analysis(matlab): convert previous (Forouzan) study to our long format

Add forouzan_load_data.m (joins raw/Data_Forouzan.csv + raw/Total_Success.csv) and make_forouzan_data.m, producing analysis/forouzan_reach_data.csv in our curated column format (subject, group, day, success, total). Group is mapped Anodal -> b2_f (tDCS), Control -> a2_f (control); Hand ignored; day 0-indexed (Session 1 = day 0 = paper 'Day 1'); early-stopped sessions (total=0) dropped. Conversion validated by refitting the paper's own LME on the converted data: interaction t(227)=2.66, F(1)=7.09, p=0.0083 -- reproduces the paper's reported t(227)=2.68, F(1)=7.12, p=0.008, N=24 (12 Anodal / 12 Control). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-22 14:18:47 -04:00
parent a4dff31772
commit d9b65a3279
3 changed files with 348 additions and 0 deletions
@@ -0,0 +1,78 @@
+function T = forouzan_load_data()
+%FOROUZAN_LOAD_DATA Load the previous (Forouzan) tDCS reaching study into our
+%   long format, with group labels matching our convention.
+%
+%   T = FOROUZAN_LOAD_DATA() reads two raw files under analysis/matlab/raw/:
+%     Data_Forouzan.csv   long, fill-down RatName; per rat/session: success,
+%                         failure, total (attempts). Sessions 1..10; rats that
+%                         stopped early have blank success and total = 0
+%                         (encoded #DIV/0!), which are dropped.
+%     Total_Success.csv   per-rat Group (Anodal | Control) and Hand.
+%
+%   and returns a table with the same variables as TDCS_LOAD_DATA:
+%     subject  (string)      rat name
+%     group    (categorical) 'b2_f' for Anodal (tDCS), 'a2_f' for Control
+%     day      (double)      Session - 1, so day 0 = the paper's "Day 1"
+%                            (matching our 0-indexed day convention)
+%     success  (double)      successful reaches in the session
+%     total    (double)      total attempts in the session
+%
+%   Hand is ignored per request. The "_f" suffix marks this as the Forouzan
+%   (previous) dataset, distinct from our Electrode-Box-A2/B2 animals.
+
+thisDir = fileparts(mfilename('fullpath'));
+longFile = fullfile(thisDir, 'raw', 'Data_Forouzan.csv');
+grpFile = fullfile(thisDir, 'raw', 'Total_Success.csv');
+
+% --- group map: rat -> Anodal|Control -> b2_f|a2_f -----------------------
+G = readtable(grpFile, 'VariableNamingRule', 'preserve');
+ratNames = string(G{:, 1});                 % col 1 = Rat_Name (BOM-safe by index)
+rawGroup = string(G{:, end});               % last col = Group (Anodal|Control)
+% Keep only the real Anodal/Control rows (drops any header/blank artifact that
+% readtable mis-parses as data because of the numeric 0..9 column headers).
+keep = ismember(rawGroup, ["Anodal", "Control"]);
+ratNames = ratNames(keep);
+rawGroup = rawGroup(keep);
+label = repmat("a2_f", numel(ratNames), 1);
+label(rawGroup == "Anodal") = "b2_f";       % Control -> a2_f (default), Anodal -> b2_f
+grpMap = containers.Map(cellstr(ratNames), cellstr(label));
+
+% --- parse the long success/total file (fill-down RatName) ---------------
+lines = readlines(longFile);
+lines = lines(strlength(strip(lines)) > 0);
+lines(1) = erase(lines(1), char(65279));    % strip UTF-8 BOM from the header
+
+subj = strings(0, 1); day = []; success = []; total = [];
+curRat = "";
+for i = 2:numel(lines)                       % skip header row
+    p = strsplit(lines(i), ',', 'CollapseDelimiters', false);
+    name = strtrim(p(1));
+    if strlength(name) > 0
+        curRat = name;
+    end
+    suc = str2double(p(3));
+    tot = str2double(p(5));
+    if isnan(suc) || isnan(tot) || tot == 0  % no session that day -> drop
+        continue
+    end
+    subj(end + 1, 1) = curRat;               %#ok<AGROW>
+    day(end + 1, 1) = str2double(p(2)) - 1;  %#ok<AGROW> Session 1 -> day 0
+    success(end + 1, 1) = suc;               %#ok<AGROW>
+    total(end + 1, 1) = tot;                 %#ok<AGROW>
+end
+
+% --- attach group and finalise -------------------------------------------
+grp = strings(numel(subj), 1);
+for i = 1:numel(subj)
+    if ~isKey(grpMap, char(subj(i)))
+        error('forouzan_load_data:missingRat', ...
+            'Rat "%s" in Data_Forouzan.csv has no group in Total_Success.csv.', subj(i));
+    end
+    grp(i) = grpMap(char(subj(i)));
+end
+
+T = table(subj, categorical(grp), day, success, total, ...
+    'VariableNames', {'subject', 'group', 'day', 'success', 'total'});
+T = sortrows(T, {'subject', 'day'});
+
+end