lagrange_projection

std.optim.lagrange_projection · Level L0

The Lagrange condition for minimizing ‖x − c‖² subject to one linear constraint g·x = h (g ≠ 0): the minimizer x* = c − ((g·c − h)/‖g‖²)·g, the multiplier λ with ∇f(x*) = λ·∇(g·x) (this sign convention), and the residuals of stationarity, 2(x* − c) − λg, and of feasibility, g·x* − h, both 0. The condition is necessary, not sufficient, in general; here the problem is convex, so x* is the global minimizer. It is not the KKT condition for inequalities.

x* = c − ((g·c − h)/‖g‖²) g, 2(x* − c) = λ g

Signature

lagrange_projection(c: f64[n], g: f64[n], h: f64[]) → f64[n], f64[], f64[n], 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.

cf64[n]gf64[n]hf64[]dotggdotgcSubtractviol-2.0DividetMultiplylamMultiplytgIdentitylambdaSubtractxMultiplylgIdentityx_starSubtractxc2.0dotgxMultiplygradfSubtractfeasibilitySubtractstationaritylambdaf64[]x_starf64[n]stationarityf64[n]feasibilityf64[]
  • input
  • operation
  • constant
  • call
  • output

Verification

  • Signature proven by NOVA’s shape solver, for every size.
  • Equal to the reference the projection formula in exact arithmetic in exact rational arithmetic, on all 40 test cases.
  • All 388 float64 results inside the running error bound; the closest uses 87% of it.
  • Interpreter and NumPy backend return bit-identical results.
  • At float32 too: the 40 test cases rounded to float32, and 40 of them inside the running error bound at u = 2⁻²⁴; the closest uses 69% of it.
Accuracy in detail
correctly rounded (the float64 nearest the exact value)
64%
bit-equal to the NumPy formula in float64
84%
largest error, in units in the last place
7.7e+3

Large ulp counts appear where a result is tiny next to the numbers it is computed from (after cancellation, for example), so one unit in the last place is tiny too; the absolute error is still inside the bound. Results within their own error of zero are not counted.

Identity

Calls
Called by
—
sha256:27c492c10d08dd10f07f3eed016a9eb5683fd59456a2b7ea882d7412d94faf67

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.lagrange_projection · Ω:lagrange_projection
Pins
sha256:d13b78fcb1038fb4406d56bc4c7817659f193e09be01ad5c2723ff4340e42a38this graph and the 1 it reaches through calls
Evidence
sha256:bc6dd0fc42742b43da16dad33a647105dd66dcafb867894767edb7ccdff382b6the 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.

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