pfb-network-connectivity

PFB Bicycle Network Connectivity

Getting Started

Requirements:

• Vagrant 1.8+
• VirtualBox 4.3+
• Ansible 2.0+

Run ./scripts/setup to install project dependencies and prepare the development environment. Then, SSH into the VM:

vagrant ssh

At this point, if you only intend to run the 'Bike Network Analysis', skip directly to Running the Analysis

To start the application containers:

./scripts/server

In order to use the API, you'll need to create a superuser in development by following the prompts:

./scripts/django-manage createsuperuser

Ports

Port	Service	Notes
9200	Nginx
9202	Gunicorn
9203	Django Runserver	Not running by default. Must be started manually via scripts/django-manage
9210	Webpack	Runs Angular webpack dev server
9211	LiveReload	Angular webpack dev server live reload
9212	Webpack	Runs Angular webpack prod server. Not running by default. Must start manually via ./scripts/console
9213	LiveReload	Angular webpack prod server live reload
9214	Postgresql	Allows direct connections to the database where an analysis run is stored

Scripts

Name	Description
setup	Bring up a dev VM, and perform initial installation steps
update	Re-build application Docker containers and run database migrations
server	Start the application containers
console	Start a bash shell on one of the running Docker containers
django-manage	Run a Django management command on the django container

Running the Analysis

Copy the 'neighborhood_boundary_02138.zip' file on fileshare and unzip to ./data/neighborhood_boundary.shp.

In this example, we configure the analysis to be run for Cambridge MA.

Run:

pushd pfb-analysis
docker build -t pfb .
popd

docker run \
    -e PFB_SHPFILE=/data/neighborhood_boundary.shp \
    -e PFB_STATE=ma \
    -e PFB_STATE_FIPS=25 \
    -e NB_INPUT_SRID=2249 \
    -e NB_BOUNDARY_BUFFER=11000 \
    -v /vagrant/data/:/data/ \
    pfb

This will take up to 1hr, so just let it work. Consider piping script output to a file and running in a screen/tmux session.

Re-running the analysis

If you want to run a different neighborhood, simply rerun the docker run command with the appropriate arguments, which are described below, in Importing other neighborhoods.

Importing other neighborhoods

Running the analysis requires a neighborhood shapefile polygon to run the analysis against.

To get started, place your neighborhood boundary shapefile, unzipped, in the project ./data directory.

You will also need to know the following:

• State abbrev that your neighborhood is found in, e.g. 'ma' for Massachussetts
• State FIPS code that your neighborhood is found in: https://www.census.gov/geo/reference/ansi_statetables.html
• SRID of your neighborhood boundary file (input)
• SRID you want to run the analysis in (output)

Now run:

docker run \
    -e PFB_SHPFILE=<path_to_boundary_shp> \
    -e PFB_STATE=<state abbrev> \
    -e PFB_STATE_FIPS=<state fips> \
    -e NB_INPUT_SRID=<input srid> \
    -e NB_BOUNDARY_BUFFER=<buffer distance in units of NB_OUTPUT_SRID> \
    -v /vagrant/data/:/data/ \
    pfb