_angle': -27.92735429908726,#     'decayed': 0,#     'doppler': 1259.6041017128405,#     'eci_obs_x': -2438.227652191655,#     'eci_obs_y': -4420.154476060397,#     'eci_obs_z': 3885.390601342013,#     'eci_sun_x': 148633398.020844,#     'eci_sun_y': -7451536.44122029,#     'eci_sun_z': -3229999.50056359,#     'eci_vx': 0.20076213530665032,#     'eci_vy': -1.3282146055077213,#     'eci_vz': 7.377067234096598,#     'eci_x': 6045.827328897242,#     'eci_y': -3540.5885778261277,#     'eci_z': -825.4065096776636,#     'eclipse_depth': -87.61858291647795,#     'elevation': -43.711904591801726,#     'epoch': 1521290038.347793,#     'footprint': 5633.548906707907,#     'geostationary': 0,#     'has_aos': 1,#     'latitude': -6.759563817939698,#     'longitude': 326.1137007912563,#     'name': '0 LEMUR 1',#     'norad_id': 40044,#     'orbit': 20532,#     'orbital_model': 'SGP4',#     'orbital_phase': 145.3256815318047,#     'orbital_velocity': 26994.138671706416,#     'slant_range': 9743.943478523843,#     'sunlit': 1,#     'visibility': 'D'#    }Show upcoming transits of satellite over ground station# start and stop transit times as UNIX timestamptransit_start=1680775200transit_stop=1681034400p=predict.transits(tle,qth,transit_start,transit_stop)print("Start of Transit\tTransit Duration (s)\tPeak Elevation")fortransitinp:print(f"{transit.start}\t{transit.duration()}\t{transit.peak()['elevation']}")Modeling an entire constellationGenerating transits for a lot of satellites over a lot of ground stations can be slow.
Luckily, generating transits for each satellite-groundstation pair can be parallelized for a big speed-up.importitertoolsfrommultiprocessing.poolimportPoolimporttimeimportpredictimportrequests# Define a function that returns arguments for all the transits() calls you want to makedef_transits_call_arguments():now=time.time()tle=requests.get('http://tle.spire.com/25544').text.rstrip()forlatitudeinrange(-90,91,15):forlongitudeinrange(-180,181,15):qth=(latitude,longitude,0)yield{'tle':tle,'qth':qth,'ending_before':now+60*60*24*7}# Define a function that calls the transit function on a set of arguments and does per-transit processingdef_transits_call_fx(kwargs):try:transits=list(predict.transits(**kwargs))return[t.above(10)fortintransits]exceptpredict.PredictException:pass# Map the transit() caller across all the arguments you want, then flatten results into a single listpool=Pool(processes=10)array_of_results=pool.map(_transits_call_fx,_transits_call_arguments())flattened_results=list(itertools.chain.from_iterable(filter(None,array_of_results)))transits=flattened_resultsNOTE: If precise accuracy isn't necessary (for modeling purposes, for example) setting the tolerance argument
to theabovecall to a larger value, say 1 degree, can provide a significant performance boost.Call predict analogs directlypredict.quick_find(tle.split('\n'),time.time(),(37.7727,122.407,25))predict.quick_predict(tle.split('\n'),time.time(),(37.7727,122.407,25))APIobserve(tle, qth[, at=None])  
    Return an observation of a satellite relative to a groundstation.qthgroundstation coordinates as (lat(N),long(W),alt(m))
    Ifatis not defined, defaults to current time (time.time())
    Returns an "observation" or dictionary containing:altitude_ altitude of satellite in kilometersazimuth- azimuth of satellite in degrees from perspective of groundstation.beta_angledecayed- 1 if satellite has decayed out of orbit, 0 otherwise.doppler- doppler shift between groundstation and satellite.eci_obs_xeci_obs_yeci_obs_zeci_sun_xeci_sun_yeci_sun_zeci_vxeci_vyeci_vzeci_xeci_yeci_zeclipse_depthelevation- elevation of satellite in degrees from perspective of groundstation.epoch- time of observation in seconds (unix epoch)footprintgeostationary- 1 if satellite is determined to be geostationary, 0 otherwise.has_aos- 1 if the satellite will eventually be visible from the groundstationlatitude- north latitude of point on earth directly under satellite.longitude- west longitude of point on earth directly under satellite.name- name of satellite from first line of TLE.norad_id- NORAD id of satellite.orbitorbital_phaseorbital_modelorbital_velocityslant_range- distance to satellite from groundstation in meters.sunlit- 1 if satellite is in sunlight, 0 otherwise.visibilitytransits(tle, qth[, ending_after=None][, ending_before=None])  
    Returns iterator ofTransitobjects representing passes of tle over qth.  
    Ifending_afteris not defined, defaults to current time  
    Ifending_beforeis not defined, the iterator will yield until calculation failure.NOTE: We yield passes based on their end time.  This means we'll yield currently active passes in the two-argument invocation form, but their start times will be in the past.Transit(tle, qth, start, end)  
    Utility class representing a pass of a satellite over a groundstation.
    Instantiation parameters are parsed and made available as fields.duration()  
        Returns length of transit in secondspeak(epsilon=0.1)  
        Returns epoch time where transit reaches maximum elevation (within ~epsilon)at(timestamp)  
        Returns observation during transit viaquick_find(tle, timestamp, qth)aboveb(elevation,tolerance)
        Returns portion of transit above elevation. If the entire transit is below the target elevation, both
        endpoints will be set to the peak and the duration will be zero. If a portion of the transit is above
        the elevation target, the endpoints will be between elevation and elevation + tolerance (unless
        endpoint is already above elevation, in which case it will be unchanged)quick_find(tle[, time[, (lat, long, alt)]])timedefaults to current time(lat, long, alt)defaults to values in ~/.predict/predict.qth  
    Returns observation dictionary equivalent to observe(tle, time, (lat, long, alt))quick_predict(tle[, time[, (lat, long, alt)]])  
        Returns an array of observations for the next pass as calculated by predict.
        Each observation is identical to that returned byquick_find.