REMOVE THE SPIKES¶
Removes transient spikes from a curve by scanning a sliding X-axis window and replacing samples that exceed a defined amplitude threshold relative to surrounding data. Iterative passes can be applied for stubborn or overlapping spikes. Use this worker to clean sensor noise or numerical artifacts before downstream signal analysis.
When to use¶
Classification: process.
Tagged: curve_cleaning, iterative, noise_removal, signal_conditioning, spike_removal, threshold, x_window.
Inputs¶
| Label | ID | Type | Default | Required | Description |
|---|---|---|---|---|---|
| Curve In | curve_in | vector | — | Input curve (X/Y vector) from which spikes will be removed; accepts any time-history or signal curve. | |
| Min Max X-window | min_max_duration | string | 50 | Width of the sliding X-axis window (in X-axis units, e.g. ms) used to identify spike extents; any spike fully contained within this window is a candidate for removal — default is 50. | |
| Spike Start Value | spike_start | string | -0.01:0.01 | Y-value range (colon-separated, e.g. ‘-0.01:0.01’) that defines the near-zero baseline band; a spike is considered to start and end within this range — default is ‘-0.01:0.01’. | |
| Threshold Value | threshold_value | string | 10% | Amplitude threshold above which a deviation is classified as a spike; can be an absolute value or a percentage of the local signal range (e.g. ‘10%’) — default is ‘10%’. | |
| Number Of Iterations | num_iterations | string | 1 | Number of spike-removal passes to apply sequentially; increase beyond the default of 1 when multiple overlapping or closely spaced spikes are present. |
Outputs¶
| Label | ID | Type | Description |
|---|---|---|---|
| curve_remove_spikes_output_1 | curve_remove_spikes_output_1 | vector | Cleaned output curve with detected spikes replaced by interpolated values, retaining the original X-axis sampling of the input curve. |
Disciplines¶
- data.curve.transform
- 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=curve_remove_spikes
Auto-generated from transformation schema. Worker id: curve_remove_spikes. Schema hash: 8431bee2435a. Hand-curated docs in workerexamples/ override this page when present.