From 6fcf549f9fd238dc333a7404203b60b0b097b16d Mon Sep 17 00:00:00 2001
From: Laurie Boffelli <laurie.boffelli@orange.fr>
Date: Mon, 24 Apr 2023 10:09:03 +0200
Subject: [PATCH] Correction Dynamics_Model (modification: fmincon)
---
parmorceauxMax-git/Dynamics_Model.m | 59 ++++++++++++++++++++++++-----
1 file changed, 49 insertions(+), 10 deletions(-)
diff --git a/parmorceauxMax-git/Dynamics_Model.m b/parmorceauxMax-git/Dynamics_Model.m
index a5d35bb..e2a7ca6 100644
--- a/parmorceauxMax-git/Dynamics_Model.m
+++ b/parmorceauxMax-git/Dynamics_Model.m
@@ -161,7 +161,13 @@ classdef Dynamics_Model < matlab.mixin.Copyable %handle
X_ini = [X_ini; new_X_ini];
X_ini=obj.normalise_X(X_ini)
- [new_X_variable,loglikelihood] = fminunc(f,X_ini);
+ lb = repmat(0,1,length(X_ini));
+ ub = repmat(1,1,length(X_ini));
+ A = [];
+ b = [];
+ Aeq = [];
+ beq = [];
+ [new_X_variable,loglikelihood] = fmincon(f,X_ini,A,b,Aeq,beq,lb,ub);
obj.confidence = [obj.confidence, -loglikelihood / size(new_X_variable,1)];
new_X_variable = obj.normalise_X(new_X_variable);
@@ -178,7 +184,7 @@ classdef Dynamics_Model < matlab.mixin.Copyable %handle
obj.nb_times_fixed = [obj.nb_times_fixed; 0];
end
- if abs(obj.X(i) - new_X(i)) < 1e-3
+ if abs(obj.X(i) - new_X(i)) < 1e-3%1e-2
obj.nb_times_fixed(i) = obj.nb_times_fixed(i)+1;
else
obj.nb_times_fixed(i) = 0;
@@ -202,21 +208,21 @@ classdef Dynamics_Model < matlab.mixin.Copyable %handle
if new_N_fixed > N-3
new_N_fixed = N-3;
end
-
+%
if new_N_fixed < 0
new_N_fixed = 0;
end
-
- if new_N_fixed < N-13
- new_N_fixed = N-13;
+%
+ if new_N_fixed < N-13 %N-8
+ new_N_fixed = N-13; %N-8;
end
- if size(new_X, 1) < 12
+ if size(new_X, 1) < 4 %12
new_N_fixed = size(new_X, 1) - 2;
if new_N_fixed < 0
new_N_fixed = 0;
end
- elseif size(new_X, 1) == 12
+ elseif size(new_X, 1) == 4 %12
new_N_fixed = 0;
end
@@ -262,8 +268,13 @@ classdef Dynamics_Model < matlab.mixin.Copyable %handle
X_ini = X_tmp(2:end-1)';
-
- [new_X,loglikelihood] = fminunc(f,X_ini);
+ lb = repmat(0,1,length(X_ini));
+ ub = repmat(1,1,length(X_ini));
+ A = [];
+ b = [];
+ Aeq = [];
+ beq = [];
+ [new_X,loglikelihood] = fmincon(f,X_ini,A,b,Aeq,beq,lb,ub);
new_X = [0; obj.normalise_X(new_X); 1];
obj.X = new_X;
@@ -288,6 +299,8 @@ classdef Dynamics_Model < matlab.mixin.Copyable %handle
function loglikelihood = logP_x_knowing_y_partialUpdate(obj, last_fixed_X, variable_X, alpha, sigma)
N_variable = size(variable_X,1);
+ % variable_X = obj.normalise_X(variable_X);
+
% if N == 1, we only maximise P_cond_y(Y(1),X(1))
% if N == 2, we maximise P_cond_y(Y(2),X(2)) * P_x_Markov_simple(X(2),X(1)) * P_cond_y(Y(1),X(1)) with P_x_Markov_simple(X(2),X(1)) = 0 if delta_X is negative, and uniform proba otherwise
@@ -415,11 +428,37 @@ classdef Dynamics_Model < matlab.mixin.Copyable %handle
ylabel(['Manifold coordinate Y_' i])
hold on
plot(obj.normalise_X(obj.X(start_frame:N)),obj.Y(start_frame:N,i),'kx')
+
+ end
+ %pour faire des gifs
+ %saveas(obj.display_screen, strcat('estimatedX_frame', int2str(N), '.png'))
+ end
+
+ end
+
+ function [im]=final_plot_estimated_X(obj)
+ if obj.display_screen ~= -1
+ N = size(obj.X,1);
+ start_frame = max(N - 50, 1);
+
+ figure(obj.display_screen)
+
+
+ for i=1:obj.num_dim_Y
+ subplot(obj.num_dim_Y,1,i)
+ hold off
+ im=imagesc([0 1],[obj.limits_Yi(i,1) obj.limits_Yi(i,2)],obj.marginal_X_Yi(:,:,i),'CDataMapping','scaled')
+ %set(gca,'YDir','normal')
+ hold on
+ plot(obj.normalise_X(obj.X(start_frame:N)),obj.Y(start_frame:N,i),'kx')
+ axis off
+
end
%pour faire des gifs
%saveas(obj.display_screen, strcat('estimatedX_frame', int2str(N), '.png'))
end
end
+
function X = normalise_X(obj, X)
X(X<0) = 0;
X(X>1) = 1;
--
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