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ensemble_enum_hist

PURPOSE ^

Plots the distributions of the response tallies in the categories of an enum.

SYNOPSIS ^

function an_st = ensemble_enum_hist(data_st,params)

DESCRIPTION ^

 Plots the distributions of the response tallies in the categories of an enum.

 outdata = ensemble_enum_hist(data_st,params);

 Calculates and plots the distributions of the response tallies in the
 different categories of an enum. The function will operate on all qids that
 it finds in the input data that are of type enum

 Note: Currently, the script will not treat the same question appearing on
 different forms as a different instance of the question. If you don't want
 answers to the same question on different forms combined, you must filter the
 data to only process forms with unique question IDs.  This behavior may
 change in future versions.

 Required variables:
 params.mysql.conn_id

 Optional parameters
 params.filt - struct for ensemble_filter for narrowing range of analyzed
               question_ids
 params.item_var - variable by which to summarize responses. Options: 
                   'session_id','subject_id','stimulus_id'
 params.report.figs.plot
 params.report.figs.ylim
 params.report.figs.title
 params.report.figs.{} - a number of other parameters that govern figure
                         plotting
 params.report.tables - specification for writing to a file. See
                        ensemble_init_fid()

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SUBFUNCTIONS ^

SOURCE CODE ^

0001 function an_st = ensemble_enum_hist(data_st,params)
0002 % Plots the distributions of the response tallies in the categories of an enum.
0003 %
0004 % outdata = ensemble_enum_hist(data_st,params);
0005 %
0006 % Calculates and plots the distributions of the response tallies in the
0007 % different categories of an enum. The function will operate on all qids that
0008 % it finds in the input data that are of type enum
0009 %
0010 % Note: Currently, the script will not treat the same question appearing on
0011 % different forms as a different instance of the question. If you don't want
0012 % answers to the same question on different forms combined, you must filter the
0013 % data to only process forms with unique question IDs.  This behavior may
0014 % change in future versions.
0015 %
0016 % Required variables:
0017 % params.mysql.conn_id
0018 %
0019 % Optional parameters
0020 % params.filt - struct for ensemble_filter for narrowing range of analyzed
0021 %               question_ids
0022 % params.item_var - variable by which to summarize responses. Options:
0023 %                   'session_id','subject_id','stimulus_id'
0024 % params.report.figs.plot
0025 % params.report.figs.ylim
0026 % params.report.figs.title
0027 % params.report.figs.{} - a number of other parameters that govern figure
0028 %                         plotting
0029 % params.report.tables - specification for writing to a file. See
0030 %                        ensemble_init_fid()
0031 
0032 % 01/28/07 Petr Janata - adapted from quest_resp_dist.m and an earlier start on
0033 % ensemble_enum_hist which was much more oriented towards returning function
0034 % handles to sub-functions that performed the various steps.
0035 %
0036 % 02/17/07 PJ - adapted to handle either sessions, subjects, or stimuli as item
0037 %               to be analyzed.
0038 % 11/13/2007 FB - added error checking in plot_hist, to support blank enum
0039 % labels, such as in the case of data_format_id 142, 144 & 145
0040 % 04/17/09 PJ - added output of plotted data to comma-separated files.
0041 % 05/11/10 PJ - Fixed bug where enum_mask was being checked instead of
0042 %               qinfo_enum_mask, leading to erroneous question skipping.
0043 % 02/15/11 PJ - Fixed conn_id checking, handling of only 1 subject
0044 % 23Aug2013 PJ - fixed minor issues associated with labeling of plots and
0045 %                figure printing
0046 % 01Nov2013 PJ - added optional suppression of by-item results
0047 % 02Sep2014 PJ - added ability to restrict plotting to particular analysis
0048 %                types, e.g. prop, count
0049 
0050 an_st = {};
0051 na = 0;
0052 
0053 try 
0054   conn_id = params.ensemble.conn_id; 
0055 catch
0056   conn_id = []; 
0057 end
0058 
0059 if isempty(conn_id)
0060   try 
0061     conn_id = params.mysql.conn_id; 
0062   catch
0063     conn_id = []; 
0064   end
0065 end
0066 
0067 % Deal with some ambiguity in how reporting structures are defined
0068 if isfield(params,'display') && isfield(params,'report')
0069   fprintf('%s: both display and report fields specified. Do not know which to use...\n', mfilename);
0070 end
0071 report_string_types = {'display','report'};
0072 repstr = 'report';
0073 for itype = 1:length(report_string_types)
0074   if isfield(params,report_string_types{itype})
0075     repstr = report_string_types{itype};
0076     break
0077   end
0078 end
0079 
0080 try 
0081   do_plot = params.(repstr).figs.plot; 
0082 catch
0083   do_plot = 0; 
0084 end
0085 
0086 % Apply any specified filtering to the input data
0087 if isfield(params,'filt')
0088   fprintf('Applying filtering criteria\n')
0089   data_st = ensemble_filter(data_st, params.filt);
0090 end
0091 
0092 % Set the column constants
0093 incol = set_var_col_const(data_st.vars);
0094 
0095 %
0096 % Gather metadata on the questions
0097 %
0098 
0099 % Figure out whether questions are referred to by their qids or composite qids
0100 if isfield(incol,'question_id')
0101   qids = unique(data_st.data{incol.question_id});
0102 elseif isfield(incol,'compqid')
0103   qids = fix(unique(data_st.data{incol.compqid}));
0104 else
0105   fprintf('Did not find question_id column in the input data\n');
0106   return
0107 end
0108 
0109 qinfo = mysql_extract_metadata('table','question', ...
0110   'question_id',qids, ...
0111   'conn_id', conn_id);
0112 
0113 % Generate the compqid for each row in the data if necessary
0114 compqid_vect = [];
0115 if isfield(incol,'compqid')
0116   compqid_vect = data_st.data{incol.compqid};
0117 elseif isfield(incol,'subquestion')
0118   compqid_vect = make_compqid(data_st.data{incol.question_id}, ...
0119     data_st.data{incol.subquestion});
0120 end
0121 
0122 % Figure out which of the questions in the qinfo structure are enums
0123 qinfo_enum_mask = ismember({qinfo.type},'enum');
0124 qinfo_enum_idxs = find(qinfo_enum_mask);
0125 nqid = length(qinfo_enum_idxs);
0126 
0127 % Figure out which of the questions are bitmasks that allow for selection of
0128 % multiple values (checkbox as opposed to radiogroup)
0129 qinfo_bitmask_mask = ismember({qinfo.html_field_type},'checkbox');
0130 
0131 qinfo_notbitmask_mask = qinfo_enum_mask & ~qinfo_bitmask_mask;
0132 
0133 % Create masks for all of the response data
0134 enum_compqids = [qinfo(qinfo_enum_mask).compqid];
0135 enum_mask = ismember(compqid_vect, enum_compqids);
0136 
0137 notbitmask_compqids = [qinfo(qinfo_notbitmask_mask).compqid];
0138 notbitmask_mask = ismember(compqid_vect, notbitmask_compqids);
0139 
0140 % Copy all of the enum data to the data_vect
0141 data_vect = zeros(size(compqid_vect));
0142 if ~iscell(data_st.data{incol.response_enum}(enum_mask))
0143   data_vect(enum_mask) = data_st.data{incol.response_enum}(enum_mask);
0144 elseif params.force_cell2double
0145   data_vect(enum_mask) = cellfun(@str2num,data_st.data{incol.response_enum}(enum_mask));
0146 else
0147   error('Response enum data is likely encrypted!')
0148 end
0149   
0150 
0151 % Convert the data for all of the non-bitmask enums to category indices
0152 data_vect(notbitmask_mask) = enum2data(data_vect(notbitmask_mask));
0153 
0154 % Figure out which variable is being used as the item for the item
0155 if isfield(params,'item_var')
0156   item_str = params.item_var;
0157 else
0158   item_str = 'session_id';
0159 end
0160 
0161 switch item_str
0162   case 'session_id'
0163     item_type = 'session';
0164   case 'subject_id'
0165     item_type = 'subject';
0166   case 'stimulus_id'
0167     item_type = 'stimulus';
0168   case 'none'
0169     item_type = 'none';
0170   otherwise
0171     fprintf('%s: Unknown item variable: %s\n', mfilename, item_str);
0172 end
0173 
0174 if strcmp(item_type,'none')
0175   item_mask_mtx = ones(length(data_st.data{1}),1);
0176   itemids = 1;
0177 else
0178   % Precalculate the masks for the item variable we are using
0179   [item_mask_mtx, itemids] = make_mask_mtx(data_st.data{incol.(item_str)});
0180 end
0181 nitems = length(itemids);
0182 
0183 %
0184 % Set stuff up for writing to a file, if that's what we're going to do.
0185 %
0186 try
0187   fid = ensemble_init_fid(params.(repstr).tables);
0188 catch
0189   fid = 1;
0190 end
0191 
0192 %
0193 % Loop over all of the unique question/subquestion combinations or compqids
0194 %
0195 for iqid = 1:nqid
0196   curr_qid_idx = qinfo_enum_idxs(iqid);
0197   
0198   % Copy the question info over to the display parameter structure in case we
0199   % are going to display some of the data
0200   params.(repstr).qinfo = qinfo(curr_qid_idx);
0201   
0202   % Make sure this question is an enum - arguably this is very redundant
0203   if ~qinfo_enum_mask(curr_qid_idx)
0204     fprintf('Unexpected qinfo type mismatch: expected enum\n');
0205     continue
0206   end
0207   
0208   % Get the enum values
0209   enum_values = qinfo(curr_qid_idx).enum_values;
0210   ncat = length(enum_values);
0211   
0212   % Make a mask for the data corresponding to this question
0213   qid_mask = ismember(compqid_vect,qinfo(curr_qid_idx).compqid);
0214   
0215   %
0216   % Perform analyses that retain item identity
0217   %
0218   na = na+1;
0219   
0220   an_st{na} = init_analysis_struct;
0221   an_st{na}.type = sprintf('enum_category_by_%s', item_type);
0222   an_vars = {item_str,'count','prop','nresp'};
0223   an_st{na}.vars = an_vars;
0224   an_cols = set_var_col_const(an_vars);
0225   by_item_an_cols = an_cols;
0226   by_item_an_idx = na;
0227   nr = 0;  % set the tally of reports for this analysis to zero
0228   
0229   % Initialize output variables
0230   for ia = 1:length(an_vars)
0231     switch an_vars{ia}
0232       case {'count','prop'}
0233         an_st{na}.data{ia} = zeros(nitems,ncat);
0234       case item_str
0235         an_st{na}.data{ia} = itemids;
0236       case {'nresp'}
0237         an_st{na}.data{ia} = zeros(nitems,1);
0238     end
0239   end
0240   
0241   % Prepare an output data matrix that tallies the number of times each
0242   % category was selected for each item
0243   
0244   for iitem = 1:nitems
0245     item_mask = item_mask_mtx(:,iitem);
0246     
0247     % Tally the number of responses the made for this item and this question
0248     nresp = sum(item_mask&qid_mask);
0249     an_st{na}.data{an_cols.nresp}(iitem) = nresp;
0250     
0251     if ~nresp
0252       continue
0253     end
0254     
0255     switch qinfo(curr_qid_idx).html_field_type
0256       case {'radiogroup','menu'}
0257         an_st{na}.data{an_cols.count}(iitem,:) = hist(data_vect(item_mask&qid_mask),1:ncat)';
0258       otherwise
0259         bitmask = data2bitmask(data_vect(item_mask&qid_mask),ncat);
0260         if size(bitmask,1) > 1
0261           sumvect = sum(bitmask);
0262         else
0263           sumvect = bitmask;
0264         end
0265         an_st{na}.data{an_cols.count}(iitem,:) = sumvect;
0266     end
0267   end % for iitem
0268   
0269   nresp_mtx = repmat(an_st{na}.data{an_cols.nresp},1,ncat);
0270   nresp_mtx(nresp_mtx == 0) = NaN;
0271   an_st{na}.data{an_cols.prop} = an_st{na}.data{an_cols.count} ./ nresp_mtx;
0272   
0273   an_st{na}.meta.question = qinfo(curr_qid_idx);
0274   
0275   %% Reports
0276   
0277   %
0278   % Perform any reports of the data in which reporting is done on a per-item basis
0279   %
0280 
0281   reportByItem = 1;
0282   if isfield(params.report, 'by_item')
0283     reportByItem = params.report.by_item;
0284   end
0285   
0286   if reportByItem
0287     nr=nr+1;
0288     an_st{na}.report{nr}.type = 'distrib_by_cat';
0289     an_st{na}.report{nr}.figfun = @plot_distrib_by_cat;
0290     if do_plot
0291       an_st{na}.report{nr}.figs = ...
0292         plot_distrib_by_cat(an_st{na}.data{an_cols.prop}, params.(repstr));
0293     end
0294     
0295     fprintf(fid,'\nQuestion (%1.2f): %s\n', ...
0296       qinfo(curr_qid_idx).compqid, qinfo(curr_qid_idx).question_text);
0297     if ~isempty(qinfo(curr_qid_idx).heading)
0298       fprintf(fid,'Subquestion: %s\n', qinfo(curr_qid_idx).heading);
0299     end
0300     fprintf(fid,'N = %d\n', nitems);
0301     fprintf(fid,'%s\t%s\n', item_str, cell2str(enum_values,'\t'));
0302     for iitem = 1:nitems
0303       switch item_str
0304         case {'session_id','stimulus_id'}
0305           itemval_str = sprintf('%d',itemids(iitem));
0306         case 'subject_id'
0307           itemval_str = itemids{iitem};
0308         case 'none'
0309           itemval_str = 'all';
0310         otherwise
0311           itemval_str = itemids{iitem};
0312       end
0313       
0314       enum_str = sprintf('\t%d', an_st{na}.data{an_cols.count}(iitem,:));
0315       fprintf(fid,'%s%s\n', itemval_str, enum_str);
0316     end
0317   end % isfield(params.report, 'by_item') && params.report.by_item
0318   %
0319   % Now perform the set of analyses that collapse across items
0320   %
0321   na = na+1;
0322   
0323   an_st{na} = init_analysis_struct;
0324   an_st{na}.type = sprintf('enum_category_across_%s', item_type);
0325     
0326   an_vars = {'prop','count'};
0327   an_st{na}.vars = an_vars;
0328   an_cols = set_var_col_const(an_vars);
0329   nr = 0;
0330   
0331   if isfield(params.report, 'across_items') && isfield(params.report.across_items, 'an_types')
0332     report_vars = params.report.across_items.an_types;
0333   else
0334     report_vars = an_vars;
0335   end
0336 
0337   
0338   for ivar = 1:length(an_vars)
0339     an_type = an_vars{ivar};
0340     switch an_type
0341       case 'prop'
0342         data_col = by_item_an_cols.(an_type);
0343         plot_title = 'Average proportion of responses in each category';
0344       case 'count'
0345         data_col = by_item_an_cols.(an_type);
0346         plot_title = 'Overall counts within in each category';
0347         
0348     end % switch an_type
0349     data = an_st{by_item_an_idx}.data{data_col};
0350     
0351     % Create a subanalysis structure so that we can accumulate distributional
0352     % statistics for each category
0353     sa_st = init_analysis_struct;
0354     sa_st.type = 'distrib_stats';
0355     sa_vars = {'mean','std','min','max','nitems'};
0356     sa_cols = set_var_col_const(sa_vars);
0357     sa_st.vars = sa_vars;
0358     
0359     % Loop over all of the things we want to calculate
0360     for jvar = 1:length(sa_vars)
0361       sa_str = sa_vars{jvar};
0362       switch sa_str
0363         case 'mean'
0364           if any(isnan(data)) fun = @nanmean; else fun = @mean; end
0365           result = fun(data,1);
0366         case 'nitems'
0367           result = sum(~isnan(data(:,1)));
0368         case 'std'
0369           if any(isnan(data)) fun = @nanstd; else fun = @std; end
0370           result = fun(data,1);
0371         case 'min'
0372           if any(isnan(data)) fun = @nanmin; else fun = @min; end
0373           result = fun(data,1);
0374         case 'max'
0375           if any(isnan(data)) fun = @nanmax; else fun = @max; end
0376           result = fun(data,1);
0377           
0378       end % switch sa_str
0379       
0380       % Assign the result
0381       sa_st.data{sa_cols.(sa_str)} = result;
0382     end % for jvar
0383     
0384     % Assign the sub-analyses to the main analysis
0385     an_st{na}.data{ivar} = sa_st;
0386     
0387     %
0388     % Perform any reports of the data in which reporting is done on an across-items basis
0389     %
0390     nr=nr+1;
0391     an_st{na}.report{nr}.type = 'distrib_by_cat';
0392     an_st{na}.report{nr}.figfun = @plot_hist;
0393     if do_plot && any(strcmp(an_type, report_vars))
0394       switch an_type
0395         case 'prop'
0396           plot_title = 'Average proportion of responses in each category';
0397           ylim = [0 1];
0398         case 'count'
0399           plot_title = 'Overall counts within in each category';
0400           ylim = []; % do it based on max at time of display
0401       end
0402       params.(repstr).figs.ylim = ylim;
0403       params.(repstr).figs.title = plot_title;
0404       an_st{na}.report{nr}.figs = plot_hist(an_st{na}.data{an_cols.(an_type)},params.(repstr));
0405     end % if do_plot
0406   end % for ivar=
0407   an_st{na}.meta.question = qinfo(curr_qid_idx);
0408   
0409   fprintf(fid,'\nQuestion (%1.2f): %s\n', ...
0410     qinfo(curr_qid_idx).compqid, qinfo(curr_qid_idx).question_text);
0411   if ~isempty(qinfo(curr_qid_idx).heading)
0412     fprintf(fid,'Subquestion: %s\n', qinfo(curr_qid_idx).heading);
0413   end
0414   
0415   fprintf(fid,'\nN = %d\n', nitems);
0416   
0417   for ienum = 1:length(qinfo(curr_qid_idx).enum_values)
0418     fprintf(fid,'%30s:\t%1.2f\n', qinfo(curr_qid_idx).enum_values{ienum}, ...
0419       an_st{na}.data{an_cols.prop}.data{sa_cols.mean}(ienum));
0420   end
0421 end % for iqid
0422 
0423 if fid > 1
0424   fclose(fid);
0425 end
0426 
0427 end % function ensemble_enum_hist
0428 
0429 function an_st = init_analysis_struct
0430 an_st.type = '';
0431 an_st.vars = {};
0432 an_st.data = {};
0433 an_st.meta = [];
0434 
0435 end % function an_st = init_analysis_struct
0436 
0437 function out_pp = plot_hist(data_st,params)
0438 
0439 % FB 11/13/2007 - added error checking, to support blank enum labels, such
0440 % as in the case of data_format_id 142, 144 & 145
0441 
0442 pp = params.figs;
0443 
0444 % Parse some of the input parameters
0445 try use_fig = params.use_fig;
0446 catch
0447   try use_fig = pp.start_fignum; catch use_fig = []; end
0448 end
0449 
0450 try use_axes = params.use_axes; catch use_axes = []; end
0451 
0452 try labelfontsize = params.axislabelfontsize; catch labelfontsize = 9; end
0453 
0454 col = set_var_col_const(data_st.vars);
0455 
0456 ncat = length(params.qinfo.enum_values);
0457 nitems = data_st.data{col.nitems};
0458 
0459 max_chars_per_line = 50;
0460 
0461 %
0462 % Generate a figure that summarizes the distributions across categories
0463 %
0464 if isempty(use_fig)
0465   figure
0466 else
0467   figure(use_fig), clf
0468 end
0469 
0470 nax = 0;
0471 
0472 nax=nax+1;
0473 if ~isempty(use_axes)
0474   axes(use_axes)
0475 end
0476 
0477 % Check to see if we need to sort the data
0478 try plot_sorted = pp.sort; catch plot_sorted = 0; end
0479 
0480 if plot_sorted
0481   try sortdir = pp.sort_dir; catch sortdir = 'descend'; end
0482   [sorted_data, sorted_idxs] = sort(data_st.data{col.mean},sortdir);
0483 else
0484   sorted_idxs = 1:length(data_st.data{col.mean});
0485 end
0486 
0487 % Create output variables
0488 sorted_data = data_st.data{col.mean}(sorted_idxs);
0489 sorted_stderr = sorted_data/sqrt(data_st.data{col.nitems});
0490 
0491 % Plot the data
0492 bs = bar(1:ncat, sorted_data);
0493 add_errorbars(bs,sorted_stderr');
0494 set(gca,'xtick',[],'xlim',[0 ncat+1])
0495 set(gca,'activepositionproperty','outerposition')
0496 
0497 ax(nax) = gca;
0498 
0499 % Set axes formatting
0500 
0501 % Add xtick labels as text objects so that we can rotate them
0502 label_data = {};
0503 for icat = 1:ncat
0504   % FB 11/13/2007 added this conditional, since empty enum values create
0505   % an empty cell return from linewrap, which in turn is illegal in
0506   % cell2str, which finally kills any analysis in its tracks
0507   if ~isempty(params.qinfo.enum_values{sorted_idxs(icat)}) && ...
0508       ~isempty(linewrap(params.qinfo.enum_values{sorted_idxs(icat)},18))
0509     label_text = cell2str(linewrap(params.qinfo.enum_values{sorted_idxs(icat)},18),'\n');
0510   else
0511     label_text = ' ';
0512   end
0513   text(icat,0,label_text,'rotation',-90, ...
0514     'horizontalalign','left', ...
0515     'verticalalign','middle', ...
0516     'fontsize', labelfontsize);
0517   label_data{icat} = label_text;
0518 end
0519 
0520 try ylim = pp.ylim; catch ylim=[]; end
0521 if isempty(ylim)
0522   ylim = [0 1.2*max(data_st.data{col.mean}(sorted_idxs))];
0523 end
0524 set(gca,'ylim',ylim)
0525 
0526 try ylabel_str = pp.ylabel; catch ylabel_str = ''; end
0527 ylabel(ylabel_str)
0528 
0529 if ~isfield(pp,'title')
0530   pp.title = '';
0531 end
0532 title(pp.title)
0533 
0534 if ~isfield(pp,'add_nitems') || pp.add_nitems
0535   th = add_nitems_txt(data_st.data{col.nitems});
0536 end
0537 
0538 % Add a page header
0539 try add_pagehdr = params.add_pagehdr; catch add_pagehdr = 1; end
0540 if add_pagehdr
0541   pp.pagehdr.title = sprintf(['%s\nQuestion (%1.2f): %s'], ...
0542     pp.title, params.qinfo.compqid, ...
0543     cell2str(linewrap(params.qinfo.question_text,max_chars_per_line),'\n'));
0544   nax = nax+1;
0545   ax(nax)=add_fighdr(pp.pagehdr);
0546   pp.fig.title = pp.pagehdr.title;
0547 end
0548 
0549 print_fig(pp)
0550 
0551 % Write the data that were plotted to a comma-delimited text file
0552 try data2file = pp.data2file; catch data2file = true; end
0553 if data2file && isfield(pp, 'figfname') && ~isempty(pp.figfname)
0554   [fpath,fname,fext] = fileparts(pp.figfname);
0555   datafname = fullfile(fpath,[fname '.csv']);
0556   % open the file for writing
0557   fid = fopen(datafname,'wt');
0558   if fid == -1
0559     fprintf('FAILED to open %s for writing\n', datafname);
0560   else
0561     fprintf('Writing figure data to: %s\n', datafname);
0562     fprintf(fid,'Category,Data,StdErr\n');
0563     for icat = 1:length(label_data)
0564       fprintf(fid,'%s,%1.6f,%1.6f\n', label_data{icat}, sorted_data(icat), sorted_stderr(icat));
0565     end
0566     fclose(fid);
0567   end
0568 end
0569 
0570 pp.fignum = gcf;
0571 pp.axes = ax;
0572 
0573 out_pp = pp;
0574 end % plot_hist()
0575 
0576 function pp = plot_distrib_by_cat(data_st,params)
0577 pp = params.figs;
0578 max_chars_per_line = 50;
0579 
0580 % Parse some of the input parameters
0581 try use_fig = params.use_fig;
0582 catch
0583   try use_fig = pp.start_fignum; catch use_fig = []; end
0584 end
0585 
0586 try use_axes = params.use_axes; catch use_axes = []; end
0587 
0588 try labelfontsize = params.axislabelfontsize; catch labelfontsize = 9; end
0589 
0590 if ~isstruct(data_st)
0591   tmp.vars = {'prop'};
0592   tmp.data = {data_st};
0593   data_st = tmp;
0594 end
0595 col = set_var_col_const(data_st.vars);
0596 ncat = length(params.qinfo.enum_values);
0597 nitems = size(data_st.data{col.prop},1);
0598 
0599 %
0600 % Generate a figure that shows distributions of responses across items
0601 % separately for each enum category
0602 %
0603 if isempty(use_fig)
0604   figure
0605 else
0606   figure(use_fig)
0607   clf
0608 end
0609 
0610 nax = 0;
0611 ax = [];
0612 
0613 try ncol = params.ncol; catch ncol = 3; end
0614 try tick_interval = pp.tick_interval; catch tick_interval = 0.1; end
0615 hist_scale = 0:tick_interval:1;
0616 
0617 for icat = 1:ncat
0618   hist_vals = hist(data_st.data{col.prop}(:,icat),hist_scale);
0619   
0620   try ylim = params.ylim; catch ylim=[]; end
0621   if isempty(ylim)
0622     ylim = [0 1.2*max(hist_vals)];
0623   end
0624   
0625   nax = nax+1;
0626   ax(nax) = subplot(fix(ncat/ncol)+rem(ncat,ncol),ncol,icat);
0627   bar(hist_scale,hist_vals)
0628   set(gca,'xtick',0:tick_interval:1,'xlim',[-0.05 1.05])
0629   set(gca,'ylim',ylim)
0630   title_str = params.qinfo.enum_values{icat};
0631   if strcmpi(title_str,'parent')
0632     title_str = [title_str ' '];
0633   end
0634   title(title_str)
0635   if ~isfield(pp,'add_nitems') || pp.add_nitems
0636     th = add_nitems_txt(nitems);
0637   end
0638 end % for icat=
0639 
0640 pp.fig.fignum = gcf;
0641 
0642 if ~isfield(pp,'title')
0643   pp.title = '';
0644 end
0645 
0646 pp.pagehdr.title = sprintf(['%s\nQuestion (%1.2f): %s'], pp.title, ...
0647   params.qinfo.compqid,...
0648   cell2str(linewrap(params.qinfo.question_text,max_chars_per_line),'\n'));
0649 nax = nax+1;
0650 ax(nax)=add_fighdr(pp.pagehdr);
0651 
0652 pp.fig.title = pp.pagehdr.title;
0653 pp.fig.axes = ax;
0654 
0655 print_fig(pp);
0656 
0657 out_pp = pp;
0658 end % function pp = plot_distrib_by_cat(data_st,params)
0659 
0660 function th = add_nitems_txt(nitems,params)
0661 th = text(0.95,0.95,sprintf('N=%d', nitems), ...
0662   'units','norm', ...
0663   'horizontalalign','right', ...
0664   'verticalalign', 'top');
0665 end % function add_nitems_txt(nitems,params)
0666 
0667 function print_fig(pp)
0668 if isfield(pp,'write2file') && pp.write2file
0669   if isfield(pp,'printargs')
0670     printargs = pp.printargs;
0671   else
0672     printargs = {'-dpsc','-append'};
0673   end
0674   fprintf('Printing figure to file: %s\n', pp.figfname);
0675   print(pp.figfname, printargs{:})
0676 end
0677 end % print_fig

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