feat: add shape to gsd result (#102)

* feat: add shape to gsd result

adapt to new version of ml-spectra

* chore: remove support for node 12

* chore: reverse change in test case

.github/workflows/nodejs-ts.yml

@@ -11,5 +11,5 @@ jobs:
     # Documentation: https://github.com/zakodium/workflows#nodejs-ci
     uses: zakodium/workflows/.github/workflows/nodejs.yml@nodejs-v1
     with:
-      node-version-matrix: '[12, 14, 16, 18]'
+      node-version-matrix: '[14, 16, 18]'
       lint-check-types: true

package.json

@@ -82,7 +82,7 @@
     "cheminfo-types": "^1.1.0",
     "ml-peak-shape-generator": "^4.1.1",
     "ml-savitzky-golay-generalized": "4.0.1",
-    "ml-spectra-fitting": "4.0.2",
+    "ml-spectra-fitting": "4.1.0",
     "ml-spectra-processing": "^11.6.0"
   }
 }

src/GSDPeak.ts

@@ -1,3 +1,5 @@
+import { Shape1D } from 'ml-peak-shape-generator';
+
 export interface GSDPeak {
   x: number;
   y: number;
@@ -14,6 +16,9 @@ export interface GSDPeak {
    * This allows to determine if a peak is soft or not
    */
   ddY: number;
+
+  shape: Shape1D;
+
   inflectionPoints: {
     from: { x: number; index: number };
     to: { x: number; index: number };

src/__tests__/gaussian-smooth.test.ts

@@ -38,6 +38,10 @@ describe('gaussian simulated peaks', () => {
         ddY: -259.83290100626783,
         width: 0.08,
         index: 25,
+        shape: {
+          fwhm: 0.09419280180123805,
+          kind: 'gaussian',
+        },
         inflectionPoints: {
           from: { x: -0.54, index: 23 },
           to: { x: -0.46, index: 27 },
@@ -49,6 +53,10 @@ describe('gaussian simulated peaks', () => {
         ddY: -259.83290100626783,
         width: 0.08,
         index: 75,
+        shape: {
+          fwhm: 0.09419280180123805,
+          kind: 'gaussian',
+        },
         inflectionPoints: {
           from: { x: 0.46, index: 73 },
           to: { x: 0.54, index: 77 },

src/__tests__/gaussian.test.ts

@@ -38,6 +38,10 @@ describe('smooth:false option', () => {
         ddY: -259.83290100626783,
         width: 0.08,
         index: 25,
+        shape: {
+          fwhm: 0.09419280180123805,
+          kind: 'gaussian',
+        },
         inflectionPoints: {
           from: { index: 23, x: -0.54 },
           to: { index: 27, x: -0.46 },
@@ -49,6 +53,10 @@ describe('smooth:false option', () => {
         ddY: -259.83290100626783,
         width: 0.08,
         index: 75,
+        shape: {
+          fwhm: 0.09419280180123805,
+          kind: 'gaussian',
+        },
         inflectionPoints: {
           from: { index: 73, x: 0.46 },
           to: { index: 77, x: 0.54 },
@@ -68,6 +76,10 @@ describe('smooth:false option', () => {
         ddY: -259.83290100626783,
         width: 0.08,
         index: 25,
+        shape: {
+          fwhm: 0.09419280180123805,
+          kind: 'gaussian',
+        },
         inflectionPoints: {
           from: { index: 23, x: -0.54 },
           to: { index: 27, x: -0.46 },
@@ -79,6 +91,10 @@ describe('smooth:false option', () => {
         ddY: -259.83290100626783,
         width: 0.08,
         index: 75,
+        shape: {
+          fwhm: 0.09419280180123805,
+          kind: 'gaussian',
+        },
         inflectionPoints: {
           from: { index: 73, x: 0.46 },
           to: { index: 77, x: 0.54 },
@@ -101,6 +117,10 @@ describe('smooth:false option', () => {
         ddY: 259.83290100626783,
         width: 0.08,
         index: 25,
+        shape: {
+          fwhm: 0.09419280180123805,
+          kind: 'gaussian',
+        },
         inflectionPoints: {
           from: { index: 23, x: -0.54 },
           to: { index: 27, x: -0.46 },
@@ -112,6 +132,10 @@ describe('smooth:false option', () => {
         ddY: 259.83290100626783,
         width: 0.08,
         index: 75,
+        shape: {
+          fwhm: 0.09419280180123805,
+          kind: 'gaussian',
+        },
         inflectionPoints: {
           from: { index: 73, x: 0.46 },
           to: { index: 77, x: 0.54 },
@@ -135,6 +159,10 @@ describe('smooth:false option', () => {
         ddY: 259.83290100626783,
         width: 0.08,
         index: 25,
+        shape: {
+          fwhm: 0.09419280180123805,
+          kind: 'gaussian',
+        },
         inflectionPoints: {
           from: { index: 23, x: -0.54 },
           to: { index: 27, x: -0.46 },
@@ -146,6 +174,10 @@ describe('smooth:false option', () => {
         ddY: 259.83290100626783,
         width: 0.08,
         index: 75,
+        shape: {
+          fwhm: 0.09419280180123805,
+          kind: 'gaussian',
+        },
         inflectionPoints: {
           from: { index: 73, x: 0.46 },
           to: { index: 77, x: 0.54 },

src/__tests__/power.test.ts

@@ -56,6 +56,10 @@ describe('power', () => {
         width: 0.3,
         index: 100,
         ddY: -33832.03463203485,
+        shape: {
+          fwhm: 0.35322300675464324,
+          kind: 'gaussian',
+        },
         inflectionPoints: {
           from: { x: 4.85, index: 97 },
           to: { x: 5.15, index: 103 },
@@ -78,6 +82,10 @@ describe('power', () => {
         width: 0.05,
         index: 89,
         ddY: 800,
+        shape: {
+          fwhm: 0.05887050112577352,
+          kind: 'gaussian',
+        },
         inflectionPoints: {
           from: { x: 4.4, index: 88 },
           to: { x: 4.45, index: 89 },
@@ -89,6 +97,10 @@ describe('power', () => {
         width: 0.2,
         index: 100,
         ddY: -44914.28571428623,
+        shape: {
+          fwhm: 0.2354820045030941,
+          kind: 'gaussian',
+        },
         inflectionPoints: {
           from: { x: 4.9, index: 98 },
           to: { x: 5.1, index: 102 },
@@ -100,6 +112,10 @@ describe('power', () => {
         width: 0.05,
         index: 111,
         ddY: 800,
+        shape: {
+          fwhm: 0.05887050112577352,
+          kind: 'gaussian',
+        },
         inflectionPoints: {
           from: { x: 5.55, index: 111 },
           to: { x: 5.6, index: 112 },

src/__tests__/ubiquitin.test.ts

@@ -28,6 +28,10 @@ describe('Global spectra deconvolution ubiquitin', () => {
       ddY: -15468134.039875854,
       width: 0.002420000000000755,
       index: 11,
+      shape: {
+        fwhm: 0.0028493322544883375,
+        kind: 'gaussian',
+      },
       inflectionPoints: {
         from: { x: 200.054133, index: 9 },
         to: { x: 200.056553, index: 13 },

src/gsd.ts

@@ -1,4 +1,5 @@
 import type { DataXY } from 'cheminfo-types';
+import { Shape1D } from 'ml-peak-shape-generator';
 import { sgg, SGGOptions } from 'ml-savitzky-golay-generalized';
 import {
   xIsEquallySpaced,
@@ -9,6 +10,7 @@ import {
 } from 'ml-spectra-processing';
 
 import { GSDPeak } from './GSDPeak';
+import { appendShapeAndFWHM } from './utils/appendShapeAndFWHM';
 import { optimizeTop } from './utils/optimizeTop';
 
 export interface GSDOptions {
@@ -44,6 +46,11 @@ export interface GSDOptions {
    * @default false
    */
   realTopDetection?: boolean;
+  /**
+   * Shape used to add FWHM property in the peaks
+   * @default {kind:'gaussian'}
+   */
+  shape?: Shape1D;
 }
 
 /**
@@ -60,6 +67,7 @@ export function gsd(data: DataXY, options: GSDOptions = {}): GSDPeak[] {
       windowSize: 9,
       polynomial: 3,
     },
+    shape,
     noiseLevel,
     smoothY = false,
     maxCriteria = true,
@@ -239,14 +247,14 @@ export function gsd(data: DataXY, options: GSDOptions = {}): GSDPeak[] {
         peaks.push({
           x: deltaX,
           y: yData[minddYIndex],
-          width: width,
+          width,
           index: minddYIndex,
           ddY: ddY[minddYIndex],
           inflectionPoints: {
             from: intervalL[possible],
             to: intervalR[possible],
           },
-        });
+        } as GSDPeak);
       }
     }
   }
@@ -266,5 +274,5 @@ export function gsd(data: DataXY, options: GSDOptions = {}): GSDPeak[] {
     return a.x - b.x;
   });
 
-  return peaks;
+  return appendShapeAndFWHM(peaks, { shape });
 }

src/post/__tests__/optimizePeaksWithLogs.test.ts

@@ -30,7 +30,7 @@ describe('optimizePeaksWithLogs', () => {
     expect(result.logs).toMatchObject([
       {
         iterations: 100,
-        error: 0.000017852930772995625,
+        error: 0.000017852931247867768,
         parameters: { kind: 'lm', options: { timeout: 10 } },
         message: 'optimization successful',
         groupSize: 1,

src/post/broadenPeaks.ts

@@ -10,7 +10,7 @@ import { GSDPeak } from '../GSDPeak';
  */
 
 export function broadenPeaks(
-  peakList: GSDPeak[],
+  peakList: Omit<GSDPeak, 'shape'>[],
   options: {
     /**
      * @default 2

src/post/optimizePeaks.ts

@@ -1,4 +1,5 @@
 import type { DataXY, PeakXYWidth } from 'cheminfo-types';
+import { FromTo } from 'cheminfo-types';
 import { Shape1D } from 'ml-peak-shape-generator';
 import type { OptimizationOptions } from 'ml-spectra-fitting';
 
@@ -7,6 +8,14 @@ import { GSDPeakOptimized } from '../GSDPeakOptimized';
 import { optimizePeaksWithLogs } from './optimizePeaksWithLogs';
 
 export interface OptimizePeaksOptions {
+  /**
+   * baseline
+   */
+  baseline?: number;
+  /**
+   * range to apply the optimization
+   */
+  fromTo?: Partial<FromTo>;
   /**
    * Shape to use for optimization
    * @default {kind:'gaussian'}

src/post/optimizePeaksWithLogs.ts

@@ -21,6 +21,8 @@ export function optimizePeaksWithLogs(
   options: OptimizePeaksOptions = {},
 ): { logs: any[]; optimizedPeaks: GSDPeakOptimized[] } {
   const {
+    fromTo = {},
+    baseline,
     shape = { kind: 'gaussian' },
     groupingFactor = 1,
     factorLimits = 2,
@@ -40,7 +42,6 @@ export function optimizePeaksWithLogs(
   let groups = groupPeaks(peakList, { factor: groupingFactor });
   let logs: any[] = [];
   let results: GSDPeakOptimized[] = [];
-
   groups.forEach((peakGroup) => {
     const start = Date.now();
     // In order to make optimization we will add fwhm and shape on all the peaks
@@ -49,8 +50,11 @@ export function optimizePeaksWithLogs(
     const firstPeak = peaks[0];
     const lastPeak = peaks[peaks.length - 1];
 
-    const from = firstPeak.x - firstPeak.width * factorLimits;
-    const to = lastPeak.x + lastPeak.width * factorLimits;
+    const {
+      from = firstPeak.x - firstPeak.width * factorLimits,
+      to = lastPeak.x + lastPeak.width * factorLimits,
+    } = fromTo;
+
     const { fromIndex, toIndex } = xGetFromToIndex(data.x, { from, to });
 
     const x =
@@ -76,6 +80,7 @@ export function optimizePeaksWithLogs(
         peaks: optimizedPeaks,
       } = optimize({ x, y }, peaks, {
         shape,
+        baseline,
         optimization,
       });