UnaryStridedDispatch

Constructor for performing a reduction on an input ndarray.

Usage

var UnaryStridedDispatch = require( '@stdlib/stats/tools/reduce/unary-strided-dispatch' );

UnaryStridedDispatch( table, idtypes, odtypes, policy )

Constructor for performing a reduction on an input ndarray.

var base = require( '@stdlib/stats/base/ndarray/max' );

var table = {
    'default': base
};

var dtypes = [ 'float64', 'float32', 'generic' ];
var policy = 'same';

var unary = new UnaryStridedDispatch( table, [ dtypes ], dtypes, policy );

The constructor has the following parameters:

• table: strided reduction function dispatch table. Must have a 'default' property and a corresponding strided reduction function. May have additional properties corresponding to specific data types and associated specialized strided reduction functions.
• idtypes: list containing lists of supported input data types for each input ndarray argument.
• odtypes: list of supported input data types.
• policy: output data type policy.

UnaryStridedDispatch.prototype.apply( x[, ...args][, options] )

Performs a reduction on a provided input ndarray.

var ndarray = require( '@stdlib/ndarray/base/ctor' );
var base = require( '@stdlib/stats/base/ndarray/max' );

var table = {
    'default': base
};

var dtypes = [ 'float64', 'float32', 'generic' ];
var policy = 'same';

var unary = new UnaryStridedDispatch( table, [ dtypes ], dtypes, policy );

var xbuf = [ -1.0, 2.0, -3.0 ];
var x = new ndarray( 'generic', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );

var y = unary.apply( x );
// returns <ndarray>

var v = y.get();
// returns 2.0

The method has the following parameters:

• x: input ndarray.
• ...args: additional input ndarray arguments (optional).
• options: function options (optional).

The method accepts the following options:

• dims: list of dimensions over which to perform a reduction.
• dtype: output ndarray data type. Setting this option, overrides the output data type policy.
• keepdims: boolean indicating whether the reduced dimensions should be included in the returned ndarray as singleton dimensions. Default: false.

By default, the method returns an ndarray having a data type determined by the output data type policy. To override the default behavior, set the dtype option.

var ndarray = require( '@stdlib/ndarray/base/ctor' );
var base = require( '@stdlib/stats/base/ndarray/max' );
var getDType = require( '@stdlib/ndarray/dtype' );

var table = {
    'default': base
};

var dtypes = [ 'float64', 'float32', 'generic' ];
var policy = 'same';

var unary = new UnaryStridedDispatch( table, [ dtypes ], dtypes, policy );

var xbuf = [ -1.0, 2.0, -3.0 ];
var x = new ndarray( 'generic', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );

var y = unary.apply( x, {
    'dtype': 'float64'
});
// returns <ndarray>

var dt = getDType( y );
// returns 'float64'

UnaryStridedDispatch.prototype.assign( x[, ...args], out[, options] )

Performs a reduction on a provided input ndarray and assigns results to a provided output ndarray.

var base = require( '@stdlib/stats/base/ndarray/max' );
var dtypes = require( '@stdlib/ndarray/dtypes' );
var ndarray = require( '@stdlib/ndarray/base/ctor' );

var idt = dtypes( 'real_and_generic' );
var odt = idt;
var policy = 'same';

var table = {
    'default': base
};
var unary = new UnaryStridedDispatch( table, [ idt ], odt, policy );

var xbuf = [ -1.0, 2.0, -3.0 ];
var x = new ndarray( 'generic', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );

var ybuf = [ 0.0 ];
var y = new ndarray( 'generic', ybuf, [], [ 0 ], 0, 'row-major' );

var out = unary.assign( x, y );
// returns <ndarray>

var v = out.get();
// returns 2.0

var bool = ( out === y );
// returns true

The method has the following parameters:

• x: input ndarray.
• args: additional input ndarray arguments (optional).
• out: output ndarray.
• options: function options (optional).

The function accepts the following options:

• dims: list of dimensions over which to perform a reduction.

Notes

• The output data type policy only applies to the apply method. For the assign method, the output ndarray is allowed to have any data type.

Examples

var base = require( '@stdlib/stats/base/ndarray/max' );
var uniform = require( '@stdlib/random/array/uniform' );
var dtypes = require( '@stdlib/ndarray/dtypes' );
var dtype = require( '@stdlib/ndarray/dtype' );
var ndarray2array = require( '@stdlib/ndarray/to-array' );
var ndarray = require( '@stdlib/ndarray/ctor' );
var UnaryStridedDispatch = require( '@stdlib/stats/tools/reduce/unary-strided-dispatch' );

// Define the supported input and output data types:
var idt = dtypes( 'real_and_generic' );
var odt = dtypes( 'real_and_generic' );

// Define the policy mapping an input data type to an output data type:
var policy = 'same';

// Define a dispatch table:
var table = {
    'default': base
};

// Create an interface for performing a reduction:
var max = new UnaryStridedDispatch( table, [ idt ], odt, policy );

// Generate an array of random numbers:
var xbuf = uniform( 100, -1.0, 1.0, {
    'dtype': 'generic'
});

// Wrap in an ndarray:
var x = new ndarray( 'generic', xbuf, [ 10, 10 ], [ 10, 1 ], 0, 'row-major' );

// Perform a reduction:
var y = max.apply( x, {
    'dims': [ 0 ]
});

// Resolve the output array data type:
var dt = dtype( y );
console.log( dt );

// Print the results:
console.log( ndarray2array( y ) );