COMPUTE THE MEAN SQUARE ERROR BETWEEN TWO CURVES

Computes the Mean Square Error (MSE) between two XY curves, optionally resampling both to a common grid and normalizing x-values before comparison. Use this worker to quantify the pointwise difference between a simulation curve and a reference curve.

When to use

Classification: process.

Tagged: curve_comparison, digitize, mean_square_error, mse, normalize, similarity.

Inputs

Label ID Type Default Required Description
Curve 1 curve1 vector   First input curve (the test/simulation curve) supplied as an XY vector; compared against curve2 to produce the MSE.
Curve 2 curve2 vector   Second input curve (the reference curve) supplied as an XY vector; used as the baseline against which curve1 is evaluated.
Digitize Points numberofpointstodigitize integer 100   Number of uniformly spaced points to which both curves are resampled before computing MSE; default is 100. Increase for higher-resolution comparison, leave at default for most use cases.
X-Value Type normalize string yes   Whether to normalize the x-axis values before comparison (‘yes’ maps x to a common relative scale, ‘no’ uses raw x values); default is ‘yes’. Set to ‘no’ when both curves already share the same physical x-axis units and range.

Outputs

Label ID Type Description
curves_mse_output_1 curves_mse_output_1 scalar Scalar MSE value representing the mean of squared pointwise differences between the two resampled curves; dimensionless if normalization is applied, otherwise in the squared units of the y-axis.

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_mse


Auto-generated from transformation schema. Worker id: curves_mse. Schema hash: e40f4d6a7d81. Hand-curated docs in workerexamples/ override this page when present.