cartopy_installation_on_colab.ipynb

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    "kernelspec": {
      "display_name": "Python [cartopy]",
      "language": "python",
      "name": "Python [cartopy]"
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    "colab": {
      "name": "cartopy_getstarted_on_colab.ipynb",
      "provenance": [],
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      "include_colab_link": true
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/swatchai/cartopy_asean_proj/blob/master/cartopy_installation_on_colab.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JAD3FcFsSHgH"
      },
      "source": [
        "## Get started using Cartopy"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "W2H18pSjvct3"
      },
      "source": [
        "Purpose: To assist my followers to install Cartopy and get started."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AUZH_aC6SHgM"
      },
      "source": [
        "Author: swatchai kriengkraipet"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "k2-BzWVOSHgP"
      },
      "source": [
        "Summaries:\n",
        "- This is Jupyter notebook\n",
        "- Shared on: colab\n",
        "- Requires: Python3 + matplotlib + cartopy + etc. packages\n",
        "- Prepared for my followers\n",
        "- Some hacks included to get around the bugs.\n",
        "\n",
        "Following inexperienced people can be more adventurous and have a lot of fun, but following experienced ones often lead you to the desired destination. \n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": true,
        "id": "7qJFoOyqSHgQ"
      },
      "source": [
        "%matplotlib inline"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ngh5WE9PVz_Z",
        "outputId": "5974c31f-58bf-4631-867b-55f672def46c"
      },
      "source": [
        "! which python"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/bin/python\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eiCAnOFiV6Vu"
      },
      "source": [
        "import sys"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "V9z-KVVwWMqU",
        "outputId": "bbd81853-9faf-4a61-e033-710002c81e95"
      },
      "source": [
        "sys.version"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'3.7.11 (default, Jul  3 2021, 18:01:19) \\n[GCC 7.5.0]'"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sNH9JK5rSsQZ",
        "outputId": "5db43e3a-ac82-4af0-f40c-69dd54008e95"
      },
      "source": [
        "!pip install cartopy"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting cartopy\n",
            "  Using cached Cartopy-0.19.0.post1-cp37-cp37m-linux_x86_64.whl\n",
            "Requirement already satisfied: pyshp>=2 in /usr/local/lib/python3.7/dist-packages (from cartopy) (2.1.3)\n",
            "Requirement already satisfied: numpy>=1.13.3 in /usr/local/lib/python3.7/dist-packages (from cartopy) (1.19.5)\n",
            "Requirement already satisfied: shapely>=1.5.6 in /usr/local/lib/python3.7/dist-packages (from cartopy) (1.7.1)\n",
            "Installing collected packages: cartopy\n",
            "Successfully installed cartopy-0.19.0.post1\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zF8OJxfPtWw-",
        "outputId": "63667ddd-9e1b-4611-8f47-a29e13cbb1f3"
      },
      "source": [
        "## uninstall the BAD implementation of shapely\n",
        "## .. that causes cartopy's crashes\n",
        "\n",
        "!pip uninstall shapely -y"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Found existing installation: Shapely 1.7.1\n",
            "Uninstalling Shapely-1.7.1:\n",
            "  Successfully uninstalled Shapely-1.7.1\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "y8xXgWJstWhq",
        "outputId": "9007b25c-ce41-45ce-d121-71fd81f80459"
      },
      "source": [
        "## Install the GOOD shapely\n",
        "## .. that wont crash cartopy.\n",
        "\n",
        "!pip install shapely --no-binary shapely"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting shapely\n",
            "  Downloading Shapely-1.7.1.tar.gz (383 kB)\n",
            "\u001b[?25l\r\u001b[K     |▉                               | 10 kB 25.2 MB/s eta 0:00:01\r\u001b[K     |█▊                              | 20 kB 27.6 MB/s eta 0:00:01\r\u001b[K     |██▋                             | 30 kB 29.4 MB/s eta 0:00:01\r\u001b[K     |███▍                            | 40 kB 31.1 MB/s eta 0:00:01\r\u001b[K     |████▎                           | 51 kB 32.4 MB/s eta 0:00:01\r\u001b[K     |█████▏                          | 61 kB 35.0 MB/s eta 0:00:01\r\u001b[K     |██████                          | 71 kB 33.3 MB/s eta 0:00:01\r\u001b[K     |██████▉                         | 81 kB 34.9 MB/s eta 0:00:01\r\u001b[K     |███████▊                        | 92 kB 33.1 MB/s eta 0:00:01\r\u001b[K     |████████▌                       | 102 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |█████████▍                      | 112 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |██████████▎                     | 122 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |███████████▏                    | 133 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |████████████                    | 143 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |████████████▉                   | 153 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |█████████████▊                  | 163 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |██████████████▌                 | 174 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |███████████████▍                | 184 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |████████████████▎               | 194 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |█████████████████               | 204 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |██████████████████              | 215 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |██████████████████▉             | 225 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |███████████████████▊            | 235 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |████████████████████▌           | 245 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |█████████████████████▍          | 256 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |██████████████████████▎         | 266 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |███████████████████████         | 276 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |████████████████████████        | 286 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |████████████████████████▉       | 296 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |█████████████████████████▋      | 307 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |██████████████████████████▌     | 317 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |███████████████████████████▍    | 327 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |████████████████████████████▏   | 337 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |█████████████████████████████   | 348 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |██████████████████████████████  | 358 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |██████████████████████████████▉ | 368 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |███████████████████████████████▋| 378 kB 30.6 MB/s eta 0:00:01\r\u001b[K     |████████████████████████████████| 383 kB 30.6 MB/s \n",
            "\u001b[?25hSkipping wheel build for shapely, due to binaries being disabled for it.\n",
            "Installing collected packages: shapely\n",
            "    Running setup.py install for shapely ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "albumentations 0.1.12 requires imgaug<0.2.7,>=0.2.5, but you have imgaug 0.2.9 which is incompatible.\u001b[0m\n",
            "Successfully installed shapely-1.7.1\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "NtcnatpTYPad",
        "outputId": "bab2fe15-9284-4041-d3f0-2f9ba894bcf4"
      },
      "source": [
        "## cartopy is installed, sometimes NOT able to use in subsequent cells\n",
        "## this checks if we can use it\n",
        "\n",
        "import cartopy\n",
        "cartopy.__version__"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'0.19.0.post1'"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 496
        },
        "id": "wYYT8g9QYODb",
        "outputId": "75ba2cfe-0501-4c62-ac7f-7103db960e9c"
      },
      "source": [
        "# Has troubles with GEOS library!\n",
        "# Crashes with unknown reason!\n",
        "# Sometimes, err messages is:  Geometry must be a Point or LineString\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "import cartopy.crs as ccrs\n",
        "\n",
        "projn_lonlat = ccrs.PlateCarree()  # for graticule labeling\n",
        "projn_axis = ccrs.Mercator()       # for plot's axis; many to choose from\n",
        "\n",
        "fig = plt.figure(figsize=(10, 8))\n",
        "ax = fig.add_subplot(projection=projn_axis)\n",
        "ax.set_extent( [90, 115, 0, 25], crs=projn_lonlat )\n",
        "\n",
        "ax.coastlines()\n",
        "ax.gridlines(crs=projn_lonlat, draw_labels=True, lw=1.2, edgecolor=\"darkblue\", zorder=12)\n",
        "plt.show()\n"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j7XOgXERxF4M"
      },
      "source": [
        "help(ax.gridlines)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8iiwgSNlvUsz"
      },
      "source": [
        "End of file."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Dl3CXW7ruCNc"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}