uwLinAlg deleted and find_xmin commented

find_xmin to be tested (issues with double exponential fits)

src/juobs_tools.jl

@@ -141,3 +141,52 @@ Computes the results of a linear interpolation/extrapolation in the y axis
 y_lin_fit(par::Vector{uwreal}, x::Union{uwreal, Float64}) = par[1] + par[2] * x
 
 #TODO: add combined fits
+#=
+using LsqFit
+@doc raw"""
+find_xmin(obs::Vector{uwreal}, y0::Int64; pl::Bool=false)
+
+find_xmin(corr::Corr; pl::Bool=false)
+
+Find the platau starting point for a given correlator. 
+The starting point xmin is determined 
+|C_2|^2 * exp(-M_2 * (xmin-y0)) / (2 * M_2) < dC(xmin, y0) / 4
+where C_2 and M_2 are the matrix element and mass of the first excited state and dC is 
+the statistical error of the correlator
+"""
+function find_xmin(obs::Vector{uwreal}, y0::Int64; pl::Bool=false)
+    p0 = [0.5, 0.5, 1.0, 1.0]
+    @. model(t, p) = p[1] * exp(-p[2] * (t-y0)) + p[3] * exp(-p[4] * (t-y0))
+
+    x = Int64.(0:length(obs)-1)
+    uwerr.(obs)
+    y = value.(obs)
+    dy = err.(obs)
+    wt = 1 ./ dy.^2
+
+    fit = curve_fit(model, Float64.(x[y0+1:end]), y[y0+1:end], p0)
+    fit = curve_fit(model, Float64.(x[y0+1:end]), y[y0+1:end], wt[y0+1:end], fit.param)
+    par = fit.param
+    #println(par)
+    
+    if par[2] > par[4]
+        p1 = par[1]
+        p2 = par[2]
+    else
+        p1 = par[3]
+        p2 = par[4]
+    end
+    @. f(t) = p1^2 * exp(-p2 * (t-y0)) / (2 * p2)
+    xmin = findfirst(t-> f(t) < 0.25*dy[t + 1], x)
+
+    if pl
+        errorbar(x, y, dy, fmt="x")
+        t = Int64.(y0:length(obs))
+        plot(t, model(t, par))
+        display(gcf())    
+    end
+    return xmin
+end
+
+find_xmin(corr::Corr; pl::Bool=false) = find_xmin(corr.obs, corr.y0, pl=pl)
+=#
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