docs/notebooks/0_Reqs_Install.ipynb

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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Notebook Overview and Installation Setup\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Authors: [Irene Farah](https://www.linkedin.com/in/imfarah/),  [Julia Koschinsky](https://www.linkedin.com/in/julia-koschinsky-657599b1/), [Logan Noel](https://www.linkedin.com/in/lmnoel/).  \n",
    "Contact: [Julia Koschinsky](mailto:jkoschinsky@uchicago.edu)  \n",
    "\n",
    "Research assistance of [Shiv Agrawal](http://simonlab.uchicago.edu/people/ShivAgrawal.html), [Caitlyn Tien](https://www.linkedin.com/in/caitlyn-tien-0b784b161/) and [Richard Lu](https://www.linkedin.com/in/richard-lu-576874155/) is gratefully acknowledged.\n",
    "\n",
    "Center for Spatial Data Science  \n",
    "University of Chicago  \n",
    "\n",
    "July 30, 2019\n",
    "\n",
    "---\n",
    "\n",
    "## Notebook Overview\n",
    "\n",
    "**The content of this notebook folder is organized as follows:**\n",
    "\n",
    "* [0_Reqs_Install.ipynb](./0_Reqs_Install.ipynb): Installation requirements to run the notebook demos  \n",
    "* [1_Simple_Test_Demo](.//1_Simple_Test_Demo.ipynb): Simple demo to test your setup installation works   \n",
    "\n",
    "\n",
    "The remaining notebooks walk through how to run the travel time matrix and spatial access metrics, including main functions and parameters:  \n",
    "\n",
    "* [2_Methods](./2_Methods.ipynb): Purpose and structure of the package + methodology for estimating travel time matrices and spatial access metrics  \n",
    "* [3_Travel_Time_Matrix.ipynb](./3_Travel_Time_Matrix.ipynb): How to run the travel time matrices using [p2p.py](./scripts/p2p.py) \n",
    "* [4_Access_Metrics.ipynb](./4_Access_Metrics.ipynb): How to run the access metrics (origin-based) using  [Models.py](./scripts/Models.py)  \n",
    "* [5_Coverage_Metrics.ipynb](./5_Coverage_Metrics.ipynb): How to run the coverage metrics (destination-based) using [Models.py](./spatial_access/Models.py)\n",
    "* [6_TSFCA.ipynb](./6_TSFCA.ipynb): How to run a two-stage floating catchment area model (origin-based) using [Models.py](./spatial_access/Models.py)\n",
    "\n",
    "\n",
    "The **data** folder contains the input_data needed to estimate the metrics under **sources** (for origins) and **destinations** (for destinations). Note that the capacity field in the destinations file is not real but only for demo purposes.  \n",
    "In output_data, the **matrices** folder stores the estimated symmetric and asymmetric matrices.  \n",
    "The **models** folder contains the results of the models' analyses.  \n",
    "Finally, **figures** stores the results of maps and plots calculated during the process. \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Installation Setup"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "--- \n",
    "The package is written in Python 3.6, C++ 11 and Cython by [Logan Noel](https://www.linkedin.com/in/lmnoel/). (Minimum Python version 3.5)  \n",
    "Currently, the only supported operating systems are MacOS and Ubuntu (if you don't have either, a guide for installing Ubuntu 16.04 LTS is in README.)\n",
    "\n",
    "We recommend setting up a separate anaconda environment for this package to prevent version conflicts between dependencies of this and other packages."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Note: Experienced users can download installation requirements directly in the terminal.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**For MacOS:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install Python3\n",
    "! brew install python3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install homebrew\n",
    "! /usr/bin/ruby -e \"$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install pip3\n",
    "! brew install pip3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install jupyter, jupyterlab, and jupyter hub\n",
    "! brew install jupyter\n",
    "! brew install jupyterlab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Clone the repository:\n",
    "! git clone https://github.com/jupyterhub/jupyterhub"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install spatial index package\n",
    "! brew install spatialindex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install spatial access package\n",
    "! pip3 install spatial_access"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install scipy package\n",
    "! brew install scipy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install geopy package\n",
    "! pip install geopy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install rtree package\n",
    "! pip install rtree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install geopandas package\n",
    "! conda install geopandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run setup.py to install all the packages\n",
    "! sudo python setup.py install"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install scipy package\n",
    "! brew install btree"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**In Ubuntu add:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "! sudo apt-get install libspatialindex-dev"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "! sudo apt-get install python-tk"
   ]
  }
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