Skip to main content

A package to handle the space targets catalogue query

Project description

Welcome to the SATQUERY package

PyPI version shields.io PyPI pyversions PyPI status GitHub contributors Maintenance GitHub license Documentation Status Build Status

This package is an archive of scientific routines for data processing related to the space targets catalogue query. Currently, operations on targets catalogue query include:

  1. targets catalogue query on shape info from DISCOS(Database and Information System Characterising Objects in Space) database;
  2. targets catalogue query on orbit info from CelesTrak database;
  3. targets catalogue query on both shape and orbit from a combined database;

How to Install

On Linux, macOS and Windows architectures, the binary wheels can be installed using pip by executing one of the following commands:

pip install satcatalogquery
pip install satcatalogquery --upgrade # to upgrade a pre-existing installation

How to use

Targets catalogue query from DISCOS

Query by NORAD_ID, where type of NORAD_ID can be int/str, list of int/str, or a text file named satno.txt in the following format:

# satno
52132
51454
37637
26758
44691
>>> from satcatalogquery import discos_query
>>> satcatlog = discos_query(NORAD_ID=[52132,51454,37637,26758,44691])
>>> # satcatog = discos_query(NORAD_ID='satno.txt')
>>> satcatlog.df # output pandas dataframe
>>> satcatlog.save() # save dataframe to .csv file

Query by mutiple options at the same time, such as COSPAR_ID, MASS, SHAPE, RCSAvg, etc.

>>> from satcatalogquery import discos_query
>>> satcatlog = discos_query(SHAPE=['Box','Pan'],RCSAvg=[0.5,100],DECAYED=False)

Targets catalogue query from CelesTrak

>>> from satcatalogquery import celestrak_query
>>> satcatlog = celestrak_query(MEAN_ALT=[300,2000],ECC=[0.01,0.1],PAYLOAD=False)

Targets catalogue query from combined database

>>> from satcatalogquery import targets_query
>>> satcatlog = targets_query(DECAYED=False,RCSAvg=[0.25,1e4],MEAN_ALT=[250,2000],TLE_STATUS=True,sort='RCSAvg')

Create object SatCatlog from a loacl .csv file

>>> from satcatalogquery import SatCatlog
>>> satcatlog = SatCatlog.from_csv('filename.csv')

Statistics

>>> satcatlog.statistics1d('RCSAvg')
>>> satcatlog.statistics1d(['StdMag','LAUNCH_DATE'])
>>> satcat.statistics2d('MEAN_ALT','INCLINATION')

Download TLE from results of targets catalogue query

>>> tle_path = satcatlog.get_tle()

Change log

  • 0.2.0 — Jan 4, 2023

    • Add method from_csv to class SatCatlog

    • Add statistics figures to README.md

  • 0.1.1 — Jan 2, 2023

    • The satcatalogquery package was released.

Reference

Project details


Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

satcatalogquery-0.2.0-py3-none-any.whl (15.9 kB view details)

Uploaded Python 3

File details

Details for the file satcatalogquery-0.2.0-py3-none-any.whl.

File metadata

  • Download URL: satcatalogquery-0.2.0-py3-none-any.whl
  • Upload date:
  • Size: 15.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.8.2 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7

File hashes

Hashes for satcatalogquery-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 29341e3a5ba5dd37d95f54a8b9582b63f352a07ef95f38c0f666fe24a1c71487
MD5 dbf3ea56557aa3cf2e2ea33b66c85150
BLAKE2b-256 b0776dfd9fbf7d1ca81cc99c6cc9c6399523511f49356c625cc8c0bb62c3e4be

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page