https://github.com/PerezOrtegaJ/Neural_Ensemble_Analysis
Tip revision: 9d37fd031dfbdb4eb69faa449d0a6416267a7d4f authored by Jesús Pérez on 28 July 2020, 20:36:58 UTC
Update README.md
Update README.md
Tip revision: 9d37fd0
Plot_Sequences.m
% Plot all sequences in vertical way
%
% PÈrez-Ortega Jes˙s - May 2018
function Plot_Sequences(sequences,division_ms,save,name,colors)
n_colors=max(sequences(:));
default_colors= Read_Colors(n_colors);
if(nargin==2)
save=false;
name='Sequences';
colors=default_colors;
elseif(nargin==3)
name='Sequences';
colors=default_colors;
elseif(nargin==4)
colors=default_colors;
end
[n,n_in_seq]=size(sequences);
if(division_ms*n_in_seq>=3000)
times=(division_ms:division_ms:division_ms*n_in_seq)/1000;
elseif(division_ms==0)
times=1:n_in_seq;
else
times=division_ms:division_ms:division_ms*n_in_seq;
end
Set_Figure(name,[0 0 900 200]);
map=winter(n);
for i=1:n
plot(times,sequences(i,:)+1*i,'color',map(i,:));hold on
end
sequence_mode=mode(sequences);
errors=0;
for i=1:n_in_seq
errors=errors+length(find(sequences(:,i)~=sequence_mode(i)));
end
if(division_ms*n_in_seq>=3000)
xlabel('time (s)')
elseif(division_ms==0)
xlabel('peak # (t)')
else
xlabel('time (ms)')
end
ylabel('sequence #')
errors_percetage=errors/(n*n_in_seq)*100;
title([name ' - ' num2str(errors) ' errors from the mode - '...
num2str(errors_percetage) '%'])
% to save
if(save)
Save_Figure(name);
end
% Sequences in image
Set_Figure([name ' - image'],[0 0 1000 800]);
imagesc(sequences)
colormap(colors)
title([name ' - ' num2str(errors) ' errors from the mode - '...
num2str(errors_percetage) '%'])
% to save
if(save)
Save_Figure([name ' - image']);
end
end