Auto-generated commit

CHANGELOG.md

@@ -10,6 +10,7 @@
 
 ### Features
 
+-   [`2c01b65`](https://github.com/stdlib-js/stdlib/commit/2c01b654e7fcfae9bde232c5fdda10d14f02e30e) - add `ndfilterMap` to namespace
 -   [`9ecc3d3`](https://github.com/stdlib-js/stdlib/commit/9ecc3d30b87a0d38cc7608a35024a15c920a2f29) - add `ndreject` to namespace
 -   [`b916456`](https://github.com/stdlib-js/stdlib/commit/b916456714e3c8a4ecaf6605adf4d36188e924f9) - add `ndmap` and `ndfilter` to namespace
 -   [`254fa9e`](https://github.com/stdlib-js/stdlib/commit/254fa9ec906b3a6c62551e13bd0aeef1c1f29af8) - add `Float64ArrayLE`, `Float32ArrayLE`, `Float64ArrayFE`, and `Float32ArrayFE` to namespace
@@ -35,6 +36,7 @@
 
 <details>
 
+-   [`2c01b65`](https://github.com/stdlib-js/stdlib/commit/2c01b654e7fcfae9bde232c5fdda10d14f02e30e) - **feat:** add `ndfilterMap` to namespace _(by Athan Reines)_
 -   [`9ecc3d3`](https://github.com/stdlib-js/stdlib/commit/9ecc3d30b87a0d38cc7608a35024a15c920a2f29) - **feat:** add `ndreject` to namespace _(by Athan Reines)_
 -   [`b916456`](https://github.com/stdlib-js/stdlib/commit/b916456714e3c8a4ecaf6605adf4d36188e924f9) - **feat:** add `ndmap` and `ndfilter` to namespace _(by Athan Reines)_
 -   [`05e89d4`](https://github.com/stdlib-js/stdlib/commit/05e89d4f958c0363eddb9e18e1610289e8d64377) - **docs:** update REPL namespace documentation [(#3901)](https://github.com/stdlib-js/stdlib/pull/3901) _(by stdlib-bot, Philipp Burckhardt)_

data/data.csv

@@ -4124,7 +4124,8 @@ ndarrayStrides,"\nndarrayStrides( x )\n    Returns the strides of a provided nda
 ndat,"\nndat( x[, ...indices] )\n    Returns an ndarray element.\n\n    Negative indices are resolved relative to the last element along the\n    respective dimension, with the last element corresponding to `-1`.\n\n    If provided out-of-bounds indices, the function always returns `undefined`.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    indices: ...integer (optional)\n        Index arguments. The number of index arguments must equal the number of\n        dimensions.\n\n    Returns\n    -------\n    out: any\n        Element value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > ndat( x, 0, 1 )\n    2\n    > ndat( x, 1, 0 )\n    3\n\n    See Also\n    --------\n    array, ndslice\n"
 ndempty,"\nndempty( shape[, options] )\n    Returns an uninitialized ndarray having a specified shape and data type.\n\n    In browser environments, the function always returns zero-filled ndarrays.\n\n    If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n    For returned ndarrays whose underlying memory is *not* initialized, memory\n    contents are unknown and may contain *sensitive* data.\n\n    Parameters\n    ----------\n    shape: ArrayLikeObject<integer>|integer\n        Array shape.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Underlying data type. Default: 'float64'.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var arr = ndempty( [ 2, 2 ] )\n    <ndarray>\n    > var sh = arr.shape\n    [ 2, 2 ]\n    > var dt = arr.dtype\n    'float64'\n\n    See Also\n    --------\n    ndemptyLike, ndzeros\n"
 ndemptyLike,"\nndemptyLike( x[, options] )\n    Returns an uninitialized ndarray having the same shape and data type as a\n    provided input ndarray.\n\n    The function infers the following attributes from the input array:\n\n    - shape: array shape.\n    - dtype: underlying array data type.\n    - order: whether the array order is row-major (C-style) or column-major\n      (Fortran-style).\n\n    In browser environments, the function always returns zero-filled ndarrays.\n\n    If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n    For returned ndarrays whose underlying memory is *not* initialized, memory\n    contents are unknown and may contain *sensitive* data.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.shape: ArrayLikeObject<integer>|integer (optional)\n        Array shape. Overrides the input array's inferred shape.\n\n    options.dtype: string (optional)\n        Array data type. Overrides the input array's inferred data type.\n\n    options.order: string (optional)\n        Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n        style)). Overrides the input array's inferred order.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var dt = x.dtype\n    'float64'\n    > var y = ndemptyLike( x )\n    <ndarray>\n    > sh = y.shape\n    [ 2, 2 ]\n    > dt = y.dtype\n    'float64'\n\n    See Also\n    --------\n    ndempty, ndzerosLike\n"
-ndfilter,"\nndfilter( x[, options], predicate[, thisArg] )\n    Returns a shallow copy of an ndarray containing only those elements which\n    pass a test implemented by a predicate function.\n\n    The predicate function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Output ndarray data type. Overrides using the input array's inferred\n        data type.\n\n    options.order: string (optional)\n        Index iteration order. By default, the function iterates over elements\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manor, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Predicate function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { return v > 2.0; };\n    > var y = ndfilter( x, f );\n    > ndarray2array( y )\n    [ 3.0, 4.0 ]\n\n    See Also\n    --------\n    ndmap, ndslice"
+ndfilter,"\nndfilter( x[, options], predicate[, thisArg] )\n    Returns a shallow copy of an ndarray containing only those elements which\n    pass a test implemented by a predicate function.\n\n    The predicate function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Output ndarray data type. Overrides using the input array's inferred\n        data type.\n\n    options.order: string (optional)\n        Index iteration order. By default, the function iterates over elements\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manor, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Predicate function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { return v > 2.0; };\n    > var y = ndfilter( x, f );\n    > ndarray2array( y )\n    [ 3.0, 4.0 ]\n\n    See Also\n    --------\n    ndmap, ndreject, ndslice"
+ndfilterMap,"\nndfilterMap( x[, options], fcn[, thisArg] )\n    Filters and maps elements in an input ndarray to elements in a new output\n    ndarray according to a callback function.\n\n    The callback function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    If a provided callback function returns `undefined`, the function skips the\n    respective ndarray element. If the callback function returns a value other\n    than `undefined`, the function stores the callback's return value in the\n    output ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Output ndarray data type. Overrides using the input array's inferred\n        data type.\n\n    options.order: string (optional)\n        Index iteration order. By default, the function iterates over elements\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manor, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    fcn: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { return v > 2.0; };\n    > var y = ndfilterMap( x, f );\n    > ndarray2array( y )\n    [ 3.0, 4.0 ]\n\n    See Also\n    --------\n    ndfilter, ndmap, ndreject, ndslice"
 ndims,"\nndims( x )\n    Returns the number of ndarray dimensions.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    n: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n    3\n\n    See Also\n    --------\n    array, ndarray, numel, ndarrayShape\n"
 nditerColumnEntries,"\nnditerColumnEntries( x[, options] )\n    Returns an iterator which returns [index, column] pairs for each column in a\n    matrix (or stack of matrices).\n\n    Each returned index is a Cartesian index (i.e., an array of subscripts/\n    dimension indices). A dimension index equal to `null` indicates that all\n    values along the respective dimension are included in the returned ndarray.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerColumnEntries( x );\n    > var v = it.next().value;\n    > v[ 0 ]\n    [ null, 0 ]\n    > ndarray2array( v[ 1 ] )\n    [ 1, 3 ]\n    > v = it.next().value;\n    > v[ 0 ]\n    [ null, 1 ]\n    > ndarray2array( v[ 1 ] )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    nditerColumns, nditerEntries, nditerRowEntries, ndslice\n"
 nditerColumns,"\nnditerColumns( x[, options] )\n    Returns an iterator which iterates over each column in a matrix (or stack of\n    matrices).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerColumns( x );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ 1, 3 ]\n    > v = it.next().value;\n    > ndarray2array( v )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    nditerColumnEntries, nditerRows, ndslice\n"