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K_PhaseWave_demo.m
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K_PhaseWave_demo.m
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%% K_PhaseWave_demo.mlx
% Status: Done
%
%
%
% Requirements:
%
% *CircStats*
%
%
%
% See also
%
% |K_PhaseWave, K_PhaseWave_test, K_plotLinearPhaseWave|
%
%
% Load data as |WaveformChan| objects
load('data.mat')
%% |K_PhaseWave| without Bootstrap
Wn = normalizedfreq([13 30],1024);
[b, a] = butter(3, Wn,'bandpass');
% fvtool(b,a,'Fs',newRate);
% xlim([0 5]);ylim('auto');
assert(isstable(b,a));
%%
% *flip LFP (but not BUA) for polarity*
results = K_PhaseWave(-lfp1L.Data,eeg1L.Data,1024,1024,b,a,'randomization','none',...
'plotLinear',true,'plotCirc',true)
fprintf('Vector length is only %.1f%% of SD of data\n',results.meanvec.length/std(-lfp1L.Data)*100)
%%
% *BUA*
results = K_PhaseWave(bua1L.Data,eeg1L.Data,1024,1024,b,a,'randomization','none',...
'plotLinear',true,'plotCirc',true)
fprintf('Vector length is only %.1f%% of SD of data\n',results.meanvec.length/std(bua1L.Data)*100)
%%
% |hbin| = 36 seems all right for |bar|
K_PhaseWave(bua1L.Data,eeg1L.Data,1024,1024, b, a,'randomization','none',...
'histtype','bar','histbin',36,...
'plotLinear',true,'plotCirc',true)
%%
K_PhaseWave(bua1L.Data,eeg1L.Data,1024,1024, b, a,'randomization','none',...
'histtype','bar','histbin',72,...
'plotLinear',true,'plotCirc',true)
%% plot One neuron with |K_plotLinearPhaseWave|
hlin = K_plotLinearPhaseWave(results,'ErrorBar','std');
hlin = K_plotLinearPhaseWave(results,'ErrorBar','sem');
hlin = K_plotLinearPhaseWave(results,'errorbar','none');
%%
figure
ax(1) = subplot(2,1,1);
ax(2) = subplot(2,1,2);
hlin = K_plotLinearPhaseWave(ax(2),results)
%%
hlin = K_plotLinearPhaseWave(results,'Color',defaultPlotColors(2));
hlin = K_plotLinearPhaseWave(results,'XGrid','on');
hlin = K_plotLinearPhaseWave(results,'XGrid','off');
hlin = K_plotLinearPhaseWave(results,'plotType','bar');
hlin = K_plotLinearPhaseWave(results,'plotType','line');
hlin = K_plotLinearPhaseWave(results,'Title','This is a great plot!');
%%
hlin = K_plotLinearPhaseWave(results,'Color',defaultPlotColors(2));
%% plot One neuron with |K_plotCircPhaseWave_one|
hcirc = K_plotCircPhaseWave_one(results,'Title','This is a great plot!');
%%
hcirc = K_plotCircPhaseWave_one(results,'ZeroPos','right');
%%
hcirc = K_plotCircPhaseWave_one(results,'Direction','anti');
%%
hcirc = K_plotCircPhaseWave_one(results,'ShowMeanVector',false);
%%
hcirc = K_plotCircPhaseWave_one(results,'ShowPatch',false);
%%
hcirc = K_plotCircPhaseWave_one(results,'ErrorRange','sem');
%%
% |std| is practically no use...
hcirc = K_plotCircPhaseWave_one(results,'ErrorRange','std');
%%
hcirc = K_plotCircPhaseWave_one(results,'Title','This is a great plot!');
%%
hcirc = K_plotCircPhaseWave_one(results,'Radius',0.0002);
hcirc = K_plotCircPhaseWave_one(results,'Radius',0.0010);
%% Group data
results = K_PhaseWave(bua1L.Data,eeg1L.Data,1024,1024,b,a,'randomization','none','HistBin',18);
results(2) = K_PhaseWave(bua2L.Data,eeg2L.Data,1024,1024,b,a,'randomization','none','HistBin',18);
results(3) = K_PhaseWave(bua3L.Data,eeg3L.Data,1024,1024,b,a,'randomization','none','HistBin',18)
%% K_plotLinearPhaseWave for group
K_plotLinearPhaseWave(results)
%%
K_plotLinearPhaseWave(results,'Color','g')
%%
K_plotLinearPhaseWave(results,'PlotType','bar','Color',defaultPlotColors(5))
%% K_plotLinearPhaseWave for group (surface)
K_plotLinearPhaseWave(results,'PlotType','surface')
%% K_plotCircPhaseWave_group
K_plotCircPhaseWave_group(results)
%%
K_plotCircPhaseWave_group(results,'Direction','anti');
%%
K_plotCircPhaseWave_group(results,'ZeroPos','left');
%%
K_plotCircPhaseWave_group(results,'ShowGroupCirc',false);
%%
K_plotCircPhaseWave_group(results,'ShowGroupSyn',false);
%%
K_plotCircPhaseWave_group(results,'Color','r');
%% with |Randomization| = |bootstrap|
% takes 0.8 min by Win
%
% MacBook cannot cope
%
%
Wn = normalizedfreq([13 30],1024);
[b, a] = butter(3, Wn,'bandpass');
% fvtool(b,a,'Fs',newRate);
% xlim([0 5]);ylim('auto');
assert(isstable(b,a));
%%
[results,handles] = K_PhaseWave(bua1L.Data,eeg1L.Data, 1024, 1024, b, a,...
'plotLinear',true,'plotcirc',true,'randomization','bootstrap');
%%
results(2)= K_PhaseWave(bua2L.Data,eeg2L.Data, 1024, 1024, b, a,...
'plotLinear',true,'plotcirc',true,'randomization','bootstrap');
%%
results(3) = K_PhaseWave(bua3L.Data,eeg3L.Data, 1024, 1024, b, a,...
'plotLinear',true,'plotcirc',true,'randomization','bootstrap');
%%
K_plotLinearPhaseWave(results,'Color','g')
%%
% Force group analysis even when |results| is scalar
K_plotLinearPhaseWave(results(1),'AnalysisMode','group');
%%
K_plotCircPhaseWave_group(results,'Title','What a great plot!');
%% with |Randomization| = |circshift|
% takes 0.8 min by Win
%
% MacBook cannot cope
%
%
Wn = normalizedfreq([13 30],1024);
[b, a] = butter(3, Wn,'bandpass');
% fvtool(b,a,'Fs',newRate);
% xlim([0 5]);ylim('auto');
assert(isstable(b,a));
%%
[results,handles] = K_PhaseWave(bua1L.Data,eeg1L.Data, 1024, 1024, b, a,...
'plotLinear',true,'plotcirc',true,'randomization','circshift');
%%
results(2)= K_PhaseWave(bua2L.Data,eeg2L.Data, 1024, 1024, b, a,...
'plotLinear',true,'plotcirc',true,'randomization','circshift');
%%
results(3) = K_PhaseWave(bua3L.Data,eeg3L.Data, 1024, 1024, b, a,...
'plotLinear',true,'plotcirc',true,'randomization','circshift');
%%
K_plotLinearPhaseWave(results,'Color','g')
%%
% Force group analysis even when |results| is scalar
K_plotLinearPhaseWave(results(1),'AnalysisMode','group');
%%
K_plotCircPhaseWave_group(results,'Title','What a great plot!');
%%
%% Local Functions
function [matname,eeg,wide] = local_getChan(chanSpec,S,I)
strongLFPBetaBZ = chanSpec.choose(...
chanSpec.ismatnamematched(regexptranslate('escape', S(I,:).parent))...
& (chanSpec.ischantitlematched(S(I,:).title) | chanSpec.ischan_EEG) ...
& chanSpec.ismatvalid(chanSpec.ischan_probeA00h));
matname = strrep(strongLFPBetaBZ.MatNames{1}, '.mat','');
eeg = strongLFPBetaBZ.constructChan(1,'IpsiEEG');
wide = strongLFPBetaBZ.constructChan(1,2); % supposedly beta containig LFP channel
eeg.plotPowerSpectrum(1024, 2048, 2048); % very clear beta in the EEG channel!!!
wide.plotPowerSpectrum(1024, 2048, 2048); % very clear beta in the LFP channel!!!
eeg.plotCohere(wide, 1024, 2048, 2048); % good beta in spike-EEG coherence as well
end
%--------------------------------------------------------------------------
function [eegL,lfpL,buaL] = local_getEEGLFPBUA(eeg,wide)
eegL = eeg.resample(1024);
Wn = normalizedfreq(300,wide.SRate);
[b,a] = butter(5,Wn,'low');
% fvtool(b,a,'Fs',wide.SRate);
% close
lfp = wide;
lfp.Data = filtfilt(b,a,wide.Data);
lfpL = lfp.resample(1024);
lfpL.Data = lfpL.Data - mean(lfpL.Data);% mean subtraction
Wn = normalizedfreq(300,wide.SRate);
[b,a] = butter(5,Wn,'high');
high = filtfilt(b,a,wide.Data);
thre = std(high)*3;
clear b a
buaL = wide.getBUA('wideband thresholding',3,thre,...
'plotTriggered','on','plotwith','averageonly','spikewindow',[2,3],...
'meanadjustment','global');
buaL.plotPowerSpectrum(1024,2048,2048);
ylim([0 5e-8])
xlim([0 100])
buaL.plotCohere(eegL,1024,2048,2048);
ylim([0 1])
xlim([0 100])
end