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_Raster_And_Similarity.m
function Plot_Raster_And_Similarity(raster,similarity,name,sim_method,states)
% Plot Similarity and raster toghether
%
% Plot_Raster_And_Similarity(raster,similarity,name,sim_method,states)
%
% Pķrez-Ortega Jes·s - Dec 2019
% modified Mar 2020
switch nargin
case 4
states = [];
case 3
sim_method = '';
states = [];
case 2
sim_method = '';
name = '';
states = [];
end
frames = size(raster,2);
if frames == size(similarity,1)
Set_Figure(['Raster and similarity (' name ')'],[0 0 1220 900]);
% Plot similarity in time function
Set_Axes(['SimAxes' name],[0 0 1 0.65]);
imagesc(similarity)
set(gca,'YDir','normal','xtick',[],'ytick',[])
title([sim_method ' similarity'])
xlabel('neural vectors')
% Plot raster
ax = Set_Axes(['RasterAxes' name],[0 0.65 1 0.35]);
if ~isempty(states)
rasterColor = double(raster);
rasterColor(rasterColor>0) = -1;
ensembles(1,:) = unique(states);
for i = ensembles
% Get the raster form ensemble i
rasterSingle = rasterColor(:,states==i);
rasterSingle(rasterSingle==0) = i;
rasterColor(:,states==i) = rasterSingle;
end
colors = Read_Colors(length(ensembles));
colors = (colors+ones(size(colors)))/2;
imagesc(rasterColor,[-1 length(ensembles)]);
set(gca,'ydir','normal')
colormap(ax,[0 0 0;1 1 1;colors])
ylabel('neurons')
title(strrep(name,'_','-'))
else
Plot_Raster(raster,name,true,false,false);
end
else
error(' Size of the neural vectors in the raster should be the same in the similarity matrix!')
end