WIP - use new wavelet

best/mem/be_launch_mem.m

@@ -213,7 +213,8 @@
         transl  =   OPTIONS.automatic.selected_samples(3,ii);
         wav     =   zeros( 1, nbSmp );
         wav( nbSmp/2^scale + transl ) = 1;
-        wav     =   sparse(be_wavelet_inverse( wav, OPTIONS ));
+        %wav     =   sparse(be_wavelet_inverse( wav, OPTIONS ));
+        wav     =   sparse(BEst_Wave850synthesis( wav, OPTIONS.automatic.Winfo ));
         SOL     =   sparse(vec) * wav;
 
     else

best/wmem/wavelet/BEst_Wave850analysis.m

@@ -0,0 +1,12 @@
+function [ out_W, info ] = BEst_Wave850analysis( in_C, Nb_scales, Nb_level, Vmoments )
+% Real Daubechies wavelet transform from Wavelab850
+addpath(genpath('./Wavelab850'));
+info.Wfiltre = MakeONFilter('Daubechies',2*(Vmoments+1));
+info.Noff    = Nb_scales - Nb_level;
+out_W = zeros(size(in_C));
+for i = 1:size(in_C,1)
+    out_W(i,:) = fwt_po(in_C(i,:),info.Noff,info.Wfiltre);
+end
+end
+
+

best/wmem/wavelet/BEst_Wave850synthesis.m

@@ -0,0 +1,12 @@
+function [out_C] = BEst_Wave850synthesis( in_W, Winfo)
+% Real Daubechies wavelet reconstruction from Wavelab850
+% Winfo.Noff : scaling level
+% Winfo.Wfiltre: filter used for the previous decomposition
+addpath(genpath('./Wavelab850'));
+out_C = zeros(size(in_W));
+for i = 1:size(in_W,1)
+    out_C(i,:) = iwt_po(in_W(i,:),Winfo.Noff,Winfo.Wfiltre);
+end
+end
+
+

best/wmem/wavelet/be_discrete_wavelet_transform.m

@@ -69,9 +69,14 @@
         Njs   = max(Nj-3,1);
         SData = zeros(size(Data));
         WData = zeros(size(Data));
-        [WData, info ] = be_dwanalysis( Data, Njs, filter );
-        WData(:,1:No/2^Njs) = 0.0;
+
+        %[WData, Winfo ] = be_dwanalysis( Data, Njs, filter );
+
+        [WData, Winfo ] = BEst_Wave850analysis(Data,Nj,Njs,3);
         SData(:,1:No/2^Njs) = WData(:,1:No/2^Njs);
+        WData(:,1:No/2^Njs) = 0.0;
+
+        OPTIONS.automatic.Winfo = Winfo;
         OPTIONS.automatic.scales(1,:) = 1:Njs;
         OPTIONS.automatic.scales(2,:) = 3./2.^(1:Njs)/4;