{{alias}}( fcn, arrays, dims[, options] ) Applies a one-dimensional strided array function to a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. 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). Any additional ndarray arguments are expected to have the same leading dimensions as the loop dimensions of the input ndarray. When calling the strided array function, any additional ndarray arguments are provided as k-dimensional subarrays, where `k = M - N` with `M` being the number of dimensions in an ndarray argument and `N` being the number of loop dimensions for the input ndarray. For example, if an input ndarray has three dimensions, the number of loop dimensions is one, and an additional ndarray argument has one dimension, thus matching the number of loop dimensions for the input ndarray, the strided array function is provided a zero-dimensional subarray as an additional ndarray argument. In the same scenario but where an additional ndarray argument has two dimensions, thus exceeding the number of loop dimensions, the strided array function is provided a one-dimensional subarray as an additional ndarray argument. Parameters ---------- fcn: Function Function which will be applied to a one-dimensional input subarray and should update a one-dimensional output subarray with results. The function should have the following signature: fcn( arrays[, options] ) where - arrays: array containing a one-dimensional subarray of the input ndarray, a one-dimensional subarray of the output ndarray, and any additional ndarray arguments as subarrays. - options: function options. arrays: ArrayLikeObject Array-like object containing one input ndarray and one output ndarray, followed by any additional ndarray arguments. dims: Array List of dimensions to which to apply a strided array function. options: Object (optional) Function options. Examples -------- // Define ndarray data and meta data... > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); > var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0, 0.0 ] ); > var dtype = 'float64'; > var shx = [ 2, 2 ]; > var shy = [ 2, 2 ]; > var sx = [ 2, 1 ]; > var sy = [ 2, 1 ]; > var ox = 0; > var oy = 0; > var order = 'row-major'; // Define a wrapper for an extended BLAS function... > var f = {{alias:@stdlib/blas/ext/base/gcusum}}.ndarray; > function fcn( arrays ) { ... var x = arrays[ 0 ]; ... var y = arrays[ 1 ]; ... var s = arrays[ 2 ]; ... var N = x.shape[ 0 ]; ... var dx = x.data; ... var dy = y.data; ... var sx = x.strides[ 0 ]; ... var sy = y.strides[ 0 ]; ... var ox = x.offset; ... var oy = y.offset; ... var init = s.data[ s.offset ]; ... return f( N, init, dx, sx, ox, dy, sy, oy ); ... }; // Using minimal ndarray-like objects... > var x = { ... 'dtype': dtype, ... 'data': xbuf, ... 'shape': shx, ... 'strides': sx, ... 'offset': ox, ... 'order': order ... }; > var initial = { ... 'dtype': dtype, ... 'data': new {{alias:@stdlib/array/float64}}( [ 0.0 ] ), ... 'shape': [], ... 'strides': [ 0 ], ... 'offset': 0, ... 'order': order ... }; > var y = { ... 'dtype': dtype, ... 'data': ybuf, ... 'shape': shy, ... 'strides': sy, ... 'offset': oy, ... 'order': order ... }; > {{alias}}( fcn, [ x, y, initial ], [ 0, 1 ] ); > y.data [ 1.0, 3.0, 6.0, 10.0 ] See Also --------