refactor: add support for ancillary ndarray arguments having trailing dimensions

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Author: kgryte

lib/node_modules/@stdlib/ndarray/base/unary-reduce-strided1d-assign-struct/README.md

@@ -154,7 +154,11 @@ Each provided ndarray should be an object with the following properties:
 
 ## Notes
 
--   The output ndarray and any additional ndarray arguments are expected to have the same dimensions as the non-reduced dimensions of the input ndarray. When calling the reduction function, any additional ndarray arguments are provided as zero-dimensional ndarray-like objects.
+-   The output ndarray is expected to have the same dimensions as the non-reduced dimensions of the input ndarray.
+
+-   Any additional ndarray arguments are expected to have the same leading dimensions as the non-reduced dimensions of the input ndarray.
+
+-   When calling the reduction function, any additional ndarray arguments are provided as k-dimensional subarrays, where `k = M - N` with `M` being the number of dimensions in an ndarray argument and `N` being the number of non-reduced dimensions in the input ndarray. For example, if an input ndarray has three dimensions, the number of reduced dimensions is two, and an additional ndarray argument has one dimension, thus matching the number of non-reduced dimensions in the input ndarray, the reduction function is provided a zero-dimensional subarray as an additional ndarray argument. In the same scenario but where an additional ndarray argument has two dimensions, thus exceeding the number of non-reduced dimensions in the input ndarray, the reduction function is provided a one-dimensional subarray as an additional ndarray argument.
 
 -   The reduction function is expected to have the following signature:
 
@@ -164,7 +168,7 @@ Each provided ndarray should be an object with the following properties:
 
     where
 
-    -   **arrays**: array containing a one-dimensional subarray of the input ndarray, a zero-dimensional subarray of the output ndarray containing the output [`struct`][@stdlib/dstructs/struct] object, and any additional ndarray arguments as zero-dimensional ndarrays.
+    -   **arrays**: array containing a one-dimensional subarray of the input ndarray, a zero-dimensional subarray of the output ndarray containing the output [`struct`][@stdlib/dstructs/struct] object, and any additional ndarray arguments as subarrays.
     -   **options**: function options (_optional_).
 
 -   For very high-dimensional ndarrays which are non-contiguous, one should consider copying the underlying data to contiguous memory before performing a reduction in order to achieve better performance.

lib/node_modules/@stdlib/ndarray/base/unary-reduce-strided1d-assign-struct/docs/repl.txt

@@ -14,10 +14,24 @@
     - order: specifies whether an ndarray is row-major (C-style) or column-major
     (Fortran-style).
 
-    The output ndarray and any additional ndarray arguments are expected to have
-    the same dimensions as the non-reduced dimensions of the input ndarray. When
-    calling the reduction function, any additional ndarray arguments are
-    provided as zero-dimensional ndarray-like objects.
+    The output ndarray is expected to have the same dimensions as the non-
+    reduced dimensions of the input ndarray.
+
+    Any additional ndarray arguments are expected to have the same leading
+    dimensions as the non-reduced dimensions of the input ndarray.
+
+    When calling the reduction function, any additional ndarray arguments are
+    provided as k-dimensional subarrays, where `k = M - N` with `M` being the
+    number of dimensions in an ndarray argument and `N` being the number of non-
+    reduced dimensions in the input ndarray. For example, if an input ndarray
+    has three dimensions, the number of reduced dimensions is two, and an
+    additional ndarray argument has one dimension, thus matching the number of
+    non-reduced dimensions in the input ndarray, the reduction function is
+    provided a zero-dimensional subarray as an additional ndarray argument. In
+    the same scenario but where an additional ndarray argument has two
+    dimensions, thus exceeding the number of non-reduced dimensions in the input
+    ndarray, the reduction function is provided a one-dimensional subarray as an
+    additional ndarray argument.
 
     Parameters
     ----------
@@ -32,8 +46,8 @@
 
         - arrays: array containing a one-dimensional subarray of the input
         ndarray, a zero-dimensional subarray of the output ndarray containing
-        the output struct object, and any additional ndarray arguments as zero-
-        dimensional ndarrays.
+        the output struct object, and any additional ndarray arguments as
+        subarrays.
         - options: function options.
 
     arrays: ArrayLikeObject<ndarray>

lib/node_modules/@stdlib/ndarray/base/unary-reduce-strided1d-assign-struct/lib/initialize_array_views.js

@@ -18,10 +18,15 @@
 
 'use strict';
 
+// MODULES //
+
+var slice = require( '@stdlib/array/base/slice' );
+
+
 // MAIN //
 
 /**
-* Initialize ndarray-like objects for representing zero-dimensional sub-array views of the output and ancillary ndarray arguments.
+* Initialize ndarray-like objects for representing sub-array views of the output and ancillary ndarray arguments.
 *
 * ## Notes
 *
@@ -30,20 +35,25 @@
 *
 * @private
 * @param {ArrayLikeObject<Object>} arrays - list of ndarray-like objects
+* @param {NonNegativeInteger} k - number of non-reduced dimensions
 * @param {Array<Object>} out - output array
 * @returns {Array<Object>} output array
 */
-function initializeViews( arrays, out ) {
+function initializeViews( arrays, k, out ) {
+	var sh;
+	var N;
 	var v;
 	var i;
 
 	for ( i = 1; i < arrays.length; i++ ) {
 		v = arrays[ i ];
+		sh = v.shape;
+		N = sh.length;
 		out.push({
 			'dtype': v.dtype,
 			'data': v.data,
-			'shape': [],
-			'strides': [ 0 ],
+			'shape': slice( sh, k, N ),
+			'strides': ( N === k ) ? [ 0 ] : slice( v.strides, k, N ),
 			'offset': v.offset,
 			'order': v.order
 		});

lib/node_modules/@stdlib/ndarray/base/unary-reduce-strided1d-assign-struct/lib/main.js

@@ -416,10 +416,16 @@ function unaryReduceStrided1d( fcn, arrays, dims, options ) {
 	if ( M > ndims ) {
 		throw new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );
 	}
-	// Verify that provided ndarrays have the expected number of dimensions...
+	// Compute the number of non-reduced dimensions:
 	K = ndims - M;
-	for ( i = 1; i < N; i++ ) {
-		if ( arr[ i ].shape.length !== K ) {
+
+	// Verify that the output ndarray has the expected number of dimensions...
+	if ( arr[ 1 ].shape.length !== K ) {
+		throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ 1 ].shape, ',' ), 1 ) );
+	}
+	// Verify that any ancillary ndarrays have at least the number of non-reduced dimensions...
+	for ( i = 2; i < N; i++ ) {
+		if ( arr[ i ].shape.length < K ) {
 			throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );
 		}
 	}
@@ -467,7 +473,7 @@ function unaryReduceStrided1d( fcn, arrays, dims, options ) {
 			'order': x.order
 		}
 	];
-	initializeViews( arr, views );
+	initializeViews( arr, K, views );
 
 	// Determine the strategy for reshaping sub-array views of the input array prior to performing a reduction:
 	strategy = reshapeStrategy( views[ 0 ] );
@@ -480,8 +486,6 @@ function unaryReduceStrided1d( fcn, arrays, dims, options ) {
 	if ( K === 1 ) {
 		return UNARY[ K ]( fcn, arr, views, sl, strategy, opts );
 	}
-	sy = y.strides;
-
 	// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...
 	if ( ns === K-1 ) {
 		// Get the index of the non-singleton dimension...
@@ -497,6 +501,7 @@ function unaryReduceStrided1d( fcn, arrays, dims, options ) {
 		sl = [ sl[i] ];
 		return UNARY[ 1 ]( fcn, arr, views, sl, strategy, opts );
 	}
+	sy = y.strides;
 	iox = iterationOrder( sl ); // +/-1
 	ioy = iterationOrder( sy ); // +/-1
 

lib/node_modules/@stdlib/ndarray/base/unary-reduce-strided1d-assign-struct/lib/reshape_strategy.js

@@ -186,7 +186,7 @@ function copy( len, workspace ) {
 *
 * @private
 * @param {ndarrayLike} x - input ndarray
-* @param {string} x.dtype - input ndarray data type
+* @param {*} x.dtype - input ndarray data type
 * @param {Collection} x.data - input ndarray data buffer
 * @param {NonNegativeIntegerArray} x.shape - input ndarray shape
 * @param {IntegerArray} x.strides - input ndarray strides