function LabView = LabView_importData(fullFileName,varargin)
%
% LabView_importData reads data log ASCII files stored by LabView into
% a Matlab time series.
%
% LabView = LabView_importData(A) imports file A
% and stores its content as time series in a structure called "LabView".
%
% LabView = LabView_importData(A,LabView) imports file A
% and appends its content as time series to the LabView structure.
%
%
% Example
% LabView = LabView_importData('exmpl.dat',LabView)
%
% Input
% * Napp_chamber_file: Complete and absolute path to the Napp chamber log file.
% * LabView: name of output structure. Always call this'LabView'
%
% Output
% * LabView: time series, the name starting with "ts"
% followed by date and time the recording started.
%
% See also LABVIEW_COMBINE, LABVIEW_PLOT, LABVIEW_CUTDATA
%
%% Data Structure
%
% Data structure before 4.3.2019
% col 1:    Date
% col 2:    Time
% col 3:    Reservoir "Pressure 1" - Unit "1 water" - mbar  -> ts.Data:2
% col 4:    Reservoir "Pressure 2" - Unit "2 other" - mbar  -> ts.Data:3
% col 5:    Baratron 1	- cell - 1mbar max - mbar      -> ts.Data:4
% col 6:    Baratron 2	- cell - 10mbar max - mbar      -> ts.Data:8
% col 7:    Baratron 3	- cell - 0.05mbar max  - mbar      -> ts.Data:9
% col 8:    Baratron 4  -                       - mbar
% col 9:    Temp.Ice Sample                     - °C        -> ts.Data:1
% col 10:   Temp.Heated Sample
% col 11:   none
% col 12:   Temp. Reservoir "Cooler 1"          - °C        -> ts.Data:5
% col 13:   Temp. Reservoir "Cooler 2"          - °C        -> ts.Data:6
% col 14:   Flow He(cryoholder)                 - l/min     -> ts.Data:7
% col 15:   none
% col 16:   none
%
% Data structure after 4.3.2019
% col 1:    Date
% col 2:    Time
% col 3:    Reservoir "Pressure 1" - Unit "1 water" - mbar  -> ts.Data:2
% col 4:    Reservoir "Pressure 2" - Unit "2 other" - mbar  -> ts.Data:3
% col 5:    Baratron 1	- cell - 1mbar max - mbar      -> ts.Data:4
% col 6:    Baratron 2	- cell - 10mbar max - mbar      -> ts.Data:8
% col 7:    Baratron 3	- cell - 0.05mbar max  - mbar      -> ts.Data:9
% col 8:    Baratron 4  -                       - mbar
% col 9:    Temp.Ice Sample                     - °C        -> ts.Data:1
% col 10:   Temp.Heated Sample
% col 11:   Temp. Reservoir "Cooler 1"          - °C        -> ts.Data:5
% col 12:   Temp. Reservoir "Cooler 2"          - °C        -> ts.Data:6
% col 13:   Flow He(cryoholder)                 - l/min     -> ts.Data:7
% col 14:   Flow gas 1
% col 15:   Pressure chamber                    -  mbar
% col 16:   x-position of cryoholder            - mm        -> ts.Data:10
% col 17:   y-position of cryoholder            - mm        -> ts.Data:11
% col 18:   z-position of cryoholder            - mm        -> ts.Data:12
% col 19:   nothing
% col 20:   Temp.Sealing                        - °C        -> ts.Data:13


%%

% Create an InputParser object
p = inputParser;
% Add inputs to the scheme.
defaultAppendToStructure = 0;
addRequired(p,'fullFileName',@isfile);
addOptional(p,'appendToStructure',defaultAppendToStructure,@isstruct);
% Parse the inputs.
parse(p,fullFileName,varargin{:})

%% =====================================================================
%  NEW FILE FORMAT (added 2026-07-02)
%  ---------------------------------------------------------------------
%  Detect the mid-2026 LabView format from its header and import it here,
%  then return early so none of the older-format logic below is touched.
%  New file: ISO-8859-1 encoded, 2 header lines, tab-delimited, 16 data
%  columns + trailing tab, CRLF. The temperature column is written
%  corrupted as "<int>NaN" (e.g. "-8NaN"); the leading integer is the real
%  ice-sample temperature. Channels no longer logged are filled with NaN so
%  the output keeps the same 13-column ts.Data layout, field naming and
%  .Name as older files.
%    col 3  pressure_cell (hPa) -> ts.Data:4    col 4  temperature -> ts.Data:1
%    col 5-7 x/y/z (mm)         -> ts.Data:10-12 col 8  Tsealing   -> ts.Data:13
%    col 9  flow cryo (l/min)   -> ts.Data:7
% =====================================================================
keepTemperatureInteger = true;   % true: recover a value from corrupted "-8NaN"-style
                                 % entries (via the leading integer); false: NaN those out.
                                 % Clean values (e.g. "32.072") are ALWAYS parsed in full,
                                 % decimals included, regardless of this toggle -- it only
                                 % affects what happens to the corrupted "<int>NaN" case.

if isstruct(p.Results.appendToStructure)
    LabView = p.Results.appendToStructure;
end

fidChk = fopen(p.Results.fullFileName,'r','n','ISO-8859-1');
hdrLine1 = fgetl(fidChk);
hdrLine2 = fgetl(fidChk);
fclose(fidChk);

if (ischar(hdrLine2) && contains(hdrLine2,'pressure_cell')) || ...
        (ischar(hdrLine1) && contains(hdrLine1,'gas name'))

    fid  = fopen(p.Results.fullFileName,'r','n','ISO-8859-1');
    data = textscan(fid, ...
        '%s %s %f %s %f %f %f %f %f %f %f %f %f %f %f %f %*s', ...
        'HeaderLines', 2, 'Delimiter', '\t', 'EndOfLine', '\r\n');
    fclose(fid);

    if keepTemperatureInteger
        temperature = cellfun(@(s) parseTemperature(s), data{4});
    else
        temperature = cellfun(@(s) parseTemperature(s, false), data{4});
    end

    nanCol = nan(numel(data{3}),1);

    tsName = ['ts_' datestr(datenum([char(data{1}{1}), char(data{2}{1})], ...
        'dd.mm.yyyyHH:MM:SS'),'YYYYmmdd_HHMM')];

    LabView.(tsName) = timeseries( ...
        [ temperature nanCol nanCol data{3} nanCol nanCol data{9} ...
          nanCol nanCol data{5} data{6} data{7} data{8} ], ...
        datestr(datenum([char(data{1}), char(data{2})],'dd.mm.yyyyHH:MM:SS'),0));
    LabView.(tsName).Name = 'Readout Napp Chamber raw signal';

    clearvars fid data temperature nanCol tsName hdrLine1 hdrLine2 fidChk ...
        keepTemperatureInteger
    return
end
%% =====================================================================

%%
% get filedate
[~,name,~] = fileparts(p.Results.fullFileName);
tmp = strsplit(name,'_PC');
filedate = datenum(tmp{1},'yyyy-mm-dd_HH.MM.SS');

clearvars name tmp

%%
% parse structure to append to

if isstruct(p.Results.appendToStructure)
    LabView = p.Results.appendToStructure;
end
%%
if datenum(filedate) <= datenum('04-Mar-2019 13:30:00')

    fid             = fopen(p.Results.fullFileName);
    data            = textscan(fid, ...
        '%s %s %f %f %f %f %f %f %f %f %f %f %f %f %f %f',...
        'HeaderLines',1); % data file has 2 text columns, followed by 14 numeric columns
    fclose(fid);
    % define time series
    LabView.(['ts_' datestr(datenum([char(data{1}{1}), char(data{2}{1})],'dd.mm.yyyyHH:MM:SS'),'YYYYmmdd_HHMM')])      ...
        = timeseries([data{9} data{3} data{4} data{5} data{12} ...
        data{13} data{14} data{6} data{7}] , ...
        datestr(datenum([char(data{1}), char(data{2})],...
        'dd.mm.yyyyHH:MM:SS'),0));
    LabView.(['ts_' datestr(datenum([char(data{1}{1}), char(data{2}{1})],'dd.mm.yyyyHH:MM:SS'),'YYYYmmdd_HHMM')]).Name ...
        = 'Readout Napp Chamber raw signal';
    clear fid ans formatOut  nans t x

elseif datenum(filedate) >= datenum('15-Sep-2021 01:00:00') && datenum(filedate) <= datenum('01-Apr-2023 01:00:00')
    % during this time, date and time were in american format.
    fid             = fopen(p.Results.fullFileName);
    data            = textscan(fid, ...
        '%s %s %s %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f',...
        'HeaderLines',1); %

    fclose(fid);
    % the date formating in the dat file is really messed up. Try to make
    % it consitent with MATLAB. The problem is that MATLAB does not
    % understand 1 digit month and hours.
    %
    %
    % Split the date in column 1 into year,month,day
    newDateSplit = cellfun(@(x) split(char(x),'/'),data{1},'UniformOutput', false);
    % Split the time in column 2 into hours, minutes, seconds
    newTimeSplit = cellfun(@(x) split(char(x),':'),data{2},'UniformOutput', false);
    % combine both with the am/pm string in column 3 to a new datestring
    customDateStr = cellfun(@(x,y,z) [datestr(datenum([str2double(x{3}),str2double(x{1}),str2double(x{2}),str2double(y{1}),str2double(y{2}),str2double(y{3})])), ' ', char(z)], newDateSplit,newTimeSplit,data{3}, 'uniformOutput',false) ;

    % define time series
    LabView.(['ts_' datestr(customDateStr{1},'YYYYmmdd_HHMM')])      ...
        = timeseries([data{10} data{4} data{5} data{6} data{12} ...
        data{13} data{14} data{7} data{8} data{17} data{18} data{19} data{21}], ...
        customDateStr);
    LabView.(['ts_' datestr(customDateStr{1},'YYYYmmdd_HHMM')]).Name ...
        = 'Readout Napp Chamber raw signal';
    clearvars fid ans formatOut  nans t x new* custom*


elseif datenum(filedate) >= datenum('01-Apr-2023 02:00:00')

    fid             = fopen(p.Results.fullFileName);
    data            = textscan(fid, ...
        '%s %s %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f',...
        'HeaderLines',1);
    % data file has 2 text columns, followed by 18 numeric columns (THE AM
    % PM IS MISSING and some changes to the LabView file. Confirm with Luca....)
    fclose(fid);
    % define time series

    LabView.(['ts_' datestr(datenum([char(data{1}{1}), char(data{2}{1})],'dd.mm.yyyyHH:MM:SS'),'YYYYmmdd_HHMM')])      ...
        = timeseries([data{9} data{3} data{4} data{5} data{11} ...
        data{12} data{20} data{6} data{7} data{15} data{16} data{17} data{19}] , ...
        datestr(datenum([char(data{1}), char(data{2})],...
        'dd.mm.yyyyHH:MM:SS'),0));

    LabView.(['ts_' datestr(datenum([char(data{1}{1}), char(data{2}{1})],'dd.mm.yyyyHH:MM:SS'),'YYYYmmdd_HHMM')]).Name ...
        = 'Readout Napp Chamber raw signal';
    clear fid ans formatOut  nans t x

else
    fid             = fopen(p.Results.fullFileName);
    data            = textscan(fid, ...
        '%s %s %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f',...
        'HeaderLines',1); % data file has 2 text columns, followed by 14 numeric columns
    fclose(fid);
    % define time series

    LabView.(['ts_' datestr(datenum([char(data{1}{1}), char(data{2}{1})],'dd.mm.yyyyHH:MM:SS'),'YYYYmmdd_HHMM')])      ...
        = timeseries([data{9} data{3} data{4} data{5} data{11} ...
        data{12} data{13} data{6} data{7} data{16} data{17} data{18} data{20}] , ...
        datestr(datenum([char(data{1}), char(data{2})],...
        'dd.mm.yyyyHH:MM:SS'),0));

    LabView.(['ts_' datestr(datenum([char(data{1}{1}), char(data{2}{1})],'dd.mm.yyyyHH:MM:SS'),'YYYYmmdd_HHMM')]).Name ...
        = 'Readout Napp Chamber raw signal';
    clear fid ans formatOut  nans t x
end
end

% =========================================================================
%  LOCAL FUNCTION
% =========================================================================
function val = parseTemperature(s, recoverCorrupted)
%PARSETEMPERATURE Parse one temperature field from the new-format file.
%
%   Handles two cases seen in the "temperature (degC)" column across
%   different logging sessions:
%     * CLEAN value, e.g. "32.072"   -> parsed in full, decimals included.
%     * CORRUPTED value, e.g. "-8NaN" (an integer immediately followed by
%       the literal text "NaN", from an older logger bug) -> if
%       recoverCorrupted is true (default), the leading integer is
%       recovered (e.g. -8); if false, this returns NaN instead.
%     * Legitimate "NaN" (a genuinely missing reading) -> always NaN.
%
%   A field is only treated as "clean" if str2double can parse the WHOLE
%   string as a number, so this never accidentally truncates a valid
%   decimal reading -- it only engages the leading-integer fallback for
%   strings that fail a full numeric parse (the corrupted pattern).

    if nargin < 2
        recoverCorrupted = true;
    end

    val = str2double(s);              % succeeds for clean floats AND for 'NaN' itself
    if ~isnan(val)
        return                        % clean numeric value (decimals intact) -- done
    end
    if strcmpi(strtrim(s), 'NaN')
        return                        % genuinely missing reading -- stays NaN
    end

    % Anything else that failed a full parse is treated as the corrupted
    % "<int>NaN" pattern.
    if recoverCorrupted
        val = str2double(regexp(s, '^-?\d+', 'match', 'once'));
    else
        val = NaN;
    end
end