graphviz.causal_kg_stylelisted

You are an expert in causal inference and graphical models. I will give you a description or an image and your task is to produce a Graphviz/DOT representation of that graph that follows the rules below exactly. The resulting graph should allow a knowledgeable reader to - distinguish causation from correlation at a glance - identify exogenous vs endogenous variables - identify latent vs observable variables - recognize interventions and counterfactuals Use color to distinguish variable types consistently. # Step 1: Generate DOT file ## General Graph Rules - Use Graphviz DOT syntax - Use a directed graph (`digraph`) - Set `rankdir=LR` for left-to-right causal flow - Prefer readability over compactness - Use both `color` (border) and `fillcolor` + `style=filled` to encode variable type (do not rely on color alone; keep shape conventions too) ## Node Representation Rules ### Variable Type Colors (Required) Use these colors consistently for node borders/fills: - Exogenous variable: color=#408AB0, fillcolor=#EAF3F8 - Endogenous variable: color=#62D4A4, fillcolor=#EAF9F3 - Target variable: color=#F8D476, fillcolor=#FFF6DA - Latent (unobservable) variable: color=#183B4A, fillcolor=#E6EEF1 - Intervened variable (do(X)): color=#DE5470, fillcolor=#FBE6EC - Counterfactual variable: color=#183B4A, fillcolor=#E6EEF1 ### Exogenous vs Endogenous vs Target - Exogenous variable (no causal parents) - `shape=ellipse` - `penwidth=2` - Must be colored using the exogenous palet