[numbers] add partial solution

projects/project_numbers/solution/main.m

@@ -0,0 +1,146 @@
+clear all
+close all
+
+%% loading, splitting data and metadata, data sorting, and definition of constants 
+load('../data/Neuron22.mat', 'data_unsorted')
+sample_rate = 1000;
+conditions = data_unsorted(:, 1);
+spike_data = data_unsorted(:, 2:end);
+data_sorted = sortrows(data_unsorted, 1, 'descend');
+sorted_conditions = data_sorted(:,1);
+sorted_spike_data = data_sorted(:, 2:end);
+
+condition_colors = ["red", "green", "blue", "k"];
+segments = ["Fixation", "Stimulus ON", "Delay"];
+segment_times = [-0.5, 0; 0.001, 0.8; 0.801, 1.8];
+
+%% Scatterplots of the spike responses  
+fig = scatterplot(spike_data, conditions, sample_rate, segments, segment_times, condition_colors);
+fig = format_figure(fig, [15, 10]);
+saveas(fig, "scatterplot_unsorted", "pdf")
+
+fig = scatterplot(sorted_spike_data, sorted_conditions, sample_rate, segments, segment_times, condition_colors);
+fig = format_figure(fig, [15, 10]);
+saveas(fig, "scatterplot_sorted", "pdf");
+
+%% Firing rate analysis
+bin_width = 0.1;
+[rates, bins] = get_firing_rates(spike_data, sample_rate, bin_width);
+fig = plot_firing_rates(conditions, rates, bins, segments, segment_times, condition_colors);
+fig = format_figure(fig, [15, 10]);
+saveas(fig, "firing_rates", "pdf")
+
+fig = plot_average_rates(rates, bins, conditions, segments, segment_times, condition_colors);
+fig = format_figure(fig, [10,10]);
+saveas(fig, "rate_comparison", "pdf")
+
+%% function definitions
+function f = plot_average_rates(rates, bins, conditions, segments, segment_times, condition_colors)
+    f = figure();
+    unique_conditions = sort(unique(conditions));
+    bins = bins + segment_times(1,1); 
+    max_rate = floor(max(rates(:))/5) * 5;
+    for i = 1:length(segments)
+        subplot(1, length(segments), i)
+        hold on
+        box_data = [];
+        grouping_data = [];
+        for j = 1:length(unique_conditions)
+            condition_rates = mean(rates(conditions == unique_conditions(j), ...
+                bins >= segment_times(i,1) & bins < segment_times(i, 2)));
+            box_data = cat(1, box_data, condition_rates);
+            grouping_data = cat(1, grouping_data, ... 
+                ones(length(condition_rates),1) * unique_conditions(j));
+        end
+        boxplot(box_data, grouping_data, "Widths", 0.3, "ColorGroup", condition_colors)
+        xticklabels(1:length(unique_conditions))
+        xlabel("Number of dots")
+        if i == 1
+            ylabel("Firing rate [Hz]")
+        end
+        ylim([0, max_rate])
+        box("off")
+        title(segments(i))
+    end
+end
+
+function f = format_figure(f, size)
+    f.Color = "White";
+    f.PaperSize = size;
+    f.PaperPosition = [0, 0, size(1), size(2)];
+end
+
+function f = plot_firing_rates(conditions, rates, bins, segments, segment_times, condition_colors)
+    f = figure();
+    unique_conditions = sort(unique(conditions));
+
+    for i = 1:length(unique_conditions)
+        condition = unique_conditions(i);
+        subplot(length(unique_conditions), 1, i)
+        hold on
+        e = errorbar(bins + segment_times(1,1), mean(rates(conditions == condition, :)), std(rates), ...
+            "Color", condition_colors(condition-1), "DisplayName", ...
+            sprintf("Number of points: %i", condition-1));
+        xlim([segment_times(1,1)-0.1, segment_times(end, end) + 0.1])
+        ylim([0, 5]) 
+        ylabel("Firing rate [Hz]")
+        if i < length(unique_conditions)
+            xticklabels([])
+        else
+            xlabel("Time [s]")
+        end
+        
+        for j = 1:length(segments)
+            if i == 1 
+                label_x_pos = segment_times(j,2) - (segment_times(j, 2) - segment_times(j, 1))/2;
+                t = text(label_x_pos, 5.5, segments(j));
+                t.HorizontalAlignment = "center";
+                t.FontSize = 10;
+            end
+            if j < length(segments)
+                plot([segment_times(j, 2), segment_times(j, 2)], ... 
+                    [0, 5],'k--', 'linewidth', 1.5)
+            end
+        end
+        legend(e);
+        box('off')
+    end  
+end
+
+function [rates, bins] = get_firing_rates(data, sample_rate, bin_width)
+    
+    time = (0:size(data, 2)-1) ./ sample_rate;
+    edges = 0:bin_width:time(end)+bin_width; 
+    rates = zeros(size(data, 1), length(edges)-1);
+    for i = 1:size(data, 1)
+        rates(i, :) = histcounts(time(data(i,:) == 1), edges);
+    end
+    bins = edges(1:end-1);
+end
+
+function f = scatterplot(data, conditions, sample_rate, segments, segment_times, colors)
+     
+    f = figure();
+    hold on
+    time = (0:size(data, 2)-1) ./ sample_rate + segment_times(1,1);
+    for i = 1:size(data, 1)
+        c = colors(conditions(i) - 1);
+        spike_times = time(data(i,:) == 1);
+        scatter(spike_times, ones(length(spike_times),1) * i, c)
+    end
+    xlabel('Time [s]')
+    ylabel('Trials')
+    for i = 1:length(segments)
+        label_x_pos = segment_times(i,2) - (segment_times(i, 2) - segment_times(i, 1))/2;
+        t = text(label_x_pos, 275, segments(i));
+        t.HorizontalAlignment = "center";
+        t.FontSize = 10;
+        if i < length(segments)
+            plot([segment_times(i, 2), segment_times(i, 2)],[0, size(data,1)],'k--', 'linewidth', 1.5)
+        end
+    end
+    ylim([0, size(data, 1) + 50])
+    yticks(0:50:250)
+    box off
+    hold off
+end