source: tag/release-8/yao8/sample/jeuvie/jeuvie.i @ 1

#==========================================================
#            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

#====================================================================