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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 blockedaccessorcount2d = require( './2d_blocked_accessors.js' );
var blockedaccessorcount3d = require( './3d_blocked_accessors.js' );
var blockedaccessorcount4d = require( './4d_blocked_accessors.js' );
var blockedaccessorcount5d = require( './5d_blocked_accessors.js' );
var blockedaccessorcount6d = require( './6d_blocked_accessors.js' );
var blockedaccessorcount7d = require( './7d_blocked_accessors.js' );
var blockedaccessorcount8d = require( './8d_blocked_accessors.js' );
var blockedaccessorcount9d = require( './9d_blocked_accessors.js' );
var blockedaccessorcount10d = require( './10d_blocked_accessors.js' );
var blockedcomplexcount2d = require( './2d_blocked_complex.js' );
var blockedcomplexcount3d = require( './3d_blocked_complex.js' );
var blockedcomplexcount4d = require( './4d_blocked_complex.js' );
var blockedcomplexcount5d = require( './5d_blocked_complex.js' );
var blockedcomplexcount6d = require( './6d_blocked_complex.js' );
var blockedcomplexcount7d = require( './7d_blocked_complex.js' );
var blockedcomplexcount8d = require( './8d_blocked_complex.js' );
var blockedcomplexcount9d = require( './9d_blocked_complex.js' );
var blockedcomplexcount10d = require( './10d_blocked_complex.js' );
var blockedcount2d = require( './2d_blocked.js' );
var blockedcount3d = require( './3d_blocked.js' );
var blockedcount4d = require( './4d_blocked.js' );
var blockedcount5d = require( './5d_blocked.js' );
var blockedcount6d = require( './6d_blocked.js' );
var blockedcount7d = require( './7d_blocked.js' );
var blockedcount8d = require( './8d_blocked.js' );
var blockedcount9d = require( './9d_blocked.js' );
var blockedcount10d = require( './10d_blocked.js' );
var accessorcount0d = require( './0d_accessors.js' );
var accessorcount1d = require( './1d_accessors.js' );
var accessorcount2d = require( './2d_accessors.js' );
var accessorcount3d = require( './3d_accessors.js' );
var accessorcount4d = require( './4d_accessors.js' );
var accessorcount5d = require( './5d_accessors.js' );
var accessorcount6d = require( './6d_accessors.js' );
var accessorcount7d = require( './7d_accessors.js' );
var accessorcount8d = require( './8d_accessors.js' );
var accessorcount9d = require( './9d_accessors.js' );
var accessorcount10d = require( './10d_accessors.js' );
var accessorcountnd = require( './nd_accessors.js' );
var complexcount0d = require( './0d_complex.js' );
var complexcount1d = require( './1d_complex.js' );
var complexcount2d = require( './2d_complex.js' );
var complexcount3d = require( './3d_complex.js' );
var complexcount4d = require( './4d_complex.js' );
var complexcount5d = require( './5d_complex.js' );
var complexcount6d = require( './6d_complex.js' );
var complexcount7d = require( './7d_complex.js' );
var complexcount8d = require( './8d_complex.js' );
var complexcount9d = require( './9d_complex.js' );
var complexcount10d = require( './10d_complex.js' );
var complexcountnd = require( './nd_complex.js' );
var count0d = require( './0d.js' );
var count1d = require( './1d.js' );
var count2d = require( './2d.js' );
var count3d = require( './3d.js' );
var count4d = require( './4d.js' );
var count5d = require( './5d.js' );
var count6d = require( './6d.js' );
var count7d = require( './7d.js' );
var count8d = require( './8d.js' );
var count9d = require( './9d.js' );
var count10d = require( './10d.js' );
var countnd = require( './nd.js' );
// VARIABLES //
var COUNT = [
count0d,
count1d,
count2d,
count3d,
count4d,
count5d,
count6d,
count7d,
count8d,
count9d,
count10d
];
var ACCESSOR_COUNT = [
accessorcount0d,
accessorcount1d,
accessorcount2d,
accessorcount3d,
accessorcount4d,
accessorcount5d,
accessorcount6d,
accessorcount7d,
accessorcount8d,
accessorcount9d,
accessorcount10d
];
var COMPLEX_COUNT = [
complexcount0d,
complexcount1d,
complexcount2d,
complexcount3d,
complexcount4d,
complexcount5d,
complexcount6d,
complexcount7d,
complexcount8d,
complexcount9d,
complexcount10d
];
var BLOCKED_COUNT = [
blockedcount2d, // 0
blockedcount3d,
blockedcount4d,
blockedcount5d,
blockedcount6d,
blockedcount7d,
blockedcount8d,
blockedcount9d,
blockedcount10d // 8
];
var BLOCKED_ACCESSOR_COUNT = [
blockedaccessorcount2d, // 0
blockedaccessorcount3d,
blockedaccessorcount4d,
blockedaccessorcount5d,
blockedaccessorcount6d,
blockedaccessorcount7d,
blockedaccessorcount8d,
blockedaccessorcount9d,
blockedaccessorcount10d // 8
];
var BLOCKED_COMPLEX_COUNT = [
blockedcomplexcount2d, // 0
blockedcomplexcount3d,
blockedcomplexcount4d,
blockedcomplexcount5d,
blockedcomplexcount6d,
blockedcomplexcount7d,
blockedcomplexcount8d,
blockedcomplexcount9d,
blockedcomplexcount10d // 8
];
var MAX_DIMS = COUNT.length - 1;
// MAIN //
/**
* Counts the number of truthy elements in an ndarray.
*
* ## 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 one input array
* @returns {NonNegativeInteger} result
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* // 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 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'
* };
*
* // Perform operation:
* var out = countTruthy( [ x ] );
* // returns 6
*/
function countTruthy( arrays ) {
var isCmplx;
var ndims;
var xmmv;
var shx;
var iox;
var len;
var sx;
var ox;
var ns;
var x;
var d;
var i;
// Unpack the ndarray and standardize ndarray meta data:
x = ndarray2object( arrays[ 0 ] );
shx = x.shape;
ndims = shx.length;
// 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_COUNT[ ndims ]( x );
}
if ( isCmplx ) {
return COMPLEX_COUNT[ ndims ]( x );
}
return COUNT[ ndims ]( x );
}
// 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 0;
}
// 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_COUNT[ ndims ]( x );
}
if ( isCmplx ) {
return COMPLEX_COUNT[ ndims ]( x );
}
return COUNT[ ndims ]( x );
}
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_COUNT[ 1 ]( x );
}
if ( isCmplx ) {
return COMPLEX_COUNT[ 1 ]( x );
}
return COUNT[ 1 ]( x );
}
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_COUNT[ 1 ]( x );
}
if ( isCmplx ) {
return COMPLEX_COUNT[ 1 ]( x );
}
return COUNT[ 1 ]( x );
}
// 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_COUNT[ ndims ]( x );
}
if ( isCmplx ) {
return COMPLEX_COUNT[ ndims ]( x );
}
return COUNT[ ndims ]( x );
}
// 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_COUNT[ ndims-2 ]( x );
}
if ( isCmplx ) {
return BLOCKED_COMPLEX_COUNT[ ndims-2 ]( x );
}
return BLOCKED_COUNT[ ndims-2 ]( x );
}
// 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 accessorcountnd( x );
}
if ( isCmplx ) {
return complexcountnd( x );
}
return countnd( x );
}
// EXPORTS //
module.exports = countTruthy;
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