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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.
*/
/* eslint-disable no-restricted-syntax, no-invalid-this */
'use strict';
// MODULES //
var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
var hasProp = require( '@stdlib/assert/has-property' );
var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
var isObject = require( '@stdlib/assert/is-object' );
var isFunction = require( '@stdlib/assert/is-function' );
var isCollection = require( '@stdlib/assert/is-collection' );
var isEmptyCollection = require( '@stdlib/assert/is-empty-collection' );
var isFunctionArray = require( '@stdlib/assert/is-function-array' );
var isDataType = require( '@stdlib/array/base/assert/is-data-type' );
var isOutputDataTypePolicy = require( '@stdlib/ndarray/base/assert/is-output-data-type-policy' );
var contains = require( '@stdlib/array/base/assert/contains' );
var unaryStrided1d = require( '@stdlib/ndarray/base/unary-strided1d' );
var unaryOutputDataType = require( '@stdlib/ndarray/base/unary-output-dtype' );
var resolveEnum = require( '@stdlib/ndarray/base/dtype-resolve-enum' );
var getShape = require( '@stdlib/ndarray/shape' ); // note: non-base accessor is intentional due to input ndarrays originating in userland
var ndims = require( '@stdlib/ndarray/ndims' );
var getDType = require( '@stdlib/ndarray/base/dtype' );
var getOrder = require( '@stdlib/ndarray/base/order' );
var empty = require( '@stdlib/ndarray/empty' );
var zeroTo = require( '@stdlib/array/base/zero-to' );
var join = require( '@stdlib/array/base/join' );
var copy = require( '@stdlib/array/base/copy' );
var everyBy = require( '@stdlib/array/base/every-by' );
var slice = require( '@stdlib/array/base/slice' );
var objectAssign = require( '@stdlib/object/assign' );
var format = require( '@stdlib/string/format' );
var defaults = require( './defaults.json' );
var validate = require( './validate.js' );
var indexOfTypes = require( './index_of_types.js' );
// FUNCTIONS //
/**
* Returns a list of data type enumeration constants.
*
* @private
* @param {Collection} types - list of types
* @returns {IntegerArray} list of data type enumeration constants
*/
function types2enums( types ) {
var out;
var i;
out = [];
for ( i = 0; i < types.length; i++ ) {
out.push( resolveEnum( types[ i ] ) ); // note: we're assuming that `types[i]` is a known data type; otherwise, the resolved enum will be `null`
}
return out;
}
/**
* Reorders a list of ndarrays such that the output ndarray is the specified index ndarray argument when passing along to a resolved lower-level strided function.
*
* @private
* @param {Array<ndarray>} arrays - list of input ndarrays
* @param {ndarray} output - output ndarray
* @param {NonNegativeInteger} index - specified index
* @returns {Array<ndarray>} reordered list
*/
function reorder( arrays, output, index ) {
var out;
var a1;
var a2;
out = [];
a1 = slice( arrays, 0, index );
a2 = slice( arrays, index, arrays.length - 1 );
out = a1.concat( [ output ], a2 );
return out;
}
// MAIN //
/**
* Constructor for applying a strided function to an input ndarray.
*
* @constructor
* @param {Object} table - dispatch table
* @param {Function} table.default - default strided function
* @param {StringArray} [table.types=[]] - one-dimensional list of ndarray data types describing specialized input and output ndarray argument signatures
* @param {ArrayLikeObject<Function>} [table.fcns=[]] - list of strided functions which are specific to specialized input and output ndarray argument signatures
* @param {ArrayLikeObject<StringArray>} idtypes - list containing lists of supported input data types for each ndarray argument
* @param {StringArray} odtypes - list of supported output data types
* @param {string} policy - output data type policy
* @throws {TypeError} first argument must be an object having valid properties
* @throws {TypeError} second argument must be an array containing arrays of supported data types
* @throws {TypeError} third argument must be an array of supported data types
* @throws {TypeError} fourth argument must be a supported output data type policy
* @throws {Error} first argument must be an object having valid properties
* @returns {UnaryStrided1dDispatch} instance
*
* @example
* var base = require( '@stdlib/stats/base/ndarray/cumax' );
* var dtypes = require( '@stdlib/ndarray/dtypes' );
* var ndarray2array = require( '@stdlib/ndarray/to-array' );
* var ndarray = require( '@stdlib/ndarray/base/ctor' );
*
* var idt = dtypes( 'real_and_generic' );
* var odt = idt;
* var policy = 'same';
*
* var table = {
* 'default': base
* };
* var cumax = new UnaryStrided1dDispatch( table, [ idt ], odt, policy );
*
* var xbuf = [ -1.0, 2.0, -3.0 ];
* var x = new ndarray( 'generic', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
*
* var y = cumax.apply( x );
* // returns <ndarray>
*
* var arr = ndarray2array( y );
* // returns [ -1.0, 2.0, 2.0 ]
*/
function UnaryStrided1dDispatch( table, idtypes, odtypes, policy ) {
var dt;
var i;
if ( !( this instanceof UnaryStrided1dDispatch ) ) {
return new UnaryStrided1dDispatch( table, idtypes, odtypes, policy );
}
if ( !isObject( table ) ) {
throw new TypeError( format( 'invalid argument. First argument must be an object. Value: `%s`.', table ) );
}
if ( !isFunction( table.default ) ) {
throw new TypeError( format( 'invalid argument. First argument must be an object having a "default" property and an associated method.' ) );
}
if ( hasProp( table, 'types' ) && !isCollection( table.types ) && !isEmptyCollection( table.types ) ) {
throw new TypeError( format( 'invalid argument. First argument must be an object having a "types" property whose associated value is an array-like object.' ) );
}
if ( hasProp( table, 'fcns' ) && !isFunctionArray( table.fcns ) && !isEmptyCollection( table.fcns ) ) {
throw new TypeError( format( 'invalid argument. First argument must be an object having a "fcns" property whose associated value is an array-like object containing functions.' ) );
}
if ( !isCollection( idtypes ) ) {
throw new TypeError( format( 'invalid argument. Second argument must be an array-like object. Value: `%s`.', idtypes ) );
}
for ( i = 0; i < idtypes.length; i++ ) {
dt = idtypes[ i ];
if (
!isCollection( dt ) ||
dt.length < 1 ||
!everyBy( dt, isDataType )
) {
throw new TypeError( format( 'invalid argument. Second argument must contain arrays of data types. Value: `%s`.', idtypes ) );
}
}
if (
!isCollection( odtypes ) ||
odtypes.length < 1 ||
!everyBy( odtypes, isDataType )
) {
throw new TypeError( format( 'invalid argument. Third argument must be an array of data types. Value: `%s`.', odtypes ) );
}
if ( !isOutputDataTypePolicy( policy ) ) {
throw new TypeError( format( 'invalid argument. Fourth argument must be a supported output data type policy. Value: `%s`.', policy ) );
}
this._table = {
'default': table.default,
'types': ( table.types ) ? types2enums( table.types ) : [], // note: convert to enums (i.e., integers) to ensure faster comparisons
'fcns': ( table.fcns ) ? copy( table.fcns ) : []
};
if ( this._table.types.length !== this._table.fcns.length*2 ) {
throw new Error( 'invalid argument. First argument specifies an unexpected number of types. A pair of input and output ndarray data types must be specified for each provided strided function.' );
}
this._idtypes = idtypes;
this._odtypes = odtypes;
this._policy = policy;
return this;
}
/**
* Applies a strided function to a provided input ndarray.
*
* @name apply
* @memberof UnaryStrided1dDispatch.prototype
* @type {Function}
* @param {ndarrayLike} x - input ndarray
* @param {...ndarrayLike} [args] - additional ndarray arguments
* @param {Options} [options] - function options
* @param {IntegerArray} [options.dims] - list of dimensions over which to perform an operation
* @param {string} [options.dtype] - output ndarray data type
* @throws {TypeError} first argument must be an ndarray-like object
* @throws {TypeError} options argument must be an object
* @throws {RangeError} dimension indices must not exceed input ndarray bounds
* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions
* @throws {Error} must provide valid options
* @returns {ndarray} output ndarray
*
* @example
* var base = require( '@stdlib/stats/base/ndarray/cumax' );
* var dtypes = require( '@stdlib/ndarray/dtypes' );
* var ndarray2array = require( '@stdlib/ndarray/to-array' );
* var ndarray = require( '@stdlib/ndarray/base/ctor' );
*
* var idt = dtypes( 'real_and_generic' );
* var odt = idt;
* var policy = 'same';
*
* var table = {
* 'default': base
* };
* var cumax = new UnaryStrided1dDispatch( table, [ idt ], odt, policy );
*
* var xbuf = [ -1.0, 2.0, -3.0 ];
* var x = new ndarray( 'generic', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
*
* var y = cumax.apply( x );
* // returns <ndarray>
*
* var arr = ndarray2array( y );
* // returns [ -1.0, 2.0, 2.0 ]
*/
setReadOnly( UnaryStrided1dDispatch.prototype, 'apply', function apply( x ) {
var options;
var dtypes;
var nargs;
var args;
var opts;
var err;
var shx;
var arr;
var idx;
var dt;
var f;
var N;
var y;
var i;
nargs = arguments.length;
if ( !isndarrayLike( x ) ) {
throw new TypeError( format( 'invalid argument. First argument must be an ndarray-like object. Value: `%s`.', x ) );
}
dt = getDType( x );
if ( !contains( this._idtypes[ 0 ], dt ) ) {
throw new TypeError( format( 'invalid argument. First argument must have one of the following data types: "%s". Data type: `%s`.', join( this._idtypes[ 0 ], '", "' ), dt ) );
}
args = [ x ];
for ( i = 1; i < nargs; i++ ) {
arr = arguments[ i ];
if ( !isndarrayLike( arr ) ) {
break;
}
dt = getDType( arr );
if ( !contains( this._idtypes[ i ], dt ) ) {
throw new TypeError( format( 'invalid argument. Argument %d must have one of the following data types: "%s". Data type: `%s`.', i, join( this._idtypes[ i ], '", "' ), dt ) );
}
args.push( arr );
}
// If we didn't make it up until the last argument, this means that we found a non-options argument which was not an ndarray...
if ( i < nargs-1 ) {
throw new TypeError( format( 'invalid argument. Argument %d must be an ndarray-like object. Value: `%s`.', i, arguments[ i ] ) );
}
shx = getShape( x );
N = shx.length;
opts = objectAssign( {}, defaults );
if ( nargs > i ) {
options = arguments[ nargs-1 ];
err = validate( opts, N, this._odtypes, options );
if ( err ) {
throw err;
}
}
// When a list of dimensions is not provided, apply the strided function across all dimensions...
if ( opts.dims === null ) {
opts.dims = zeroTo( N );
}
// Initialize an output array whose shape and memory layout matches the input array:
y = empty( shx, {
'dtype': opts.dtype || unaryOutputDataType( dt, this._policy ),
'order': getOrder( x )
});
// Resolve the lower-level strided function satisfying the input and output ndarray data types:
dtypes = [ resolveEnum( dt ), resolveEnum( getDType( y ) ) ];
idx = indexOfTypes( this._table.fcns.length, 2, this._table.types, 2, 1, 0, dtypes, 1, 0 ); // eslint-disable-line max-len
if ( idx >= 0 ) {
f = this._table.fcns[ idx ];
} else {
f = this._table.default;
}
// Perform operation:
unaryStrided1d( f, reorder( args, y ), opts.dims );
return y;
});
/**
* Applies a strided function to a provided input ndarray and assigns results to a provided output ndarray.
*
* @name assign
* @memberof UnaryStrided1dDispatch.prototype
* @type {Function}
* @param {ndarrayLike} x - input ndarray
* @param {...ndarrayLike} [args] - additional ndarray arguments
* @param {ndarrayLike} out - output ndarray
* @param {Options} [options] - function options
* @param {IntegerArray} [options.dims] - list of dimensions over which to perform an operation
* @throws {TypeError} first argument must be an ndarray
* @throws {TypeError} first argument must have a supported data type
* @throws {TypeError} output argument must be an ndarray
* @throws {TypeError} options argument must be an object
* @throws {RangeError} dimension indices must not exceed input ndarray bounds
* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions
* @throws {Error} must provide valid options
* @returns {ndarrayLike} output ndarray
*
* @example
* var base = require( '@stdlib/stats/base/ndarray/cumax' );
* var dtypes = require( '@stdlib/ndarray/dtypes' );
* var ndarray2array = require( '@stdlib/ndarray/to-array' );
* var ndarray = require( '@stdlib/ndarray/base/ctor' );
*
* var idt = dtypes( 'real_and_generic' );
* var odt = idt;
* var policy = 'same';
*
* var table = {
* 'default': base
* };
* var cumax = new UnaryStrided1dDispatch( table, [ idt ], odt, policy );
*
* var xbuf = [ -1.0, 2.0, -3.0 ];
* var x = new ndarray( 'generic', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
*
* var ybuf = [ 0.0, 0.0, 0.0 ];
* var y = new ndarray( 'generic', ybuf, [ ybuf.length ], [ 1 ], 0, 'row-major' );
*
* var out = cumax.assign( x, y );
* // returns <ndarray>
*
* var arr = ndarray2array( y );
* // returns [ -1.0, 2.0, 2.0 ]
*
* var bool = ( out === y );
* // returns true
*/
setReadOnly( UnaryStrided1dDispatch.prototype, 'assign', function assign( x ) {
var options;
var dtypes;
var nargs;
var opts;
var args;
var arr;
var err;
var flg;
var idx;
var dt;
var N;
var f;
var y;
var i;
nargs = arguments.length;
if ( !isndarrayLike( x ) ) {
throw new TypeError( format( 'invalid argument. First argument must be an ndarray-like object. Value: `%s`.', x ) );
}
// Validate the input ndarray data type in order to maintain similar behavior to `apply` above...
dt = getDType( x );
if ( !contains( this._idtypes[ 0 ], dt ) ) {
throw new TypeError( format( 'invalid argument. First argument must have one of the following data types: "%s". Data type: `%s`.', join( this._idtypes[ 0 ], '", "' ), dt ) );
}
args = [ x ];
// Resolve additional ndarray arguments...
for ( i = 1; i < nargs; i++ ) {
arr = arguments[ i ];
if ( !isndarrayLike( arr ) ) {
break;
}
args.push( arr );
}
// Ensure that we were provided an output ndarray...
if ( i < 2 ) {
throw new TypeError( format( 'invalid argument. Second argument must be an ndarray-like object. Value: `%s`.', arguments[ 1 ] ) );
}
// If we processed all but the last argument, assume that the last argument is an options argument...
else if ( i === nargs-1 ) {
options = arguments[ i ];
flg = true;
}
// Otherwise, if we have more than one argument remaining, then at least one argument is not an ndarray but should be...
else if ( i < nargs-1 ) {
throw new TypeError( format( 'invalid argument. Argument %d must be an ndarray-like object. Value: `%s`.', i, arguments[ i ] ) );
}
// Cache a reference to the output ndarray:
y = args.pop();
// Verify that additional ndarray arguments have expected dtypes (note: we intentionally don't validate the output ndarray dtype in order to provide an escape hatch for a user wanting to have an output ndarray having a specific dtype that `apply` does not support)...
for ( i = 1; i < args.length; i++ ) {
dt = getDType( args[ i ] );
if ( !contains( this._idtypes[ i ], dt ) ) {
throw new TypeError( format( 'invalid argument. Argument %d must have one of the following data types: "%s". Data type: `%s`.', i, join( this._idtypes[ i ], '", "' ), dt ) );
}
}
// Validate any provided options...
N = ndims( x );
opts = objectAssign( {}, defaults );
if ( flg ) {
err = validate( opts, N, this._odtypes, options );
if ( err ) {
throw err;
}
}
// When a list of dimensions is not provided, apply the strided function across all dimensions...
if ( opts.dims === null ) {
opts.dims = zeroTo( N );
}
// Resolve the lower-level strided function satisfying the input and output ndarray data types:
dtypes = [ resolveEnum( dt ), resolveEnum( getDType( y ) ) ];
idx = indexOfTypes( this._table.fcns.length, 2, this._table.types, 2, 1, 0, dtypes, 1, 0 ); // eslint-disable-line max-len
if ( idx >= 0 ) {
f = this._table.fcns[ idx ];
} else {
f = this._table.default;
}
// Perform operation:
unaryStrided1d( f, reorder( args, y ), opts.dims ); // note: we assume that this lower-level function handles further validation of the output ndarray (e.g., expected shape, etc)
return y;
});
// EXPORTS //
module.exports = UnaryStrided1dDispatch;
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