fixed bug n fit motorsensory adaptation

planart/motorsensory/_adaptation.py

@@ -116,31 +116,34 @@ def adaptation_somatosensory_perturbation_experiment(config, perturbations,
             ).squeeze()
         produced_articulatory_matrix[n, :] = x0
         predicted_articulatory_matrix[n, :] = x0_sol
-        # contours = parametric.articulatory_to_contour(x0_sol)
-        # contours_perturbed = contours.copy()
-        # lx, ly, ux, uy = contours[0].contours
-        # distance = (lx[-3] - 10)
-        # lx[-3:] += distance * p
-        # ux[-3:] += distance * p
-        # distance = (lx[-1] - lx[-2])
-        # lx[-1:] += distance * p
-        # ux[-1:] += distance * p
-        # contours_perturbed[0].contours = np.array([lx, ly, ux, uy])
-        # formants = parametric.contour_to_formant(contours_perturbed,
-        #                                          min_area=5e-6).squeeze()
-        x0_perturbed = [x for x in x0]
-        x0_perturbed[5] = (1+p) * (x0_perturbed[5] + 3) - 3
-        formants = parametric.articulatory_to_formant(x0_perturbed).squeeze()
-        produced_acoustics_matrix[n, :] = formants
-        auditory_feedback_matrix[n, :] = formants
         
-        # received_somatosensory_feedback = parametric.contour_to_task(
-        #     contours_perturbed, 
-        #     get_c()
+        contours = parametric.articulatory_to_contour(x0_sol)
+        contours_perturbed = contours.copy()
+        lx, ly, ux, uy = contours[0].contours
+        distance = (lx[-3] - 10)
+        lx[-3:] += distance * p
+        ux[-3:] += distance * p
+        distance = (lx[-1] - lx[-2])
+        lx[-1:] += distance * p
+        ux[-1:] += distance * p
+        contours_perturbed[0].contours = np.array([lx, ly, ux, uy])
+        formants = parametric.contour_to_formant(contours_perturbed,
+                                                 min_area=5e-6).squeeze()
+        received_somatosensory_feedback = parametric.contour_to_task(
+            contours_perturbed, 
+            get_c()
+            )        
+        
+        # x0_perturbed = [x for x in x0]
+        # x0_perturbed[5] = (1+p) * (x0_perturbed[5] + 3) - 3
+        # formants = parametric.articulatory_to_formant(x0_perturbed).squeeze()
+        # produced_acoustics_matrix[n, :] = formants
+        # auditory_feedback_matrix[n, :] = formants
+        # received_somatosensory_feedback = parametric.articulatory_to_task(
+        #     x0_perturbed
         #     )
-        received_somatosensory_feedback = parametric.articulatory_to_task(
-            x0_perturbed
-            )
+               
+        
         somatosensory_feedback_matrix[n, :] = received_somatosensory_feedback.squeeze()
                 
         predicted_acoustics_matrix[n, :] = sensory_prediction(

planart/motorsensory/_fit.py

@@ -119,7 +119,7 @@ def annealing_simple_xt3c_inversion(config, true_formants, min_x,
     rem = config['adaptation optimization']['patience'] * 1
 
     local_cost = objective(x0, config, true_formants, 
-                           min_x, perturbations, vowel)
+                           min_x, perturbations, vowel, initializer)
     local_solution = [x for x in x0]
 
     col_len = print_first_line(config['adaptation optimization']['optimizer'])