analysis(matlab): add per-variation power simulation (powersim.m + power_result.txt)

Add variation_power.m (self-contained Monte-Carlo power for the paper's
stim x day interaction, using each folder's own data as ground truth; scores
per-animal cluster-honest power + LME power across N=[3..24] and effect
multipliers 1/0.5) and make_variation_power.m, which drops powersim.m into
every variations/<name>/ folder and runs it, writing power_result.txt beside
the existing data.csv/analyze.m/result.txt. Named powersim (not power) to
avoid shadowing the MATLAB builtin. All 28 folders processed.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

analysis/matlab/make_variation_power.m

@@ -0,0 +1,29 @@
+function make_variation_power()
+%MAKE_VARIATION_POWER Add a power-simulation script + result to every variation.
+%   MAKE_VARIATION_POWER() copies variation_power.m into each
+%   variations/<name>/ folder that contains a data.csv (as powersim.m) and runs
+%   it, producing power_result.txt beside the existing data.csv / analyze.m /
+%   result.txt. Re-runnable; also picks up any folders added later.
+
+thisDir = fileparts(mfilename('fullpath'));
+template = fullfile(thisDir, 'variation_power.m');
+root = fullfile(thisDir, 'variations');
+
+d = dir(root);
+n = 0;
+for i = 1:numel(d)
+    if ~d(i).isdir || ismember(d(i).name, {'.', '..'}); continue; end
+    folder = fullfile(root, d(i).name);
+    if ~exist(fullfile(folder, 'data.csv'), 'file'); continue; end
+    copyfile(template, fullfile(folder, 'powersim.m'));
+    fprintf('\n### %s ###\n', d(i).name);
+    localRun(fullfile(folder, 'powersim.m'));
+    n = n + 1;
+end
+fprintf('\nAdded powersim.m + power_result.txt to %d variation folders.\n', n);
+
+end
+
+function localRun(scriptPath)
+run(scriptPath);
+end