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#astropython — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #astropython, aggregated by home.social.

  1. Random Astro package of the week is python3-reproject. This is a package to reproject astronomical images using various techniques via a uniform interface. Reprojection means the re-gridding of images from one world coordinate system to another (for example changing the pixel resolution, orientation, coordinate system). Currently implemented are reprojection of celestial images by interpolation, as well as by finding the exact
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  2. Random Astro package of the week is python3-pyavm. PyAVM is a module to represent, read, and write metadata following the Astronomy Visualization Metadata (AVM) standard. With pyavm you can:

    * Parse AVM meta-data from an existing image.
    * Access and Set the metadata.
    * Create an AVM object from scratch.
    * Convert to a WCS object.
    * Initialize from a FITS header.
    * Initialize from a WCS object.
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  3. Random Astro package of the week is python3-ephem. PyEphem provides an ephem Python package for performing high-precision astronomy computations. The underlying numeric routines are coded in C and are the same ones that drive the popular XEphem astronomy application, whose author, Elwood Charles Downey, generously gave permission for their use in PyEphem.

    The name ephem is short for the word ephemeris, which is the traditional
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  4. Random Astro package of the week is python3-vispy. Vispy is a high-performance interactive 2D/3D data visualization library.

    Vispy leverages the computational power of modern Graphics Processing Units (GPUs) through the OpenGL library to display very large datasets.

    This package provides VisPy for the Python 3 interpreter.

    vispy.org/

  5. Random Astro package of the week is python3-pyraf. PyRAF is a command language for running IRAF tasks in a Python like environment. It works very similar to IRAF CL, but has been updated to allow such things as importing Python modules, GUI parameter editing and help. It can be imported into Python allowing you to run IRAF commands from within a larger script.

    iraf-community.github.io/pyraf

  6. Random Astro package of the week is python3-asdf. ASDF (Advanced Scientific Data Format) is a proposed next generation interchange format for scientific data. ASDF aims to exist in the same middle ground that made FITS so successful, by being a hybrid text and binary format: containing human editable metadata for interchange, and raw binary data that is fast to load and use. Unlike FITS, the metadata is highly structured and is
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  7. Random Astro package of the week is python3-drms. The drms module provides an easy-to-use Python interface for accessing HMI, AIA and MDI data with Python. It uses the publicly accessible Joint Science Operations Center (JSOC) server by default, but can also be used with local NetDRMS sites.

    The Helioseismic and Magnetic Imager (HMI) and the Atmospheric Imaging Assembly (AIA) are instruments aboard the Solar Dynamics
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  8. Random Astro package of the week is python3-montagepy. MontagePy is a toolkit for assembling astronomical images into custom mosaics.

    It uses algorithms that preserve the calibration and positional (astrometric) fidelity of the input images to deliver mosaics that meet user-specified parameters of projection, coordinates, and spatial scale. It supports all projections and coordinate systems in use in
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  9. Random Astro package of the week is python3-fast-histogram. fast-histogram aims to provide simple and fast histogram functions for regular bins that don't compromise on performance. It doesn't do anything complicated - it just implements a simple histogram algorithm in C and keeps it simple. The aim is to have functions that are fast but also robust and reliable. The result is a 1D histogram function here that is 7-15x faster
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  10. Random Astro package of the week is python3-healpy. HEALPix is an acronym for Hierarchical Equal Area isoLatitude Pixelization of a sphere. As suggested in the name, this pixelization produces a subdivision of a spherical surface in which each pixel covers the same surface area as every other pixel. It is commonly used to store all-sky astronomical images, most famously maps of the cosmic microwave background.
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  11. Random Astro package of the week is python3-drizzle. The drizzle library is a Python package for combining dithered images into a single image. This library is derived from code used in drizzlepac. Like drizzlepac, most of the code is implemented in the C language. The biggest change from drizzlepac is that this code passes an array that maps the input to output image into the C code, while the drizzlepac code computes the
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  12. Random Astro package of the week is python3-pysynphot. pysynphot simulates photometric data and spectra as they are observed with the Hubble Space Telescope (HST). Passbands for standard photometric systems are available, and users can incorporate their own filters, spectra, and data. pysynphot user interface allows you to:

    * Construct complicated composite spectra from various grids of model
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  13. Random Astro package of the week is python3-fitsio. Fitsio provides an easy to use object-oriented API including providing a Numpy interface to FITS files read from CFITSIO. It allows direct access to the columns of a FITS binary table which can be useful for reading large fits files. Compared to astropy.io.fits, this package is closer to the underlying cfitsio library.

    Fitsio also exposes a microlanguage (implemented in
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  14. Random Astro package of the week is python3-numpy. NumPy contains a powerful N-dimensional array object, sophisticated (broadcasting) functions, tools for integrating C/C++ and Fortran code, and useful linear algebra, Fourier transform, and random number capabilities.

    This package installs NumPy for Python 3.

    numpy.org/

  15. #AstroPython #VirtualObservatory #AstronomySoftware #ScienceSoftware

    Random #Debian Astro package of the week is python3-pymoc. PyMOC provides a Python compatible library for handling MOCs.

    Frequently astronomical survey catalogues or images are sparse and cover only a small part of the sky. In a Multi-Order Coverage map the extent of data in a particular dataset is cached as a pre-calculated mask image. The hierarchical nature enables fast boolean operations in image space,
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