COMPUTE THE MEAN SQUARE ERROR BETWEEN TWO CURVES

Computes the Mean Squared Error (MSE) between two curves by resampling both onto a common grid before comparison. Use this worker to quantify the pointwise deviation between a candidate curve and a reference curve, e.g. for simulation-vs-test correlation or curve-fitting quality checks.

When to use

Classification: process.

Tagged: correlation, curve_comparison, digitize, mean_square_error, mse, r2, resampling.

Inputs

Label ID Type Default Required Description
Curve 1 curve1 vector   Candidate curve (X-Y vector) whose deviation from Curve 2 is being measured; accepts multiple curves in batch mode.
Curve 2 curve2 vector   Reference curve (X-Y vector) against which Curve 1 is compared; both curves will be resampled onto the same grid before MSE is calculated.
Digitize Points numberofpointstodigitize integer 100   Number of evenly-spaced points used to resample both curves onto a common grid before computing MSE; default is 100 — increase for higher-resolution curves or decrease for speed.

Outputs

Label ID Type Description
curves_r2_output_1 curves_r2_output_1 scalar Scalar MSE value representing the mean of the squared pointwise differences between Curve 1 and Curve 2 on the resampled grid (dimensionless ratio of the curve’s Y-unit squared).

Disciplines

  • data.correlation
  • data.curve.pair
  • data.statistics

Runnable example

A runnable example is registered for this worker. Open the example workflow on the d3VIEW canvas: /api/workflow/example?id=curves_r2


Auto-generated from transformation schema. Worker id: curves_r2. Schema hash: 02ec7b705af7. Hand-curated docs in workerexamples/ override this page when present.