ml-peak-shape-generator - npm Package Compare versions

Comparing version 4.1.3 to 4.1.4

CHANGELOG.md

 # Changelog
 
+### [4.1.4](https://www.github.com/mljs/peak-shape-generator/compare/v4.1.3...v4.1.4) (2024-09-26)
+
+
+### Bug Fixes
+
+* correct fwhm for generalized lorentzian ([#78](https://www.github.com/mljs/peak-shape-generator/issues/78)) ([515b882](https://www.github.com/mljs/peak-shape-generator/commit/515b8828c06f0d4babd42275881a4c47c74de021))
+
 ### [4.1.3](https://www.github.com/mljs/peak-shape-generator/compare/v4.1.2...v4.1.3) (2024-09-24)
@@ -4,0 +11,0 @@

lib-esm/shapes/1d/generalizedLorentzian/GeneralizedLorentzian.js

 import { ROOT_THREE } from '../../../util/constants';
+/**
+ * This shape is a linear combination of rational function (n|n+2), for n = 0 (lorentzian function) and n = 2
+ * the parameter that combines those two functions is `gamma` and it is called the kurtosis parameter, it is an
+ * implementation of generalized lorentzian shape published by Stanislav Sykora in the SMASH 2010. DOI:10.3247/SL3nmr10.006
+ * @link http://www.ebyte.it/stan/Talk_ML_UserMeeting_SMASH_2010_GeneralizedLorentzian.html
+ */
 export class GeneralizedLorentzian {
@@ -39,3 +45,3 @@ constructor(options = {}) {
 export const calculateGeneralizedLorentzianHeight = ({ fwhm = 1, gamma = 1, area = 1, }) => {
-    return area / fwhm / (3.14159 - 0.420894 * gamma) / 2;
+    return (area / fwhm / (3.14159 - 0.420894 * gamma)) * 2;
 };
@@ -47,6 +53,6 @@ /**
     const { fwhm = 500, height = 1, gamma = 1 } = options;
-    return 2 * height * fwhm * (3.14159 - 0.420894 * gamma);
+    return (height * fwhm * (3.14159 - 0.420894 * gamma)) / 2;
 };
 export const generalizedLorentzianFct = (x, fwhm, gamma) => {
-    const u = (x / 2 / fwhm) ** 2;
+    const u = ((2 * x) / fwhm) ** 2;
     return (1 - gamma) / (1 + u) + (gamma * (1 + u / 2)) / (1 + u + u ** 2);
@@ -70,3 +76,3 @@ };
     let { fwhm = 500, gamma = 1 } = shape;
-    let { length, factor = getGeneralizedLorentzianFactor(), height = 1, } = options;
+    let { length, factor = getGeneralizedLorentzianFactor(), height = calculateGeneralizedLorentzianHeight({ fwhm, area: 1, gamma }), } = options;
     if (!length) {
@@ -73,0 +79,0 @@ length = Math.min(Math.ceil(fwhm * factor), Math.pow(2, 25) - 1);

lib/shapes/1d/gaussian/Gaussian.d.ts

@@ -39,3 +39,3 @@ import type { GetData1DOptions } from '../GetData1DOptions';
     /**
-     * The halft width between the inflection points or standard deviation.
+     * The half width between the inflection points or standard deviation.
      * If it is defined the fwhm would be re-assigned.
@@ -42,0 +42,0 @@ */

lib/shapes/1d/generalizedLorentzian/GeneralizedLorentzian.d.ts

@@ -29,2 +29,8 @@ import type { GetData1DOptions } from '../GetData1DOptions';
 }
+/**
+ * This shape is a linear combination of rational function (n|n+2), for n = 0 (lorentzian function) and n = 2
+ * the parameter that combines those two functions is `gamma` and it is called the kurtosis parameter, it is an
+ * implementation of generalized lorentzian shape published by Stanislav Sykora in the SMASH 2010. DOI:10.3247/SL3nmr10.006
+ * @link http://www.ebyte.it/stan/Talk_ML_UserMeeting_SMASH_2010_GeneralizedLorentzian.html
+ */
 export declare class GeneralizedLorentzian implements Shape1DClass {
@@ -31,0 +37,0 @@ /**

lib/shapes/1d/generalizedLorentzian/GeneralizedLorentzian.js

@@ -5,2 +5,8 @@ "use strict";
 const constants_1 = require("../../../util/constants");
+/**
+ * This shape is a linear combination of rational function (n|n+2), for n = 0 (lorentzian function) and n = 2
+ * the parameter that combines those two functions is `gamma` and it is called the kurtosis parameter, it is an
+ * implementation of generalized lorentzian shape published by Stanislav Sykora in the SMASH 2010. DOI:10.3247/SL3nmr10.006
+ * @link http://www.ebyte.it/stan/Talk_ML_UserMeeting_SMASH_2010_GeneralizedLorentzian.html
+ */
 class GeneralizedLorentzian {
@@ -44,3 +50,3 @@ constructor(options = {}) {
 const calculateGeneralizedLorentzianHeight = ({ fwhm = 1, gamma = 1, area = 1, }) => {
-    return area / fwhm / (3.14159 - 0.420894 * gamma) / 2;
+    return (area / fwhm / (3.14159 - 0.420894 * gamma)) * 2;
 };
@@ -53,7 +59,7 @@ exports.calculateGeneralizedLorentzianHeight = calculateGeneralizedLorentzianHeight;
     const { fwhm = 500, height = 1, gamma = 1 } = options;
-    return 2 * height * fwhm * (3.14159 - 0.420894 * gamma);
+    return (height * fwhm * (3.14159 - 0.420894 * gamma)) / 2;
 };
 exports.getGeneralizedLorentzianArea = getGeneralizedLorentzianArea;
 const generalizedLorentzianFct = (x, fwhm, gamma) => {
-    const u = (x / 2 / fwhm) ** 2;
+    const u = ((2 * x) / fwhm) ** 2;
     return (1 - gamma) / (1 + u) + (gamma * (1 + u / 2)) / (1 + u + u ** 2);
@@ -81,3 +87,3 @@ };
     let { fwhm = 500, gamma = 1 } = shape;
-    let { length, factor = (0, exports.getGeneralizedLorentzianFactor)(), height = 1, } = options;
+    let { length, factor = (0, exports.getGeneralizedLorentzianFactor)(), height = (0, exports.calculateGeneralizedLorentzianHeight)({ fwhm, area: 1, gamma }), } = options;
     if (!length) {
@@ -84,0 +90,0 @@ length = Math.min(Math.ceil(fwhm * factor), Math.pow(2, 25) - 1);

package.json

 {
   "name": "ml-peak-shape-generator",
-  "version": "4.1.3",
+  "version": "4.1.4",
   "description": "Generate various peak shapes",
@@ -5,0 +5,0 @@ "main": "./lib/index.js",

src/shapes/1d/gaussian/Gaussian.ts

@@ -48,3 +48,3 @@ import {
   /**
-   * The halft width between the inflection points or standard deviation.
+   * The half width between the inflection points or standard deviation.
    * If it is defined the fwhm would be re-assigned.
@@ -51,0 +51,0 @@ */

src/shapes/1d/generalizedLorentzian/GeneralizedLorentzian.ts

@@ -33,2 +33,8 @@ import { ROOT_THREE } from '../../../util/constants';
 
+/**
+ * This shape is a linear combination of rational function (n|n+2), for n = 0 (lorentzian function) and n = 2
+ * the parameter that combines those two functions is `gamma` and it is called the kurtosis parameter, it is an
+ * implementation of generalized lorentzian shape published by Stanislav Sykora in the SMASH 2010. DOI:10.3247/SL3nmr10.006
+ * @link http://www.ebyte.it/stan/Talk_ML_UserMeeting_SMASH_2010_GeneralizedLorentzian.html
+ */
 export class GeneralizedLorentzian implements Shape1DClass {
@@ -96,3 +102,3 @@ /**
 }) => {
-  return area / fwhm / (3.14159 - 0.420894 * gamma) / 2;
+  return (area / fwhm / (3.14159 - 0.420894 * gamma)) * 2;
 };
@@ -107,3 +113,3 @@
   const { fwhm = 500, height = 1, gamma = 1 } = options;
-  return 2 * height * fwhm * (3.14159 - 0.420894 * gamma);
+  return (height * fwhm * (3.14159 - 0.420894 * gamma)) / 2;
 };
@@ -116,3 +122,3 @@
 ) => {
-  const u = (x / 2 / fwhm) ** 2;
+  const u = ((2 * x) / fwhm) ** 2;
   return (1 - gamma) / (1 + u) + (gamma * (1 + u / 2)) / (1 + u + u ** 2);
@@ -152,3 +158,3 @@ };
     factor = getGeneralizedLorentzianFactor(),
-    height = 1,
+    height = calculateGeneralizedLorentzianHeight({ fwhm, area: 1, gamma }),
   } = options;
@@ -155,0 +161,0 @@

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Improved metrics

Total package byte prevSize

157964

increased by1.64%

Lines of code

2604

increased by0.93%

No dependency changes