classdef tLme < matlab.unittest.TestCase
    %TLME Tests for the linear "days x tDCS" mixed model (tdcs_lme) and its
    %   switch/case entry. Golden values computed from this dataset; the
    %   mergeA2_full interaction closely reproduces the paper's F=7.12/p=0.008.

    methods (Test)

        function testSubjectCountsAndDayEffect(testCase)
            % N (Box-A2 + Box-B2 subjects) per scenario, and the always-present
            % strong learning (day) effect.
            cfg = tdcs_config();
            expectedN = struct('unmerged_full', 6, 'mergeA2_full', 8, 'mergeB2_full', 8);
            for sc = fieldnames(expectedN)'
                L = tdcs_lme(tdcs_scenario_data(sc{1}), cfg);
                testCase.verifyEqual(L.nSubjects, expectedN.(sc{1}), ...
                    sprintf('%s: wrong subject count', sc{1}));
                testCase.verifyEqual(L.day.df1, 1);          % F(1) term
                testCase.verifyLessThan(L.day.p, 1e-6, ...
                    sprintf('%s: day (learning) effect should be highly significant', sc{1}));
            end
        end

        function testMergeA2ReplicatesPaperInteraction(testCase)
            % mergeA2_full reproduces the paper's days x tDCS interaction
            % (paper: F(1)=7.12, p=0.008; |t|=2.68).
            cfg = tdcs_config();
            L = tdcs_lme(tdcs_scenario_data('mergeA2_full'), cfg);
            testCase.verifyEqual(L.interaction.df1, 1);
            testCase.verifyEqual(L.interaction.F, 7.09, 'AbsTol', 0.1);
            testCase.verifyEqual(L.interaction.p, 0.009, 'AbsTol', 0.002);
            testCase.verifyEqual(abs(L.interaction.t), 2.66, 'AbsTol', 0.05);
            % single-df term: F == t^2
            testCase.verifyEqual(L.interaction.F, L.interaction.t^2, 'RelTol', 1e-6);
        end

        function testEffectStructShape(testCase)
            cfg = tdcs_config();
            L = tdcs_lme(tdcs_scenario_data('unmerged_full'), cfg);
            for f = {'interaction', 'day', 'tDCS'}
                e = L.(f{1});
                for g = {'estimate', 'se', 't', 'df', 'p', 'F', 'df1', 'df2', 'Fp'}
                    testCase.verifyTrue(isfield(e, g{1}), ...
                        sprintf('%s missing field %s', f{1}, g{1}));
                end
            end
        end

        function testSwitchRunsAndWritesResults(testCase)
            % The lme_* switch cases run end-to-end and write results/<name>.txt.
            here = fileparts(fileparts(mfilename('fullpath')));  % analysis/matlab
            outFile = fullfile(here, 'results', 'lme_mergeA2_full.txt');
            if exist(outFile, 'file'); delete(outFile); end
            evalc("tdcs_glm('lme_mergeA2_full')");
            testCase.verifyTrue(exist(outFile, 'file') == 2, ...
                'lme_mergeA2_full.txt was not written');
        end

        function testBadScenarioErrors(testCase)
            testCase.verifyError(@() tdcs_glm('lme_nonsense'), 'tdcs_glm:badScenario');
        end

    end
end