{ "slug": "peak-detector", "name": "gizza-ai/peak-detector", "version": "0.1.0", "title": "Peak Detector — Find Local Maxima and Minima in a Signal — gizza.ai", "description": "Paste a 1-D signal and find its peaks and valleys, with prominence, height, distance and width filters. Free, runs in your browser.", "tags": [ "peak detector", "find peaks online", "local maxima finder", "local minima finder", "signal peak finder", "prominence peak detection", "find peaks in data", "valley detector", "peak finding tool" ], "category": "audio", "urls": { "page": "https://gizza.ai/tools/peak-detector/", "markdown": "https://gizza.ai/tools/peak-detector/index.md", "descriptor": "https://gizza.ai/tools/peak-detector/tool.json", "deep_link_example": "https://gizza.ai/tools/peak-detector/?data=0%2C%201%2C%200%2C%203%2C%200%2C%202%2C%200&mode=maxima&separator=auto&smooth=0&min_value=e.g.%205&max_value=e.g.%20100&threshold=0&min_distance=0&min_prominence=0&min_width=0&rel_height=0.5&max_peaks=0&sort_by=position&format=text" }, "cli": "gizza tool peak-detector \"0, 1, 0, 3, 0, 2, 0\"", "tool": { "description": "Find the local maxima (peaks) and local minima (valleys) in a pasted 1-D signal and report each one's 0-based index, value, prominence and width. Candidates can be filtered by amplitude band (min_value/max_value), vertical drop to both immediate neighbours (threshold), spacing between peaks (min_distance), prominence (min_prominence) and width (min_width), evaluated in that documented order; an optional moving-average window (smooth) suppresses noise before detection. Flat-topped peaks collapse to the middle sample and the first and last sample are never peaks. Results can be sorted by position, prominence or value and capped with max_peaks. Accepts comma, space, tab, newline, semicolon or pipe separated values, decimals, negatives and scientific notation, up to 20000 samples. Text, JSON or CSV output. Report-only — it never changes the data.", "parameters": { "additionalProperties": false, "properties": { "data": { "description": "The 1-D signal to analyse, as pasted text: one number per sample, in order. Values may be separated by commas, spaces, tabs, newlines, semicolons or pipes (see separator) — for example `0, 1, 0, 3, 0, 2, 0`. Integers, decimals, negatives and scientific notation (`1e6`) are all accepted; non-numeric tokens such as a pasted column header are skipped and counted. Up to 20000 samples per run. Indices in the report are 0-based, so the first sample is index 0.", "type": "string" }, "format": { "default": "text", "description": "Output format. `text` (default) is the readable report: a peak table plus the highest peak, deepest valley, mean spacing, signal statistics and the filters in force. `json` returns the full report object, including each peak's bases and interpolated width endpoints. `csv` returns just the peak table with a header row, ready to paste into a spreadsheet.", "enum": [ "text", "json", "csv" ], "type": "string" }, "max_peaks": { "default": 0, "description": "Report at most this many peaks, applied AFTER sorting, so with `sort_by=prominence` it gives you the N most significant peaks. 0 (default) reports every peak that passed the filters. The report always states how many peaks matched in total, so you can see what was withheld.", "maximum": 10000, "minimum": 0, "type": "integer" }, "max_value": { "default": "", "description": "Amplitude ceiling: ignore any extremum whose value is above this number. Blank (default) means no ceiling. Combined with min_value it forms a band, so you can isolate mid-height features and drop a saturating spike — for example `min_value=5` with `max_value=7`. min_value above max_value is rejected, since no value could pass.", "type": "string" }, "min_distance": { "default": 0, "description": "Minimum spacing, in samples, between reported peaks of the same kind. 0 (default) turns it off. Peaks are kept tallest-first: the most extreme peak survives and every peak closer than this many samples to an already-kept one is dropped. Use it to report one peak per event when a single event produces a cluster of samples above the surroundings.", "maximum": 20000, "minimum": 0, "type": "integer" }, "min_prominence": { "default": 0.0, "description": "Minimum prominence: how far the signal must fall on BOTH sides of the peak before it rises back above that peak (or reaches an end of the data). 0 (default) turns it off. This is the standard \"is this a real peak or just a bump on the side of a bigger one\" test, and is usually the most effective single filter on noisy data — try a few percent of the signal's range.", "minimum": 0, "type": "number" }, "min_value": { "default": "", "description": "Amplitude floor: ignore any extremum whose value is below this number. Blank (default) means no floor. Applied to the value as you see it, so in `minima` mode it still means \"no lower than this\". Use it to skip the baseline wiggle of a signal whose real events all sit above a known level — for example `min_value=5` on a 0-10 signal.", "type": "string" }, "min_width": { "default": 0.0, "description": "Minimum peak width in samples, measured across the peak at rel_height of its prominence with linear interpolation between samples. 0 (default) turns it off. Use it to reject a one-sample spike (width near 1) while keeping broad, genuine features — the complement of min_prominence, which judges height rather than breadth.", "minimum": 0, "type": "number" }, "mode": { "default": "maxima", "description": "Which extrema to find. `maxima` (default) reports peaks — samples higher than both neighbours. `minima` reports valleys — samples lower than both neighbours; every measurement (prominence, width) is then the mirror image, measured on the way down. `both` reports peaks and valleys in one table with a `kind` column.", "enum": [ "maxima", "minima", "both" ], "type": "string" }, "rel_height": { "default": 0.5, "description": "Where the width is measured, as a fraction of the peak's prominence, 0-1 (default 0.5 = half prominence, the usual convention and the same reference point as a FWHM measurement). 1 measures right down at the peak's base, giving the widest number; a small value measures just below the tip. It changes the reported `width` and therefore what min_width rejects.", "maximum": 1, "minimum": 0, "type": "number" }, "separator": { "default": "auto", "description": "How the samples are separated. `auto` (default) splits on any whitespace, comma, semicolon or pipe, which handles most pasted columns and CSV rows. Pick an explicit separator for ambiguous data — for example `newline` for one value per line, or `tab` for a column copied out of a spreadsheet. Blank entries are skipped.", "enum": [ "auto", "comma", "newline", "space", "semicolon", "tab", "pipe" ], "type": "string" }, "smooth": { "default": 0, "description": "Moving-average window, in samples, applied BEFORE detection to stop noise registering as peaks. 0 or 1 (default 0) means no smoothing. Must be an odd number so the window stays centred on its sample — try 3, 5 or 7 for lightly noisy data, larger for very noisy data. Reported values are the smoothed ones; the window shrinks at the two ends so no artificial ramp is introduced.", "maximum": 501, "minimum": 0, "type": "integer" }, "sort_by": { "default": "position", "description": "Row order in the report. `position` (default) keeps the peaks in the order they occur in the signal — best for reading a trace end to end. `prominence` puts the most significant peaks first, and `value` the highest-valued ones; pair either with max_peaks to get a top-N list.", "enum": [ "position", "prominence", "value" ], "type": "string" }, "threshold": { "default": 0.0, "description": "Minimum vertical drop from the peak to BOTH of its immediate neighbours, in the signal's own units. 0 (default) turns the filter off. This is a purely local test — it rejects a peak that barely clears the samples touching it, without looking any further along the signal. Use min_prominence instead when you care how the peak compares to the wider curve.", "minimum": 0, "type": "number" } }, "required": [ "data" ], "type": "object" } } }