{ "info": { "author": "Angel Ruiz", "author_email": "angel.ruizca@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Intended Audience :: Science/Research", "License :: OSI Approved :: BSD License", "Operating System :: POSIX :: Linux", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3.6", "Topic :: Scientific/Engineering :: Astronomy" ], "description": "gdpyc \u2500 Gas and Dust Python Calculator\n======================================\n.. inclusion-marker-main-readme\n\n``gdpyc`` is a Python 2/3 package for calculating Hydrogen column density\nand optical extinction. ``gdpyc`` offers functionalities similar\nto the `nh tool`_ included in HEASoft, or on-line web services like\nHEASARC's `nH`_ or IRSA's `Galactic Dust Reddening and Extinction`_.\n\nThis package uses HEALpix maps provided by NASA's LAMBDA service. Please\ncite the original papers and authors of the surveys if you use this tool\nfor your research (see sections Surveys and References below).\n\n|astropy| |DOI|\n\nDependencies\n------------\n``gdpyc`` depends on:\n\n* ``astropy``\n* ``astropy-healpix``\n* ``numpy`` \n\nCertain functionalities also requiere:\n\n* ``healpix``\n* ``matplotlib``\n\nInstallation\n------------\n\n``gdpyc`` can be easily installed using ``pip``::\n\n pip install gdpyc\n\nExample\n-------\nA simple example of using ``gdpyc``::\n\n >>> from gdpyc import GasMap, DustMap\n >>> from astropy.coordinates import SkyCoord\n\n >>> coords = SkyCoord(34.0, -5.0, unit='deg')\n >>> GasMap.nh(coords, nhmap='DL')\n\n \n\n >>> GasMap.nh(coords, nhmap='LAB')\n\n \n\n >>> DustMap.ebv(coords, dustmap='Planck13')\n\n '0.027179038520908336'\n\n >>> DustMap.extinction(coords, dustmap='SFD', filters='SDSS_r')\n\n \n SDSS_r \n float64 \n --------------------\n 0.049108389441137615\n\n >>> GasMap.plot_map('HI4PI')\n\nSurveys\n-------\n``gdpyc`` includes several HI and dust surveys with nH and E(B - V)\nestimations. We created low resolution HEALPix maps for all surveys\n(NSIDE=64 ~ 1 degree pixels) by degrading the original maps using\nthe `ud_grade` tool from `healpy`. Only low resolution maps are\nincluded in the installation. If the user asks for high resolution\nmaps (`hires` parameter, see API documentation), they are downloaded\nas needed and stored for future use.\n\nHI surveys\n^^^^^^^^^^\n\n`DL`_: Composite all-sky map of neutral Hydrogen column density (NHI),\nformed from the Leiden/Dwingeloo survey data [1]_ and the composite NHI\nmap of [2]_. The two datasets are not matched in sensitivity or resolution;\nnote that discontinuities exist in the constructed composite map. \n\n`DL high resolution data`_ (oversampled), NSIDE=512 ~ 0.11 deg.\n\n`LAB`_: Observations of 21-cm emission from Galactic neutral Hydrogen\nover the entire sky, merging the Leiden/Dwingeloo Survey [1]_ of the sky\nnorth of -30\u00b0 with the Instituto Argentino de Radioastronomia Survey\n[3]_, [4]_ of the sky south of -25\u00b0. [5]_\n\n`LAB high resolution data`_ (oversampled), NSIDE=512 ~ 0.11 deg. [6]_\n\n`HI4PI`_: The HI 4-PI Survey (HI4PI) is a 21-cm all-sky survey of\nneutral atomic Hydrogen. It is constructed from the Effelsberg-Bonn HI\nSurvey (EBHIS) and the Galactic All-Sky Survey (GASS). [7]_\n\n`HI4PI high resolution data`_, NSIDE=1024 ~ 0.06 deg.\n\nDust surveys\n^^^^^^^^^^^^\n`SFD`_: All-sky map of Galactic reddening, E(B - V), from a\ncomposite 100 micron map formed from IRAS/ISSA maps calibrated\nusing DIRBE observations. [8]_\n\n`SFD high resolution data`_ (undersampled), NSIDE=512 ~ 0.11 deg.\n\n`Planck13`_: All-sky map of Galactic reddening, E(B - V), using\nPlanck-HFI and IRAS data, for extra-galactic studies. [9]_\n\n`Planck13 high resolution data`_, NSIDE=2048 ~ 0.03 deg.\n\nExtinction values for different filters are estimated using the E(B - V)\nconversion factors presented in [10]_, assuming an extinction to\nreddening ratio R=3.1 Additional factors for 2MASS, `Spitzer`-IRAC\nand WISE filters are from IRSA's `Galactic Dust Reddening and Extinction`_ \nservice.\n\nReferences\n----------\n.. [1] Hartmann & Burton 1997, Cambridge University Press.\n.. [2] Dickey & Lockman 1990, Ann. Rev. A&A, 28, 215.\n.. [3] Arnal et al. 2000, A&AS, 142.\n.. [4] Bajaja et al. 2005, A&A, 440, 2\n.. [5] Kalberla et al. 2005, A&A, 440, 775.\n.. [6] Land & Slosar 2007, Phys. Rev. D, 76, 8.\n.. [7] HI4PI Collaboration et al. 2016, A&A, 594, A116.\n.. [8] Schlegel, Finkbeiner & Davis 1998, ApJ, 500, 2.\n.. [9] Planck Collaboration et al. 2013, A&A, 571, A11.\n.. [10] Schlafly & Finkbeiner 2011, ApJ, 737, 2, 103.\n\n\n.. _nh tool: https://heasarc.gsfc.nasa.gov/lheasoft/ftools/heasarc.html\n.. _nH: https://heasarc.gsfc.nasa.gov/cgi-bin/Tools/w3nh/w3nh.pl\n.. _Galactic Dust Reddening and Extinction: https://irsa.ipac.caltech.edu/applications/DUST/\n.. _DL: https://lambda.gsfc.nasa.gov/product/foreground/fg_combnh_map.cfm\n.. _DL high resolution data: https://lambda.gsfc.nasa.gov/product/foreground/fg_HI_get.cfm\n.. _LAB: https://lambda.gsfc.nasa.gov/product/foreground/fg_LAB_HI_Survey_info.cfm\n.. _LAB high resolution data: https://lambda.gsfc.nasa.gov/product/foreground/fg_LAB_HI_Survey_get.cfm\n.. _HI4PI: https://lambda.gsfc.nasa.gov/product/foreground/fg_hi4pi_info.cfm\n.. _HI4PI high resolution data: https://lambda.gsfc.nasa.gov/product/foreground/fg_hi4pi_get.cfm\n.. _SFD: https://lambda.gsfc.nasa.gov/product/foreground/fg_ebv_map.cfm\n.. _SFD high resolution data: https://lambda.gsfc.nasa.gov/product/foreground/fg_sfd_get.cfm\n.. _Planck13: https://wiki.cosmos.esa.int/planckpla/index.php/CMB_and_astrophysical_component_maps#Thermal_dust_emission\n.. _Planck13 high resolution data: http://pla.esac.esa.int/pla/aio/product-action?MAP.MAP_ID=HFI_CompMap_ThermalDustModel_2048_R1.20.fits\n\n.. |astropy| image:: http://img.shields.io/badge/powered%20by-AstroPy-orange.svg?style=flat\n :target: http://www.astropy.org/\n\n.. |DOI| image:: https://zenodo.org/badge/156710074.svg\n :target: https://zenodo.org/badge/latestdoi/156710074\n\n", "description_content_type": "text/x-rst", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/ruizca/gdpyc", "keywords": "", "license": "", "maintainer": "", "maintainer_email": "", "name": "gdpyc", "package_url": "https://pypi.org/project/gdpyc/", "platform": "", "project_url": "https://pypi.org/project/gdpyc/", "project_urls": { "Homepage": "https://github.com/ruizca/gdpyc" }, "release_url": "https://pypi.org/project/gdpyc/1.0/", "requires_dist": [ "astropy", "numpy", "astropy-healpix", "regions", "matplotlib; extra == 'plot_map'", "healpy; extra == 'plot_map'" ], "requires_python": "", "summary": "Gas and Dust Python Calculator", "version": "1.0" }, "last_serial": 4474609, "releases": { "1.0": [ { "comment_text": "", "digests": { "md5": "159331a7b841e1b46628b341d3024e53", "sha256": "fe5be2ba22ac7062e767db84ac4583dd5f3680e78d6a97db118c83a41c313655" }, "downloads": -1, "filename": "gdpyc-1.0-py3-none-any.whl", "has_sig": false, "md5_digest": "159331a7b841e1b46628b341d3024e53", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 1300580, "upload_time": "2018-11-11T15:55:10", "url": "https://files.pythonhosted.org/packages/71/ed/ae506a5fadd8599dcde7ff1ee415808ef567a8b0bb559b89a6f4ab37fa41/gdpyc-1.0-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "b209afc44d497d48557a10edbd6f7f12", "sha256": "20ab89d8856c6a4f87c347dbdf94f3b041a7e951ef55325ca822a32e3556eed9" }, "downloads": -1, "filename": "gdpyc-1.0.tar.gz", "has_sig": false, "md5_digest": "b209afc44d497d48557a10edbd6f7f12", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 1300831, "upload_time": "2018-11-11T15:55:18", "url": "https://files.pythonhosted.org/packages/05/0a/a36f3084839ddc2abe0f9242827f01f2193fb5dfcbd8e73e6096faf9c9b9/gdpyc-1.0.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "159331a7b841e1b46628b341d3024e53", "sha256": "fe5be2ba22ac7062e767db84ac4583dd5f3680e78d6a97db118c83a41c313655" }, "downloads": -1, "filename": "gdpyc-1.0-py3-none-any.whl", "has_sig": false, "md5_digest": "159331a7b841e1b46628b341d3024e53", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 1300580, "upload_time": "2018-11-11T15:55:10", "url": "https://files.pythonhosted.org/packages/71/ed/ae506a5fadd8599dcde7ff1ee415808ef567a8b0bb559b89a6f4ab37fa41/gdpyc-1.0-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "b209afc44d497d48557a10edbd6f7f12", "sha256": "20ab89d8856c6a4f87c347dbdf94f3b041a7e951ef55325ca822a32e3556eed9" }, "downloads": -1, "filename": "gdpyc-1.0.tar.gz", "has_sig": false, "md5_digest": "b209afc44d497d48557a10edbd6f7f12", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 1300831, "upload_time": "2018-11-11T15:55:18", "url": "https://files.pythonhosted.org/packages/05/0a/a36f3084839ddc2abe0f9242827f01f2193fb5dfcbd8e73e6096faf9c9b9/gdpyc-1.0.tar.gz" } ] }