finite_optimize

std.optim.finite_optimize · Level L2

An optimization problem over a finite list of candidates with their objective values and a feasibility mask: whether any candidate is feasible; the minimum over the feasible set, the first feasible minimizer, and all the minimizers (an optimum may be attained more than once); and the maximum and the first maximizer. On a finite set these are its infimum and supremum. Conclusions hold for the listed set only.

min/max_{x feasible} f(x), argmin, argmax

Signature

finite_optimize(f: f64[n], feasible: f64[n]) → f64[], f64[], f64[], f64[n], f64[], f64[]

Structure

The function as NOVA stores it: one box per input, operation and output, and arrows that carry values. A double border marks another library function this one runs — called once, or by Scan once per element; select it to open that function.

input
operation
constant
call
output

Verification

Signature proven by NOVA’s shape solver, for every size.
Equal to the reference the feasible values in Python, first minimizer and maximizer in exact rational arithmetic, on all 40 test cases.
All 317 float64 results are exact: the error is zero.
Interpreter and NumPy backend return bit-identical results.
At float32 too: the 40 test cases rounded to float32, and 40 of them exact, with zero error.

Accuracy in detail

correctly rounded (the float64 nearest the exact value): 100%
bit-equal to the NumPy formula in float64: 97%
largest error, in units in the last place: 0

Identity

Calls

—

Called by

—

sha256:fc0f1ef5edaab41c5a41db76dc9ecbda821e12f1a66f94c3c75f27d3a62badfe

The semantic hash of the graph. It changes when the program changes, and never when only its documentation does.

Control handle

Symbol: Ω:std.optim.finite_optimize · Ω:finite_optimize
Pins: sha256:b81130c40e744a80da5e2a76f9ef3d94e9b65746acc8b53ce870facb82ddb1a0this graph alone
Evidence: sha256:70e0a359f46d418df3b0469ed5ada5c5152cb48442ee61f879ca2e7296f5108bthe hash of its verification record
Needs: no capability: a pure function

Through NOVA’s control layer, the symbol launches this function only while the program still matches what it pins: a change to this graph, or to any graph it reaches, needs a migration first.