Error root

[jmarcellopereira]

An error occurs when using Roots.jl to solve an equation, the result should be -2.0, not -1.58.

using Measurements, Roots

a = measurement(1.0  , 0.1)
b = measurement(-3.0 , 0.1)
c = measurement(-10.0, 0.1)

f(x) = a*x^2 + b*x + c

find_zero(f, measurement(0.0, 0.1))

−1.58±0.12

[giordano]

Why not opening an issue in Roots.jl? The root finding algorithm is defined there, not here, f returns correct values:

julia> using Measurements

julia> a = measurement(1.0  , 0.1)
1.0 ± 0.1

julia> b = measurement(-3.0 , 0.1)
-3.0 ± 0.1

julia> c = measurement(-10.0, 0.1)
-10.0 ± 0.1

julia> f(x) = a*x^2 + b*x + c
f (generic function with 2 methods)

julia> f(-2.0)
0.0 ± 0.46

julia> f(-1.58)
-2.76 ± 0.31

[giordano]

I tried to reduce the code to

using Roots, Measurements

using Measurements, Roots

a = measurement(1.0  , 0.1)
b = measurement(-3.0 , 0.1)
c = measurement(-10.0, 0.1)
x0 = measurement(0.0, 0.1)

f(x) = a*x^2 + b*x + c
# Compare with function which doesn't have uncertainties
g(x) = Measurements.value(a*x^2 + b*x + c)

𝑭𝑿 = ZeroProblem(f, x0)
𝑮𝑿 = ZeroProblem(g, x0)
M = Order0()
p = nothing
verbose = false
tracks = Roots.NullTracks()

Zf = Roots.init(𝑭𝑿, M, p; verbose, tracks)
solve!(Zf; verbose)
Zg = Roots.init(𝑮𝑿, M, p; verbose, tracks)
solve!(Zg; verbose)

but now I'm lost in Roots.jl code. I'm not going to look into that, I'm not familiar with it and it looks quite complicated. Unless @jverzani is going to help I'll close this issue as I don't know what to do here.

[giordano]

Perhaps one relevant thing is that

julia> iszero(measurement(0, 0.1))
false

julia> measurement(0, 0.1) == 0
false

julia> isequal(measurement(0, 0.1), 0)
false

which may screw up some logic in Roots.jl, but the thing is that measurement(0, err) with non-zero err is not the neutral element of addition (that's measurement(0, 0)), which is the contract of the iszero function, so I'm not going to change that.

[jmarcellopereira]

Why not opening an issue in Roots.jl? The root finding algorithm is defined there, not here, f returns correct values:

julia> using Measurements

julia> a = measurement(1.0 , 0.1)
1.0 ± 0.1

julia> b = measurement(-3.0 , 0.1)
-3.0 ± 0.1

julia> c = measurement(-10.0, 0.1)
-10.0 ± 0.1

julia> f(x) = ax^2 + bx + c
f (generic function with 2 methods)

julia> f(-2.0)
0.0 ± 0.46

julia> f(-1.58)
-2.76 ± 0.31

Hello Giordano. I forgot to comment: the error in the value only appears when the uncertainties are declared.

[jmarcellopereira]

I tried to reduce the code to

using Roots, Measurements

using Measurements, Roots

a = measurement(1.0 , 0.1)
b = measurement(-3.0 , 0.1)
c = measurement(-10.0, 0.1)
x0 = measurement(0.0, 0.1)

f(x) = ax^2 + bx + c

Compare with function which doesn't have uncertainties

g(x) = Measurements.value(ax^2 + bx + c)

𝑭𝑿 = ZeroProblem(f, x0)
𝑮𝑿 = ZeroProblem(g, x0)
M = Order0()
p = nothing
verbose = false
tracks = Roots.NullTracks()

Zf = Roots.init(𝑭𝑿, M, p; verbose, tracks)
solve!(Zf; verbose)
Zg = Roots.init(𝑮𝑿, M, p; verbose, tracks)
solve!(Zg; verbose)
but now I'm lost in Roots.jl code. I'm not going to look into that, I'm not familiar with it and it looks quite complicated. Unless @jverzani is going to help I'll close this issue as I don't know what to do here.

Okay, I understand. The result was consistent and so were the uncertainties. Thank you for your response.