GET R2 FIT TIME-HISTORY

Computes a rolling polynomial-fit R² time-history for one or more input curves by sliding a fixed-width window along each curve. Use this worker to quantify how linearly (or how well a chosen polynomial order) a signal behaves locally over time.

When to use

Classification: process.

Tagged: curve_quality, goodness_of_fit, linear_fit, polynomial_fit, r2, rolling_window, time_history.

Inputs

Label ID Type Default Required Description
Base Curves base_curves vector   One or more input time-history curves (x–y vector pairs) on which the rolling R² fit will be computed; accepts multiple curves simultaneously.
Window Size window_size string 0.01   Width of the sliding window in the same x-axis units as the input curves (default 0.01); controls the local interval over which each polynomial fit is evaluated — smaller values capture faster local changes.
Number Of Digitize Points num_dig string 1000   Number of evenly-spaced digitisation points used to re-sample each curve before fitting (default 1000); the effective value is max(original point count, this value) to ensure sufficient resolution.
Order order string 1   Polynomial order used for the local least-squares fit when computing R² (default 1 = linear); increase to 2 or higher to measure goodness-of-fit for nonlinear trends.

Outputs

Label ID Type Description
R2 histories curves_get_linear_fit_output_1 vector One R² time-history curve per input curve, where each y-value (0–1) represents the coefficient of determination of the polynomial fit within the sliding window centred at that x-position.

Disciplines

  • data.curve.transform
  • data.signal_processing
  • 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_get_linear_fit_r2


Auto-generated from transformation schema. Worker id: curves_get_linear_fit_r2. Schema hash: a29625572b16. Hand-curated docs in workerexamples/ override this page when present.