{
    "cells": [
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "e0bf8629",
            "metadata": {},
            "source": [
                "# RA2CE: Do It Yourself"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "43bce1c4",
            "metadata": {},
            "source": [
                "Now let's do it yourself!\n",
                "\n",
                "First do your imports"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "id": "e67d001f",
            "metadata": {},
            "outputs": [],
            "source": [
                "import geopandas as gpd\n",
                "from pathlib import Path"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "0c5e8b7c",
            "metadata": {},
            "source": [
                "Create a folder for your project following the RA2CE folder structure. Then, apply some basic settings. Keep in mind that you will have to specify the path to your local machine yourself."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "id": "0d6562dd",
            "metadata": {},
            "outputs": [],
            "source": [
                "from ra2ce.ra2ce_handler import Ra2ceHandler #import the ra2cehandler to run ra2ce analyses\n",
                "\n",
                "_network_ini_name = \"your input goes here\" # set the name for the network.ini\n",
                "_analysis_ini_name = \"your input goes here\" # set the name for the analysis.ini"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "id": "3f003b62",
            "metadata": {},
            "outputs": [],
            "source": [
                "folder_dir = Path(r'') #Set the path to the folders where you will store your RA2CE project folders\n",
                "\n",
                "#PS: mind the folder structure!"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "6611234c",
            "metadata": {},
            "source": [
                "## Folder structure\n",
                "\n",
                "Make sure you have the correct folder structure and that the files you want to use are in the right folder. Otherwise, RA2CE will not be able to find the correct files to use."
            ]
        },
        {
            "attachments": {
                "image1.png": {
                    "image/png": "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"
                }
            },
            "cell_type": "markdown",
            "id": "1c9ba230",
            "metadata": {},
            "source": [
                "![image1.png](attachment:image1.png)"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "96633b35",
            "metadata": {},
            "source": [
                "## Configuring a road network from OSM"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "12d4f7de",
            "metadata": {},
            "source": [
                "First, we will need to specify the area for which you want to download your road network.\n",
                "Therefore, create a .geojson polgyon which you save in the network folder.\n",
                "Set the **CRS to WGS84 EPSG:4326** (this is also the standard geojson CRS)."
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "0afbb6d2",
            "metadata": {},
            "source": [
                "Specify the way in which you want to create your road network in the network.ini\n",
                "In this example we will use OSM download. \n",
                "Download the road network until **tertiary** roads, or if you want to use a larger area, only extract the motorways (also use the links!)"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "1cdfa8aa",
            "metadata": {},
            "source": [
                "> [project]<br>\n",
                "name = beira<br>\n",
                "<br>\n",
                "[network]<br>\n",
                "directed = False<br>\n",
                "**source = ...<br>**\n",
                "primary_file = None<br>\n",
                "diversion_file = None<br>\n",
                "file_id = rfid_c<br>\n",
                "**polygon = ...<br>**\n",
                "network_type = drive<br>\n",
                "**road_types = ...<br>**\n",
                "save_gpkg = True<br>\n",
                "<br>"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "70715c43",
            "metadata": {},
            "source": [
                "Now, we tell the program where to find our project folder (by specifying the path to the project folder). The network initialisation file (network.ini) is of interest. Now that we introduced a polygon of a region, we specified the road types and that we want an OSM download, RA2CE can perform this action for us. "
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "id": "4486021e",
            "metadata": {},
            "outputs": [],
            "source": [
                "root_dir = folder_dir / \"\" #name of the folder which you created for your ra2ce analysis\n",
                "\n",
                "network_ini = root_dir / _network_ini_name #we set the network_ini_name before, so we can use this now for the project\n",
                "assert network_ini.is_file() #check whether there is a network.ini"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "73d6f950",
            "metadata": {},
            "source": [
                "Run the RA2CE analyses by inputting the right arguments.<br>\n",
                "Do you need both the network and analysis ini?"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "id": "0b11b371",
            "metadata": {
                "scrolled": true
            },
            "outputs": [],
            "source": [
                "handler = Ra2ceHandler(network=..., analysis=...)\n",
                "handler.configure()"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "9d7c18d6",
            "metadata": {},
            "source": [
                "Now, inspect your created network!"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "id": "68fdce82",
            "metadata": {},
            "outputs": [],
            "source": [
                "#Set the path to YOUR output_graph folder to find the network/graph creation:\n",
                "path_output_graph = root_dir/\" \"/\" \""
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "9de42e13",
            "metadata": {},
            "source": [
                "Load in the file you are interested in (for example the edges or the nodes). <br>\n",
                "If you are more comfortable in a GIS, you can also load your data there.<br> \n",
                "Notice the different files in the output_graph folder. Inspect them all and see what their differences are."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "id": "546e31e6",
            "metadata": {},
            "outputs": [],
            "source": [
                "#your code goes here"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "551b8b78",
            "metadata": {},
            "source": [
                "Have you checked whether the network is nicely connected together? The disconnected islands plugin in QGIS is great help for this!"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "a92b918a",
            "metadata": {},
            "source": [
                "## Single redundancy test"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "5620ac4f",
            "metadata": {},
            "source": [
                "Now, let's perform a single redundancy test for your area of interest! Perform the analysis in the same folder as in which you created your graph. In this way, you can use the created road network for this analysis.<br>\n",
                "\n",
                "*You can also create a new folder and extract a network and perform the analysis from scratch if you want to get more advanced*"
            ]
        },
        {
            "attachments": {
                "image2.png": {
                    "image/png": "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"
                }
            },
            "cell_type": "markdown",
            "id": "a6364f20",
            "metadata": {},
            "source": [
                "![image2.png](attachment:image2.png)"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "5b1a507f",
            "metadata": {},
            "source": [
                "Put the following arguments in the analysis.ini"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "c9047579",
            "metadata": {},
            "source": [
                "> [project] <br>\n",
                "name = beira <br>\n",
                " <br>\n",
                "[analysis1] <br>\n",
                "name = beira_redundancy <br>\n",
                "analysis = single_link_redundancy <br>\n",
                "weighing = distance <br>\n",
                "save_gpkg = True <br>\n",
                "save_csv = True <br>"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "a8cba717",
            "metadata": {},
            "source": [
                "Run RA2CE "
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "id": "4b086c33",
            "metadata": {},
            "outputs": [],
            "source": [
                "analysis_ini = root_dir / _analysis_ini_name\n",
                "assert analysis_ini.is_file()\n",
                "handler = Ra2ceHandler(network=..., analysis=...)\n",
                "handler.configure()\n",
                "handler.run_analysis()"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "12774f27",
            "metadata": {},
            "source": [
                "Let's check your output!"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "id": "d9c98a5c",
            "metadata": {},
            "outputs": [],
            "source": [
                "analysis_output_folder = root_dir/\" \"/\" \" #specify path to output folder and the folder which holds the results"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "8f77caeb",
            "metadata": {},
            "source": [
                "Inspect the contents of the output"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "id": "943fad42",
            "metadata": {},
            "outputs": [],
            "source": [
                "#use gdf.head()"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "ddbd08ef",
            "metadata": {},
            "source": [
                "Read in the results. <br>\n",
                "What are the redundancy options for your network? "
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "id": "7f070454",
            "metadata": {},
            "outputs": [],
            "source": [
                "#Your code goes here"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "539b8425",
            "metadata": {},
            "source": [
                "What is the difference between the alternative route and the original route? <br>\n",
                "\n",
                "\n",
                "*(hint: you can use the column diff_dist)*"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "id": "12020e3b",
            "metadata": {},
            "outputs": [],
            "source": [
                "#Your code goes here"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "6630c8bf",
            "metadata": {},
            "source": [
                "## Level up: you're now an emergency responder"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "363f0bdb",
            "metadata": {},
            "source": [
                "For this analysis you need a flood map in your region. \n",
                "You can for example download one from the Global Flood Database or find a synthetic flood map for your area"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "e463d847",
            "metadata": {},
            "source": [
                "Put the flood map in the right folder for RA2CE and specify its parameters in the network.ini<br>\n",
                "Don't forget to specify the projection!"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "7e6bb154",
            "metadata": {},
            "source": [
                "Inspect your flood map here or in a GIS:"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "id": "b20e74a3",
            "metadata": {},
            "outputs": [],
            "source": [
                "#your code goes here"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "d8b9482c",
            "metadata": {},
            "source": [
                "Run RA2CE and perform the hazard overlay on the roads by running the network.ini file"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "id": "4a4f29cc",
            "metadata": {},
            "outputs": [],
            "source": [
                "#your code goes here"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "8e28867f",
            "metadata": {},
            "source": [
                "Inspect which roads are affected by the flood "
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "id": "bf6575a2",
            "metadata": {},
            "outputs": [],
            "source": [
                "#your code goes here"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "5dd6e6c7",
            "metadata": {},
            "source": [
                "Create origins and destinations data for your area of interest. Use the tips and requirements in the example material to create suitable files for RA2CE.\n",
                "\n",
                "*It is easiest to do the processing in a GIS*"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "83b3ee0a",
            "metadata": {},
            "source": [
                "Inspect your created files. Do they contain all the right columns and are they in the right projection?"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "id": "008bfdb6",
            "metadata": {},
            "outputs": [],
            "source": [
                "#inspect"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "66301b0e",
            "metadata": {},
            "source": [
                "Initialize the network.ini with your created origins and destinations and the right column names"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "63bedf88",
            "metadata": {},
            "source": [
                "Initialize the analysis.ini with the analysis of interest. Specify the right parameters"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "84523590",
            "metadata": {},
            "source": [
                "Now you are ready to run RA2CE again!"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "id": "4bf539f0",
            "metadata": {},
            "outputs": [],
            "source": [
                "#your code goes here"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "789c5e23",
            "metadata": {},
            "source": [
                "Inspect which origins still have access to one of their closest destinations:"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "id": "43bdd538",
            "metadata": {},
            "outputs": [],
            "source": [
                "#your code goes here"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "b0b44818",
            "metadata": {},
            "source": [
                "How many people do not have acces to their closest destination? \n",
                "\n",
                "(hint: there are also summary output files in your output folder)"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "id": "170581f9",
            "metadata": {},
            "source": []
        }
    ],
    "metadata": {
        "kernelspec": {
            "display_name": "ra2ce_env",
            "language": "python",
            "name": "python3"
        },
        "language_info": {
            "codemirror_mode": {
                "name": "ipython",
                "version": 3
            },
            "file_extension": ".py",
            "mimetype": "text/x-python",
            "name": "python",
            "nbconvert_exporter": "python",
            "pygments_lexer": "ipython3",
            "version": "3.10.11"
        }
    },
    "nbformat": 4,
    "nbformat_minor": 5
}