similar

similar(array, [element_type=eltype(array)], [dims=size(array)])

Create an uninitialized mutable array with the given element type and size, based upon the given source array. The second and third arguments are both optional, defaulting to the given array's eltype and size. The dimensions may be specified either as a single tuple argument or as a series of integer arguments.

Custom AbstractArray subtypes may choose which specific array type is best-suited to return for the given element type and dimensionality. If they do not specialize this method, the default is an Array(element_type, dims...).

For example, similar(1:10, 1, 4) returns an uninitialized Array{Int,2} since ranges are neither mutable nor support 2 dimensions:

julia> similar(1:10, 1, 4)
1x4 Array{Int64,2}:
 4419743872  4374413872  4419743888  0

Conversely, similar(trues(10,10), 2) returns an uninitialized BitVector with two elements since BitArrays are both mutable and can support 1-dimensional arrays:

julia> similar(trues(10,10), 2)
2-element BitArray{1}:
 false
 false

Since BitArrays can only store elements of type Bool, however, if you request a different element type it will create a regular Array instead:

julia> similar(falses(10), Float64, 2, 4)
2x4 Array{Float64,2}:
 2.18425e-314  2.18425e-314  2.18425e-314  2.18425e-314
 2.18425e-314  2.18425e-314  2.18425e-314  2.18425e-314

Examples

julia> foo = [1,2,3];
julia> similar(foo, Int8, 3, 3)
3x3 Array{Int8,2}:
 -112   -101    0
 19     -30     0
 124    127     64

See Also

Array, broadcast, cat, combinations, conj!, digits!, fieldnames, fill, fill!, last, length, maximum, minimum, ones, parent, parentindexes, partitions, permutations, pointer, pointer_to_array, promote_shape, rand!, reshape, scale, similar, sum, sum_kbn, takebuf_array, transpose!, vec, zeros,

User Contributed Notes

Add a Note

The format of note supported is markdown, use triple backtick to start and end a code block.

*Required Field
Details

Checking you are not a robot: