Getting Started


This section outlines how ADRIA may be used to arrive at a select range of possible pathways that are robust to possible future conditions.

Create a directory for your project, and start Julia inside that directory:

$ julia --project=.

ADRIA may be installed through the package manager or from the github repository (for the most recent development version).

julia> ]add ADRIA

# OR, to install the latest development version:

julia> ]add

Similarly, ADRIA can be updated as new releases are made:

julia> ]up ADRIA

If desired, you can create a config.toml file inside your project directory. This is optional, and the assumed default values are shown below:

num_cores = 2     # No. of cores to use. Values <= 0 will use all available cores.
threshold = 1e-8  # Result values below this will be set to 0.0 (to save disk space)
debug = false     # Disable multi-processing to allow error messages to be shown

output_dir = "./Outputs"  # Change this to point to where you want to store results

This config.toml file is specific to your computer and project. It should not be committed to version control.


ADRIA uses an on-disk data store to hold results from model runs. Setting output_dir to a directory on an SSD (Solid State Drive) will maximize performance.

To setup ADRIA for development, see the Development setup page.

Quick Start

A common workflow would be the following:

Start Julia from the project directory:

$ julia --project=.

Load data for a spatial domain. See Loading a Domain for more details:

using ADRIA

dom = ADRIA.load_domain("path to domain data package")

Generate scenarios based on available environmental data layers and model parameters. The number of scenarios shoud be a power of two. See Generating scenarios for more details:

num_scenarios = 128
scens = ADRIA.sample(dom, num_scenarios)

Run sampled scenarios for one or more RCPs. Be aware that this may take a while:

rcp_45 = "45"
rs = ADRIA.run_scenarios(dom, scens, rcp_45)

Or run scenarios across several RCPs:

rcps = ["45", "60", "85"]
rs = ADRIA.run_scenarios(dom, scens, rcps)

It is also possible to load previously run scenarios. See Running scenarios for more details:

rs = ADRIA.load_results("path to results")

Extract some metric for analysis (e.g., the total absolute cover for each site and timestep):

s_tc = ADRIA.metrics.scenario_total_cover(rs)

Use the visualization tools to plot the results. The Makie package ecosystem is used for producing plots:

using GLMakie, GeoMakie, GraphMakie

# Plot a quick scenario overview
fig = ADRIA.viz.scenarios(rs, s_tc; axis_opts=Dict(:ylabel=>"Absolute Cover"))
save("path_to_save_figure", fig)

See Analysis for further examples of analysis and plots.