# matlab/export//catalog2csv.m
% -----------------
% Copyright © 2022 ACK Cyfronet AGH, Poland.
% -----------------
function catalog2csv(catalog, csvFileName)

  fieldNames = getFieldNames(catalog);
  fieldTypes = getFieldTypes(catalog);
  lineFormat = getLineFormat(fieldTypes);
  M = prepareCellMatrix(catalog);

  fid = fopen(csvFileName, 'w+');
  fprintf(fid, '%s\n', strjoin(fieldNames', ','));
  for k=1:size(M,1)
    fprintf(fid, lineFormat, M{k, :});
  end
  fclose(fid);

end

function fieldNames = getFieldNames(catalog)
 fieldNames = [];
 for i=1:length(catalog)
   fieldNames{i} = catalog(i).field;
 end
end

function fieldTypes = getFieldTypes(catalog)
  fieldTypes = [];
  for i=1:length(catalog)
    fieldTypes{i} = catalog(i).type;
  end
end

function M = prepareCellMatrix(catalog)
  M = {};
  for i=1:length(catalog)
    val = catalog(i).val;
    type = catalog(i).type;
  	if iscell(val)
  	  M(:,i) = val;
  	elseif isTime(type)
  	  M(:,i) = formatCatalogTime(val, type);
  	else
  	  M(:,i) = num2cell(val);
  	end
  end
end

function timeStrVector = formatCatalogTime(timeVector, fieldType)
  if iscell(timeVector)
    timeVector = cell2mat(timeVector);
  end
  emptyIndexes = isnan(timeVector);
  timeStrVector(~emptyIndexes, 1) = cellstr(datestr(timeVector(~emptyIndexes), 'yyyy-mm-dd HH:MM:SS.FFF'));
  timeStrVector(emptyIndexes, 1) = { 'NaN' };
end

# matlab/export//extractGdfFields.m
%
% -----------------
% Copyright © 2020 ACK Cyfronet AGH, Poland. 
%
% This work was partially funded by EPOS Project funded in frame of PL-POIR4.2
% --------------
%
function [varargout] = extractGdfFields(gdf, fieldNames)

  for i = 1:length(fieldNames)
    fieldName = fieldNames{i};
    assert(isfield(gdf.d, fieldName), ['gdf has no field with name: ' fieldName])
    varargout{i} = getfield(gdf.d, fieldName);
  end

end

# matlab/export//formatTime.m
% -----------------
% Copyright © 2022 ACK Cyfronet AGH, Poland.
% -----------------
%
% Get string format for the time values provided in timeVector. Format is based
% on numeric 'FieldType' (GDF) or 'type' (catalog) field
% see https://docs.cyfronet.pl/display/ISEPOS/GDF+v2.2+-+description
function timeStrVector = formatTime(timeVector, fieldType)
  % if we have '5a' and '5b', the date value is a string instead of a number)
  if (ischar(fieldType) && (strcmp(fieldType, '5a') || strcmp(fieldType, '5b')))
    timeStrVector = timeVector;
    return;
  end
  if iscell(timeVector)
    timeVector = cell2mat(timeVector);
  end
  emptyIndexes = isnan(timeVector);
  timeFormat = getTimeFormat(fieldType);
  timeStrVector(~emptyIndexes, 1) = cellstr(datestr(timeVector(~emptyIndexes), timeFormat));
  timeStrVector(emptyIndexes, 1) = { 'NaN' };
end

function timeFormat = getTimeFormat(fieldType)
  if (fieldType == 5)
    timeFormat = 'yyyy mmm dd HH:MM:SS.FFF';
  else
    timeFormat = arrayfun(@changeToMatlabFormat, fieldType(2:end));
  end
end

% Matlab uses different specification of the format than the one used in GDF files (based on Java format) - e.g., 'M' is
% used in GDF for month, while in Matlab it is used for minutes
function correctedFormatId = changeToMatlabFormat(javaTimeFormatId)
  switch javaTimeFormatId
    case 'M'
      correctedFormatId = 'm';
    case 'm'
      correctedFormatId = 'M';
    case 's'
      correctedFormatId = 'S';
    case 'S'
      correctedFormatId = 'F';
    otherwise
      correctedFormatId = javaTimeFormatId;
  end
end


# matlab/export//gdf2csv.m
% -----------------
% Copyright © 2020 ACK Cyfronet AGH, Poland.
%
% This work was partially funded by EPOS Project funded in frame of PL-POIR4.2
% -----------------
function csvFiles = gdf2csv(gdfFilePath)

  csvFiles = {};
  load(gdfFilePath);
  [~, resultFileNameBase] = fileparts(gdfFilePath);

  fieldNames = fieldnames(d);
  fieldTypes = getFieldTypes(FieldType, fieldNames);

  if (hasSingleData(d, fieldNames))
    if (length(d) > 1)
      M = prepareCellMatrixFromStructArrayWithScalars(d, fieldTypes);
    else
      M = prepareCellMatrixFromSingleStructWithVectors(d, fieldTypes, fieldNames);
    end
    resultFileName = [resultFileNameBase, '.csv'];
    saveCsvFile(M, fieldTypes, fieldNames, resultFileName);
    csvFiles = { resultFileName };
  else
    for i = 1:length(d)
      resultFileName = [resultFileNameBase, '-', num2str(i), '.csv'];
      M = prepareCellMatrixFromSingleStructWithVectors(d(i), fieldTypes, fieldNames);
      saveCsvFile(M, fieldTypes, fieldNames, resultFileName);
      csvFiles{i} = resultFileName;
    end
  end
end

function isSingle = hasSingleData(d, fieldNames)
  isSingle = length(d) == 1 || ~hasAnyVectors(d, fieldNames);
end

function hasVector = hasAnyVectors(d, fieldNames)
  hasVector = false;
  for i = 1:length(d)
    vectorValue = findFirstVectorValue(d(i), fieldNames);
    if ~isempty(vectorValue)
      hasVector = true;
      return;
    end
  end
end

function vectorValue = findFirstVectorValue(d, fieldNames)
  vectorValue = [];
  for i = 1:length(fieldNames)
    value = d.(fieldNames{i});
    if ~ischar(value) && ~isscalar(value)
      vectorValue = value;
      return;
    end
  end
end

function saveCsvFile(M, fieldTypes, fieldNames, filename)
  lineFormat = getLineFormat(fieldTypes);
  fid = fopen(filename, 'w+');
  fprintf(fid, '%s\n', strjoin(fieldNames', ','));
  for k=1:size(M,1)
    fprintf(fid, lineFormat, M{k, :});
  end
  fclose(fid);
end 

function M = prepareCellMatrixFromSingleStructWithVectors(d, fieldTypes, fieldNames)
  % some structures might contain vectors mixed with scalars, in that case we want to repeat the scalar values in the csv file
  d = convertScalarsToVectors(d, fieldNames);
  M = cell(length(d.(fieldNames{1})), length(fieldNames));
  for f = 1:length(fieldTypes)
    fieldType = fieldTypes{f};
    field = d.(fieldNames{f});
    if (isTime(fieldType))
      M(:, f) = formatTime(field, fieldType);
    elseif isnumeric(field)
      if (isrow(field))
        field = field';
      end
      M(:, f) = num2cell(field);
    else
      if (isrow(field))
        field = field';
      end
      M(:, f) = field;
    end
  end
end

function M = prepareCellMatrixFromStructArrayWithScalars(d, fieldTypes)
  M = squeeze(struct2cell(d))';
  M = cellfun(@handleEmptyArray, M, 'UniformOutput', false);
  for f = 1:length(fieldTypes)
    fieldType = fieldTypes{f};
    if (isTime(fieldType))
      M(:, f) = formatTime(M(:, f), fieldType);
    end
  end
end

function struct = convertScalarsToVectors(d, fieldNames)
  struct = d;
  firstVectorValue = findFirstVectorValue(d, fieldNames);
  if isempty(firstVectorValue)
    return;
  end
  count = length(firstVectorValue);
  for i = 1:length(fieldNames)
    field = struct.(fieldNames{i});
    if (isempty(field)) 
      field = nan;
    end
    if ischar(field) || isscalar(field)
      [vectorValue{1:count}] = deal(field);
      struct.(fieldNames{i}) = vectorValue';
    end
  end
end

function value = handleEmptyArray(value)
  if (isempty(value))
    value = nan;
  end
end

% creates a vector of field types written as in FieldType, but preserving the same order of fields as in the 'd'
% structure (fallback for a situation when the types in FieldType are in different order than fieldnames(d) or when
% FieldType contains more entries than fieldnames(d)
function fieldTypes = getFieldTypes(fieldTypeCell, fieldNames)
  fieldTypes = cell(1, length(fieldNames));
  for i = 1:length(fieldNames)
    for j = 1:size(fieldTypeCell, 1)
      if strcmp(fieldNames{i}, fieldTypeCell{j, 1})
        fieldTypes{i} = fieldTypeCell{j, 2};
      end
    end
  end
end



# matlab/export//getLineFormat.m
% -----------------
% Copyright © 2022 ACK Cyfronet AGH, Poland.
% -----------------
%
% Get string format specification used for fpritf, based on numeric 'FieldType' (GDF) or 'type' (catalog) field
% see https://docs.cyfronet.pl/display/ISEPOS/GDF+v2.2+-+description
function lineFormat = getLineFormat(fieldTypes)
  lineFormat = '';
  for f = 1:length(fieldTypes)
    fieldType = fieldTypes{f};
    formatSpec = getFormatSpec(fieldType);
    lineFormat = [lineFormat ',' formatSpec];
  end
  lineFormat = [lineFormat(2:end) '\n'];
end

function formatSpec = getFormatSpec(fieldType)
  if isTime(fieldType)
    formatSpec = '"%s"';
  elseif isnumeric(fieldType)
    if fieldType < 10
      formatSpec = getFormatSpecFromReservedFieldType(fieldType);
    elseif fieldType < 200
      formatSpec = ['%.', num2str(mod(fieldType, 10)), 'f'];
    elseif fieldType < 300
      formatSpec = ['%.', num2str(mod(fieldType, 10)), 'e'];
    else
      error(['Unrecognized fieldType: ', num2str(fieldType)])
    end
  else
    error(['Unrecognized fieldType: ', num2str(fieldType)])
  end
end

function formatSpec = getFormatSpecFromReservedFieldType(fieldType)
  switch fieldType
   case 1
     formatSpec = '%f';
   case 2
     formatSpec = '%d';
   case 3
     formatSpec = '"%s"';
   case 4
     formatSpec = '%.1f';
   case 5
     formatSpec = '%s';
   case 6
     formatSpec = '%1.1e';
   case 7
     formatSpec = '%1.2e';
   otherwise
     error(['Unrecognized fieldType: ', num2str(fieldType)])
  end
end


# matlab/export//isTime.m
% -----------------
% Copyright © 2022 ACK Cyfronet AGH, Poland.
% -----------------
%
% Check if the format defined in 'fieldType' marks time or other type of field.
% Based on numeric 'FieldType' (GDF) or 'type' (catalog) field
% see https://docs.cyfronet.pl/display/ISEPOS/GDF+v2.2+-+description
function isTime = isTime(fieldType)
  isTime = fieldType == 5 || fieldType(1) == '5';
end