docs: update REPL namespace documentation

Signed-off-by: stdlib-bot <[email protected]>

Author: kgryte

lib/node_modules/@stdlib/repl/help/data/data.csv

@@ -1141,7 +1141,7 @@ base.ndarray.prototype.set,"\nbase.ndarray.prototype.set( ...idx, v )\n    Sets
 base.ndarray.prototype.iset,"\nbase.ndarray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0"
 base.ndarray.prototype.toString,"\nbase.ndarray.prototype.toString()\n    Serializes an ndarray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'"
 base.ndarray.prototype.toJSON,"\nbase.ndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, ndarray"
-base.ndarrayUnary,"\nbase.ndarrayUnary( arrays, fcn )\n    Applies a unary callback to elements in an input ndarray and assigns results\n    to elements in an output ndarray.\n\n    Each provided \"ndarray\" should be an `object` with the following properties:\n\n    - dtype: data type.\n    - data: data buffer.\n    - shape: dimensions.\n    - strides: stride lengths.\n    - offset: index offset.\n    - order: specifies whether an ndarray is row-major (C-style) or column-major\n    (Fortran-style).\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ndarray>\n        Array-like object containing one input ndarray and one output ndarray.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    // Define ndarray data and meta data...\n    > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dtype = 'float64';\n    > var shape = [ 2, 2 ];\n    > var sx = [ 2, 1 ];\n    > var sy = [ 2, 1 ];\n    > var ox = 0;\n    > var oy = 0;\n    > var order = 'row-major';\n\n    // Using ndarrays...\n    > var x = ndarray( dtype, xbuf, shape, sx, ox, order );\n    > var y = ndarray( dtype, ybuf, shape, sy, oy, order );\n    > base.ndarrayUnary( [ x, y ], base.abs );\n    > y.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using minimal ndarray-like objects...\n    > x = {\n    ...     'dtype': dtype,\n    ...     'data': xbuf,\n    ...     'shape': shape,\n    ...     'strides': sx,\n    ...     'offset': ox,\n    ...     'order': order\n    ... };\n    > y = {\n    ...     'dtype': dtype,\n    ...     'data': ybuf,\n    ...     'shape': shape,\n    ...     'strides': sy,\n    ...     'offset': oy,\n    ...     'order': order\n    ... };\n    > base.ndarrayUnary( [ x, y ], base.abs );\n    > y.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    ndarrayDispatch\n"
+base.ndarrayUnary,"\nbase.ndarrayUnary( arrays, fcn )\n    Applies a unary callback to elements in an input ndarray and assigns results\n    to elements in an output ndarray.\n\n    Each provided \"ndarray\" should be an object with the following properties:\n\n    - dtype: data type.\n    - data: data buffer.\n    - shape: dimensions.\n    - strides: stride lengths.\n    - offset: index offset.\n    - order: specifies whether an ndarray is row-major (C-style) or column-major\n    (Fortran-style).\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ndarray>\n        Array-like object containing one input ndarray and one output ndarray.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    // Define ndarray data and meta data...\n    > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dtype = 'float64';\n    > var shape = [ 2, 2 ];\n    > var sx = [ 2, 1 ];\n    > var sy = [ 2, 1 ];\n    > var ox = 0;\n    > var oy = 0;\n    > var order = 'row-major';\n\n    // Using ndarrays...\n    > var x = ndarray( dtype, xbuf, shape, sx, ox, order );\n    > var y = ndarray( dtype, ybuf, shape, sy, oy, order );\n    > base.ndarrayUnary( [ x, y ], base.abs );\n    > y.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using minimal ndarray-like objects...\n    > x = {\n    ...     'dtype': dtype,\n    ...     'data': xbuf,\n    ...     'shape': shape,\n    ...     'strides': sx,\n    ...     'offset': ox,\n    ...     'order': order\n    ... };\n    > y = {\n    ...     'dtype': dtype,\n    ...     'data': ybuf,\n    ...     'shape': shape,\n    ...     'strides': sy,\n    ...     'offset': oy,\n    ...     'order': order\n    ... };\n    > base.ndarrayUnary( [ x, y ], base.abs );\n    > y.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    ndarrayDispatch\n"
 base.ndzeros,"\nbase.ndzeros( dtype, shape, order )\n    Returns a zero-filled ndarray having a specified shape and data type.\n\n    Parameters\n    ----------\n    dtype: string\n        Underlying data type. Must be a numeric data type or \"generic\".\n\n    shape: ArrayLikeObject<integer>\n        Array shape.\n\n    order: string\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style).\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n    <ndarray>\n    > var sh = arr.shape\n    [ 2, 2 ]\n    > var dt = arr.dtype\n    'float64'\n\n    See Also\n    --------\n    base.ndarray, base.ndzerosLike\n"
 base.ndzerosLike,"\nbase.ndzerosLike( x )\n    Returns a zero-filled ndarray having the same shape and data type as a\n    provided input ndarray.\n\n    Along with data type, shape, and order, the function infers the \"class\" of\n    the returned ndarray from the provided ndarray. For example, if provided a\n    \"base\" ndarray, the function returns a base ndarray. If provided a non-base\n    ndarray, the function returns a non-base ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var dt = x.dtype\n    'float64'\n    > var y = base.ndzerosLike( x )\n    <ndarray>\n    > sh = y.shape\n    [ 2, 2 ]\n    > dt = y.dtype\n    'float64'\n\n    See Also\n    --------\n    base.ndarray, base.ndzeros\n"
 base.negafibonacci,"\nbase.negafibonacci( n )\n    Computes the nth negaFibonacci number.\n\n    The negaFibonacci numbers follow the recurrence relation\n\n      F_{n-2} = F_{n} - F_{n-1}\n\n    with seed values F_0 = 0 and F_{-1} = 1.\n\n    If `|n|` is greater than `78`, the function returns `NaN` as larger\n    negaFibonacci numbers cannot be accurately represented due to limitations of\n    double-precision floating-point format.\n\n    If not provided a non-positive integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        NegaFibonacci number.\n\n    Examples\n    --------\n    > var y = base.negafibonacci( 0 )\n    0\n    > y = base.negafibonacci( -1 )\n    1\n    > y = base.negafibonacci( -2 )\n    -1\n    > y = base.negafibonacci( -3 )\n    2\n    > y = base.negafibonacci( -4 )\n    -3\n    > y = base.negafibonacci( -79 )\n    NaN\n    > y = base.negafibonacci( -80 )\n    NaN\n    > y = base.negafibonacci( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci, base.negalucas\n"