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Test whether at least
n
elements along one or morendarray
dimensions pass a test implemented by a predicate function.
npm install @stdlib/ndarray-some-by
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var someBy = require( '@stdlib/ndarray-some-by' );
Tests whether at least n
elements along one or more ndarray
dimensions pass a test implemented by a predicate function.
var array = require( '@stdlib/ndarray-array' );
function predicate( value ) {
return value > 0.0;
}
// Create an input ndarray:
var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
// returns <ndarray>
// Perform reduction:
var out = someBy( x, 2, predicate );
// returns <ndarray>
console.log( out.get() );
// => true
The function accepts the following arguments:
- x: input
ndarray
. - n: number of elements which must pass the test implemented by a predicate function. May be either a scalar or an
ndarray
. Must be broadcast-compatible with the non-reduced dimensions of inputndarray
. Must have an integer data type. - options: function options (optional).
- predicate: predicate function.
- thisArg: predicate execution context (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.
var array = require( '@stdlib/ndarray-array' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
function predicate( value ) {
return value > 0.0;
}
// Create an input ndarray:
var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
// returns <ndarray>
var opts = {
'dims': [ 0, 1 ]
};
// Perform reduction:
var out = someBy( x, 2, opts, predicate );
// returns <ndarray>
var v = ndarray2array( out );
// returns [ true, true ]
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
.
var array = require( '@stdlib/ndarray-array' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
function predicate( value ) {
return value > 0.0;
}
// Create an input ndarray:
var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
// returns <ndarray>
var opts = {
'dims': [ 0, 1 ],
'keepdims': true
};
// Perform reduction:
var out = someBy( x, 2, opts, predicate );
// returns <ndarray>
var v = ndarray2array( out );
// returns [ [ [ true, true ] ] ]
To set the predicate function execution context, provide a thisArg
.
var array = require( '@stdlib/ndarray-array' );
function predicate( value ) {
this.count += 1;
return value > 0.0;
}
// Create an input ndarray:
var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
// returns <ndarray>
// Create a context object:
var ctx = {
'count': 0
};
// Perform operation:
var out = someBy( x, 2, predicate, ctx );
// returns <ndarray>
var v = out.get();
// returns true
var count = ctx.count;
// returns 2
Tests whether at least n
elements along one or more ndarray
dimensions pass a test implemented by a predicate function and assigns results to a provided output ndarray
.
var array = require( '@stdlib/ndarray-array' );
var empty = require( '@stdlib/ndarray-empty' );
function predicate( value ) {
return value > 0.0;
}
// Create an input ndarray:
var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
// returns <ndarray>
// Create an output ndarray:
var y = empty( [], {
'dtype': 'bool'
});
// Perform reduction:
var out = someBy.assign( x, 2, y, predicate );
// returns <ndarray>
var bool = ( out === y );
// returns true
var v = y.get();
// returns true
The function accepts the following arguments:
- x: input
ndarray
. - n: number of elements which must pass the test implemented by a predicate function. May be either a scalar or an
ndarray
. Must be broadcast-compatible with the non-reduced dimensions of inputndarray
. Must have an integer data type. - out: output
ndarray
. The outputndarray
must have a shape matching the non-reduced dimensions of the inputndarray
. - options: function options (optional).
- predicate: predicate function.
- thisArg: predicate execution context (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.
var array = require( '@stdlib/ndarray-array' );
var empty = require( '@stdlib/ndarray-empty' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
function predicate( value ) {
return value > 0.0;
}
// Create an input ndarray:
var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
// returns <ndarray>
// Create an output ndarray:
var y = empty( [ 2 ], {
'dtype': 'bool'
});
var opts = {
'dims': [ 0, 1 ]
};
// Perform reduction:
var out = someBy.assign( x, 2, y, opts, predicate );
var bool = ( out === y );
// returns true
var v = ndarray2array( y );
// returns [ true, true ]
-
The predicate function is provided the following arguments:
- value: current array element.
- indices: current array element indices.
- arr: the input ndarray.
var discreteUniform = require( '@stdlib/random-base-discrete-uniform' ).factory;
var isEven = require( '@stdlib/assert-is-even' ).isPrimitive;
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var scalar2ndarray = require( '@stdlib/ndarray-from-scalar' );
var fillBy = require( '@stdlib/ndarray-fill-by' );
var zeros = require( '@stdlib/ndarray-zeros' );
var someBy = require( '@stdlib/ndarray-some-by' );
var x = zeros( [ 2, 4, 5 ], {
'dtype': 'float64'
});
x = fillBy( x, discreteUniform( 0, 10 ) );
console.log( ndarray2array( x ) );
var n = scalar2ndarray( 4, {
'dtype': 'int8'
});
var y = someBy( x, n, isEven );
console.log( y.get() );
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
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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