[Fixed Issues]

Author: 23f3001304

lib/node_modules/@stdlib/stats/incr/nanpcorr2/README.md

@@ -94,17 +94,17 @@ var accumulator = incrnanpcorr2();
 var r2 = accumulator( 2.0, 1.0 );
 // returns 0.0
 
-r2 = accumulator( 1.0, NaN );
-// returns 0.0
+r2 = accumulator( 1.0, 90 );
+// returns 1.0
 
 r2 = accumulator( NaN, NaN );
-// returns ~0.0
+// returns ~1.0
 
 r2 = accumulator( 8.0, NaN );
-// returns ~0.0
+// returns ~1.0
 
 r2 = accumulator();
-// returns ~0.0
+// returns ~1.0
 ```
 
 </section>
@@ -135,6 +135,7 @@ var incrnanpcorr2 = require( '@stdlib/stats/incr/nanpcorr2' );
 var accumulator;
 var x;
 var y;
+var r2;
 var i;
 
 // Initialize an accumulator:
@@ -143,13 +144,10 @@ accumulator = incrnanpcorr2();
 // For each simulated datum, update the squared sample correlation coefficient...
 console.log( '\nx\ty\tr^2\n' );
 for ( i = 0; i < 100; i++ ) {
-	x = randu() < 0.9 ? randu() * 100.0:NaN;
-	y = randu() < 0.9 ? randu() * 100.0:NaN;
-	r2 = accumulator( x, y );
-	console.log( '%d\t%d\t%d',
-	isNaN(x) ? 'NaN' : x.toFixed( 4 ), 
-	isNaN(y) ? 'NaN': y.toFixed( 4 ), 
-	r2 === null ? 'null' : r2.toFixed( 4 ) );
+    x = (randu() < 0.9) ? (randu() * 100.0) : NaN;
+    y = (randu() < 0.9) ? (randu() * 100.0) : NaN;
+    r2 = accumulator( x, y );
+    console.log('%s\t%s\t%s', ( isNaN( x ) ) ? 'NaN' : x.toFixed( 4 ), (isNaN(y)) ? 'NaN' : y.toFixed( 4 ), ( r2 === null ) ? 'null' : r2.toFixed( 4 ));
 }
 console.log( accumulator() );
 ```

lib/node_modules/@stdlib/stats/incr/nanpcorr2/docs/repl.txt

@@ -1,15 +1,12 @@
 
 {{alias}}( [mx, my] )
     Returns an accumulator function which incrementally computes the squared
-    sample Pearson product-moment correlation coefficient.
+    sample Pearson product-moment correlation coefficient ignoring NaN values.
 
     If provided values, the accumulator function returns an updated accumulated
     value. If not provided values, the accumulator function returns the current
     accumulated value.
 
-
-    If provided `NaN` or a value which, when used in computations
-    gets ignored.
     Parameters
     ----------
     mx: number (optional)

lib/node_modules/@stdlib/stats/incr/nanpcorr2/docs/types/index.d.ts

@@ -23,18 +23,14 @@
 /**
 * If provided arguments, returns an updated squared sample correlation coefficient.
 *
-* ## Notes
-*
-* -   If provided `NaN` it ignores itand return the previous accumulated value.
-*
 * @param x - value
 * @param y - value
 * @returns updated squared sample correlation coefficient
 */
 type accumulator = ( x?: number, y?: number ) => number | null;
 
 /**
-* Returns an accumulator function which incrementally computes a squared sample Pearson product-moment correlation coefficient,ignoring NaN Values.
+* Returns an accumulator function which incrementally computes a squared sample Pearson product-moment correlation coefficient, ignoring NaN Values.
 *
 * @param meanx - mean value
 * @param meany - mean value
@@ -53,7 +49,7 @@ declare function incrnanpcorr2( meanx: number, meany: number ): accumulator;
 * @example
 * var accumulator = incrnanpcorr2();
 *
- var r2 = accumulator();
+* var r2 = accumulator();
 * // returns null
 *
 * r2 = accumulator( 2.0, 1.0 );

lib/node_modules/@stdlib/stats/incr/nanpcorr2/examples/index.js

@@ -33,12 +33,9 @@ accumulator = incrnanpcorr2();
 // For each simulated datum, update the squared sample Pearson correlation coefficient...
 console.log( '\nx\ty\tr^2\n' );
 for ( i = 0; i < 100; i++ ) {
-	x = randu() < 0.9 ? randu() * 100.0:NaN;
-	y = randu() < 0.9 ? randu() * 100.0:NaN;
+	x = ( randu() < 0.9 ) ? ( randu() * 100.0 ) : NaN;
+	y = ( randu() < 0.9 ) ? ( randu() * 100.0 ) : NaN;
 	r2 = accumulator( x, y );
-	console.log( '%d\t%d\t%d',
-	isNaN(x) ? 'NaN' : x.toFixed( 4 ), 
-	isNaN(y) ? 'NaN': y.toFixed( 4 ), 
-	r2 === null ? 'null' : r2.toFixed( 4 ) );
+	console.log( '%d\t%d\t%d', ( isNaN( x ) ) ? 'NaN' : x.toFixed( 4 ), ( isNaN( y ) ) ? 'NaN' : y.toFixed( 4 ), ( r2 === null ) ? 'null' : r2.toFixed( 4 ) );
 }
 console.log( '\nFinal r^2: %d\n', accumulator());

lib/node_modules/@stdlib/stats/incr/nanpcorr2/lib/index.js

@@ -49,7 +49,7 @@
 
 // MODULES //
 
-var incrnanpcorr2 = require( '@stdlib/stats/incr/nanpcorr2/lib/main.js' );
+var incrnanpcorr2 = require( './main.js' );
 
 
 // EXPORTS //

lib/node_modules/@stdlib/stats/incr/nanpcorr2/lib/main.js

@@ -19,7 +19,8 @@
 'use strict';
 
 // MODULES //
-var isNaN = require( '@stdlib/math/base/assert/is-nan' );
+
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var incrpcorr2 = require( '@stdlib/stats/incr/pcorr2' );
 
 
@@ -60,10 +61,10 @@ var incrpcorr2 = require( '@stdlib/stats/incr/pcorr2' );
 */
 function incrnanpcorr2( meanx, meany ) {
 	var pcorr2;
-	if(arguments.length === 0) {
+	if ( arguments.length === 0 ) {
 		pcorr2 = incrpcorr2();
 	}
-	else{
+	else {
 		pcorr2 = incrpcorr2(meanx, meany);
 	}
 	return accumulator;
@@ -76,14 +77,14 @@ function incrnanpcorr2( meanx, meany ) {
 	* @returns {(number|null)} squared sample correlation coefficient or null
 	*/
 	function accumulator( x, y ) {
-		if (arguments.length === 0 ) {
+		if ( arguments.length === 0 ) {
 			return pcorr2();
 		}
-        if(isNaN(x) || isNaN(y)){
+		if ( isnan( x ) || isnan( y ) ) {
 			return pcorr2();
 		}
 		return pcorr2( x, y );
-		}
+	}
 }
 
 

lib/node_modules/@stdlib/stats/incr/nanpcorr2/package.json

@@ -1,7 +1,7 @@
 {
-  "name": "@stdlib/stats/incr/pcorr2",
+  "name": "@stdlib/stats/incr/nanpcorr2",
   "version": "0.0.0",
-  "description": "Compute a squared sample Pearson product-moment correlation coefficient.",
+  "description": "Compute a squared sample Pearson product-moment correlation coefficient, ignoring NaN values.",
   "license": "Apache-2.0",
   "author": {
     "name": "The Stdlib Authors",

lib/node_modules/@stdlib/stats/incr/nanpcorr2/test/test.js

@@ -279,6 +279,7 @@ tape( 'the accumulated result ignores NaN values', function test( t ) {
 	y = [ 1.5, 2.0, NaN, 4.0, 5.0, NaN ];
 
 	// Only pairs where neither x nor y is NaN should be considered
+
 	// Effective data: [ [2.0, 1.5], [4.0, 4.0] ]
 	expected = 1.0; // Perfect correlation with only these two points
 
@@ -287,35 +288,29 @@ tape( 'the accumulated result ignores NaN values', function test( t ) {
 	for ( i = 0; i < x.length; i++ ) {
 		acc( x[ i ], y[ i ] );
 	}
-	
 	actual = acc();
-	
 	if ( actual === expected ) {
 		t.strictEqual( actual, expected, 'returns expected result' );
 	} else {
 		delta = abs( expected - actual );
 		tol = 7.0 * EPS * abs( expected );
 		t.equal( delta <= tol, true, 'expected: '+expected+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' );
 	}
-	
 	t.end();
 });
 
 tape( 'the accumulated result ignores NaN values (known means)', function test( t ) {
 	var acc;
-	
+
 	// Create accumulator with known means
 	acc = incrnanpcorr2( 3.0, 2.0 );
-	
-	// Add data with some NaN values
+
 	acc( 2.0, 1.0 );
-	acc( NaN, 3.0 ); // Should ignore
-	acc( 4.0, NaN ); // Should ignore
+	acc( NaN, 3.0 );
+	acc( 4.0, NaN );
 	acc( 4.0, 3.0 );
-	
+
 	// NaN values should be ignored in the calculation
 	t.false( isnan(acc()), 'does not return NaN' );
-	
 	t.end();
 });
-