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Commit 8676cdff authored by Ali Karimi's avatar Ali Karimi
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working on the proofs

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......@@ -22,13 +22,6 @@ for i = 1:3
end
concen.sep = cat(2, concen.sep{:});
concen.sep = util.padcat(concen.sep{:});
%% Doing tests
[h, p] = ttest2(high_low_betas(:, 1), high_low_betas(:,2));
fprintf('P-value: %d\n', p)
avg = mean(high_low_betas, 1,'omitnan');
SD = std(high_low_betas,1,'omitnan');
fprintf('The average: %d\n The SD: %d\n', avg, SD);
%% plotting
c = util.plot.getColors();
......
......@@ -3,6 +3,7 @@ util.clearAll;
cur_save_dir = fullfile(util.get_paths().figs,'ANOVA_correlations');
util.mkdir(cur_save_dir)
c = util.plot.getColors();
%% Anova analysis for the pairwise region correlations
beta_tables_taste = util.load.all_taste_betas();
taste_names = beta_tables_taste.sep_table.Properties.VariableNames;
......
......@@ -55,7 +55,7 @@ num_animals = length(observed_per_animal);
for i = 1:num_animals
[h(i),p(i),stats] = chi2gof([1,2,3],'Frequency',observed_per_animal(i, :),...
'Expected',expected_per_animal(i, :),'Alpha',0.05/num_animals);
'Expected',expected_per_animal(i, :),'Alpha',0.05);
disp(stats)
end
%% Write the csv for python
......
......@@ -9,7 +9,7 @@ Ts = [pd.read_csv(dir,index_col=0) for dir in dirs]
arrays = [t.to_numpy() for t in Ts]
# Chi square test
chiq, p_vals = chisquare(f_obs=arrays[0], f_exp=arrays[1], axis=1)
significance = p_vals < (0.05/8)
significance = p_vals < (0.05)
# Create table and display
p_value_T = pd.DataFrame([chiq, p_vals, significance],columns=Ts[0].index,
......
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