Refactor incrmvariance Implementation for NaN Handling

Author: gkbishnoi07

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

@@ -20,10 +20,8 @@
 
 // MODULES //
 
-var isPositiveInteger = require( '@stdlib/assert/is-positive-integer' ).isPrimitive;
-var isNumber = require( '@stdlib/assert/is-number' ).isPrimitive;
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
-var format = require( '@stdlib/string/format' );
+var incrmvariance = require( '@stdlib/stats/incr/mvariance' );
 
 
 // MAIN //
@@ -65,37 +63,13 @@ var format = require( '@stdlib/string/format' );
 * var accumulator = incrnanmvariance( 3, -2.0 );
 */
 function incrnanmvariance( W, mean ) {
-	var delta;
-	var buf;
-	var tmp;
-	var M2;
-	var mu;
-	var d1;
-	var d2;
-	var N;
-	var n;
-	var i;
-
-	if ( !isPositiveInteger( W ) ) {
-		throw new TypeError( format( 'invalid argument. Must provide a positive integer. Value: `%s`.', W ) );
-	}
-
-	buf = [];
-	n = W - 1;
-	M2 = 0.0;
-	i = -1;
-	N = 0;
-
+	var acc;
 	if ( arguments.length > 1 ) {
-		if ( !isNumber( mean ) ) {
-			throw new TypeError( format( 'invalid argument. Must provide a number. Value: `%s`.', mean ) );
-		}
-		mu = mean;
-		return accumulator2;
+		acc = incrmvariance( W, mean );
+	} else {
+		acc = incrmvariance( W );
 	}
-
-	mu = 0.0;
-	return accumulator1;
+	return accumulator;
 
 	/**
 	* If provided a value, the accumulator function returns an updated unbiased sample variance, ignoring NaN values. If not provided a value, the accumulator function returns the current unbiased sample variance.
@@ -104,145 +78,14 @@ function incrnanmvariance( W, mean ) {
 	* @param {number} [x] - input value
 	* @returns {(number|null)} unbiased sample variance or null
 	*/
-	function accumulator1( x ) {
+	function accumulator( x ) {
 		if ( arguments.length === 0 ) {
-			if ( N === 0 ) {
-				return null;
-			}
-			if ( N === 1 ) {
-				return 0.0;
-			}
-			if ( N < W ) {
-				return M2 / ( N - 1 );
-			}
-			return M2 / n;
+			return acc();
 		}
-
 		if ( isnan( x ) ) {
-			if ( N === 0 ) {
-				return null;
-			}
-			if ( N === 1 ) {
-				return 0.0;
-			}
-			if ( N < W ) {
-				return M2 / ( N - 1 );
-			}
-			return M2 / n;
+			return acc();
 		}
-
-		// Update the index for managing the circular buffer:
-		i = ( i+1 ) % W;
-
-		// Case: initial window...
-		if ( N < W ) {
-			if ( N < W ) {
-				buf.push( x );
-			} else {
-				buf[ i ] = x;
-			}
-			N += 1;
-			delta = x - mu;
-			mu += delta / N;
-			M2 += delta * ( x - mu );
-			if ( N === 1 ) {
-				return 0.0;
-			}
-			return M2 / ( N-1 );
-		}
-
-		// Case: N = W = 1
-		if (N === 1) {
-			M2 = 0.0;
-			return M2;
-		}
-
-		// Case: outgoing value is NaN, which we need to simply replace without affecting the variance
-		if (isnan(buf[i])) {
-			buf[i] = x;
-
-			// When replacing NaN with a value, update M2 with the squared difference from the mean
-			M2 += (x - mu) * (x - mu);
-			return M2 / n;
-		}
-
-		// Case: standard update when neither incoming nor outgoing values are NaN
-		tmp = buf[i];
-		delta = x - tmp;
-		d1 = tmp - mu;
-		mu += delta / N;
-		d2 = x - mu;
-		M2 += delta * (d1 + d2);
-
-		buf[i] = x;
-		return M2 / n;
-	}
-
-	/**
-	* If provided a value, the accumulator function returns an updated unbiased sample variance, ignoring NaN values. If not provided a value, the accumulator function returns the current unbiased sample variance.
-	*
-	* @private
-	* @param {number} [x] - input value
-	* @returns {(number|null)} unbiased sample variance or null
-	*/
-	function accumulator2( x ) {
-		if ( arguments.length === 0 ) {
-			if ( N === 0 ) {
-				return null;
-			}
-			if ( N < W ) {
-				return M2 / N;
-			}
-			return M2 / W;
-		}
-
-		// If incoming value is NaN, ignore it:
-		if ( isnan( x ) ) {
-			if ( N === 0 ) {
-				return null;
-			}
-			if (N < W) {
-				return M2 / N;
-			}
-			return M2 / W;
-		}
-
-		// Update the index for managing the circular buffer:
-		i = (i+1) % W;
-
-		// Case: initial window...
-		if ( N < W ) {
-			if ( N < W ) {
-				buf.push( x );
-			} else {
-				buf[ i ] = x;
-			}
-			N += 1;
-			delta = x - mu;
-			M2 += delta * delta;
-			return M2 / N;
-		}
-
-		// Case: outgoing value is NaN, which we need to simply replace without affecting the variance
-		if ( isnan( buf[ i ] ) ) {
-			buf[ i ] = x;
-
-			// Add the squared difference between the new value and mean
-			M2 += (x - mu) * (x - mu);
-			return M2 / W;
-		}
-
-		// Case: standard update when neither incoming nor outgoing values are NaN
-		tmp = buf[ i ];
-
-		// Remove the contribution of the outgoing value
-		M2 -= ( tmp - mu ) * ( tmp - mu );
-
-		// Add the contribution of the incoming value
-		M2 += ( x - mu ) * ( x - mu );
-
-		buf[ i ] = x;
-		return M2 / W;
+		return acc( x );
 	}
 }