function
causalis.scenarios.multi_unconfoundedness.refutation.overlap.overlap_plot.plot_m_overlapplot_m_overlap
Multi-treatment overlap plot for pairwise conditional propensity scores.
For each comparison baseline (default 0) vs k, this plots
P(D=k | X, D in {baseline, k}) = m_k(X) / (m_baseline(X) + m_k(X))
on the observed pair sample D in {baseline, k}, comparing:
units with D=k (treated for the pair),
units with D=baseline (control for the pair).
Parameters:
diag.d: (n, K) one-hot
diag.m_hat / diag.m_hat_raw: (n, K) propensity
treatment_idx:
None -> plot all k != baseline_idx (multi-panel)
int -> plot one comparison
list[int] -> plot selected comparisons
ax: supported only for a single comparison (exactly one k)
Returns matplotlib.figure.Figure.
Canonical target
causalis.scenarios.multi_unconfoundedness.refutation.overlap.overlap_plot.plot_m_overlap