{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "raw",
      "source": [
        "---\n",
        "date: 2024-05-20\n",
        "toc: true\n",
        "format: \n",
        "  html: default\n",
        "  ipynb: default\n",
        "categories:\n",
        "  - cosmology\n",
        "  - healpy\n",
        "---"
      ],
      "metadata": {
        "id": "amJGRE8uxNHb"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# HEALPix in Megapixels\n",
        "\n",
        "How many megapixels is a HEALPix map?"
      ],
      "metadata": {
        "id": "ySEK3AO_usIL"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Oy9E_3j5ukaR",
        "outputId": "3c7f621d-dd7f-41b2-c1a9-f83f6ddffdc2"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting healpy\n",
            "  Downloading healpy-1.16.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (24.5 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m24.5/24.5 MB\u001b[0m \u001b[31m16.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: matplotlib in /usr/local/lib/python3.10/dist-packages (from healpy) (3.7.1)\n",
            "Requirement already satisfied: numpy>=1.19 in /usr/local/lib/python3.10/dist-packages (from healpy) (1.25.2)\n",
            "Requirement already satisfied: astropy in /usr/local/lib/python3.10/dist-packages (from healpy) (5.3.4)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.10/dist-packages (from healpy) (1.11.4)\n",
            "Requirement already satisfied: pyerfa>=2.0 in /usr/local/lib/python3.10/dist-packages (from astropy->healpy) (2.0.1.4)\n",
            "Requirement already satisfied: PyYAML>=3.13 in /usr/local/lib/python3.10/dist-packages (from astropy->healpy) (6.0.1)\n",
            "Requirement already satisfied: packaging>=19.0 in /usr/local/lib/python3.10/dist-packages (from astropy->healpy) (24.0)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->healpy) (1.2.1)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib->healpy) (0.12.1)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->healpy) (4.51.0)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->healpy) (1.4.5)\n",
            "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->healpy) (9.4.0)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->healpy) (3.1.2)\n",
            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib->healpy) (2.8.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib->healpy) (1.16.0)\n",
            "Installing collected packages: healpy\n",
            "Successfully installed healpy-1.16.6\n"
          ]
        }
      ],
      "source": [
        "!pip install healpy"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import healpy as hp"
      ],
      "metadata": {
        "id": "ZQKIgPhpvUnz"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "megapixels = []\n",
        "for nside_power in range(8, 15):\n",
        "  nside = 2**nside_power\n",
        "  megapixels.append((nside, hp.nside2npix(nside)/1e6))"
      ],
      "metadata": {
        "id": "tCOTEQDUulw3"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "megapixels"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ALfTBVV_vWgE",
        "outputId": "8b97dac5-fd44-48da-8956-3d6c4f479c10"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[(256, 0.786432),\n",
              " (512, 3.145728),\n",
              " (1024, 12.582912),\n",
              " (2048, 50.331648),\n",
              " (4096, 201.326592),\n",
              " (8192, 805.306368),\n",
              " (16384, 3221.225472)]"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    }
  ]
}