refactor: add explicit rank tests for initial value argument

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---

Author: kgryte

lib/node_modules/@stdlib/blas/ext/cusum/lib/assign.js

@@ -30,6 +30,7 @@ var nonCoreShape = require( '@stdlib/ndarray/base/complement-shape' );
 var getDType = require( '@stdlib/ndarray/dtype' );
 var getShape = require( '@stdlib/ndarray/shape' );
 var getOrder = require( '@stdlib/ndarray/order' );
+var ndims = require( '@stdlib/ndarray/base/ndims' );
 var format = require( '@stdlib/string/format' );
 var base = require( './base.js' ).assign;
 
@@ -112,6 +113,9 @@ function assign( x ) {
 			// Case: assign( x, initial_ndarray, out )
 			if ( isndarrayLike( v ) ) {
 				// As the operation is performed across all dimensions, `v` is assumed to be a zero-dimensional ndarray...
+				if ( ndims( v ) !== 0 ) {
+					throw new TypeError( format( 'invalid argument. Second argument must be a zero-dimensional ndarray.' ) );
+				}
 				return base( x, v, out );
 			}
 			// When computing the sum, initial values must be numeric...
@@ -134,9 +138,11 @@ function assign( x ) {
 	}
 	// Case: assign( x, initial_ndarray, out, opts )
 	if ( isndarrayLike( v ) ) {
-		// When not provided `dims`, the operation is performed across all dimensions and `v` is assumed to be a zero-dimensional ndarray; when `dims` is provided, we need to broadcast `v` to match the shape of the non-core dimensions...
+		// When not provided `dims`, the operation is performed across all dimensions and `v` must be a zero-dimensional ndarray; when `dims` is provided, we need to broadcast `v` to match the shape of the non-core dimensions...
 		if ( hasOwnProp( opts, 'dims' ) ) {
 			v = maybeBroadcastArray( v, nonCoreShape( getShape( x ), opts.dims ) ); // eslint-disable-line max-len
+		} else if ( ndims( v ) !== 0 ) {
+			throw new TypeError( format( 'invalid argument. Second argument must be a zero-dimensional ndarray.' ) );
 		}
 	}
 	// Case: assign( x, initial_scalar, out, opts )

lib/node_modules/@stdlib/blas/ext/cusum/lib/main.js

@@ -30,6 +30,7 @@ var nonCoreShape = require( '@stdlib/ndarray/base/complement-shape' );
 var getDType = require( '@stdlib/ndarray/dtype' );
 var getShape = require( '@stdlib/ndarray/shape' );
 var getOrder = require( '@stdlib/ndarray/order' );
+var ndims = require( '@stdlib/ndarray/base/ndims' );
 var format = require( '@stdlib/string/format' );
 var base = require( './base.js' );
 
@@ -99,7 +100,10 @@ function cusum( x ) {
 	if ( nargs === 2 ) {
 		// Case: cusum( x, initial_ndarray )
 		if ( isndarrayLike( v ) ) {
-			// As the operation is performed across all dimensions, `v` is assumed to be a zero-dimensional ndarray...
+			// As the operation is performed across all dimensions, `v` must be a zero-dimensional ndarray...
+			if ( ndims( v ) !== 0 ) {
+				throw new TypeError( format( 'invalid argument. Second argument must be a zero-dimensional ndarray.' ) );
+			}
 			return base( x, v );
 		}
 		// Case: cusum( x, initial_scalar )
@@ -118,9 +122,11 @@ function cusum( x ) {
 	}
 	// Case: cusum( x, initial_ndarray, opts )
 	if ( isndarrayLike( v ) ) {
-		// When not provided `dims`, the operation is performed across all dimensions and `v` is assumed to be a zero-dimensional ndarray; when `dims` is provided, we need to broadcast `v` to match the shape of the non-core dimensions...
+		// When not provided `dims`, the operation is performed across all dimensions and `v` must be a zero-dimensional ndarray; when `dims` is provided, we need to broadcast `v` to match the shape of the non-core dimensions...
 		if ( hasOwnProp( opts, 'dims' ) ) {
 			v = maybeBroadcastArray( v, nonCoreShape( getShape( x ), opts.dims ) ); // eslint-disable-line max-len
+		} else if ( ndims( v ) !== 0 ) {
+			throw new TypeError( format( 'invalid argument. Second argument must be a zero-dimensional ndarray.' ) );
 		}
 	}
 	// Case: cusum( x, initial_scalar, opts )