Getting Started

Installation

using Pkg
Pkg.add("CausalDynamics")

Julia 1.12+ is required. For the tip of main before a new version is on General, use Pkg.add(url="https://github.com/SimonAB/CausalDynamics.jl.git").

Causal graphs

using CausalDynamics, Graphs, DAGMakie, CairoMakie

g = DiGraph(3)
add_edge!(g, 1, 2)  # Z → X
add_edge!(g, 1, 3)  # Z → Y
add_edge!(g, 2, 3)  # X → Y
g

{3, 3} directed simple Int64 graph

d-separation

d_separated(g, 2, 3, [1])  # true (Z blocks the path)

false

Adjustment sets

adj_set = backdoor_adjustment_set(g, 2, 3)  # Set([1])

Set{Int64} with 1 element:
  1

Plotting (optional)

plot_causal_graph and related façades require using DAGMakie so the package extension loads. Layout and styling conventions are documented in the DAGMakie user guide.

fig = plot_backdoor_paths(g, 2, 3; node_labels = ["Z", "X", "Y"])
fig

Highlight an explicit adjustment set (here {Z}):

fig = plot_with_adjustment_set(g, 2, 3, [1]; node_labels = ["Z", "X", "Y"])
fig

SCM simulation and intervention

equations = Dict{Int, Function}(
    1 => (u,) -> u,
    2 => (z, u) -> z + u,
    3 => (x, u) -> 2x + u,
)
scm = GraphSCM(g, equations, Set{Int}())
U = Dict(1 => 1.0, 2 => 0.5, 3 => -0.3)
y_factual = simulate_scm(scm, U)
y_do = simulate_scm(apply_intervention(scm, do_intervention(2, 10.0)), U)