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.copy( x[, options] ): copy an input ndarray to a new ndarray having the same shape and data type.ndarray( dtype, buffer, shape, strides, offset, order[, options] ): multidimensional array constructor.emptyLike( x[, options] ): create an uninitialized ndarray having the same shape and data type as a provided ndarray.empty( shape[, options] ): create an uninitialized ndarray having a specified shape and data type.scalar2ndarrayLike( x, value[, options] ): convert a scalar value to a zero-dimensional ndarray having the same data-type as a provided ndarray.scalar2ndarray( value[, options] ): convert a scalar value to a zero-dimensional ndarray.ndarraylike2ndarray( x[, options] ): convert an ndarray-like object to anndarray.ones( shape[, options] ): create a ones-filled ndarray having a specified shape and data type.ndarray2fancy( x[, options] ): convert an ndarray to an object supporting fancy indexing.zerosLike( x[, options] ): create a zero-filled ndarray having the same shape and data type as a provided ndarray.zeros( shape[, options] ): create a zero-filled ndarray having a specified shape and data type.
The namespace exports the following functions to manipulate multidimensional arrays:
broadcastArray( x, shape ): broadcast an ndarray to a specified shape.broadcastArrays( ...arrays ): broadcast ndarrays to a common shape.broadcastScalar( value, shape[, options] ): broadcast a scalar value to an ndarray of a specified shape.colcat( arrays ): concatenate a list of one-dimensional or two-dimensional ndarrays as columns.concat( arrays[, options] ): concatenate a list of ndarrays along a specified ndarray dimension.concat1d( ...arrays ): return a one-dimensional ndarray formed by concatenating provided input arguments.fillBy( x, fcn[, thisArg] ): fill an input ndarray according to a callback function.fillSlice( x, value, ...s[, options] ): fill an inputndarrayview with a specified value.fill( x, value ): fill an inputndarraywith a specified value.flattenBy( x[, options], fcn[, thisArg] ): flatten an ndarray according to a callback function.flattenFromBy( x, dim[, options], fcn[, thisArg] ): flatten an ndarray according to a callback function starting from a specified dimension.flattenFrom( x, dim[, options] ): return a copy of an input ndarray where all dimensions of the input ndarray are flattened starting from a specified dimension.flatten( x[, options] ): return a flattened copy of an input ndarray.fliplr( x ): return a read-only view of an inputndarrayin which the order of elements along the last dimension is reversed.flipud( x ): return a read-only view of an inputndarrayin which the order of elements along the second-to-last dimension is reversed.hconcat( arrays ): concatenate a list of ndarrays along the last dimension.map( x[, options], fcn[, thisArg] ): apply a callback function to elements in an input ndarray and assign results to elements in a new output ndarray.maybeBroadcastArray( x, shape ): broadcast an ndarray to a specified shape if and only if the specified shape differs from the provided ndarray's shape.maybeBroadcastArrays( arrays ): broadcast ndarrays to a common shape.pop( x[, options] ): return an array containing a read-only truncated view of an inputndarrayand a read-only view of the last element(s) along a specified dimension.prependSingletonDimensions( x, n ): return a read-only view of an input ndarray with a specified number of prepended singleton dimensions.push( x, ...values ): return a one-dimensional ndarray formed by appending provided scalar values to a one-dimensional input ndarray.removeSingletonDimensions( x ): return a read-only view of an input ndarray with singleton dimensions removed.reverseDimension( x, dim ): return a read-only view of an inputndarrayin which the order of elements along a specified dimension is reversed.reverse( x ): return a read-only view of an inputndarrayin which the order of elements along each dimension is reversed.rotr90( x, k ): return a read-only view of a matrix (or a stack of matrices) rotated90degrees clockwise.rowcat( arrays ): concatenate a list of one-dimensional or two-dimensional ndarrays as rows.shift( x[, options] ): return an array containing a read-only truncated view of an inputndarrayand a read-only view of the first element(s) along a specified dimension.sliceAssign( x, y, ...s[, options] ): assign element values from a broadcasted inputndarrayto corresponding elements in an outputndarrayview.sliceDimensionFrom( x, dim, start[, options] ): return a read-only shifted view of an inputndarrayalong a specified dimension.sliceDimensionTo( x, dim, stop[, options] ): return a read-only truncated view of an inputndarrayalong a specified dimension.sliceDimension( x, dim, slice[, options] ): return a read-only view of an inputndarraywhen sliced along a specified dimension.sliceFrom( x, ...start[, options] ): return a read-only shifted view of an input ndarray.sliceTo( x, ...stop[, options] ): return a read-only truncated view of an input ndarray.slice( x, ...s[, options] ): return a read-only view of an inputndarray.spreadDimensions( ndims, x, dims ): return a read-only view of an input ndarray where the dimensions of the input ndarray are expanded to a specified dimensionality by spreading dimensions to specified dimension indices and inserting dimensions of size one for the remaining dimensions.toFlippedlr( x ): return a newndarraywhere the order of elements along the last dimension of an inputndarrayis reversed.toFlippedud( x ): return a newndarraywhere the order of elements along the second-to-last dimension of an inputndarrayis reversed.toReversedDimension( x[, options] ): return a new ndarray where the order of elements of an input ndarray along a specified dimension is reversed.toReversed( x ): return a newndarraywhere the order of elements of an inputndarrayis reversed along each dimension.unshift( x, ...values ): return a one-dimensional ndarray formed by prepending provided scalar values to a one-dimensional input ndarray.vconcat( arrays ): concatenate a list of ndarrays along the second-to-last dimension.ndarrayWith( x, indices, value ): return a new ndarray with the element at a specified index replaced by a provided value.
The namespace exports the following functions to search multidimensional arrays:
anyBy( x[, options], predicate[, thisArg] ): test whether at least one element along one or morendarraydimensions passes a test implemented by a predicate function.any( x[, options] ): test whether at least one element along one or morendarraydimensions is truthy.countFalsy( x[, options] ): count the number of falsy elements along one or morendarraydimensions.countIf( x[, options], predicate[, thisArg] ): count the number of truthy elements along one or morendarraydimensions.countTruthy( x[, options] ): count the number of truthy elements along one or morendarraydimensions.everyBy( x[, options], predicate[, thisArg] ): test whether all elements along one or morendarraydimensions pass a test implemented by a predicate function.every( x[, options] ): test whether every element along one or morendarraydimensions is truthy.filterMap( x[, options], fcn[, thisArg] ): filter and map elements in an input ndarray to elements in a new output ndarray according to a callback function.filter( x[, options], predicate[, thisArg] ): return a shallow copy of an ndarray containing only those elements which pass a test implemented by a predicate function.findLast( x[, options], predicate[, thisArg] ): return a new ndarray containing the last elements which pass a test implemented by a predicate function along one or more ndarray dimensions.find( x[, options], predicate[, thisArg] ): return a new ndarray containing the first elements which pass a test implemented by a predicate function along one or more ndarray dimensions.includes( x, searchElement[, options] ): test whether anndarraycontains a specified value along one or more dimensions.reject( x[, options], predicate[, thisArg] ): return a shallow copy of an ndarray containing only those elements which fail a test implemented by a predicate function.someBy( x, n[, options], predicate[, thisArg] ): test whether at leastnelements along one or morendarraydimensions pass a test implemented by a predicate function.some( x, n[, options] ): test whether at leastnelements along one or morendarraydimensions are truthy.
The namespace exports the following functions to inspect multidimensional arrays:
dataBuffer( x ): return the underlying data buffer of a provided ndarray.dtype( x ): return the data type of a provided ndarray.flag( x, name ): return a specified flag for a provided ndarray.flags( x ): return the flags of a provided ndarray.ndims( x ): return the number of ndarray dimensions.numelDimension( x, dim ): return the size (i.e., number of elements) of a specified dimension for a provided ndarray.numel( x ): return the number of elements in an ndarray.offset( x ): return the index offset specifying the underlying buffer index of the first iterated ndarray element.order( x ): return the layout order of a provided ndarray.shape( x ): return the shape of a provided ndarray.stride( x, dim ): return the stride along a specified dimension for a provided ndarray.strides( x ): return the strides of a provided ndarray.
The namespace exports the following functions to index multidimensional arrays:
at( x[, ...indices] ): return anndarrayelement.ind2sub( shape, idx[, options] ): convert a linear index to an array of subscripts.ndindex( x[, options] ): ndarray index constructor.sub2ind( shape, ...subscripts[, options] ): convert subscripts to a linear index.
The namespace exports the following functions to convert multidimensional arrays:
The namespace exports the following functions for working with multidimensional array data types:
The namespace contains the following sub-namespaces:
The namespace contains the following multidimensional array utility functions:
castingModes(): 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.DataType( value[, options] ): data type constructor.dtypes( [kind] ): list of ndarray data types.FancyArray( dtype, buffer, shape, strides, offset, order[, options] ): fancy multidimensional array constructor.forEach( x, fcn[, thisArg] ): invoke a callback function once for each ndarray element.indexModes(): list of ndarray index modes.inputCastingPolicies(): list of input ndarray casting policies.minDataType( value ): determine the minimum ndarray data type of the closest "kind" necessary for storing a provided scalar value.mostlySafeCasts( [dtype] ): return a list of ndarray data types to which a provided ndarray data type can be safely cast and, for floating-point data types, can be downcast.nextDataType( [dtype] ): return the next larger ndarray data type of the same kind.orders(): list of ndarray orders.outputDataTypePolicies(): list of output ndarray data type policies.promotionRules( [dtype1, dtype2] ): return the ndarray data type with the smallest size and closest "kind" to which ndarray data types can be safely cast.safeCasts( [dtype] ): return a list of ndarray data types to which a provided ndarray data type can be safely cast.sameKindCasts( [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".ndarray2array( x ): convert an ndarray to a generic array.ndarray2json( x ): serialize an ndarray as a JSON object.ndarray2localeString( x[, locales[, options]] ): serialize an ndarray as a locale-aware string.ndarray2string( x ): serialize an ndarray as a string.
var objectKeys = require( '@stdlib/utils/keys' );
var ns = require( '@stdlib/ndarray' );
console.log( objectKeys( ns ) );