# Convert arrays to single precision
**URL:** https://discourse.julialang.org/t/convert-arrays-to-single-precision/10903
**Category:** General Usage
**Tags:** question
**Created:** [May 15, 2018, 4:18am UTC](https://discourse.julialang.org/t/convert-arrays-to-single-precision/10903 "2018-05-15T04:18:15Z")
**Posts on this page:** 7
**Page:** 1
### Author:  [@jebej](https://discourse.julialang.org/u/jebej)
#### Post date: [May 15, 2018, 4:18am UTC](https://discourse.julialang.org/t/convert-arrays-to-single-precision/10903/1 "2018-05-15T04:18:15Z")
Hello, I was wondering if there exists a function to convert objects, e.g. `Array`, `SparseMatrix`, special matrix types like `Diagonal`, etc…) to single precision.
It should also handle converting objects of complex numbers (e.g. `Matrix{Complex{Float64}}` → `Matrix{Complex{Float32}}`).
Thanks,
Jeremy
---
### Author:  [@fredrikekre](https://discourse.julialang.org/u/fredrikekre)
#### Post date: [May 15, 2018, 4:29am UTC](https://discourse.julialang.org/t/convert-arrays-to-single-precision/10903/2 "2018-05-15T04:29:05Z")
```julia
julia> A = rand(Complex128, 2, 2)
2×2 Array{Complex{Float64},2}:
0.675516+0.723924im 0.599831+0.998357im
0.526924+0.509325im 0.223859+0.164175im
julia> convert(Matrix{Complex64}, A)
2×2 Array{Complex{Float32},2}:
0.675516+0.723924im 0.599831+0.998357im
0.526924+0.509325im 0.223859+0.164175im
```
---
### Author:  [@jebej](https://discourse.julialang.org/u/jebej)
#### Post date: [May 15, 2018, 4:33am UTC](https://discourse.julialang.org/t/convert-arrays-to-single-precision/10903/3 "2018-05-15T04:33:20Z")
I know about `convert`, but I am looking for something that will preserve the container type…
---
### Author:  [@rdeits](https://discourse.julialang.org/u/rdeits)
#### Post date: [May 15, 2018, 4:33am UTC](https://discourse.julialang.org/t/convert-arrays-to-single-precision/10903/4 "2018-05-15T04:33:32Z")
i don’t believe such a function exists, but Julia provides all the tools to construct one.
```julia
julia> singlify(x::Float64) = Float32(x)
singlify (generic function with 1 method)
julia> singlify(x::Complex{Float64}) = Complex{Float32}(x)
singlify (generic function with 2 methods)
```
Broadcasting works quite nicely for applying the function elementwise to various different kinds of arrays:
```julia
julia> x = rand(2, 2)
2×2 Array{Float64,2}:
0.689747 0.539186
0.607853 0.858326
julia> singlify.(x)
2×2 Array{Float32,2}:
0.689747 0.539186
0.607853 0.858326
julia> x = sprand(2, 2, 0.5)
2×2 SparseMatrixCSC{Float64,Int64} with 4 stored entries:
[1, 1] = 0.0518641
[2, 1] = 0.896834
[1, 2] = 0.0067949
[2, 2] = 0.57429
julia> singlify.(x)
2×2 SparseMatrixCSC{Float32,Int64} with 4 stored entries:
[1, 1] = 0.0518641
[2, 1] = 0.896834
[1, 2] = 0.0067949
[2, 2] = 0.57429
```
Unfortunately, Diagonals aren’t handled perfectly:
```julia
julia> x = Diagonal([1., 2])
2×2 Diagonal{Float64}:
1.0 ⋅
⋅ 2.0
julia> singlify.(x)
2×2 SparseMatrixCSC{Float32,Int64} with 2 stored entries:
[1, 1] = 1.0
[2, 2] = 2.0
```
The fact that broadcasting over a `Diagonal` returns a plain sparse matrix is, fortunately, resolved in the latest nightly builds of Julia, so in the future, you should get a `Diagonal` out.
---
### Author:  [@jebej](https://discourse.julialang.org/u/jebej)
#### Post date: [May 15, 2018, 4:37am UTC](https://discourse.julialang.org/t/convert-arrays-to-single-precision/10903/5 "2018-05-15T04:37:05Z")
I see, thanks!
---
### Author:  [@fredrikekre](https://discourse.julialang.org/u/fredrikekre)
#### Post date: [May 15, 2018, 5:57am UTC](https://discourse.julialang.org/t/convert-arrays-to-single-precision/10903/6 "2018-05-15T05:57:47Z")
Note that the broadcasting solution above makes a copy even in cases where the data is already of single precision.
Another solution is to convert to an `AbstractArray`
```julia
julia> x = sprand(2, 2, 0.5)
2×2 SparseMatrixCSC{Float64,Int64} with 1 stored entry:
[1, 2] = 0.897311
julia> convert(AbstractArray{Float32}, x)
2×2 SparseMatrixCSC{Float32,Int64} with 1 stored entry:
[1, 2] = 0.897311
julia> x = Diagonal([1., 2])
2×2 Diagonal{Float64}:
1.0 ⋅
⋅ 2.0
julia> convert(AbstractArray{Float32}, x)
2×2 Diagonal{Float32}:
1.0 ⋅
⋅ 2.0
```
---
### Author:  [@jebej](https://discourse.julialang.org/u/jebej)
#### Post date: [May 15, 2018, 12:48pm UTC](https://discourse.julialang.org/t/convert-arrays-to-single-precision/10903/7 "2018-05-15T12:48:02Z")
Even better!