fix:lint_changed_files / Lint Changed Files (pull_request) and also fix:run_affected_examples / Run changed examples (pull_request)

Author: anoofmhd

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

@@ -88,37 +88,34 @@ If provided an input value `x`, the accumulator function updates and returns the
 
 ```javascript
 var incrnanmmeanvar = require( '@stdlib/stats/incr/nanmmeanvar' );
-
 var accumulator = incrnanmmeanvar( 3 );
-
 var out = accumulator();
-// returns null
 
 // Fill the window (no NaNs yet)...
 out = accumulator( 2.0 ); // [2.0]
-// returns [ 2.0, 0.0 ]
+// => [ 2.0, 0.0 ]
 
 out = accumulator( NaN ); // NaN is ignored [2.0]
-// returns [ 2.0, 0.0 ]
+// => [ 2.0, 0.0 ]
 
 out = accumulator( 1.0 ); // [2.0, 1.0]
-// returns [ 1.5, 0.5 ]
+// => [ 1.5, 0.5 ]
 
 out = accumulator( 3.0 ); // [2.0, 1.0, 3.0]
-// returns [ 2.0, 1.0 ]
+// => [ 2.0, 1.0 ]
 
 // Window begins sliding...
 out = accumulator( -7.0 ); // [1.0, 3.0, -7.0]
-// returns [ -1.0, 28.0 ]
+// => [ -1.0, 28.0 ]
 
 out = accumulator( NaN );  // NaN ignored [1.0, 3.0, -7.0]
-// returns [ -1.0, 28.0 ]
+// => [ -1.0, 28.0 ]
 
 out = accumulator( -5.0 ); // [3.0, -7.0, -5.0]
-// returns [ -3.0, 28.0 ]
+// => [ -3.0, 28.0 ]
 
 out = accumulator();
-// returns [ -3.0, 28.0 ]
+// => [ -3.0, 28.0 ]
 ```
 
 </section>
@@ -141,7 +138,6 @@ out = accumulator();
 ## Examples
 
 <!-- eslint no-undef: "error" -->
-
 ```javascript
 var randu = require( '@stdlib/random/base/randu' );
 var Float64Array = require( '@stdlib/array/float64' );

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

@@ -66,4 +66,4 @@ bench( pkg+'::accumulator', function benchmark( b ) {
 	}
 	b.pass( 'benchmark finished' );
 	b.end();
-});
+});

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

@@ -10,10 +10,12 @@
     values. If not provided a value, the accumulator function returns the
     current moving accumulated values.
 
-    NaN values are ignored and do not affect the accumulator state.
+    NaN values are ignored 
+    and do not affect the accumulator state.
 
-    Until the window contains at least one valid (non-NaN) value, the accumulator
-    returns `null`. If the window contains only one valid value, the sample
+    Until the window contains at least one valid (non-NaN) value, the 
+    accumulator returns `null`.
+    If the window contains only one valid value, the sample
     variance is `0.0`.
 
     Parameters
@@ -35,18 +37,17 @@
     > var v = accumulator()
     null
     > v = accumulator( 2.0 )
-    [ 2.0, 0.0 ]
-    > v = accumulator( NaN )   
-    [ 2.0, 0.0 ]
+    [ 2, 0 ]
+    > v = accumulator( NaN )
+    [ 2, 0 ]
     > v = accumulator( 4.0 )
-    [ 3.0, 2.0 ]
+    [ 3, 2 ]
     > v = accumulator( 6.0 )
-    [ 4.0, 4.0 ]
-    > v = accumulator( NaN )   
-    [ 4.0, 4.0 ]
+    [ 4, 4 ]
+    > v = accumulator( NaN )
+    [ 4, 4 ]
     > v = accumulator()
-    [ 4.0, 4.0 ]
+    [ 4, 4 ]
 
     See Also
     --------
-

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

@@ -30,6 +30,7 @@ import { ArrayLike } from '@stdlib/types/array';
 * -   If provided `NaN`, the value is **ignored** and the accumulator state is **not updated**.
 *
 * @param x - input value
+*
 * @returns output array or null
 */
 type accumulator = ( x?: number ) => ArrayLike<number> | null;
@@ -47,6 +48,7 @@ type accumulator = ( x?: number ) => ArrayLike<number> | null;
 * @param window - window size
 * @throws window size must be a positive integer
 * @returns accumulator function
+* 
 */
 declare function incrnanmmeanvar( out: ArrayLike<number>, window: number ): accumulator;
 
@@ -62,6 +64,7 @@ declare function incrnanmmeanvar( out: ArrayLike<number>, window: number ): accu
 * @param window - window size
 * @throws window size must be a positive integer
 * @returns accumulator function
+* 
 * @example
 * var incrnanmmeanvar = require( '@stdlib/stats/incr/nanmmeanvar' );
 *
@@ -71,27 +74,27 @@ declare function incrnanmmeanvar( out: ArrayLike<number>, window: number ): accu
 * // returns null
 *
 * v = accumulator( 2.0 );
-* // returns [ 2.0, 0.0 ]
+* // returns [ 2, 0 ]
 *
 * v = accumulator( NaN );
-* // returns [ 2.0, 0.0 ]  
+* // returns [ 2, 0 ]
 *
 * v = accumulator( 4.0 );
-* // returns [ 3.0, 2.0 ]  
+* // returns [ 3, 2 ]
 *
 * v = accumulator( 6.0 );
-* // returns [ 4.0, 4.0 ]  
+* // returns [ 4, 4 ]
 *
 * v = accumulator( NaN );
-* // returns [ 4.0, 4.0 ]  
+* // returns [ 4, 4 ]
 *
 * v = accumulator( 8.0 );
 * // Window is [4,6,8]
 * // mean = 6, variance = ((4-6)^2+(6-6)^2+(8-6)^2) / 2 = 4
-* // returns [ 6.0, 4.0 ]
+* // returns [ 6, 4 ]
 *
 * v = accumulator();
-* // returns [ 6.0, 4.0 ]
+* // returns [ 6, 4 ]
 */
 declare function incrnanmmeanvar( window: number ): accumulator;
 

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

@@ -36,15 +36,15 @@ var isArrayLike = require( '@stdlib/assert/is-array-like' );
 *
 * @example
 * var acc = incrnanmmeanvar( 3 );
-* acc( 2.0 );  // => [ 2.0, 0.0 ]
-* acc( NaN );  // => [ 2.0, 0.0 ] (NaN skipped)
-* acc( 4.0 );  // => [ 3.0, 2.0 ]
+* acc( 2.0 ); // returns [ 2, 0 ]
+* acc( NaN ); // returns [ 2, 0 ] (NaN skipped)
+* acc( 4.0 ); // returns [ 3, 2 ]
 *
 * @example
 * var out = [ 0.0, 0.0 ];
 * var acc = incrnanmmeanvar( out, 3 );
 * acc( 2.0 );
-* console.log( out ); // => [ 2.0, 0.0 ]
+* console.log( out ); // returns [ 2, 0 ]
 */
 function incrnanmmeanvar( out, W ) {
 	var mmeanvar;
@@ -63,6 +63,7 @@ function incrnanmmeanvar( out, W ) {
 	*
 	* @param {number} [x] - input value
 	* @returns {(Array|null)} current mean and variance
+	* @private
 	*/
 	function accumulator( x ) {
 		// If no arguments → return current state:

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

@@ -308,46 +308,46 @@ tape( 'if provided `NaN`, the accumulator skips the value and returns the previo
 	    3.14,
 	    NaN,
 	    3.14,
-        3.14,
-        NaN,
-        NaN,
-        NaN,
-        NaN,
-        3.14
+	3.14,
+	NaN,
+	NaN,
+	NaN,
+	NaN,
+	3.14
 	];
 	expected = [
 		null,
-        [ 3.14, 0.0 ],
-        [ 3.14, 0.0 ],
-        [ 3.14, 0.0 ],
-        [ 3.14, 0.0 ],
-        [ 3.14, 0.0 ],
-        [ 3.14, 0.0 ],
-        [ 3.14, 0.0 ],
-        [ 3.14, 0.0 ],
-        [ 3.14, 0.0 ],
-        [ 3.14, 0.0 ],
-        [ 3.14, 0.0 ],
-        [ 3.14, 0.0 ],
-        [ 3.14, 0.0 ],
-        [ 3.14, 0.0 ],
-        [ 3.14, 0.0 ],
-        [ 3.14, 0.0 ],
-        [ 3.14, 0.0 ],
-        [ 3.14, 0.0 ]
+	[ 3.14, 0.0 ],
+	[ 3.14, 0.0 ],
+	[ 3.14, 0.0 ],
+	[ 3.14, 0.0 ],
+	[ 3.14, 0.0 ],
+	[ 3.14, 0.0 ],
+	[ 3.14, 0.0 ],
+	[ 3.14, 0.0 ],
+	[ 3.14, 0.0 ],
+	[ 3.14, 0.0 ],
+	[ 3.14, 0.0 ],
+	[ 3.14, 0.0 ],
+	[ 3.14, 0.0 ],
+	[ 3.14, 0.0 ],
+	[ 3.14, 0.0 ],
+	[ 3.14, 0.0 ],
+	[ 3.14, 0.0 ],
+	[ 3.14, 0.0 ]
 	];
 	for ( i = 0; i < data.length; i++ ) {
 		v = acc( data[ i ] );
 
-		
+
 		if ( i === 0 ) {
 			t.strictEqual( v, null, 'NaN ignored; still no data' );
 			continue;
 		}
-        if ( isnan( data[ i ] ) ) {
+	if ( isnan( data[ i ] ) ) {
 			t.deepEqual( v, acc(), 'NaN skipped — state unchanged at step '+i );
 		}
-        else {
+	else {
 			t.strictEqual( isnan( v[0] ), false, 'mean is not NaN' );
 			t.strictEqual( isnan( v[1] ), false, 'variance is not NaN' );
 		}
@@ -363,7 +363,6 @@ tape( 'if provided `NaN`, the accumulator skips values when W=1', function test(
 	var i;
 
 	acc = incrnanmmeanvar( 1 );
-
 	data = [
 		NaN,
 		3.14,
@@ -386,25 +385,25 @@ tape( 'if provided `NaN`, the accumulator skips values when W=1', function test(
 		3.14
 	];
 	expected = [
-		null,              
-		[ 3.14, 0.0 ],     
-		[ 3.14, 0.0 ],     
-		[ 3.14, 0.0 ],     
+		null,
+		[ 3.14, 0.0 ],
+		[ 3.14, 0.0 ],
+		[ 3.14, 0.0 ],
+		[ 3.14, 0.0 ],
+		[ 3.14, 0.0 ],
+		[ 3.14, 0.0 ],
 		[ 3.14, 0.0 ],
 		[ 3.14, 0.0 ],
 		[ 3.14, 0.0 ],
-		[ 3.14, 0.0 ],     
 		[ 3.14, 0.0 ],
 		[ 3.14, 0.0 ],
 		[ 3.14, 0.0 ],
-		[ 3.14, 0.0 ],     
 		[ 3.14, 0.0 ],
 		[ 3.14, 0.0 ],
-		[ 3.14, 0.0 ],     
 		[ 3.14, 0.0 ],
 		[ 3.14, 0.0 ],
 		[ 3.14, 0.0 ],
-		[ 3.14, 0.0 ]  
+		[ 3.14, 0.0 ]
 	];
 	for ( i = 0; i < data.length; i++ ) {
 		v = acc( data[ i ] );