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# accumulateUnary

> Perform a reduction over elements in an input ndarray.

<section class="intro">

</section>

<!-- /.intro -->

<section class="usage">

## Usage

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

#### accumulateUnary( arrays, initial, clbk )

Performs a reduction over elements in an input ndarray.

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

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

function add( acc, x ) {
    return acc + x;
}

// Create a data buffer:
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 ] );

// Define the shape of the input array:
var shape = [ 3, 1, 2 ];

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

// Define the index offset:
var ox = 1;

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

// Compute the sum:
var v = accumulateUnary( [ x ], 0.0, add );
// returns 39.0
```

The function accepts the following arguments:

-   **arrays**: array-like object containing one input ndarray.
-   **initial**: initial value.
-   **clbk**: callback function to apply.

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).

The callback is invoked with two arguments:

-   **acc**: the current accumulated value. The first time the callback is invoked, `acc` is equal to the initial value.
-   **value**: the current element.

After each callback invocation, the callback return value is subsequently used as the accumulated value for the next callback invocation.

</section>

<!-- /.usage -->

<section class="notes">

## Notes

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

</section>

<!-- /.notes -->

<section class="examples">

## Examples

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

```javascript
var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
var add = require( '@stdlib/number/float64/base/add' );
var accumulateUnary = require( '@stdlib/ndarray/base/unary-accumulate' );

var N = 10;
var x = {
    'dtype': 'generic',
    'data': discreteUniform( N, -100, 100, {
        'dtype': 'generic'
    }),
    'shape': [ 5, 2 ],
    'strides': [ 2, 1 ],
    'offset': 0,
    'order': 'row-major'
};

var sum = accumulateUnary( [ x ], 0.0, add );
console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) );

console.log( 'sum: %d', sum );
```

</section>

<!-- /.examples -->

<!-- C interface documentation. -->

* * *

<section class="c">

## C APIs

<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->

<section class="intro">

Character codes for data types:

<!-- The following is auto-generated. Do not manually edit. See scripts/loops.js. -->

<!-- charcodes -->

-   **x**: `bool` (boolean).
-   **c**: `complex64` (single-precision floating-point complex number).
-   **z**: `complex128` (double-precision floating-point complex number).
-   **f**: `float32` (single-precision floating-point number).
-   **d**: `float64` (double-precision floating-point number).
-   **k**: `int16` (signed 16-bit integer).
-   **i**: `int32` (signed 32-bit integer).
-   **s**: `int8` (signed 8-bit integer).
-   **t**: `uint16` (unsigned 16-bit integer).
-   **u**: `uint32` (unsigned 32-bit integer).
-   **b**: `uint8` (unsigned 8-bit integer).

<!-- ./charcodes -->

Function name suffix naming convention:

```text
stdlib_ndarray_<accumulation_data_type><input_data_type>_<output_data_type>[_as_<callback_arg1_data_type><callback_arg2_data_type>_<callback_return_data_type>]
```

For example,

<!-- run-disable -->

```c
void stdlib_ndarray_accumulate_dd_d(...) {...}
```

is a function which performs accumulation in double-precision and accepts one double-precision floating-point input ndarray and one double-precision floating-point output ndarray. In other words, the suffix encodes the function type signature.

To support callbacks whose input arguments and/or return values are of a different data type than the input and/or output ndarray data types, the naming convention supports appending an `as` suffix. For example,

<!-- run-disable -->

```c
void stdlib_ndarray_accumulate_ff_f_as_dd_d(...) {...}
```

is a function which performs accumulation in single-precision and accepts one single-precision floating-point input ndarray and one single-precision floating-point output ndarray. However, the callback accepts and returns double-precision floating-point numbers. Accordingly, the input and output values need to be cast using the following conversion sequence

```c
// Convert the current accumulated value to double-precision:
double curr = (double)acc;

// Convert each input array element to double-precision:
double in1 = (double)x[ i ];

// Evaluate the callback:
double out = f( curr, in1 );

// Convert the callback return value to single-precision:
acc = (float)out;
```

The accumulation data type and the output ndarray data type should **always** be the same.

The callback is invoked with two arguments:

-   **acc**: the current accumulated value. The first time the callback is invoked, this argument is equal to the initial value.
-   **value**: the current element.

After each callback invocation, the callback return value is subsequently used as the accumulated value for the next callback invocation.

</section>

<!-- /.intro -->

<!-- C usage documentation. -->

<section class="usage">

### Usage

```c
#include "stdlib/ndarray/base/unary_accumulate.h"
```

<!-- The following is auto-generated. Do not manually edit. See scripts/loops.js. -->

<!-- loops -->

<!-- ./loops -->

<!-- macros -->

<!-- TODO: consider documenting macros -->

<!-- ./macros -->

</section>

<!-- /.usage -->

<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->

<section class="notes">

* * *

### Notes

-   The initial value and output ndarrays are assumed to be zero-dimensional ndarrays.

</section>

<!-- /.notes -->

<!-- C API usage examples. -->

* * *

<section class="examples">

### Examples

```c
#include "stdlib/ndarray/base/unary_accumulate.h"
#include "stdlib/ndarray/dtypes.h"
#include "stdlib/ndarray/index_modes.h"
#include "stdlib/ndarray/orders.h"
#include "stdlib/ndarray/ctor.h"
#include <stdint.h>
#include <stdlib.h>
#include <stdio.h>
#include <inttypes.h>

static void print_ndarray_contents( const struct ndarray *x ) {
    int64_t i;
    int8_t s;
    double v;

    for ( i = 0; i < stdlib_ndarray_length( x ); i++ ) {
        s = stdlib_ndarray_iget_float64( x, i, &v );
        if ( s != 0 ) {
            fprintf( stderr, "Unable to resolve data element.\n" );
            exit( EXIT_FAILURE );
        }
        fprintf( stdout, "data[%"PRId64"] = %lf\n", i, v );
    }
}

static double add( const double acc, const double x ) {
    return acc + x;
}

int main( void ) {
    // Define the ndarray data type:
    enum STDLIB_NDARRAY_DTYPE dtype = STDLIB_NDARRAY_FLOAT64;

    // Create underlying byte arrays:
    double xvalues[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 };
    double ivalues[] = { 0.0 };
    double ovalues[] = { 0.0 };

    uint8_t *xbuf = (uint8_t *)xvalues;
    uint8_t *ibuf = (uint8_t *)ivalues;
    uint8_t *obuf = (uint8_t *)ovalues;

    // Define the number of dimensions:
    int64_t ndims = 3;

    // Define the array shapes:
    int64_t xsh[] = { 2, 2, 2 };
    int64_t ish[] = {};
    int64_t osh[] = {};

    // Define the strides:
    int64_t sx[] = { 32, 16, 8 };
    int64_t si[] = { 0 };
    int64_t so[] = { 0 };

    // Define the offsets:
    int64_t ox = 0;
    int64_t oi = 0;
    int64_t oo = 0;

    // Define the array order:
    enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR;

    // Specify the index mode:
    enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR;

    // Specify the subscript index modes:
    int8_t submodes[] = { imode };
    int64_t nsubmodes = 1;

    // Create an input ndarray:
    struct ndarray *x = stdlib_ndarray_allocate( dtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes );
    if ( x == NULL ) {
        fprintf( stderr, "Error allocating memory.\n" );
        exit( EXIT_FAILURE );
    }

    // Create an initial value zero-dimensional ndarray:
    struct ndarray *initial = stdlib_ndarray_allocate( dtype, ibuf, ndims, ish, si, oi, order, imode, nsubmodes, submodes );
    if ( initial == NULL ) {
        fprintf( stderr, "Error allocating memory.\n" );
        exit( EXIT_FAILURE );
    }

    // Create an output zero-dimensional ndarray:
    struct ndarray *out = stdlib_ndarray_allocate( dtype, obuf, ndims, osh, so, oo, order, imode, nsubmodes, submodes );
    if ( out == NULL ) {
        fprintf( stderr, "Error allocating memory.\n" );
        exit( EXIT_FAILURE );
    }

    // Define an array containing the ndarrays:
    struct ndarray *arrays[] = { x, initial, out };

    // Apply the callback:
    int8_t status = stdlib_ndarray_accumulate_dd_d( arrays, (void *)add );
    if ( status != 0 ) {
        fprintf( stderr, "Error during computation.\n" );
        exit( EXIT_FAILURE );
    }

    // Print the results:
    print_ndarray_contents( out );
    fprintf( stdout, "\n" );

    // Free allocated memory:
    stdlib_ndarray_free( x );
    stdlib_ndarray_free( initial );
    stdlib_ndarray_free( out );
}
```

</section>

<!-- /.examples -->

</section>

<!-- /.c -->

<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->

<section class="related">

</section>

<!-- /.related -->

<section class="links">

<!-- <related-links> -->

<!-- </related-links> -->

</section>

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