Aggiorna 'code/matlab/H5_raster.m'

code/matlab/H5_raster.m

@@ -1,127 +1,127 @@
-% The script plots the neural and behavioural data contained in a .h5 file of the Diomedi et al., 2023 dataset
-% in the form of a raster plot
-clear all; clc; close all;
-currentFolder = pwd;
-parentFolder = fileparts(fileparts(currentFolder));
-[filename,path_folder_data] = uigetfile('*.h5','Select a h5 dataset',[parentFolder '\data']);
-
-str = '/DATA/unit_01'; %it can be either unitXX, unitXX/conditionYY or unitXX/conditionYY/trialZZ
-
-[spikes, markers, all_strings] = get_all_data_from_level_h5([path_folder_data filename],str); %extract data
-
-str2readmk = ['/DATA/unit_01/condition_01/trial_01/events_markers']; 
-
-marker_labels = h5readatt([path_folder_data filename],str2readmk,'Marker labels'); %extract names of marker events
-
-figure
-hold on
-for count = 1:length(spikes)
-    clmap = jet(length(markers{count}));
-    scatter(spikes{count},count,'|','k')
-    sz = 30;
-    c = linspace(1,10,length(markers{count}));
-    if count == length(spikes)
-        for mk = 1:size(markers{count},2)
-            tmp = scatter(markers{count}(mk),1*count,sz,clmap(mk,:),'filled','DisplayName',marker_labels{mk});
-            dots(mk) = tmp;
-        end
-    end
-    scatter(markers{count},ones(size(markers{count}))*count,sz,clmap,'filled')
-end
-hold off
-ylim([0 count+1])
-xlabel('Time (ms)')
-ylabel('Trial #')
-legend(dots,marker_labels)
-colormap(jet)
-title('Raster Plot')
-
-function [spikes, markers, all_strings] = get_all_data_from_level_h5(filename,str)
-
-% The function extracts the spikes and the markers from a .h5 dataset
-
-% INPUT: 
-%     filename = a string that identify the h5 file from which extract data
-%     str = the group from which extract the data. The function
-%     automatically extracts every dataset of the group
-
-% OUTPUT:
-%     spikes = contains the extracted spike timing for each dataset
-%     markers = contains the extracted marker timing for each dataset
-%     all_strings = keeps track of the datasets extracted
-
-% Francesco E. Vaccari 10/2022 
-
-
-if ~isempty(strfind(str,'trial'))
-    lev = 4;
-elseif ~isempty(strfind(str,'condition'))
-    lev = 3;
-elseif ~isempty(strfind(str,'unit'))
-    lev = 2;
-elseif ~isempty(strfind(str,'DATA'))
-    lev = 1;
-else
-    disp('str is not correct')
-end
-
-info = h5info(filename,str);
-
-count = 1;
-
-switch lev
-    case 4
-        spikes{count} = h5read(filename,[str '/spike_trains']);
-        markers{count} = h5read(filename,[str '/events_markers']);
-
-    case 3
-        for trial = 1:length(info.Groups)
-            str_trial = [str '/trial_' sprintf('%02d',trial)];
-            spikes{count} = h5read(filename,[str_trial '/spike_trains']);
-            markers{count} = h5read(filename,[str_trial '/events_markers']);
-            all_strings{count} = str_trial;
-            count = count+1;
-        end
-
-    case 2
-        str2check = str; %check how many conditions for this unit
-        info2check = h5info(filename,str2check);
-        num_cond = length(info2check.Groups);
-        for cond = 1:length(info.Groups)
-            str2check = [str '/condition_' sprintf('%02d',cond)]; %check how many trials for this unit / condition
-            info2check = h5info(filename,str2check);
-            num_trial = length(info2check.Groups);
-            for trial = 1:length(info.Groups(cond).Groups)
-                str_trial = [str '/condition_' sprintf('%02d',cond) '/trial_' sprintf('%02d',trial)];
-                spikes{count} = h5read(filename,[str_trial '/spike_trains']);
-                markers{count} = h5read(filename,[str_trial '/events_markers']);
-                all_strings{count} = str_trial;
-                count = count+1;
-            end
-        end
-
-    case 1
-        for neu = 1:length(info.Groups)
-            str2check = [str '/unit_' sprintf('%02d',neu)]; %check how many conditions for this unit 
-            info2check = h5info(filename,str2check);
-            num_cond = length(info2check.Groups);
-            for cond = 1:num_cond
-                str2check = [str '/unit_' sprintf('%02d',neu) '/condition_' sprintf('%02d',cond)]; %check how many trials for this unit / condition
-                info2check = h5info(filename,str2check);
-                num_trial = length(info2check.Groups);
-                for trial = 1:num_trial
-                    str_trial = [str '/unit_' sprintf('%02d',neu) '/condition_' sprintf('%02d',cond) '/trial_' sprintf('%02d',trial)];
-                    spikes{count} = h5read(filename,[str_trial '/spike_trains']);
-                    markers{count} = h5read(filename,[str_trial '/events_markers']);
-                    all_strings{count} = str_trial;
-                    count = count+1;
-                end
-            end
-        end
-
-end
-
-spikes = spikes'; markers = markers'; all_strings = all_strings';
-
-
+% The script plots the neural and behavioural data contained in a .h5 file of the Diomedi et al., 2023 dataset
+% in the form of a raster plot
+clear all; clc; close all;
+currentFolder = pwd;
+parentFolder = fileparts(fileparts(currentFolder));
+[filename,path_folder_data] = uigetfile('*.h5','Select a h5 dataset',[parentFolder '\data']);
+
+str = '/DATA/unit_01'; %it can be either unitXX, unitXX/conditionYY or unitXX/conditionYY/trialZZ
+
+[spikes, markers, all_strings] = get_all_data_from_level_h5([path_folder_data filename],str); %extract data
+
+str2readmk = ['/DATA/unit_01/condition_01/trial_01/event_markers']; 
+
+marker_labels = h5readatt([path_folder_data filename],str2readmk,'Marker labels'); %extract names of event markers
+
+figure
+hold on
+for count = 1:length(spikes)
+    clmap = jet(length(markers{count}));
+    scatter(spikes{count},count,'|','k')
+    sz = 30;
+    c = linspace(1,10,length(markers{count}));
+    if count == length(spikes)
+        for mk = 1:size(markers{count},2)
+            tmp = scatter(markers{count}(mk),1*count,sz,clmap(mk,:),'filled','DisplayName',marker_labels{mk});
+            dots(mk) = tmp;
+        end
+    end
+    scatter(markers{count},ones(size(markers{count}))*count,sz,clmap,'filled')
+end
+hold off
+ylim([0 count+1])
+xlabel('Time (ms)')
+ylabel('Trial #')
+legend(dots,marker_labels)
+colormap(jet)
+title('Raster Plot')
+
+function [spikes, markers, all_strings] = get_all_data_from_level_h5(filename,str)
+
+% The function extracts the spikes and the markers from a .h5 dataset
+
+% INPUT: 
+%     filename = a string that identify the h5 file from which extract data
+%     str = the group from which extract the data. The function
+%     automatically extracts every dataset of the group
+
+% OUTPUT:
+%     spikes = contains the extracted spike timing for each dataset
+%     markers = contains the extracted marker timing for each dataset
+%     all_strings = keeps track of the datasets extracted
+
+% Francesco E. Vaccari 10/2022 
+
+
+if ~isempty(strfind(str,'trial'))
+    lev = 4;
+elseif ~isempty(strfind(str,'condition'))
+    lev = 3;
+elseif ~isempty(strfind(str,'unit'))
+    lev = 2;
+elseif ~isempty(strfind(str,'DATA'))
+    lev = 1;
+else
+    disp('str is not correct')
+end
+
+info = h5info(filename,str);
+
+count = 1;
+
+switch lev
+    case 4
+        spikes{count} = h5read(filename,[str '/spike_trains']);
+        markers{count} = h5read(filename,[str '/event_markers']);
+
+    case 3
+        for trial = 1:length(info.Groups)
+            str_trial = [str '/trial_' sprintf('%02d',trial)];
+            spikes{count} = h5read(filename,[str_trial '/spike_trains']);
+            markers{count} = h5read(filename,[str_trial '/event_markers']);
+            all_strings{count} = str_trial;
+            count = count+1;
+        end
+
+    case 2
+        str2check = str; %check how many conditions for this unit
+        info2check = h5info(filename,str2check);
+        num_cond = length(info2check.Groups);
+        for cond = 1:length(info.Groups)
+            str2check = [str '/condition_' sprintf('%02d',cond)]; %check how many trials for this unit / condition
+            info2check = h5info(filename,str2check);
+            num_trial = length(info2check.Groups);
+            for trial = 1:length(info.Groups(cond).Groups)
+                str_trial = [str '/condition_' sprintf('%02d',cond) '/trial_' sprintf('%02d',trial)];
+                spikes{count} = h5read(filename,[str_trial '/spike_trains']);
+                markers{count} = h5read(filename,[str_trial '/event_markers']);
+                all_strings{count} = str_trial;
+                count = count+1;
+            end
+        end
+
+    case 1
+        for neu = 1:length(info.Groups)
+            str2check = [str '/unit_' sprintf('%02d',neu)]; %check how many conditions for this unit 
+            info2check = h5info(filename,str2check);
+            num_cond = length(info2check.Groups);
+            for cond = 1:num_cond
+                str2check = [str '/unit_' sprintf('%02d',neu) '/condition_' sprintf('%02d',cond)]; %check how many trials for this unit / condition
+                info2check = h5info(filename,str2check);
+                num_trial = length(info2check.Groups);
+                for trial = 1:num_trial
+                    str_trial = [str '/unit_' sprintf('%02d',neu) '/condition_' sprintf('%02d',cond) '/trial_' sprintf('%02d',trial)];
+                    spikes{count} = h5read(filename,[str_trial '/spike_trains']);
+                    markers{count} = h5read(filename,[str_trial '/event_markers']);
+                    all_strings{count} = str_trial;
+                    count = count+1;
+                end
+            end
+        end
+
+end
+
+spikes = spikes'; markers = markers'; all_strings = all_strings';
+
+
 end