refactor: loop reordering

---
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---

lib/node_modules/@stdlib/lapack/base/dlange/lib/base.js

@@ -22,6 +22,7 @@
 
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var dlassq = require( '@stdlib/lapack/base/dlassq' ).ndarray;
+var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' );
 var Float64Array = require( '@stdlib/array/float64' );
 var min = require( '@stdlib/math/base/special/min' );
 var abs = require( '@stdlib/math/base/special/abs' );
@@ -31,14 +32,14 @@
 // MAIN //
 
 /**
 * Returns the value of the one norm, or the frobenius norm, or the infinity norm, or the element with the largest absolute value of a real matrix `A`.
 *
 * ## Notes
 *
 * -   use `norm` = `max`, to calculate the element with the largest absolute value
 * -   use `norm` = `one`, to calculate the one norm
 * -   use `norm` = `infinity`, to calculate the infinity norm
 * -   use `norm` = `frobenius`, to calculate the frobenius norm
 *
 * @private
 * @param {string} norm - specifies the type of norm to be calculated
@@ -79,17 +80,32 @@
 
 	else if ( norm === 'max' ) {
 		value = 0.0;
-		ia1 = offsetA;
-		for ( i = 0; i < M; i++ ) {
-			ia2 = 0;
+		if ( isRowMajor( [ strideA1, strideA2 ] ) ) {
+			ia1 = offsetA;
+			for ( i = 0; i < M; i++ ) {
+				ia2 = 0;
+				for ( j = 0; j < N; j++ ) {
+					temp = A[ ia1 + ia2 ];
+					if ( value < temp || isnan( temp ) ) {
+						value = temp;
+					}
+					ia2 += strideA2;
+				}
+				ia1 += strideA1;
+			}
+		} else {
+			ia1 = offsetA;
 			for ( j = 0; j < N; j++ ) {
-				temp = A[ ia1 + ia2 ];
-				if ( value < temp || isnan( temp ) ) {
-					value = temp;
+				ia2 = 0;
+				for ( i = 0; i < M; i++ ) {
+					temp = A[ ia1 + ia2 ];
+					if ( value < temp || isnan( temp ) ) {
+						value = temp;
+					}
+					ia2 += strideA1;
 				}
-				ia2 += strideA2;
+				ia1 += strideA2;
 			}
-			ia1 += strideA1;
 		}
 	}
 
@@ -117,16 +133,30 @@
 			iw += strideWork;
 		}
 
-		ia1 = offsetA;
-		for ( j = 0; j < N; j++ ) {
-			ia2 = 0;
+		if ( isRowMajor( [ strideA1, strideA2 ] ) ) {
+			ia1 = offsetA;
 			iw = offsetWork;
 			for ( i = 0; i < M; i++ ) {
-				work[ iw ] += abs( A[ ia1 + ia2 ] );
+				ia2 = 0;
+				for ( j = 0; j < N; j++ ) {
+					work[ iw ] += abs( A[ ia1 + ia2 ] );
+					ia2 += strideA2;
+				}
+				ia1 += strideA1;
 				iw += strideWork;
-				ia2 += strideA1;
 			}
-			ia1 += strideA2;
+		} else {
+			ia1 = offsetA;
+			for ( j = 0; j < N; j++ ) {
+				ia2 = 0;
+				iw = offsetWork;
+				for ( i = 0; i < M; i++ ) {
+					work[ iw ] += abs( A[ ia1 + ia2 ] );
+					iw += strideWork;
+					ia2 += strideA1;
+				}
+				ia1 += strideA2;
+			}
 		}
 
 		value = 0;