You can use @sprintf macro from the standard library package Printf. This returns a string rather than just printing it as @printf. using Printf x = 1.77715 print(“I’m long: $x, but I’m alright: $(@sprintf(“%.2f”, x))”) Output: I’m long: 1.77715, but I’m alright: 1.78
Updated answer, for Julia 0.7 onwards. import Random Random.seed!(1234) dim = 5 A = randn(dim,dim) H = (A + A’)/sqrt(2) Previous answer, for Julia 0.6 and earlier. You are looking for the srand function, e.g. srand(1234) dim = 5 A = randn(dim,dim) H = (A + A’)/sqrt(2) Will always produce the same results.
Currently (julia 1.2) is able to manage virual environments via it’s builtin Pkg standard library module: https://docs.julialang.org/en/v1/stdlib/Pkg julia> ] (v1.2) pkg> activate tutorial [ Info: activating new environment at `/tmp/tutorial/Project.toml`. (tutorial) pkg> (tutorial) pkg> status Status `/tmp/tutorial/Project.toml` (empty environment) (tutorial) pkg> add Example … (tutorial) pkg> status Status `/tmp/tutorial/Project.toml` [7876af07] Example v0.5.1 There is Playground.jl … Read more
The standard CPython implementation of Python parses source code and does some pre-processing and simplification of it – aka “lowering” – transforming it to a machine-friendly, easy-to-interpret format called “bytecode”. This is what is displayed when you “disassemble” a Python function. This code is not executable by the hardware – it is “executable” by the CPython interpreter. … Read more
EDIT: For Julia version 1.1+ Use the Pkg REPL notation: ] status # Show every installed package version ] status pkgName # Show the specific version of the package ] status pkgName1 pkgName2 # Show the named packages. You can continue the list. The ] enters the Pkg REPL, so you basically write status … … Read more
Certainly! Here’s the complete code incorporating the approaches discussed: using Traits @traitdef IsProduct{X} begin isnew(X) -> Bool coolness(X) -> Float64 end @traitdef IsProductWithMeasurement{X,M} begin @constraints begin istrait(IsProduct{X}) end measurements(X) -> M end type Rope color::String age_in_years::Float64 strength::Float64 length::Float64 end type Paper color::String age_in_years::Int64 content::String width::Float64 height::Float64 end function isnew(x::Rope) x.age_in_years < 10.0 end function coolness(x::Rope) … Read more
If you want to run the julia script from a command line then just do /path/to/julia script-name.jl In the shell of your choice. If you want to run it from the julia repl then you want something like so: julia> include(“path/to/script-name.jl”) As to why your output is split like that I think we would need … Read more
Just entering out the constant VERSION would also display the version number. julia> VERSION v”0.4.0″
In Julia, it’s a convention to append ! to names of functions that modify their arguments. The reason is Julia function arguments are passed-by-sharing, without this “bang” convention, it’s not easy to know whether a function will change the content of input arguments or not.
The first index is not necessarily 1 because Julia supports custom indexing. To understand why it is useful, you can’t beat Tim Holy’s blog post. Custom indices allow you to encode information about your data in the indexing pattern itself: sometimes it is more natural to start counting from one, sometimes from zero, sometimes from … Read more