ml-optimize-lorentzian - npm Package Compare versions

Comparing version 0.1.5 to 0.2.0

History.md

@@ -0,1 +1,5 @@
+# [0.2.0](https://github.com/mljs/optimize-lorentzian/compare/v0.1.5...v0.2.0) (2020-05-19)
+
+
+
 ## [0.1.5](https://github.com/mljs/optimize-lorentzian/compare/v0.1.4...v0.1.5) (2020-05-06)
@@ -2,0 +6,0 @@

lib/index.js

@@ -89,3 +89,3 @@ 'use strict';
     maxValues: pMax,
-    gradientDifference: 10e-2,
+    gradientDifference: dt / 10000,
     maxIterations: 100,
@@ -161,8 +161,8 @@ errorTolerance: 10e-5,
     pMin[i] = group[i].x - dt;
-    pMin[i + nL] = (group[i].y * 0.8) / maxY;
-    pMin[i + 2 * nL] = group[i].width / 2;
+    pMin[i + nL] = 0;
+    pMin[i + 2 * nL] = group[i].width / 4;
 
     pMax[i] = group[i].x + dt;
     pMax[i + nL] = (group[i].y * 1.2) / maxY;
-    pMax[i + 2 * nL] = group[i].width * 2;
+    pMax[i + 2 * nL] = group[i].width * 4;
   }
@@ -181,3 +181,3 @@
     maxValues: pMax,
-    gradientDifference: 10e-2,
+    gradientDifference: dt / 10000,
     maxIterations: 100,
@@ -195,3 +195,3 @@ errorTolerance: 10e-5,
         pFit.parameterValues[i + nL] * maxY,
-        pFit.parameterValues[i + nL + 2],
+        pFit.parameterValues[i + nL * 2],
       ],
@@ -237,3 +237,3 @@ error: pFit.parameterError,
   let pInit = new Float64Array([peak.x, 1, peak.width]);
-  let pMin = new Float64Array([peak.x - dt, 0.75, peak.width / 4]);
+  let pMin = new Float64Array([peak.x - dt, 0, peak.width / 4]);
   let pMax = new Float64Array([peak.x + dt, 1.25, peak.width * 4]);
@@ -251,3 +251,3 @@
     maxValues: pMax,
-    gradientDifference: 10e-2,
+    gradientDifference: dt / 10000,
     maxIterations: 100,
@@ -388,3 +388,3 @@ errorTolerance: 10e-5,
     maxValues: pMax,
-    gradientDifference: 10e-2,
+    gradientDifference: dt / 10000,
     maxIterations: 100,
@@ -402,3 +402,3 @@ errorTolerance: 10e-5,
         pFit.parameterValues[i + nL] * maxY,
-        pFit.parameterValues[i + nL + 2],
+        pFit.parameterValues[i + nL * 2],
       ],
@@ -457,3 +457,3 @@ error: pFit.parameterError,
     maxValues: pMax,
-    gradientDifference: 10e-2,
+    gradientDifference: dt / 10000,
     maxIterations: 100,
@@ -460,0 +460,0 @@ errorTolerance: 10e-5,

package.json

 {
   "name": "ml-optimize-lorentzian",
-  "version": "0.1.5",
+  "version": "0.2.0",
   "description": "Optimize Lorentzian",
@@ -5,0 +5,0 @@ "main": "lib/index.js",

src/optimizeGaussianLorentzianSum.js

@@ -45,3 +45,3 @@ import LM from 'ml-levenberg-marquardt';
     maxValues: pMax,
-    gradientDifference: 10e-2,
+    gradientDifference: dt / 10000,
     maxIterations: 100,
@@ -48,0 +48,0 @@ errorTolerance: 10e-5,

src/optimizeGaussianSum.js

@@ -28,8 +28,8 @@ import LM from 'ml-levenberg-marquardt';
     pMin[i] = group[i].x - dt;
-    pMin[i + nL] = (group[i].y * 0.8) / maxY;
-    pMin[i + 2 * nL] = group[i].width / 2;
+    pMin[i + nL] = 0;
+    pMin[i + 2 * nL] = group[i].width / 4;
 
     pMax[i] = group[i].x + dt;
     pMax[i + nL] = (group[i].y * 1.2) / maxY;
-    pMax[i + 2 * nL] = group[i].width * 2;
+    pMax[i + 2 * nL] = group[i].width * 4;
   }
@@ -48,3 +48,3 @@
     maxValues: pMax,
-    gradientDifference: 10e-2,
+    gradientDifference: dt / 10000,
     maxIterations: 100,
@@ -62,3 +62,3 @@ errorTolerance: 10e-5,
         pFit.parameterValues[i + nL] * maxY,
-        pFit.parameterValues[i + nL + 2],
+        pFit.parameterValues[i + nL * 2],
       ],
@@ -65,0 +65,0 @@ error: pFit.parameterError,

src/optimizeLorentzianSum.js

@@ -49,3 +49,3 @@ import LM from 'ml-levenberg-marquardt';
     maxValues: pMax,
-    gradientDifference: 10e-2,
+    gradientDifference: dt / 10000,
     maxIterations: 100,
@@ -63,3 +63,3 @@ errorTolerance: 10e-5,
         pFit.parameterValues[i + nL] * maxY,
-        pFit.parameterValues[i + nL + 2],
+        pFit.parameterValues[i + nL * 2],
       ],
@@ -66,0 +66,0 @@ error: pFit.parameterError,

src/optimizeSingleGaussian.js

@@ -17,3 +17,3 @@ import LM from 'ml-levenberg-marquardt';
   let pInit = new Float64Array([peak.x, 1, peak.width]);
-  let pMin = new Float64Array([peak.x - dt, 0.75, peak.width / 4]);
+  let pMin = new Float64Array([peak.x - dt, 0, peak.width / 4]);
   let pMax = new Float64Array([peak.x + dt, 1.25, peak.width * 4]);
@@ -31,3 +31,3 @@
     maxValues: pMax,
-    gradientDifference: 10e-2,
+    gradientDifference: dt / 10000,
     maxIterations: 100,
@@ -34,0 +34,0 @@ errorTolerance: 10e-5,

src/optimizeSingleLorentzian.js

@@ -30,3 +30,3 @@ import LM from 'ml-levenberg-marquardt';
     maxValues: pMax,
-    gradientDifference: 10e-2,
+    gradientDifference: dt / 10000,
     maxIterations: 100,
@@ -33,0 +33,0 @@ errorTolerance: 10e-5,

Fixed alerts

Major refactor

Supply chain risk

Package has recently undergone a major refactor. It may be unstable or indicate significant internal changes. Use caution when updating to versions that include significant changes.

Found 1 instance in 1 package

Improved metrics

Total package byte prevSize

39067

increased by0.23%

Number of medium supply chain risk alerts

0

decreased by-100%

No dependency changes