Multidimensional arrays.
var ns = require( '@stdlib/ndarray' );ndarray namespace.
var o = ns;
// returns {...}The namespace exports the following functions to create multidimensional arrays:
array( [buffer,] [options] ): create a multidimensional array.ndarray( dtype, buffer, shape, strides, offset, order[, options] ): multidimensional array constructor.
The namespace contains the following sub-namespaces:
base: base ndarray.
In addition, the namespace contains the following multidimensional array utility functions:
ndarrayCastingModes(): list of ndarray casting modes.defaults(): default ndarray settings.dispatch( fcns, types, data, nargs, nin, nout ): create an ndarray function interface which performs multiple dispatch.ndarrayDataTypes( [kind] ): list of ndarray data types.ndemptyLike( x[, options] ): create an uninitialized ndarray having the same shape and data type as a provided ndarray.ndempty( shape[, options] ): create an uninitialized ndarray having a specified shape and data type.scalar2ndarray( value[, options] ): convert a scalar value to a zero-dimensional ndarray.ind2sub( shape, idx[, options] ): convert a linear index to an array of subscripts.ndarrayIndexModes(): list of ndarray index modes.ndarrayMinDataType( value ): determine the minimum ndarray data type of the closest "kind" necessary for storing a provided scalar value.ndarrayNextDataType( [dtype] ): return the next larger ndarray data type of the same kind.ndarrayOrders(): list of ndarray orders.ndarrayOutputDataTypePolicies(): list of output ndarray data type policies.ndarrayPromotionRules( [dtype1, dtype2] ): return the ndarray data type with the smallest size and closest "kind" to which ndarray data types can be safely cast.ndarraySafeCasts( [dtype] ): return a list of ndarray data types to which a provided ndarray data type can be safely cast.ndarraySameKindCasts( [dtype] ): return a list of ndarray data types to which a provided ndarray data type can be safely cast or cast within the same "kind".sub2ind( shape, ...subscripts[, options] ): convert subscripts to a linear index.ndarray2array( arr ): convert an ndarray to a generic array.ndzerosLike( x[, options] ): create a zero-filled ndarray having the same shape and data type as a provided ndarray.ndzeros( shape[, options] ): create a zero-filled ndarray having a specified shape and data type.
var objectKeys = require( '@stdlib/utils/keys' );
var ns = require( '@stdlib/ndarray' );
console.log( objectKeys( ns ) );