feat: update blas/base/ndarray TypeScript declarations

lib/node_modules/@stdlib/blas/base/ndarray/docs/types/index.d.ts

@@ -70,6 +70,7 @@ import snrm2 = require( '@stdlib/blas/base/ndarray/snrm2' );
 import sscal = require( '@stdlib/blas/base/ndarray/sscal' );
 import sspr = require( '@stdlib/blas/base/ndarray/sspr' );
 import sswap = require( '@stdlib/blas/base/ndarray/sswap' );
+import ssymv = require( '@stdlib/blas/base/ndarray/ssymv' );
 import ssyr = require( '@stdlib/blas/base/ndarray/ssyr' );
 import ssyr2 = require( '@stdlib/blas/base/ndarray/ssyr2' );
 import zaxpy = require( '@stdlib/blas/base/ndarray/zaxpy' );
@@ -1631,6 +1632,51 @@ interface Namespace {
 	*/
 	sswap: typeof sswap;
 
+	/**
+	* Performs the matrix-vector operation `y = alpha*A*x + beta*y`, where `alpha` and `beta` are scalars, `x` and `y` are one-dimensional ndarrays, and `A` is an `N` by `N` symmetric matrix.
+	*
+	* ## Notes
+	*
+	* -   The function expects the following ndarrays:
+	*
+	*     -   a two-dimensional input ndarray corresponding to `A`.
+	*     -   a one-dimensional input ndarray corresponding to `x`.
+	*     -   a one-dimensional input/output ndarray corresponding to `y`.
+	*     -   a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced.
+	*     -   a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`.
+	*     -   a zero-dimensional ndarray containing a scalar constant corresponding to `beta`.
+	*
+	* @param arrays - array-like object containing ndarrays
+	* @returns output ndarray
+	*
+	* @example
+	* var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' );
+	* var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
+	* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+	* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
+	*
+	* var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] );
+	* var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] );
+	* var y = new Float32Vector( [ 4.0, 5.0, 6.0 ] );
+	*
+	* var uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+	*     'dtype': 'int32'
+	* });
+	* var alpha = scalar2ndarray( 3.0, {
+	*     'dtype': 'float32'
+	* });
+	* var beta = scalar2ndarray( 2.0, {
+	*     'dtype': 'float32'
+	* });
+	*
+	* var z = ns.ssymv( [ A, x, y, uplo, alpha, beta ] );
+	* // returns <ndarray>[ 50.0, 40.0, 42.0 ]
+	*
+	* var bool = ( z === y );
+	* // returns true
+	*/
+	ssymv: typeof ssymv;
+
 	/**
 	* Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an `N` by `N` symmetric matrix.
 	*