ml-array-utils - npm Package Compare versions

Comparing version 0.1.2 to 0.1.3

package.json

 {
   "name": "ml-array-utils",
-  "version": "0.1.2",
+  "version": "0.1.3",
   "description": "",
@@ -5,0 +5,0 @@ "main": "src/index.js",

README.md

@@ -120,9 +120,7 @@ # ArrayUtils
 
-Function that applies the standard normal variate (SNV) to each row vector of y's
-values.
+Function that applies the standard normal variate (SNV) to an array of values.
 
 __Arguments__
 
-* `results` - object with three values, 'result' with the applied SNV, 'means' with
-              the means calculated, and 'standardDeviations' calculated by the SNV.
+* `data` - array of values.
 
@@ -129,0 +127,0 @@ ## Authors

src/snv.js

@@ -8,22 +8,12 @@ 'use strict';
 /**
- * Function that applies the standard normal variate (SNV) to each row vector of y's
- * values.
+ * Function that applies the standard normal variate (SNV) to an array of values.
  *
- * @param data - Matrix of y vectors
- * @returns {Object}
+ * @param data - Array of values.
+ * @returns {Array} - applied the SNV.
  */
 function SNV(data) {
-    var Y = data;
-    if(!Matrix.isMatrix(data)) {
-        Y = new Matrix(data).clone();
-    }
+    var mean = Stat.array.mean(data);
+    var std = Stat.array.standardDeviation(data);
 
-    var means = Matrix.columnVector(Stat.matrix.mean(data, 1));
-    var std = Matrix.columnVector(Stat.matrix.standardDeviation(data.transpose(), means));
-
-    return {
-        result: Y.sub(means.mmul(Matrix.ones(1, Y.columns))).divM(std.mmul(Matrix.ones(1, Y.columns))),
-        means: means,
-        standardDeviations: std
-    };
+    return new Matrix([data]).clone().sub(mean).div(std).getRow(0);
 }

test/snv.js

@@ -7,11 +7,10 @@ 'use strict';
     it('Main test', function () {
-        var data = [[0.323, 2.56, 4.67, 13.23],
-                    [1.76, 1.81, 2.20, 2.45]];
-        var dataNorm = SNV(data).result;
+        var data = [0.323, 2.56, 4.67, 13.23];
+        var dataNorm = SNV(data);
 
-        dataNorm[0][0].should.be.approximately(-0.8636, 1e-3);
-        dataNorm[0][3].should.be.approximately(1.4239, 1e-3);
-        dataNorm[1][0].should.be.approximately(-0.8975, 1e-3);
-        dataNorm[1][3].should.be.approximately(1.2018, 1e-3);
+        dataNorm[0].should.be.approximately(-0.8636, 1e-3);
+        dataNorm[1].should.be.approximately(-0.4671, 1e-3);
+        dataNorm[2].should.be.approximately(-0.0931, 1e-3);
+        dataNorm[3].should.be.approximately(1.4239, 1e-3);
     });
 });

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Worsened metrics

Total package byte prevSize

24026

decreased by-1.99%

Lines of code

569

decreased by-1.73%

Number of lines in readme file

134

decreased by-1.47%

No dependency changes