diff --git a/calculations/3body_Berggren_B2R_EC.jl b/calculations/3body_Berggren_B2R_EC.jl
index 263130d..7a5f867 100644
--- a/calculations/3body_Berggren_B2R_EC.jl
+++ b/calculations/3body_Berggren_B2R_EC.jl
@@ -5,7 +5,8 @@ include("../EC.jl")
 m = 1.0
 V_of_r(r) =  2 * exp(-(r-3)^2 / (1.5)^2)
 
-vertices = [0, 2 - 0.2im, 3, 4]
+ϕ = 0.1
+vertices = [0, 2 * exp(-2im * ϕ), 3, 4]
 subdivisions = [15, 10, 10]
 jmax = 4
 
diff --git a/calculations/3body_CSM_B2R_EC.jl b/calculations/3body_CSM_B2R_EC.jl
index 8e34f6d..5de6106 100644
--- a/calculations/3body_CSM_B2R_EC.jl
+++ b/calculations/3body_CSM_B2R_EC.jl
@@ -5,7 +5,8 @@ include("../EC.jl")
 m = 1.0
 V_of_r(r) =  2 * exp(-(r-3)^2 / (1.5)^2)
 
-vertices = [0, 6 - 0.6im]
+ϕ = 0.1
+vertices = [0, 6 * exp(-1im * ϕ)]
 subdivisions = [50]
 jmax = 4
 
@@ -23,13 +24,13 @@ extrapolating_c = 0.0 : 0.2 : 1.2
 
 training_ref = -2.22 # complete list not needed because identification is simple
 
-exact_E = [4.077092809998592-0.01206085331850782im,
-3.613579042377367-0.006920188044987599im,
-3.145489628680764-0.003757512658877539im,
-2.673033482861357-0.001939576896512454im,
-2.196539134888566-0.0009597849595725841im,
-1.7163902133045392-0.000456595029296216im,
-1.2329696647679096-0.00019879325231064393im]
+exact_E = [4.076662025307587-0.012709842443350328im,
+    3.613318119833891-0.007335804709990623im,
+    3.1453431847006783-0.004030580410326795im,
+    2.672967129943755-0.00211498327461944im,
+    2.196542557810288-0.0010719835443437104im,
+    1.7164583929199813-0.0005455212208182736im,
+    1.233088227541505-0.0003070320106485624im]
 
 EC = affine_EC(H0, Vp, weights)
 train!(EC, training_c; ref_eval=training_ref, CAEC=true)
diff --git a/calculations/3body_HO_B2R_EC.jl b/calculations/3body_HO_B2R_EC.jl
index ee52f80..7d37c2d 100644
--- a/calculations/3body_HO_B2R_EC.jl
+++ b/calculations/3body_HO_B2R_EC.jl
@@ -5,19 +5,27 @@ V_of_r(r) = 2 * exp(-(r-3)^2 / (1.5)^2)
 Λ = 0
 m = 1.0
 
-μω_global = 0.5 * exp(-2im * pi / 9)
-E_max = 30
+ϕ = 0.1
+μω_global = 0.5 * exp(-2im * ϕ)
+E_max = 36
 
-H0 = get_3b_H_matrix(src, V_of_r, μω_global, E_max, Λ, m, true, true)
+H0 = get_3b_H_matrix(jacobi, V_of_r, μω_global, E_max, Λ, m, true, true)
 
 # Vp = perturbation to make the state artificially bound
 Vp_of_r(r) = -exp(-(r/3)^2)
-@time "Vp" Vp = get_3b_H_matrix(src, Vp_of_r, μω_global, E_max, Λ, m, false, true)
+@time "Vp" Vp = get_3b_H_matrix(jacobi, Vp_of_r, μω_global, E_max, Λ, m, false, true)
 
-training_ref = -0.72763
-extrapolating_ref = 4.0766890719636635 - 0.01275892774109674im
+training_ref = -2.22
 
-training_c = [2.0, 1.9, 1.8]
+extrapolating_ref = [4.076662025307587-0.012709842443350328im,
+    3.613318119833891-0.007335804709990623im,
+    3.1453431847006783-0.004030580410326795im,
+    2.672967129943755-0.00211498327461944im,
+    2.196542557810288-0.0010719835443437104im,
+    1.7164583929199813-0.0005455212208182736im,
+    1.233088227541505-0.0003070320106485624im]
+
+training_c = [2.6, 2.4, 2.2, 2.0, 1.8]
 extrapolating_c = 0.0 : 0.2 : 1.2
 
 EC = affine_EC(H0, Vp)