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# Vector

> Create a vector (i.e., a one-dimensional [ndarray][@stdlib/ndarray/ctor]).

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</section>

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## Usage

```javascript
var vector = require( '@stdlib/ndarray/vector/ctor' );
```

#### vector( \[dtype]\[, options] )

Returns a one-dimensional [ndarray][@stdlib/ndarray/ctor] having a specified [data type][@stdlib/ndarray/dtypes].

```javascript
var getDType = require( '@stdlib/ndarray/dtype' );
var numel = require( '@stdlib/ndarray/numel' );

var arr = vector();
// returns <ndarray>

var len = numel( arr );
// returns 0

var dt = getDType( arr );
// returns 'float64'
```

By default, the function returns an [ndarray][@stdlib/ndarray/ctor] having a [`float64`][@stdlib/ndarray/dtypes] data type. To specify an alternative [data type][@stdlib/ndarray/dtypes], provide a `dtype` argument.

```javascript
var getDType = require( '@stdlib/ndarray/dtype' );
var numel = require( '@stdlib/ndarray/numel' );

var arr = vector( 'int32' );
// returns <ndarray>

var len = numel( arr );
// returns 0

var dt = getDType( arr );
// returns 'int32'
```

The function accepts the following options:

-   **order**: specifies whether an [ndarray][@stdlib/ndarray/ctor] is `'row-major'` (C-style) or `'column-major'` (Fortran-style). Default: `'row-major'`.
-   **mode**: specifies how to handle indices which exceed array dimensions (see [`ndarray`][@stdlib/ndarray/ctor]). Default: `'throw'`.
-   **readonly**: boolean indicating whether an array should be **read-only**. Default: `false`.

#### vector( length\[, dtype]\[, options] )

Returns a one-dimensional [ndarray][@stdlib/ndarray/ctor] having a specified `length`.

```javascript
var numel = require( '@stdlib/ndarray/numel' );

var arr1 = vector( 5 );
// returns <ndarray>

var len1 = numel( arr1 );
// returns 5

var arr2 = vector( 5, 'uint8' );
// returns <ndarray>

var len2 = numel( arr2 );
// returns 5
```

#### vector( obj\[, dtype]\[, options] )

Creates a one-dimensional [ndarray][@stdlib/ndarray/ctor] from an array-like object or iterable.

```javascript
var numel = require( '@stdlib/ndarray/numel' );

var arr1 = vector( [ 0.5, 0.5, 0.5 ] );
// returns <ndarray>

var len1 = numel( arr1 );
// returns 3

var arr2 = vector( [ 0.5, 0.5, 0.5 ], 'float32' );
// returns <ndarray>

var len2 = numel( arr2 );
// returns 3
```

#### vector( buffer\[, byteOffset\[, length]]\[, dtype]\[, options] )

Returns a one-dimensional [ndarray][@stdlib/ndarray/ctor] view of an [`ArrayBuffer`][@stdlib/array/buffer].

```javascript
var ArrayBuffer = require( '@stdlib/array/buffer' );
var getDType = require( '@stdlib/ndarray/dtype' );
var numel = require( '@stdlib/ndarray/numel' );

var buf = new ArrayBuffer( 32 );

var arr1 = vector( buf );
// returns <ndarray>

var len1 = numel( arr1 );
// returns 4

var dt1 = getDType( arr1 );
// returns 'float64'

var arr2 = vector( buf, 'float32' );
// returns <ndarray>

var len2 = numel( arr2 );
// returns 8

var dt2 = getDType( arr2 );
// returns 'float32'

var arr3 = vector( buf, 16 );
// returns <ndarray>

var len3 = numel( arr3 );
// returns 2

var dt3 = getDType( arr3 );
// returns 'float64'

var arr4 = vector( buf, 16, 'float32' );
// returns <ndarray>

var len4 = numel( arr4 );
// returns 4

var dt4 = getDType( arr4 );
// returns 'float32'

var arr5 = vector( buf, 16, 1 );
// returns <ndarray>

var len5 = numel( arr5 );
// returns 1

var dt5 = getDType( arr5 );
// returns 'float64'

var arr6 = vector( buf, 10, 4, 'int16' );
// returns <ndarray>

var len6 = numel( arr6 );
// returns 4

var dt6 = getDType( arr6 );
// returns 'int16'
```

#### vector.factory( dtype\[, options] )

Returns a function for creating a one-dimensional [ndarray][@stdlib/ndarray/ctor].

```javascript
var getDType = require( '@stdlib/ndarray/dtype' );
var numel = require( '@stdlib/ndarray/numel' );

var Float32Vector = vector.factory( 'float32' );

var arr = new Float32Vector( [ 1, 2, 3 ] );
// returns <ndarray>

var dt = getDType( arr );
// returns 'float32'

var len = numel( arr );
// returns 3
```

The function supports the following parameters:

-   **dtype**: [data type][@stdlib/ndarray/dtypes].
-   **options**: function options (_optional_).

The function accepts the following options:

-   **order**: specifies whether the default memory layout for a returned [ndarray][@stdlib/ndarray/ctor] should be `'row-major'` (C-style) or `'column-major'` (Fortran-style). Default: `'row-major'`.
-   **mode**: specifies the default behavior when handling indices which exceed array dimensions (see [`ndarray`][@stdlib/ndarray/ctor]). Default: `'throw'`.
-   **readonly**: boolean indicating whether to return a **read-only** [ndarray][@stdlib/ndarray/ctor] by default. Default: `false`.

The function returned by the `factory` method supports the same arguments and options as `vector` above, except for the `dtype` argument, as the returned function always returns a one-dimensional [ndarray][@stdlib/ndarray/ctor] having the same [data type][@stdlib/ndarray/dtypes].

When providing options to the returned function, the provided option values override the defaults established during function creation.

</section>

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</section>

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## Examples

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```javascript
var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var cartesianProduct = require( '@stdlib/array/cartesian-product' );
var unzip = require( '@stdlib/utils/unzip' );
var dtypes = require( '@stdlib/ndarray/dtypes' );
var sum = require( '@stdlib/blas/ext/sum' );
var logEachMap = require( '@stdlib/console/log-each-map' );
var vector = require( '@stdlib/ndarray/vector/ctor' );

// Create an array of random array lengths:
var lens = discreteUniform( 10, 5, 15, {
    'dtype': 'int32'
});

// Resolve a list of supported ndarray integer-valued data types:
var dts = dtypes( 'integer_and_generic' );

// Create length-dtype pairs:
var pairs = cartesianProduct( lens, dts );

// Split the pairs into individual arguments:
var args = unzip( pairs );

// Define a callback to create a random vector and return the sum of all vector elements:
function clbk( len, dtype ) {
    var x = vector( discreteUniform( len, 0, 100 ), dtype );
    return sum( x ).get();
}

// Apply the callback and print the results:
logEachMap( 'len: %2d. dtype: %7s. sum: %d.', args[ 0 ], args[ 1 ], clbk );
```

</section>

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</section>

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* * *

## See Also

-   <span class="package-name">[`@stdlib/ndarray/vector/float64`][@stdlib/ndarray/vector/float64]</span><span class="delimiter">: </span><span class="description">create a double-precision floating-point vector (i.e., a one-dimensional ndarray).</span>
-   <span class="package-name">[`@stdlib/ndarray/vector/float32`][@stdlib/ndarray/vector/float32]</span><span class="delimiter">: </span><span class="description">create a single-precision floating-point vector (i.e., a one-dimensional ndarray).</span>
-   <span class="package-name">[`@stdlib/ndarray/vector/complex128`][@stdlib/ndarray/vector/complex128]</span><span class="delimiter">: </span><span class="description">create a double-precision complex floating-point vector (i.e., a one-dimensional ndarray).</span>
-   <span class="package-name">[`@stdlib/ndarray/vector/complex64`][@stdlib/ndarray/vector/complex64]</span><span class="delimiter">: </span><span class="description">create a single-precision complex floating-point vector (i.e., a one-dimensional ndarray).</span>
-   <span class="package-name">[`@stdlib/ndarray/ctor`][@stdlib/ndarray/ctor]</span><span class="delimiter">: </span><span class="description">multidimensional array constructor.</span>

</section>

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[@stdlib/array/buffer]: https://www.npmjs.com/package/@stdlib/array-buffer

[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/ndarray/tree/main/ctor

[@stdlib/ndarray/dtypes]: https://github.com/stdlib-js/ndarray/tree/main/dtypes

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[@stdlib/ndarray/vector/float64]: https://github.com/stdlib-js/ndarray/tree/main/vector/float64

[@stdlib/ndarray/vector/float32]: https://github.com/stdlib-js/ndarray/tree/main/vector/float32

[@stdlib/ndarray/vector/complex128]: https://github.com/stdlib-js/ndarray/tree/main/vector/complex128

[@stdlib/ndarray/vector/complex64]: https://github.com/stdlib-js/ndarray/tree/main/vector/complex64

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