Revision f4b194a6
Added by Benoit Parmentier over 11 years ago
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#STAGE 5: Output analyses: assessment of results for specific dates... |
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# |
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#AUTHOR: Benoit Parmentier |
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#DATE: 07/06/2013
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#DATE: 07/09/2013
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#PROJECT: NCEAS INPLANT: Environment and Organisms --TASK#363, TASK$568-- |
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##SCRIPT USED FOR THE PREDICTIONS: Source or list all scripts here to avoid confusion on versions being run!!!! |
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#source(file.path(script_path,"master_script_temp_06272013.R")) #Master script can be run directly...
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#source(file.path(script_path,"master_script_temp_07092013.R")) #Master script can be run directly...
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#CALLED FROM MASTER SCRIPT: |
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stages_to_run<-c(0,2,3,4,5) #May decide on antoher strategy later on... |
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var<-"TMAX" # variable being interpolated |
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out_prefix<-"_365d_gam_day_lst_comb1_07062013" #User defined output prefix
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out_suffix<-"_OR_07062013"
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out_prefix<-"_365d_gam_day_lst_comb3_07092013" #User defined output prefix
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out_suffix<-"_OR_07092013"
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out_suffix_modis <-"_05302013" #use tiles produce previously |
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#interpolation_method<-c("gam_fusion","gam_CAI","gam_daily") #other otpions to be added later
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out_region_name<-"_oregon_region" #generated on the fly |
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#The names of covariates can be changed...these names should be output/input from covar script!!! |
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rnames<-c("x","y","lon","lat","N","E","N_w","E_w","elev_s","slope","aspect","CANHEIGHT","DISTOC")
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rnames<-c("x","y","lon","lat","N","E","N_w","E_w","elev_s","slope","aspect","CANHGHT","DISTOC")
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lc_names<-c("LC1","LC2","LC3","LC4","LC5","LC6","LC7","LC8","LC9","LC10","LC11","LC12")
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#lc_names<-c("LC1","LC2","LC3","LC4","LC5","LC6","LC7","LC8","LC9","LC10") #use older version for continuity check to be changed
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lst_names<-c("mm_01","mm_02","mm_03","mm_04","mm_05","mm_06","mm_07","mm_08","mm_09","mm_10","mm_11","mm_12",
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covar_names<-c(rnames,lc_names,lst_names) |
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list_val_range <-c("lon,-180,180","lat,-90,90","N,-1,1","E,-1,1","N_w,-1,1","E_w,-1,1","elev_s,0,6000","slope,0,90",
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"aspect,0,360","DISTOC,-0,10000000","CANHEIGHT,0,255","LC2,0,100","LC6,0,100","mm_01,-15,50",
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"aspect,0,360","DISTOC,-0,10000000","CANHGHT,0,255","LC1,0,100","LC5,0,100","mm_01,-15,50",
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"mm_02,-15,50","mm_03,-15,50","mm_04,-15,50","mm_05,-15,50","mm_06,-15,50","mm_07,-15,50", |
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"mm_08,-15,50","mm_09,-15,50","mm_10,-15,50","mm_11,-15,50","mm_12,-15,50") |
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prop_minmax<-c(0.3,0.3) #if prop_min=prop_max and step=0 then predicitons are done for the number of dates... |
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#dates_selected<-c("20100101","20100102","20100103","20100901") # Note that the dates set must have a specific format: yyymmdd
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dates_selected<-"" # if empty string then predict for the full year specified earlier |
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screen_data_training<-TRUE
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screen_data_training<-FALSE
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#Models to run...this can be change for each run |
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#Combination 1 |
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list_models<-c("y_var ~ s(elev_s)",
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"y_var ~ s(LST)", |
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"y_var ~ s(elev_s,LST)", |
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"y_var ~ s(lat) + s(lon)+ s(elev_s)", |
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"y_var ~ s(lat,lon,elev_s)", |
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"y_var ~ s(lat,lon) + s(elev_s) + s(N_w,E_w) + s(LST)", |
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"y_var ~ s(lat,lon) + s(elev_s) + s(N_w,E_w) + s(LST) + s(LC6)", |
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"y_var ~ s(lat,lon) + s(elev_s) + s(N_w,E_w) + s(LST) + ti(LC6,LST)", |
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"y_var ~ s(lat,lon) + s(elev_s) + s(N_w,E_w) + s(LST) + s(DISTOC)") |
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#LC1: Evergreen/deciduous needleleaf trees |
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#Combination 3: for paper baseline=s(lat,lon)+s(elev) |
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list_models<-c("y_var ~ s(lat,lon) + s(elev_s)",
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"y_var ~ s(lat,lon) + s(elev_s) + s(N_w)", |
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"y_var ~ s(lat,lon) + s(elev_s) + s(E_w)", |
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"y_var ~ s(lat,lon) + s(elev_s) + s(LST)", |
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"y_var ~ s(lat,lon) + s(elev_s) + s(DISTOC)", |
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"y_var ~ s(lat,lon) + s(elev_s) + s(LC1)", |
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"y_var ~ s(lat,lon) + s(elev_s) + s(CANHGHT)", |
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"y_var ~ s(lat,lon) + s(elev_s) + s(LST) + ti(LST,LC1)", |
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"y_var ~ s(lat,lon) + s(elev_s) + s(LST) + ti(LST,CANHGHT)") |
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# list_models<-c("y_var ~ s(elev_s)",
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# "y_var ~ s(LST)", |
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# "y_var ~ s(elev_s,LST)", |
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# "y_var ~ s(lat) + s(lon)+ s(elev_s)", |
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# "y_var ~ s(lat,lon,elev_s)", |
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# "y_var ~ s(lat,lon) + s(elev_s) + s(N_w,E_w) + s(LST)", |
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# "y_var ~ s(lat,lon) + s(elev_s) + s(N_w,E_w) + s(LST) + s(LC6)", |
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# "y_var ~ s(lat,lon) + s(elev_s) + s(N_w,E_w) + s(LST) + ti(LC6,LST)", |
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# "y_var ~ s(lat,lon) + s(elev_s) + s(N_w,E_w) + s(LST) + s(DISTOC)") |
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#testing new combinations and tensor for paper |
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# list_models<-c("y_var ~ s(x,y)",
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############### END OF SCRIPT ################### |
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##################################################### |
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# #LAND COVER INFORMATION |
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# LC1: Evergreen/deciduous needleleaf trees |
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# LC2: Evergreen broadleaf trees |
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# LC3: Deciduous broadleaf trees |
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# LC4: Mixed/other trees |
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# LC5: Shrubs |
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# LC6: Herbaceous vegetation |
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# LC7: Cultivated and managed vegetation |
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# LC8: Regularly flooded shrub/herbaceous vegetation |
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# LC9: Urban/built-up |
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# LC10: Snow/ice |
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# LC11: Barren lands/sparse vegetation |
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# LC12: Open water |
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Also available in: Unified diff
gam day predictions for paper testing covariates combination 3