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_Adjacencies_And_Network.m
% Plot weighted and binary adjacency and its network
function Plot_Adjacencies_And_Network(adjacency,adjacency_threshold,name,xy,node_color,...
edge_color,save_plot)
if(nargin==1)
adjacency_threshold = adjacency;
name = 'network';
xy = [];
node_color = [0.2 0.2 0.2];
edge_color = [0.5 0.5 0.5];
save_plot = false;
elseif(nargin==2)
name = 'network';
xy = [];
node_color = [0.2 0.2 0.2];
edge_color = [0.5 0.5 0.5];
save_plot = false;
elseif(nargin==3)
xy = [];
node_color = [0.2 0.2 0.2];
edge_color = [0.5 0.5 0.5];
save_plot = false;
elseif(nargin==4)
node_color = [0.2 0.2 0.2];
edge_color = [0.5 0.5 0.5];
save_plot = false;
elseif(nargin==5)
edge_color = [0.5 0.5 0.5];
save_plot = false;
elseif(nargin==6)
save_plot = false;
end
size_node = 20;
numbers = true;
Set_Figure(name,[0 0 1000 300]);
% Plot weighted adjacency matrix
subplot(1,3,1)
imagesc(adjacency); pbaspect([1 1 1])
title(name)
% Plot significant adjacency matrix
ax=subplot(1,3,2);
imagesc(adjacency_threshold>0); colormap(ax,[1 1 1; 0 0 0]);
pbaspect([1 1 1])
% Plot weighted network
subplot(1,3,3)
Plot_Network(adjacency_threshold,'undirected',xy,node_color,edge_color,size_node,numbers);
% Save Plot
if(save_plot)
%Save_Figure(name)
Save_Figure(name,'eps')
end
end