nmr-processing - npm Package Compare versions

Comparing version 1.3.0 to 1.4.0

CHANGELOG.md

 # Changelog
 
+## [1.4.0](https://www.github.com/cheminfo/nmr-processing/compare/v1.3.0...v1.4.0) (2021-05-18)
+
+
+### Features
+
+* add multiplicity when join signals from prediction ([#61](https://www.github.com/cheminfo/nmr-processing/issues/61)) ([e938688](https://www.github.com/cheminfo/nmr-processing/commit/e938688fe6fceaea725b129b602602a7eab37695))
+* add san plot as an option to determine the noise level of 1D spectrum. ([#59](https://www.github.com/cheminfo/nmr-processing/issues/59)) ([0f20e1f](https://www.github.com/cheminfo/nmr-processing/commit/0f20e1f50824747c76f96c832bbb6c89888c7750))
+
 ## [1.3.0](https://www.github.com/cheminfo/nmr-processing/compare/v1.2.0...v1.3.0) (2021-05-11)
@@ -4,0 +12,0 @@

package.json

 {
   "name": "nmr-processing",
-  "version": "1.3.0",
+  "version": "1.4.0",
   "description": "",
@@ -16,2 +16,4 @@ "main": "lib/index.js",
     "prepublishOnly": "rollup -c",
+    "prettier": "prettier --check src",
+    "prettier-write": "prettier --write src",
     "test": "npm run test-coverage && npm run eslint",
@@ -18,0 +20,0 @@ "test-coverage": "jest --coverage",

src/signals/signalsJoin.js

@@ -71,7 +71,13 @@ import mean from 'ml-array-mean';
   newSignals = newSignals
-    .map((signal) =>
-      signalNormalize(signalJoinCouplings(signal, { tolerance })),
-    )
+    .map((signal) => {
+      signal = signalNormalize(signalJoinCouplings(signal, { tolerance }));
+      if (signal.j) {
+        signal.multiplicity = signal.j.reduce((multiplicity, jCoupling) => {
+          return `${multiplicity}${jCoupling.multiplicity}`;
+        }, '');
+      }
+      return signal;
+    })
     .sort((a, b) => a.delta - b.delta);
   return newSignals;
 }

src/xy/xyAutoPeaksPicking.js

 import { gsd, joinBroadPeaks, optimizePeaks } from 'ml-gsd';
-import { xAbsoluteMedian, xyExtract } from 'ml-spectra-processing';
+import {
+  xyExtract,
+  xNoiseSanPlot,
+  xAbsoluteMedian,
+} from 'ml-spectra-processing';
 /**
@@ -30,4 +34,7 @@ * Implementation of the peak picking method described by Cobas in:
     to,
-    minMaxRatio = 0.01,
+    noiseLevel,
+    thresholdFactor = 3,
+    minMaxRatio = 0.05,
     broadRatio = 0.00025,
+    useSanPlot = false,
     smoothY = true,
@@ -41,3 +48,2 @@ optimize = false,
     lookNegative = false,
-    noiseLevel = xAbsoluteMedian(data.y) * (options.thresholdFactor || 3),
     sgOptions = { windowSize: 9, polynomial: 3 },
@@ -50,2 +56,4 @@ } = options;
 
+  const cutOff = getCutOff(data.y, { noiseLevel, useSanPlot, thresholdFactor });
+
   let getPeakOptions = {
@@ -59,3 +67,3 @@ shape,
     broadRatio,
-    noiseLevel,
+    noiseLevel: cutOff.positive,
     smoothY,
@@ -66,6 +74,10 @@ optimization,
 
-  let result = getPeakList(data, getPeakOptions);
-  return lookNegative
-    ? result.concat(getNegativePeaks(data, getPeakOptions))
-    : result;
+  let peaks = getPeakList(data, getPeakOptions);
+
+  if (lookNegative) {
+    getPeakOptions.noiseLevel = cutOff.negative;
+    peaks.push(...getNegativePeaks(data, getPeakOptions));
+  }
+
+  return peaks;
 }
@@ -130,1 +142,18 @@
 }
+
+function getCutOff(data, options = {}) {
+  const { noiseLevel, useSanPlot, thresholdFactor } = options;
+
+  const formatResult = (noiseLevel) =>
+    typeof noiseLevel === 'number'
+      ? { positive: noiseLevel, negative: -noiseLevel }
+      : noiseLevel;
+
+  if (noiseLevel) {
+    return formatResult(noiseLevel);
+  } else {
+    return useSanPlot
+      ? xNoiseSanPlot(data, { factorStd: thresholdFactor })
+      : formatResult(xAbsoluteMedian(data) * thresholdFactor);
+  }
+}

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330188

increased by0.73%

Lines of code

12361

increased by0.44%

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