#========================================================== # fichier de D'INSTRUCTIONS jeuvie.i #nb PAS DE TAB, un retour chariot en fin de fichier #========================================================== echo on lmod #========================================================== #init du modèle ------------------------------------------- setstate Seuil 2.0 | remplace xset_seuil 2.0 setstate Sigma 2.0 | 0.5 setstate Mask 1.0 #loadstate Mask 1 ij 0 A 0 ./msk50x50.dat F #GOTO LABXX #xinit_bio #savestate Biocell 1 ij 1 A 0 BioInit1 loadstate Biocell 1 ij 1 A 0 BioInit1 D #========================================================== #expérience jumelle --------------------------------------- # ==> passe avant 1 fois sur tous les pas de temps pour # générer des observations : print_time ON set_modeltime 0 FORWARD set_modeltime 0 print_time OFF # #savestate Biocell 1 ij SZA A 0 BiOd6 #savestate Biocell 1 ij SZA A 0 BiOc6_2_0v5 #savestate Biocell 1 ij SZA A 0 BiOc6_2_1v0 #savestate Biocell 1 ij SZA A 0 BiOc2_2_0v5 #savestate Biocell 1 ij SZA A 0 BiOc2_2_1v0 #savestate Biocell 1 ij 0 A 0 BioTrj #>>matlab: y2dsurf BioTrj 50 50 ij 1 1 outoobs Biocell 1 SZA #LABXX #loadobs Biocell 1 ij SZA A 0 BiOd2 D #loadobs Biocell 1 ij SZA A 0 BiOc2_2_1v0 D #---------------------------------------------------------- # pour tracer la fonction de cout : #GOTO PLOTOF #---------------------------------------------------------- # préparation de l'execution de l'assimilation #=====> choix de la fonction de cout cost lms 1.0e6 cost lms 0.5 #cost lms 0.0005 #cost appli #adjust appli #=====> on perturbe les variables à contrôler: valeur(s) initiale(s) # 1) scenario : recherche de l'état initial (Biocell is target) : #xinit_bio #savestate Biocell 1 ij 1 A 0 BioInit1P loadstate Biocell 1 ij 1 A 0 BioInit1P D #loadstate Biocell 1 ij 1 A 0 BioInit1Pz D #loadstate Biocell 1 ij 1 A 0 BioObs1 D #loadstate Biocell 1 ij 1 A 0 BioObsi1 D # 2) scenario : recherche de parametre(s) (ex: Sigma => is target) #setstate Sigma 0.49 #setstate Sigma 0.3 #setstate Sigma 0.35 #setstate Seuil 2.2 #---------------------------------------------------------- # Choix RUN : std/m1qn3 std/incr GOTO RUNMQN #---------------------------------------------------------- # soit le RUN standard de Yao : #=> choix du (ou des) pas de gradient setepsi Biocell 0.5 | scenar 1 setepsi Biocell 0.2 | scenar 1 #setepsi Sigma 0.5 | scenar 2 #=>et en route pour le run print_cost ON print_time OFF set_nbiter 5000 RUN GOTO AFT_RUN # incremental ........ setepsi Sigma 0.0000000000001 set_nbextl 10 set_nbiter 4 set_pcoef Sigma 0.001 | (scenar 1) #set_pcoef Biocell 0.0 | (scenar 2) RUNI xdisplay STOP #^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ RUNMQN # soit le run sous m1qn3 .................................. print_cost ON setm_impres 0 setm_io 6 setm_mode 0 set_nbiter 50000 setm_nsim 50000 setm_dxmin 1.0e-20 setm_epsg 1.0e-20 setm_ddf1 1.0 RUNM GOTO AFT_RUN #incrémental ........ setm_impres 5 setm_io 6 setm_mode 2 #setm_mode 0 set_nbextl 10 set_nbiter 3 setm_nsim 3 setm_dxmin 1.0e-20 setm_epsg 1.0e-20 setm_ddf1 1.0 set_pcoef Sigma 0.0 | (scenar 1) set_pcoef Seuil 0.0 | (scenar 1) #set_pcoef Biocell 0.0 | (scenar 2) RUNIM GOTO AFT_RUN AFT_RUN print_cost xdisplay #savestate Biocell 1 ij 1 A 0 Final1_Bio #savestate Biocell 1 ij 21 A 0 Final21_Bio #savestate Biocell 1 ij 5 A 0 Final5_Bio savestate Biocell 1 ij 1 A 0 BioInit1A xcalibre_bio savestate Biocell 1 ij 1 A 0 BioInit1A01 TCHAO #load_inst jeuvie.i #==================================================================== PLOTOF cost lms 0.0005 #setstate Sigma 0.3 #setepsi Sigma 0.0001 #setepsi Sigma 0.001 #run #sampleof Sigma 0.1 1.0 0.05 Sigma 0.3 0.3 9.999 ./SigmaA.pof #sampleof Sigma 0.1 1.0 0.005 Sigma 0.3 0.3 9.999 ./SigmaB.pof #sampleof Sigma 0.1 1.0 0.001 Sigma 0.3 0.3 9.999 ./SigmaC.pof #sampleof Sigma 0.4 0.6 0.00051 Sigma 0.3 0.3 9.999 ./SigmaD.pof #sampleof Sigma 0.49995 0.50005 0.000000101 Sigma 0.3 0.3 9.999 ./SigmaE.pof sampleof Sigma 0.499995 0.500005 0.0000000101 Sigma 0.3 0.3 9.999 ./SigmaF.pof stop #sampleof Sigma 0.35 0.60 0.001 Sigma 0.3 0.3 9.999 ./Sigma.pof #sampleof Sigma 0.45 0.55 0.0005 Sigma 0.3 0.3 9.999 ./Sigma.pof #sampleof Sigma 0.47 0.53 0.0001 Sigma 0.3 0.3 9.999 ./Sigma.pof #sampleof Sigma 0.30 0.35 0.0001 Sigma 0.3 0.3 9.999 ./Sigma.pof #sampleof Sigma 1.00 100.0 0.5 Sigma 0.3 0.3 9.999 ./Sigma.pof #sampleof Sigma 100.0 1000.0 5.0 Sigma 0.3 0.3 9.999 ./Sigma.pof #sampleof Sigma 1000.0 10000.0 50.0 Sigma 0.3 0.3 9.999 ./Sigma.pof #sampleof Sigma 1.0 10000.0 50.0 Sigma 0.3 0.3 9.999 ./Sigma.pof #sampleof Sigma 0.1 2.0 0.005 Sigma 0.3 0.3 9.999 ./Sigma.pof #sampleof Sigma 2.0 5.0 0.005 Sigma 0.3 0.3 9.999 ./Sigma.pof #sampleof Sigma 99.5 100.5 0.0005 Sigma 0.3 0.3 9.999 ./Sigma.pof #sampleof Sigma 0.4995 0.5005 0.00000101 Sigma 0.3 0.3 9.999 ./Sigma.pof #sampleof Sigma 0.49995 0.50005 0.000000101 Sigma 0.3 0.3 9.999 ./Sigma.pof #sampleof Sigma 0.499995 0.500005 0.0000000101 Sigma 0.3 0.3 9.999 ./Sigma.pof #sampleof Sigma 0.4999995 0.5000005 0.00000000101 Sigma 0.3 0.3 9.999 ./Sigma.pof #sampleof Sigma 0.30 0.60 0.001 Sigma 0.3 0.3 9.999 ./Sigma.pof #sampleof Sigma 0.30 0.60 0.01 Sigma 0.3 0.3 9.999 ./Sigma.pof #sampleof Sigma 0.30 0.60 0.01 Seuil 1.5 2.5 0.1 ./Sigma.pof #sampleof Sigma 0.45 0.55 0.001 Seuil 1.7 2.3 0.05 ./Sigma.pof #====================================================================