ml-spectra-fitting - npm Package Compare versions

Comparing version 4.1.0 to 4.1.1

lib-esm/index.d.ts

@@ -16,2 +16,3 @@ import { DataXY, DoubleArray } from 'cheminfo-types';
 export interface Peak {
+    id?: string;
     x: number;
@@ -32,2 +33,7 @@ y: number;
 }
+declare type OptimizedPeakIDOrNot<T extends Peak> = T extends {
+    id: string;
+} ? OptimizedPeak & {
+    id: string;
+} : OptimizedPeak;
 declare type OptimizationParameter = number | ((peak: Peak) => number);
@@ -86,5 +92,5 @@ export interface OptimizationOptions {
  */
-export declare function optimize(data: DataXY<DoubleArray>, peaks: Peak[], options?: OptimizeOptions): {
+export declare function optimize<T extends Peak>(data: DataXY<DoubleArray>, peaks: T[], options?: OptimizeOptions): {
     error: number;
-    peaks: OptimizedPeak[];
+    peaks: OptimizedPeakIDOrNot<T>[];
     iterations: number;
@@ -91,0 +97,0 @@ };

lib-esm/index.js

@@ -51,12 +51,12 @@ import { xMinMaxValues } from 'ml-spectra-processing';
     for (let peak of internalPeaks) {
-        const newPeak = {
-            x: 0,
-            y: 0,
-            shape: peak.shape,
-        };
-        newPeak.x = fittedValues[peak.fromIndex];
-        newPeak.y = fittedValues[peak.fromIndex + 1] * minMaxY.range + shiftValue;
-        for (let i = 2; i < peak.parameters.length; i++) {
+        const { id, shape, parameters, fromIndex } = peak;
+        let newPeak = { x: 0, y: 0, shape };
+        if (id) {
+            newPeak = { ...newPeak, id };
+        }
+        newPeak.x = fittedValues[fromIndex];
+        newPeak.y = fittedValues[fromIndex + 1] * minMaxY.range + shiftValue;
+        for (let i = 2; i < parameters.length; i++) {
             //@ts-expect-error should be fixed once
-            newPeak.shape[peak.parameters[i]] = fittedValues[peak.fromIndex + i];
+            newPeak.shape[parameters[i]] = fittedValues[fromIndex + i];
         }
@@ -63,0 +63,0 @@ newPeaks.push(newPeak);

lib-esm/util/internalPeaks/getInternalPeaks.d.ts

@@ -6,2 +6,3 @@ import { Shape1D, Shape1DInstance } from 'ml-peak-shape-generator';
 export interface InternalPeak {
+    id?: string;
     shape: Shape1D;
@@ -8,0 +9,0 @@ shapeFct: Shape1DInstance;

lib-esm/util/internalPeaks/getInternalPeaks.js

@@ -22,9 +22,4 @@ import { getShape1D } from 'ml-peak-shape-generator';
     for (const peak of normalizedPeaks) {
-        const shape = peak.shape
-            ? peak.shape
-            : options.shape
-                ? options.shape
-                : { kind: 'gaussian' };
+        const { id, shape = options.shape ? options.shape : { kind: 'gaussian' } } = peak;
         const shapeFct = getShape1D(shape);
-        //@ts-expect-error Should disappear with next release of peak-shape-generator
         const parameters = ['x', 'y', ...shapeFct.getParameters()];
@@ -72,2 +67,3 @@ const propertiesValues = {
         internalPeaks.push({
+            id,
             shape,
@@ -74,0 +70,0 @@ shapeFct,

lib/index.d.ts

@@ -16,2 +16,3 @@ import { DataXY, DoubleArray } from 'cheminfo-types';
 export interface Peak {
+    id?: string;
     x: number;
@@ -32,2 +33,7 @@ y: number;
 }
+declare type OptimizedPeakIDOrNot<T extends Peak> = T extends {
+    id: string;
+} ? OptimizedPeak & {
+    id: string;
+} : OptimizedPeak;
 declare type OptimizationParameter = number | ((peak: Peak) => number);
@@ -86,5 +92,5 @@ export interface OptimizationOptions {
  */
-export declare function optimize(data: DataXY<DoubleArray>, peaks: Peak[], options?: OptimizeOptions): {
+export declare function optimize<T extends Peak>(data: DataXY<DoubleArray>, peaks: T[], options?: OptimizeOptions): {
     error: number;
-    peaks: OptimizedPeak[];
+    peaks: OptimizedPeakIDOrNot<T>[];
     iterations: number;
@@ -91,0 +97,0 @@ };

lib/index.js

@@ -54,12 +54,12 @@ "use strict";
     for (let peak of internalPeaks) {
-        const newPeak = {
-            x: 0,
-            y: 0,
-            shape: peak.shape,
-        };
-        newPeak.x = fittedValues[peak.fromIndex];
-        newPeak.y = fittedValues[peak.fromIndex + 1] * minMaxY.range + shiftValue;
-        for (let i = 2; i < peak.parameters.length; i++) {
+        const { id, shape, parameters, fromIndex } = peak;
+        let newPeak = { x: 0, y: 0, shape };
+        if (id) {
+            newPeak = { ...newPeak, id };
+        }
+        newPeak.x = fittedValues[fromIndex];
+        newPeak.y = fittedValues[fromIndex + 1] * minMaxY.range + shiftValue;
+        for (let i = 2; i < parameters.length; i++) {
             //@ts-expect-error should be fixed once
-            newPeak.shape[peak.parameters[i]] = fittedValues[peak.fromIndex + i];
+            newPeak.shape[parameters[i]] = fittedValues[fromIndex + i];
         }
@@ -66,0 +66,0 @@ newPeaks.push(newPeak);

lib/util/internalPeaks/getInternalPeaks.d.ts

@@ -6,2 +6,3 @@ import { Shape1D, Shape1DInstance } from 'ml-peak-shape-generator';
 export interface InternalPeak {
+    id?: string;
     shape: Shape1D;
@@ -8,0 +9,0 @@ shapeFct: Shape1DInstance;

lib/util/internalPeaks/getInternalPeaks.js

@@ -25,9 +25,4 @@ "use strict";
     for (const peak of normalizedPeaks) {
-        const shape = peak.shape
-            ? peak.shape
-            : options.shape
-                ? options.shape
-                : { kind: 'gaussian' };
+        const { id, shape = options.shape ? options.shape : { kind: 'gaussian' } } = peak;
         const shapeFct = (0, ml_peak_shape_generator_1.getShape1D)(shape);
-        //@ts-expect-error Should disappear with next release of peak-shape-generator
         const parameters = ['x', 'y', ...shapeFct.getParameters()];
@@ -75,2 +70,3 @@ const propertiesValues = {
         internalPeaks.push({
+            id,
             shape,
@@ -77,0 +73,0 @@ shapeFct,

package.json

 {
   "name": "ml-spectra-fitting",
-  "version": "4.1.0",
+  "version": "4.1.1",
   "description": "Fit spectra using gaussian or lorentzian",
@@ -65,5 +65,5 @@ "main": "./lib/index.js",
     "ml-levenberg-marquardt": "^4.1.0",
-    "ml-peak-shape-generator": "^4.1.1",
+    "ml-peak-shape-generator": "^4.1.2",
     "ml-spectra-processing": "^11.5.0"
   }
 }

src/__tests__/specifyShapeInOptimize.test.ts

@@ -12,4 +12,14 @@ import type { DataXY } from 'cheminfo-types';
     const peaks = [
-      { x: -0.5, y: 1, shape: { kind: 'gaussian' as const, fwhm: 0.05 } },
-      { x: 0.5, y: 1, shape: { kind: 'gaussian' as const, fwhm: 0.05 } },
+      {
+        id: 'first',
+        x: -0.5,
+        y: 1,
+        shape: { kind: 'gaussian' as const, fwhm: 0.05 },
+      },
+      {
+        id: 'second',
+        x: 0.5,
+        y: 1,
+        shape: { kind: 'gaussian' as const, fwhm: 0.05 },
+      },
     ];
@@ -27,4 +37,14 @@
     let result = optimize(data, [
-      { x: -0.55, y: 0.9, shape: { kind: 'gaussian' as const, fwhm: 0.08 } },
-      { x: 0.55, y: 0.9, shape: { kind: 'gaussian' as const, fwhm: 0.08 } },
+      {
+        id: 'first',
+        x: -0.55,
+        y: 0.9,
+        shape: { kind: 'gaussian' as const, fwhm: 0.08 },
+      },
+      {
+        id: 'second',
+        x: 0.55,
+        y: 0.9,
+        shape: { kind: 'gaussian' as const, fwhm: 0.08 },
+      },
     ]);
@@ -31,0 +51,0 @@

src/index.ts

@@ -23,2 +23,3 @@ import { DataXY, DoubleArray } from 'cheminfo-types';
 export interface Peak {
+  id?: string;
   x: number;
@@ -39,2 +40,6 @@ y: number;
 
+type OptimizedPeakIDOrNot<T extends Peak> = T extends { id: string }
+  ? OptimizedPeak & { id: string }
+  : OptimizedPeak;
+
 type OptimizationParameter = number | ((peak: Peak) => number);
@@ -97,9 +102,9 @@
  */
-export function optimize(
+export function optimize<T extends Peak>(
   data: DataXY<DoubleArray>,
-  peaks: Peak[],
+  peaks: T[],
   options: OptimizeOptions = {},
 ): {
   error: number;
-  peaks: OptimizedPeak[];
+  peaks: OptimizedPeakIDOrNot<T>[];
   iterations: number;
@@ -148,16 +153,18 @@ } {
 
-  let newPeaks: OptimizedPeak[] = [];
+  let newPeaks = [];
   for (let peak of internalPeaks) {
-    const newPeak = {
-      x: 0,
-      y: 0,
-      shape: peak.shape,
-    };
-    newPeak.x = fittedValues[peak.fromIndex];
-    newPeak.y = fittedValues[peak.fromIndex + 1] * minMaxY.range + shiftValue;
-    for (let i = 2; i < peak.parameters.length; i++) {
+    const { id, shape, parameters, fromIndex } = peak;
+
+    let newPeak = { x: 0, y: 0, shape } as OptimizedPeakIDOrNot<T>;
+
+    if (id) {
+      newPeak = { ...newPeak, id } as OptimizedPeakIDOrNot<T>;
+    }
+
+    newPeak.x = fittedValues[fromIndex];
+    newPeak.y = fittedValues[fromIndex + 1] * minMaxY.range + shiftValue;
+    for (let i = 2; i < parameters.length; i++) {
       //@ts-expect-error should be fixed once
-      newPeak.shape[peak.parameters[i]] = fittedValues[peak.fromIndex + i];
+      newPeak.shape[parameters[i]] = fittedValues[fromIndex + i];
     }
-
     newPeaks.push(newPeak);
@@ -164,0 +171,0 @@ }

src/util/internalPeaks/getInternalPeaks.ts

@@ -13,2 +13,3 @@ import { getShape1D, Shape1D, Shape1DInstance } from 'ml-peak-shape-generator';
 export interface InternalPeak {
+  id?: string;
   shape: Shape1D;
@@ -45,11 +46,7 @@ shapeFct: Shape1DInstance;
   for (const peak of normalizedPeaks) {
-    const shape: Shape1D = peak.shape
-      ? peak.shape
-      : options.shape
-      ? options.shape
-      : { kind: 'gaussian' };
+    const { id, shape = options.shape ? options.shape : { kind: 'gaussian' } } =
+      peak;
 
     const shapeFct: Shape1DInstance = getShape1D(shape);
 
-    //@ts-expect-error Should disappear with next release of peak-shape-generator
     const parameters: Parameter[] = ['x', 'y', ...shapeFct.getParameters()];
@@ -125,2 +122,3 @@
     internalPeaks.push({
+      id,
       shape,
@@ -127,0 +125,0 @@ shapeFct,

No alert changes

Improved metrics

Total package byte prevSize

103410

1.11%

Lines of code

2034

1.4%

Dependency changes

• Updated

  ml-peak-shape-generator@^4.1.2