\set ECHO none rv_normal|rv_exponential|rv_latent normal(2.5, 0.5)|exponential(0.7)|normal(normal(0, 1), 1) (1 row) a_plus|a_times|a_minus|a_div|a_neg normal(0, 1) + uniform(0, 1)|normal(0, 1) * uniform(0, 1)|normal(0, 1) - uniform(0, 1)|normal(0, 1) / 2|-normal(0, 1) (1 row) a_pow|a_ln|a_exp uniform(1, 2) ^ 2|ln(uniform(1, 2))|exp(normal(0, 1)) (1 row) a_max|a_min max(uniform(0, 1), uniform(2, 3))|min(uniform(0, 1), uniform(2, 3)) (1 row) m_bernoulli|m_categorical ? normal(0, 1) : normal(5, 1)|categorical(; 0.25: 1, 0.75: 2) (1 row) observation observe(normal(normal(0, 1), 1) = 2.5) (1 row) conditioned uniform(0, 1) | [uniform(0, 1) ≤ uniform(0, 1)] (1 row) guarded case([uniform(0, 1) ≥ uniform(0, 1)] → uniform(0, 1); else uniform(0, 1)) (1 row) agg_sum|agg_avg|agg_percentile normal(1, 1) + normal(2, 1) + normal(3, 1)|(normal(1, 1) + normal(2, 1) + normal(3, 1)) / 3|percentile(0.5; [1] normal(1, 1), [1] normal(2, 1), [1] normal(3, 1)) (1 row) add_provenance (1 row) create_provenance_mapping (1 row) remove_provenance (1 row) unmapped|partially_mapped|shape_ok|distinct_leaves |1 ⊗ |t|t (1 row) ERROR: ProvSQL: provenance_evaluate_compiled: This semiring does not support rv gates: a continuous distribution is not a semiring value. Query a random-variable token through the measure surface (expected / variance / quantile / support / sample), or use the formula pseudo-semiring for a symbolic rendering. remove_provenance (1 row)