225 lines
7.9 KiB
Matlab
225 lines
7.9 KiB
Matlab
function[] = export_stats(e, file_out, varargin)
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% Export routine for the PDExperiment class:
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%
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% Writes a textfile with relevant properties and statistics
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% Options: Delimiter -> ','
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%
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% Thresholding:
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%
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% Quality -> Thresholding.Quality = [0/1],
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% Default Quality Threshold adopted from
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% PDExperiment class, can be altered in
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% extra parameter QualityThreshold
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%
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% Baseline -> Thresholding.Baseline = [0/1]
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% Check whether baseline is within range
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% BaselineThreshold specifies this setting
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%
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% BlinkCount -> Thresholding.BlinkCount = [0/1]
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% Check whether BlinkCount is within range
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% BlinkCountThreshold specifies this setting
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%
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% MissingLabels -> Thresholding.MissingLabels = [0/1]
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% MissingLabels is an optional cell array
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% to filter trials without those labels/fieldnames
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%
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% MatchingLabels -> Thresholding.Label = [0/1]
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% MatchingLabels is an optional cell array
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% to filter labels with a certain value
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%
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settings = struct('Delimiter', ',',...
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'LineEndings', '\n',...
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'Thresholding', struct('Quality', 0, ...
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'Baseline', 0, ...
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'BlinkCount', 0, ...
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'MissingLabels',0,...
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'Label',0), ...), ...
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'QualityThreshold', e.settings.QualityThreshold, ...
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'BaselineThreshold', [],...
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'BlinkCountThreshold', Inf, ...
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'MissingLabels', {},...
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'MatchingLabels', {});
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settings(1).QualityThreshold = e.settings.QualityThreshold;
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settings(1).Delimiter = ',';
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settings(1).LineEndings = '\n';
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settings = parse(settings, varargin);
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fp = fopen(file_out, 'w+');
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fprintf(fp,'%s\\n', repmat('-',1,100));
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fprintf(fp,'\tExport on:\t %s\n', datestr(now));
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%sprintf('\tPDParser version:\t%s\n', num2str(e.version));
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sep = settings.Delimiter; % separator
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le = settings.LineEndings; %'\n'; % line ending
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int_f = '%d'; % integer format
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dec_f = '%8.4f'; % decimal format
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str_f = '"%s"'; %string format
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max_typelength = -1; max_tl_ind = -1;
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for i = 1:length(e.subjects(1).sessions(1).trials)
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if max_typelength < length(fieldnames(e.subjects(1).sessions(1).trials(i).type))
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max_tl_ind = i;
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end
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max_typelength = max(max_typelength, length(fieldnames(e.subjects(1).sessions(1).trials(i).type)));
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end
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types = fieldnames(e.subjects(1).sessions(1).trials(max_tl_ind).type);
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type_header = '';format_type_header ='';
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for t = 1:length(types)
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type_header = [type_header types{t} sep '# of chars' sep];
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format_type_header = [format_type_header str_f sep];
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end
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cov_header = []; cov_format = [];
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for i =1:length(e.subjects(1).covariates)
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cov_header = [cov_header sprintf('Covariate%d', i) sep];
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cov_format = [cov_format int_f sep];
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end
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header = ['Subject' sep ...
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cov_header ...
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'Datafile' sep ...
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'Subject Id' sep ...
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'Session' sep ...
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'Trial' sep ...
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'Quality (%)' sep ...
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'BlinkCount' sep ...
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type_header, ...
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'Baseline (raw)' sep ...
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'Max' sep ...
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'TimeOfMax (rel to s.o.)' sep ...
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'Mean' sep ...
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'Median' sep ...
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'Mode' sep ...
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'Q1 (25%)' sep ...
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'Q2 (median)' sep ...
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'Q3 (75%)' sep ...
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'AUC' ];
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format = [str_f sep ... % subject
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'%s' ... % covariates
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str_f sep ... % datafile
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int_f sep ... % subject id
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int_f sep ... % session
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int_f sep ... % trial
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dec_f sep ... % quality
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int_f sep ... % blinkcount
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'%s' ... % types are formatted within trial, so string with no formatting
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dec_f sep ... % baseline
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dec_f sep ... % max
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dec_f sep ... % maxtime
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dec_f sep ... % mean
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dec_f sep ... % median
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dec_f sep ... % mode
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dec_f sep ... % q1
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dec_f sep ... % q2
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dec_f sep ... % q3
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dec_f le]; % AUC
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fprintf(fp,'%s\n', repmat('-',1,100));
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fprintf(fp, '%s', header);
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fprintf(fp, '\n');
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for s = 1:length(e.subjects)
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covariates = [];
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for cov =1:length(e.subjects(1).covariates)
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covariates = [covariates sprintf([dec_f sep], e.subjects(s).covariates(cov))];
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end
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for sess = 1:length(e.subjects(s).sessions)
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for t = 1:length(e.subjects(s).sessions(sess).trials)
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trial = e.subjects(s).sessions(sess).trials(t);
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%Continue with the next trial if thresholding is enabled and
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%trial suffers quality
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if ((~isempty(settings.Thresholding)) && (settings.Thresholding.Quality) && (trial.quality < settings.QualityThreshold))
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continue;
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end
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if ((~isempty(settings.Thresholding)) && (settings.Thresholding.Quality) && (trial.quality < settings.QualityThreshold))
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continue;
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end
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%% Baseline items can be skipped
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if (strmatch(trial.type.TRIAL_VAR_stim, 'Baseline'))
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continue;
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end
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tt_string = ''; % build string containg type identifiers
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for tt = 1:length(types)
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if isfield(trial.type,types{tt})
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if ischar(trial.type.(types{tt}))
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numchars = length(strtrim(trial.type.(types{tt})));
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else
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numchars = -1;
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end
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trial_type_value = trial.type.(types{tt});
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tt_string = [tt_string ...
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sprintf([str_f sep], strrep(trial_type_value(1,:),'"', '')) ...
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sprintf([int_f sep], numchars)];
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else
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tt_string = [tt_string ...
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sprintf([str_f sep], ''), ...
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sprintf([int_f sep], numchars)];
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end
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end
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if ~isempty(trial.stats)
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fprintf(fp, format, ...
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e.subjects(s).name, ...
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covariates,...
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e.subjects(s).sessions(sess).datafile, ...
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s, ...
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sess, ...
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t, ...
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trial.quality, ...
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trial.blink_count, ...
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tt_string, ...
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trial.baseline, ...
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trial.stats.max.value, ...
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trial.stats.max.time, ...
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trial.stats.mean, ...
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trial.stats.median, ...
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trial.stats.mode, ...
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trial.stats.q1, ...
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trial.stats.q2, ...
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trial.stats.q3, ...
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trial.stats.auc);
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end
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end
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end
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end
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fclose(fp);
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display(sprintf('\t*) Statistics written to %s', file_out));
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function[settings] = parse(settings,varlist);
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if length(varlist)<2;return;end
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f=fieldnames(settings);
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for k=2:2:length(varlist);
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if ~any(strcmp(varlist{k-1},f));
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error(sprintf('invalid field %s\n',varlist{k-1}));
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end
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if isstruct(varlist{k})
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substructfields = fieldnames(varlist{k});
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for sf = 1:length(substructfields)
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settings(1).(varlist{k-1}).(substructfields{sf}) = varlist{k}.(substructfields{sf});
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end
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else
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settings=setfield(settings,varlist{k-1},varlist{k});
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end
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end
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