Mostly finished results and lots of plots

1 files changed, 104 insertions, 0 deletions

diff --git a/report/figures/results/plot_results.m b/report/figures/results/plot_results.m
new file mode 100644
index 0000000..f6c1713
--- /dev/null
+++ b/report/figures/results/plot_results.m
@@ -0,0 +1,104 @@
+close all;
+clear; clc;
+
+% Get all results files
+files = dir("../../../results/*.out");
+tw = load("../tracy-widom-approx/tracy_widom_normal.txt");
+x = tw(:,1);
+tw1 = tw(:,2);
+nrm = tw(:,3);
+
+N_list = []
+
+%% Make a histogram for every results file
+
+for f = 1:length(files)
+
+    % Get filename
+    filename = files(f).name;
+
+    % Extract N and L
+    tokens = regexp(filename,'eigs_(\d+)_(\d+)\.out', 'tokens');
+    N = str2double(tokens{1}{1});
+    N_list = [N_list, N];
+    L = str2double(tokens{1}{2});
+
+    % Import actual data
+    data = load(strcat("../../../results/",filename));
+    % And clip to just the eigenvalues
+    data = data(:,2);
+
+    % Remove outliers
+    data_clean = data(data > sqrt(N));
+    
+    % Scale and such
+    s_data = (data_clean - 2*sqrt(N))*N^(1/6);
+
+    % Plot them
+    figure(f);
+    title([num2str(N)," matrix size, ",num2str(L)," data points"])
+    hold on
+    [counts, bins] = hist(s_data(s_data > -6), linspace(-6,4,40));
+    bin_width = bins(2)-bins(1);
+    pdf = counts/(sum(counts) * bin_width);
+    bar(bins, pdf);
+    plot(x,tw1);
+    A = [bins', pdf']
+    save("-ascii",["N",num2str(N),"_L",num2str(L),".txt"],"A")
+end
+
+%% Plot largest sample size for each matrix size N
+
+skews = [];
+kurts = [];
+i = 0;
+% Plot totals
+for n = unique(N_list)
+    i = i + 1;
+
+    % Plot all histogram values for this N
+    n_files = dir(strcat("../../../results/eigs_",num2str(n),"_*.out"));
+    n_vals = [];
+    SSE = [];
+    
+    % Get cumulative values
+    for f = 1:length(n_files)
+        filename = n_files(f).name;
+        data = load(strcat("../../../results/",filename));
+        data = data(:,2);
+        data_clean = data(data > sqrt(n));
+        s_data = (data_clean -2*sqrt(n)) * n^(1/6);
+        n_vals = [n_vals, s_data'];
+    end
+
+    % Plot a histogram showing the Gaussian, TW1, and sampled distribution
+    figure(n)
+    title(num2str(length(n_vals)))
+    hold on
+
+    % Generate the histogram
+    [counts, bins] = hist(n_vals(n_vals > -8), linspace(-8,6,70));
+    bin_width = bins(2)-bins(1);
+    pdf = counts/(sum(counts) * bin_width);
+    
+    % And plot it
+    bar(bins,pdf)
+    plot(bins, pdf);
+    plot(x,nrm,'--')
+    plot(x,tw1);
+
+    % Save the histogram to file
+    A = [bins', pdf']
+    save("-ascii",[num2str(n),"_max.txt"], "A")
+
+    % Calculate some statistics 
+    [skews(i),kurts(i)]=pdf_stats(bins,pdf);
+end
+
+figure(n+1)
+plot(unique(N_list),skews)
+hold on
+plot(unique(N_list),kurts)
+set(gca, "xtick", unique(N_list))
+A = [unique(N_list)', skews', kurts']
+save -ascii props.txt A