ml-airpls - npm Package Compare versions

Comparing version 1.0.3 to 2.0.0

lib/index.js

 'use strict';
 
+var mlSpectraProcessing = require('ml-spectra-processing');
 var cuthillMckee = require('cuthill-mckee');
@@ -358,5 +359,37 @@
 
+function getControlPoints(x, y, options = {}) {
+  const { length } = x;
+  let { controlPoints = Int8Array.from({ length }).fill(0) } = options;
+  const { zones = [], weights = Float64Array.from({ length }).fill(1) } =
+    options;
+
+  if (x.length !== y.length) {
+    throw new RangeError('Y should match the length with X');
+  } else if (controlPoints.length !== x.length) {
+    throw new RangeError('controlPoints should match the length with X');
+  } else if (weights.length !== x.length) {
+    throw new RangeError('weights should match the length with X');
+  }
+
+  zones.forEach((range) => {
+    let indexFrom = getCloseIndex(x, range.from);
+    let indexTo = getCloseIndex(x, range.to);
+    if (indexFrom > indexTo) [indexFrom, indexTo] = [indexTo, indexFrom];
+    for (let i = indexFrom; i < indexTo; i++) {
+      controlPoints[i] = 1;
+    }
+  });
+
+  return {
+    weights:
+      'controlPoints' in options || zones.length > 0
+        ? mlSpectraProcessing.xMultiply(weights, controlPoints)
+        : weights,
+    controlPoints,
+  };
+}
+
 /**
  * Fit the baseline drift by iteratively changing weights of sum square error between the fitted baseline and original signals,
- * for further information about the parameters you can get the [paper of airPLS](https://github.com/zmzhang/airPLS/blob/master/airPLS_manuscript.pdf)
+ * for further information about the parameters you can get the [paper of airPLS](https://github.com/zmzhang/airPLS/blob/main/airPLS_manuscript.pdf)
  * @param {Array<number>} x - x axis data useful when control points or zones are submitted
@@ -369,41 +402,25 @@ * @param {Array<number>} y - Original data
  * @param {number} [options.lambda = 100] - Factor of weights matrix in -> [I + lambda D'D]z = x
- * @param {Array<number>} [options.controlPoints = []] - Array of x axis values to force that baseline cross those points.
- * @param {Array<number>} [options.baseLineZones = []] - Array of x axis values (as from - to), to force that baseline cross those zones.
+ * @param {Array<number>} [options.controlPoints = []] - Array of 0|1 to force the baseline cross those points.
+ * @param {Array<number>} [options.zones = []] - Array of x axis values (as from - to), to force that baseline cross those zones.
  * @returns {{corrected: Array<number>, error: number, iteration: number, baseline: Array<number>}}
  */
+
 function airPLS(x, y, options = {}) {
-  let {
-    maxIterations = 100,
-    lambda = 100,
-    tolerance = 0.001,
-    weights = new Array(y.length).fill(1),
-    controlPoints = [],
-    baseLineZones = [],
-  } = options;
+  const { weights, controlPoints } = getControlPoints(x, y, options);
+  let { maxIterations = 100, lambda = 10, tolerance = 0.001 } = options;
 
-  if (controlPoints.length > 0) {
-    controlPoints.forEach((e, i, arr) => (arr[i] = getCloseIndex(x, e)));
-  }
-  if (baseLineZones.length > 0) {
-    baseLineZones.forEach((range) => {
-      let indexFrom = getCloseIndex(x, range.from);
-      let indexTo = getCloseIndex(x, range.to);
-      if (indexFrom > indexTo) [indexFrom, indexTo] = [indexTo, indexFrom];
-      for (let i = indexFrom; i < indexTo; i++) {
-        controlPoints.push(i);
-      }
-    });
-  }
-
   let baseline, iteration;
-  let nbPoints = y.length;
-  let l = nbPoints - 1;
   let sumNegDifferences = Number.MAX_SAFE_INTEGER;
-  let stopCriterion = tolerance * y.reduce((sum, e) => Math.abs(e) + sum, 0);
+  const corrected = Float64Array.from(y);
+  let stopCriterion = getStopCriterion(y, tolerance);
 
+  const { length } = y;
   let { lowerTriangularNonZeros, permutationEncodedArray } = getDeltaMatrix(
-    nbPoints,
+    length,
     lambda,
   );
 
+  let threshold = 1;
+  const l = length - 1;
+  let prevNegSum = Number.MAX_SAFE_INTEGER;
   for (
@@ -420,29 +437,36 @@ iteration = 0;
 
-    let cho = prepare(leftHandSide, nbPoints, permutationEncodedArray);
+    let cho = prepare(leftHandSide, length, permutationEncodedArray);
 
     baseline = cho(rightHandSide);
 
-    sumNegDifferences = 0;
+    sumNegDifferences = applyCorrection(y, baseline, corrected);
+    if (iteration === 1) {
+      const { positive } = mlSpectraProcessing.xNoiseSanPlot(corrected);
+      threshold = positive;
+    } else {
+      const absChange = Math.abs(prevNegSum / sumNegDifferences);
+      if (absChange < 1.01 && absChange > 0.99) {
+        break;
+      }
+    }
 
-    let difference = y.map(calculateError);
-
-    let maxNegativeDiff = -1 * Number.MAX_SAFE_INTEGER;
+    prevNegSum = sumNegDifferences + 0;
     for (let i = 1; i < l; i++) {
-      let diff = difference[i];
-      if (diff >= 0) {
+      const diff = corrected[i];
+      if (controlPoints[i] < 1 && Math.abs(diff) > threshold) {
         weights[i] = 0;
       } else {
-        weights[i] = Math.exp((iteration * diff) / sumNegDifferences);
-        if (maxNegativeDiff < diff) maxNegativeDiff = diff;
+        const factor = diff > 0 ? -1 : 1;
+        weights[i] = Math.exp(
+          (factor * (iteration * diff)) / Math.abs(sumNegDifferences),
+        );
       }
     }
 
-    let value = Math.exp((iteration * maxNegativeDiff) / sumNegDifferences);
-    weights[0] = value;
-    weights[l] = value;
-    controlPoints.forEach((i) => (weights[i] = value));
+    weights[0] = 1;
+    weights[l] = 1;
   }
 
   return {
-    corrected: y.map((e, i) => e - baseline[i]),
+    corrected,
     baseline,
@@ -453,9 +477,19 @@ iteration,
 
-  function calculateError(e, i) {
-    let diff = e - baseline[i];
-    if (diff < 0) sumNegDifferences += diff;
-    return diff;
+  function applyCorrection(y, baseline, corrected) {
+    let sumNegDifferences = 0;
+    for (let i = 0; i < y.length; i++) {
+      let diff = y[i] - baseline[i];
+      if (diff < 0) sumNegDifferences += diff;
+      corrected[i] = diff;
+    }
+
+    return sumNegDifferences;
   }
 }
 
+function getStopCriterion(y, tolerance) {
+  let sum = mlSpectraProcessing.xAbsoluteSum(y);
+  return tolerance * sum;
+}
+
 module.exports = airPLS;

package.json

 {
   "name": "ml-airpls",
-  "version": "1.0.3",
+  "version": "2.0.0",
   "description": "Baseline correction using adaptive iteratively reweighted penalized least",
@@ -14,4 +14,5 @@ "main": "lib/index.js",
   "scripts": {
+    "build": "cheminfo-build --entry src/index.js --root AirPLS",
     "compile": "rollup -c",
-    "prepublishOnly": "npm run compile",
+    "prepack": "npm run compile",
     "eslint": "eslint src",
@@ -39,13 +40,15 @@ "eslint-fix": "npm run eslint -- --fix",
   "devDependencies": {
-    "@babel/plugin-transform-modules-commonjs": "^7.16.8",
-    "eslint": "^8.10.0",
-    "eslint-config-cheminfo": "^8.0.2",
-    "jest": "^29.5.0",
+    "@babel/plugin-transform-modules-commonjs": "^7.24.1",
+    "cheminfo-build": "^1.2.0",
+    "eslint": "^8.57.0",
+    "eslint-config-cheminfo": "^9.2.0",
+    "jest": "^29.7.0",
     "jest-matcher-deep-close-to": "^3.0.2",
-    "prettier": "^2.5.1",
-    "rollup": "^3.22.0"
+    "prettier": "^3.2.5",
+    "rollup": "^4.17.2"
   },
   "dependencies": {
-    "cuthill-mckee": "^1.0.0"
+    "cuthill-mckee": "^1.0.0",
+    "ml-spectra-processing": "^14.5.0"
   }
 }

README.md

@@ -9,3 +9,3 @@ # airpls
 
-It is an javascript implementation of [airpls](https://github.com/zmzhang/airPLS/blob/master/airPLS_manuscript.pdf) using cholesky decomposition and reverse Cuthill-Mckee method for reducing the bandwidth of sparse linear systems, obtaining a fast baseline fitter. 
+It is an javascript implementation of [airpls](https://github.com/zmzhang/airPLS/blob/main/airPLS_manuscript.pdf) using cholesky decomposition and reverse Cuthill-Mckee method for reducing the bandwidth of sparse linear systems, obtaining a fast baseline fitter. 
 
@@ -12,0 +12,0 @@ ## Installation

src/index.js

@@ -0,7 +1,41 @@
+import { xMultiply, xNoiseSanPlot, xAbsoluteSum } from 'ml-spectra-processing';
+
 import cholesky from './choleskySolver';
 import { updateSystem, getDeltaMatrix, getCloseIndex } from './utils';
 
+function getControlPoints(x, y, options = {}) {
+  const { length } = x;
+  let { controlPoints = Int8Array.from({ length }).fill(0) } = options;
+  const { zones = [], weights = Float64Array.from({ length }).fill(1) } =
+    options;
+
+  if (x.length !== y.length) {
+    throw new RangeError('Y should match the length with X');
+  } else if (controlPoints.length !== x.length) {
+    throw new RangeError('controlPoints should match the length with X');
+  } else if (weights.length !== x.length) {
+    throw new RangeError('weights should match the length with X');
+  }
+
+  zones.forEach((range) => {
+    let indexFrom = getCloseIndex(x, range.from);
+    let indexTo = getCloseIndex(x, range.to);
+    if (indexFrom > indexTo) [indexFrom, indexTo] = [indexTo, indexFrom];
+    for (let i = indexFrom; i < indexTo; i++) {
+      controlPoints[i] = 1;
+    }
+  });
+
+  return {
+    weights:
+      'controlPoints' in options || zones.length > 0
+        ? xMultiply(weights, controlPoints)
+        : weights,
+    controlPoints,
+  };
+}
+
 /**
  * Fit the baseline drift by iteratively changing weights of sum square error between the fitted baseline and original signals,
- * for further information about the parameters you can get the [paper of airPLS](https://github.com/zmzhang/airPLS/blob/master/airPLS_manuscript.pdf)
+ * for further information about the parameters you can get the [paper of airPLS](https://github.com/zmzhang/airPLS/blob/main/airPLS_manuscript.pdf)
  * @param {Array<number>} x - x axis data useful when control points or zones are submitted
@@ -14,41 +48,25 @@ * @param {Array<number>} y - Original data
  * @param {number} [options.lambda = 100] - Factor of weights matrix in -> [I + lambda D'D]z = x
- * @param {Array<number>} [options.controlPoints = []] - Array of x axis values to force that baseline cross those points.
- * @param {Array<number>} [options.baseLineZones = []] - Array of x axis values (as from - to), to force that baseline cross those zones.
+ * @param {Array<number>} [options.controlPoints = []] - Array of 0|1 to force the baseline cross those points.
+ * @param {Array<number>} [options.zones = []] - Array of x axis values (as from - to), to force that baseline cross those zones.
  * @returns {{corrected: Array<number>, error: number, iteration: number, baseline: Array<number>}}
  */
+
 export default function airPLS(x, y, options = {}) {
-  let {
-    maxIterations = 100,
-    lambda = 100,
-    tolerance = 0.001,
-    weights = new Array(y.length).fill(1),
-    controlPoints = [],
-    baseLineZones = [],
-  } = options;
+  const { weights, controlPoints } = getControlPoints(x, y, options);
+  let { maxIterations = 100, lambda = 10, tolerance = 0.001 } = options;
 
-  if (controlPoints.length > 0) {
-    controlPoints.forEach((e, i, arr) => (arr[i] = getCloseIndex(x, e)));
-  }
-  if (baseLineZones.length > 0) {
-    baseLineZones.forEach((range) => {
-      let indexFrom = getCloseIndex(x, range.from);
-      let indexTo = getCloseIndex(x, range.to);
-      if (indexFrom > indexTo) [indexFrom, indexTo] = [indexTo, indexFrom];
-      for (let i = indexFrom; i < indexTo; i++) {
-        controlPoints.push(i);
-      }
-    });
-  }
-
   let baseline, iteration;
-  let nbPoints = y.length;
-  let l = nbPoints - 1;
   let sumNegDifferences = Number.MAX_SAFE_INTEGER;
-  let stopCriterion = tolerance * y.reduce((sum, e) => Math.abs(e) + sum, 0);
+  const corrected = Float64Array.from(y);
+  let stopCriterion = getStopCriterion(y, tolerance);
 
+  const { length } = y;
   let { lowerTriangularNonZeros, permutationEncodedArray } = getDeltaMatrix(
-    nbPoints,
+    length,
     lambda,
   );
 
+  let threshold = 1;
+  const l = length - 1;
+  let prevNegSum = Number.MAX_SAFE_INTEGER;
   for (
@@ -65,29 +83,36 @@ iteration = 0;
 
-    let cho = cholesky(leftHandSide, nbPoints, permutationEncodedArray);
+    let cho = cholesky(leftHandSide, length, permutationEncodedArray);
 
     baseline = cho(rightHandSide);
 
-    sumNegDifferences = 0;
+    sumNegDifferences = applyCorrection(y, baseline, corrected);
+    if (iteration === 1) {
+      const { positive } = xNoiseSanPlot(corrected);
+      threshold = positive;
+    } else {
+      const absChange = Math.abs(prevNegSum / sumNegDifferences);
+      if (absChange < 1.01 && absChange > 0.99) {
+        break;
+      }
+    }
 
-    let difference = y.map(calculateError);
-
-    let maxNegativeDiff = -1 * Number.MAX_SAFE_INTEGER;
+    prevNegSum = sumNegDifferences + 0;
     for (let i = 1; i < l; i++) {
-      let diff = difference[i];
-      if (diff >= 0) {
+      const diff = corrected[i];
+      if (controlPoints[i] < 1 && Math.abs(diff) > threshold) {
         weights[i] = 0;
       } else {
-        weights[i] = Math.exp((iteration * diff) / sumNegDifferences);
-        if (maxNegativeDiff < diff) maxNegativeDiff = diff;
+        const factor = diff > 0 ? -1 : 1;
+        weights[i] = Math.exp(
+          (factor * (iteration * diff)) / Math.abs(sumNegDifferences),
+        );
       }
     }
 
-    let value = Math.exp((iteration * maxNegativeDiff) / sumNegDifferences);
-    weights[0] = value;
-    weights[l] = value;
-    controlPoints.forEach((i) => (weights[i] = value));
+    weights[0] = 1;
+    weights[l] = 1;
   }
 
   return {
-    corrected: y.map((e, i) => e - baseline[i]),
+    corrected,
     baseline,
@@ -98,7 +123,17 @@ iteration,
 
-  function calculateError(e, i) {
-    let diff = e - baseline[i];
-    if (diff < 0) sumNegDifferences += diff;
-    return diff;
+  function applyCorrection(y, baseline, corrected) {
+    let sumNegDifferences = 0;
+    for (let i = 0; i < y.length; i++) {
+      let diff = y[i] - baseline[i];
+      if (diff < 0) sumNegDifferences += diff;
+      corrected[i] = diff;
+    }
+
+    return sumNegDifferences;
   }
 }
+
+function getStopCriterion(y, tolerance) {
+  let sum = xAbsoluteSum(y);
+  return tolerance * sum;
+}

New alerts

License Policy Violation

License

This package is not allowed per your license policy. Review the package's license to ensure compliance.

Found 1 instance in 1 package

Fixed alerts

License Policy Violation

License

This package is not allowed per your license policy. Review the package's license to ensure compliance.

Found 1 instance in 1 package

Improved metrics

Total package byte prevSize

34783

increased by6.89%

Lines of code

913

increased by6.78%

Worsened metrics

Dependency count

2

increased by100%

Dev dependency count

8

increased by14.29%

Dependency changes

• + Addedml-spectra-processing@^14.5.0

• + Addedbinary-search@1.3.6(transitive)

• + Addedcheminfo-types@1.8.1(transitive)

• + Addedd3-array@0.7.1(transitive)

• + Addedfft.js@4.0.4(transitive)

• + Addedis-any-array@2.0.1(transitive)

• + Addedml-array-max@1.2.4(transitive)

• + Addedml-array-min@1.2.3(transitive)

• + Addedml-array-rescale@1.3.7(transitive)

• + Addedml-matrix@6.12.0(transitive)

• + Addedml-spectra-processing@14.9.1(transitive)

• + Addedml-xsadd@3.0.1(transitive)

• + Addedspline-interpolator@1.0.0(transitive)