add filesep

code_MATLAB/Main_Load_NIX_Data.m

@@ -1,216 +1,216 @@
-%% Close all figures, clear variables and command window
-close all
-clear
-clc
-
-%% Directory of the repository and the NIX library
-strMainPath = 'Human_Amygdala_MUA_sEEG_FearVideo\';
-strNIXLibraryPath = 'nix-mx_Win64_1.4.1\';
-
-%% Add necessary folders to the MATLAB path
-addpath([strMainPath,'\code_MATLAB\'])
-addpath(genpath(strNIXLibraryPath))
-
-warning('strMainPath should be the full path of the folder Human_Amygdala_MUA_sEEG_FearVideo')
-warning('strNIXLibraryPath should be the full path of the NIX library ''nix-mx_Win64_1.4.1''')
-
-%% NIX data files
-strNIXFileNames = dir([strMainPath,'\data_NIX\*.h5']);
-strNIXFileNames = {strNIXFileNames.name}';
-
-assert(~isempty(strNIXFileNames),'strMainPath should be the full path of the folder Human_Amygdala_MUA_sEEG_FearVideo')
-
-%% Select NIX file to open
-nFile = 1;
-
-%% Open NIX file
-strFilePath = [strMainPath,'\data_NIX\',strNIXFileNames{nFile}];
-try
-    f = nix.File(strFilePath,nix.FileMode.ReadOnly);
-catch s
-    if(strcmpi(s.message,'Undefined variable "nix" or class "nix.FileMode.ReadOnly".'))
-        error('strNIXLibraryPath should be the full path of the NIX library ''nix-mx_Win64_1.4.1''')
-    else
-        error(s.message)
-    end
-end
-
-%% Read metadata
-% Display names of all sections
-cellfun(@(x) disp(x.name),f.sections)
-
-%% General information
-sectionGeneral = f.openSection('General');
-% Properties
-cellfun(@(x) disp(x.name),sectionGeneral.properties)
-% Institution
-fprintf(['Institution: ',sectionGeneral.openProperty('Institution').values{1}.value,'\n'])
-% Recording location
-fprintf(['Recording location: ',sectionGeneral.openProperty('Recording location').values{1}.value,'\n'])
-% Sections
-cellfun(@(x) disp(x.name),sectionGeneral.sections)
-% Publications
-sectionPublications = sectionGeneral.openSection('Related publications');
-cellfun(@(x) disp(x.name),sectionPublications.properties)
-fprintf(['Publication name: ',sectionPublications.openProperty('Publication name').values{1}.value,'\n'])
-fprintf(['Publication DOI: ',sectionPublications.openProperty('Publication DOI').values{1}.value,'\n'])
-% Recording setup
-sectionRecordingSetup = sectionGeneral.openSection('Recording setup');
-cellfun(@(x) disp(x.name),sectionRecordingSetup.properties)
-fprintf(['Recording setup iEEG: ',sectionRecordingSetup.openProperty('Recording setup iEEG').values{1}.value,'\n'])
-
-%% Task information
-sectionTask = f.openSection('Task');
-% Properties
-cellfun(@(x) disp(x.name),sectionTask.properties)
-% Task characteristics
-fprintf(['Task name: ',sectionTask.openProperty('Task name').values{1}.value,'\n'])
-fprintf(['Task description: ',sectionTask.openProperty('Task description').values{1}.value,'\n'])
-fprintf(['Task URL: ',sectionTask.openProperty('Task URL').values{1}.value,'\n']) % TODO
-
-%% Subject information
-sectionSubject = f.openSection('Subject');
-% Properties
-cellfun(@(x) disp(x.name),sectionSubject.properties)
-% Subject characteristics
-fprintf(['Age: ',num2str(sectionSubject.openProperty('Age').values{1}.value),'\n'])
-fprintf(['Gender: ',sectionSubject.openProperty('Gender').values{1}.value,'\n']) % Sex?
-fprintf(['Pathology: ',sectionSubject.openProperty('Pathology').values{1}.value,'\n'])
-fprintf(['Depth electrodes: ',sectionSubject.openProperty('Depth electrodes').values{1}.value,'\n'])
-fprintf(['Electrodes in seizure onset zone (SOZ): ',sectionSubject.openProperty('Electrodes in seizure onset zone (SOZ)').values{1}.value,'\n'])
-
-%% Session information
-sectionSession = f.openSection('Session');
-% Properties
-cellfun(@(x) disp(x.name),sectionSession.properties)
-% Session characteristics
-fprintf(['Number of trials: ',num2str(sectionSession.openProperty('Number of trials').values{1}.value),'\n'])
-fprintf(['Trial duration: ',num2str(sectionSession.openProperty('Trial duration').values{1}.value),' ',sectionSession.openProperty('Trial duration').unit,'\n'])
-% Sections
-cellfun(@(x) disp(x.name),sectionSession.sections)
-
-%% Trial information
-sectionTrialProperties = sectionSession.openSection('Trial properties');
-% Sections
-cellfun(@(x) disp(x.name),sectionTrialProperties.sections)
-% Each section is for a single trial
-% Select trial
-nTrial = 1;
-sectionSingleTrial = sectionTrialProperties.sections{nTrial};
-
-%% Single trial
-% Properties
-cellfun(@(x) disp(x.name),sectionSingleTrial.properties)
-for nProperty = 1:length(sectionSingleTrial.properties)
-    switch sectionSingleTrial.properties{nProperty}.datatype
-        case {'double','logical'}
-            fprintf([sectionSingleTrial.properties{nProperty}.name,': ',num2str(sectionSingleTrial.properties{nProperty}.values{1}.value),'\n'])
-        otherwise
-            fprintf([sectionSingleTrial.properties{nProperty}.name,': ',sectionSingleTrial.properties{nProperty}.values{1}.value,'\n'])
-    end
-end
-
-%% Blocks
-cellfun(@(x) disp(x.name),f.blocks)
-block = f.blocks{1};
-
-%% Groups of data arrays, tags, multitags
-groups = block.groups;
-cellfun(@(x) disp(x.name),block.groups)
-
-%% Select trial
-nTrial = 1;
-
-%% iEEG data
-group_iEEG = block.openGroup('iEEG data');
-% Data array
-dataArray_iEEG = group_iEEG.dataArrays{nTrial};
-
-% Electrode labels
-striEEGLabels = dataArray_iEEG.dimensions{1}.labels;
-% Time axis
-tiEEG = (0:(double(dataArray_iEEG.dataExtent(2))-1))*dataArray_iEEG.dimensions{2}.samplingInterval+dataArray_iEEG.dimensions{2}.offset;
-% Read data
-data_iEEG = dataArray_iEEG.readAllData;
-
-% Plot trial data
-figure
-plot(tiEEG,data_iEEG)
-title(['iEEG data - Trial ',num2str(nTrial)])
-xlabel(['Time (',dataArray_iEEG.dimensions{2}.unit,')'])
-ylabel(['Voltage (',dataArray_iEEG.unit,')'])
-xlim([tiEEG(1),tiEEG(end)])
-legend(striEEGLabels)
-
-%% Trial events
-group_TrialEvents_iEEG = block.openGroup('Trial events single tags iEEG');
-
-%% Trial events for a single trial
-indTrialTags_iEEG = contains(cellfun(@(x) x.name,group_TrialEvents_iEEG.tags,'UniformOutput',0),['Trial_',num2str(nTrial,'%.2d')]);
-
-TrialEvents_iEEG = group_TrialEvents_iEEG.tags(indTrialTags_iEEG);
-
-cellfun(@(x) disp(x.name),TrialEvents_iEEG)
-
-%% Time of a single event
-nEvent = 1; % Condition
-fprintf(['Event name: ',TrialEvents_iEEG{nEvent}.name,'\n'])
-fprintf([sprintf('Time w.r.t. fixation: %.1f %s',TrialEvents_iEEG{nEvent}.position(2),TrialEvents_iEEG{nEvent}.units{1}),'\n'])
-fprintf([sprintf('Duration: %.1f %s',TrialEvents_iEEG{nEvent}.extent(2),TrialEvents_iEEG{nEvent}.units{1}),'\n'])
-
-%% Units
-group_SpikeTimes = block.openGroup('Spike times');
-
-%% Select unit and trial
-nUnit = 1;
-nTrial = 5;
-indUnitSpikeTimes = contains(cellfun(@(x) x.name,group_SpikeTimes.dataArrays,'UniformOutput',0),['Unit_',num2str(nUnit),'_'])&...
-    contains(cellfun(@(x) x.name,group_SpikeTimes.dataArrays,'UniformOutput',0),['Trial_',num2str(nTrial,'%.2d')]);
-
-dataArray_SpikeTimes = group_SpikeTimes.dataArrays{indUnitSpikeTimes};
-% Read data
-SpikeTimes = dataArray_SpikeTimes.readAllData;
-
-figure
-stem(dataArray_SpikeTimes.readAllData,ones(length(SpikeTimes),1))
-title(['Spike times - Unit ',num2str(nUnit),' - Trial ',num2str(nTrial)])
-xlabel(['Time (',dataArray_SpikeTimes.dimensions{1}.unit,')'])
-
-%% Multitag for the unit
-indMultiTagUnitSpikeTimes = contains(cellfun(@(x) x.name,block.multiTags,'UniformOutput',0),['Unit_',num2str(nUnit),'_'])&...
-    contains(cellfun(@(x) x.name,block.multiTags,'UniformOutput',0),['Trial_',num2str(nTrial,'%.2d')]);
-
-multiTag_SpikeTimes = block.multiTags{indMultiTagUnitSpikeTimes};
-
-%% Waveform for the unit
-dataArray_Waveform = multiTag_SpikeTimes.features{1}.openData;
-% Time axis
-tWaveform = (0:(double(dataArray_Waveform.dataExtent(2))-1))*dataArray_Waveform.dimensions{2}.samplingInterval+dataArray_Waveform.dimensions{2}.offset;
-% Read data
-waveform = dataArray_Waveform.readAllData;
-% Plot
-figure
-plot(tWaveform,waveform(1,:),'b')
-hold on
-plot(tWaveform,waveform(1,:)+waveform(2,:),'b--')
-plot(tWaveform,waveform(1,:)-waveform(2,:),'b--')
-title(['Waveform - Unit ',num2str(nUnit)])
-xlabel(['Time (',dataArray_Waveform.dimensions{2}.unit,')'])
-ylabel(['Voltage (',dataArray_Waveform.unit,')'])
-legend({'Mean','Std'})
-
-%% Source of the unit
-sourceUnit = dataArray_SpikeTimes.sources{1};
-% Electrode label
-sourceUnit.sources{1}.name
-% Anatomical location
-sourceUnit.sources{2}.name
-
-%% Use electrode map to get properties of the macroelectrode the unit is on
-groupiEEGElecrodes = block.openGroup('iEEG electrode information');
-
-nElectrode = find(strcmpi(cellfun(@(x) x.name,groupiEEGElecrodes.sources,'UniformOutput',0),sourceUnit.name));
-
-% MNI coordinates of the electrode
-groupiEEGElecrodes.multiTags{1}.retrieveFeatureData(nElectrode,'iEEG_Electrode_MNI_Coordinates')
-
+%% Close all figures, clear variables and command window
+close all
+clear
+clc
+
+%% Directory of the repository and the NIX library
+strMainPath = 'Human_Amygdala_MUA_sEEG_FearVideo';
+strNIXLibraryPath = 'nix-mx_Win64_1.4.1'; % or 'nix_mx_macOS_1.4.2_Matlab2020a'
+
+%% Add necessary folders to the MATLAB path
+addpath([strMainPath filesep 'code_MATLAB' filesep])
+addpath(genpath(strNIXLibraryPath))
+
+warning('strMainPath should be the full path of the folder Human_Amygdala_MUA_sEEG_FearVideo')
+warning('strNIXLibraryPath should be the full path of the NIX library ''nix-mx_Win64_1.4.1''')
+
+%% NIX data files
+strNIXFileNames = dir([strMainPath filesep 'data_NIX' filesep '*.h5']);
+strNIXFileNames = {strNIXFileNames.name}';
+
+assert(~isempty(strNIXFileNames),'strMainPath should be the full path of the folder Human_Amygdala_MUA_sEEG_FearVideo')
+
+%% Select NIX file to open
+nFile = 1;
+
+%% Open NIX file
+strFilePath = [strMainPath filesep 'data_NIX' filesep strNIXFileNames{nFile}];
+try
+    f = nix.File(strFilePath,nix.FileMode.ReadOnly);
+catch s
+    if(strcmpi(s.message,'Undefined variable "nix" or class "nix.FileMode.ReadOnly".'))
+        error('strNIXLibraryPath should be the full path of the NIX library ''nix-mx_Win64_1.4.1''')
+    else
+        error(s.message)
+    end
+end
+
+%% Read metadata
+% Display names of all sections
+cellfun(@(x) disp(x.name),f.sections)
+
+%% General information
+sectionGeneral = f.openSection('General');
+% Properties
+cellfun(@(x) disp(x.name),sectionGeneral.properties)
+% Institution
+fprintf(['Institution: ',sectionGeneral.openProperty('Institution').values{1}.value,'\n'])
+% Recording location
+fprintf(['Recording location: ',sectionGeneral.openProperty('Recording location').values{1}.value,'\n'])
+% Sections
+cellfun(@(x) disp(x.name),sectionGeneral.sections)
+% Publications
+sectionPublications = sectionGeneral.openSection('Related publications');
+cellfun(@(x) disp(x.name),sectionPublications.properties)
+fprintf(['Publication name: ',sectionPublications.openProperty('Publication name').values{1}.value,'\n'])
+fprintf(['Publication DOI: ',sectionPublications.openProperty('Publication DOI').values{1}.value,'\n'])
+% Recording setup
+sectionRecordingSetup = sectionGeneral.openSection('Recording setup');
+cellfun(@(x) disp(x.name),sectionRecordingSetup.properties)
+fprintf(['Recording setup iEEG: ',sectionRecordingSetup.openProperty('Recording setup iEEG').values{1}.value,'\n'])
+
+%% Task information
+sectionTask = f.openSection('Task');
+% Properties
+cellfun(@(x) disp(x.name),sectionTask.properties)
+% Task characteristics
+fprintf(['Task name: ',sectionTask.openProperty('Task name').values{1}.value,'\n'])
+fprintf(['Task description: ',sectionTask.openProperty('Task description').values{1}.value,'\n'])
+fprintf(['Task URL: ',sectionTask.openProperty('Task URL').values{1}.value,'\n']) % TODO
+
+%% Subject information
+sectionSubject = f.openSection('Subject');
+% Properties
+cellfun(@(x) disp(x.name),sectionSubject.properties)
+% Subject characteristics
+fprintf(['Age: ',num2str(sectionSubject.openProperty('Age').values{1}.value),'\n'])
+fprintf(['Gender: ',sectionSubject.openProperty('Gender').values{1}.value,'\n']) % Sex?
+fprintf(['Pathology: ',sectionSubject.openProperty('Pathology').values{1}.value,'\n'])
+fprintf(['Depth electrodes: ',sectionSubject.openProperty('Depth electrodes').values{1}.value,'\n'])
+fprintf(['Electrodes in seizure onset zone (SOZ): ',sectionSubject.openProperty('Electrodes in seizure onset zone (SOZ)').values{1}.value,'\n'])
+
+%% Session information
+sectionSession = f.openSection('Session');
+% Properties
+cellfun(@(x) disp(x.name),sectionSession.properties)
+% Session characteristics
+fprintf(['Number of trials: ',num2str(sectionSession.openProperty('Number of trials').values{1}.value),'\n'])
+fprintf(['Trial duration: ',num2str(sectionSession.openProperty('Trial duration').values{1}.value),' ',sectionSession.openProperty('Trial duration').unit,'\n'])
+% Sections
+cellfun(@(x) disp(x.name),sectionSession.sections)
+
+%% Trial information
+sectionTrialProperties = sectionSession.openSection('Trial properties');
+% Sections
+cellfun(@(x) disp(x.name),sectionTrialProperties.sections)
+% Each section is for a single trial
+% Select trial
+nTrial = 1;
+sectionSingleTrial = sectionTrialProperties.sections{nTrial};
+
+%% Single trial
+% Properties
+cellfun(@(x) disp(x.name),sectionSingleTrial.properties)
+for nProperty = 1:length(sectionSingleTrial.properties)
+    switch sectionSingleTrial.properties{nProperty}.datatype
+        case {'double','logical'}
+            fprintf([sectionSingleTrial.properties{nProperty}.name,': ',num2str(sectionSingleTrial.properties{nProperty}.values{1}.value),'\n'])
+        otherwise
+            fprintf([sectionSingleTrial.properties{nProperty}.name,': ',sectionSingleTrial.properties{nProperty}.values{1}.value,'\n'])
+    end
+end
+
+%% Blocks
+cellfun(@(x) disp(x.name),f.blocks)
+block = f.blocks{1};
+
+%% Groups of data arrays, tags, multitags
+groups = block.groups;
+cellfun(@(x) disp(x.name),block.groups)
+
+%% Select trial
+nTrial = 1;
+
+%% iEEG data
+group_iEEG = block.openGroup('iEEG data');
+% Data array
+dataArray_iEEG = group_iEEG.dataArrays{nTrial};
+
+% Electrode labels
+striEEGLabels = dataArray_iEEG.dimensions{1}.labels;
+% Time axis
+tiEEG = (0:(double(dataArray_iEEG.dataExtent(2))-1))*dataArray_iEEG.dimensions{2}.samplingInterval+dataArray_iEEG.dimensions{2}.offset;
+% Read data
+data_iEEG = dataArray_iEEG.readAllData;
+
+% Plot trial data
+figure
+plot(tiEEG,data_iEEG)
+title(['iEEG data - Trial ',num2str(nTrial)])
+xlabel(['Time (',dataArray_iEEG.dimensions{2}.unit,')'])
+ylabel(['Voltage (',dataArray_iEEG.unit,')'])
+xlim([tiEEG(1),tiEEG(end)])
+legend(striEEGLabels)
+
+%% Trial events
+group_TrialEvents_iEEG = block.openGroup('Trial events single tags iEEG');
+
+%% Trial events for a single trial
+indTrialTags_iEEG = contains(cellfun(@(x) x.name,group_TrialEvents_iEEG.tags,'UniformOutput',0),['Trial_',num2str(nTrial,'%.2d')]);
+
+TrialEvents_iEEG = group_TrialEvents_iEEG.tags(indTrialTags_iEEG);
+
+cellfun(@(x) disp(x.name),TrialEvents_iEEG)
+
+%% Time of a single event
+nEvent = 1; % Condition
+fprintf(['Event name: ',TrialEvents_iEEG{nEvent}.name,'\n'])
+fprintf([sprintf('Time w.r.t. fixation: %.1f %s',TrialEvents_iEEG{nEvent}.position(2),TrialEvents_iEEG{nEvent}.units{1}),'\n'])
+fprintf([sprintf('Duration: %.1f %s',TrialEvents_iEEG{nEvent}.extent(2),TrialEvents_iEEG{nEvent}.units{1}),'\n'])
+
+%% Units
+group_SpikeTimes = block.openGroup('Spike times');
+
+%% Select unit and trial
+nUnit = 1;
+nTrial = 5;
+indUnitSpikeTimes = contains(cellfun(@(x) x.name,group_SpikeTimes.dataArrays,'UniformOutput',0),['Unit_',num2str(nUnit),'_'])&...
+    contains(cellfun(@(x) x.name,group_SpikeTimes.dataArrays,'UniformOutput',0),['Trial_',num2str(nTrial,'%.2d')]);
+
+dataArray_SpikeTimes = group_SpikeTimes.dataArrays{indUnitSpikeTimes};
+% Read data
+SpikeTimes = dataArray_SpikeTimes.readAllData;
+
+figure
+stem(dataArray_SpikeTimes.readAllData,ones(length(SpikeTimes),1))
+title(['Spike times - Unit ',num2str(nUnit),' - Trial ',num2str(nTrial)])
+xlabel(['Time (',dataArray_SpikeTimes.dimensions{1}.unit,')'])
+
+%% Multitag for the unit
+indMultiTagUnitSpikeTimes = contains(cellfun(@(x) x.name,block.multiTags,'UniformOutput',0),['Unit_',num2str(nUnit),'_'])&...
+    contains(cellfun(@(x) x.name,block.multiTags,'UniformOutput',0),['Trial_',num2str(nTrial,'%.2d')]);
+
+multiTag_SpikeTimes = block.multiTags{indMultiTagUnitSpikeTimes};
+
+%% Waveform for the unit
+dataArray_Waveform = multiTag_SpikeTimes.features{1}.openData;
+% Time axis
+tWaveform = (0:(double(dataArray_Waveform.dataExtent(2))-1))*dataArray_Waveform.dimensions{2}.samplingInterval+dataArray_Waveform.dimensions{2}.offset;
+% Read data
+waveform = dataArray_Waveform.readAllData;
+% Plot
+figure
+plot(tWaveform,waveform(1,:),'b')
+hold on
+plot(tWaveform,waveform(1,:)+waveform(2,:),'b--')
+plot(tWaveform,waveform(1,:)-waveform(2,:),'b--')
+title(['Waveform - Unit ',num2str(nUnit)])
+xlabel(['Time (',dataArray_Waveform.dimensions{2}.unit,')'])
+ylabel(['Voltage (',dataArray_Waveform.unit,')'])
+legend({'Mean','Std'})
+
+%% Source of the unit
+sourceUnit = dataArray_SpikeTimes.sources{1};
+% Electrode label
+sourceUnit.sources{1}.name
+% Anatomical location
+sourceUnit.sources{2}.name
+
+%% Use electrode map to get properties of the macroelectrode the unit is on
+groupiEEGElecrodes = block.openGroup('iEEG electrode information');
+
+nElectrode = find(strcmpi(cellfun(@(x) x.name,groupiEEGElecrodes.sources,'UniformOutput',0),sourceUnit.name));
+
+% MNI coordinates of the electrode
+groupiEEGElecrodes.multiTags{1}.retrieveFeatureData(nElectrode,'iEEG_Electrode_MNI_Coordinates')
+