minor modifications to some constant values

constants/juobs_const.jl

@@ -17,10 +17,11 @@ const ZV_err = [74, 89, 46, 48, 49] .* 1e-5
 #2005.01352
 const ZS_over_ZP_data = [1.3497, 1.2914, 1.2317, 1.1709, 1.1343]
 const ZS_over_ZP_err = [83, 64, 48, 23, 25 ] .* 1e-4
-#1608.08900
+#2101.02694
 # const b_values2 = [3.40, 3.46, 3.55, 3.70]
-const t0_data = [2.86, 3.659, 5.164, 8.595, 14.040]
-const t0_error = [11, 16, 18, 29, 49] .* 1e-3
+const t0_data = [2.846, 3.634, 5.140, 8.564, 14.064]
+const t0_error = [8, 13, 21, 24, 63] .* 1e-3
+# from AS analysis 
 const t0_ph_value = [0.4118]
 const t0_ph_error = ones(1,1) .* 25e-4
 #2101.10969
@@ -38,6 +39,10 @@ z = cobs([0.348629, 0.020921, 0.070613], C, "z")
 ZP(b) = z[1] + z[2] * (b - 3.79) + z[3] * (b - 3.79)^2
 Mrat = uwreal([.9148, 0.0088], "M/mhad")
 zm_tm_covar(b) = Mrat / ZP(b)
+# same for zm wilson
+CC = [[0.164635e-4, 0.215658e-4, -0.754203e-4] [0.215658e-4, 0.121072e-2, 0.308890e-2] [-0.754203e-4, 0.308890e-2, 0.953843e-2]]
+zz = cobs([2.270073, 0.121644, -0.464575], CC, "zm")
+z_covar(b) = value(Mrat) * (zz[1] + zz[2]*(b-3.79) + zz[3]*(b-3.79)^2)
 
 ## taking into account correlations in r_m
 #Crm = [[3.699760, -2.198586, -1.476913e-3] [-2.198586, 1.306512, 8.776569e-4] [-1.476913e-3, 8.776569e-4, 5.895710e-7] ]

src/juobs_linalg.jl

@@ -853,7 +853,9 @@ function Base.getindex(uw::uwreal, ii::Int64)
     idx = getindex(value(uw), ii)
     return  uw # uwreal([getindex(value(uw), kwargs...), err(uw)], " ")
 end
-
+function Base.abs2(uw::uwreal)
+    return (uw^2)^0.5
+end
 """
 Base.:*(x::uwreal, y::Matrix{uwreal})
 

src/juobs_tools.jl

@@ -1266,7 +1266,7 @@ function fit_routine(model::Function, xdata::Array{uwreal}, ydata::Array{uwreal}
         println("Chisq / chiexp: ", min_fun_cov(sol.minimizer), " / ", chi2_exp, " (dof: ", length(ydata) - param,")")
         chis2_corrected = (length(ydata) - param) * min_fun_cov(sol.minimizer) / chi2_exp
         println("Chisq corrected: ", chis2_corrected)
-        return upar, min_fun_cov(sol.minimizer) / chi2_exp
+        return upar, min_fun_cov(sol.minimizer) / chi2_exp, chi2_exp
 
     else
         chisq_full(p, d) = get_chi2(model, d, ddat, p, Nalpha)
@@ -1277,7 +1277,7 @@ function fit_routine(model::Function, xdata::Array{uwreal}, ydata::Array{uwreal}
         println("Chisq / chiexp: ", min_fun(sol.minimizer), " / ", chi2_exp, " (dof: ", length(ydata) - param,")")
         chis2_corrected = (length(ydata) - param) * min_fun(sol.minimizer) / chi2_exp
         println("Chisq corrected: ", chis2_corrected)
-        return upar, min_fun(sol.minimizer) / chi2_exp
+        return upar, min_fun(sol.minimizer) / chi2_exp, chi2_exp
     end
 
     #### chisq_full, min_fun out of conditional ->