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* @license Apache-2.0
*
* Copyright (c) 2025 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
'use strict';
// MODULES //
var isComplexArray = require( '@stdlib/array/base/assert/is-complex-typed-array' );
var isBooleanArray = require( '@stdlib/array/base/assert/is-booleanarray' );
var iterationOrder = require( '@stdlib/ndarray/base/iteration-order' );
var minmaxViewBufferIndex = require( '@stdlib/ndarray/base/minmax-view-buffer-index' );
var ndarray2object = require( '@stdlib/ndarray/base/ndarraylike2object' );
var reinterpretComplex = require( '@stdlib/strided/base/reinterpret-complex' );
var reinterpretBoolean = require( '@stdlib/strided/base/reinterpret-boolean' );
var gscal = require( '@stdlib/blas/base/gscal' );
var blockedaccessorsome2d = require( './2d_blocked_accessors.js' );
var blockedaccessorsome3d = require( './3d_blocked_accessors.js' );
var blockedcomplexsome2d = require( './2d_blocked_complex.js' );
var blockedcomplexsome3d = require( './3d_blocked_complex.js' );
var blockedsome2d = require( './2d_blocked.js' );
var blockedsome3d = require( './3d_blocked.js' );
var accessorsome0d = require( './0d_accessors.js' );
var accessorsome1d = require( './1d_accessors.js' );
var accessorsome2d = require( './2d_accessors.js' );
var accessorsome3d = require( './3d_accessors.js' );
var accessorsomend = require( './nd_accessors.js' );
var complexsome0d = require( './0d_complex.js' );
var complexsome1d = require( './1d_complex.js' );
var complexsome2d = require( './2d_complex.js' );
var complexsome3d = require( './3d_complex.js' );
var complexsomend = require( './nd_complex.js' );
var some0d = require( './0d.js' );
var some1d = require( './1d.js' );
var some2d = require( './2d.js' );
var some3d = require( './3d.js' );
var somend = require( './nd.js' );
// VARIABLES //
var SOME = [
some0d,
some1d,
some2d,
some3d
];
var ACCESSOR_SOME = [
accessorsome0d,
accessorsome1d,
accessorsome2d,
accessorsome3d
];
var COMPLEX_SOME = [
complexsome0d,
complexsome1d,
complexsome2d,
complexsome3d
];
var BLOCKED_SOME = [
blockedsome2d, // 0
blockedsome3d
];
var BLOCKED_ACCESSOR_SOME = [
blockedaccessorsome2d, // 0
blockedaccessorsome3d
];
var BLOCKED_COMPLEX_SOME = [
blockedcomplexsome2d, // 0
blockedcomplexsome3d
];
var MAX_DIMS = SOME.length - 1;
// MAIN //
/**
* Tests whether at least `n` elements in an ndarray are truthy.
*
* ## Notes
*
* - A 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).
*
* @param {ArrayLikeObject<Object>} arrays - array-like object containing an input ndarray and a zero-dimensional ndarray specifying the minimum number of elements in the input ndarray that must satisfy the predicate function
* @returns {boolean} boolean indicating whether at least `n` elements are truthy
*
* @example
* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
* var Float64Array = require( '@stdlib/array/float64' );
*
* // Create a data buffer:
* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 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'
* };
*
* // Define the success criterion:
* var n = scalar2ndarray( 3, {
* 'dtype': 'generic'
* });
*
* // Test elements:
* var out = some( [ x, n ] );
* // returns true
*/
function some( arrays ) {
var isCmplx;
var ndims;
var xmmv;
var shx;
var iox;
var len;
var sx;
var ox;
var ns;
var N;
var x;
var n;
var d;
var i;
// Unpack the ndarray and standardize ndarray meta data:
x = ndarray2object( arrays[ 0 ] );
n = ndarray2object( arrays[ 1 ] );
shx = x.shape;
ndims = shx.length;
// Resolve the success criterion:
N = n.accessors[ 0 ]( n.data, n.offset );
if ( N < 1 ) {
return true;
}
// Check for known array types which can be reinterpreted for better iteration performance...
if ( isBooleanArray( x.data ) ) {
x.data = reinterpretBoolean( x.data, 0 );
x.accessorProtocol = false;
} else if ( isComplexArray( x.data ) ) {
x.data = reinterpretComplex( x.data, 0 );
x.accessorProtocol = false;
x.strides = gscal( ndims, 2, x.strides, 1 );
x.offset *= 2;
isCmplx = true;
}
// Determine whether we can avoid iteration altogether...
if ( ndims === 0 ) {
if ( x.accessorProtocol ) {
return ACCESSOR_SOME[ ndims ]( x, N );
}
if ( isCmplx ) {
return COMPLEX_SOME[ ndims ]( x, N );
}
return SOME[ ndims ]( x, N );
}
// Compute the number of elements and the number of singleton dimensions...
len = 1; // number of elements
ns = 0; // number of singleton dimensions
for ( i = 0; i < ndims; i++ ) {
d = shx[ i ];
// Note that, if one of the dimensions is `0`, the length will be `0`...
len *= d;
// Check whether the current dimension is a singleton dimension...
if ( d === 1 ) {
ns += 1;
}
}
// Check whether we were provided an empty ndarray...
if ( len === 0 ) {
return false;
}
// Determine whether the ndarray is one-dimensional and thus readily translates to a one-dimensional strided array...
if ( ndims === 1 ) {
if ( x.accessorProtocol ) {
return ACCESSOR_SOME[ ndims ]( x, N );
}
if ( isCmplx ) {
return COMPLEX_SOME[ ndims ]( x, N );
}
return SOME[ ndims ]( x, N );
}
sx = x.strides;
// Determine whether the ndarray has only **one** non-singleton dimension (e.g., ndims=4, shape=[10,1,1,1]) so that we can treat an ndarray as being equivalent to a one-dimensional strided array...
if ( ns === ndims-1 ) {
// Get the index of the non-singleton dimension...
for ( i = 0; i < ndims; i++ ) {
if ( shx[ i ] !== 1 ) {
break;
}
}
x.shape = [ shx[i] ];
x.strides = [ sx[i] ];
if ( x.accessorProtocol ) {
return ACCESSOR_SOME[ 1 ]( x, N );
}
if ( isCmplx ) {
return COMPLEX_SOME[ 1 ]( x, N );
}
return SOME[ 1 ]( x, N );
}
iox = iterationOrder( sx ); // +/-1
// Determine whether we can avoid blocked iteration...
if ( iox !== 0 ) {
// Determine the minimum and maximum linear indices which are accessible by the array view:
xmmv = minmaxViewBufferIndex( shx, sx, x.offset );
// Determine whether we can ignore shape (and strides) and treat the ndarray as a linear one-dimensional strided array...
if ( len === ( xmmv[1]-xmmv[0]+1 ) || ( isCmplx && len*2 === ( xmmv[1]-xmmv[0]+1 ) ) ) { // eslint-disable-line max-len
// Note: the above is equivalent to @stdlib/ndarray/base/assert/is-contiguous, but in-lined so we can retain computed values...
if ( iox === 1 ) {
ox = xmmv[ 0 ];
} else {
ox = xmmv[ 1 ];
}
x.shape = [ len ];
x.strides = [ ( isCmplx ) ? iox*2 : iox ];
x.offset = ox;
if ( x.accessorProtocol ) {
return ACCESSOR_SOME[ 1 ]( x, N );
}
if ( isCmplx ) {
return COMPLEX_SOME[ 1 ]( x, N );
}
return SOME[ 1 ]( x, N );
}
// The ndarray is non-contiguous, so we cannot directly use one-dimensional array functionality...
// Determine whether we can use simple nested loops...
if ( ndims <= MAX_DIMS ) {
// So long as iteration always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...
if ( x.accessorProtocol ) {
return ACCESSOR_SOME[ ndims ]( x, N );
}
if ( isCmplx ) {
return COMPLEX_SOME[ ndims ]( x, N );
}
return SOME[ ndims ]( x, N );
}
// Fall-through to blocked iteration...
}
// At this point, we're either dealing with a non-contiguous n-dimensional array or a high dimensional n-dimensional array, so our only hope is that we can still perform blocked iteration...
// Determine whether we can perform blocked iteration...
if ( ndims <= MAX_DIMS ) {
if ( x.accessorProtocol ) {
return BLOCKED_ACCESSOR_SOME[ ndims-2 ]( x, N );
}
if ( isCmplx ) {
return BLOCKED_COMPLEX_SOME[ ndims-2 ]( x, N );
}
return BLOCKED_SOME[ ndims-2 ]( x, N );
}
// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...
if ( x.accessorProtocol ) {
return accessorsomend( x, N );
}
if ( isCmplx ) {
return complexsomend( x, N );
}
return somend( x, N );
}
// EXPORTS //
module.exports = some;
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