chore: fixed linting and clean-up

Author: Girish-Garg

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

@@ -8,7 +8,7 @@ Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
 You may obtain a copy of the License at
 
-    http://www.apache.org/licenses/LICENSE-2.0
+   http://www.apache.org/licenses/LICENSE-2.0
 
 Unless required by applicable law or agreed to in writing, software
 distributed under the License is distributed on an "AS IS" BASIS,
@@ -20,7 +20,7 @@ limitations under the License.
 
 # incrnanpcorr
 
-> Compute a [sample Pearson product-moment correlation coefficient][pearson-correlation] incrementally.
+> Compute a [sample Pearson product-moment correlation coefficient][pearson-correlation] incrementally, ignoring `NaN` values.
 
 <section class="intro">
 
@@ -70,7 +70,7 @@ var incrnanpcorr = require( '@stdlib/stats/incr/nanpcorr' );
 
 #### incrnanpcorr( \[mx, my] )
 
-Returns an accumulator `function` which incrementally computes a [sample Pearson product-moment correlation coefficient][pearson-correlation].
+Returns an accumulator function which incrementally computes a [sample Pearson product-moment correlation coefficient][pearson-correlation], ignoring `NaN` values.
 
 ```javascript
 var accumulator = incrnanpcorr();
@@ -92,7 +92,7 @@ var accumulator = incrnanpcorr();
 var v = accumulator( 2.0, 1.0 );
 // returns 0.0
 
-var v = accumulator( NaN, 1.0 );
+v = accumulator( NaN, 1.0 );
 // returns 0.0
 
 v = accumulator( 1.0, -5.0 );
@@ -116,7 +116,7 @@ v = accumulator();
 
 ## Notes
 
--   Input values are **not** type checked. If provided `NaN` or a value which, when used in computations, results in `NaN`, it will be ignored but you are advised to type check and handle accordingly **before** passing the value to the accumulator function.
+-   Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function.
 
 </section>
 
@@ -130,8 +130,8 @@ v = accumulator();
 
 ```javascript
 var randu = require( '@stdlib/random/base/randu' );
-var incrnanpcorr = require( './../lib' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var incrnanpcorr = require( '@stdlib/stats/incr/nanpcorr' );
 
 var accumulator;
 var r;
@@ -145,8 +145,8 @@ accumulator = incrnanpcorr();
 // For each simulated datum, update the sample Pearson correlation coefficient...
 console.log( '\nx\ty\tCorrelation Coefficient\n' );
 for ( i = 0; i < 100; i++ ) {
-    x = (randu() < 0.2) ? NaN : randu()*100.0; // ~20% NaN values assigned to `x`
-    y = (randu() < 0.2) ? NaN : randu()*100.0; // ~20% NaN values assigned to `y`
+    x = ( randu() < 0.2 ) ? NaN : randu()*100.0; // ~20% NaN values assigned to `x`
+    y = ( randu() < 0.2 ) ? NaN : randu()*100.0; // ~20% NaN values assigned to `y`
     r = accumulator( x, y );
 }
 console.log( accumulator() );

lib/node_modules/@stdlib/stats/incr/nanpcorr/benchmark/benchmark.js

@@ -21,7 +21,6 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
 var pkg = require( './../package.json' ).name;
 var incrnanpcorr = require( './../lib' );
 
@@ -55,7 +54,7 @@ bench( pkg+'::accumulator', function benchmark( b ) {
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		v = acc( randu(), randu() );
+		v = acc( i, i );
 		if ( v !== v ) {
 			b.fail( 'should not return NaN' );
 		}
@@ -77,7 +76,7 @@ bench( pkg+'::accumulator,known_means', function benchmark( b ) {
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		v = acc( randu(), randu() );
+		v = acc( i, i );
 		if ( v !== v ) {
 			b.fail( 'should not return NaN' );
 		}

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

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

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

@@ -23,18 +23,14 @@
 /**
 * If provided arguments, returns an updated sample correlation coefficient.
 *
-* ## Notes
-*
-* -   If provided `NaN` or a value which, when used in computations, results in `NaN`, the accumulated value is `NaN` for all future invocations.
-*
 * @param x - value
 * @param y - value
 * @returns updated sample correlation coefficient
 */
 type accumulator = ( x?: number, y?: number ) => number | null;
 
 /**
-* Returns an accumulator function which incrementally computes an updated sample correlation coefficient.
+* Returns an accumulator function which incrementally computes an updated sample correlation coefficient, ignoring `NaN` values.
 *
 * @param meanx - mean value
 * @param meany - mean value
@@ -46,7 +42,7 @@ type accumulator = ( x?: number, y?: number ) => number | null;
 declare function incrnanpcorr( meanx: number, meany: number ): accumulator;
 
 /**
-* Returns an accumulator function which incrementally computes an updated sample correlation coefficient.
+* Returns an accumulator function which incrementally computes an updated sample correlation coefficient, ignoring `NaN` values.
 *
 * @returns accumulator function
 *

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

@@ -19,8 +19,8 @@
 'use strict';
 
 var randu = require( '@stdlib/random/base/randu' );
-var incrnanpcorr = require( './../lib' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var incrnanpcorr = require( './../lib' );
 
 var accumulator;
 var r;
@@ -34,9 +34,9 @@ accumulator = incrnanpcorr();
 // For each simulated datum, update the sample Pearson correlation coefficient...
 console.log( '\nx\ty\tCorrelation Coefficient\n' );
 for ( i = 0; i < 100; i++ ) {
-	x = (randu() < 0.2) ? NaN : randu()*100.0; // ~20% NaN values assigned to `x`
-	y = (randu() < 0.2) ? NaN : randu()*100.0; // ~20% NaN values assigned to `y`
+	x = ( randu() < 0.2 ) ? NaN : randu() * 100.0; // ~20% NaN values assigned to `x`
+	y = ( randu() < 0.2 ) ? NaN : randu() * 100.0; // ~20% NaN values assigned to `y`
 	r = accumulator( x, y );
-	console.log( '%d\t%d\t%d', isnan(x) ? 'NaN' : x.toFixed( 4 ), isnan(y) ? 'NaN' : y.toFixed( 4 ), r.toFixed( 4 ) );
+	console.log( '%d\t%d\t%d', ( isnan(x) ) ? 'NaN' : x.toFixed( 4 ), ( isnan(y) ) ? 'NaN' : y.toFixed( 4 ), r.toFixed( 4 ) );
 }
 console.log( '\nFinal r: %d\n', accumulator() );

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

@@ -19,7 +19,7 @@
 'use strict';
 
 /**
-* Compute a sample Pearson product-moment correlation coefficient incrementally, ignpring `NaN` value.
+* Compute a sample Pearson product-moment correlation coefficient incrementally, ignoring `NaN` values.
 *
 * @module @stdlib/stats/incr/nanpcorr
 *

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

@@ -20,15 +20,14 @@
 
 // MODULES //
 
-var isNumber = require( '@stdlib/assert/is-number' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var incrpcorr = require( '@stdlib/stats/incr/pcorr' );
 
 
 // MAIN //
 
 /**
-* Returns an accumulator function which incrementally computes a sample Pearson product-moment correlation coefficient, ignoring `NaN` value.
+* Returns an accumulator function which incrementally computes a sample Pearson product-moment correlation coefficient, ignoring `NaN` values.
 *
 * ## Method
 *
@@ -168,12 +167,6 @@ function incrnanpcorr( meanx, meany ) {
 	var N;
 
 	if ( arguments.length ) {
-		if ( !isNumber( meanx ) ) {
-			throw new TypeError( 'invalid argument. First argument must be a number. Value: `' + meanx + '`.' );
-		}
-		if ( !isNumber( meany ) ) {
-			throw new TypeError( 'invalid argument. Second argument must be a number. Value: `' + meany + '`.' );
-		}
 		pcorr = incrpcorr( meanx, meany );
 	} else {
 		pcorr = incrpcorr();
@@ -196,10 +189,10 @@ function incrnanpcorr( meanx, meany ) {
 			if ( N === 0 ) {
 				return null;
 			}
-			return pcorr(); // Return the current correlation
+			return pcorr();
 		}
 		if ( isnan( x ) || isnan( y ) ) {
-			return pcorr(); // Ignore NaN values
+			return pcorr();
 		}
 		N += 1;
 		return pcorr( x, y );

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

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