Enter the query into the form above. You can look for specific version of a package by using @ symbol like this: gcc@10.
API method:
GET /api/packages?search=hello&page=1&limit=20
where search is your query, page is a page number and limit is a number of items on a single page. Pagination information (such as a number of pages and etc) is returned
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TANGOS is a tool to build a database (along the lines of Eagle or MultiDark) for cosmological and zoom simulations.
Features:
designed to store and manage results from custom analysis code
provides web and Python interfaces
science-focussed queries across entire merger trees, without requiring any knowledge of SQL
manages the process of populating the database with science data, including auto-parallelising custom analysis
customization with multiple Python modules such as
pynbodyorytto process raw simulation datasuports file-based database SQLite, server-based MySQL and PostgreSQL
The Advanced Scientific Data Format (ASDF) is a next-generation interchange format for scientific data. This package contains the Python implementation of the ASDF Standard.
The DKIST package aims to help you search, obtain and use DKIST data as part of your Python software.
The CALCEPH Library is designed to access the binary planetary ephemeris files, such INPOPxx and JPL DExxx ephemeris files, (called original JPL binary or INPOP 2.0 or 3.0 binary ephemeris files in the next sections) and the SPICE kernel files (called SPICE ephemeris files in the next sections). At the moment, supported SPICE files are:
text Planetary Constants Kernel (KPL/PCK) files;
binary PCK (DAF/PCK) files;
binary SPK (DAF/SPK) files containing segments of type 1, 2, 3, 5, 8, 9, 12, 13, 17, 18, 19, 20, 21, 102, 103 and 120;
meta kernel (KPL/MK) files;
frame kernel (KPL/FK) files (only basic support).
GenetIC is a code to generate initial conditions for cosmological simulations, especially for zoom simulations of galaxies. It provides support for "genetic modifications" as described by e.g. Roth et al 2015, Rey & Pontzen 2018. It also supports 'splicing' as described by Cadiou et al 2021.
BayesicFitting is a package for model fitting and Bayesian evidence calculation, it is a Python version of the the fitter classes in HCSS. HCSS was the all encompassing software system for the operations and analysis of the ESA satelite Herschel.
The Advanced Scientific Data Format (ASDF) is a next-generation interchange format for scientific data. This package contains the Python implementation of the ASDF Standard.
This package provides tools for machine learning and data mining in astronomy.
Regions is an Astropy package for region handling.
This package provides a replacement for IRAF STSDAS SYNPHOT and ASTROLIB PYSYNPHOT, utilizing Astropy covering instrument specific portions of the old packages for HST.
This package provides a collection of Space Telescope Science Institute utility functions.
POLIASTRO is a Python library for interactive Astrodynamics and Orbital Mechanics, with a focus on ease of use, speed, and quick visualization. It provides a simple and intuitive API, and handles physical quantities with units.
Some features include orbit propagation, solution of the Lambert's problem, conversion between position and velocity vectors and classical orbital elements and orbit plotting, among others. It focuses on interplanetary applications, but can also be used to analyze artificial satellites in Low-Earth Orbit (LEO).
This package provides a Low-Frequency Array a large radio telescope Solution Tool.
astrodata is a package for managing astronomical data through a uniform interface. It is designed to be used with the Astropy package. astrodata was created for use as part of the DRAGONS data reduction pipeline, but it is now implemented to be useful for any astronomical data reduction or analysis project.
Unlike managing files using the astropy.io.fits package alone, astrodata is designed to be extendible to any data format, and to parse, respond to, and store metadata in a consistent, intentional way. This makes it especially useful for managing data from multiple instruments, telescopes, and data generation utilities.
STPSF produces simulated PSFs for the James Webb Space Telescope, NASA's flagship infrared space telescope. STPSF can simulate images for any of the four science instruments plus the fine guidance sensor, including both direct imaging, coronagraphic, and spectroscopic modes.
This package provides a Python package of Roman Datamodels for the calibration pipelines started with the JWST calibration pipelines. The goal for the JWST pipelines was motivated primarily by the need to support FITS data files, specifically with isolating the details of where metadata and data were located in the FITS file from the representation of the same items within the Python code. That is not a concern for Roman since FITS format data files will not be used by the Roman calibration pipelines.
RAD is package which defines schemas for the Nancy Grace Roman Space Telescope shared attributes for processing and archive. These schemas are schemas for the ASDF file file format, which are used by ASDF to serialize and deserialize data for the Nancy Grace Roman Space Telescope.
The spherical_geometry library is a Python package for handling spherical polygons that represent arbitrary regions of the sky.
This package provides a a simple program to predict the levels of background emission in JWST observations, for use in proposal planning.
It accesses a precompiled background cache prepared by Space Telescope Science Institute. The background cache is hosted by the Mikulski Archive for Space Telescopes (MAST), so you need internet access to run the tool with the remote cache. It is possible to download the full background cache to your local machine.
Python read-only implementation of the EventIO file format.
This package provides an way to compute dendrograms of observed or simulated Astronomical data in Python.
Gpredict is a real-time satellite tracking and orbit prediction application. It can track a large number of satellites and display their position and other data in lists, tables, maps, and polar plots (radar view). Gpredict can also predict the time of future passes for a satellite, and provide you with detailed information about each pass.
Some core features of Gpredict include:
Tracking of a large number of satellites only limited by the physical memory and processing power of the computer
Display the tracking data in lists, maps, polar plots and any combination of these
Have many modules open at the same either in a notebook or in their own windows. The modules can also run in full-screen mode
You can use many ground stations
Predict upcoming passes
Gpredict can run in real-time, simulated real-time (fast forward and backward), and manual time control
Detailed information both the real time and non-real time modes
Doppler tuning of radios via Hamlib rigctld
Antenna rotator control via Hamlib rotctld