function unary0d( x, y, fcn ) {
	y.data[ y.offset ] = fcn( x.data[ x.offset ] );
}
Applies a unary callback to elements in a zero-dimensional input ndarray and assigns results to elements in an equivalently shaped output ndarray.

@private
@param {Object} x - object containing input ndarray meta data
@param {string} x.dtype - data type
@param {Collection} x.data - data buffer
@param {NonNegativeIntegerArray} x.shape - dimensions
@param {IntegerArray} x.strides - stride lengths
@param {NonNegativeInteger} x.offset - index offset
@param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style)
@param {Object} y - object containing output ndarray meta data
@param {string} y.dtype - data type
@param {Collection} y.data - data buffer
@param {NonNegativeIntegerArray} y.shape - dimensions
@param {IntegerArray} y.strides - stride lengths
@param {NonNegativeInteger} y.offset - index offset
@param {string} y.order - specifies whether `y` is row-major (C-style) or column-major (Fortran-style)
@param {Callback} fcn - unary callback
@returns {void}

@example
var Float64Array = require( '@stdlib/array/float64' );

function scale( x ) {
    return x * 10.0;
}

// Create data buffers:
var xbuf = new Float64Array( [ 1.0, 2.0 ] );
var ybuf = new Float64Array( 1 );

// Define the shape of the input and output arrays:
var shape = [];

// Define the array strides:
var sx = [ 0 ];
var sy = [ 0 ];

// Define the index offsets:
var ox = 1;
var oy = 0;

// Create the input and output ndarray-like objects:
var x = {
    'dtype': 'float64',
    'data': xbuf,
    'shape': shape,
    'strides': sx,
    'offset': ox,
    'order': 'row-major'
};
var y = {
    'dtype': 'float64',
    'data': ybuf,
    'shape': shape,
    'strides': sy,
    'offset': oy,
    'order': 'row-major'
};

// Apply the unary function:
unary0d( x, y, scale );

console.log( y.data );
// => <Float64Array>[ 20.0 ]