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fastLowess Node.js API Reference

The Node.js bindings provide a high-performance interface to the core Rust library, mirroring the Rust API structure.

Classes

Lowess

The Lowess class allows configuring the LOWESS parameters once and fitting multiple datasets using those parameters.

Constructor:

const model = new Lowess(options);
  • options: An object containing LowessOptions fields.

Methods:

const result = model.fit(x, y);
  • Fits the model to the provided x and y typed arrays.
  • Returns a LowessResult object containing the smoothed values and optional diagnostics.

StreamingLowess

The StreamingLowess class processes data in chunks, suitable for very large datasets or streaming applications.

Constructor:

const stream = new StreamingLowess(options, streamingOptions);
  • options: An object containing LowessOptions fields.
  • streamingOptions: An object containing StreamingOptions fields.

Methods:

const partialResult = stream.processChunk(x, y);
  • Processes a chunk of data. Returns partial results.
const finalResult = stream.finalize();
  • Finalizes the smoothing process and returns any remaining buffered results.

OnlineLowess

The OnlineLowess class updates the model incrementally with new data points.

Constructor:

const online = new OnlineLowess(options, onlineOptions);
  • options: An object containing LowessOptions fields.
  • onlineOptions: An object containing OnlineOptions fields.

Methods:

const result = online.addPoints(x, y);
  • Adds new points to the model and returns the smoothed values (retrospective or prospective depending on mode).

Options Structures

LowessOptions

Field Type Default Description
fraction number 0.67 Smoothing fraction (bandwidth)
iterations number 3 Number of robustifying iterations
delta number NaN Interpolation distance (NaN for auto)
weightFunction string "tricube" Weight function name
robustnessMethod string "bisquare" Robustness method name
scalingMethod string "mad" Residual scaling method
boundaryPolicy string "extend" Boundary handling policy
zeroWeightFallback string "useLocalMean" Zero-weight handling strategy
autoConverge number null Auto-convergence tolerance
confidenceIntervals number null Confidence level (e.g., 0.95)
predictionIntervals number null Prediction level (e.g., 0.95)
returnDiagnostics boolean false Include diagnostics in result
returnResiduals boolean false Include residuals in result
returnRobustnessWeights boolean false Include weights in result
parallel boolean true Enable parallel execution
cvMethod string "kfold" Cross-validation method ("kfold")
cvK number 5 Number of CV folds
cvFractions number[] null Manual fractions for CV grid

StreamingOptions

Field Type Default Description
chunkSize number 5000 Data chunk size
overlap number 500 Overlap size (-1 for auto)
mergeStrategy string "average" Merge strategy for overlap

OnlineOptions

Field Type Default Description
windowCapacity number 100 Max window size
minPoints number 2 Min points before smoothing
updateMode string "incremental" Update mode ("full" or "incremental")

Result Structure

LowessResult

Field Type Description
x Float64Array Smoothed X coordinates
y Float64Array Smoothed Y coordinates
valid boolean True if result is valid
error string Error message if failed
diagnostics Diagnostics Diagnostic metrics object
residuals Float64Array Residuals (if requested)
confidenceLower Float64Array Lower CI bounds
confidenceUpper Float64Array Upper CI bounds
predictionLower Float64Array Lower PI bounds
predictionUpper Float64Array Upper PI bounds
robustnessWeights Float64Array Robustness weights

Diagnostics

Field Type Description
rmse number Root Mean Squared Error
mae number Mean Absolute Error
rSquared number R-squared
residualSd number Residual standard deviation
effectiveDf number Effective degrees of freedom
aic number AIC
aicc number AICc

String Options

Weight Functions

  • "tricube" (default)
  • "epanechnikov"
  • "gaussian"
  • "uniform"
  • "biweight"
  • "triangle"
  • "cosine"

Robustness Methods

  • "bisquare" (default)
  • "huber"
  • "talwar"

Boundary Policies

  • "extend" (default - linear extrapolation)
  • "reflect"
  • "zero"
  • "noBoundary"

Scaling Methods

  • "mad" (default - Median Absolute Deviation)
  • "mar" (Median Absolute Residual)
  • "mean" (Mean Absolute Residual)

Zero Weight Fallback

  • "useLocalMean" (default)
  • "returnOriginal"
  • "returnNone"

Merge Strategies (Streaming)

  • "weighted" (default - weighted average of overlapping chunks)
  • "average"
  • "left"
  • "right"

Update Modes (Online)

  • "full" (default - re-smooth entire window)
  • "incremental" (O(1) update using existing fit)

Example

const { Lowess } = require('fastlowess');

const x = new Float64Array([1, 2, 3, 4, 5]);
const y = new Float64Array([2.1, 4.0, 6.2, 8.0, 10.1]);

// Configure model
const model = new Lowess({ fraction: 0.5 });

// Fit data
const result = model.fit(x, y);

console.log("Smoothed Y:", result.y);