General-purpose utilities for data processing and formatting. These are available as standalone functions or via chart.analysis.

Requirement

While many of these are standalone utilities, the recommended way to use them within a chart is to load the PluginAnalysis.

calculateStats

Calculate basic statistics for a dataset.

import { calculateStats } from 'velo-plot/scientific'

// Use standalone
const stats = calculateStats(yData)

// Or via chart (if PluginAnalysis is loaded)
const stats = chart.analysis.calculateStats(yData)

Returns

interface DataStats {
  min: number     // Minimum value
  max: number     // Maximum value
  mean: number    // Arithmetic mean
  stdDev: number  // Standard deviation
  count: number   // Number of points
}

Example

import { calculateStats } from 'velo-plot/scientific'

const stats = calculateStats(yData)

console.log(`Count: ${stats.count}`)
console.log(`Range: ${stats.min.toFixed(4)} to ${stats.max.toFixed(4)}`)
console.log(`Mean: ${stats.mean.toFixed(4)}`)
console.log(`Std Dev: ${stats.stdDev.toFixed(4)}`)

---

movingAverage

Apply moving average smoothing to reduce noise.

function movingAverage(
  data: Float32Array | Float64Array | number[],
  windowSize: number
): Float32Array

Parameters

Parameter	Type	Description
data	Float32Array | Float64Array | number[]	Input data
windowSize	number	Number of points to average (should be odd)

Example

import { movingAverage } from 'velo-plot/scientific'

// Smooth noisy data with 5-point moving average
const smoothed = movingAverage(noisyData, 5)

chart.addSeries({
  id: 'smoothed',
  data: { x: xData, y: smoothed },
  style: { color: '#00ff88' },
})

---

downsampleLTTB

Reduce point count using the Largest Triangle Three Buckets (LTTB) algorithm. Preserves visual shape while dramatically reducing data size.

function downsampleLTTB(
  x: Float32Array | Float64Array,
  y: Float32Array | Float64Array,
  targetPoints: number
): { x: Float32Array; y: Float32Array }

Parameters

Parameter	Type	Description
x	Float32Array | Float64Array	X values
y	Float32Array | Float64Array	Y values
targetPoints	number	Desired number of output points

Example

import { downsampleLTTB } from 'velo-plot/scientific'

// Reduce 10 million points to 10,000 for display
const { x: sampledX, y: sampledY } = downsampleLTTB(
  originalX,
  originalY,
  10000
)

chart.addSeries({
  id: 'data',
  data: { x: sampledX, y: sampledY },
})

When to Use

• Displaying very large datasets (1M+ points)
• Reducing data transfer size
• Improving render performance
• Creating thumbnails or previews

---

validateData

Check for invalid values (NaN, Infinity, -Infinity).

function validateData(
  data: Float32Array | Float64Array | number[]
): ValidationResult

Returns

interface ValidationResult {
  valid: boolean          // True if all values are finite
  invalidCount: number    // Number of invalid values
  firstInvalidIndex: number  // Index of first invalid (-1 if none)
}

Example

import { validateData } from 'velo-plot/scientific'

const result = validateData(yData)

if (!result.valid) {
  console.warn(`Found ${result.invalidCount} invalid values`)
  console.warn(`First invalid at index ${result.firstInvalidIndex}`)
}

---

formatWithPrefix

Format numbers with automatic SI prefix (k, M, G, m, µ, n, p).

function formatWithPrefix(
  value: number,
  unit: string,
  decimals?: number
): string

Parameters

Parameter	Type	Default	Description
value	number	required	Value to format
unit	string	required	Unit symbol (V, A, m, s, etc.)
decimals	number	2	Decimal places

Example

import { formatWithPrefix } from 'velo-plot/scientific'

formatWithPrefix(0.000001, 'A')    // "1.00 µA"
formatWithPrefix(0.5, 'V')         // "500.00 mV"
formatWithPrefix(1500, 'm')        // "1.50 km"
formatWithPrefix(2.5e-9, 's')      // "2.50 ns"
formatWithPrefix(1e6, 'Hz')        // "1.00 MHz"

---

formatValue

Format a number with automatic scientific notation for extreme values.

function formatValue(value: number, decimals?: number): string

Example

import { formatValue } from 'velo-plot/scientific'

formatValue(123.456)      // "123.456"
formatValue(0.0001)       // "1.000e-4"
formatValue(1234567)      // "1.235e+6"

---

formatScientific

Always format in scientific notation.

function formatScientific(value: number, decimals?: number): string

Example

import { formatScientific } from 'velo-plot/scientific'

formatScientific(123.456)    // "1.23e+2"
formatScientific(0.001)      // "1.00e-3"

---

getBestPrefix

Get the optimal SI prefix for a value.

function getBestPrefix(value: number): PrefixInfo

Returns

interface PrefixInfo {
  symbol: string   // 'p' | 'n' | 'µ' | 'm' | '' | 'k' | 'M' | 'G'
  factor: number   // Multiplication factor (e.g., 1e-6 for µ)
}

Example

import { getBestPrefix } from 'velo-plot/scientific'

const prefix = getBestPrefix(0.000001)
// { symbol: 'µ', factor: 1e-6 }

const scaled = 0.000001 / prefix.factor  // 1
console.log(`${scaled} ${prefix.symbol}A`)  // "1 µA"

---

integrate

Numerical integration using the trapezoidal rule. Essential for calculating areas under curves (e.g., total charge, energy).

function integrate(
  x: number[] | Float32Array,
  y: number[] | Float32Array,
  xMin?: number,
  xMax?: number
): number

Parameters

Name	Type	Description
x	number[] | Float32Array	X values (must be sorted).
y	number[] | Float32Array	Y values.
xMin	number	Optional: start of integration range (in X units).
xMax	number	Optional: end of integration range (in X units).

Example

import { integrate } from 'velo-plot/scientific'

const area = integrate(xData, yData, 0.2, 0.8)
// Or via chart: chart.analysis.integrate(...)
console.log(`Peak Area: ${area.toFixed(4)}`)

---

subtractBaseline

Subtract a linear baseline from a dataset. Useful for removing drift or constant backgrounds.

function subtractBaseline(
  x: number[] | Float32Array,
  y: number[] | Float32Array,
  x1: number,
  x2: number
): Float32Array

Parameters

Name	Type	Description
x	number[] | Float32Array	X values.
y	number[] | Float32Array	Y values.
x1	number	X coordinate of the first baseline point.
x2	number	X coordinate of the second baseline point.

Example

import { subtractBaseline } from 'velo-plot/scientific'

// Subtract background using points at x=0.1 and x=0.9
const correctedY = subtractBaseline(xData, yData, 0.1, 0.9)
// Or via chart: chart.analysis.subtractBaseline(...)

chart.addSeries({
  id: 'corrected',
  data: { x: xData, y: correctedY }
})

Known limitations

• Bundle entry — pick velo-plot, velo-plot/trading, velo-plot/scientific, or velo-plot/full. See Bundle Architecture.
• WebGPU renderer (renderer: 'webgpu') requires an extended bundle entry and is experimental — use WebGL (default) for production.
• SVG — exportSVG() and renderer: 'svg' require an extended bundle. LaTeX labels and contour overlays are partial; 3D is not supported in SVG. See SVG examples.
• See Plugin status registry for plugin maturity (complete, partial, experimental).