ml-spectra-processing - npm Package Compare versions

Comparing version 4.10.0 to 4.11.0

CHANGELOG.md

 # Changelog
 
+## [4.11.0](https://www.github.com/mljs/spectra-processing/compare/v4.10.0...v4.11.0) (2021-01-08)
+
+
+### Features
+
+* add createSequentialArray ([649547d](https://www.github.com/mljs/spectra-processing/commit/649547d48c51f8b4ce95553824ed8b92b6b17040))
+* add xParetoNormalization ([ec0c517](https://www.github.com/mljs/spectra-processing/commit/ec0c5170f097fb0d4e8ed2a05e8aa96c5a4062b4))
+
+
+### Bug Fixes
+
+* change mean by median close[#32](https://www.github.com/mljs/spectra-processing/issues/32) ([#40](https://www.github.com/mljs/spectra-processing/issues/40)) ([9272c73](https://www.github.com/mljs/spectra-processing/commit/9272c7373b930567ee5ca2ab01ca746af495e8bc))
+
 ## [4.10.0](https://www.github.com/mljs/spectra-processing/compare/v4.9.4...v4.10.0) (2020-12-08)
@@ -4,0 +17,0 @@

package.json

 {
   "name": "ml-spectra-processing",
-  "version": "4.10.0",
+  "version": "4.11.0",
   "description": "Various method to process spectra",
@@ -44,5 +44,5 @@ "main": "lib/index.js",
     "@babel/plugin-transform-modules-commonjs": "^7.12.1",
-    "@types/jest": "^26.0.15",
+    "@types/jest": "^26.0.20",
     "cheminfo-build": "^1.1.8",
-    "eslint": "^7.13.0",
+    "eslint": "^7.17.0",
     "eslint-config-cheminfo": "^5.2.2",
@@ -52,4 +52,4 @@ "esm": "^3.2.25",
     "jest-matcher-deep-close-to": "^2.0.1",
-    "prettier": "^2.1.2",
-    "rollup": "^2.33.3"
+    "prettier": "^2.2.1",
+    "rollup": "^2.36.1"
   },
@@ -61,6 +61,7 @@ "dependencies": {
     "ml-array-median": "^1.1.4",
-    "ml-gsd": "^6.1.2",
-    "ml-matrix": "^6.5.3",
+    "ml-array-standard-deviation": "^1.1.5",
+    "ml-gsd": "^6.4.0",
+    "ml-matrix": "^6.6.0",
     "spline-interpolator": "^1.0.0"
   }
 }

src/index.js

@@ -44,2 +44,3 @@ /**
 export * from './x/xNorm';
+export * from './x/xParetoNormalization';
 export * from './x/xPadding';
@@ -102,1 +103,3 @@ export * from './x/xRotate';
 export * from './matrix/probabilisticQuotientNormalization';
+
+export * from './utils/createSequentialArray';

src/matrix/probabilisticQuotientNormalization.js

@@ -1,2 +0,2 @@
-import mean from 'ml-array-mean';
+import median from 'ml-array-median';
 import { Matrix } from 'ml-matrix';
@@ -11,40 +11,35 @@
  * @param {number} [options.max=100] - Normalization integral constant.
- * @return {Object} { data, averageQuotients }.
+ * @return {Object} { data, medianOfQuotients }.
  * data: Normalized dataset.
- * averageQuotients: The quotients of all variables of interest.
+ * medianOfQuotients: The median of quotients of each variables.
  */
 export function probabilisticQuotientNormalization(matrix, options = {}) {
-  let { max = 100 } = options;
+  const { max = 100 } = options;
   matrix = new Matrix(matrix);
   for (let i = 0; i < matrix.rows; i++) {
-    let row = matrix.getRowVector(i).div(matrix.getRowVector(i).norm() / max);
+    const normalizationFactor = matrix.getRowVector(i).norm() / max;
+    const row = matrix.getRowVector(i).div(normalizationFactor);
     matrix.setRow(i, row);
   }
-  let normalizationFactor = matrix.norm() / max;
-  matrix.div(normalizationFactor);
+
   let referenceSpectrum = [];
   for (let i = 0; i < matrix.columns; i++) {
-    let currentVariable = [];
-    for (let j = 0; j < matrix.rows; j++) {
-      currentVariable.push(matrix.get(j, i));
-    }
-    referenceSpectrum.push(mean(currentVariable));
+    const currentVariable = matrix.getColumn(i);
+    referenceSpectrum.push(median(currentVariable));
   }
-  let averageQuotients = [];
-  for (let i = 0; i < matrix.rows; i++) {
-    let quotients = [];
-    for (let j = 0; j < matrix.columns; j++) {
-      let quotient = matrix.get(i, j) / referenceSpectrum[j];
-      quotients.push(quotient);
-    }
-    averageQuotients.push(mean(quotients));
+
+  let medianOfQuotients = [];
+  for (let i = 0; i < matrix.columns; i++) {
+    let quotients = matrix.getColumnVector(i).div(referenceSpectrum[i]);
+    medianOfQuotients.push(median(quotients.getColumn(0)));
   }
 
   for (let i = 0; i < matrix.rows; i++) {
-    matrix.mulRow(i, averageQuotients[i]);
+    matrix.mulRow(i, 1 / medianOfQuotients[i]);
   }
+
   return {
     data: matrix,
-    averageQuotients: averageQuotients,
+    medianOfQuotients: medianOfQuotients,
   };
 }

src/reim/reimAutoPhaseCorrection.js

@@ -192,4 +192,4 @@ import { xNoiseSanPlot } from '../x/xNoiseSanPlot';
   /* Just to know what is the matrix system that we solve
-   let Mx = [[sxtw, swx], [swx, sw]];
-   let My = [[sxtwy], [swy]];
+   let Mx=[[sxtw, swx], [swx, sw]];
+   let My=[[sxtwy], [swy]];
   */
@@ -196,0 +196,0 @@

src/reim/reimPhaseCorrection.js

 /**
  * Phase correction filter
  * @param {object} reim - An object of kind {re:[], im:[]}
- * @param {number} [phi0 = 0] - Angle in radians for zero order phase correction
- * @param {number} [phi1 = 0] - Angle in radians for first order phase correction
+ * @param {number} [phi0=0] - Angle in radians for zero order phase correction
+ * @param {number} [phi1=0] - Angle in radians for first order phase correction
  * @return {object} returns a new object {re:[], im:[]}
@@ -7,0 +7,0 @@ */

src/x/erfcinv.js

@@ -218,3 +218,3 @@ /* eslint-disable no-loss-of-precision */
   }
-  // [2] Get the sign and make use of `erfc` reflection formula: `erfc(-z) = 2 - erfc(z)`...
+  // [2] Get the sign and make use of `erfc` reflection formula: `erfc(-z)=2 - erfc(z)`...
   if (x > 1) {
@@ -221,0 +221,0 @@ q = 2 - x;

src/x/xAutoCorrelation.js

@@ -7,4 +7,4 @@ import { xCrossCorrelation } from './xCrossCorrelation';
  * @param {object} [options={}]
- * @param {number} [options.tau = 1] - sweep increment size (in number of points, min = 1, max = A.length)
- * @param {number} [options.lag = A.length - 1] - scalar lag parameter
+ * @param {number} [options.tau=1] - sweep increment size (in number of points, min=1, max=A.length)
+ * @param {number} [options.lag=A.length - 1] - scalar lag parameter
  */
@@ -11,0 +11,0 @@

src/x/xCrossCorrelation.js

@@ -8,4 +8,4 @@ import { xDotProduct } from './xDotProduct';
  * @param {object} [options={}]
- * @param {number} [options.tau = 1] - sweep increment size (in number of points, min = 1, max = A.length)
- * @param {number} [options.lag = A.length - 1] - scalar lag parameter
+ * @param {number} [options.tau=1] - sweep increment size (in number of points, min=1, max=A.length)
+ * @param {number} [options.lag=A.length - 1] - scalar lag parameter
  */
@@ -12,0 +12,0 @@

src/xy/xyAlign.js

@@ -7,7 +7,7 @@ /**
  * @param {DataXY} spectrum2 Second spectrum data
- * @param {object} options
- * @param {number} [options.delta = 1] The range in which the two x values of the spectra must be to be placed on the same line
- * @param {boolean} [options.common = true] If `true`, only the data considered as common to both spectra is kept. If `false`, the data y arrays are completed with zeroes where no common values are found
- * @param {string} [options.x = 'x1'] Defines what x values should be kept (`x1` : spectrum 1 x values, `x2` spectrum 2 x values, `weighted`: weighted average of both spectra x values)
- * @param {function} [options.weightFunction = undefined] Function that allows to weight `delta` depending on the X values of the spectrum
+ * @param {object} [options={}]
+ * @param {number} [options.delta=1] The range in which the two x values of the spectra must be to be placed on the same line
+ * @param {boolean} [options.common=true] If `true`, only the data considered as common to both spectra is kept. If `false`, the data y arrays are completed with zeroes where no common values are found
+ * @param {string} [options.x='x1'] Defines what x values should be kept (`x1` : spectrum 1 x values, `x2` spectrum 2 x values, `weighted`: weighted average of both spectra x values)
+ * @param {function} [options.weightFunction=undefined] Function that allows to weight `delta` depending on the X values of the spectrum
  */
@@ -14,0 +14,0 @@ export function xyAlign(spectrum1, spectrum2, options = {}) {

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Improved metrics

Total package byte prevSize

188056

increased by1.58%

Number of package files

79

increased by2.6%

Lines of code

5287

increased by1.03%

Worsened metrics

Dependency count

8

increased by14.29%

Dependency changes

• + Addedml-array-standard-deviation@^1.1.5

• Updatedml-gsd@^6.4.0

• Updatedml-matrix@^6.6.0