docs: update blas/ext/base/dnanasumors to follow current project conventions

lib/node_modules/@stdlib/blas/ext/base/dnanasumors/README.md

@@ -59,19 +59,18 @@ Computes the sum of absolute values ([_L1_ norm][l1norm]) of double-precision fl
 var Float64Array = require( '@stdlib/array/float64' );
 
 var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
-var N = x.length;
 
-var v = dnanasumors( N, x, 1 );
+var v = dnanasumors( x.length, x, 1 );
 // returns 5.0
 ```
 
 The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: input [`Float64Array`][@stdlib/array/float64].
--   **strideX**: index increment for `x`.
+-   **strideX**: stride length.
 
-The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of absolute values ([_L1_ norm][l1norm]) for every other element in `x`,
+The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of absolute values ([_L1_ norm][l1norm]) for every other element:
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
@@ -104,17 +103,16 @@ Computes the sum of absolute values ([_L1_ norm][l1norm]) of double-precision fl
 var Float64Array = require( '@stdlib/array/float64' );
 
 var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
-var N = x.length;
 
-var v = dnanasumors.ndarray( N, x, 1, 0 );
+var v = dnanasumors.ndarray( x.length, x, 1, 0 );
 // returns 5.0
 ```
 
 The function has the following additional parameters:
 
--   **offsetX**: starting index for `x`.
+-   **offsetX**: starting index.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the sum of absolute values ([_L1_ norm][l1norm]) for every other value in `x` starting from the second value
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the sum of absolute values ([_L1_ norm][l1norm]) for every other value in the strided array starting from the second value:
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
@@ -153,7 +151,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' );
 var dnanasumors = require( '@stdlib/blas/ext/base/dnanasumors' );
 
 function rand() {
-    if ( bernoulli( 0.5 ) < 0.2 ) {
+    if ( bernoulli( 0.5 ) < 1 ) {
         return NaN;
     }
     return discreteUniform( 0, 100 );
@@ -211,7 +209,7 @@ The function accepts the following arguments:
 
 -   **N**: `[in] CBLAS_INT` number of indexed elements.
 -   **X**: `[in] double*` input array.
--   **strideX**: `[in] CBLAS_INT` index increment for `X`.
+-   **strideX**: `[in] CBLAS_INT` stride length.
 
 ```c
 double stdlib_strided_dnanasumors( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
@@ -232,8 +230,8 @@ The function accepts the following arguments:
 
 -   **N**: `[in] CBLAS_INT` number of indexed elements.
 -   **X**: `[in] double*` input array.
--   **strideX**: `[in] CBLAS_INT` index increment for `X`.
--   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+-   **strideX**: `[in] CBLAS_INT` stride length.
+-   **offsetX**: `[in] CBLAS_INT` starting index.
 
 ```c
 double stdlib_strided_dnanasumors_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );

lib/node_modules/@stdlib/blas/ext/base/dnanasumors/benchmark/benchmark.js

@@ -32,6 +32,19 @@ var dnanasumors = require( './../lib/dnanasumors.js' );
 
 // FUNCTIONS //
 
+/**
+* Returns a random number.
+*
+* @private
+* @returns {number} random number
+*/
+function rand() {
+	if ( bernoulli( 0.5 ) < 1 ) {
+		return uniform( -10.0, 10.0 );
+	}
+	return NaN;
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -43,13 +56,6 @@ function createBenchmark( len ) {
 	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
-	function rand() {
-		if ( bernoulli( 0.2 ) ) {
-			return NaN;
-		}
-		return uniform( -10.0, 10.0 );
-	}
-
 	function benchmark( b ) {
 		var v;
 		var i;

lib/node_modules/@stdlib/blas/ext/base/dnanasumors/benchmark/benchmark.native.js

@@ -41,6 +41,19 @@ var opts = {
 
 // FUNCTIONS //
 
+/**
+* Returns a random number.
+*
+* @private
+* @returns {number} random number
+*/
+function rand() {
+	if ( bernoulli( 0.5 ) < 1 ) {
+		return uniform( -10.0, 10.0 );
+	}
+	return NaN;
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -52,13 +65,6 @@ function createBenchmark( len ) {
 	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
-	function rand() {
-		if ( bernoulli( 0.2 ) ) {
-			return NaN;
-		}
-		return uniform( -10.0, 10.0 );
-	}
-
 	function benchmark( b ) {
 		var v;
 		var i;

lib/node_modules/@stdlib/blas/ext/base/dnanasumors/benchmark/benchmark.ndarray.js

@@ -32,6 +32,19 @@ var dnanasumors = require( './../lib/ndarray.js' );
 
 // FUNCTIONS //
 
+/**
+* Returns a random number.
+*
+* @private
+* @returns {number} random number
+*/
+function rand() {
+	if ( bernoulli( 0.5 ) < 1 ) {
+		return uniform( -10.0, 10.0 );
+	}
+	return NaN;
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -43,13 +56,6 @@ function createBenchmark( len ) {
 	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
-	function rand() {
-		if ( bernoulli( 0.2 ) ) {
-			return NaN;
-		}
-		return uniform( -10.0, 10.0 );
-	}
-
 	function benchmark( b ) {
 		var v;
 		var i;

lib/node_modules/@stdlib/blas/ext/base/dnanasumors/benchmark/benchmark.ndarray.native.js

@@ -41,6 +41,19 @@ var opts = {
 
 // FUNCTIONS //
 
+/**
+* Returns a random number.
+*
+* @private
+* @returns {number} random number
+*/
+function rand() {
+	if ( bernoulli( 0.5 ) < 1 ) {
+		return uniform( -10.0, 10.0 );
+	}
+	return NaN;
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -52,13 +65,6 @@ function createBenchmark( len ) {
 	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
-	function rand() {
-		if ( bernoulli( 0.2 ) ) {
-			return NaN;
-		}
-		return uniform( -10.0, 10.0 );
-	}
-
 	function benchmark( b ) {
 		var v;
 		var i;

lib/node_modules/@stdlib/blas/ext/base/dnanasumors/docs/repl.txt

@@ -4,8 +4,8 @@
     point strided array elements, ignoring `NaN` values and using ordinary
     recursive summation.
 
-    The `N` and stride parameters determine which elements in `x` are accessed
-    at runtime.
+    The `N` and stride parameters determine which elements in the strided array
+    are accessed at runtime.
 
     Indexing is relative to the first index. To introduce an offset, use a typed
     array view.
@@ -21,7 +21,7 @@
         Input array.
 
     strideX: integer
-        Index increment.
+        Stride length.
 
     Returns
     -------
@@ -35,19 +35,15 @@
     > {{alias}}( x.length, x, 1 )
     5.0
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > var stride = 2;
-    > {{alias}}( N, x, stride )
+    > {{alias}}( 4, x, 2 )
     5.0
 
     // Using view offsets:
     > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );
     > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > stride = 2;
-    > {{alias}}( N, x1, stride )
+    > {{alias}}( 4, x1, 2 )
     5.0
 
 
@@ -69,7 +65,7 @@
         Input array.
 
     strideX: integer
-        Index increment.
+        Stride length.
 
     offsetX: integer
         Starting index.
@@ -88,8 +84,7 @@
 
     // Using offset parameter:
     > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1 )
+    > {{alias}}.ndarray( 4, x, 2, 1 )
     5.0
 
     See Also

lib/node_modules/@stdlib/blas/ext/base/dnanasumors/examples/index.js

@@ -24,7 +24,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' );
 var dnanasumors = require( './../lib' );
 
 function rand() {
-	if ( bernoulli( 0.2 ) ) {
+	if ( bernoulli( 0.5 ) < 1 ) {
 		return NaN;
 	}
 	return discreteUniform( 0, 100 );

lib/node_modules/@stdlib/blas/ext/base/dnanasumors/lib/dnanasumors.js

@@ -38,9 +38,8 @@ var ndarray = require( './ndarray.js' );
 * var Float64Array = require( '@stdlib/array/float64' );
 *
 * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
-* var N = x.length;
 *
-* var v = dnanasumors( N, x, 1 );
+* var v = dnanasumors( x.length, x, 1 );
 * // returns 5.0
 */
 function dnanasumors( N, x, strideX ) {

lib/node_modules/@stdlib/blas/ext/base/dnanasumors/lib/dnanasumors.native.js

@@ -37,9 +37,8 @@ var addon = require( './../src/addon.node' );
 * var Float64Array = require( '@stdlib/array/float64' );
 *
 * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
-* var N = x.length;
 *
-* var v = dnanasumors( N, x, 1 );
+* var v = dnanasumors( x.length, x, 1 );
 * // returns 5.0
 */
 function dnanasumors( N, x, strideX ) {

lib/node_modules/@stdlib/blas/ext/base/dnanasumors/lib/index.js

@@ -28,9 +28,8 @@
 * var dnanasumors = require( '@stdlib/blas/ext/base/dnanasumors' );
 *
 * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
-* var N = x.length;
 *
-* var v = dnanasumors( N, x, 1 );
+* var v = dnanasumors( x.length, x, 1 );
 * // returns 5.0
 *
 * @example

lib/node_modules/@stdlib/blas/ext/base/dnanasumors/lib/ndarray.js

@@ -31,7 +31,7 @@ var abs = require( '@stdlib/math/base/special/abs' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - input array
-* @param {integer} strideX - index increment
+* @param {integer} strideX - stride length
 * @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} sum
 *
@@ -52,13 +52,13 @@ function dnanasumors( N, x, strideX, offsetX ) {
 	if ( N <= 0 ) {
 		return 0.0;
 	}
+	ix = offsetX;
 	if ( strideX === 0 ) {
-		if ( isnan( x[ offsetX ] ) ) {
+		if ( isnan( x[ ix ] ) ) {
 			return 0.0;
 		}
-		return abs( x[ offsetX ] ) * N;
+		return abs( x[ ix ] ) * N;
 	}
-	ix = offsetX;
 	sum = 0.0;
 	for ( i = 0; i < N; i++ ) {
 		v = x[ ix ];

lib/node_modules/@stdlib/blas/ext/base/dnanasumors/src/main.c

@@ -40,7 +40,7 @@ double API_SUFFIX(stdlib_strided_dnanasumors)( const CBLAS_INT N, const double *
 *
 * @param N        number of indexed elements
 * @param X        input array
-* @param strideX  index increment
+* @param strideX  stride length
 * @param offsetX  starting index
 * @return         output value
 */
@@ -53,13 +53,13 @@ double API_SUFFIX(stdlib_strided_dnanasumors_ndarray)( const CBLAS_INT N, const
 	if ( N <= 0 ) {
 		return 0.0;
 	}
+	ix = offsetX;
 	if ( strideX == 0 ) {
-		if ( stdlib_base_is_nan( X[ offsetX ] ) ) {
+		if ( stdlib_base_is_nan( X[ ix ] ) ) {
 			return 0.0;
 		}
-		return stdlib_base_abs( X[ offsetX ] ) * N;
+		return stdlib_base_abs( X[ ix ] ) * N;
 	}
-	ix = offsetX;
 	sum = 0.0;
 	for ( i = 0; i < N; i++ ) {
 		v = X[ ix ];