fix: joinBroadPeaks n types (#91)

* fix: remove data from joinBroadPeaks close #89

* fix: use appendShapeAndFWHM n adapt types

* fix: update cheminfo-types

* chore: fix prettier

* feat: use PeakXYWidth

* fix(gsd): avoid falsy noiseLevel close #92

* fix: remove type definition file

Co-authored-by: Luc Patiny <[email protected]>

Author: jobo322

package.json

@@ -82,6 +82,6 @@
     "ml-peak-shape-generator": "^4.0.3",
     "ml-savitzky-golay-generalized": "4.0.0",
     "ml-spectra-fitting": "^3.0.4",
-    "ml-spectra-processing": "^10.1.2"
+    "ml-spectra-processing": "^10.2.0"
   }
 }

src/__tests__/gaussian.test.ts

@@ -155,4 +155,12 @@ describe('smooth:false option', () => {
 
     expect(peakList).toBeDeepCloseTo(expected);
   });
+
+  it('negative peaks with maxCriteria true', () => {
+    let peakList = gsd(
+      { x: data.x, y: data.y.map((value) => -value) },
+      { maxCriteria: true },
+    );
+    expect(peakList).toHaveLength(0);
+  });
 });

src/gsd.ts

@@ -71,6 +71,7 @@ export function gsd(data: DataXY, options: GSDOptions = {}): GSDPeak[] {
   if (!xIsMonotoneIncreasing(x)) {
     throw new Error('GSD only accepts monotone increasing x values');
   }
+  //rescale;
   y = y.slice();
 
   // If the max difference between delta x is less than 5%, then,
@@ -99,7 +100,7 @@ export function gsd(data: DataXY, options: GSDOptions = {}): GSDPeak[] {
       y[i] *= -1;
     }
   }
-  if (noiseLevel) {
+  if (noiseLevel !== undefined) {
     for (let i = 0; i < y.length; i++) {
       if (y[i] < noiseLevel) {
         y[i] = noiseLevel;
@@ -151,15 +152,12 @@ export function gsd(data: DataXY, options: GSDOptions = {}): GSDPeak[] {
 
   const minY = xMinValue(yData);
   const maxY = xMaxValue(yData);
+
+  if (minY > maxY || minY === maxY) return [];
+
   const yThreshold = minY + (maxY - minY) * minMaxRatio;
 
   const dX = x[1] - x[0];
-  let maxAbsDdy = 0;
-  for (let i = 0; i < yData.length; i++) {
-    if (Math.abs(ddY[i]) > maxAbsDdy) {
-      maxAbsDdy = Math.abs(ddY[i]);
-    }
-  }
 
   interface XIndex {
     x: number;
@@ -259,7 +257,7 @@ export function gsd(data: DataXY, options: GSDOptions = {}): GSDPeak[] {
 
   peaks.forEach((peak) => {
     if (!maxCriteria) {
-      peak.y = -peak.y;
+      peak.y *= -1;
       peak.ddY = peak.ddY * -1;
     }
   });

src/index.ts

@@ -1,9 +1,8 @@
 export * from './gsd';
 export * from './post/optimizePeaks';
-// joinBroadPeaks is not tested and should not be used
-// export * from './post/joinBroadPeaks';
+export * from './post/joinBroadPeaks';
 export * from './post/broadenPeaks';
-
+export * from './utils/appendShapeAndFWHM';
 export * from './GSDBroadenPeak';
 export * from './GSDPeak';
 export * from './GSDPeakOptimized';

src/post/XYWidth.ts

@@ -22,7 +22,7 @@ describe('joinBroadPeaks', () => {
     );
 
     const peaks = gsd(data);
-    const newPeaks = joinBroadPeaks(data, peaks, {
+    const newPeaks = joinBroadPeaks(peaks, {
       broadRatio: 0.03,
       broadWidth: 0.25,
     });

src/post/__tests__/joinBroadPeaks.test.ts

@@ -1,9 +1,9 @@
-import type { DataXY } from 'cheminfo-types';
 import type { Shape1D } from 'ml-peak-shape-generator';
 import { OptimizationOptions } from 'ml-spectra-fitting';
 
-import { optimizePeaks } from '..';
+import { GSDPeakOptimized, optimizePeaks } from '..';
 import { GSDPeak } from '../GSDPeak';
+import { appendShapeAndFWHM } from '../utils/appendShapeAndFWHM';
 
 export interface JoinBroadPeaksOptions {
   /**
@@ -31,7 +31,6 @@ export interface JoinBroadPeaksOptions {
  */
 
 export function joinBroadPeaks(
-  data: DataXY,
   peakList: GSDPeak[],
   options: JoinBroadPeaksOptions = {},
 ): GSDPeak[] {
@@ -45,8 +44,10 @@ export function joinBroadPeaks(
   let max = 0;
   let maxI = 0;
   let count = 1;
-  const broadLines: any[] = [];
-  const peaks: any[] = JSON.parse(JSON.stringify(peakList));
+  const broadLines: GSDPeakOptimized[] = [];
+  const peaks = appendShapeAndFWHM(peakList, { shape });
+
+  if (peaks.length < 2) return peaks;
 
   let maxDdy = peakList[0].ddY;
   for (let i = 1; i < peakList.length; i++) {
@@ -59,8 +60,8 @@ export function joinBroadPeaks(
     }
   }
 
-  // Push a feke peak
-  broadLines.push({ x: Number.MAX_VALUE, y: 0, width: 0 });
+  //@ts-expect-error Push a feke peak
+  broadLines.push({ x: Number.MAX_VALUE, y: 0 });
 
   let candidates: { x: number[]; y: number[] } = {
     x: [broadLines[0].x],
@@ -90,10 +91,12 @@ export function joinBroadPeaks(
           ],
           { shape, optimization },
         );
+        //@ts-expect-error type is equal as expected
         peaks.push(fitted[0]);
       } else {
-        // Put back the candidates to the signals list
+        // Put back the candidates to the peak list
         indexes.forEach((index) => {
+          // @ts-expect-error todo 2
           peaks.push(broadLines[index]);
         });
       }

src/post/joinBroadPeaks.ts

@@ -1,4 +1,5 @@
 import type { DataXY } from 'cheminfo-types';
+import { PeakXYWidth } from 'cheminfo-types';
 import { getShape1D, Shape1D } from 'ml-peak-shape-generator';
 import { optimize } from 'ml-spectra-fitting';
 import type { OptimizationOptions } from 'ml-spectra-fitting';
@@ -30,12 +31,6 @@ export interface OptimizePeaksOptions {
   optimization?: OptimizationOptions;
 }
 
-interface XYWidth {
-  x: number;
-  y: number;
-  width: number;
-}
-
 /**
  * Optimize the position (x), max intensity (y), full width at half maximum (fwhm)
  * and the ratio of gaussian contribution (mu) if it's required. It currently supports three kind of shapes: gaussian, lorentzian and pseudovoigt
@@ -44,7 +39,7 @@ interface XYWidth {
  */
 export function optimizePeaks(
   data: DataXY,
-  peakList: XYWidth[],
+  peakList: PeakXYWidth[],
   options: OptimizePeaksOptions = {},
 ): GSDPeakOptimized[] {
   const {