Periodic BC for Gaussians

vpuri3 · Aug 13, 2024 · 98f9483 · 98f9483
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diff --git a/experiments_NGN/data_AD1D/traj_1.png b/experiments_NGN/data_AD1D/traj_1.png
diff --git a/experiments_NGN/data_AD1D/traj_2.png b/experiments_NGN/data_AD1D/traj_2.png
diff --git a/experiments_NGN/data_AD1D/traj_3.png b/experiments_NGN/data_AD1D/traj_3.png
diff --git a/experiments_NGN/data_AD1D/traj_4.png b/experiments_NGN/data_AD1D/traj_4.png
diff --git a/experiments_NGN/data_AD1D/traj_5.png b/experiments_NGN/data_AD1D/traj_5.png
diff --git a/experiments_NGN/data_AD1D/traj_6.png b/experiments_NGN/data_AD1D/traj_6.png
diff --git a/experiments_NGN/data_AD1D/traj_7.png b/experiments_NGN/data_AD1D/traj_7.png
diff --git a/experiments_NGN/data_AD1D/traj_8.png b/experiments_NGN/data_AD1D/traj_8.png
diff --git a/experiments_NGN/datagen_AD1D.jl b/experiments_NGN/datagen_AD1D.jl
@@ -161,8 +161,8 @@ c = 1f0
 T = Float64
 mu = nothing # parameters
 
-cs = T[1, 0, 1]
-νs = T[0, 0.01, 0.01]
+cs = T[1,    0,    1, 2.5]
+νs = T[0, 0.01, 0.01, 0]
 mu = zip(cs, νs) |> collect
 device = cpu_device()
 

diff --git a/experiments_NGN/dump_gaussian/evolve_e1_case1.png b/experiments_NGN/dump_gaussian/evolve_e1_case1.png
diff --git a/experiments_NGN/dump_gaussian/evolve_e1_case2.png b/experiments_NGN/dump_gaussian/evolve_e1_case2.png
diff --git a/experiments_NGN/dump_gaussian/evolve_e1_case3.png b/experiments_NGN/dump_gaussian/evolve_e1_case3.png
diff --git a/experiments_NGN/dump_gaussian/evolve_e1_case4.png b/experiments_NGN/dump_gaussian/evolve_e1_case4.png
diff --git a/experiments_NGN/dump_gaussian/evolve_e1_case5.png b/experiments_NGN/dump_gaussian/evolve_e1_case5.png
diff --git a/experiments_NGN/dump_gaussian/evolve_e1_case6.png b/experiments_NGN/dump_gaussian/evolve_e1_case6.png
diff --git a/experiments_NGN/dump_gaussian/evolve_e1_case7.png b/experiments_NGN/dump_gaussian/evolve_e1_case7.png
diff --git a/experiments_NGN/dump_gaussian/evolve_u1_case1.png b/experiments_NGN/dump_gaussian/evolve_u1_case1.png
diff --git a/experiments_NGN/dump_gaussian/evolve_u1_case2.png b/experiments_NGN/dump_gaussian/evolve_u1_case2.png
diff --git a/experiments_NGN/dump_gaussian/evolve_u1_case3.png b/experiments_NGN/dump_gaussian/evolve_u1_case3.png
diff --git a/experiments_NGN/dump_gaussian/evolve_u1_case4.png b/experiments_NGN/dump_gaussian/evolve_u1_case4.png
diff --git a/experiments_NGN/dump_gaussian/evolve_u1_case5.png b/experiments_NGN/dump_gaussian/evolve_u1_case5.png
diff --git a/experiments_NGN/dump_gaussian/evolve_u1_case6.png b/experiments_NGN/dump_gaussian/evolve_u1_case6.png
diff --git a/experiments_NGN/dump_gaussian/evolve_u1_case7.png b/experiments_NGN/dump_gaussian/evolve_u1_case7.png
diff --git a/experiments_NGN/dump_gaussian/plt_param2/plt_p1.png b/experiments_NGN/dump_gaussian/plt_param2/plt_p1.png
diff --git a/experiments_NGN/dump_gaussian/plt_param2/plt_p2.png b/experiments_NGN/dump_gaussian/plt_param2/plt_p2.png
diff --git a/experiments_NGN/dump_gaussian/plt_param2/plt_p3.png b/experiments_NGN/dump_gaussian/plt_param2/plt_p3.png
diff --git a/experiments_NGN/dump_gaussian/plt_param2/plt_p4.png b/experiments_NGN/dump_gaussian/plt_param2/plt_p4.png
diff --git a/experiments_NGN/dump_gaussian/plt_param3/plt_p1.png b/experiments_NGN/dump_gaussian/plt_param3/plt_p1.png
diff --git a/experiments_NGN/dump_gaussian/plt_param3/plt_p2.png b/experiments_NGN/dump_gaussian/plt_param3/plt_p2.png
diff --git a/experiments_NGN/dump_gaussian/plt_param3/plt_p3.png b/experiments_NGN/dump_gaussian/plt_param3/plt_p3.png
diff --git a/experiments_NGN/dump_gaussian/plt_param3/plt_p4.png b/experiments_NGN/dump_gaussian/plt_param3/plt_p4.png
diff --git a/experiments_NGN/dump_gaussian/plt_param4/plt_p1.png b/experiments_NGN/dump_gaussian/plt_param4/plt_p1.png
diff --git a/experiments_NGN/dump_gaussian/plt_param4/plt_p2.png b/experiments_NGN/dump_gaussian/plt_param4/plt_p2.png
diff --git a/experiments_NGN/dump_gaussian/plt_param4/plt_p3.png b/experiments_NGN/dump_gaussian/plt_param4/plt_p3.png
diff --git a/experiments_NGN/dump_gaussian/plt_param4/plt_p4.png b/experiments_NGN/dump_gaussian/plt_param4/plt_p4.png
diff --git a/experiments_NGN/dump_gaussian/project1/plt1.png b/experiments_NGN/dump_gaussian/project1/plt1.png
diff --git a/experiments_NGN/dump_gaussian/project1/plt_training.png b/experiments_NGN/dump_gaussian/project1/plt_training.png
diff --git a/experiments_NGN/dump_gaussian/project1/statistics_01.txt b/experiments_NGN/dump_gaussian/project1/statistics_01.txt
@@ -1,21 +1,21 @@
-Epoch [0 / 0]	TRAIN LOSS: 9.9374197e-13 || TEST LOSS: 9.9374197e-13
+Epoch [0 / 0]	TRAIN LOSS: 2.5130424e-9 || TEST LOSS: 2.5130424e-9
 #======================#
 TRAIN STATS
-R² score:             1.0
-MSE (mean SQR error): 9.9374197e-13
-RMSE (Root MSE):      9.9686607e-7
-MAE (mean ABS error): 6.7875755e-7
-maxAE (max ABS error) 3.7766936e-6
+R² score:             0.99999995
+MSE (mean SQR error): 2.5130424e-9
+RMSE (Root MSE):      5.0130254e-5
+MAE (mean ABS error): 3.2035673e-5
+maxAE (max ABS error) 0.00021987989
 Lipschitz bound:      1.0
 
 #======================#
 #======================#
 TEST  STATS
-R² score:             1.0
-MSE (mean SQR error): 9.9374197e-13
-RMSE (Root MSE):      9.9686607e-7
-MAE (mean ABS error): 6.7875755e-7
-maxAE (max ABS error) 3.7766936e-6
+R² score:             0.99999995
+MSE (mean SQR error): 2.5130424e-9
+RMSE (Root MSE):      5.0130254e-5
+MAE (mean ABS error): 3.2035673e-5
+maxAE (max ABS error) 0.00021987989
 Lipschitz bound:      1.0
 
 #======================#
diff --git a/experiments_NGN/dump_gaussian/project1/statistics_02.txt b/experiments_NGN/dump_gaussian/project1/statistics_02.txt
@@ -1,21 +1,21 @@
-Epoch [0 / 0]	TRAIN LOSS: 3.5519407e-21 || TEST LOSS: 3.5519407e-21
+Epoch [0 / 0]	TRAIN LOSS: 6.4720554e-23 || TEST LOSS: 6.4720554e-23
 #======================#
 TRAIN STATS
 R² score:             1.0
-MSE (mean SQR error): 3.5519407e-21
-RMSE (Root MSE):      5.959816e-11
-MAE (mean ABS error): 3.4676842e-11
-maxAE (max ABS error) 2.3533642e-10
+MSE (mean SQR error): 6.4720554e-23
+RMSE (Root MSE):      8.0449086e-12
+MAE (mean ABS error): 4.471342e-12
+maxAE (max ABS error) 3.2871261e-11
 Lipschitz bound:      1.0
 
 #======================#
 #======================#
 TEST  STATS
 R² score:             1.0
-MSE (mean SQR error): 3.5519407e-21
-RMSE (Root MSE):      5.959816e-11
-MAE (mean ABS error): 3.4676842e-11
-maxAE (max ABS error) 2.3533642e-10
+MSE (mean SQR error): 6.4720554e-23
+RMSE (Root MSE):      8.0449086e-12
+MAE (mean ABS error): 4.471342e-12
+maxAE (max ABS error) 3.2871261e-11
 Lipschitz bound:      1.0
 
 #======================#
diff --git a/experiments_NGN/dump_gaussian/project1/statistics_03.txt b/experiments_NGN/dump_gaussian/project1/statistics_03.txt
@@ -1,21 +1,21 @@
-Epoch [0 / 0]	TRAIN LOSS: 2.5670929e-31 || TEST LOSS: 2.5670929e-31
+Epoch [0 / 0]	TRAIN LOSS: 7.2146536e-31 || TEST LOSS: 7.2146536e-31
 #======================#
 TRAIN STATS
 R² score:             1.0
-MSE (mean SQR error): 2.5670929e-31
-RMSE (Root MSE):      5.0666487e-16
-MAE (mean ABS error): 2.0461871000000002e-16
-maxAE (max ABS error) 2.4424907e-15
+MSE (mean SQR error): 7.2146536e-31
+RMSE (Root MSE):      8.493911700000001e-16
+MAE (mean ABS error): 3.6614886000000005e-16
+maxAE (max ABS error) 4.3298698e-15
 Lipschitz bound:      1.0
 
 #======================#
 #======================#
 TEST  STATS
 R² score:             1.0
-MSE (mean SQR error): 2.5670929e-31
-RMSE (Root MSE):      5.0666487e-16
-MAE (mean ABS error): 2.0461871000000002e-16
-maxAE (max ABS error) 2.4424907e-15
+MSE (mean SQR error): 7.2146536e-31
+RMSE (Root MSE):      8.493911700000001e-16
+MAE (mean ABS error): 3.6614886000000005e-16
+maxAE (max ABS error) 4.3298698e-15
 Lipschitz bound:      1.0
 
 #======================#
diff --git a/experiments_NGN/dump_gaussian/project1/statistics_04.txt b/experiments_NGN/dump_gaussian/project1/statistics_04.txt
@@ -1,21 +1,21 @@
-Epoch [0 / 0]	TRAIN LOSS: 2.1978478e-31 || TEST LOSS: 2.1978478e-31
+Epoch [0 / 0]	TRAIN LOSS: 6.0327308e-31 || TEST LOSS: 6.0327308e-31
 #======================#
 TRAIN STATS
 R² score:             1.0
-MSE (mean SQR error): 2.1978478e-31
-RMSE (Root MSE):      4.688121e-16
-MAE (mean ABS error): 2.1360208000000003e-16
-maxAE (max ABS error) 2.4424907e-15
+MSE (mean SQR error): 6.0327308e-31
+RMSE (Root MSE):      7.767065600000001e-16
+MAE (mean ABS error): 3.8524347000000004e-16
+maxAE (max ABS error) 3.8857806e-15
 Lipschitz bound:      1.0
 
 #======================#
 #======================#
 TEST  STATS
 R² score:             1.0
-MSE (mean SQR error): 2.1978478e-31
-RMSE (Root MSE):      4.688121e-16
-MAE (mean ABS error): 2.1360208000000003e-16
-maxAE (max ABS error) 2.4424907e-15
+MSE (mean SQR error): 6.0327308e-31
+RMSE (Root MSE):      7.767065600000001e-16
+MAE (mean ABS error): 3.8524347000000004e-16
+maxAE (max ABS error) 3.8857806e-15
 Lipschitz bound:      1.0
 
 #======================#
diff --git a/experiments_NGN/dump_gaussian/project1/statistics_05.txt b/experiments_NGN/dump_gaussian/project1/statistics_05.txt
@@ -1,21 +1,21 @@
-Epoch [0 / 0]	TRAIN LOSS: 2.1978478e-31 || TEST LOSS: 2.1978478e-31
+Epoch [0 / 0]	TRAIN LOSS: 6.0327308e-31 || TEST LOSS: 6.0327308e-31
 #======================#
 TRAIN STATS
 R² score:             1.0
-MSE (mean SQR error): 2.1978478e-31
-RMSE (Root MSE):      4.688121e-16
-MAE (mean ABS error): 2.1360208000000003e-16
-maxAE (max ABS error) 2.4424907e-15
+MSE (mean SQR error): 6.0327308e-31
+RMSE (Root MSE):      7.767065600000001e-16
+MAE (mean ABS error): 3.8524347000000004e-16
+maxAE (max ABS error) 3.8857806e-15
 Lipschitz bound:      1.0
 
 #======================#
 #======================#
 TEST  STATS
 R² score:             1.0
-MSE (mean SQR error): 2.1978478e-31
-RMSE (Root MSE):      4.688121e-16
-MAE (mean ABS error): 2.1360208000000003e-16
-maxAE (max ABS error) 2.4424907e-15
+MSE (mean SQR error): 6.0327308e-31
+RMSE (Root MSE):      7.767065600000001e-16
+MAE (mean ABS error): 3.8524347000000004e-16
+maxAE (max ABS error) 3.8857806e-15
 Lipschitz bound:      1.0
 
 #======================#
diff --git a/experiments_NGN/dump_gaussian/project2/plt1.png b/experiments_NGN/dump_gaussian/project2/plt1.png
diff --git a/experiments_NGN/dump_gaussian/project2/plt_training.png b/experiments_NGN/dump_gaussian/project2/plt_training.png
diff --git a/experiments_NGN/dump_gaussian/project2/statistics_01.txt b/experiments_NGN/dump_gaussian/project2/statistics_01.txt
@@ -1,21 +1,21 @@
-Epoch [0 / 0]	TRAIN LOSS: 9.9374197e-13 || TEST LOSS: 9.9374197e-13
+Epoch [0 / 0]	TRAIN LOSS: 5.6184621e-15 || TEST LOSS: 5.6184621e-15
 #======================#
 TRAIN STATS
 R² score:             1.0
-MSE (mean SQR error): 9.9374197e-13
-RMSE (Root MSE):      9.9686607e-7
-MAE (mean ABS error): 6.7875755e-7
-maxAE (max ABS error) 3.7766936e-6
+MSE (mean SQR error): 5.6184621e-15
+RMSE (Root MSE):      7.4956402e-8
+MAE (mean ABS error): 2.3870774e-8
+maxAE (max ABS error) 3.397996e-7
 Lipschitz bound:      1.0
 
 #======================#
 #======================#
 TEST  STATS
 R² score:             1.0
-MSE (mean SQR error): 9.9374197e-13
-RMSE (Root MSE):      9.9686607e-7
-MAE (mean ABS error): 6.7875755e-7
-maxAE (max ABS error) 3.7766936e-6
+MSE (mean SQR error): 5.6184621e-15
+RMSE (Root MSE):      7.4956402e-8
+MAE (mean ABS error): 2.3870774e-8
+maxAE (max ABS error) 3.397996e-7
 Lipschitz bound:      1.0
 
 #======================#
diff --git a/experiments_NGN/dump_gaussian/project2/statistics_02.txt b/experiments_NGN/dump_gaussian/project2/statistics_02.txt
@@ -1,21 +1,21 @@
-Epoch [0 / 0]	TRAIN LOSS: 3.5519407e-21 || TEST LOSS: 3.5519407e-21
+Epoch [0 / 0]	TRAIN LOSS: 5.5139156e-32 || TEST LOSS: 5.5139156e-32
 #======================#
 TRAIN STATS
 R² score:             1.0
-MSE (mean SQR error): 3.5519407e-21
-RMSE (Root MSE):      5.959816e-11
-MAE (mean ABS error): 3.4676842e-11
-maxAE (max ABS error) 2.3533642e-10
+MSE (mean SQR error): 5.5139156e-32
+RMSE (Root MSE):      2.3481728000000003e-16
+MAE (mean ABS error): 8.5861566e-17
+maxAE (max ABS error) 1.110223e-15
 Lipschitz bound:      1.0
 
 #======================#
 #======================#
 TEST  STATS
 R² score:             1.0
-MSE (mean SQR error): 3.5519407e-21
-RMSE (Root MSE):      5.959816e-11
-MAE (mean ABS error): 3.4676842e-11
-maxAE (max ABS error) 2.3533642e-10
+MSE (mean SQR error): 5.5139156e-32
+RMSE (Root MSE):      2.3481728000000003e-16
+MAE (mean ABS error): 8.5861566e-17
+maxAE (max ABS error) 1.110223e-15
 Lipschitz bound:      1.0
 
 #======================#
diff --git a/experiments_NGN/dump_gaussian/project2/statistics_03.txt b/experiments_NGN/dump_gaussian/project2/statistics_03.txt
@@ -1,21 +1,21 @@
-Epoch [0 / 0]	TRAIN LOSS: 2.5670929e-31 || TEST LOSS: 2.5670929e-31
+Epoch [0 / 0]	TRAIN LOSS: 1.3164037e-32 || TEST LOSS: 1.3164037e-32
 #======================#
 TRAIN STATS
 R² score:             1.0
-MSE (mean SQR error): 2.5670929e-31
-RMSE (Root MSE):      5.0666487e-16
-MAE (mean ABS error): 2.0461871000000002e-16
-maxAE (max ABS error) 2.4424907e-15
+MSE (mean SQR error): 1.3164037e-32
+RMSE (Root MSE):      1.1473464000000002e-16
+MAE (mean ABS error): 4.719512e-17
+maxAE (max ABS error) 5.551115100000001e-16
 Lipschitz bound:      1.0
 
 #======================#
 #======================#
 TEST  STATS
 R² score:             1.0
-MSE (mean SQR error): 2.5670929e-31
-RMSE (Root MSE):      5.0666487e-16
-MAE (mean ABS error): 2.0461871000000002e-16
-maxAE (max ABS error) 2.4424907e-15
+MSE (mean SQR error): 1.3164037e-32
+RMSE (Root MSE):      1.1473464000000002e-16
+MAE (mean ABS error): 4.719512e-17
+maxAE (max ABS error) 5.551115100000001e-16
 Lipschitz bound:      1.0
 
 #======================#
diff --git a/experiments_NGN/dump_gaussian/project2/statistics_04.txt b/experiments_NGN/dump_gaussian/project2/statistics_04.txt
@@ -1,21 +1,21 @@
-Epoch [0 / 0]	TRAIN LOSS: 2.1978478e-31 || TEST LOSS: 2.1978478e-31
+Epoch [0 / 0]	TRAIN LOSS: 1.3051595000000001e-32 || TEST LOSS: 1.3051595000000001e-32
 #======================#
 TRAIN STATS
 R² score:             1.0
-MSE (mean SQR error): 2.1978478e-31
-RMSE (Root MSE):      4.688121e-16
-MAE (mean ABS error): 2.1360208000000003e-16
-maxAE (max ABS error) 2.4424907e-15
+MSE (mean SQR error): 1.3051595000000001e-32
+RMSE (Root MSE):      1.1424358e-16
+MAE (mean ABS error): 5.0813553e-17
+maxAE (max ABS error) 5.551115100000001e-16
 Lipschitz bound:      1.0
 
 #======================#
 #======================#
 TEST  STATS
 R² score:             1.0
-MSE (mean SQR error): 2.1978478e-31
-RMSE (Root MSE):      4.688121e-16
-MAE (mean ABS error): 2.1360208000000003e-16
-maxAE (max ABS error) 2.4424907e-15
+MSE (mean SQR error): 1.3051595000000001e-32
+RMSE (Root MSE):      1.1424358e-16
+MAE (mean ABS error): 5.0813553e-17
+maxAE (max ABS error) 5.551115100000001e-16
 Lipschitz bound:      1.0
 
 #======================#
diff --git a/experiments_NGN/dump_gaussian/project2/statistics_05.txt b/experiments_NGN/dump_gaussian/project2/statistics_05.txt
@@ -1,21 +1,21 @@
-Epoch [0 / 0]	TRAIN LOSS: 2.1978478e-31 || TEST LOSS: 2.1978478e-31
+Epoch [0 / 0]	TRAIN LOSS: 1.3051595000000001e-32 || TEST LOSS: 1.3051595000000001e-32
 #======================#
 TRAIN STATS
 R² score:             1.0
-MSE (mean SQR error): 2.1978478e-31
-RMSE (Root MSE):      4.688121e-16
-MAE (mean ABS error): 2.1360208000000003e-16
-maxAE (max ABS error) 2.4424907e-15
+MSE (mean SQR error): 1.3051595000000001e-32
+RMSE (Root MSE):      1.1424358e-16
+MAE (mean ABS error): 5.0813553e-17
+maxAE (max ABS error) 5.551115100000001e-16
 Lipschitz bound:      1.0
 
 #======================#
 #======================#
 TEST  STATS
 R² score:             1.0
-MSE (mean SQR error): 2.1978478e-31
-RMSE (Root MSE):      4.688121e-16
-MAE (mean ABS error): 2.1360208000000003e-16
-maxAE (max ABS error) 2.4424907e-15
+MSE (mean SQR error): 1.3051595000000001e-32
+RMSE (Root MSE):      1.1424358e-16
+MAE (mean ABS error): 5.0813553e-17
+maxAE (max ABS error) 5.551115100000001e-16
 Lipschitz bound:      1.0
 
 #======================#
diff --git a/experiments_NGN/dump_gaussian/project3/plt1.png b/experiments_NGN/dump_gaussian/project3/plt1.png
diff --git a/experiments_NGN/dump_gaussian/project3/plt_training.png b/experiments_NGN/dump_gaussian/project3/plt_training.png
diff --git a/experiments_NGN/dump_gaussian/project3/statistics_01.txt b/experiments_NGN/dump_gaussian/project3/statistics_01.txt
@@ -1,21 +1,21 @@
-Epoch [0 / 0]	TRAIN LOSS: 9.9374197e-13 || TEST LOSS: 9.9374197e-13
+Epoch [0 / 0]	TRAIN LOSS: 5.6184621e-15 || TEST LOSS: 5.6184621e-15
 #======================#
 TRAIN STATS
 R² score:             1.0
-MSE (mean SQR error): 9.9374197e-13
-RMSE (Root MSE):      9.9686607e-7
-MAE (mean ABS error): 6.7875755e-7
-maxAE (max ABS error) 3.7766936e-6
+MSE (mean SQR error): 5.6184621e-15
+RMSE (Root MSE):      7.4956402e-8
+MAE (mean ABS error): 2.3870774e-8
+maxAE (max ABS error) 3.397996e-7
 Lipschitz bound:      1.0
 
 #======================#
 #======================#
 TEST  STATS
 R² score:             1.0
-MSE (mean SQR error): 9.9374197e-13
-RMSE (Root MSE):      9.9686607e-7
-MAE (mean ABS error): 6.7875755e-7
-maxAE (max ABS error) 3.7766936e-6
+MSE (mean SQR error): 5.6184621e-15
+RMSE (Root MSE):      7.4956402e-8
+MAE (mean ABS error): 2.3870774e-8
+maxAE (max ABS error) 3.397996e-7
 Lipschitz bound:      1.0
 
 #======================#
diff --git a/experiments_NGN/dump_gaussian/project3/statistics_02.txt b/experiments_NGN/dump_gaussian/project3/statistics_02.txt
@@ -1,21 +1,21 @@
-Epoch [0 / 0]	TRAIN LOSS: 3.5519407e-21 || TEST LOSS: 3.5519407e-21
+Epoch [0 / 0]	TRAIN LOSS: 5.5139156e-32 || TEST LOSS: 5.5139156e-32
 #======================#
 TRAIN STATS
 R² score:             1.0
-MSE (mean SQR error): 3.5519407e-21
-RMSE (Root MSE):      5.959816e-11
-MAE (mean ABS error): 3.4676842e-11
-maxAE (max ABS error) 2.3533642e-10
+MSE (mean SQR error): 5.5139156e-32
+RMSE (Root MSE):      2.3481728000000003e-16
+MAE (mean ABS error): 8.5861566e-17
+maxAE (max ABS error) 1.110223e-15
 Lipschitz bound:      1.0
 
 #======================#
 #======================#
 TEST  STATS
 R² score:             1.0
-MSE (mean SQR error): 3.5519407e-21
-RMSE (Root MSE):      5.959816e-11
-MAE (mean ABS error): 3.4676842e-11
-maxAE (max ABS error) 2.3533642e-10
+MSE (mean SQR error): 5.5139156e-32
+RMSE (Root MSE):      2.3481728000000003e-16
+MAE (mean ABS error): 8.5861566e-17
+maxAE (max ABS error) 1.110223e-15
 Lipschitz bound:      1.0
 
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