tutorial update

notebooks/tutorials/tutorial_molecule.pqr

@@ -0,0 +1,3 @@
+ATOM      1  CH3 MEOH    1      0.0190  0.0000   0.6556  0.2700  1.8875
+ATOM      2  O   MEOH    1     -0.1197  0.0000  -0.7372 -0.7000  1.5350
+ATOM      3  H   MEOH    1      0.7370  0.0000  -1.1390  0.4300  0.2000

notebooks/tutorials/tutorial.yaml → notebooks/tutorials/tutorial_parameters.yaml

@@ -1,14 +1,17 @@
 # Simulation settings
 
+pinns_method: DCM
+
 # Equation to solve
-equation: standard
+equation: regularized_scheme_2
 
 # PBE model
 pbe_model: linear
+phi_units: qe_eps0_angs
 
 # Domain properties
 domain_properties:
-    molecule: methanol
+    molecule: tutorial_molecule
     epsilon_1: 1
     epsilon_2: 80
     kappa: 0.125
@@ -20,17 +23,19 @@ mesh_properties:
     vol_max_exterior: 2.5
     density_mol: 1.5
     density_border: 3
-    dx_experimental: 2
-    N_pq: 100
-    G_sigma: 0.04
     mesh_generator: msms
-    dR_exterior: 3
+    dR_exterior: 4
+    center_pqr: false
+
 
 # Sampling method
 sample_method: random_sample
 
+# Boundary condition
+bc_enforcement: soft
+
 # Frequency of solvation energy calculation
-G_solve_iter: 4
+G_solve_iter: 1
 
 # Losses to add, and initial weights
 losses:
@@ -39,9 +44,6 @@ losses:
     - D2
     - Iu
     - Id
-    - K2
-weights:
-    E2: 1e-10
 
 # Weights adapting algorithm inputs
 adapt_weights: true
@@ -50,31 +52,33 @@ adapt_w_method: gradients
 alpha_w: 0.7
 
 # Architecture
-network: xpinn
+num_networks: 2
 
 hyperparameters_in:
     input_shape: [null, 3]
-    num_hidden_layers: 2
-    num_neurons_per_layer: 15
+    num_hidden_layers: 4
+    num_neurons_per_layer: 200
     output_dim: 1
     activation: tanh
-    adaptative_activation: true
+    adaptive_activation: true
     architecture_Net: FCNN
     fourier_features: true
-    num_fourier_features: 256
+    weight_factorization: false
+    scale_input: true
+    scale_output: true
 
 hyperparameters_out:
     input_shape: [null, 3]
-    num_hidden_layers: 2
-    num_neurons_per_layer: 15
+    num_hidden_layers: 4
+    num_neurons_per_layer: 200
     output_dim: 1
     activation: tanh
-    adaptative_activation: true
+    adaptive_activation: true
     architecture_Net: FCNN
     fourier_features: true
-
-# Scale charges
-scale_NN_q: true
+    weight_factorization: false
+    scale_input: true
+    scale_output: true
 
 # Optimizer properties
 optimizer: Adam
@@ -84,7 +88,16 @@ lr:
     decay_steps: 2000
     decay_rate: 0.9
     staircase: true
+
+optimizer2: L-BFGS-B
 
 # Solve parameters
-N_iters: 150
-iters_save_model: 5000
+N_iters: 1000
+N_steps_2: 0
+
+
+iters_save_model: 0
+
+partition_simulation: false
+num_iters_per_step: 5000
+total_N_iters: 20000