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ensemble_deduce_trial_number

PURPOSE ^

Deduces trial numbers associated with repeated forms in a response table

SYNOPSIS ^

function out_st = ensemble_deduce_trial_number(resp_st,params)

DESCRIPTION ^

 Deduces trial numbers associated with repeated forms in a response table
 structure. Returns trial numbers (starting at 1 for each subject
 indicated in the subject_id field) in a new field called trial_number. 

 out_st = ensemble_deduce_trial_number(resp_st,params);

 This function is useful for generating a variable that can be used to
 group multiple rows that belong together conceptually. Having such
 information is necessary for rearranging functions that convert between
 long and wide formats, such as when different question_id or compqid
 values are broken out into their own variables. For example,
 export_respnstim accomplishes this rearrangement by virtue of a
 consistent stimulus_id across a set of rows. However, non-stimulus
 related blocks of questions have no grouping information, and so
 trial_number fulfills that purpose.

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

0001 function out_st = ensemble_deduce_trial_number(resp_st,params)
0002 % Deduces trial numbers associated with repeated forms in a response table
0003 % structure. Returns trial numbers (starting at 1 for each subject
0004 % indicated in the subject_id field) in a new field called trial_number.
0005 %
0006 % out_st = ensemble_deduce_trial_number(resp_st,params);
0007 %
0008 % This function is useful for generating a variable that can be used to
0009 % group multiple rows that belong together conceptually. Having such
0010 % information is necessary for rearranging functions that convert between
0011 % long and wide formats, such as when different question_id or compqid
0012 % values are broken out into their own variables. For example,
0013 % export_respnstim accomplishes this rearrangement by virtue of a
0014 % consistent stimulus_id across a set of rows. However, non-stimulus
0015 % related blocks of questions have no grouping information, and so
0016 % trial_number fulfills that purpose.
0017 %
0018 %
0019 
0020 % 03Sep2014 Petr Janata
0021 % 24Jan2014 PJ - added handling of successive numbering across multiple
0022 %                sessions within a single subject
0023 
0024 % Make sure we have the columns we need
0025 requiredVars = {'subject_id','response_order','form_order','session_id'};
0026 if ~all(ismember(requiredVars, resp_st.vars))
0027   error('Required variables (%s) not in data struct', cell2str(requiredVars,','))
0028 end
0029 
0030 % Add the new column
0031 resp_st.vars{end+1} = 'trial_number';
0032 resp_st.data{end+1} = zeros(size(resp_st.data{1},1),1);
0033 
0034 % Get column names and indices
0035 rcols = set_var_col_const(resp_st.vars);
0036 
0037 % Get the number of subjects
0038 subids = unique(resp_st.data{rcols.subject_id});
0039 nsubs = length(subids);
0040 
0041 % Generate a matrix of response and form orders
0042 rofo = [resp_st.data{rcols.response_order} resp_st.data{rcols.form_order}];
0043 
0044 for isub = 1:nsubs
0045   currSub = subids{isub};
0046   submask = strcmp(resp_st.data{rcols.subject_id}, currSub);
0047   
0048   newro = [1; diff(rofo(submask,1))>0];
0049   newsamefo = [1; diff(rofo(submask,2))<1];
0050   newsess = [1; diff(resp_st.data{rcols.session_id}(submask))~=0];
0051   
0052   rofomask = newro & newsamefo | newsess;
0053   
0054   resp_st.data{rcols.trial_number}(submask) = cumsum(rofomask);
0055   
0056 end % for isub
0057 
0058 out_st = resp_st;  % Assign the output
0059 
0060 return

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