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* @license Apache-2.0
*
* Copyright (c) 2026 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 isComplexDataType = require( '@stdlib/ndarray/base/assert/is-complex-floating-point-data-type' );
var isRealDataType = require( '@stdlib/ndarray/base/assert/is-real-data-type' );
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 strides2order = require( '@stdlib/ndarray/base/strides2order' );
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 blockedaccessorassign2d = require( './2d_blocked_accessors.js' );
var blockedaccessorassign3d = require( './3d_blocked_accessors.js' );
var blockedaccessorassign4d = require( './4d_blocked_accessors.js' );
var blockedaccessorassign5d = require( './5d_blocked_accessors.js' );
var blockedaccessorassign6d = require( './6d_blocked_accessors.js' );
var blockedaccessorassign7d = require( './7d_blocked_accessors.js' );
var blockedaccessorassign8d = require( './8d_blocked_accessors.js' );
var blockedaccessorassign9d = require( './9d_blocked_accessors.js' );
var blockedaccessorassign10d = require( './10d_blocked_accessors.js' );
var blockedcomplexassign2d = require( './2d_blocked_complex.js' );
var blockedcomplexassign3d = require( './3d_blocked_complex.js' );
var blockedcomplexassign4d = require( './4d_blocked_complex.js' );
var blockedcomplexassign5d = require( './5d_blocked_complex.js' );
var blockedcomplexassign6d = require( './6d_blocked_complex.js' );
var blockedcomplexassign7d = require( './7d_blocked_complex.js' );
var blockedcomplexassign8d = require( './8d_blocked_complex.js' );
var blockedcomplexassign9d = require( './9d_blocked_complex.js' );
var blockedcomplexassign10d = require( './10d_blocked_complex.js' );
var blockedassign2d = require( './2d_blocked.js' );
var blockedassign3d = require( './3d_blocked.js' );
var blockedassign4d = require( './4d_blocked.js' );
var blockedassign5d = require( './5d_blocked.js' );
var blockedassign6d = require( './6d_blocked.js' );
var blockedassign7d = require( './7d_blocked.js' );
var blockedassign8d = require( './8d_blocked.js' );
var blockedassign9d = require( './9d_blocked.js' );
var blockedassign10d = require( './10d_blocked.js' );
var accessorassign0d = require( './0d_accessors.js' );
var accessorassign1d = require( './1d_accessors.js' );
var accessorassign2d = require( './2d_accessors.js' );
var accessorassign3d = require( './3d_accessors.js' );
var accessorassign4d = require( './4d_accessors.js' );
var accessorassign5d = require( './5d_accessors.js' );
var accessorassign6d = require( './6d_accessors.js' );
var accessorassign7d = require( './7d_accessors.js' );
var accessorassign8d = require( './8d_accessors.js' );
var accessorassign9d = require( './9d_accessors.js' );
var accessorassign10d = require( './10d_accessors.js' );
var accessorassignnd = require( './nd_accessors.js' );
var complexassign0d = require( './0d_complex.js' );
var complexassign1d = require( './1d_complex.js' );
var complexassign2d = require( './2d_complex.js' );
var complexassign3d = require( './3d_complex.js' );
var complexassign4d = require( './4d_complex.js' );
var complexassign5d = require( './5d_complex.js' );
var complexassign6d = require( './6d_complex.js' );
var complexassign7d = require( './7d_complex.js' );
var complexassign8d = require( './8d_complex.js' );
var complexassign9d = require( './9d_complex.js' );
var complexassign10d = require( './10d_complex.js' );
var complexassignnd = require( './nd_complex.js' );
var assign0d = require( './0d.js' );
var assign1d = require( './1d.js' );
var assign2d = require( './2d.js' );
var assign3d = require( './3d.js' );
var assign4d = require( './4d.js' );
var assign5d = require( './5d.js' );
var assign6d = require( './6d.js' );
var assign7d = require( './7d.js' );
var assign8d = require( './8d.js' );
var assign9d = require( './9d.js' );
var assign10d = require( './10d.js' );
var assignnd = require( './nd.js' );
// VARIABLES //
var ASSIGN = [
assign0d,
assign1d,
assign2d,
assign3d,
assign4d,
assign5d,
assign6d,
assign7d,
assign8d,
assign9d,
assign10d
];
var ACCESSOR_ASSIGN = [
accessorassign0d,
accessorassign1d,
accessorassign2d,
accessorassign3d,
accessorassign4d,
accessorassign5d,
accessorassign6d,
accessorassign7d,
accessorassign8d,
accessorassign9d,
accessorassign10d
];
var COMPLEX_ASSIGN = [
complexassign0d,
complexassign1d,
complexassign2d,
complexassign3d,
complexassign4d,
complexassign5d,
complexassign6d,
complexassign7d,
complexassign8d,
complexassign9d,
complexassign10d
];
var BLOCKED_ASSIGN = [
blockedassign2d, // 0
blockedassign3d,
blockedassign4d,
blockedassign5d,
blockedassign6d,
blockedassign7d,
blockedassign8d,
blockedassign9d,
blockedassign10d // 8
];
var BLOCKED_ACCESSOR_ASSIGN = [
blockedaccessorassign2d, // 0
blockedaccessorassign3d,
blockedaccessorassign4d,
blockedaccessorassign5d,
blockedaccessorassign6d,
blockedaccessorassign7d,
blockedaccessorassign8d,
blockedaccessorassign9d,
blockedaccessorassign10d // 8
];
var BLOCKED_COMPLEX_ASSIGN = [
blockedcomplexassign2d, // 0
blockedcomplexassign3d,
blockedcomplexassign4d,
blockedcomplexassign5d,
blockedcomplexassign6d,
blockedcomplexassign7d,
blockedcomplexassign8d,
blockedcomplexassign9d,
blockedcomplexassign10d // 8
];
var MAX_DIMS = ASSIGN.length - 1;
// TODO: consider adding a package utility for mapping a complex dtype to its complementary real-valued counterpart
var COMPLEX_TO_REAL = { // WARNING: this table needs to be manually updated if we add support for additional complex number dtypes
'complex128': 'float64',
'complex64': 'float32',
'complex32': 'float16'
};
// FUNCTIONS //
/**
* Converts a boolean ndarray to an 8-bit unsigned integer ndarray.
*
* ## Notes
*
* - The function mutates the input ndarray object.
*
* @private
* @param {Object} x - input ndarray object
* @returns {Object} output ndarray object
*/
function boolean2uint8( x ) {
x.data = reinterpretBoolean( x.data, 0 );
x.accessorProtocol = false;
return x;
}
/**
* Converts a complex-valued floating-point ndarray to a real-valued floating-point ndarray.
*
* ## Notes
*
* - The function mutates the input ndarray object.
*
* @private
* @param {Object} x - input ndarray object
* @returns {Object} output ndarray object
*/
function complex2real( x ) {
var ndims = x.shape.length;
x.data = reinterpretComplex( x.data, 0 );
x.accessorProtocol = false;
x.dtype = COMPLEX_TO_REAL[ String( x.dtype ) ];
x.strides = gscal( ndims, 2, x.strides, 1 );
x.offset *= 2;
return x;
}
// MAIN //
/**
* Assigns a scalar value to every element of an output ndarray.
*
* ## Notes
*
* - Each 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 a zero-dimensional ndarray containing the scalar value and one output ndarray
* @returns {void}
*
* @example
* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
* var Float64Array = require( '@stdlib/array/float64' );
*
* // Create a zero-dimensional ndarray containing the scalar value:
* var x = scalar2ndarray( 5.0, {
* 'dtype': 'float64'
* });
*
* // Create a data buffer:
* var ybuf = new Float64Array( 12 );
*
* // Define the shape of the output array:
* var shape = [ 3, 1, 2 ];
*
* // Define the array strides:
* var sy = [ 4, 4, 1 ];
*
* // Define the index offset:
* var oy = 1;
*
* // Create the output ndarray-like object:
* var y = {
* 'dtype': 'float64',
* 'data': ybuf,
* 'shape': shape,
* 'strides': sy,
* 'offset': oy,
* 'order': 'row-major'
* };
*
* // Assign the scalar value:
* assignScalar( [ x, y ] );
*
* console.log( y.data );
* // => <Float64Array>[ 0.0, 5.0, 5.0, 0.0, 0.0, 5.0, 5.0, 0.0, 0.0, 5.0, 5.0, 0.0 ]
*/
function assignScalar( arrays ) {
var isCmplx;
var ndims;
var ymmv;
var shy;
var ioy;
var len;
var ord;
var sy;
var oy;
var ns;
var re;
var im;
var x;
var y;
var d;
var i;
// Unpack the ndarrays and standardize ndarray meta data:
x = ndarray2object( arrays[ 0 ] );
y = ndarray2object( arrays[ 1 ] );
// Check for known array types which can be reinterpreted for better iteration performance...
if ( isBooleanArray( x.data ) && isBooleanArray( y.data ) ) {
x = boolean2uint8( x );
y = boolean2uint8( y );
} else if ( isComplexArray( x.data ) && isComplexArray( y.data ) ) {
x = complex2real( x );
y = complex2real( y );
re = x.data[ x.offset ];
im = x.data[ x.offset+1 ];
isCmplx = true;
}
// Determine whether we are casting a real data type to a complex data type and we need to use a specialized accessor (note: we don't support the other way, complex-to-real, as this is not an allowed (mostly) safe cast; note: we cannot create a specialized view for assigning only real components, as the imaginary component for each element in `y` also needs to be set to zero and while we could perform two passes, it's not clear it's worth the effort)...
else if ( isRealDataType( x.dtype ) && isComplexDataType( y.dtype ) ) {
y = complex2real( y );
re = x.data[ x.offset ];
im = 0.0;
isCmplx = true;
}
shy = y.shape;
ndims = shy.length;
// Determine whether we can avoid iteration altogether...
if ( ndims === 0 ) {
if ( x.accessorProtocol || y.accessorProtocol ) {
return ACCESSOR_ASSIGN[ ndims ]( x, y );
}
if ( isCmplx ) {
return COMPLEX_ASSIGN[ ndims ]( re, im, y );
}
return ASSIGN[ ndims ]( x, y );
}
// 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 = shy[ 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;
}
// Determine whether the ndarray is one-dimensional and thus readily translates to a one-dimensional strided array...
if ( ndims === 1 ) {
if ( x.accessorProtocol || y.accessorProtocol ) {
return ACCESSOR_ASSIGN[ ndims ]( x, y );
}
if ( isCmplx ) {
return COMPLEX_ASSIGN[ ndims ]( re, im, y );
}
return ASSIGN[ ndims ]( x, y );
}
sy = y.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 the 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 ( shy[ i ] !== 1 ) {
break;
}
}
y.shape = [ shy[i] ];
y.strides = [ sy[i] ];
if ( x.accessorProtocol || y.accessorProtocol ) {
return ACCESSOR_ASSIGN[ 1 ]( x, y );
}
if ( isCmplx ) {
return COMPLEX_ASSIGN[ 1 ]( re, im, y );
}
return ASSIGN[ 1 ]( x, y );
}
ioy = iterationOrder( sy ); // +/-1
// Determine whether we can avoid blocked iteration...
if ( ioy !== 0 ) {
// Determine the minimum and maximum linear indices which are accessible by the array view:
ymmv = minmaxViewBufferIndex( shy, sy, y.offset );
// Determine whether we can ignore shape (and strides) and treat the ndarray as a linear one-dimensional strided array...
if ( len === ( ymmv[1]-ymmv[0]+1 ) ) {
// Note: the above is equivalent to @stdlib/ndarray/base/assert/is-contiguous, but in-lined so we can retain computed values...
if ( ioy === 1 ) {
oy = ymmv[ 0 ];
} else {
oy = ymmv[ 1 ];
}
y.shape = [ len ];
y.strides = [ ioy ];
y.offset = oy;
if ( x.accessorProtocol || y.accessorProtocol ) {
return ACCESSOR_ASSIGN[ 1 ]( x, y );
}
if ( isCmplx ) {
return COMPLEX_ASSIGN[ 1 ]( re, im, y );
}
return ASSIGN[ 1 ]( x, y );
}
// 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 ) {
ord = strides2order( sy );
// 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 || y.accessorProtocol ) {
return ACCESSOR_ASSIGN[ ndims ]( x, y, ord === 1 );
}
if ( isCmplx ) {
return COMPLEX_ASSIGN[ ndims ]( re, im, y, ord === 1 );
}
return ASSIGN[ ndims ]( x, y, ord === 1 );
}
// 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 || y.accessorProtocol ) {
return BLOCKED_ACCESSOR_ASSIGN[ ndims-2 ]( x, y );
}
if ( isCmplx ) {
return BLOCKED_COMPLEX_ASSIGN[ ndims-2 ]( re, im, y );
}
return BLOCKED_ASSIGN[ ndims-2 ]( x, y );
}
// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...
if ( x.accessorProtocol || y.accessorProtocol ) {
return accessorassignnd( x, y );
}
if ( isCmplx ) {
return complexassignnd( re, im, y );
}
assignnd( x, y );
}
// EXPORTS //
module.exports = assignScalar;
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