# forEach
> Invoke a callback function once for each element in an ndarray.
## Usage
```javascript
var forEach = require( '@stdlib/ndarray/base/for-each' );
```
#### forEach( arrays, fcn\[, thisArg] )
Invokes a callback function once for each element in an ndarray.
```javascript
var Float64Array = require( '@stdlib/array/float64' );
var naryFunction = require( '@stdlib/utils/nary-function' );
var log = require( '@stdlib/console/log' );
// Create data buffers:
var xbuf = new Float64Array( 12 );
// Define the shape of the array:
var shape = [ 3, 1, 2 ];
// Define the array strides:
var sx = [ 4, 4, 1 ];
// Define the index offset:
var ox = 1;
// Create an ndarray-like object:
var x = {
'dtype': 'float64',
'data': xbuf,
'shape': shape,
'strides': sx,
'offset': ox,
'order': 'row-major'
};
// Apply the callback function:
forEach( [ x ], naryFunction( log, 1 ) );
```
The function accepts the following arguments:
- **arrays**: array-like object containing an input ndarray.
- **fcn**: callback to apply.
- **thisArg**: callback execution context.
The callback function is provided the following arguments:
- **value**: current array element.
- **indices**: current array element indices.
- **arr**: the input ndarray.
## Notes
- The 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).
- For very high-dimensional ndarrays which are non-contiguous, one should consider copying the underlying data to contiguous memory before applying a callback function in order to achieve better performance.
## Examples
```javascript
var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
var zeroTo = require( '@stdlib/array/base/zero-to' );
var naryFunction = require( '@stdlib/utils/nary-function' );
var log = require( '@stdlib/console/log' );
var forEach = require( '@stdlib/ndarray/base/for-each' );
var x = {
'dtype': 'generic',
'data': zeroTo( 10 ),
'shape': [ 5, 2 ],
'strides': [ -2, 1 ],
'offset': 8,
'order': 'row-major'
};
log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) );
forEach( [ x ], naryFunction( log, 2 ) );
x = {
'dtype': 'generic',
'data': zeroTo( 10 ),
'shape': [ 5, 2 ],
'strides': [ 1, -5 ],
'offset': 5,
'order': 'column-major'
};
log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) );
forEach( [ x ], naryFunction( log, 2 ) );
x = {
'dtype': 'generic',
'data': zeroTo( 18 ),
'shape': [ 2, 3, 3 ],
'strides': [ 9, 3, 1 ],
'offset': 0,
'order': 'row-major'
};
log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) );
forEach( [ x ], naryFunction( log, 2 ) );
x = {
'dtype': 'generic',
'data': zeroTo( 18 ),
'shape': [ 2, 3, 3 ],
'strides': [ -1, -2, -6 ],
'offset': 17,
'order': 'column-major'
};
log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) );
forEach( [ x ], naryFunction( log, 2 ) );
```