VentralPallidumAlcohol2019/AnalysisAndFigures/SupportingPrograms/readNexFile.m

function [nexFile] = readNexFile(fileName)
% [nexfile] = readNexFile(fileName) -- read .nex file and return file data
% in nexfile structure
%
% INPUT:
%   fileName - if empty string, will use File Open dialog
%
% OUTPUT:
%   nexFile - a structure containing .nex file data
%   nexFile.version - file version
%   nexFile.comment - file comment
%   nexFile.tbeg - beginning of recording session (in seconds)
%   nexFile.teng - end of resording session (in seconds)
%
%   nexFile.neurons - array of neuron structures
%           neuron.name - name of a neuron variable
%           neuron.timestamps - array of neuron timestamps (in seconds)
%               to access timestamps for neuron 2 use {n} notation:
%               nexFile.neurons{2}.timestamps
%
%   nexFile.events - array of event structures
%           event.name - name of neuron variable
%           event.timestamps - array of event timestamps (in seconds)
%               to access timestamps for event 3 use {n} notation:
%               nexFile.events{3}.timestamps
%
%   nexFile.intervals - array of interval structures
%           interval.name - name of neuron variable
%           interval.intStarts - array of interval starts (in seconds)
%           interval.intEnds - array of interval ends (in seconds)
%
%   nexFile.waves - array of wave structures
%           wave.name - name of neuron variable
%           wave.NPointsWave - number of data points in each wave
%           wave.WFrequency - A/D frequency for wave data points
%           wave.timestamps - array of wave timestamps (in seconds)
%           wave.waveforms - matrix of waveforms (in milliVolts), each
%                             waveform is a vector 
%
%   nexFile.contvars - array of contvar structures
%           contvar.name - name of neuron variable
%           contvar.ADFrequency - A/D frequency for data points
%
%           continuous (a/d) data come in fragments. Each fragment has a timestamp
%           and an index of the a/d data points in data array. The timestamp corresponds to
%           the time of recording of the first a/d value in this fragment.
%
%           contvar.timestamps - array of timestamps (fragments start times in seconds)
%           contvar.fragmentStarts - array of start indexes for fragments in contvar.data array
%           contvar.data - array of data points (in milliVolts)
%
%   nexFile.popvectors - array of popvector (population vector) structures
%           popvector.name - name of popvector variable
%           popvector.weights - array of population vector weights
%
%   nexFile.markers - array of marker structures
%           marker.name - name of marker variable
%           marker.timestamps - array of marker timestamps (in seconds)
%           marker.values - array of marker value structures
%           	marker.value.name - name of marker value 
%           	marker.value.strings - array of marker value strings
%

nexFile = [];

if (nargin == 0 | length(fileName) == 0)
   [fname, pathname] = uigetfile('*.nex', 'Select a NeuroExplorer file');
	fileName = strcat(pathname, fname);
end

fid = fopen(fileName, 'r');
if(fid == -1)
   error 'Unable to open file'
   return
end

magic = fread(fid, 1, 'int32');
if magic ~= 827868494
    error 'The file is not a valid .nex file'
end
nexFile.version = fread(fid, 1, 'int32');
nexFile.comment = deblank(char(fread(fid, 256, 'char')'));
nexFile.freq = fread(fid, 1, 'double');
nexFile.tbeg = fread(fid, 1, 'int32')./nexFile.freq;
nexFile.tend = fread(fid, 1, 'int32')./nexFile.freq;
nvar = fread(fid, 1, 'int32');

% skip location of next header and padding
fseek(fid, 260, 'cof');

neuronCount = 0;
eventCount = 0;
intervalCount = 0;
waveCount = 0;
popCount = 0;
contCount = 0;
markerCount = 0;

% real all variables
for i=1:nvar
    type = fread(fid, 1, 'int32');
    varVersion = fread(fid, 1, 'int32');
	name = deblank(char(fread(fid, 64, 'char')'));
    offset = fread(fid, 1, 'int32');
	n = fread(fid, 1, 'int32');
    WireNumber = fread(fid, 1, 'int32');
	UnitNumber = fread(fid, 1, 'int32');
	Gain = fread(fid, 1, 'int32');
	Filter = fread(fid, 1, 'int32');
	XPos = fread(fid, 1, 'double');
	YPos = fread(fid, 1, 'double');
	WFrequency = fread(fid, 1, 'double'); % wf sampling fr.
	ADtoMV  = fread(fid, 1, 'double'); % coeff to convert from AD values to Millivolts.
	NPointsWave = fread(fid, 1, 'int32'); % number of points in each wave
	NMarkers = fread(fid, 1, 'int32'); % how many values are associated with each marker
	MarkerLength = fread(fid, 1, 'int32'); % how many characters are in each marker value
	MVOfffset = fread(fid, 1, 'double'); % coeff to shift AD values in Millivolts: mv = raw*ADtoMV+MVOfffset
    filePosition = ftell(fid);
    switch type
        case 0 % neuron
            neuronCount = neuronCount+1;
            nexFile.neurons{neuronCount,1}.name = name;
            fseek(fid, offset, 'bof');
            nexFile.neurons{neuronCount,1}.timestamps = fread(fid, [n 1], 'int32')./nexFile.freq;
            fseek(fid, filePosition, 'bof');
            
        case 1 % event
            eventCount = eventCount+1;
            nexFile.events{eventCount,1}.name = name;
            fseek(fid, offset, 'bof');
            nexFile.events{eventCount,1}.timestamps = fread(fid, [n 1], 'int32')./nexFile.freq;
            fseek(fid, filePosition, 'bof');
        
        case 2 % interval
            intervalCount = intervalCount+1;
            nexFile.intervals{intervalCount,1}.name = name;
            fseek(fid, offset, 'bof');
            nexFile.intervals{intervalCount,1}.intStarts = fread(fid, [n 1], 'int32')./nexFile.freq;
            nexFile.intervals{intervalCount,1}.intEnds = fread(fid, [n 1], 'int32')./nexFile.freq;
            fseek(fid, filePosition, 'bof');  
        
        case 3 % waveform
            waveCount = waveCount+1;
            nexFile.waves{waveCount,1}.name = name;
            nexFile.waves{waveCount,1}.NPointsWave = NPointsWave;
            nexFile.waves{waveCount,1}.WFrequency = WFrequency;
            
            fseek(fid, offset, 'bof');
            nexFile.waves{waveCount,1}.timestamps = fread(fid, [n 1], 'int32')./nexFile.freq;
            nexFile.waves{waveCount,1}.waveforms = fread(fid, [NPointsWave n], 'int16').*ADtoMV + MVOfffset;
            fseek(fid, filePosition, 'bof'); 
            
        case 4 % population vector
            popCount = popCount+1;
            nexFile.popvectors{popCount,1}.name = name;
            fseek(fid, offset, 'bof');
            nexFile.popvectors{popCount,1}.weights = fread(fid, [n 1], 'double');
            fseek(fid, filePosition, 'bof');
            
        case 5 % continuous variable
            contCount = contCount+1;
            nexFile.contvars{contCount,1}.name = name;
            nexFile.contvars{contCount,1}.ADFrequency = WFrequency;
            fseek(fid, offset, 'bof');
            nexFile.contvars{contCount,1}.timestamps = fread(fid, [n 1], 'int32')./nexFile.freq;
            nexFile.contvars{contCount,1}.fragmentStarts = fread(fid, [n 1], 'int32') + 1;
            nexFile.contvars{contCount,1}.data = fread(fid, [NPointsWave 1], 'int16').*ADtoMV + MVOfffset;
            fseek(fid, filePosition, 'bof'); 
         
        case 6 % marker
            markerCount = markerCount+1;
            nexFile.markers{markerCount,1}.name = name;
            fseek(fid, offset, 'bof');
            nexFile.markers{markerCount,1}.timestamps = fread(fid, [n 1], 'int32')./nexFile.freq;
            for i=1:NMarkers
                nexFile.markers{markerCount,1}.values{i,1}.name = deblank(char(fread(fid, 64, 'char')'));
                for p = 1:n
                    nexFile.markers{markerCount,1}.values{i,1}.strings{p, 1} = deblank(char(fread(fid, MarkerLength, 'char')'));
                end
            end
            fseek(fid, filePosition, 'bof');
        
        otherwise
            disp (['unknown variable type ' num2str(type)]);
    end
	dummy = fread(fid, 60, 'char');
end
fclose(fid);