stepan
/
dynare
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

GSA: remove some unused functions and move other to inline ones

new-samplers
Johannes Pfeifer 2023-12-02 12:52:01 +01:00 committed by Sébastien Villemot
parent 19b2619d06
commit 9efb784763
No known key found for this signature in database
GPG Key ID: 2CECE9350ECEBE4A
13 changed files with 92 additions and 484 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
license.txt
View File

@ -171,16 +171,13 @@ Comment: Written by Jessica Cariboni and Francesca Campolongo
Files: matlab/gsa/cumplot.m
matlab/gsa/filt_mc_.m
matlab/gsa/gsa_plotmatrix.m
matlab/gsa/gsa_skewness.m
matlab/gsa/log_trans_.m
matlab/gsa/map_calibration.m
matlab/gsa/map_ident_.m
matlab/gsa/mcf_analysis.m
matlab/gsa/myboxplot.m
matlab/gsa/myprctilecol.m
matlab/gsa/prior_draw_gsa.m
matlab/gsa/read_data.m
matlab/gsa/redform_map.m
matlab/gsa/redform_screen.m
matlab/gsa/scatter_mcf.m
@ -191,9 +188,8 @@ Files: matlab/gsa/cumplot.m
matlab/gsa/stand_.m
matlab/gsa/tcrit.m
matlab/gsa/teff.m
matlab/gsa/trank.m
Copyright: 2011-2018 European Commission
2011-2018 Dynare Team
2011-2023 Dynare Team
License: GPL-3+
Files: matlab/gsa/pick.m

13
matlab/gsa/cumplot.m
View File

@ -1,5 +1,10 @@
function h = cumplot(x)
%function h =cumplot(x)
% Inputs:
% - x [double] data series
%
% Outputs:
% - h [handle] figure handle
% Written by Marco Ratto
% Joint Research Centre, The European Commission,
@ -26,9 +31,5 @@ function h = cumplot(x)
n=length(x);
x=[-inf; sort(x); Inf];
y=[0:n n]./n;
h0 = stairs(x,y);
grid on,
if nargout
h=h0;
end
h = stairs(x,y);
grid on

99
matlab/gsa/gsa_plotmatrix.m
View File

@ -1,99 +0,0 @@
function gsa_plotmatrix(type,varargin)
% function gsa_plotmatrix(type,varargin)
% extended version of the standard MATLAB plotmatrix
%
% Written by Marco Ratto
% Joint Research Centre, The European Commission,
% marco.ratto@ec.europa.eu
% Copyright © 2011-2012 European Commission
% Copyright © 2011-2017 Dynare Team
%
% This file is part of Dynare.
%
% Dynare 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
% (at your option) any later version.
%
% Dynare 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 Dynare. If not, see <https://www.gnu.org/licenses/>.
global bayestopt_ options_ M_
RootDirectoryName = CheckPath('gsa',M_.dname);
if options_.opt_gsa.pprior
load([ RootDirectoryName filesep M_.fname '_prior.mat'],'lpmat0','lpmat','istable','iunstable','iindeterm','iwrong')
else
load([ RootDirectoryName filesep M_.fname '_mc.mat'],'lpmat0','lpmat','istable','iunstable','iindeterm','iwrong')
eval(['load ' options_.mode_file ' xparam1;']');
end
iexplosive = iunstable(~ismember(iunstable,[iindeterm;iwrong]));
switch type
case 'all'
x=[lpmat0 lpmat];
NumberOfDraws=size(x,1);
B=NumberOfDraws;
case 'stable'
x=[lpmat0(istable,:) lpmat(istable,:)];
NumberOfDraws=size(x,1);
B=NumberOfDraws;
case 'nosolution'
x=[lpmat0(iunstable,:) lpmat(iunstable,:)];
NumberOfDraws=size(x,1);
B=NumberOfDraws;
case 'unstable'
x=[lpmat0(iexplosive,:) lpmat(iexplosive,:)];
NumberOfDraws=size(x,1);
B=NumberOfDraws;
case 'indeterm'
x=[lpmat0(iindeterm,:) lpmat(iindeterm,:)];
NumberOfDraws=size(x,1);
B=NumberOfDraws;
case 'wrong'
x=[lpmat0(iwrong,:) lpmat(iwrong,:)];
NumberOfDraws=size(x,1);
B=NumberOfDraws;
end
if isempty(x)
disp('Empty parameter set!')
return
end
for j=1:length(varargin)
jcol(j)=strmatch(varargin{j},bayestopt_.name,'exact');
end
[H,AX,BigA,P,PAx]=plotmatrix(x(:,jcol));
for j=1:length(varargin)
% axes(AX(1,j)), title(varargin{j})
% axes(AX(j,1)), ylabel(varargin{j})
% set(AX(1,j),'title',varargin{j}),
set(get(AX(j,1),'ylabel'),'string',varargin{j})
set(get(AX(end,j),'xlabel'),'string',varargin{j})
end
if options_.opt_gsa.pprior==0
xparam1=xparam1(jcol);
for j=1:length(varargin)
for i=1:j-1
axes(AX(j,i))
hold on, plot(xparam1(i),xparam1(j),'*r')
end
for i=j+1:length(varargin)
axes(AX(j,i))
hold on, plot(xparam1(i),xparam1(j),'*r')
end
end
end

10
matlab/gsa/map_ident_.m
View File

@ -365,3 +365,13 @@ if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
fprintf(fidTeX,'%% End Of TeX file. \n');
fclose(fidTeX);
end
function yr = trank(y)
% yr is the rank transformation of y
yr=NaN(size(y));
[nr, nc] = size(y);
for j=1:nc
[~, is]=sort(y(:,j));
yr(is,j)=[1:nr]'./nr;
end

113
matlab/gsa/myboxplot.m
View File

@ -1,12 +1,8 @@
function sout = myboxplot (data,notched,symbol,vertical,maxwhisker)
% sout = myboxplot (data,notched,symbol,vertical,maxwhisker)
% sout = myboxplot (data,notched,symbol,vertical,maxwhisker)
% Creates a box plot
% Written by Marco Ratto
% Joint Research Centre, The European Commission,
% marco.ratto@ec.europa.eu
% Copyright © 2012 European Commission
% Copyright © 2012-2017 Dynare Team
% Copyright © 2010-2023 Dynare Team
%
% This file is part of Dynare.
%
@ -23,18 +19,17 @@ function sout = myboxplot (data,notched,symbol,vertical,maxwhisker)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
% % % % endif
if nargin < 5 | isempty(maxwhisker), maxwhisker = 1.5; end
if nargin < 4 | isempty(vertical), vertical = 1; end
if nargin < 3 | isempty(symbol), symbol = ['+','o']; end
if nargin < 2 | isempty(notched), notched = 0; end
if nargin < 5 || isempty(maxwhisker), maxwhisker = 1.5; end
if nargin < 4 || isempty(vertical), vertical = 1; end
if nargin < 3 || isempty(symbol), symbol = ['+','o']; end
if nargin < 2 || isempty(notched), notched = 0; end
if length(symbol)==1, symbol(2)=symbol(1); end
if notched==1, notched=0.25; end
a=1-notched;
% ## figure out how many data sets we have
% % figure out how many data sets we have
if iscell(data)
nc = length(data);
else
@ -42,11 +37,11 @@ else
nc = size(data,2);
end
% ## compute statistics
% ## s will contain
% ## 1,5 min and max
% ## 2,3,4 1st, 2nd and 3rd quartile
% ## 6,7 lower and upper confidence intervals for median
% compute statistics
% s will contain
% 1,5 min and max
% 2,3,4 1st, 2nd and 3rd quartile
% 6,7 lower and upper confidence intervals for median
s = zeros(7,nc);
box = zeros(1,nc);
whisker_x = ones(2,1)*[1:nc,1:nc];
@ -57,44 +52,36 @@ outliers2_x = [];
outliers2_y = [];
for i=1:nc
% ## Get the next data set from the array or cell array
% Get the next data set from the array or cell array
if iscell(data)
col = data{i}(:);
else
col = data(:,i);
end
% ## Skip missing data
% Skip missing data
% % % % % % % col(isnan(col) | isna (col)) = [];
col(isnan(col)) = [];
% ## Remember the data length
% Remember the data length
nd = length(col);
box(i) = nd;
if (nd > 1)
% ## min,max and quartiles
% s(1:5,i) = statistics(col)(1:5);
% min,max and quartiles
s(1,i)=min(col);
s(5,i)=max(col);
s(2,i)=myprctilecol(col,25);
s(3,i)=myprctilecol(col,50);
s(4,i)=myprctilecol(col,75);
% ## confidence interval for the median
% confidence interval for the median
est = 1.57*(s(4,i)-s(2,i))/sqrt(nd);
s(6,i) = max([s(3,i)-est, s(2,i)]);
s(7,i) = min([s(3,i)+est, s(4,i)]);
% ## whiskers out to the last point within the desired inter-quartile range
% whiskers out to the last point within the desired inter-quartile range
IQR = maxwhisker*(s(4,i)-s(2,i));
whisker_y(:,i) = [min(col(col >= s(2,i)-IQR)); s(2,i)];
whisker_y(:,nc+i) = [max(col(col <= s(4,i)+IQR)); s(4,i)];
% ## outliers beyond 1 and 2 inter-quartile ranges
% outliers beyond 1 and 2 inter-quartile ranges
outliers = col((col < s(2,i)-IQR & col >= s(2,i)-2*IQR) | (col > s(4,i)+IQR & col <= s(4,i)+2*IQR));
outliers2 = col(col < s(2,i)-2*IQR | col > s(4,i)+2*IQR);
outliers_x = [outliers_x; i*ones(size(outliers))];
@ -102,41 +89,37 @@ for i=1:nc
outliers2_x = [outliers2_x; i*ones(size(outliers2))];
outliers2_y = [outliers2_y; outliers2];
elseif (nd == 1)
% ## all statistics collapse to the value of the point
% all statistics collapse to the value of the point
s(:,i) = col;
% ## single point data sets are plotted as outliers.
% single point data sets are plotted as outliers.
outliers_x = [outliers_x; i];
outliers_y = [outliers_y; col];
else
% ## no statistics if no points
% no statistics if no points
s(:,i) = NaN;
end
end
% % % % if isempty(outliers2_y)
% % % % outliers2_y=
% ## Note which boxes don't have enough stats
% Note which boxes don't have enough stats
chop = find(box <= 1);
% ## Draw a box around the quartiles, with width proportional to the number of
% ## items in the box. Draw notches if desired.
% Draw a box around the quartiles, with width proportional to the number of
% items in the box. Draw notches if desired.
box = box*0.23/max(box);
quartile_x = ones(11,1)*[1:nc] + [-a;-1;-1;1;1;a;1;1;-1;-1;-a]*box;
quartile_y = s([3,7,4,4,7,3,6,2,2,6,3],:);
% ## Draw a line through the median
% Draw a line through the median
median_x = ones(2,1)*[1:nc] + [-a;+a]*box;
% median_x=median(col);
median_y = s([3,3],:);
% ## Chop all boxes which don't have enough stats
% Chop all boxes which don't have enough stats
quartile_x(:,chop) = [];
quartile_y(:,chop) = [];
whisker_x(:,[chop,chop+nc]) = [];
whisker_y(:,[chop,chop+nc]) = [];
median_x(:,chop) = [];
median_y(:,chop) = [];
% % % %
% ## Add caps to the remaining whiskers
% Add caps to the remaining whiskers
cap_x = whisker_x;
cap_x(1,:) =cap_x(1,:)- 0.05;
cap_x(2,:) =cap_x(2,:)+ 0.05;
@ -146,11 +129,14 @@ cap_y = whisker_y([1,1],:);
% #whisker_x,whisker_y
% #median_x,median_y
% #cap_x,cap_y
%
% ## Do the plot
% Do the plot
mm=min(min(data));
MM=max(max(data));
if isnan(mm)
mm=0;
MM=0;
end
if vertical
plot (quartile_x, quartile_y, 'b', ...
@ -162,17 +148,30 @@ if vertical
set(gca,'XTick',1:nc);
set(gca, 'XLim', [0.5, nc+0.5]);
set(gca, 'YLim', [mm-(MM-mm)*0.05-eps, MM+(MM-mm)*0.05+eps]);
else
% % % % % plot (quartile_y, quartile_x, "b;;",
% % % % % whisker_y, whisker_x, "b;;",
% % % % % cap_y, cap_x, "b;;",
% % % % % median_y, median_x, "r;;",
% % % % % outliers_y, outliers_x, [symbol(1),"r;;"],
% % % % % outliers2_y, outliers2_x, [symbol(2),"r;;"]);
end
if nargout
sout=s;
end
% % % endfunction
function y = myprctilecol(x,p)
xx = sort(x);
[m,n] = size(x);
if m==1 | n==1
m = max(m,n);
if m == 1
y = x*ones(length(p),1);
return
end
n = 1;
q = 100*(0.5:m - 0.5)./m;
xx = [min(x); xx(:); max(x)];
else
q = 100*(0.5:m - 0.5)./m;
xx = [min(x); xx; max(x)];
end
q = [0 q 100];
y = interp1(q,xx,p);

43
matlab/gsa/myprctilecol.m
View File

@ -1,43 +0,0 @@
function y = myprctilecol(x,p)
% Written by Marco Ratto
% Joint Research Centre, The European Commission,
% marco.ratto@ec.europa.eu
% Copyright © 2012 European Commission
% Copyright © 2012-2017 Dynare Team
%
% This file is part of Dynare.
%
% Dynare 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
% (at your option) any later version.
%
% Dynare 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 Dynare. If not, see <https://www.gnu.org/licenses/>.
xx = sort(x);
[m,n] = size(x);
if m==1 | n==1
m = max(m,n);
if m == 1
y = x*ones(length(p),1);
return
end
n = 1;
q = 100*(0.5:m - 0.5)./m;
xx = [min(x); xx(:); max(x)];
else
q = 100*(0.5:m - 0.5)./m;
xx = [min(x); xx; max(x)];
end
q = [0 q 100];
y = interp1(q,xx,p);

5
matlab/gsa/priorcdf.m
View File

@ -1,5 +1,5 @@
function xcum = priorcdf(para, pshape, p6, p7, p3, p4)
% xcum = priorcdf(para, pshape, p6, p7, p3, p4)
% This procedure transforms x vectors into cumulative values
% pshape: 0 is point mass, both para and p2 are ignored
% 1 is BETA(mean,stdd)
@ -11,7 +11,7 @@ function xcum = priorcdf(para, pshape, p6, p7, p3, p4)
% 8 is WEIBULL(s, k)
% Adapted by M. Ratto from MJ priordens.m
% Copyright © 2012-2015 Dynare Team
% Copyright © 2012-2023 Dynare Team
%
% This file is part of Dynare.
%
@ -28,6 +28,7 @@ function xcum = priorcdf(para, pshape, p6, p7, p3, p4)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
xcum=NaN(size(para));
for i=1:length(pshape)
switch pshape(i)
case 1 % (generalized) BETA Prior

44
matlab/gsa/read_data.m
View File

@ -1,44 +0,0 @@
function [gend, data] = read_data()
% Written by Marco Ratto
% Joint Research Centre, The European Commission,
% marco.ratto@ec.europa.eu
% Copyright © 2012-2015 European Commission
% Copyright © 2012-2017 Dynare Team
%
% This file is part of Dynare.
%
% Dynare 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
% (at your option) any later version.
%
% Dynare 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 Dynare. If not, see <https://www.gnu.org/licenses/>.
global options_
rawdata = read_variables(options_.datafile,options_.varobs,[],options_.xls_sheet,options_.xls_range);
options_ = set_default_option(options_,'nobs',size(rawdata,1)-options_.first_obs+1);
gend = options_.nobs;
rawdata = rawdata(options_.first_obs:options_.first_obs+gend-1,:);
if options_.loglinear == 1 & ~options_.logdata
rawdata = log(rawdata);
end
if options_.prefilter == 1
data = transpose(rawdata-ones(gend,1)* mean(rawdata,1));
else
data = transpose(rawdata);
end
if ~isreal(rawdata)
error(['There are complex values in the data. Probably a wrong' ...
' transformation'])
end

24
matlab/gsa/stand_.m
View File

@ -1,20 +1,22 @@
function [y, meany, stdy] = stand_(x)
% STAND_ Standardise a matrix by columns
% [y, meany, stdy] = stand_(x)
% Standardise a matrix by columns
%
% [x,my,sy]=stand(y)
%
% y: Time series (column matrix)
% Inputs:
% - x: Time series (column matrix)
%
% x: standardised equivalent of y
% my: Vector of mean values for each column of y
% sy: Vector of standard deviations for each column of y
% - y: standardised equivalent of x
% - meany: Vector of mean values for each column of x
% - stdy: Vector of standard deviations for each column of x
%
% Written by Marco Ratto
% Joint Research Centre, The European Commission,
% marco.ratto@ec.europa.eu
% Copyright © 2012 European Commission
% Copyright © 2012-2017 Dynare Team%
% Copyright © 2012-2023 Dynare Team
% This file is part of Dynare.
%
% Dynare is free software: you can redistribute it and/or modify
@ -34,9 +36,11 @@ if nargin==0
return
end
meany=NaN(size(x,2),1);
stdy=NaN(size(x,2),1);
y=NaN(size(x));
for j=1:size(x,2)
meany(j)=mean(x(find(~isnan(x(:,j))),j));
stdy(j)=std(x(find(~isnan(x(:,j))),j));
meany(j)=mean(x(~isnan(x(:,j)),j));
stdy(j)=std(x(~isnan(x(:,j)),j));
y(:,j)=(x(:,j)-meany(j))./stdy(j);
end
% end of m-file
end

2
matlab/gsa/tcrit.m
View File

@ -150,4 +150,4 @@ if n<=100
t_crit=t_crit(n,ncol);
else
t_crit=t_crit(end,ncol);
end
end

6
matlab/gsa/teff.m
View File

@ -37,15 +37,12 @@ if ndim==3
[ir, ic]=(find( (tmax-tmin)>1.e-8));
j0 = length(ir);
yt=zeros(Nsam, j0);
for j=1:j0
y0=squeeze(T(ir(j),ic(j),:));
%y1=ones(size(lpmat,1),1)*NaN;
y1=ones(Nsam,1)*NaN;
y1(istable,1)=y0;
yt(:,j)=y1;
end
else
tmax=max(T,[],2);
tmin=min(T,[],2);
@ -53,7 +50,4 @@ else
j0 = length(ir);
yt=NaN(Nsam, j0);
yt(istable,:)=T(ir,:)';
end
%clear y0 y1;

34
matlab/gsa/trank.m
View File

@ -1,34 +0,0 @@
function yr = trank(y)
% yr = trank(y);
% yr is the rank transformation of y
%
% Written by Marco Ratto
% Joint Research Centre, The European Commission,
% marco.ratto@ec.europa.eu
%
% Reference:
% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
% Copyright © 2012 European Commission
% Copyright © 2012-2017 Dynare Team
%
% This file is part of Dynare.
%
% Dynare 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
% (at your option) any later version.
%
% Dynare 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 Dynare. If not, see <https://www.gnu.org/licenses/>.
[nr, nc] = size(y);
for j=1:nc
[dum, is]=sort(y(:,j));
yr(is,j)=[1:nr]'./nr;
end

177
matlab/myboxplot.m
View File

@ -1,177 +0,0 @@
function sout = myboxplot (data,notched,symbol,vertical,maxwhisker)
% sout = myboxplot (data,notched,symbol,vertical,maxwhisker)
%
% Copyright © 2010-2017 Dynare Team
%
% This file is part of Dynare.
%
% Dynare 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
% (at your option) any later version.
%
% Dynare 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 Dynare. If not, see <https://www.gnu.org/licenses/>.
% % % % endif
if nargin < 5 || isempty(maxwhisker), maxwhisker = 1.5; end
if nargin < 4 || isempty(vertical), vertical = 1; end
if nargin < 3 || isempty(symbol), symbol = ['+','o']; end
if nargin < 2 || isempty(notched), notched = 0; end
if length(symbol)==1, symbol(2)=symbol(1); end
if notched==1, notched=0.25; end
a=1-notched;
% ## figure out how many data sets we have
if iscell(data)
nc = length(data);
else
% if isvector(data), data = data(:); end
nc = size(data,2);
end
% ## compute statistics
% ## s will contain
% ## 1,5 min and max
% ## 2,3,4 1st, 2nd and 3rd quartile
% ## 6,7 lower and upper confidence intervals for median
s = zeros(7,nc);
box = zeros(1,nc);
whisker_x = ones(2,1)*[1:nc,1:nc];
whisker_y = zeros(2,2*nc);
outliers_x = [];
outliers_y = [];
outliers2_x = [];
outliers2_y = [];
for i=1:nc
% ## Get the next data set from the array or cell array
if iscell(data)
col = data{i}(:);
else
col = data(:,i);
end
% ## Skip missing data
% % % % % % % col(isnan(col) | isna (col)) = [];
col(isnan(col)) = [];
% ## Remember the data length
nd = length(col);
box(i) = nd;
if (nd > 1)
% ## min,max and quartiles
% s(1:5,i) = statistics(col)(1:5);
s(1,i)=min(col);
s(5,i)=max(col);
s(2,i)=myprctilecol(col,25);
s(3,i)=myprctilecol(col,50);
s(4,i)=myprctilecol(col,75);
% ## confidence interval for the median
est = 1.57*(s(4,i)-s(2,i))/sqrt(nd);
s(6,i) = max([s(3,i)-est, s(2,i)]);
s(7,i) = min([s(3,i)+est, s(4,i)]);
% ## whiskers out to the last point within the desired inter-quartile range
IQR = maxwhisker*(s(4,i)-s(2,i));
whisker_y(:,i) = [min(col(col >= s(2,i)-IQR)); s(2,i)];
whisker_y(:,nc+i) = [max(col(col <= s(4,i)+IQR)); s(4,i)];
% ## outliers beyond 1 and 2 inter-quartile ranges
outliers = col((col < s(2,i)-IQR & col >= s(2,i)-2*IQR) | (col > s(4,i)+IQR & col <= s(4,i)+2*IQR));
outliers2 = col(col < s(2,i)-2*IQR | col > s(4,i)+2*IQR);
outliers_x = [outliers_x; i*ones(size(outliers))];
outliers_y = [outliers_y; outliers];
outliers2_x = [outliers2_x; i*ones(size(outliers2))];
outliers2_y = [outliers2_y; outliers2];
elseif (nd == 1)
% ## all statistics collapse to the value of the point
s(:,i) = col;
% ## single point data sets are plotted as outliers.
outliers_x = [outliers_x; i];
outliers_y = [outliers_y; col];
else
% ## no statistics if no points
s(:,i) = NaN;
end
end
% % % % if isempty(outliers2_y)
% % % % outliers2_y=
% ## Note which boxes don't have enough stats
chop = find(box <= 1);
% ## Draw a box around the quartiles, with width proportional to the number of
% ## items in the box. Draw notches if desired.
box = box*0.23/max(box);
quartile_x = ones(11,1)*[1:nc] + [-a;-1;-1;1;1;a;1;1;-1;-1;-a]*box;
quartile_y = s([3,7,4,4,7,3,6,2,2,6,3],:);
% ## Draw a line through the median
median_x = ones(2,1)*[1:nc] + [-a;+a]*box;
% median_x=median(col);
median_y = s([3,3],:);
% ## Chop all boxes which don't have enough stats
quartile_x(:,chop) = [];
quartile_y(:,chop) = [];
whisker_x(:,[chop,chop+nc]) = [];
whisker_y(:,[chop,chop+nc]) = [];
median_x(:,chop) = [];
median_y(:,chop) = [];
% % % %
% ## Add caps to the remaining whiskers
cap_x = whisker_x;
cap_x(1,:) =cap_x(1,:)- 0.05;
cap_x(2,:) =cap_x(2,:)+ 0.05;
cap_y = whisker_y([1,1],:);
% #quartile_x,quartile_y
% #whisker_x,whisker_y
% #median_x,median_y
% #cap_x,cap_y
%
% ## Do the plot
mm=min(min(data));
MM=max(max(data));
if isnan(mm), mm=0; MM=0; end
if vertical
plot (quartile_x, quartile_y, 'b', ...
whisker_x, whisker_y, 'b--', ...
cap_x, cap_y, 'k', ...
median_x, median_y, 'r', ...
outliers_x, outliers_y, [symbol(1),'r'], ...
outliers2_x, outliers2_y, [symbol(2),'r']);
set(gca,'XTick',1:nc);
set(gca, 'XLim', [0.5, nc+0.5]);
set(gca, 'YLim', [mm-(MM-mm)*0.05-eps, MM+(MM-mm)*0.05+eps]);
else
% % % % % plot (quartile_y, quartile_x, "b;;",
% % % % % whisker_y, whisker_x, "b;;",
% % % % % cap_y, cap_x, "b;;",
% % % % % median_y, median_x, "r;;",
% % % % % outliers_y, outliers_x, [symbol(1),"r;;"],
% % % % % outliers2_y, outliers2_x, [symbol(2),"r;;"]);
end
if nargout
sout=s;
end
% % % endfunction