function unarynd( fcn, arrays, views, shape, stridesX, stridesY, strategyX, strategyY, opts ) { // eslint-disable-line max-len
	var len;
	var arr;
	var iv;
	var io;
	var N;
	var v;
	var i;
	var j;

	N = arrays.length;

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

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

	// Shallow copy the list of views to an internal array so that we can update with reshaped views without impacting the original list of views:
	v = copyIndexed( views );

	// 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++ ) {
			arr = arrays[ j ];
			io[ j ] = vind2bind( shape, arr.strides, iv[ j ], arr.order, i, MODE ); // eslint-disable-line max-len
		}
		setViewOffsets( views, io );
		v[ 0 ] = strategyX.input( views[ 0 ] );
		v[ 1 ] = strategyY.input( views[ 1 ] );
		fcn( v, opts );
		strategyY.output( views[ 1 ] );
	}
}
Applies a one-dimensional strided array function to a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.

@private
@param {Function} fcn - wrapper for a one-dimensional strided array reduction function
@param {Array<Object>} arrays - ndarrays
@param {Array<Object>} views - initialized ndarray-like objects representing sub-array views
@param {NonNegativeIntegerArray} shape - loop dimensions
@param {IntegerArray} stridesX - loop dimension strides for the input ndarray
@param {IntegerArray} stridesY - loop dimension strides for the output ndarray
@param {Object} strategyX - strategy for marshaling data to and from an input ndarray view
@param {Object} strategyY - strategy for marshaling data to and from an output ndarray view
@param {Options} opts - function options
@returns {void}

@example
var Float64Array = require( '@stdlib/array/float64' );
var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
var getStride = require( '@stdlib/ndarray/base/stride' );
var getOffset = require( '@stdlib/ndarray/base/offset' );
var getData = require( '@stdlib/ndarray/base/data-buffer' );
var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' );
var gcusum = require( '@stdlib/blas/ext/base/gcusum' ).ndarray;

function wrapper( arrays ) {
    var x = arrays[ 0 ];
    var y = arrays[ 1 ];
    var s = arrays[ 2 ];
    return gcusum( numelDimension( x, 0 ), getData( s )[ getOffset( s ) ], getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ) );
}

// Create data buffers:
var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

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

// Define the array strides:
var sx = [ 4, 2, 1 ];
var sy = [ 4, 2, 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 ndarray-like object for the initial sum:
var initial = {
    'dtype': 'float64',
    'data': new Float64Array( [ 0.0 ] ),
    'shape': [ 3 ],
    'strides': [ 0 ],
    'offset': 0,
    'order': 'row-major'
};

// Create an output ndarray-like object:
var y = {
    'dtype': 'float64',
    '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
    },
    {
        'dtype': y.dtype,
        'data': y.data,
        'shape': [ 2, 2 ],
        'strides': [ 2, 1 ],
        'offset': y.offset,
        'order': y.order
    },
    {
        'dtype': initial.dtype,
        'data': initial.data,
        'shape': [],
        'strides': [ 0 ],
        'offset': initial.offset,
        'order': initial.order
    }
];

// Define an input strategy:
function inputStrategy( x ) {
    return {
        'dtype': x.dtype,
        'data': x.data,
        'shape': [ 4 ],
        'strides': [ 1 ],
        'offset': x.offset,
        'order': x.order
    };
}

// Define an output strategy:
function outputStrategy( x ) {
    return x;
}

var strategy = {
    'input': inputStrategy,
    'output': outputStrategy
};

// Apply strided function:
unarynd( wrapper, [ x, y, initial ], views, [ 3 ], [ 4 ], [ 4 ], strategy, strategy, {} );

var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );
// returns [ [ [ 1.0, 3.0 ], [ 6.0, 10.0 ] ], [ [ 5.0, 11.0 ], [ 18.0, 26.0 ] ], [ [ 9.0, 19.0 ], [ 30.0, 42.0 ] ] ]