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palm_saveall.m
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palm_saveall.m
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function palm_saveall(plm,opts)
% Save most of the outputs from PALM.
%
% _____________________________________
% Anderson M. Winkler
% FMRIB / University of Oxford
% Oct/2014
% http://brainder.org
% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
% PALM -- Permutation Analysis of Linear Models
% Copyright (C) 2015 Anderson M. Winkler
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% any later version.
%
% This program is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with this program. If not, see <http://www.gnu.org/licenses/>.
% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
% For the MV and NPC methods in which the most significant stats are the
% smallest, rather than the largest, use reverse comparisons.
if opts.NPC,
if plm.npcrev,
npcextr = @min;
else
npcextr = @max;
end
end
% For the "noperm" approximation, the statistic didn't have to be saved
% that early, since it's all pretty fast. Save it now then.
if opts.accel.noperm,
if opts.saveunivariate,
for y = 1:plm.nY,
if opts.designperinput, loopM = y; else, loopM = 1:plm.nM; end
for m = loopM,
for c = 1:plm.nC(m),
palm_quicksave(plm.G{y}{m}{c},0,opts,plm,y,m,c, ...
sprintf('%s',opts.o,plm.Ykindstr{y},plm.Gname{m}{c},plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
end
end
if opts.MV,
for m = 1:plm.nM,
for c = 1:plm.nC(m),
palm_quicksave(plm.Q{m}{c},0,opts,plm,[],m,c, ...
sprintf('%s',opts.o,plm.Ykindstr{1},plm.mvstr,plm.Qname{m}{c},plm.mstr{m},plm.cstr{m}{c}));
end
end
end
end
% Start with the uncorrected, but don't save them yet.
% They'll be used later for the FDR.
fprintf('Computing p-values.\n');
if opts.saveuncorrected,
for y = 1:plm.nY,
if opts.designperinput, loopM = y; else, loopM = 1:plm.nM; end
for m = loopM,
for c = 1:plm.nC(m),
if opts.accel.negbin,
idx = plm.Gpperm{y}{m}{c} == opts.accel.negbin;
plm.Gpperm{y}{m}{c}( idx) = (plm.Gpperm{y}{m}{c}( idx) )./(plm.Gppermp{y}{m}{c}( idx)); % Haldane (1945), but need to add 1 to num and den, see Besag & Clifford (1991).
plm.Gpperm{y}{m}{c}(~idx) = (plm.Gpperm{y}{m}{c}(~idx) + 1)./plm.nP{m}(c); % the unpermuted isn't counted here, hence the +1. Also, this is the same as if dividing by (plm.Gppermp{y}{m}{c}(~idx) + 1)
elseif opts.accel.tail,
for t = 1:plm.Ysiz(y),
plm.Gpperm{y}{m}{c}(1,t) = palm_pareto(plm.G{y}{m}{c}(1,t),plm.Gperms{y}{m}{c}(:,t),false,opts.accel.tail_thr,opts.accel.G1out);
end
elseif opts.accel.gamma,
for t = 1:plm.Ysiz(y),
plm.Gpperm{y}{m}{c}(1,t) = approxgamma(plm.G{y}{m}{c}(1,t),plm.Gperms{y}{m}{c}(:,t),false,1/plm.nP{m}(c),opts.accel.G1out);
end
elseif ~ opts.accel.noperm, % the "noperm" case is already treated
plm.Gpperm{y}{m}{c} = plm.Gpperm{y}{m}{c}/plm.nP{m}(c);
end
end
end
end
if opts.tfce.uni.do,
for y = 1:plm.nY,
if opts.designperinput, loopM = y; else, loopM = 1:plm.nM; end
for m = loopM,
for c = 1:plm.nC(m),
if opts.accel.tail,
for t = 1:plm.Ysiz(y),
plm.Gtfcepperm{y}{m}{c}(1,t) = palm_pareto(plm.Gtfce{y}{m}{c}(1,t),plm.Gtfceperms{y}{m}{c}(:,t),false,opts.accel.tail_thr,opts.accel.G1out);
end
elseif opts.accel.gamma,
for t = 1:plm.Ysiz(y),
plm.Gtfcepperm{y}{m}{c}(1,t) = approxgamma(plm.Gtfce{y}{m}{c}(1,t),plm.Gtfceperms{y}{m}{c}(:,t),false,1/plm.nP{m}(c),opts.accel.G1out);
end
else
plm.Gtfcepperm{y}{m}{c} = plm.Gtfcepperm{y}{m}{c}/plm.nP{m}(c);
end
end
end
end
end
if opts.NPC,
if opts.npcmod && ~ opts.npccon,
if opts.designperinput, loopM = 1; else, loopM = 1:plm.nM; end
for m = loopM,
for c = 1:plm.nC(m),
if opts.accel.tail,
for t = 1:plm.Ysiz(1),
plm.Tpperm{m}{c}(1,t) = palm_pareto(plm.T{m}{c}(1,t),plm.Tperms{m}{c}(:,t),plm.npcrev,opts.accel.tail_thr,opts.accel.G1out);
end
elseif opts.accel.gamma,
for t = 1:plm.Ysiz(1),
plm.Tpperm{m}{c}(1,t) = approxgamma(plm.T{m}{c}(1,t),plm.Tperms{m}{c}(:,t),plm.npcrev,1/plm.nP{m}(c),opts.accel.G1out);
end
else
plm.Tpperm{m}{c} = plm.Tpperm{m}{c}/plm.nP{m}(c);
end
end
end
if opts.tfce.npc.do,
for m = loopM,
for c = 1:plm.nC(m),
if opts.accel.tail,
for t = 1:plm.Ysiz(1),
plm.Ttfcepperm{m}{c}(1,t) = palm_pareto(plm.Ttfce{m}{c}(1,t),plm.Ttfceperms{m}{c}(:,t),false,opts.accel.tail_thr,opts.accel.G1out);
end
elseif opts.accel.gamma,
for t = 1:plm.Ysiz(1),
plm.Ttfcepperm{m}{c}(1,t) = approxgamma(plm.Ttfce{m}{c}(1,t),plm.Ttfceperms{m}{c}(:,t),false,1/plm.nP{m}(c),opts.accel.G1out);
end
else
plm.Ttfcepperm{m}{c} = plm.Ttfcepperm{m}{c}/plm.nP{m}(c);
end
end
end
end
elseif opts.npccon,
for j = 1:numel(plm.Tmax),
if opts.accel.tail,
for t = 1:plm.Ysiz(1),
plm.Tpperm{j}(1,t) = palm_pareto(plm.T{j}(1,t),plm.Tperms{j}(:,t),plm.npcrev,opts.accel.tail_thr,opts.accel.G1out);
end
elseif opts.accel.gamma,
for t = 1:plm.Ysiz(1),
plm.Tpperm{j}(1,t) = approxgamma(plm.T{j}(1,t),plm.Tperms{j}(:,t),plm.npcrev,1/plm.nP{1}(1),opts.accel.G1out);
end
else
plm.Tpperm{j} = plm.Tpperm{j}/size(plm.Tmax{j},1);
end
end
if opts.tfce.npc.do,
for j = 1:numel(plm.Tmax),
if opts.accel.tail,
for t = 1:plm.Ysiz(1),
plm.Ttfcepperm{j}(1,t) = palm_pareto(plm.Ttfce{j}(1,t),plm.Ttfceperms{j}(:,t),false,opts.accel.tail_thr,opts.accel.G1out);
end
elseif opts.accel.gamma,
for t = 1:plm.Ysiz(1),
plm.Ttfcepperm{j}(1,t) = approxgamma(plm.Ttfce{j}(1,t),plm.Ttfceperms{j}(:,t),false,1/plm.nP{1}(1),opts.accel.G1out);
end
else
plm.Ttfcepperm{j} = plm.Ttfcepperm{j}/size(plm.Ttfcemax{j},1);
end
end
end
end
end
if opts.MV || opts.CCA || opts.PLS,
for m = 1:plm.nM,
for c = 1:plm.nC(m),
if opts.accel.negbin,
idx = plm.Qpperm{m}{c} == opts.accel.negbin;
plm.Qpperm{m}{c}( idx) = (plm.Qpperm{m}{c}( idx) - 1)./(plm.Qppermp{m}{c}( idx) - 1); % Haldane (1945)
plm.Qpperm{m}{c}(~idx) = (plm.Qpperm{m}{c}(~idx) + 1)./plm.nP{m}(c); % same as if dividing by (plm.Qppermp{m}{c}(~idx) + 1)
elseif opts.accel.tail,
for t = 1:plm.Ysiz(1),
plm.Qpperm{m}{c}(1,t) = palm_pareto(plm.Q{m}{c}(1,t),plm.Qperms{m}{c}(:,t),plm.mvrev{m}{c},opts.accel.tail_thr,opts.accel.G1out);
end
elseif opts.accel.gamma,
for t = 1:plm.Ysiz(1),
plm.Qpperm{m}{c}(1,t) = approxgamma(plm.Q{m}{c}(1,t),plm.Qperms{m}{c}(:,t),plm.mvrev{m}{c},1/plm.nP{m}(c),opts.accel.G1out);
end
elseif ~ opts.accel.noperm, % the "noperm" case is already treated
plm.Qpperm{m}{c} = plm.Qpperm{m}{c}/plm.nP{m}(c);
end
end
end
if opts.tfce.mv.do,
for m = 1:plm.nM,
for c = 1:plm.nC(m),
if opts.accel.tail,
for t = 1:plm.Ysiz(1),
plm.Qtfcepperm{m}{c}(1,t) = palm_pareto(plm.Qtfce{m}{c}(1,t),plm.Qtfceperms{m}{c}(:,t),false,opts.accel.tail_thr,opts.accel.G1out);
end
elseif opts.accel.gamma,
for t = 1:plm.Ysiz(1),
plm.Qtfcepperm{m}{c}(1,t) = approxgamma(plm.Qtfce{m}{c}(1,t),plm.Qtfceperms{m}{c}(:,t),false,1/plm.nP{m}(c),opts.accel.G1out);
end
else
plm.Qtfcepperm{m}{c} = plm.Qtfcepperm{m}{c}/plm.nP{m}(c);
end
end
end
end
end
end
% Save uncorrected & FWER-corrected within modality for this contrast.
if opts.saveunivariate,
fprintf('Saving p-values (uncorrected, and corrected within modality and within contrast).\n');
for y = 1:plm.nY,
if opts.designperinput, loopM = y; else, loopM = 1:plm.nM; end
for m = loopM,
for c = 1:plm.nC(m),
% Only permutation p-value and its FDR ajustment are saved in the negative binomial mode.
if opts.accel.negbin,
% Permutation p-value, uncorrected (the -nouncorrected
% is caught in palm_takeargs.m already)
palm_quicksave(plm.Gpperm{y}{m}{c},1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,plm.Ykindstr{y},plm.Gname{m}{c},'_uncp',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
% Permutation p-value, FDR adjusted
if opts.FDR,
palm_quicksave(fastfdr(plm.Gpperm{y}{m}{c}),1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,plm.Ykindstr{y},plm.Gname{m}{c},'_fdrp',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
else
% Permutation p-value
if opts.saveuncorrected,
palm_quicksave(plm.Gpperm{y}{m}{c},1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,plm.Ykindstr{y},plm.Gname{m}{c},'_uncp',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
% FWER-corrected
if opts.accel.tail,
Ptosave = palm_pareto(plm.G{y}{m}{c},plm.Gmax{y}{m}{c},false,opts.accel.tail_thr,opts.accel.G1out);
elseif opts.accel.noperm,
Ptosave = [];
elseif opts.accel.gamma,
Ptosave = approxgamma(plm.G{y}{m}{c},plm.Gmax{y}{m}{c},false,1/plm.nP{m}(c),opts.accel.G1out);
else
Ptosave = palm_datapval(plm.G{y}{m}{c},plm.Gmax{y}{m}{c},false);
end
palm_quicksave( ...
Ptosave,1,opts,plm,y,m,c,...
sprintf('%s',opts.o,plm.Ykindstr{y},plm.Gname{m}{c},'_fwep',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
% Save the distribution of the maximum statistic
if opts.savemax,
dlmwrite(sprintf('%s',opts.o,plm.Ykindstr{y},plm.Gname{m}{c},'_max',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c},'.csv'),plm.Gmax{y}{m}{c})
end
% Permutation p-value, FDR adjusted
if opts.FDR,
palm_quicksave(fastfdr(plm.Gpperm{y}{m}{c}),1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,plm.Ykindstr{y},plm.Gname{m}{c},'_fdrp',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
% Cluster statistic results.
if opts.cluster.uni.do,
% Cluster statistic.
palm_quicksave(plm.Gclu{y}{m}{c},0,opts,plm,y,m,c, ...
sprintf('%s',opts.o,opts.cluster.str,plm.Gname{m}{c},plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
% Cluster statistic FWER p-value
if opts.accel.tail,
Ptosave = palm_pareto(plm.Gclu{y}{m}{c},plm.Gclumax{y}{m}{c},false,opts.accel.tail_thr,opts.accel.G1out);
elseif opts.accel.gamma,
Ptosave = approxgamma(plm.Gclu{y}{m}{c},plm.Gclumax{y}{m}{c},false,1/plm.nP{m}(c),opts.accel.G1out);
else
Ptosave = palm_datapval(plm.Gclu{y}{m}{c},plm.Gclumax{y}{m}{c},false);
end
palm_quicksave( ...
Ptosave,1,opts,plm,y,m,c,...
sprintf('%s',opts.o,opts.cluster.str,plm.Gname{m}{c},'_fwep',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
% Save the distribution of the maximum statistic
if opts.savemax,
dlmwrite(sprintf('%s',opts.o,opts.cluster.str,plm.Gname{m}{c},'_max',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c},'.csv'),plm.Gclumax{y}{m}{c})
end
end
% TFCE results
if opts.tfce.uni.do,
% TFCE statistic
palm_quicksave(plm.Gtfce{y}{m}{c},0,opts,plm,y,m,c, ...
sprintf('%s',opts.o,opts.tfce.str,plm.Gname{m}{c},plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
% TFCE p-value
if opts.saveuncorrected,
palm_quicksave(plm.Gtfcepperm{y}{m}{c},1,opts,plm,y,m,c,...
sprintf('%s',opts.o,opts.tfce.str,plm.Gname{m}{c},'_uncp',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
% TFCE FWER-corrected within modality and contrast.
if opts.accel.tail,
Ptosave = palm_pareto(plm.Gtfce{y}{m}{c},plm.Gtfcemax{y}{m}{c},false,opts.accel.tail_thr,opts.accel.G1out);
elseif opts.accel.gamma,
Ptosave = approxgamma(plm.Gtfce{y}{m}{c},plm.Gtfcemax{y}{m}{c},false,1/plm.nP{m}(c),opts.accel.G1out);
else
Ptosave = palm_datapval(plm.Gtfce{y}{m}{c},plm.Gtfcemax{y}{m}{c},false);
end
palm_quicksave( ...
Ptosave,1,opts,plm,y,m,c,...
sprintf('%s',opts.o,opts.tfce.str,plm.Gname{m}{c},'_fwep',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
% Save the distribution of the maximum statistic
if opts.savemax,
dlmwrite(sprintf('%s',opts.o,opts.tfce.str,plm.Gname{m}{c},'_max',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c},'.csv'),plm.Gtfcemax{y}{m}{c})
end
% TFCE p-value, FDR adjusted.
if opts.FDR,
palm_quicksave(fastfdr(plm.Gtfcepperm{y}{m}{c}),1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,opts.tfce.str,plm.Gname{m}{c},'_fdrp',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
end
% Parametric p-value and its FDR adjustment
if opts.savepara,
if opts.saveuncorrected,
P = palm_quicksave(plm.G{y}{m}{c},2,opts,plm,y,m,c,...
sprintf('%s',opts.o,plm.Ykindstr{y},plm.Gname{m}{c},'_uncparap',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
if opts.FDR,
palm_quicksave(fastfdr(P),1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,plm.Ykindstr{y},plm.Gname{m}{c},'_fdrparap',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
end
end
end
% Save FWER & FDR corrected across modalities.
if opts.corrmod,
fprintf('Saving p-values (corrected across modalities).\n')
% FDR correction (non-spatial stats)
if opts.FDR,
if opts.designperinput,
for c = 1:plm.nC(1),
pmerged = zeros(sum(plm.Ysiz),1);
for y = 1:plm.nY,
m = y;
pmerged(plm.Ycumsiz(y)+1:plm.Ycumsiz(y+1)) = plm.Gpperm{y}{m}{c};
end
pfdradj = fastfdr(pmerged);
for y = 1:plm.nY,
m = y;
palm_quicksave(pfdradj(plm.Ycumsiz(y)+1:plm.Ycumsiz(y+1)),1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,plm.Ykindstr{y},plm.Gname{m}{c},'_mfdrp',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
else
for m = 1:plm.nM,
for c = 1:plm.nC(m),
pmerged = zeros(sum(plm.Ysiz),1);
for y = 1:plm.nY,
pmerged(plm.Ycumsiz(y)+1:plm.Ycumsiz(y+1)) = plm.Gpperm{y}{m}{c};
end
pfdradj = fastfdr(pmerged);
for y = 1:plm.nY,
palm_quicksave(pfdradj(plm.Ycumsiz(y)+1:plm.Ycumsiz(y+1)),1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,plm.Ykindstr{y},plm.Gname{m}{c},'_mfdrp',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
end
end
end
if ~ opts.accel.negbin,
% FWER correction (non-spatial stats)
if opts.designperinput,
for c = 1:plm.nC(1),
distmax = zeros(plm.nP{1}(c),plm.nY);
for y = 1:plm.nY,
m = y;
distmax(:,y) = plm.Gmax{y}{m}{c};
end
distmax = max(distmax,[],2);
for y = 1:plm.nY,
m = y;
if opts.accel.tail,
Ptosave = palm_pareto(plm.G{y}{m}{c},distmax,false,opts.accel.tail_thr,opts.accel.G1out);
elseif opts.accel.gamma,
Ptosave = approxgamma(plm.G{y}{m}{c},distmax,false,1/plm.nP{1}(c),opts.accel.G1out);
else
Ptosave = palm_datapval(plm.G{y}{m}{c},distmax,false);
end
palm_quicksave( ...
Ptosave,1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,plm.Ykindstr{y},plm.Gname{m}{c},'_mfwep',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
else
for m = 1:plm.nM,
for c = 1:plm.nC(m),
distmax = zeros(plm.nP{m}(c),plm.nY);
for y = 1:plm.nY,
distmax(:,y) = plm.Gmax{y}{m}{c};
end
distmax = max(distmax,[],2);
for y = 1:plm.nY,
if opts.accel.tail,
Ptosave = palm_pareto(plm.G{y}{m}{c},distmax,false,opts.accel.tail_thr,opts.accel.G1out);
elseif opts.accel.gamma,
Ptosave = approxgamma(plm.G{y}{m}{c},distmax,false,1/plm.nP{m}(c),opts.accel.G1out);
else
Ptosave = palm_datapval(plm.G{y}{m}{c},distmax,false);
end
palm_quicksave( ...
Ptosave,1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,plm.Ykindstr{y},plm.Gname{m}{c},'_mfwep',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
end
end
% Cluster statistic
if opts.cluster.uni.do && ...
(all(plm.Yisvol) || all(plm.Yissrf)),
if opts.designperinput,
for c = 1:plm.nC(1),
distmax = zeros(plm.nP{1}(c),plm.nY);
for y = 1:plm.nY,
m = y;
distmax(:,y) = plm.Gclumax{y}{m}{c};
end
distmax = max(distmax,[],2);
for y = 1:plm.nY,
m = y;
if opts.accel.tail,
Ptosave = palm_pareto(plm.Gclu{y}{m}{c},distmax,false,opts.accel.tail_thr,opts.accel.G1out);
elseif opts.accel.gamma,
Ptosave = approxgamma(plm.Gclu{y}{m}{c},distmax,false,1/plm.nP{1}(c),opts.accel.G1out);
else
Ptosave = palm_datapval(plm.Gclu{y}{m}{c},distmax,false);
end
palm_quicksave( ...
Ptosave,1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,opts.cluster.str,plm.Gname{m}{c},'_mfwep',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
else
for m = 1:plm.nM,
for c = 1:plm.nC(m),
distmax = zeros(plm.nP{m}(c),plm.nY);
for y = 1:plm.nY,
distmax(:,y) = plm.Gclumax{y}{m}{c};
end
distmax = max(distmax,[],2);
for y = 1:plm.nY,
if opts.accel.tail,
Ptosave = palm_pareto(plm.Gclu{y}{m}{c},distmax,false,opts.accel.tail_thr,opts.accel.G1out);
elseif opts.accel.gamma,
Ptosave = approxgamma(plm.Gclu{y}{m}{c},distmax,false,1/plm.nP{m}(c),opts.accel.G1out);
else
Ptosave = palm_datapval(plm.Gclu{y}{m}{c},distmax,false);
end
palm_quicksave( ...
Ptosave,1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,opts.cluster.str,plm.Gname{m}{c},'_mfwep',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
end
end
end
% TFCE
if opts.tfce.uni.do && ...
(all(plm.Yisvol) || all(plm.Yissrf)), %#ok<*NOCOL>
if opts.designperinput,
for c = 1:plm.nC(1),
distmax = zeros(plm.nP{1}(c),plm.nY);
for y = 1:plm.nY,
m = y;
distmax(:,y) = plm.Gtfcemax{y}{m}{c};
end
distmax = max(distmax,[],2);
for y = 1:plm.nY,
m = y;
if opts.accel.tail,
Ptosave = palm_pareto(plm.Gtfce{y}{m}{c},distmax,false,opts.accel.tail_thr,opts.accel.G1out);
elseif opts.accel.gamma,
Ptosave = approxgamma(plm.Gtfce{y}{m}{c},distmax,false,1/plm.nP{1}(c),opts.accel.G1out);
else
Ptosave = palm_datapval(plm.Gtfce{y}{m}{c},distmax,false);
end
palm_quicksave( ...
Ptosave,1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,opts.tfce.str,plm.Gname{m}{c},'_mfwep',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
else
for m = 1:plm.nM,
for c = 1:plm.nC(m),
distmax = zeros(plm.nP{m}(c),plm.nY);
for y = 1:plm.nY,
distmax(:,y) = plm.Gtfcemax{y}{m}{c};
end
distmax = max(distmax,[],2);
for y = 1:plm.nY,
if opts.accel.tail,
Ptosave = palm_pareto(plm.Gtfce{y}{m}{c},distmax,false,opts.accel.tail_thr,opts.accel.G1out);
elseif opts.accel.gamma,
Ptosave = approxgamma(plm.Gtfce{y}{m}{c},distmax,false,1/plm.nP{m}(c),opts.accel.G1out);
else
Ptosave = palm_datapval(plm.Gtfce{y}{m}{c},distmax,false);
end
palm_quicksave( ...
Ptosave,1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,opts.tfce.str,plm.Gname{m}{c},'_mfwep',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
end
end
if opts.FDR,
if opts.designperinput,
for c = 1:plm.nC(1),
pmerged = zeros(sum(plm.Ysiz),1);
for y = 1:plm.nY,
m = y;
pmerged(plm.Ycumsiz(y)+1:plm.Ycumsiz(y+1)) = plm.Gtfcepperm{y}{m}{c};
end
pfdradj = fastfdr(pmerged);
for y = 1:plm.nY,
m = y;
palm_quicksave(pfdradj(plm.Ycumsiz(y)+1:plm.Ycumsiz(y+1)),1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,opts.tfce.str,plm.Gname{m}{c},'_mfdrp',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
else
for m = 1:plm.nM,
for c = 1:plm.nC(m),
pmerged = zeros(sum(plm.Ysiz),1);
for y = 1:plm.nY,
pmerged(plm.Ycumsiz(y)+1:plm.Ycumsiz(y+1)) = plm.Gtfcepperm{y}{m}{c};
end
pfdradj = fastfdr(pmerged);
for y = 1:plm.nY,
palm_quicksave(pfdradj(plm.Ycumsiz(y)+1:plm.Ycumsiz(y+1)),1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,opts.tfce.str,plm.Gname{m}{c},'_mfdrp',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
end
end
end
end
end
end
% Save FWER & FDR corrected across contrasts.
if opts.corrcon,
fprintf('Saving p-values (corrected across contrasts).\n');
% FDR correction (non-spatial stats)
if opts.FDR,
for y = 1:plm.nY,
if opts.designperinput,
loopM = y;
pmerged = zeros(plm.nC(1),plm.Ysiz(y));
else
loopM = 1:plm.nM;
pmerged = zeros(sum(plm.nC),plm.Ysiz(y));
end
j = 1;
for m = loopM,
for c = 1:plm.nC(m),
pmerged(j,:) = plm.Gpperm{y}{m}{c};
j = j + 1;
end
end
pfdradj = reshape(fastfdr(pmerged(:)),size(pmerged));
j = 1;
for m = loopM,
for c = 1:plm.nC(m),
palm_quicksave(pfdradj(j,:),1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,plm.Ykindstr{y},plm.Gname{m}{c},'_cfdrp',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
j = j + 1;
end
end
end
end
if ~ opts.accel.negbin,
% FWER correction (non-spatial stats)
for y = 1:plm.nY,
if opts.designperinput,
loopM = y;
distmax = zeros(plm.nP{1}(1),plm.nC(1));
else
loopM = 1:plm.nM;
distmax = zeros(plm.nP{1}(1),sum(plm.nC));
end
j = 1;
for m = loopM,
for c = 1:plm.nC(m),
distmax(:,j) = plm.Gmax{y}{m}{c};
j = j + 1;
end
end
distmax = max(distmax,[],2);
for m = loopM,
for c = 1:plm.nC(m),
if opts.accel.tail,
Ptosave = palm_pareto(plm.G{y}{m}{c},distmax,false,opts.accel.tail_thr,opts.accel.G1out);
elseif opts.accel.gamma,
Ptosave = approxgamma(plm.G{y}{m}{c},distmax,false,1/plm.nP{1}(1),opts.accel.G1out);
else
Ptosave = palm_datapval(plm.G{y}{m}{c},distmax,false);
end
palm_quicksave( ...
Ptosave,1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,plm.Ykindstr{y},plm.Gname{m}{c},'_cfwep',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
end
% Cluster statistic
if opts.cluster.uni.do,
for y = 1:plm.nY,
if opts.designperinput,
loopM = y;
distmax = zeros(plm.nP{1}(1),plm.nC(1));
else
loopM = 1:plm.nM;
distmax = zeros(plm.nP{1}(1),sum(plm.nC));
end
j = 1;
for m = loopM,
for c = 1:plm.nC(m),
distmax(:,j) = plm.Gclumax{y}{m}{c};
j = j + 1;
end
end
distmax = max(distmax,[],2);
for m = loopM,
for c = 1:plm.nC(m),
if opts.accel.tail,
Ptosave = palm_pareto(plm.Gclu{y}{m}{c},distmax,false,opts.accel.tail_thr,opts.accel.G1out);
elseif opts.accel.gamma,
Ptosave = approxgamma(plm.Gclu{y}{m}{c},distmax,false,1/plm.nP{1}(1),opts.accel.G1out);
else
Ptosave = palm_datapval(plm.Gclu{y}{m}{c},distmax,false);
end
palm_quicksave( ...
Ptosave,1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,opts.cluster.str,plm.Gname{m}{c},'_cfwep',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
end
end
% TFCE
if opts.tfce.uni.do,
for y = 1:plm.nY,
if opts.designperinput,
loopM = y;
distmax = zeros(plm.nP{1}(1),plm.nC(1));
else
loopM = 1:plm.nM;
distmax = zeros(plm.nP{1}(1),sum(plm.nC));
end
j = 1;
for m = loopM,
for c = 1:plm.nC(m),
distmax(:,j) = plm.Gtfcemax{y}{m}{c};
j = j + 1;
end
end
distmax = max(distmax,[],2);
for m = loopM,
for c = 1:plm.nC(m),
if opts.accel.tail,
Ptosave = palm_pareto(plm.Gtfce{y}{m}{c},distmax,false,opts.accel.tail_thr,opts.accel.G1out);
elseif opts.accel.gamma,
Ptosave = approxgamma(plm.Gtfce{y}{m}{c},distmax,false,1/plm.nP{1}(1),opts.accel.G1out);
else
Ptosave = palm_datapval(plm.Gtfce{y}{m}{c},distmax,false);
end
palm_quicksave( ...
Ptosave,1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,opts.tfce.str,plm.Gname{m}{c},'_cfwep',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
end
if opts.FDR,
for y = 1:plm.nY,
if opts.designperinput,
loopM = y;
pmerged = zeros(plm.nC(1),plm.Ysiz(y));
else
loopM = 1:plm.nM;
pmerged = zeros(sum(plm.nC),plm.Ysiz(y));
end
j = 1;
for m = loopM,
for c = 1:plm.nC(m),
pmerged(j,:) = plm.Gtfcepperm{y}{m}{c};
j = j + 1;
end
end
pfdradj = reshape(fastfdr(pmerged(:)),size(pmerged));
j = 1;
for m = loopM,
for c = 1:plm.nC(m),
palm_quicksave(pfdradj(j,:),1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,opts.tfce.str,plm.Gname{m}{c},'_cfdrp',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
j = j + 1;
end
end
end
end
end
end
end
% Save FWER & FDR corrected across modalities and contrasts.
if opts.corrmod && opts.corrcon,
fprintf('Saving p-values (corrected across modalities and contrasts).\n')
% FDR correction (non-spatial stats)
if opts.FDR,
if opts.designperinput,
pmerged = zeros(plm.nC(1),sum(plm.Ysiz));
else
pmerged = zeros(sum(plm.nC),sum(plm.Ysiz));
end
for y = 1:plm.nY,
j = 1;
if opts.designperinput, loopM = y; else, loopM = 1:plm.nM; end
for m = loopM,
for c = 1:plm.nC(m),
pmerged(j,plm.Ycumsiz(y)+1:plm.Ycumsiz(y+1)) = plm.Gpperm{y}{m}{c};
j = j + 1;
end
end
end
pfdradj = reshape(fastfdr(pmerged(:)),size(pmerged));
for y = 1:plm.nY,
if opts.designperinput, loopM = y; else, loopM = 1:plm.nM; end
for m = loopM,
for c = 1:plm.nC(m),
palm_quicksave(pfdradj(c,plm.Ycumsiz(y)+1:plm.Ycumsiz(y+1)),1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,plm.Ykindstr{y},plm.Gname{m}{c},'_mcfdrp',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
end
end
if ~ opts.accel.negbin,
% FWER correction (non-spatial stats)
if opts.designperinput,
distmax = zeros(plm.nP{1}(1),plm.nY*plm.nC(1));
else
distmax = zeros(plm.nP{1}(1),plm.nY*sum(plm.nC));
end
j = 1;
for y = 1:plm.nY,
if opts.designperinput, loopM = y; else, loopM = 1:plm.nM; end
for m = loopM,
for c = 1:plm.nC(m),
distmax(:,j) = plm.Gmax{y}{m}{c};
j = j + 1;
end
end
end
distmax = max(distmax,[],2);
for y = 1:plm.nY,
if opts.designperinput, loopM = y; else, loopM = 1:plm.nM; end
for m = loopM,
for c = 1:plm.nC(m),
if opts.accel.tail,
Ptosave = palm_pareto(plm.G{y}{m}{c},distmax,false,opts.accel.tail_thr,opts.accel.G1out);
elseif opts.accel.gamma,
Ptosave = approxgamma(plm.G{y}{m}{c},distmax,false,1/plm.nP{1}(1),opts.accel.G1out);
else
Ptosave = palm_datapval(plm.G{y}{m}{c},distmax,false);
end
palm_quicksave( ...
Ptosave,1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,plm.Ykindstr{y},plm.Gname{m}{c},'_mcfwep',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
end
% Cluster statistic
if opts.cluster.uni.do,
if opts.designperinput,
distmax = zeros(plm.nP{1}(1),plm.nY*plm.nC(1));
else
distmax = zeros(plm.nP{1}(1),plm.nY*sum(plm.nC));
end
j = 1;
for y = 1:plm.nY,
if opts.designperinput, loopM = y; else, loopM = 1:plm.nM; end
for m = loopM,
for c = 1:plm.nC(m),
distmax(:,j) = plm.Gclumax{y}{m}{c};
j = j + 1;
end
end
end
distmax = max(distmax,[],2);
for y = 1:plm.nY,
if opts.designperinput, loopM = y; else, loopM = 1:plm.nM; end
for m = loopM,
for c = 1:plm.nC(m),
if opts.accel.tail,
Ptosave = palm_pareto(plm.Gclu{y}{m}{c},distmax,false,opts.accel.tail_thr,opts.accel.G1out);
elseif opts.accel.gamma,
Ptosave = approxgamma(plm.Gclu{y}{m}{c},distmax,false,1/plm.nP{1}(1),opts.accel.G1out);
else
Ptosave = palm_datapval(plm.Gclu{y}{m}{c},distmax,false);
end
palm_quicksave( ...
Ptosave,1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,opts.cluster.str,plm.Gname{m}{c},'_mcfwep',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
end
end
% TFCE
if opts.tfce.uni.do,
if opts.designperinput,
distmax = zeros(plm.nP{1}(1),plm.nY*plm.nC(1));
else
distmax = zeros(plm.nP{1}(1),plm.nY*sum(plm.nC));
end
j = 1;
for y = 1:plm.nY,
if opts.designperinput, loopM = y; else, loopM = 1:plm.nM; end
for m = loopM,
for c = 1:plm.nC(m),
distmax(:,j) = plm.Gtfcemax{y}{m}{c};
j = j + 1;
end
end
end
distmax = max(distmax,[],2);
for y = 1:plm.nY,
if opts.designperinput, loopM = y; else, loopM = 1:plm.nM; end
for m = loopM,
for c = 1:plm.nC(m),
if opts.accel.tail,
Ptosave = palm_pareto(plm.Gtfce{y}{m}{c},distmax,false,opts.accel.tail_thr,opts.accel.G1out);
elseif opts.accel.gamma,
Ptosave = approxgamma(plm.Gtfce{y}{m}{c},distmax,false,1/plm.nP{1}(1),opts.accel.G1out);
else
Ptosave = palm_datapval(plm.Gtfce{y}{m}{c},distmax,false);
end
palm_quicksave( ...
Ptosave,1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,opts.tfce.str,plm.Gname{m}{c},'_mcfwep',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
end
if opts.FDR,
if opts.designperinput,
pmerged = zeros(plm.nC(1),sum(plm.Ysiz));
else
pmerged = zeros(sum(plm.nC),sum(plm.Ysiz));
end
for y = 1:plm.nY,
if opts.designperinput, loopM = y; else, loopM = 1:plm.nM; end
j = 1;
for m = loopM,
for c = 1:plm.nC(m),
pmerged(j,plm.Ycumsiz(y)+1:plm.Ycumsiz(y+1)) = plm.Gtfcepperm{y}{m}{c};
j = j + 1;
end
end
end
pfdradj = reshape(fastfdr(pmerged(:)),size(pmerged));
for y = 1:plm.nY,
if opts.designperinput, loopM = y; else, loopM = 1:plm.nM; end
for m = loopM,
for c = 1:plm.nC(m),
palm_quicksave(pfdradj(c,plm.Ycumsiz(y)+1:plm.Ycumsiz(y+1)),1,opts,plm,y,m,c, ...
sprintf('%s',opts.o,opts.tfce.str,plm.Gname{m}{c},'_mcfdrp',plm.ystr{y},plm.mstr{m},plm.cstr{m}{c}));
end
end
end
end
end
end
end
end
% Save NPC between modalities, corrected within contrasts
if opts.npcmod && ~ opts.npccon,
fprintf('Saving p-values for NPC between modalities (uncorrected and corrected within contrasts).\n');
if opts.designperinput, loopM = 1; else, loopM = 1:plm.nM; end
for m = loopM,
if opts.designperinput, mstr = ''; else, mstr = plm.mstr{m}; end
for c = 1:plm.nC(m),
% NPC p-value
if opts.saveuncorrected,
palm_quicksave(plm.Tpperm{m}{c},1,opts,plm,[],m,c, ...
sprintf('%s',opts.o,plm.Ykindstr{1},plm.npcstr,plm.Tname,'_uncp',mstr,plm.cstr{m}{c}));
end
% NPC FWER-corrected
if opts.accel.tail,
Ptosave = palm_pareto(plm.T{m}{c},plm.Tmax{m}{c},plm.npcrev,opts.accel.tail_thr,opts.accel.G1out);
elseif opts.accel.gamma,
Ptosave = approxgamma(plm.T{m}{c},plm.Tmax{m}{c},plm.npcrev,1/plm.nP{m}(c),opts.accel.G1out);
else
Ptosave = palm_datapval(plm.T{m}{c},plm.Tmax{m}{c},plm.npcrev);
end
palm_quicksave( ...
Ptosave,1,opts,plm,[],m,c, ...
sprintf('%s',opts.o,plm.Ykindstr{1},plm.npcstr,plm.Tname,'_fwep',mstr,plm.cstr{m}{c}));
% Save the distribution of the maximum statistic
if opts.savemax,
dlmwrite(sprintf('%s',opts.o,plm.Ykindstr{1},plm.npcstr,plm.Tname,'_max',mstr,plm.cstr{m}{c},'.csv'),plm.Tmax{m}{c})
end
% NPC FDR
if opts.FDR,
palm_quicksave(fastfdr(plm.Tpperm{m}{c}),1,opts,plm,[],m,c, ...
sprintf('%s',opts.o,plm.Ykindstr{1},plm.npcstr,plm.Tname,'_fdrp',mstr,plm.cstr{m}{c}));
end
% Parametric combined pvalue
if opts.savepara && ~ plm.nonpcppara && opts.saveuncorrected,
palm_quicksave(plm.Tppara{m}{c},1,opts,plm,[],m,c, ...
sprintf('%s',opts.o,plm.Ykindstr{1},plm.npcstr,plm.Tname,'_uncparap',mstr,plm.cstr{m}{c}));
end
% Cluster statistic NPC results.
if opts.cluster.npc.do,
% Cluster statistic.
palm_quicksave(plm.Tclu{m}{c},0,opts,plm,[],m,c, ...
sprintf('%s',opts.o,opts.cluster.str,plm.npcstr,plm.Tname,mstr,plm.cstr{m}{c}));
% Cluster statistic FWER p-value
if opts.accel.tail,
Ptosave = palm_pareto(plm.Tclu{m}{c},plm.Tclumax{m}{c},false,opts.accel.tail_thr,opts.accel.G1out);
elseif opts.accel.gamma,
Ptosave = approxgamma(plm.Tclu{m}{c},plm.Tclumax{m}{c},false,1/plm.nP{m}(c),opts.accel.G1out);
else
Ptosave = palm_datapval(plm.Tclu{m}{c},plm.Tclumax{m}{c},false);
end
palm_quicksave( ...
Ptosave,1,opts,plm,y,m,c,...
sprintf('%s',opts.o,opts.cluster.str,plm.npcstr,plm.Tname,'_fwep',mstr,plm.cstr{m}{c}));
% Save the distribution of the maximum statistic
if opts.savemax,
dlmwrite(sprintf('%s',opts.o,opts.cluster.str,plm.npcstr,plm.Tname,'_max',mstr,plm.cstr{m}{c},'.csv'),plm.Tclumax{m}{c})
end
end
% TFCE NPC results.
if opts.tfce.npc.do,
% TFCE statistic.
palm_quicksave(plm.Ttfce{m}{c},0,opts,plm,[],m,c, ...
sprintf('%s',opts.o,opts.tfce.str,plm.npcstr,plm.Tname,mstr,plm.cstr{m}{c}));
% TFCE p-value
if opts.saveuncorrected,
palm_quicksave(plm.Ttfcepperm{m}{c},1,opts,plm,[],m,c,...
sprintf('%s',opts.o,opts.tfce.str,plm.npcstr,plm.Tname,'_uncp',mstr,plm.cstr{m}{c}));
end
% TFCE FWER p-value
if opts.accel.tail,
Ptosave = palm_pareto(plm.Ttfce{m}{c},plm.Ttfcemax{m}{c},false,opts.accel.tail_thr,opts.accel.G1out);
elseif opts.accel.gamma,
Ptosave = approxgamma(plm.Ttfce{m}{c},plm.Ttfcemax{m}{c},false,1/plm.nP{m}(c),opts.accel.G1out);
else
Ptosave = palm_datapval(plm.Ttfce{m}{c},plm.Ttfcemax{m}{c},false);
end
palm_quicksave( ...
Ptosave,1,opts,plm,[],m,c,...
sprintf('%s',opts.o,opts.tfce.str,plm.npcstr,plm.Tname,'_fwep',mstr,plm.cstr{m}{c}));
% Save the distribution of the maximum statistic