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Test whether an
ndarray
contains a specified value along one or more dimensions.
import includes from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-includes@deno/mod.js';
You can also import the following named exports from the package:
import { assign } from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-includes@deno/mod.js';
Tests whether an ndarray
contains a specified value along one or more dimensions.
import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@deno/mod.js';
import ndarray from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-ctor@deno/mod.js';
// 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 sh = [ 3, 1, 2 ];
// Define the array strides:
var sx = [ 4, 4, 1 ];
// Define the index offset:
var ox = 1;
// Create an input ndarray:
var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
// Perform reduction:
var out = includes( x, 6.0 );
// returns <ndarray>
var v = out.get();
// returns true
The function accepts the following arguments:
- x: input
ndarray
. - searchElement: search element. May be either a scalar or an
ndarray
. Must be broadcast-compatible with the non-reduced dimensions of inputndarray
. Must have a data type which can be (mostly) safely cast to the data type of the inputndarray
. - options: function options (optional).
The function accepts the following options
:
- dims: list of dimensions over which to perform a reduction.
- keepdims: boolean indicating whether the reduced dimensions should be included in the returned
ndarray
as singleton dimensions. Default:false
.
By default, the function performs a reduction over all elements in a provided ndarray
. To reduce specific dimensions, set the dims
option.
import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@deno/mod.js';
import ndarray from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-ctor@deno/mod.js';
import ndarray2array from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-to-array@deno/mod.js';
// 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 sh = [ 3, 1, 2 ];
// Define the array strides:
var sx = [ 4, 4, 1 ];
// Define the index offset:
var ox = 1;
// Create an input ndarray:
var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
// Perform reduction:
var out = includes( x, 6.0, {
'dims': [ 1, 2 ]
});
// returns <ndarray>
var v = ndarray2array( out );
// returns [ false, true, false ]
By default, the function returns an ndarray
having a shape matching only the non-reduced dimensions of the input ndarray
(i.e., the reduced dimensions are dropped). To include the reduced dimensions as singleton dimensions in the output ndarray
, set the keepdims
option to true
.
import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@deno/mod.js';
import ndarray from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-ctor@deno/mod.js';
import ndarray2array from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-to-array@deno/mod.js';
// 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 sh = [ 3, 1, 2 ];
// Define the array strides:
var sx = [ 4, 4, 1 ];
// Define the index offset:
var ox = 1;
// Create an input ndarray:
var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
// Perform reduction:
var out = includes( x, 6.0, {
'dims': [ 1, 2 ],
'keepdims': true
});
// returns <ndarray>
var v = ndarray2array( out );
// returns [ [ [ false ] ], [ [ true ] ], [ [ false ] ] ]
Tests whether an ndarray
contains a specified value along one or more dimensions and assigns results to a provided output ndarray
.
import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@deno/mod.js';
import ndarray from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-ctor@deno/mod.js';
import empty from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-empty@deno/mod.js';
// 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 sh = [ 3, 1, 2 ];
// Define the array strides:
var sx = [ 4, 4, 1 ];
// Define the index offset:
var ox = 1;
// Create an input ndarray:
var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
// Create an output ndarray:
var y = empty( [], {
'dtype': 'bool'
});
// Perform reduction:
var out = includes.assign( x, 6.0, y );
// returns <ndarray>
var bool = ( out === y );
// returns true
var v = y.get();
// returns true
The function accepts the following arguments:
- x: input
ndarray
. - searchElement: search element. May be either a scalar or an
ndarray
. Must be broadcast-compatible with the non-reduced dimensions of inputndarray
. Must have a data type which can be (mostly) safely cast to the data type of the inputndarray
. - out: output
ndarray
. The outputndarray
must have a shape matching the non-reduced dimensions of the inputndarray
. - options: function options (optional).
The function accepts the following options
:
- dims: list of dimensions over which to perform a reduction.
By default, the function performs a reduction over all elements in a provided ndarray
. To reduce specific dimensions, set the dims
option.
import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@deno/mod.js';
import ndarray from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-ctor@deno/mod.js';
import empty from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-empty@deno/mod.js';
import ndarray2array from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-to-array@deno/mod.js';
// 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 sh = [ 3, 1, 2 ];
// Define the array strides:
var sx = [ 4, 4, 1 ];
// Define the index offset:
var ox = 1;
// Create an input ndarray:
var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
// Create an output ndarray:
var y = empty( [ 3 ], {
'dtype': 'bool'
});
// Perform reduction:
var out = includes.assign( x, 6.0, y, {
'dims': [ 1, 2 ]
});
var bool = ( out === y );
// returns true
var v = ndarray2array( y );
// returns [ false, true, false ]
var discreteUniform = require( 'https://cdn.jsdelivr.net/gh/stdlib-js/random-base-discrete-uniform' ).factory;
import ndarray2array from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-to-array@deno/mod.js';
import fillBy from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-fill-by@deno/mod.js';
import zeros from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-zeros@deno/mod.js';
import includes from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-includes@deno/mod.js';
var x = zeros( [ 2, 4, 5 ], {
'dtype': 'float64'
});
x = fillBy( x, discreteUniform( 0, 10 ) );
console.log( ndarray2array( x ) );
var y = includes( x, 1 );
console.log( 'includes(x[:,:,:], 1) =' );
console.log( y.get() );
y = includes( x, 2, {
'dims': [ 0 ],
'keepdims': true
});
console.log( 'includes(x[:,j,k], 2) =' );
console.log( ndarray2array( y ) );
y = includes( x, 3, {
'dims': [ 1 ],
'keepdims': true
});
console.log( 'includes(x[i,:,k], 3) =' );
console.log( ndarray2array( y ) );
y = includes( x, 4, {
'dims': [ 2 ],
'keepdims': true
});
console.log( 'includes(x[i,j,:], 4) =' );
console.log( ndarray2array( y ) );
y = includes( x, 5, {
'dims': [ 0, 1 ],
'keepdims': true
});
console.log( 'includes(x[:,:,k], 5) =' );
console.log( ndarray2array( y ) );
y = includes( x, 6, {
'dims': [ 0, 2 ],
'keepdims': true
});
console.log( 'includes(x[:,j,:], 6) =' );
console.log( ndarray2array( y ) );
y = includes( x, 7, {
'dims': [ 1, 2 ],
'keepdims': true
});
console.log( 'includes(x[i,:,:], 7) =' );
console.log( ndarray2array( y ) );
y = includes( x, 8, {
'dims': [ 0, 1, 2 ],
'keepdims': true
});
console.log( 'includes(x[:,:,:], 8) =' );
console.log( ndarray2array( y ) );
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For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
See LICENSE.
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