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unifiedData_populationAnlaysis.m~
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%post-unification script!
scatfold = '/Users/galileo/Dropbox (HMS)/p2/correctedScatterplots_190603';
load('/Users/galileo/Dropbox (HMS)/p2/dataTable_p2.mat', 'T')
singleAntData = matfile('/Users/galileo/Dropbox (HMS)/p2/singleAntennaData.mat');
% load stuff up. Assume X vars are different
for t = 1:size(T,1)
mfile = matfile(T.linkToDataFile{t});
data(t).flyNum = T.flynum(t);
data(t).aL = mfile.aL;
data(t).aR = mfile.aR;
data(t).dir = mfile.directions;
data(t).int = mfile.intensities;
data(t).Vm = mfile.meanfiltVm;
data(t).FR = mfile.meanFR;
end
clear mfile
% I30 = intensities == 30;
% I60 = intensities == 60;
% I120 = intensities == 120;
%% population direction tuning curve at highest intensity
for t = 1:7
aR = data(t).aR;
aL = data(t).aL;
directions = data(t).dir;
intensities = data(t).int;
meanFR = data(t).FR;
I30 = intensities == 30; %patch
I60 = intensities == 60;
I120 = intensities == 120;
unifSingAntData(t).dirI30 = meanFR(I30)-meanFR(1);
unifSingAntData(t).dirI60 = meanFR(I60)-meanFR(1);
unifSingAntData(t).dirI120 = meanFR(I120)-meanFR(1);
end
figure; hold on
h = plot(directions(I120), cat(1,unifSingAntData.dirI120), '-o', 'MarkerSize', 4);
set(h, {'MarkerFaceColor'}, get(h,'Color'));
legend(num2str(T.flynum))
legend boxoff
legend('Location', 'SouthEast')
ylabel('FR (Hz)')
savefig(fullfile(scatfold, sprintf('popul_dirTuning_FR_RestSubtr_I120')))
export_fig(fullfile(scatfold, sprintf('popul_dirTuning_FR_RestSubtr_I120.pdf')))
% normalize between -1 and 1 first
Y = cat(1,unifSingAntData.dirI120);
Y = bsxfun(@rdivide, Y, max(Y,[],2) );
NegPeakDivide = max(ones(size(Y,1), 1), abs(min(Y,[],2)) );
Y = bsxfun(@rdivide, Y, NegPeakDivide );
figure; hold on
h = plot(directions(I120), Y, '-o', 'MarkerSize', 4);
set(h, {'MarkerFaceColor'}, get(h,'Color'));
legend(num2str(T.flynum))
legend boxoff
legend('Location', 'SouthEast')
ylabel('norm -1 to 1 FR')
savefig(fullfile(scatfold, sprintf('popul_dirTuning_normFR_I120')))
export_fig(fullfile(scatfold, sprintf('popul_dirTuning_normFR_I120.pdf')))
% smooth a bit?
Y = cat(1,unifSingAntData.dirI120);
Y = movmean(Y, 3, 2);
Y = bsxfun(@rdivide, Y, max(Y,[],2) );
NegPeakDivide = max(ones(size(Y,1), 1), abs(min(Y,[],2)) );
Y = bsxfun(@rdivide, Y, NegPeakDivide );
figure; hold on
h = plot(directions(I120), Y, '-o', 'MarkerSize', 4);
set(h, {'MarkerFaceColor'}, get(h,'Color'));
legend(num2str(T.flynum))
legend boxoff
legend('Location', 'SouthEast')
ylabel('norm -1 to 1: smoothed(FR), movmean 3')
savefig(fullfile(scatfold, sprintf('popul_dirTuning_normsmoothFR_I120')))
export_fig(fullfile(scatfold, sprintf('popul_dirTuning_normsmoothFR_I120.pdf')))
%% sort out single antennae contribution
for t = 1:size(T,1)
aR = data(t).aR;
aL = data(t).aL;
directions = data(t).dir;
intensities = data(t).int;
meanFR = data(t).FR;
if ~ismember(t, 8:10)
ixL = find(aR==0);
ixL = ixL([2:4,1,5:7]);
aL_ixL = aL(ixL);
ixR = find(aL==0);
ixR = ixR([2:4,1,5:7]);
aR_ixR = aR(ixR); % xaxis - intervals are not linear, plus values might not be sorted? - but they are
unifSingAntData(t).aL_only = aL_ixL;
unifSingAntData(t).aR_only = aR_ixR;
unifSingAntData(t).FR_L_only = meanFR(ixL);
unifSingAntData(t).FR_R_only = meanFR(ixR);
else % show single antenna contribution for 223 233 flies
aL_ixL = aL(aR==0); %these are already sorted!
aR_ixR = aR(aL==0); %these are already sorted!
unifSingAntData(t).aL_only = aL_ixL;
unifSingAntData(t).aR_only = aR_ixR;
unifSingAntData(t).FR_L_only = meanFR(aR==0);
unifSingAntData(t).FR_R_only = meanFR(aL==0);
end
end
clearvars -except unifSingAntData data T singleAntData scatfold
%% plot all lines for each antenna
% figure; hold on
% for t = 1:size(T,1)
% plot(unifData(t).aL_only, unifData(t).FR_L_only);
% end % all over the place
figure; hold on
a = gca;
a.ColorOrder = cat(1, a.ColorOrder, [38 34 97; 235 0 139; 0 104 56]./255);
for t = 1:size(T,1)
zero = unifSingAntData(t).aL_only==0;
plot(unifSingAntData(t).aL_only, unifSingAntData(t).FR_L_only - unifSingAntData(t).FR_L_only(zero));
end
title('L antenna')
legend(num2str(T.flynum))
legend('Location', 'Best')
ylim([-8 10])
export_fig(fullfile(scatfold, sprintf('allFlies_singleAntenna_LEFTmoving.pdf')))
figure; hold on
a = gca;
a.ColorOrder = cat(1, a.ColorOrder, [38 34 97; 235 0 139; 0 104 56]./255);
for t = 1:size(T,1)
zero = unifSingAntData(t).aL_only==0; %L-R does not matter, there is just one zero.
plot(unifSingAntData(t).aR_only, unifSingAntData(t).FR_R_only - unifSingAntData(t).FR_R_only(zero));
end
title('R antenna')
legend(num2str(T.flynum))
legend('Location', 'Best')
ylim([-8 10])
export_fig(fullfile(scatfold, sprintf('allFlies_singleAntenna_RIGHTmoving.pdf')))
%% plot one cell at the time, with CI of zero - some error, but already done in bilateralAnt_unify_datatable...
% for t = 9:size(T,1)
% figure; hold on
% title(T.flynum(t))
% zero = unifData(t).aL_only==0;
% CI_centered = singleAntData.CI95bootstrap(1,t);
% CI_centered = CI_centered{1} - unifData(t).FR_L_only(zero);
% plot(unifData(t).aL_only, unifData(t).FR_L_only - unifData(t).FR_L_only(zero), '-<');
% plot(unifData(t).aL_only, unifData(t).FR_R_only - unifData(t).FR_R_only(zero), '->');
% plot([unifData(t).aL_only(1), unifData(t).aL_only(end)], [unifData(t).FR_L_only(zero)+CI_centered(2), unifData(t).FR_L_only(zero)+CI_centered(2)], ':k')
% plot([unifData(t).aL_only(1), unifData(t).aL_only(end)], [unifData(t).FR_L_only(zero)+CI_centered(1), unifData(t).FR_L_only(zero)+CI_centered(1)], ':k')
% end
%% averaging push and averaging pull displacements
for t = 1:size(T,1)
zeroI = find(unifSingAntData(t).aL_only==0);
FR_L = unifSingAntData(t).FR_L_only - unifSingAntData(t).FR_L_only(zeroI);
FR_R = unifSingAntData(t).FR_R_only - unifSingAntData(t).FR_R_only(zeroI);
analyzedData.pullL(t) = mean(FR_L(1:zeroI-1));
analyzedData.pullR(t) = mean(FR_R(1:zeroI-1));
analyzedData.pushL(t) = mean(FR_L(zeroI+1:end));
analyzedData.pushR(t) = mean(FR_R(zeroI+1:end));
analyzedData.pullX(t) = mean(unifSingAntData(t).aL_only(1:zeroI-1));
analyzedData.pushX(t) = mean(unifSingAntData(t).aL_only(zeroI+1:end));
end
figure; hold on
a = gca;
a.ColorOrder = cat(1, a.ColorOrder, [38 34 97; 235 0 139; 0 104 56]./255);
plot([analyzedData.pullX; zeros(1,size(T,1)); analyzedData.pushX],...
[analyzedData.pullL; zeros(1,size(T,1)); analyzedData.pushL], '-')
ylim([-5 5])
export_fig(fullfile(scatfold, sprintf('allFlies_singleAnt_avgPULLavgPUSH_LEFTmoving.pdf')))
figure; hold on
a = gca;
a.ColorOrder = cat(1, a.ColorOrder, [38 34 97; 235 0 139; 0 104 56]./255);
plot([analyzedData.pullX; zeros(1,size(T,1)); analyzedData.pushX],...
[analyzedData.pullR; zeros(1,size(T,1)); analyzedData.pushR], '-')
ylim([-5 5])
legend(num2str(T.flynum))
legend('Location', 'Best')
export_fig(fullfile(scatfold, sprintf('allFlies_singleAnt_avgPULLavgPUSH_RIGHTmoving.pdf')))
%% check you can replot scatter and interpolated 2d map with this unified data
clearvars -except unifSingAntData data T singleAntData scatfold
for t = 1:size(T,1)
aR = data(t).aR;
aL = data(t).aL;
directions = data(t).dir;
intensities = data(t).int;
meanFR = data(t).FR;
if ~ismember(t, 8:10)
zero_joint = 1;
ixL = find(aR==0);
ixL = ixL([2:4,1,5:7]);
aL_ixL = aL(ixL);
ixR = find(aL==0);
ixR = ixR([2:4,1,5:7]);
aR_ixR = aR(ixR); % xaxis - intervals are not linear, plus values might not be sorted? - but they are
else % 223 233 flies
zero_joint = 25;
ixL = find(aR==0);
ixR = find(aL==0);
aL_ixL = aL(aR==0); %these are already sorted!
aR_ixR = aR(aL==0); %these are already sorted!
end
%% reg scatter
% figure; hold on; axis image
% xlabel(' Left antenna (ipsi) - angular displ')
% ylabel(' Right antenna (contra) - angular displ')
% scatter(aL, aR, 200, meanFR-meanFR(zero_joint), 'filled', 'MarkerEdgeColor', 'k')
% title(sprintf('Vm (N = %d)\n fly %d', T.NtrialsIncluded(t), T.flynum(t)), 'Interpreter', 'none')
% colormap(bluewhitered(256)), cb = colorbar;
% cb.TickLabels = num2str((cb.Ticks+meanFR(zero_joint))', '%2.1f');
% cb.Label.String = '(Hz)';
% xlim([-15 15])
% ylim([-15 15])
% set(gca, 'TickDir', 'out') % OK!
%
%% calculate scatter and interpolation:
% lin sum scatter
[Lx,Ry] = meshgrid(aL_ixL, aR_ixR);
[FRx,FRy] = meshgrid(meanFR(ixL), meanFR(ixR));
Z = (FRx+FRy)/2 -meanFR(zero_joint);
% lin sum interpolate
F = scatteredInterpolant(Lx(:),Ry(:),Z(:));
% F.Method = 'linear';
% ExtrapolationMethod = 'nearest';
F.Method = 'natural';
ExtrapolationMethod = 'nearest';
[Xq,Yq] = meshgrid(min(aL_ixL):0.25:max(aL_ixL));
Vq = F(Xq, Yq);
% original scatter and interpolate -- for difference map
% aL;
% aR;
% meanFR-meanFR(zero_joint);
V_data = meanFR'-meanFR(zero_joint);
F_data = scatteredInterpolant(aL(:),aR(:),V_data);
% F.Method = 'linear';
% ExtrapolationMethod = 'nearest';
F_data.Method = 'natural';
ExtrapolationMethod = 'nearest';
[Xqd,Yqd] = meshgrid(min(aL):0.25:max(aL));
Vqd = F(Xqd, Yqd);
subplot(1,2,2)
V = meanFR'-meanFR(zero_joint);
F = scatteredInterpolant(aL(:),aR(:),V);
% F.Method = 'linear';
% ExtrapolationMethod = 'nearest';
F.Method = 'natural';
ExtrapolationMethod = 'nearest';
[Xq,Yq] = meshgrid(min(aL):0.25:max(aL));
Vq = F(Xq, Yq);
XLIMs = [max([min(Xq(:)), min(Xqd(:))]), min([max(Xq(:)), max(Xqd(:))])];
YLIMs = [max([min(Yq(:)), min(Yqd(:))]), min([max(Yq(:)), max(Yqd(:))])];
% normalize:
Nqd = Vqd + meanFR(zero_joint);
Nq = Vq + meanFR(zero_joint);
%% plot scatter
% % figure; hold on; axis image
% % mesh(Lx,Ry,Z)
% % colormap(bluewhitered(256)), cb = colorbar;
% % cb.TickLabels = num2str((cb.Ticks+meanFR(zero_joint))', '%2.1f');
% % xlabel('L')
% % ylabel('R')
% % view(0, 90)
% %
% already done:
figure; hold on; axis image
xlabel('L')
ylabel('R')
scatter(Lx(:), Ry(:), 200, Z(:), 'filled', 'MarkerEdgeColor', 'k')
colormap(bluewhitered(256)), cb = colorbar;
cb.TickLabels = num2str((cb.Ticks+meanFR(zero_joint))', '%2.1f');
xlim([-15 15])
ylim([-15 15])
set(gca, 'TickDir', 'out')
title(sprintf('linear sum of FR of either antenna (divided by 2)\nfly %d', T.flynum(t)), 'Interpreter', 'none')
export_fig(fullfile(scatfold, sprintf('linSum_scatter_%d.pdf', T.flynum(t))))
%% plot interpolation
figure;
subplot(1,2,1)
xlabel('L (deg)')
ylabel('R (deg)')
h = surf(Xq,Yq,Vq);
az = 0;
el = 90;
view(az, el);
% ylim([min(aL), max(aL)])
% xlim([min(aL), max(aL)])
xlim([-15 15])
ylim([-15 15])
axis square
a = gca;
a.XAxis.Visible = 'off';
a.YAxis.Visible = 'off';
a.XGrid = 'off';
a.YGrid = 'off';
h.EdgeColor = 'none';
colormap(bluewhitered(256)), cb = colorbar;
cb.TickLabels = num2str((cb.Ticks+meanFR(zero_joint))', '%2.1f');
cb.Label.String = '(Hz)';
title(sprintf('interp from single antenna data - fly %d',T.flynum(t)), 'Interpreter', 'none')
% export_fig(fullfile(scatfold, sprintf('interp_linSum_scatter_%d.pdf', T.flynum(t))))
subplot(1,2,2)
V = meanFR'-meanFR(zero_joint);
F = scatteredInterpolant(aL(:),aR(:),V);
% F.Method = 'linear';
% ExtrapolationMethod = 'nearest';
F.Method = 'natural';
ExtrapolationMethod = 'nearest';
[Xq,Yq] = meshgrid(min(aL):0.25:max(aL));
Vq = F(Xq, Yq);
xlabel('L (deg)')
ylabel('R (deg)')
h = surf(Xq,Yq,Vq);
az = 0;
el = 90;
view(az, el);
% ylim([min(aL), max(aL)])
% xlim([min(aL), max(aL)])
xlim([-15 15])
ylim([-15 15])
axis square
a = gca;
a.XAxis.Visible = 'off';
a.YAxis.Visible = 'off';
a.XGrid = 'off';
a.YGrid = 'off';
h.EdgeColor = 'none';
colormap(bluewhitered(256)), cb = colorbar;
cb.TickLabels = num2str((cb.Ticks+meanFR(zero_joint))', '%2.1f');
cb.Label.String = '(Hz)';
title('interpolation of joint-antenna recorded data', 'Interpreter', 'none')
export_fig(fullfile(scatfold, sprintf('interp_2compare_%d.pdf', T.flynum(t))))
end