ml-spectra-fitting - npm Package Compare versions

Comparing version 0.8.0 to 0.9.0

CHANGELOG.md

 # Changelog
 
+## [0.9.0](https://www.github.com/mljs/spectra-fitting/compare/v0.8.0...v0.9.0) (2020-12-04)
+
+
+### Features
+
+* update ml-levenberg-marquardt and adapt to the new version ([#41](https://www.github.com/mljs/spectra-fitting/issues/41)) ([9773585](https://www.github.com/mljs/spectra-fitting/commit/9773585e691edffff06617742800ced62042d557))
+
 ## [0.8.0](https://www.github.com/mljs/spectra-fitting/compare/v0.7.1...v0.8.0) (2020-11-18)
@@ -4,0 +11,0 @@

lib/index.js

@@ -122,2 +122,3 @@ 'use strict';
 const STATE_MAX = 2;
+const STATE_GS = 3;
 
@@ -151,3 +152,6 @@ const keys = ['x', 'y', 'width', 'mu'];
   let maxY = getMaxValue__default['default'](data.y);
-  let y = data.y.map((e) => (e /= maxY));
+  let y = new Array(x.length);
+  for (let i = 0; i < x.length; i++) {
+    y[i] = data.y[i] / maxY;
+  }
 
@@ -173,13 +177,22 @@ let nbParams;
 
-  let pInit = new Float64Array(peaks.length * nbParams);
-  let pMin = new Float64Array(peaks.length * nbParams);
-  let pMax = new Float64Array(peaks.length * nbParams);
+  let nbShapes = peaks.length;
+  let pInit = new Float64Array(nbShapes * nbParams);
+  let pMin = new Float64Array(nbShapes * nbParams);
+  let pMax = new Float64Array(nbShapes * nbParams);
+  let gradientDifference = new Float64Array(nbShapes * nbParams);
   let deltaX = Math.abs(data.x[0] - data.x[1]);
 
-  for (let i = 0; i < peaks.length; i++) {
+  for (let i = 0; i < nbShapes; i++) {
     let peak = peaks[i];
     for (let s = 0; s < nbParams; s++) {
-      pInit[i + s * peaks.length] = getValue(s, peak, STATE_INIT, deltaX);
-      pMin[i + s * peaks.length] = getValue(s, peak, STATE_MIN, deltaX);
-      pMax[i + s * peaks.length] = getValue(s, peak, STATE_MAX, deltaX);
+      pInit[i + s * nbShapes] = getValue(s, peak, STATE_INIT, deltaX, maxY);
+      pMin[i + s * nbShapes] = getValue(s, peak, STATE_MIN, deltaX, maxY);
+      pMax[i + s * nbShapes] = getValue(s, peak, STATE_MAX, deltaX, maxY);
+      gradientDifference[i + s * nbShapes] = getValue(
+        s,
+        peak,
+        STATE_GS,
+        deltaX,
+        maxY,
+      );
     }
@@ -193,2 +206,3 @@ }
   optimizationOptions.initialValues = pInit;
+  optimizationOptions.gradientDifference = gradientDifference;
 
@@ -209,3 +223,3 @@ let pFit = algorithm({ x, y }, paramsFunc, optimizationOptions);
 
-function getValue(parameterIndex, peak, key, dt) {
+function getValue(parameterIndex, peak, key, dt, maxY) {
   let value;
@@ -217,2 +231,4 @@ switch (parameterIndex) {
           ? peak.x
+          : key === STATE_GS
+          ? dt / 1000
           : key === STATE_MIN
@@ -223,3 +239,10 @@ ? peak.x - dt
     case 1:
-      value = key === STATE_INIT ? peak.y : key === STATE_MIN ? 0 : 1.5;
+      value =
+        key === STATE_INIT
+          ? peak.y / maxY
+          : key === STATE_GS
+          ? 1e-3
+          : key === STATE_MIN
+          ? 0
+          : 1.5;
       break;
@@ -230,2 +253,4 @@ case 2:
           ? peak.width
+          : key === STATE_GS
+          ? dt / 1000
           : key === STATE_MIN
@@ -236,3 +261,10 @@ ? peak.width / 4
     default:
-      value = key === STATE_INIT ? 0.5 : key === STATE_MIN ? 0 : 1;
+      value =
+        key === STATE_INIT
+          ? 0.5
+          : key === STATE_GS
+          ? 0.01
+          : key === STATE_MIN
+          ? 0
+          : 1;
   }
@@ -239,0 +271,0 @@ return value;

package.json

 {
   "name": "ml-spectra-fitting",
-  "version": "0.8.0",
+  "version": "0.9.0",
   "description": "Fit spectra using gaussian or lorentzian",
@@ -57,13 +57,13 @@ "main": "lib/index.js",
     "eslint-plugin-prettier": "^3.1.4",
+    "esm": "^3.2.25",
     "jest": "^26.6.3",
     "prettier": "^2.1.2",
-    "rollup": "^2.33.1"
+    "rollup": "^2.33.1",
+    "spectrum-generator": "^4.4.1"
   },
   "dependencies": {
-    "esm": "^3.2.25",
     "ml-array-max": "^1.2.0",
-    "ml-levenberg-marquardt": "^2.1.1",
-    "ml-peak-shape-generator": "^0.10.0",
-    "spectrum-generator": "^4.4.0"
+    "ml-levenberg-marquardt": "^3.0.1",
+    "ml-peak-shape-generator": "^0.10.0"
   }
 }

src/__tests__/optimize.test.js

@@ -81,3 +81,3 @@ import { optimize } from '../index';
           kind: 'lm',
-          options: { maxIterations: 300, damping: 1 },
+          options: { maxIterations: 300, damping: 0.5, errorTolerance: 1e-8 },
         },
@@ -84,0 +84,0 @@ },

src/index.js

@@ -12,2 +12,3 @@ import getMaxValue from 'ml-array-max';
 const STATE_MAX = 2;
+const STATE_GS = 3;
 
@@ -41,3 +42,6 @@ const keys = ['x', 'y', 'width', 'mu'];
   let maxY = getMaxValue(data.y);
-  let y = data.y.map((e) => (e /= maxY));
+  let y = new Array(x.length);
+  for (let i = 0; i < x.length; i++) {
+    y[i] = data.y[i] / maxY;
+  }
 
@@ -63,13 +67,22 @@ let nbParams;
 
-  let pInit = new Float64Array(peaks.length * nbParams);
-  let pMin = new Float64Array(peaks.length * nbParams);
-  let pMax = new Float64Array(peaks.length * nbParams);
+  let nbShapes = peaks.length;
+  let pInit = new Float64Array(nbShapes * nbParams);
+  let pMin = new Float64Array(nbShapes * nbParams);
+  let pMax = new Float64Array(nbShapes * nbParams);
+  let gradientDifference = new Float64Array(nbShapes * nbParams);
   let deltaX = Math.abs(data.x[0] - data.x[1]);
 
-  for (let i = 0; i < peaks.length; i++) {
+  for (let i = 0; i < nbShapes; i++) {
     let peak = peaks[i];
     for (let s = 0; s < nbParams; s++) {
-      pInit[i + s * peaks.length] = getValue(s, peak, STATE_INIT, deltaX);
-      pMin[i + s * peaks.length] = getValue(s, peak, STATE_MIN, deltaX);
-      pMax[i + s * peaks.length] = getValue(s, peak, STATE_MAX, deltaX);
+      pInit[i + s * nbShapes] = getValue(s, peak, STATE_INIT, deltaX, maxY);
+      pMin[i + s * nbShapes] = getValue(s, peak, STATE_MIN, deltaX, maxY);
+      pMax[i + s * nbShapes] = getValue(s, peak, STATE_MAX, deltaX, maxY);
+      gradientDifference[i + s * nbShapes] = getValue(
+        s,
+        peak,
+        STATE_GS,
+        deltaX,
+        maxY,
+      );
     }
@@ -83,2 +96,3 @@ }
   optimizationOptions.initialValues = pInit;
+  optimizationOptions.gradientDifference = gradientDifference;
 
@@ -99,3 +113,3 @@ let pFit = algorithm({ x, y }, paramsFunc, optimizationOptions);
 
-function getValue(parameterIndex, peak, key, dt) {
+function getValue(parameterIndex, peak, key, dt, maxY) {
   let value;
@@ -107,2 +121,4 @@ switch (parameterIndex) {
           ? peak.x
+          : key === STATE_GS
+          ? dt / 1000
           : key === STATE_MIN
@@ -113,3 +129,10 @@ ? peak.x - dt
     case 1:
-      value = key === STATE_INIT ? peak.y : key === STATE_MIN ? 0 : 1.5;
+      value =
+        key === STATE_INIT
+          ? peak.y / maxY
+          : key === STATE_GS
+          ? 1e-3
+          : key === STATE_MIN
+          ? 0
+          : 1.5;
       break;
@@ -120,2 +143,4 @@ case 2:
           ? peak.width
+          : key === STATE_GS
+          ? dt / 1000
           : key === STATE_MIN
@@ -126,5 +151,12 @@ ? peak.width / 4
     default:
-      value = key === STATE_INIT ? 0.5 : key === STATE_MIN ? 0 : 1;
+      value =
+        key === STATE_INIT
+          ? 0.5
+          : key === STATE_GS
+          ? 0.01
+          : key === STATE_MIN
+          ? 0
+          : 1;
   }
   return value;
 }

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Improved metrics

Total package byte prevSize

30636

increased by5.89%

Dependency count

3

decreased by-40%

Lines of code

578

increased by12.45%

Worsened metrics

Dev dependency count

13

increased by18.18%

Dependency changes

• + Addedis-any-array@1.0.1(transitive)

• + Addedml-levenberg-marquardt@3.1.1(transitive)

• - Removedesm@^3.2.25

• - Removedspectrum-generator@^4.4.0

• - Removedd3-random@2.2.2(transitive)

• - Removedesm@3.2.25(transitive)

• - Removedis-any-array@0.1.1(transitive)

• - Removedml-levenberg-marquardt@2.1.1(transitive)

• - Removedml-peak-shape-generator@1.0.0(transitive)

• - Removedml-xsadd@2.0.0(transitive)

• - Removedspectrum-generator@4.8.1(transitive)

• Updatedml-levenberg-marquardt@^3.0.1