Revision 1883c4c2
Added by Benoit Parmentier about 11 years ago
| climate/research/oregon/interpolation/GAM_fusion_function_multisampling.R | ||
|---|---|---|
| 8 | 8 |
# 5)runGAMFusion <- function(i,list_param) : daily step for fusion method, perform daily prediction |
| 9 | 9 |
# |
| 10 | 10 |
#AUTHOR: Benoit Parmentier |
| 11 |
#DATE: 03/29/2013
|
|
| 11 |
#DATE: 04/02/2013
|
|
| 12 | 12 |
#PROJECT: NCEAS INPLANT: Environment and Organisms --TASK#363-- |
| 13 | 13 |
|
| 14 | 14 |
##Comments and TODO: |
| 15 | 15 |
#This script is meant to be for general processing tile by tile or region by region. |
| 16 | 16 |
# Note that the functions are called from GAM_fusion_analysis_raster_prediction_mutlisampling.R. |
| 17 | 17 |
# This will be expanded to other methods. |
| 18 |
# Change name of output tif to include the variable!!! (TMIN or TMAX) |
|
| 19 | 18 |
################################################################################################## |
| 20 | 19 |
|
| 21 | 20 |
|
| ... | ... | |
| 179 | 178 |
clim_obj<-list(rast_clim_list,data_month,mod_list,list_formulas) |
| 180 | 179 |
names(clim_obj)<-c("clim","data_month","mod","formulas")
|
| 181 | 180 |
|
| 182 |
save(clim_obj,file= paste("clim_obj_month_",j,"_",out_prefix,".RData",sep=""))
|
|
| 181 |
save(clim_obj,file= paste("clim_obj_month_",j,"_",var,"_",out_prefix,".RData",sep=""))
|
|
| 183 | 182 |
|
| 184 | 183 |
return(clim_obj) |
| 185 | 184 |
} |
| ... | ... | |
| 278 | 277 |
names(rast_clim_list)<-names(rast_bias_list) |
| 279 | 278 |
for (k in 1:nlayers(mod_rast)){
|
| 280 | 279 |
clim_fus_rast<-LST-subset(mod_rast,k) |
| 281 |
data_name<-paste("clim_LST_month_",j,"_",names(rast_clim_list)[k],"_",prop_month,
|
|
| 280 |
data_name<-paste(var,"_clim_LST_month_",j,"_",names(rast_clim_list)[k],"_",prop_month,
|
|
| 282 | 281 |
"_",run_samp,sep="") |
| 283 | 282 |
raster_name<-paste("fusion_",data_name,out_prefix,".tif", sep="")
|
| 284 | 283 |
rast_clim_list[[k]]<-raster_name |
| ... | ... | |
| 295 | 294 |
|
| 296 | 295 |
bias_rast<-interpolate(LST,fitbias) #interpolation using function from raster package |
| 297 | 296 |
#Saving kriged surface in raster images |
| 298 |
data_name<-paste("bias_LST_month_",j,"_",model_name,"_",prop_month,
|
|
| 297 |
data_name<-paste(var,"_bias_LST_month_",j,"_",model_name,"_",prop_month,
|
|
| 299 | 298 |
"_",run_samp,sep="") |
| 300 | 299 |
raster_name_bias<-paste("fusion_",data_name,out_prefix,".tif", sep="")
|
| 301 | 300 |
writeRaster(bias_rast, filename=raster_name_bias,overwrite=TRUE) #Writing the data in a raster file format...(IDRISI) |
| 302 | 301 |
|
| 303 | 302 |
#now climatology layer |
| 304 | 303 |
clim_rast<-LST-bias_rast |
| 305 |
data_name<-paste("clim_LST_month_",j,"_",model_name,"_",prop_month,
|
|
| 304 |
data_name<-paste(var,"_clim_LST_month_",j,"_",model_name,"_",prop_month,
|
|
| 306 | 305 |
"_",run_samp,sep="") |
| 307 | 306 |
raster_name_clim<-paste("fusion_",data_name,out_prefix,".tif", sep="")
|
| 308 | 307 |
writeRaster(clim_rast, filename=raster_name_clim,overwrite=TRUE) #Writing the data in a raster file format...(IDRISI) |
| ... | ... | |
| 317 | 316 |
clim_obj<-list(rast_bias_list,rast_clim_list,data_month,mod_list,list_formulas) |
| 318 | 317 |
names(clim_obj)<-c("bias","clim","data_month","mod","formulas")
|
| 319 | 318 |
|
| 320 |
save(clim_obj,file= paste("clim_obj_month_",j,"_",out_prefix,".RData",sep=""))
|
|
| 319 |
save(clim_obj,file= paste("clim_obj_month_",j,"_",var,"_",out_prefix,".RData",sep=""))
|
|
| 321 | 320 |
|
| 322 | 321 |
return(clim_obj) |
| 323 | 322 |
} |
| ... | ... | |
| 471 | 470 |
daily_delta_rast<-interpolate(rast_clim_month,fitdelta) #Interpolation of the bias surface... |
| 472 | 471 |
|
| 473 | 472 |
#Saving kriged surface in raster images |
| 474 |
data_name<-paste("daily_delta_",sampling_dat$date[i],"_",sampling_dat$prop[i],
|
|
| 473 |
data_name<-paste("daily_delta_",y_var_name,"_",sampling_dat$date[i],"_",sampling_dat$prop[i],
|
|
| 475 | 474 |
"_",sampling_dat$run_samp[i],sep="") |
| 476 | 475 |
raster_name_delta<-paste("fusion_",var,"_",data_name,out_prefix,".tif", sep="")
|
| 477 | 476 |
writeRaster(daily_delta_rast, filename=raster_name_delta,overwrite=TRUE) #Writing the data in a raster file format...(IDRISI) |
| ... | ... | |
| 507 | 506 |
|
| 508 | 507 |
obj_names<-c(y_var_name,"clim","delta","data_s","data_v", |
| 509 | 508 |
"sampling_dat",model_name) |
| 510 |
names(delta_obj)<-obj_names #add TMIN or TMAX name in saving obj
|
|
| 509 |
names(delta_obj)<-obj_names |
|
| 511 | 510 |
save(delta_obj,file= paste("delta_obj_",var,"_",sampling_dat$date[i],"_",sampling_dat$prop[i],
|
| 512 | 511 |
"_",sampling_dat$run_samp[i],out_prefix,".RData",sep="")) |
| 513 | 512 |
return(delta_obj) |
Also available in: Unified diff
gam fusion function modifications to allow any variable (TMIN) and record results