Julia: Segmentation fault: 11

[rnoxy]

This simple code gives signal segv
I cannot figure out what's wrong :-(

f1(x,y,z) = x*y-z^2-1;
f2(x,y,z) = x*y*z+y^2-x^2-2;
f3(x,y,z) = exp(x)+z-exp(y)-3;

function Fun(x)
    return [ f1(x[1],x[2],x[3]); f2(x[1],x[2],x[3]); f3(x[1],x[2],x[3]) ];
end;

function Jac(x)
    return [ x[2] x[1] -2*x[3] ; x[2]*x[3]-2x[1]  x[1]*x[3]+2x[2]  x[1]*x[2] ; exp(x[1])  -exp(x[2])  1 ];
end

x = ones(3); # [1.0, 1.0, 1.0];

for it=1:5
    h = - \(Jac(x),Fun(x))
    x = x+h
end

The propblem is probably with for loop. One can try and do several steps without loop.
My julia is Version 0.6.0 (2017-06-19 13:05 UTC)
I tried both on Mac and Win. The same problem.

[Keno]

Manifests as a stack overflow error on my machine:

julia> for it=1:5
       h = - (Jac(x),Fun(x))
       x = x+h
       end
ERROR: StackOverflowError:
Stacktrace:
 [1] _methods_by_ftype(::Any, ::Int64, ::UInt64, ::Array{UInt64,1}, ::Array{UInt64,1}) at ./reflection.jl:521
 [2] abstract_call_gf_by_type(::Any, ::Any, ::Core.Inference.InferenceState) at ./inference.jl:1311
 [3] abstract_call(::Any, ::Array{Any,1}, ::Array{Any,1}, ::Array{Any,1}, ::Core.Inference.InferenceState) at ./inference.jl:1897
 [4] abstract_eval_call(::Expr, ::Array{Any,1}, ::Core.Inference.InferenceState) at ./inference.jl:1927
 [5] abstract_eval(::Any, ::Array{Any,1}, ::Core.Inference.InferenceState) at ./inference.jl:1950
 [6] typeinf_work(::Core.Inference.InferenceState) at ./inference.jl:2722
 [7] typeinf(::Core.Inference.InferenceState) at ./inference.jl:2787
 [8] typeinf_edge(::Method, ::Any, ::SimpleVector, ::Core.Inference.InferenceState) at ./inference.jl:2535
 [9] abstract_call_gf_by_type(::Any, ::Any, ::Core.Inference.InferenceState) at ./inference.jl:1420
 [10] abstract_call(::Any, ::Array{Any,1}, ::Array{Any,1}, ::Array{Any,1}, ::Core.Inference.InferenceState) at ./inference.jl:1897
 [11] abstract_eval_call(::Expr, ::Array{Any,1}, ::Core.Inference.InferenceState) at ./inference.jl:1927
 [12] abstract_eval(::Any, ::Array{Any,1}, ::Core.Inference.InferenceState) at ./inference.jl:1950
 [13] (::Core.Inference.##189#190{Array{Any,1},Core.Inference.InferenceState})(::Expr) at ./<missing>:0
 [14] next(::Core.Inference.Generator{Array{Any,1},Core.Inference.##189#190{Array{Any,1},Core.Inference.InferenceState}}, ::Int64) at ./generator.jl:45
 [15] copy!(::Array{Any,1}, ::Core.Inference.Generator{Array{Any,1},Core.Inference.##189#190{Array{Any,1},Core.Inference.InferenceState}}) at ./abstractarray.jl:573
 [16] _collect(::Type{Any}, ::Core.Inference.Generator{Array{Any,1},Core.Inference.##189#190{Array{Any,1},Core.Inference.InferenceState}}, ::Core.Inference.HasShape) at ./array.jl:396
 [17] collect(::Type{Any}, ::Core.Inference.Generator{Array{Any,1},Core.Inference.##189#190{Array{Any,1},Core.Inference.InferenceState}}) at ./array.jl:393
 [18] abstract_eval_call(::Expr, ::Array{Any,1}, ::Core.Inference.InferenceState) at ./inference.jl:1901
 [19] abstract_eval(::Any, ::Array{Any,1}, ::Core.Inference.InferenceState) at ./inference.jl:1950
 [20] abstract_interpret(::Any, ::Array{Any,1}, ::Core.Inference.InferenceState) at ./inference.jl:2076
 [21] typeinf_work(::Core.Inference.InferenceState) at ./inference.jl:2669
 [22] typeinf(::Core.Inference.InferenceState) at ./inference.jl:2787
 [23] typeinf_ext(::Core.MethodInstance, ::UInt64) at ./inference.jl:2628

[ararslan]

Same thing happens on current master.

[rnoxy]

I know. I check 0.7 as well. I didn’t sleep this night because of this.

[fredrikekre]

Somewhat different stacktrace (d3afdfd): https://gist.github.com/fredrikekre/e4f089ca902b97932e1c6dcffc76f21a , in particular note the

ERROR: UndefVarError: #s1 not defined
Stacktrace:
 [1] anonymous at ./<missing>:?

at the end. Note also that for me it does not crash the julia session.

[rnoxy]

I was preparing my lecture for my students about Newton method for solving system of nonlinear equations. Please tell me what should say to my students.

[fredrikekre]

Wrap in a function:

f1(x,y,z) = x*y-z^2-1
f2(x,y,z) = x*y*z+y^2-x^2-2
f3(x,y,z) = exp(x)+z-exp(y)-3

function Fun(x)
    return [ f1(x[1],x[2],x[3]); f2(x[1],x[2],x[3]); f3(x[1],x[2],x[3]) ]
end

function Jac(x)
    return [ x[2] x[1] -2*x[3] ; x[2]*x[3]-2x[1]  x[1]*x[3]+2x[2]  x[1]*x[2] ; exp(x[1])  -exp(x[2])  1 ]
end

function newton(x)
    for it = 1:5
        h = - (Jac(x)\Fun(x))
        x += h
    end
    return x
end

Works on both 0.6 and master:

julia> newton(ones(3))
3-element Array{Float64,1}:
 1.77767
 1.42396
 1.23747

[rnoxy]

Thank you very much guys.

[timholy]

Also, you should use 0.6 for teaching. 0.7 is changing/breaking stuff daily.

[KristofferC]

I think he is on 0.6

My julia is Version 0.6.0 (2017-06-19 13:05 UTC)

...

I check 0.7 as well.

[timholy]

Sorry for being confused.