function plotConfMat(varargin)

%PLOTCONFMAT plots the confusion matrix with colorscale, absolute numbers

% and precision normalized percentages

%

% Usage:

% PLOTCONFMAT(confmat) plots the confmat with integers 1 to n as class labels

% PLOTCONFMAT(confmat, labels) plots the confmat with the specified labels

%

% Vahe Tshitoyan, Gutierrez PS

% 19-march-2021

%

% Arguments

% confmat (required): a square confusion matrix

% labels: vector of class labels

% fontsize: to be used on plot texts (default is 14)

% grayscale: if true, use grayscale colors (default is false, blue colors)

%

% Source: https://github.com/gutierrezps/plotConfMat

% default arguments

fontsize = 14;

grayscale = false;

% number of arguments

switch (nargin)

case 0

confmat = 1;

labels = {'1'};

case 1

confmat = varargin{1};

labels = 1:size(confmat, 1);

case 2

confmat = varargin{1};

labels = varargin{2};

case 3

confmat = varargin{1};

labels = varargin{2};

fontsize = varargin{3};

otherwise

confmat = varargin{1};

labels = varargin{2};

fontsize = varargin{3};

grayscale = varargin{4} == true;

end

confmat(isnan(confmat))=0; % in case there are NaN elements

numlabels = size(confmat, 1); % number of labels

% calculate the percentage accuracies

confpercent = 100*confmat./repmat(sum(confmat, 1),numlabels,1);

% plotting the colors

imagesc(confpercent);

title(sprintf('Accuracy: %.2f%%', 100*trace(confmat)/sum(confmat(:))));

ylabel('Output Class'); xlabel('Target Class');

% set the colormap

if grayscale

colormap(flipud(gray));

else

% scikit-learn confusion matrix colors (dark-blue, blue, white)

confColors = [

0.03 0.19 0.42; % 100%

0.29 0.60 0.79; % 60%

1.00 1.00 1.00 % 0%

];

confColorMap = zeros(64, 3);

colorPts = int8([0.4 0.6] .* 64);

for i = 1:2

colors = zeros(colorPts(i), 3);

for j = 1:3

colors(:, j) = linspace(confColors(i, j), confColors(i+1, j), colorPts(i))';

end

if i == 1

confColorMap(1:colorPts(1), :) = colors;

else

confColorMap(colorPts(1)+1:64, :) = colors;

end

end

colormap(flipud(confColorMap));

end

% Create strings from the matrix values and remove spaces

textStrings = num2str([confpercent(:), confmat(:)], '%.1f%% (%d)\n');

textStrings = strtrim(cellstr(textStrings));

% Create x and y coordinates for the strings and plot them

[x,y] = meshgrid(1:numlabels);

hStrings = text(x(:),y(:),textStrings(:), ...

'HorizontalAlignment','center', 'FontSize', fontsize);

% Get the middle value of the color range

midValue = mean(get(gca,'CLim'));

% Choose white or black for the text color of the strings so

% they can be easily seen over the background color

textColors = double(repmat(confpercent(:) > midValue,1,3));

for i = 1:length(hStrings)

set(hStrings(i),'Color', textColors(i,:));

end

% Setting the axis labels and font size

set(gca,'XTick',1:numlabels,...

'XTickLabel',labels,...

'YTick',1:numlabels,...

'YTickLabel',labels,...

'TickLength',[0 0],...

'FontSize', 18);

% add colorbar

h = colorbar;

set(h, 'FontSize', fontsize);

end