BUG: Complex observables are not evaluable

[hz-xiaxz]

Error occurs when evaluating complex observables.

ERROR: LoadError: MethodError: no method matching Carlo.Evaluable(::Int64, ::Int64, ::Int64, ::Vector{ComplexF64}, ::Vector{ComplexF64})

Closest candidates are:
  Carlo.Evaluable(::Int64, ::Int64, ::Int64, !Matched::Vector{T}, !Matched::Vector{T}) where T<:AbstractFloat
   @ Carlo ~/.julia/dev/Carlo/src/evaluable.jl:3

this is because of the definition of struct Evaluable

struct Evaluable{T<:AbstractFloat}
    internal_bin_length::Int64
    rebin_length::Int64
    rebin_count::Int64

    mean::Vector{T}
    error::Vector{T}
end

where

julia> ComplexF64 isa AbstractFloat
false

[hz-xiaxz]

How to perform jackknife reasonably on complex number datasets is a question. I will try to find some reference later, or we should find another suitable way to resample complex numbers.

[lukas-weber]

Ah, thanks forgot to test that feature!

…

-------- Original Message --------

On 7/28/24 12:01, LeoXia wrote: Error occurs when evaluating complex observables. ERROR : LoadError : MethodError : no method matching Carlo . Evaluable ( :: Int64 , :: Int64 , :: Int64 , :: Vector{ComplexF64} , :: Vector{ComplexF64} ) Closest candidates are : Carlo . Evaluable ( :: Int64 , :: Int64 , :: Int64 , ! Matched :: Vector{T} , ! Matched :: Vector{T} ) where T <: AbstractFloat @ Carlo ~ / . julia / dev / Carlo / src / evaluable . jl : 3 this is because of the definition of struct Evaluable struct Evaluable{T <: AbstractFloat } internal_bin_length :: Int64 rebin_length :: Int64 rebin_count :: Int64 mean :: Vector{T} error :: Vector{T} end where julia> ComplexF64 isa AbstractFloat false — Reply to this email directly, [view it on GitHub](#12), or [unsubscribe](https://github.com/notifications/unsubscribe-auth/ALX63HZTRG5KQ7A432XOXI3ZOUIU3AVCNFSM6AAAAABLS5FNOOVHI2DSMVQWIX3LMV43ASLTON2WKOZSGQZTIMBQGUYTQNQ). You are receiving this because you are subscribed to this thread.Message ID: ***@***.***>

[lukas-weber]

True, if you find a reference or a straightforward way to do it, you're welcome to open a pr. I think a similar question appears already when computing the variance. But here I go with the definition of summing the real and imag variance just like the Julia functions do.

…

-------- Original Message --------

On 7/28/24 12:08, LeoXia wrote: How to perform jackknife reasonably on complex number datasets is a question. I will try to find some reference later, or we should find another suitable way to resample complex numbers. — Reply to this email directly, [view it on GitHub](#12 (comment)), or [unsubscribe](https://github.com/notifications/unsubscribe-auth/ALX63H6J37VSLMTNIGBLU63ZOUJQFAVCNFSM6AAAAABLS5FNOOVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDENJUGU3DQMBYGI). You are receiving this because you are subscribed to this thread.Message ID: ***@***.***>