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# unaryStrided1d

> Apply a one-dimensional strided array function to a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.

<section class="intro">

</section>

<!-- /.intro -->

<section class="usage">

## Usage

```javascript
var unaryStrided1d = require( '@stdlib/ndarray/base/unary-strided1d' );
```

#### unaryStrided1d( fcn, arrays, dims\[, options] )

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.

<!-- eslint-disable max-len -->

```javascript
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 ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' );
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 ), ndarraylike2scalar( 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 = [ 1, 3, 2, 2 ];
var ysh = [ 1, 3, 2, 2 ];

// Define the array strides:
var sx = [ 12, 4, 2, 1 ];
var sy = [ 12, 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': [ 1, 3 ],
    'strides': [ 0, 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'
};

// Apply strided function:
unaryStrided1d( wrapper, [ x, y, initial ], [ 2, 3 ] );

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 ] ] ] ]
```

The function accepts the following arguments:

-   **fcn**: function which will be applied to a one-dimensional input subarray and should update a one-dimensional output subarray with results.
-   **arrays**: array-like object containing one input ndarray and one output ndarray, followed by any additional ndarray arguments.
-   **dims**: list of dimensions to which to apply a strided array function.
-   **options**: function options which are passed through to `fcn` (_optional_).

Each provided ndarray should be an object with the following properties:

-   **dtype**: data type.
-   **data**: data buffer.
-   **shape**: dimensions.
-   **strides**: stride lengths.
-   **offset**: index offset.
-   **order**: specifies whether an ndarray is row-major (C-style) or column major (Fortran-style).

#### TODO: document factory method

</section>

<!-- /.usage -->

<section class="notes">

## Notes

-   Any additional ndarray arguments are expected to have the same leading dimensions as the loop dimensions of the input ndarray.

-   When calling the strided array function, any additional ndarray arguments are provided as k-dimensional subarrays, where `k = M - N` with `M` being the number of dimensions in an ndarray argument and `N` being the number of loop dimensions for the input ndarray. For example, if an input ndarray has three dimensions, the number of loop dimensions is one, and an additional ndarray argument has one dimension, thus matching the number of loop dimensions for the input ndarray, the strided array function is provided a zero-dimensional subarray as an additional ndarray argument. In the same scenario but where an additional ndarray argument has two dimensions, thus exceeding the number of loop dimensions, the strided array function is provided a one-dimensional subarray as an additional ndarray argument.

-   The strided array function is expected to have the following signature:

    ```text
    fcn( arrays[, options] )
    ```

    where

    -   **arrays**: array containing a one-dimensional subarray of the input ndarray, a one-dimensional subarray of the output ndarray, and any additional ndarray arguments as subarrays.
    -   **options**: function options (_optional_).

-   The function iterates over ndarray elements according to the memory layout of the input ndarray.

-   For very high-dimensional ndarrays which are non-contiguous, one should consider copying the underlying data to contiguous memory before performing an operation in order to achieve better performance.

</section>

<!-- /.notes -->

<section class="examples">

## Examples

<!-- eslint-disable max-len -->

<!-- eslint no-undef: "error" -->

```javascript
var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var zeros = require( '@stdlib/array/base/zeros' );
var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' );
var getData = require( '@stdlib/ndarray/base/data-buffer' );
var getStride = require( '@stdlib/ndarray/base/stride' );
var getOffset = require( '@stdlib/ndarray/base/offset' );
var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' );
var gcusum = require( '@stdlib/blas/ext/base/gcusum' ).ndarray;
var unaryStrided1d = require( '@stdlib/ndarray/base/unary-strided1d' );

function wrapper( arrays ) {
    var x = arrays[ 0 ];
    var y = arrays[ 1 ];
    var s = arrays[ 2 ];
    return gcusum( numelDimension( x, 0 ), ndarraylike2scalar( s ), getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ) );
}

var N = 10;
var x = {
    'dtype': 'generic',
    'data': discreteUniform( N, -5, 5, {
        'dtype': 'generic'
    }),
    'shape': [ 1, 5, 2 ],
    'strides': [ 10, 2, 1 ],
    'offset': 0,
    'order': 'row-major'
};
var initial = {
    'dtype': 'generic',
    'data': [ 0.0 ],
    'shape': [ 1, 2 ],
    'strides': [ 0, 0 ],
    'offset': 0,
    'order': 'row-major'
};
var y = {
    'dtype': 'generic',
    'data': zeros( N ),
    'shape': [ 1, 5, 2 ],
    'strides': [ 10, 2, 1 ],
    'offset': 0,
    'order': 'row-major'
};

unaryStrided1d( wrapper, [ x, y, initial ], [ 1 ] );

console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) );
console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) );
```

</section>

<!-- /.examples -->

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<section class="related">

</section>

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<section class="links">

</section>

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