update corrections and network

.gitignore

@@ -0,0 +1,2 @@
+*.ipynb_checkpoints*
+__pycache__

.ipynb_checkpoints/app-checkpoint.py

@@ -31,7 +31,7 @@ if raq_ra is not None and fkt is not None and fkv is not None:
     
     ### calculates temperature profile ###
     x_in = get_input(r_list, t_list, v_list, y_prof)
-    y_pred_nn_pointwise = get_profile(x_in, mlp, num_sims=len(r_list), num_points=num_points) 
+    y_pred_nn_pointwise = get_profile(x_in, mlp, num_sims=len(r_list), prof_points=num_points) 
     ### calculates temperature profile ###
     
     ### writes out temperature profile ###

.ipynb_checkpoints/calculate_profiles-checkpoint.py

@@ -7,7 +7,7 @@ write_file   = True
 plot_profile = True
 #### Define outputs ####
 
-with open('numpy_networks/mlp_[128, 128, 128, 128].pkl', 'rb') as file: 
+with open('numpy_networks/mlp_[128, 128, 128, 128, 128].pkl', 'rb') as file: 
     mlp = pickle.load(file) 
 
 f_nn = "my_simulation_parameters.txt"    

.ipynb_checkpoints/utils-checkpoint.py

@@ -59,10 +59,11 @@ def get_profile(inp, mlp, num_sims=1, correction=True, prof_points=128):
             res.append(y_pred)
                 
     y_pred = y_pred.reshape(num_sims, -1)
+    
+    y_pred[:,0]  = 1.
+    y_pred[:,-1] = 0.
 
     if correction:
-        y_pred[:,0]  = 1.
-        y_pred[:,-1] = 0.
         inp = inp.reshape(num_sims, -1, inp.shape[-1])
     
         for sim_ind in range(num_sims):
@@ -70,4 +71,9 @@ def get_profile(inp, mlp, num_sims=1, correction=True, prof_points=128):
             slope = (0 - y_pred[sim_ind,inds[0]])/(0 - inp[sim_ind,inds[0],3:4])
             y_pred[sim_ind,inds] = slope*inp[sim_ind,inds,3]  
 
+            inds = np.where(inp[sim_ind,:,3] > 0.985)[0]
+            x_old = [inp[sim_ind,inds[-1],3], 1]
+            y_old = [y_pred[sim_ind,inds[-1]], 1]
+            y_pred[sim_ind,inds] = np.interp(inp[sim_ind,inds,3:4], x_old, y_old).flatten()
+
     return y_pred

calculate_profiles.py

@@ -7,7 +7,7 @@ write_file   = True
 plot_profile = True
 #### Define outputs ####
 
-with open('numpy_networks/mlp_[128, 128, 128, 128].pkl', 'rb') as file: 
+with open('numpy_networks/mlp_[128, 128, 128, 128, 128].pkl', 'rb') as file: 
     mlp = pickle.load(file) 
 
 f_nn = "my_simulation_parameters.txt"    

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utils.py

@@ -59,10 +59,11 @@ def get_profile(inp, mlp, num_sims=1, correction=True, prof_points=128):
             res.append(y_pred)
                 
     y_pred = y_pred.reshape(num_sims, -1)
+    
+    y_pred[:,0]  = 1.
+    y_pred[:,-1] = 0.
 
     if correction:
-        y_pred[:,0]  = 1.
-        y_pred[:,-1] = 0.
         inp = inp.reshape(num_sims, -1, inp.shape[-1])
     
         for sim_ind in range(num_sims):
@@ -70,4 +71,9 @@ def get_profile(inp, mlp, num_sims=1, correction=True, prof_points=128):
             slope = (0 - y_pred[sim_ind,inds[0]])/(0 - inp[sim_ind,inds[0],3:4])
             y_pred[sim_ind,inds] = slope*inp[sim_ind,inds,3]  
 
+            inds = np.where(inp[sim_ind,:,3] > 0.985)[0]
+            x_old = [inp[sim_ind,inds[-1],3], 1]
+            y_old = [y_pred[sim_ind,inds[-1]], 1]
+            y_pred[sim_ind,inds] = np.interp(inp[sim_ind,inds,3:4], x_old, y_old).flatten()
+
     return y_pred