weighted_mean

std.stats.weighted_mean · Level L0

Weighted mean with positive weights. Calls dot.

Σᵢ wᵢ·xᵢ / Σᵢ wᵢ

Signature

weighted_mean(x: f64[n], w: 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 a call to another library function; select it to open that function.

xf64[n]wf64[n]dotwxReduceSumswDividemmf64[]
  • input
  • operation
  • constant
  • call
  • output

Verification

  • Signature proven by NOVA’s shape solver, for every size.
  • Equal to the reference np.average(x, weights=w) in exact rational arithmetic, on all 40 test cases.
  • All 40 float64 results inside the running error bound; the closest uses 49% of it.
  • Interpreter and NumPy backend return bit-identical results.
Accuracy in detail
correctly rounded (the float64 nearest the exact value)
75%
bit-equal to the NumPy formula in float64
100%
largest error, in units in the last place
2.40

Identity

Calls
dot
Called by
—
sha256:a0d10179bcc5ffb43860e99e8cbc4a8bfec2e23ef636530d25259c0afd8257a8

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