- COMPUTE THE CROSS CORRELATION OF TWO CURVES USING C1XC2 *
Computes the cross-correlation of two input curves (c1×c2) to measure their similarity as a function of lag. Use this worker to quantify the relationship or time-shift between two time-history signals.
When to use¶
Classification: process.
Tagged: c1xc2, cross_correlation, curve, digitize, lag, signal, similarity, sync.
Inputs¶
| Label | ID | Type | Default | Required | Description |
|---|---|---|---|---|---|
| Curve 1 | curve1 | vector | — | Base (reference) curve — a time-history vector (e.g., force vs. time); supports multiple curves when batching. | |
| Curve 2 | curve2 | vector | — | Second curve to correlate against Curve 1 — must share compatible x-axis units and range for meaningful results. | |
| Return Type | sync_type | float | none | Pre-processing applied to both curves before correlation: ‘none’ uses raw data as-is, ‘unify’ resamples both curves to a common x-axis, ‘digitize’ resamples to a fixed number of points (set via Digitize Points); default is ‘none’. | |
| Digitize Points | numberof_pointsto_digitize | scalar | 0 | Number of evenly spaced points to resample each curve to when sync_type is ‘digitize’; ignored for other sync types; default is 0 (falls back to 100 in code). |
Outputs¶
| Label | ID | Type | Description |
|---|---|---|---|
| curves_simple_cross_correlation_output_1 | curves_simple_cross_correlation_output_1 | scalar | Resulting cross-correlation curve (or scalar peak value) produced by the c1×c2 operation, representing the correlation magnitude as a function of lag between the two input curves. |
Disciplines¶
- data.curve.pair
- data.signal_processing
Runnable example¶
A runnable example is registered for this worker. Open the example workflow on the d3VIEW canvas: /api/workflow/example?id=curves_simple_cross_correlation
Auto-generated from transformation schema. Worker id: curves_simple_cross_correlation. Schema hash: 0ddab6e6bb87. Hand-curated docs in workerexamples/ override this page when present.