From ad2fe012b12985f22871fc297e8f83c4069be39b Mon Sep 17 00:00:00 2001
From: Marco Ratto <marco.ratto@jrc.ec.europa.eu>
Date: Wed, 4 May 2011 10:40:09 +0200
Subject: [PATCH] Minor improvements to printed and plotted output.
---
matlab/plot_identification.m | 20 +++++++++++---------
1 file changed, 11 insertions(+), 9 deletions(-)
diff --git a/matlab/plot_identification.m b/matlab/plot_identification.m
index 6f9d930519..2b08ab9d5a 100644
--- a/matlab/plot_identification.m
+++ b/matlab/plot_identification.m
@@ -56,7 +56,7 @@ siLREnorm = idelre.siLREnorm;
if SampleSize == 1,
siJ = idemoments.siJ;
normJ = max(abs(siJ)')';
- figure('Name',[tittxt, 'Identification using info from observables']),
+ figure('Name',[tittxt, ' - Identification using info from observables']),
subplot(211)
mmm = (idehess.ide_strength_J);
[ss, is] = sort(mmm);
@@ -99,10 +99,11 @@ if SampleSize == 1,
title('Sensitivity bars')
if advanced
+ disp('Press ENTER to display advanced diagnostics'), pause,
% identificaton patterns
for j=1:size(idemoments.cosnJ,2),
pax=NaN(nparam,nparam);
- fprintf('\n\n')
+ fprintf('\n')
disp(['Collinearity patterns with ', int2str(j) ,' parameter(s)'])
fprintf('%-15s [%-*s] %10s\n','Parameter',(15+1)*j,' Expl. params ','cosn')
for i=1:nparam,
@@ -118,7 +119,7 @@ if SampleSize == 1,
end
fprintf('%-15s [%s] %10.3f\n',name{i},namx,idemoments.cosnJ(i,j))
end
- figure('name',[tittxt,'Collinearity patterns with ', int2str(j) ,' parameter(s)']),
+ figure('name',[tittxt,' - Collinearity patterns with ', int2str(j) ,' parameter(s)']),
imagesc(pax,[0 1]);
set(gca,'xticklabel','')
set(gca,'yticklabel','')
@@ -147,18 +148,18 @@ if SampleSize == 1,
if idehess.flag_score,
[U,S,V]=svd(idehess.AHess,0);
if nparam<5,
- f1 = figure('name',[tittxt,'Identification patterns (Information matrix)']);
+ f1 = figure('name',[tittxt,' - Identification patterns (Information matrix)']);
else
- f1 = figure('name',[tittxt,'Identification patterns (Information matrix): SMALLEST SV']);
- f2 = figure('name',[tittxt,'Identification patterns (Information matrix): HIGHEST SV']);
+ f1 = figure('name',[tittxt,' - Identification patterns (Information matrix): SMALLEST SV']);
+ f2 = figure('name',[tittxt,' - Identification patterns (Information matrix): HIGHEST SV']);
end
else
[U,S,V]=svd(siJ./normJ(:,ones(nparam,1)),0);
if nparam<5,
- f1 = figure('name',[tittxt,'Identification patterns (moments)']);
+ f1 = figure('name',[tittxt,' - Identification patterns (moments)']);
else
- f1 = figure('name',[tittxt,'Identification patterns (moments): SMALLEST SV']);
- f2 = figure('name',[tittxt,'Identification patterns (moments): HIGHEST SV']);
+ f1 = figure('name',[tittxt,' - Identification patterns (moments): SMALLEST SV']);
+ f2 = figure('name',[tittxt,' - Identification patterns (moments): HIGHEST SV']);
end
end
for j=1:min(nparam,8),
@@ -226,6 +227,7 @@ else
end
title('MC mean of sensitivity measures')
if advanced,
+ disp('Press ENTER to display advanced diagnostics'), pause,
options_.nograph=1;
figure('Name','MC Condition Number'),
subplot(221)
--
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