update

app_utils.py

@@ -47,6 +47,111 @@ def read_montage_data(loc_file):
 		}
 	return tpl_montage, in_montage, tpl_dict, in_dict
 
+def match_names(stage1_info):
+    # read the location file
+	loc_file = stage1_info["fileNames"]["inputLocation"]
+	tpl_montage, in_montage, tpl_dict, in_dict = read_montage_data(loc_file)
+	tpl_names = tpl_montage.ch_names
+	in_names = in_montage.ch_names
+	old_idx = [[None]]*30 # store the indices of the in_channels in the order of tpl_channels
+	orig_flags = [False]*30
+	
+	alias_dict = {
+		'T3': 'T7',
+		'T4': 'T8',
+		'T5': 'P7',
+		'T6': 'P8'
+	}
+	for i, name in enumerate(tpl_names):
+		if name in alias_dict and alias_dict[name] in in_dict:
+			tpl_montage.rename_channels({name: alias_dict[name]})
+			tpl_dict[alias_dict[name]] = tpl_dict.pop(name)
+			name = alias_dict[name]
+			
+		if name in in_dict:
+			old_idx[i] = [in_dict[name]["index"]]
+			orig_flags[i] = True
+			tpl_dict[name]["matched"] = True
+			in_dict[name]["assigned"] = True
+	
+	# update the names
+	tpl_names = tpl_montage.ch_names
+	
+	stage1_info.update({
+	    "unassignedInputs" : get_unassigned_inputs(in_names, in_dict),
+	    "emptyTemplates" : get_empty_templates(tpl_names, tpl_dict),
+	    "mappingResult" : [
+		{
+			"index" : old_idx,
+			"isOriginalData" : orig_flags
+		}
+	    ]
+	})
+	channel_info = {
+		"templateNames" : tpl_names,
+		"inputNames" : in_names,
+	    "templateDict" : tpl_dict,
+	    "inputDict" : in_dict
+	}
+	return stage1_info, channel_info, tpl_montage, in_montage
+
+def align_coords(channel_info, tpl_montage, in_montage):
+	tpl_names = channel_info["templateNames"]
+	in_names = channel_info["inputNames"]
+	tpl_dict = channel_info["templateDict"]
+	in_dict = channel_info["inputDict"]
+	matched_names = get_matched(tpl_names, tpl_dict)
+	
+	# 2D alignment (for visualization purposes)
+	fig = [tpl_montage.plot(), in_montage.plot()]
+	ax = [fig[0].axes[0], fig[1].axes[0]]
+	
+	# extract the displayed 2D coordinates
+	all_tpl = ax[0].collections[0].get_offsets().data
+	all_in= ax[1].collections[0].get_offsets().data
+	matched_tpl = np.array([all_tpl[tpl_dict[name]["index"]] for name in matched_names])
+	matched_in = np.array([all_in[in_dict[name]["index"]] for name in matched_names])
+	plt.close('all')
+	
+	# apply TPS to transform in_channels to align with tpl_channels positions
+	rbf_x = Rbf(matched_in[:,0], matched_in[:,1], matched_tpl[:,0], function='thin_plate')
+	rbf_y = Rbf(matched_in[:,0], matched_in[:,1], matched_tpl[:,1], function='thin_plate')
+	
+	# apply the transformation to all in_channels
+	transformed_in_x = rbf_x(all_in[:,0], all_in[:,1])
+	transformed_in_y = rbf_y(all_in[:,0], all_in[:,1])
+	transformed_in = np.vstack((transformed_in_x, transformed_in_y)).T
+	
+	for i, name in enumerate(tpl_names):
+		tpl_dict[name]["coord_2d"] = all_tpl[i]
+	for i, name in enumerate(in_names):
+		in_dict[name]["coord_2d"] = transformed_in[i].tolist()
+	
+	
+	# 3D alignment
+	all_tpl = np.array([tpl_dict[name]["coord_3d"].tolist() for name in tpl_names])
+	all_in = np.array([in_dict[name]["coord_3d"].tolist() for name in in_names])
+	matched_tpl = np.array([all_tpl[tpl_dict[name]["index"]] for name in matched_names])
+	matched_in = np.array([all_in[in_dict[name]["index"]] for name in matched_names])
+	
+	rbf_x = Rbf(matched_in[:,0], matched_in[:,1], matched_in[:,2], matched_tpl[:,0], function='thin_plate')
+	rbf_y = Rbf(matched_in[:,0], matched_in[:,1], matched_in[:,2], matched_tpl[:,1], function='thin_plate')
+	rbf_z = Rbf(matched_in[:,0], matched_in[:,1], matched_in[:,2], matched_tpl[:,2], function='thin_plate')
+	
+	transformed_in_x = rbf_x(all_in[:,0], all_in[:,1], all_in[:,2])
+	transformed_in_y = rbf_y(all_in[:,0], all_in[:,1], all_in[:,2])
+	transformed_in_z = rbf_z(all_in[:,0], all_in[:,1], all_in[:,2])
+	transformed_in = np.vstack((transformed_in_x, transformed_in_y, transformed_in_z)).T
+	
+	for i, name in enumerate(in_names):
+		in_dict[name]["coord_3d"] = transformed_in[i].tolist()
+	
+	channel_info.update({
+	    "templateDict" : tpl_dict,
+	    "inputDict" : in_dict
+	})
+	return channel_info
+
 def save_figures(channel_info, tpl_montage, filename1, filename2):
 	tpl_names = channel_info["templateNames"]
 	in_names = channel_info["inputNames"]
@@ -117,63 +222,6 @@ def save_figures(channel_info, tpl_montage, filename1, filename2):
 	})
 	return channel_info
 
-def align_coords(channel_info, tpl_montage, in_montage):
-	tpl_names = channel_info["templateNames"]
-	in_names = channel_info["inputNames"]
-	tpl_dict = channel_info["templateDict"]
-	in_dict = channel_info["inputDict"]
-	matched_names = get_matched(tpl_names, tpl_dict)
-	
-	# 2D alignment (for visualization purposes)
-	fig = [tpl_montage.plot(), in_montage.plot()]
-	ax = [fig[0].axes[0], fig[1].axes[0]]
-	
-	# extract the displayed 2D coordinates
-	all_tpl = ax[0].collections[0].get_offsets().data
-	all_in= ax[1].collections[0].get_offsets().data
-	matched_tpl = np.array([all_tpl[tpl_dict[name]["index"]] for name in matched_names])
-	matched_in = np.array([all_in[in_dict[name]["index"]] for name in matched_names])
-	plt.close('all')
-	
-	# apply TPS to transform in_channels to align with tpl_channels positions
-	rbf_x = Rbf(matched_in[:,0], matched_in[:,1], matched_tpl[:,0], function='thin_plate')
-	rbf_y = Rbf(matched_in[:,0], matched_in[:,1], matched_tpl[:,1], function='thin_plate')
-	
-	# apply the transformation to all in_channels
-	transformed_in_x = rbf_x(all_in[:,0], all_in[:,1])
-	transformed_in_y = rbf_y(all_in[:,0], all_in[:,1])
-	transformed_in = np.vstack((transformed_in_x, transformed_in_y)).T
-	
-	for i, name in enumerate(tpl_names):
-		tpl_dict[name]["coord_2d"] = all_tpl[i]
-	for i, name in enumerate(in_names):
-		in_dict[name]["coord_2d"] = transformed_in[i].tolist()
-	
-	
-	# 3D alignment
-	all_tpl = np.array([tpl_dict[name]["coord_3d"].tolist() for name in tpl_names])
-	all_in = np.array([in_dict[name]["coord_3d"].tolist() for name in in_names])
-	matched_tpl = np.array([all_tpl[tpl_dict[name]["index"]] for name in matched_names])
-	matched_in = np.array([all_in[in_dict[name]["index"]] for name in matched_names])
-	
-	rbf_x = Rbf(matched_in[:,0], matched_in[:,1], matched_in[:,2], matched_tpl[:,0], function='thin_plate')
-	rbf_y = Rbf(matched_in[:,0], matched_in[:,1], matched_in[:,2], matched_tpl[:,1], function='thin_plate')
-	rbf_z = Rbf(matched_in[:,0], matched_in[:,1], matched_in[:,2], matched_tpl[:,2], function='thin_plate')
-	
-	transformed_in_x = rbf_x(all_in[:,0], all_in[:,1], all_in[:,2])
-	transformed_in_y = rbf_y(all_in[:,0], all_in[:,1], all_in[:,2])
-	transformed_in_z = rbf_z(all_in[:,0], all_in[:,1], all_in[:,2])
-	transformed_in = np.vstack((transformed_in_x, transformed_in_y, transformed_in_z)).T
-	
-	for i, name in enumerate(in_names):
-		in_dict[name]["coord_3d"] = transformed_in[i].tolist()
-	
-	channel_info.update({
-	    "templateDict" : tpl_dict,
-	    "inputDict" : in_dict
-	})
-	return channel_info
-
 def find_neighbors(channel_info, empty_tpl_names, old_idx):
 	in_names = channel_info["inputNames"]
 	tpl_dict = channel_info["templateDict"]
@@ -193,54 +241,6 @@ def find_neighbors(channel_info, empty_tpl_names, old_idx):
     
 	return old_idx
 
-def match_names(stage1_info):
-    # read the location file
-	loc_file = stage1_info["fileNames"]["inputLocation"]
-	tpl_montage, in_montage, tpl_dict, in_dict = read_montage_data(loc_file)
-	tpl_names = tpl_montage.ch_names
-	in_names = in_montage.ch_names
-	old_idx = [[None]]*30 # store the indices of the in_channels in the order of tpl_channels
-	orig_flags = [False]*30
-	
-	alias_dict = {
-		'T3': 'T7',
-		'T4': 'T8',
-		'T5': 'P7',
-		'T6': 'P8'
-	}
-	for i, name in enumerate(tpl_names):
-		if name in alias_dict and alias_dict[name] in in_dict:
-			tpl_montage.rename_channels({name: alias_dict[name]})
-			tpl_dict[alias_dict[name]] = tpl_dict.pop(name)
-			name = alias_dict[name]
-			
-		if name in in_dict:
-			old_idx[i] = [in_dict[name]["index"]]
-			orig_flags[i] = True
-			tpl_dict[name]["matched"] = True
-			in_dict[name]["assigned"] = True
-	
-	# update the names
-	tpl_names = tpl_montage.ch_names
-	
-	stage1_info.update({
-	    "unassignedInputs" : get_unassigned_inputs(in_names, in_dict),
-	    "emptyTemplates" : get_empty_templates(tpl_names, tpl_dict),
-	    "mappingResult" : [
-		{
-			"index" : old_idx,
-			"isOriginalData" : orig_flags
-		}
-	    ]
-	})
-	channel_info = {
-		"templateNames" : tpl_names,
-		"inputNames" : in_names,
-	    "templateDict" : tpl_dict,
-	    "inputDict" : in_dict
-	}
-	return stage1_info, channel_info, tpl_montage, in_montage
-
 def optimal_mapping(channel_info):
 	tpl_names = channel_info["templateNames"]
 	in_names = channel_info["inputNames"]