I am using Julia .6.1 and get a odd result when adding across columns of an array with specific values. Consider:
x = [.10 .20;.10 .30]
x[:,1] + x[:,2]
Output:
Float64[2]
0.30000000000000004
0.400
Julia .5 provides the correct output. Interestingly, in .6.1 sum(x,2) works and x with different values also works.
Thanks for the link. It appears that the problem is even more specific than I initially thought. It occurs in Atom, but not the REPL.
Do you have any advice for avoiding these situations?
There is still something interesting how is array represented on screen. I tested in on REPL:
Julia 0.6.1, OS: Linux (x86_64-linux-gnu):
julia> [0.1+0.2, 1.]
2-element Array{Float64,1}:
0.3
1.0
Julia 0.7.0-DEV.2815, OS: Linux (x86_64-linux-gnu):
julia> [0.1+0.2, 1.]
2-element Array{Float64,1}:
0.30000000000000004
1.0
Both platform:
julia> 0.1 + 0.2
0.30000000000000004
julia> repr([0.1+0.2, 1.])
"[0.3, 1.0]"
julia> show([0.1+0.2, 1.])
[0.3, 1.0]
julia> [0.1+0.2, 1.][1]
0.30000000000000004
Is difference here:
ccall(:jl_toplevel_eval_in, Any, (Any, Any), m, e)
?
The value is the same, but the number of significant digits printed has in some situations changed between 0.6 and 0.7.
The result is the same, printing methods are different.
If you worry about printing results, you can format them as you want:
@printf "%.2f" pi
If you want to truncate numbers to have specific precision, you can round them:
round(pi, 2)
Although I doubt you even need to do it in practice.