RvHistogram.cpp File Reference

SQL function provsql.rv_histogram(token, bins). More...

#include "postgres.h"
#include "fmgr.h"
#include "utils/jsonb.h"
#include "utils/fmgrprotos.h"
#include "utils/uuid.h"
#include "provsql_utils.h"
#include "provsql_error.h"
#include "CircuitFromMMap.h"
#include "Expectation.h"
#include "GenericCircuit.h"
#include "MonteCarloSampler.h"
#include "RandomVariable.h"
#include "RangeCheck.h"
#include "provsql_utils_cpp.h"
#include <algorithm>
#include <cmath>
#include <iomanip>
#include <optional>
#include <sstream>
#include <string>
#include <tuple>
#include <utility>
#include <vector>

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Functions
Datum	rv_histogram (PG_FUNCTION_ARGS)

Detailed Description

SQL function provsql.rv_histogram(token, bins).

Returns an empirical histogram of the scalar values produced by the sub-circuit rooted at token, binned into bins equal-width intervals between the observed minimum and maximum. The sample count is taken from provsql.rv_mc_samples; pinning provsql.monte_carlo_seed makes the result reproducible.

Output: a jsonb array of objects {bin_lo, bin_hi, count}, one per non-empty bin (zero-count bins are still emitted so the client can draw a flat baseline). Returning jsonb rather than SETOF record keeps the C++ side free of SRF / FuncCallContext mechanics and matches the pattern used by simplified_circuit_subgraph.

Accepted root gate types:

• gate_value: degenerate Dirac at the constant. Emits a single bin at (v, v) with count equal to the would-be sample count, so the client can normalise to a probability mass without a special case.
• gate_rv: sampled from the leaf's distribution.
• gate_arith: sampled by recursing through the arithmetic DAG, reusing gate_rv draws within an iteration so shared leaves are correctly correlated.
• gate_mixture: sampled by recursing through the mixture's Bernoulli (gate_input) wire and the selected scalar branch, reusing per-iteration caches so a shared p_token across the circuit produces coupled draws.
• gate_agg: sampled per Monte Carlo iteration by walking the gate_semimod children, applying their Boolean filter, and finalising the chosen aggregator (COUNT / SUM / AVG / MIN / MAX). Same machinery probability evaluation uses for HAVING under MC; see MonteCarloSampler::evalScalar.
• gate_semimod: a bare per-row contribution interpreted as value · 1_{k fires}, i.e. zero in worlds where the row's Boolean filter does not fire and the scalar value otherwise.

Any other gate type still raises: Boolean-valued gates fall under probability_evaluate, and unsupported scalar shapes (delta…) have no defined sampling semantics.

Definition in file RvHistogram.cpp.

Function Documentation

rv_histogram()

Datum rv_histogram

(

PG_FUNCTION_ARGS

)

Definition at line 88 of file RvHistogram.cpp.

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