ml-gsd - npm Package Compare versions

Comparing version 9.0.0 to 9.0.1

CHANGELOG.md

 # Changelog
 
+### [9.0.1](https://www.github.com/mljs/global-spectral-deconvolution/compare/v9.0.0...v9.0.1) (2021-11-23)
+
+
+### Bug Fixes
+
+* update PSG n spectra-fitting ([#70](https://www.github.com/mljs/global-spectral-deconvolution/issues/70)) ([ac23217](https://www.github.com/mljs/global-spectral-deconvolution/commit/ac23217cc1c73f513b772661ad2712b727fa02e7))
+
 ## [9.0.0](https://www.github.com/mljs/global-spectral-deconvolution/compare/v8.0.0...v9.0.0) (2021-11-18)
@@ -4,0 +11,0 @@

lib-esm/gsd.d.ts

@@ -27,3 +27,2 @@ import type { DataXY } from 'cheminfo-types';
 export interface Peak1D {
-    index?: number;
     x: number;
@@ -35,7 +34,3 @@ y: number;
 }
-export interface LastType {
-    x: number;
-    index: number;
-}
-export interface GSDOptions {
+export interface IGSDOptions {
     noiseLevel?: number;
@@ -55,3 +50,3 @@ sgOptions?: {
 }
-export declare function gsd(data: DataXY, options?: GSDOptions): Peak1D[];
+export declare function gsd(data: DataXY, options?: IGSDOptions): Peak1D[];
 //# sourceMappingURL=gsd.d.ts.map

lib-esm/gsd.js

@@ -121,6 +121,11 @@ import { getShape1D } from 'ml-peak-shape-generator';
     }
-    let widthProcessor = getShape1D(shape).widthToFWHM;
-    let signals = [];
+    let widthToFWHM = getShape1D(shape).widthToFWHM;
     let lastK = -1;
-    let possible, frequency, distanceJ, minDistance, gettingCloser;
+    let possible;
+    let frequency;
+    let distanceJ;
+    let minDistance;
+    let gettingCloser;
+    const peaks = [];
+    const indexes = [];
     for (const minddYIndex of minddY) {
@@ -151,4 +156,4 @@ frequency = xData[minddYIndex];
                 let width = Math.abs(intervalR[possible].x - intervalL[possible].x);
-                signals.push({
-                    index: minddYIndex,
+                indexes.push(minddYIndex);
+                peaks.push({
                     x: frequency,
@@ -159,3 +164,3 @@ y: maxCriteria
                     width: width,
-                    fwhm: widthProcessor(width),
+                    fwhm: widthToFWHM(width),
                     shape,
@@ -167,8 +172,8 @@ });
     if (realTopDetection) {
-        determineRealTop(signals, xData, yData);
+        determineRealTop({ peaks, x: xData, y: yData, indexes });
     }
-    signals.sort((a, b) => {
+    peaks.sort((a, b) => {
         return a.x - b.x;
     });
-    return signals;
+    return peaks;
 }
@@ -214,6 +219,11 @@ const isEqualSpaced = (x) => {
 };
-const determineRealTop = (peakList, x, y) => {
-    let alpha, beta, gamma, p, currentPoint;
-    for (const peak of peakList) {
-        currentPoint = peak.index; // peakList[j][2];
+const determineRealTop = (options) => {
+    const { peaks, x, y, indexes } = options;
+    let alpha;
+    let beta;
+    let gamma;
+    let p;
+    for (let i = 0; i < peaks.length; i++) {
+        const peak = peaks[i];
+        let currentPoint = indexes[i];
         // The detected peak could be moved 1 or 2 units to left or right.
@@ -253,4 +263,2 @@ if (y[currentPoint - 1] >= y[currentPoint - 2] &&
             p = (0.5 * (alpha - gamma)) / (alpha - 2 * beta + gamma);
-            // console.log(alpha, beta, gamma, `p: ${p}`);
-            // console.log(x[currentPoint]+" "+tmp+" "+currentPoint);
             peak.x = x[currentPoint] + (x[currentPoint] - x[currentPoint - 1]) * p;
@@ -257,0 +265,0 @@ peak.y =

lib-esm/post/broadenPeaks.d.ts

@@ -7,3 +7,3 @@ import type { Peak1D } from '../gsd';
  */
-interface BroadenPeaksOptions {
+export interface IBroadenPeaksOptions {
     /**
@@ -19,4 +19,3 @@ * @default 2
 }
-export declare function broadenPeaks(peakList: Peak1D[], options?: BroadenPeaksOptions): Peak1D[];
-export {};
+export declare function broadenPeaks(peakList: Peak1D[], options?: IBroadenPeaksOptions): Peak1D[];
 //# sourceMappingURL=broadenPeaks.d.ts.map

lib-esm/post/joinBroadPeaks.d.ts

 import type { DataXY } from 'cheminfo-types';
 import type { Shape1D } from 'ml-peak-shape-generator';
+import type { IOptimizationOptions } from 'ml-spectra-fitting';
 import type { Peak1D } from '../gsd';
 /**
  * This function try to join the peaks that seems to belong to a broad signal in a single broad peak.
- * @param {Array} peaks - A list of initial parameters to be optimized. e.g. coming from a peak picking [{x, y, width}].
- * @param {object} [options = {}] - options
- * @param {number} [options.width=0.25] - width limit to join peaks.
- * @param {object} [options.shape={}] - it's specify the kind of shape used to fitting.
- * @param {string} [options.shape.kind = 'gaussian'] - kind of shape; lorentzian, gaussian and pseudovoigt are supported.
- * @param {object} [options.optimization = {}] - it's specify the kind and options of the algorithm use to optimize parameters.
- * @param {string} [options.optimization.kind = 'lm'] - kind of algorithm. By default it's levenberg-marquardt.
- * @param {number} [options.optimization.options.timeout = 10] - maximum time running before break in seconds.
- * @param {object} [options.optimization.options = {}] - options for the specific kind of algorithm.
+ * @param peaks - A list of initial parameters to be optimized. e.g. coming from a peak picking [{x, y, width}].
  */
@@ -21,15 +14,26 @@ interface GetSoftMaskOptions {
     };
+    /**
+     * broadRatio
+     * @default 0.0025
+     */
     broadRatio: number;
 }
-interface OptionsType extends Partial<GetSoftMaskOptions> {
-    width?: number;
+export interface IJoinBroadPeaksOptions extends Partial<GetSoftMaskOptions> {
+    /**
+     * width limit to join peaks.
+     * @default 0.25
+     */
+    broadWidth?: number;
+    /**
+     * it's specify the kind of shape used to fitting.
+     */
     shape?: Shape1D;
-    optimization?: {
-        kind: string;
-        timeout: number;
-    };
-    mask?: boolean[];
+    /**
+     * it's specify the kind and options of the algorithm use to optimize parameters.
+     */
+    optimization?: IOptimizationOptions;
+    broadMask?: boolean[];
 }
-export declare function joinBroadPeaks(data: DataXY, peakList: Peak1D[], options?: OptionsType): Peak1D[];
+export declare function joinBroadPeaks(data: DataXY, peakList: Peak1D[], options?: IJoinBroadPeaksOptions): Peak1D[];
 export {};
 //# sourceMappingURL=joinBroadPeaks.d.ts.map

lib-esm/post/joinBroadPeaks.js

@@ -5,7 +5,6 @@ import SG from 'ml-savitzky-golay-generalized';
 export function joinBroadPeaks(data, peakList, options = {}) {
-    let { mask, shape = { kind: 'gaussian' }, optimization = { kind: 'lm', timeout: 10 }, sgOptions = {
+    let { broadMask, shape = { kind: 'gaussian' }, optimization = { kind: 'lm', options: { timeout: 10 } }, sgOptions = {
         windowSize: 9,
         polynomial: 3,
-    }, broadRatio = 0.0025, } = options;
-    let { width = 0.25 } = options;
+    }, broadRatio = 0.0025, broadWidth = 0.25, } = options;
     let max = 0;
@@ -16,10 +15,10 @@ let maxI = 0;
     const peaks = JSON.parse(JSON.stringify(peakList));
-    const broadMask = !mask
+    const mask = !broadMask
         ? getSoftMask(data, peaks, { sgOptions, broadRatio })
-        : mask;
-    if (broadMask.length !== peaks.length) {
+        : broadMask;
+    if (mask.length !== peaks.length) {
         throw new Error('mask length does not match the length of peaksList');
     }
     for (let i = peaks.length - 1; i >= 0; i--) {
-        if (broadMask[i]) {
+        if (mask[i]) {
             broadLines.push(peaks.splice(i, 1)[0]);
@@ -36,3 +35,3 @@ }
     for (let i = 1; i < broadLines.length; i++) {
-        if (Math.abs(broadLines[i - 1].x - broadLines[i].x) < width) {
+        if (Math.abs(broadLines[i - 1].x - broadLines[i].x) < broadWidth) {
             candidates.x.push(broadLines[i].x);
@@ -39,0 +38,0 @@ candidates.y.push(broadLines[i].y);

lib-esm/post/optimizePeaks.d.ts

 import type { DataXY } from 'cheminfo-types';
 import type { Shape1D } from 'ml-peak-shape-generator';
+import type { IOptimizationOptions } from 'ml-spectra-fitting';
 import type { Peak1D } from '../gsd';
@@ -10,3 +11,3 @@ /**
  */
-interface OptimizePeaksOptions {
+export interface IOptimizePeaksOptions {
     /**
@@ -29,22 +30,5 @@ * times of width to group peaks.
      */
-    optimization?: {
-        /**
-         * kind of algorithm. By default it's levenberg-marquardt.
-         * @default 'lm'
-         */
-        kind: string;
-        /**
-         * options for the specific kind of algorithm.
-         */
-        options: {
-            /**
-             * maximum time running before break in seconds.
-             * @default 10
-             */
-            timeout: number;
-        };
-    };
+    optimization?: IOptimizationOptions;
 }
-export declare function optimizePeaks(data: DataXY, peakList: Peak1D[], options?: OptimizePeaksOptions): Peak1D[];
-export {};
+export declare function optimizePeaks(data: DataXY, peakList: Peak1D[], options?: IOptimizePeaksOptions): Peak1D[];
 //# sourceMappingURL=optimizePeaks.d.ts.map

lib/gsd.d.ts

@@ -27,3 +27,2 @@ import type { DataXY } from 'cheminfo-types';
 export interface Peak1D {
-    index?: number;
     x: number;
@@ -35,7 +34,3 @@ y: number;
 }
-export interface LastType {
-    x: number;
-    index: number;
-}
-export interface GSDOptions {
+export interface IGSDOptions {
     noiseLevel?: number;
@@ -55,3 +50,3 @@ sgOptions?: {
 }
-export declare function gsd(data: DataXY, options?: GSDOptions): Peak1D[];
+export declare function gsd(data: DataXY, options?: IGSDOptions): Peak1D[];
 //# sourceMappingURL=gsd.d.ts.map

lib/gsd.js

@@ -127,6 +127,11 @@ "use strict";
     }
-    let widthProcessor = (0, ml_peak_shape_generator_1.getShape1D)(shape).widthToFWHM;
-    let signals = [];
+    let widthToFWHM = (0, ml_peak_shape_generator_1.getShape1D)(shape).widthToFWHM;
     let lastK = -1;
-    let possible, frequency, distanceJ, minDistance, gettingCloser;
+    let possible;
+    let frequency;
+    let distanceJ;
+    let minDistance;
+    let gettingCloser;
+    const peaks = [];
+    const indexes = [];
     for (const minddYIndex of minddY) {
@@ -157,4 +162,4 @@ frequency = xData[minddYIndex];
                 let width = Math.abs(intervalR[possible].x - intervalL[possible].x);
-                signals.push({
-                    index: minddYIndex,
+                indexes.push(minddYIndex);
+                peaks.push({
                     x: frequency,
@@ -165,3 +170,3 @@ y: maxCriteria
                     width: width,
-                    fwhm: widthProcessor(width),
+                    fwhm: widthToFWHM(width),
                     shape,
@@ -173,8 +178,8 @@ });
     if (realTopDetection) {
-        determineRealTop(signals, xData, yData);
+        determineRealTop({ peaks, x: xData, y: yData, indexes });
     }
-    signals.sort((a, b) => {
+    peaks.sort((a, b) => {
         return a.x - b.x;
     });
-    return signals;
+    return peaks;
 }
@@ -221,6 +226,11 @@ exports.gsd = gsd;
 };
-const determineRealTop = (peakList, x, y) => {
-    let alpha, beta, gamma, p, currentPoint;
-    for (const peak of peakList) {
-        currentPoint = peak.index; // peakList[j][2];
+const determineRealTop = (options) => {
+    const { peaks, x, y, indexes } = options;
+    let alpha;
+    let beta;
+    let gamma;
+    let p;
+    for (let i = 0; i < peaks.length; i++) {
+        const peak = peaks[i];
+        let currentPoint = indexes[i];
         // The detected peak could be moved 1 or 2 units to left or right.
@@ -260,4 +270,2 @@ if (y[currentPoint - 1] >= y[currentPoint - 2] &&
             p = (0.5 * (alpha - gamma)) / (alpha - 2 * beta + gamma);
-            // console.log(alpha, beta, gamma, `p: ${p}`);
-            // console.log(x[currentPoint]+" "+tmp+" "+currentPoint);
             peak.x = x[currentPoint] + (x[currentPoint] - x[currentPoint - 1]) * p;
@@ -264,0 +272,0 @@ peak.y =

lib/post/broadenPeaks.d.ts

@@ -7,3 +7,3 @@ import type { Peak1D } from '../gsd';
  */
-interface BroadenPeaksOptions {
+export interface IBroadenPeaksOptions {
     /**
@@ -19,4 +19,3 @@ * @default 2
 }
-export declare function broadenPeaks(peakList: Peak1D[], options?: BroadenPeaksOptions): Peak1D[];
-export {};
+export declare function broadenPeaks(peakList: Peak1D[], options?: IBroadenPeaksOptions): Peak1D[];
 //# sourceMappingURL=broadenPeaks.d.ts.map

lib/post/joinBroadPeaks.d.ts

 import type { DataXY } from 'cheminfo-types';
 import type { Shape1D } from 'ml-peak-shape-generator';
+import type { IOptimizationOptions } from 'ml-spectra-fitting';
 import type { Peak1D } from '../gsd';
 /**
  * This function try to join the peaks that seems to belong to a broad signal in a single broad peak.
- * @param {Array} peaks - A list of initial parameters to be optimized. e.g. coming from a peak picking [{x, y, width}].
- * @param {object} [options = {}] - options
- * @param {number} [options.width=0.25] - width limit to join peaks.
- * @param {object} [options.shape={}] - it's specify the kind of shape used to fitting.
- * @param {string} [options.shape.kind = 'gaussian'] - kind of shape; lorentzian, gaussian and pseudovoigt are supported.
- * @param {object} [options.optimization = {}] - it's specify the kind and options of the algorithm use to optimize parameters.
- * @param {string} [options.optimization.kind = 'lm'] - kind of algorithm. By default it's levenberg-marquardt.
- * @param {number} [options.optimization.options.timeout = 10] - maximum time running before break in seconds.
- * @param {object} [options.optimization.options = {}] - options for the specific kind of algorithm.
+ * @param peaks - A list of initial parameters to be optimized. e.g. coming from a peak picking [{x, y, width}].
  */
@@ -21,15 +14,26 @@ interface GetSoftMaskOptions {
     };
+    /**
+     * broadRatio
+     * @default 0.0025
+     */
     broadRatio: number;
 }
-interface OptionsType extends Partial<GetSoftMaskOptions> {
-    width?: number;
+export interface IJoinBroadPeaksOptions extends Partial<GetSoftMaskOptions> {
+    /**
+     * width limit to join peaks.
+     * @default 0.25
+     */
+    broadWidth?: number;
+    /**
+     * it's specify the kind of shape used to fitting.
+     */
     shape?: Shape1D;
-    optimization?: {
-        kind: string;
-        timeout: number;
-    };
-    mask?: boolean[];
+    /**
+     * it's specify the kind and options of the algorithm use to optimize parameters.
+     */
+    optimization?: IOptimizationOptions;
+    broadMask?: boolean[];
 }
-export declare function joinBroadPeaks(data: DataXY, peakList: Peak1D[], options?: OptionsType): Peak1D[];
+export declare function joinBroadPeaks(data: DataXY, peakList: Peak1D[], options?: IJoinBroadPeaksOptions): Peak1D[];
 export {};
 //# sourceMappingURL=joinBroadPeaks.d.ts.map

lib/post/joinBroadPeaks.js

@@ -11,7 +11,6 @@ "use strict";
 function joinBroadPeaks(data, peakList, options = {}) {
-    let { mask, shape = { kind: 'gaussian' }, optimization = { kind: 'lm', timeout: 10 }, sgOptions = {
+    let { broadMask, shape = { kind: 'gaussian' }, optimization = { kind: 'lm', options: { timeout: 10 } }, sgOptions = {
         windowSize: 9,
         polynomial: 3,
-    }, broadRatio = 0.0025, } = options;
-    let { width = 0.25 } = options;
+    }, broadRatio = 0.0025, broadWidth = 0.25, } = options;
     let max = 0;
@@ -22,10 +21,10 @@ let maxI = 0;
     const peaks = JSON.parse(JSON.stringify(peakList));
-    const broadMask = !mask
+    const mask = !broadMask
         ? getSoftMask(data, peaks, { sgOptions, broadRatio })
-        : mask;
-    if (broadMask.length !== peaks.length) {
+        : broadMask;
+    if (mask.length !== peaks.length) {
         throw new Error('mask length does not match the length of peaksList');
     }
     for (let i = peaks.length - 1; i >= 0; i--) {
-        if (broadMask[i]) {
+        if (mask[i]) {
             broadLines.push(peaks.splice(i, 1)[0]);
@@ -42,3 +41,3 @@ }
     for (let i = 1; i < broadLines.length; i++) {
-        if (Math.abs(broadLines[i - 1].x - broadLines[i].x) < width) {
+        if (Math.abs(broadLines[i - 1].x - broadLines[i].x) < broadWidth) {
             candidates.x.push(broadLines[i].x);
@@ -45,0 +44,0 @@ candidates.y.push(broadLines[i].y);

lib/post/optimizePeaks.d.ts

 import type { DataXY } from 'cheminfo-types';
 import type { Shape1D } from 'ml-peak-shape-generator';
+import type { IOptimizationOptions } from 'ml-spectra-fitting';
 import type { Peak1D } from '../gsd';
@@ -10,3 +11,3 @@ /**
  */
-interface OptimizePeaksOptions {
+export interface IOptimizePeaksOptions {
     /**
@@ -29,22 +30,5 @@ * times of width to group peaks.
      */
-    optimization?: {
-        /**
-         * kind of algorithm. By default it's levenberg-marquardt.
-         * @default 'lm'
-         */
-        kind: string;
-        /**
-         * options for the specific kind of algorithm.
-         */
-        options: {
-            /**
-             * maximum time running before break in seconds.
-             * @default 10
-             */
-            timeout: number;
-        };
-    };
+    optimization?: IOptimizationOptions;
 }
-export declare function optimizePeaks(data: DataXY, peakList: Peak1D[], options?: OptimizePeaksOptions): Peak1D[];
-export {};
+export declare function optimizePeaks(data: DataXY, peakList: Peak1D[], options?: IOptimizePeaksOptions): Peak1D[];
 //# sourceMappingURL=optimizePeaks.d.ts.map

package.json

 {
   "name": "ml-gsd",
-  "version": "9.0.0",
+  "version": "9.0.1",
   "description": "Global Spectra Deconvolution",
@@ -75,3 +75,3 @@ "main": "./lib/index.js",
     "rimraf": "^3.0.2",
-    "spectrum-generator": "^6.0.0",
+    "spectrum-generator": "^6.0.1",
     "ts-jest": "^27.0.7",
@@ -83,7 +83,7 @@ "typescript": "^4.4.4",
     "cheminfo-types": "^0.8.0",
-    "ml-peak-shape-generator": "^3.0.2",
+    "ml-peak-shape-generator": "^3.0.3",
     "ml-savitzky-golay-generalized": "2.0.3",
-    "ml-spectra-fitting": "^3.0.0",
+    "ml-spectra-fitting": "^3.0.1",
     "ml-spectra-processing": "^6.8.0"
   }
 }

src/__tests__/broadNMR.test.ts

@@ -28,3 +28,3 @@ import { readFileSync } from 'fs';
       {
-        width: 0.25,
+        broadWidth: 0.25,
         broadRatio: 0.0025,
@@ -31,0 +31,0 @@ shape: { kind: 'lorentzian' },

src/__tests__/massPeakPicking.test.ts

@@ -45,6 +45,7 @@ import CC from 'chemcalc';
     });
+    const gaussian = new Gaussian();
     expect(result[0].x).toBeCloseTo(69.938, 1);
     expect(result[0].y).toBeCloseTo(max, 2);
     expect(result[0].fwhm).toBeCloseTo(0.01, 4);
-    expect(result[0].width).toBeCloseTo(Gaussian.fwhmToWidth(0.01), 4);
+    expect(result[0].width).toBeCloseTo(gaussian.fwhmToWidth(0.01), 4);
 
@@ -51,0 +52,0 @@ expect(result[1].x).toBeCloseTo(71.935, 2);

src/gsd.ts

@@ -29,3 +29,2 @@ import type { DataXY, DoubleArray } from 'cheminfo-types';
 export interface Peak1D {
-  index?: number;
   x: number;
@@ -37,3 +36,4 @@ y: number;
 }
-export interface LastType {
+
+interface LastType {
   x: number;
@@ -43,3 +43,3 @@ index: number;
 
-export interface GSDOptions {
+export interface IGSDOptions {
   noiseLevel?: number;
@@ -60,3 +60,3 @@ sgOptions?: {
 
-export function gsd(data: DataXY, options: GSDOptions = {}): Peak1D[] {
+export function gsd(data: DataXY, options: IGSDOptions = {}): Peak1D[] {
   let {
@@ -202,12 +202,13 @@ noiseLevel,
 
-  let widthProcessor = getShape1D(shape).widthToFWHM;
+  let widthToFWHM = getShape1D(shape).widthToFWHM;
 
-  let signals: Peak1D[] = [];
   let lastK = -1;
-  let possible: number,
-    frequency: number,
-    distanceJ: number,
-    minDistance: number,
-    gettingCloser: boolean;
+  let possible: number;
+  let frequency: number;
+  let distanceJ: number;
+  let minDistance: number;
+  let gettingCloser: boolean;
 
+  const peaks: Peak1D[] = [];
+  const indexes: number[] = [];
   for (const minddYIndex of minddY) {
@@ -239,4 +240,4 @@ frequency = xData[minddYIndex];
         let width = Math.abs(intervalR[possible].x - intervalL[possible].x);
-        signals.push({
-          index: minddYIndex,
+        indexes.push(minddYIndex);
+        peaks.push({
           x: frequency,
@@ -247,3 +248,3 @@ y: maxCriteria
           width: width,
-          fwhm: widthProcessor(width),
+          fwhm: widthToFWHM(width),
           shape,
@@ -256,10 +257,10 @@ });
   if (realTopDetection) {
-    determineRealTop(signals, xData, yData);
+    determineRealTop({ peaks, x: xData, y: yData, indexes });
   }
 
-  signals.sort((a, b) => {
+  peaks.sort((a, b) => {
     return a.x - b.x;
   });
 
-  return signals;
+  return peaks;
 }
@@ -308,14 +309,16 @@
 };
-const determineRealTop = (
-  peakList: Peak1D[],
-  x: DoubleArray,
-  y: DoubleArray,
-): void => {
-  let alpha: number,
-    beta: number,
-    gamma: number,
-    p: number,
-    currentPoint: number;
-  for (const peak of peakList) {
-    currentPoint = peak.index as number; // peakList[j][2];
+const determineRealTop = (options: {
+  peaks: Peak1D[];
+  x: DoubleArray;
+  y: DoubleArray;
+  indexes: number[];
+}): void => {
+  const { peaks, x, y, indexes } = options;
+  let alpha: number;
+  let beta: number;
+  let gamma: number;
+  let p: number;
+  for (let i = 0; i < peaks.length; i++) {
+    const peak = peaks[i];
+    let currentPoint = indexes[i];
     // The detected peak could be moved 1 or 2 units to left or right.
@@ -362,4 +365,2 @@ if (
       p = (0.5 * (alpha - gamma)) / (alpha - 2 * beta + gamma);
-      // console.log(alpha, beta, gamma, `p: ${p}`);
-      // console.log(x[currentPoint]+" "+tmp+" "+currentPoint);
       peak.x = x[currentPoint] + (x[currentPoint] - x[currentPoint - 1]) * p;
@@ -366,0 +367,0 @@ peak.y =

src/post/broadenPeaks.ts

@@ -8,3 +8,3 @@ import type { Peak1D } from '../gsd';
  */
-interface BroadenPeaksOptions {
+export interface IBroadenPeaksOptions {
   /**
@@ -27,3 +27,3 @@ * @default 2
   peakList: Peak1D[],
-  options: BroadenPeaksOptions = {},
+  options: IBroadenPeaksOptions = {},
 ): Peak1D[] {
@@ -30,0 +30,0 @@ const { factor = 2, overlap = false } = options;

src/post/joinBroadPeaks.ts

@@ -5,2 +5,3 @@ import type { DataXY } from 'cheminfo-types';
 import { optimize } from 'ml-spectra-fitting';
+import type { IOptimizationOptions } from 'ml-spectra-fitting';
 import { xFindClosestIndex } from 'ml-spectra-processing';
@@ -12,11 +13,3 @@
  * This function try to join the peaks that seems to belong to a broad signal in a single broad peak.
- * @param {Array} peaks - A list of initial parameters to be optimized. e.g. coming from a peak picking [{x, y, width}].
- * @param {object} [options = {}] - options
- * @param {number} [options.width=0.25] - width limit to join peaks.
- * @param {object} [options.shape={}] - it's specify the kind of shape used to fitting.
- * @param {string} [options.shape.kind = 'gaussian'] - kind of shape; lorentzian, gaussian and pseudovoigt are supported.
- * @param {object} [options.optimization = {}] - it's specify the kind and options of the algorithm use to optimize parameters.
- * @param {string} [options.optimization.kind = 'lm'] - kind of algorithm. By default it's levenberg-marquardt.
- * @param {number} [options.optimization.options.timeout = 10] - maximum time running before break in seconds.
- * @param {object} [options.optimization.options = {}] - options for the specific kind of algorithm.
+ * @param peaks - A list of initial parameters to be optimized. e.g. coming from a peak picking [{x, y, width}].
  */
@@ -29,10 +22,24 @@
   };
+  /**
+   * broadRatio
+   * @default 0.0025
+   */
   broadRatio: number;
 }
 
-interface OptionsType extends Partial<GetSoftMaskOptions> {
-  width?: number;
+export interface IJoinBroadPeaksOptions extends Partial<GetSoftMaskOptions> {
+  /**
+   * width limit to join peaks.
+   * @default 0.25
+   */
+  broadWidth?: number;
+  /**
+   * it's specify the kind of shape used to fitting.
+   */
   shape?: Shape1D;
-  optimization?: { kind: string; timeout: number };
-  mask?: boolean[];
+  /**
+   * it's specify the kind and options of the algorithm use to optimize parameters.
+   */
+  optimization?: IOptimizationOptions;
+  broadMask?: boolean[];
 }
@@ -43,8 +50,8 @@
   peakList: Peak1D[],
-  options: OptionsType = {},
+  options: IJoinBroadPeaksOptions = {},
 ): Peak1D[] {
   let {
-    mask,
+    broadMask,
     shape = { kind: 'gaussian' },
-    optimization = { kind: 'lm', timeout: 10 },
+    optimization = { kind: 'lm', options: { timeout: 10 } },
     sgOptions = {
@@ -55,4 +62,4 @@ windowSize: 9,
     broadRatio = 0.0025,
+    broadWidth = 0.25,
   } = options;
-  let { width = 0.25 } = options;
 
@@ -64,7 +71,7 @@ let max = 0;
   const peaks: Peak1D[] = JSON.parse(JSON.stringify(peakList));
-  const broadMask = !mask
+  const mask = !broadMask
     ? getSoftMask(data, peaks, { sgOptions, broadRatio })
-    : mask;
+    : broadMask;
 
-  if (broadMask.length !== peaks.length) {
+  if (mask.length !== peaks.length) {
     throw new Error('mask length does not match the length of peaksList');
@@ -74,3 +81,3 @@ }
   for (let i: number = peaks.length - 1; i >= 0; i--) {
-    if (broadMask[i]) {
+    if (mask[i]) {
       broadLines.push(peaks.splice(i, 1)[0]);
@@ -89,3 +96,3 @@ }
   for (let i = 1; i < broadLines.length; i++) {
-    if (Math.abs(broadLines[i - 1].x - broadLines[i].x) < width) {
+    if (Math.abs(broadLines[i - 1].x - broadLines[i].x) < broadWidth) {
       candidates.x.push(broadLines[i].x);
@@ -92,0 +99,0 @@ candidates.y.push(broadLines[i].y);

src/post/optimizePeaks.ts

@@ -5,2 +5,3 @@ import type { DataXY } from 'cheminfo-types';
 import { optimize } from 'ml-spectra-fitting';
+import type { IOptimizationOptions } from 'ml-spectra-fitting';
 import { xGetFromToIndex } from 'ml-spectra-processing';
@@ -18,3 +19,3 @@
  */
-interface OptimizePeaksOptions {
+export interface IOptimizePeaksOptions {
   /**
@@ -37,19 +38,3 @@ * times of width to group peaks.
    */
-  optimization?: {
-    /**
-     * kind of algorithm. By default it's levenberg-marquardt.
-     * @default 'lm'
-     */
-    kind: string;
-    /**
-     * options for the specific kind of algorithm.
-     */
-    options: {
-      /**
-       * maximum time running before break in seconds.
-       * @default 10
-       */
-      timeout: number;
-    };
-  };
+  optimization?: IOptimizationOptions;
 }
@@ -60,3 +45,3 @@
   peakList: Peak1D[],
-  options: OptimizePeaksOptions = {},
+  options: IOptimizePeaksOptions = {},
 ): Peak1D[] {
@@ -75,3 +60,3 @@ const {
     },
-  }: OptimizePeaksOptions = options;
+  }: IOptimizePeaksOptions = options;
 
@@ -116,10 +101,6 @@ if (data.x[0] > data.x[1]) {
     if (currentRange.x.length > 5) {
-      let { peaks: optimizedPeaks }: { peaks: Peak1D[] } = optimize(
-        currentRange,
-        peaks,
-        {
-          shape,
-          optimization,
-        },
-      );
+      let { peaks: optimizedPeaks } = optimize(currentRange, peaks, {
+        shape,
+        optimization,
+      });
       results = results.concat(optimizedPeaks);
@@ -126,0 +107,0 @@ // eslint-disable-next-line curly

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

Worsened metrics

Total package byte prevSize

6496317

decreased by-0.03%

Lines of code

63509

decreased by-0.05%

Dependency changes

• Updatedml-peak-shape-generator@^3.0.3

• Updatedml-spectra-fitting@^3.0.1