function unarynd( fcn, arrays, views, strides, opts ) {
	var ybuf;
	var len;
	var sh;
	var iv;
	var io;
	var N;
	var v;
	var y;
	var i;
	var j;

	N = arrays.length;

	// Resolve the output ndarray and associated shape:
	y = arrays[ 1 ];
	sh = y.shape;

	// Compute the total number of elements over which to iterate:
	len = numel( sh );

	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
	iv = offsets( arrays );

	// Cache a reference to the output ndarray buffer:
	ybuf = y.data;

	// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...
	io = zeros( N );
	for ( i = 0; i < len; i++ ) {
		for ( j = 0; j < N; j++ ) {
			v = arrays[ j ];
			io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );
		}
		setViewOffsets( views, io );
		ybuf[ io[1] ] = fcn( views, opts );
	}
}
Performs a reduction over an input ndarray and assigns results to a provided output ndarray.

@private
@param {Function} fcn - reduction function
@param {Array<Object>} arrays - ndarrays
@param {Array<Object>} views - initialized ndarray-like objects representing sub-array views
@param {IntegerArray} strides - loop dimension strides for the input ndarray
@param {Options} opts - function options
@returns {void}

@example
var Float64Array = require( '@stdlib/array/float64' );
var filled = require( '@stdlib/array/base/filled' );
var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
var base = require( '@stdlib/ndarray/base/every' );

// Create data buffers:
var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
var ybuf = filled( false, 3 );

// Define the array shapes:
var xsh = [ 3, 2, 2 ];
var ysh = [ 3 ];

// Define the array strides:
var sx = [ 4, 2, 1 ];
var sy = [ 1 ];

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

// Create an input ndarray-like object:
var x = {
    'dtype': 'float64',
    'data': xbuf,
    'shape': xsh,
    'strides': sx,
    'offset': ox,
    'order': 'row-major'
};

// Create an output ndarray-like object:
var y = {
    'dtype': 'generic',
    'data': ybuf,
    'shape': ysh,
    'strides': sy,
    'offset': oy,
    'order': 'row-major'
};

// Initialize ndarray-like objects representing sub-array views:
var views = [
    {
        'dtype': x.dtype,
        'data': x.data,
        'shape': [ 2, 2 ],
        'strides': [ 2, 1 ],
        'offset': x.offset,
        'order': x.order
    }
];

// Perform a reduction:
unarynd( base, [ x, y ], views, [ 4 ], {} );

var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );
// returns [ true, false, true ]