{ "metadata": { "name": "", "signature": "sha256:871d8475300d0d729c130c941a138f090207bb69124c28b877867d5d1aa50fa3" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Representations of the sphere and the cosmic microwave background (CMB)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Autor: [Eduardo Mart\u00edn Calleja](http://balbuceosastropy.blogspot.com.es/)\n", "\n", "In this post, which can be considered a continuation of the previous post, dedicated to the Mollweide projection, we will see an introduction to the Python [healpy](https://pypi.python.org/pypi/healpy) package. Healpy provides access from Python to the [HEALPix](http://healpix.sourceforge.net/) set of functions, which are the standard for data representation from the various missions that measure the temperature of the microwave background radiation of the universe.\n", "\n", "HALPIx provides an algorithm for subdividing the surface of the sphere in a series of picture elements (pixels) with the property that they all represent exactly the same area of the original spherical surface, and furthermore, these pixels are arranged into lines of equal latitude. Then this subdivision can be transferred to a plane projection like Mollweide, as it preserve the equal-area property in the flat representation.\n", "\n", "Having graphic representations of the spherical surface with pixels of the same area is crucial for the presentation and subsequent analysis of the distribution of mass, energy, radiation, etc.. Allowing relative densities to be compared and to apply various algorithms. In particular, the library HEALPix was originally developed to represent the distribution of the microwave background radiation which has been compiling data on various missions, although its use has since spread to other fields." ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Imports and references" ] }, { "cell_type": "code", "collapsed": false, "input": [ "%matplotlib inline\n", "from __future__ import division\n", "\n", "import numpy as np\n", "import healpy as hp\n", "import astroML\n", "\n", "#This removes some nasty deprecation warnings that do not interfere with the execution\n", "import warnings\n", "warnings.filterwarnings('ignore')\n", "\n", "# This IPython magic generates a table with version information\n", "#https://github.com/jrjohansson/version_information\n", "%load_ext version_information\n", "%version_information numpy, healpy, astroML, astroPy" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
Software | Version |
---|---|
Python | 2.7.9 64bit [GCC 4.4.7 20120313 (Red Hat 4.4.7-1)] |
IPython | 2.3.1 |
OS | Linux 3.13.0 45 generic x86_64 with debian jessie sid |
numpy | 1.9.1 |
healpy | 1.8.4 |
astroML | 0.2 |
astroPy | 0.4.3 |
Fri Feb 20 21:17:32 2015 CET |