Revision 643c7d19
Added by Benoit Parmentier over 11 years ago
| climate/research/oregon/interpolation/GAM_fusion_function_multisampling_validation_metrics.R | ||
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#The interpolation is done first at the monthly add delta. |
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#AUTHOR: Benoit Parmentier |
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#DATE: 02/13/2013
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#DATE: 03/12/2013
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#Change this to allow explicitly arguments... |
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#Arguments: |
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#1)list of climatology files for all models...(365*nb of models) |
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#2)data_s:training |
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#3)data_v:testing |
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#4)list of dates?? |
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#4)list of dates??: index
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#5)stack of covariates: not needed at this this stage |
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#6)dst: data at the monthly time scale |
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#Function used in the script |
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calculate_accuracy_metrics<-function(i){
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calculate_accuracy_metrics<-function(i,list_param){
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### Caculate accuracy metrics |
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calc_val_metrics<-function(x,y){
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## BEGIN ## |
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day_list <-rast_day_yearlist[[i]] #list of prediction for the current date... |
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#PARSING INPUT PARAMETERS |
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day_list<- list_param$rast_day_year_list[[i]] |
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#day_list <-rast_day_yearlist[[i]] #list of prediction for the current date... |
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names_mod<-names(day_list) |
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#this needs to be changed...this must be assigned earlier |
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# names(day_list)<-c("mod1","mod2","mod3","mod4","mod_kr")
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# obj_names<-c(y_var_name,"clim","delta","data_s","sampling_dat","data_v", |
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# ,model_name) |
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# names(gam_fus_mod[[i]]) |
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# |
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data_v <- gam_fus_mod[[i]]$data_v |
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data_s <- gam_fus_mod[[i]]$data_s |
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method_mod_obj<-list_param$method_mod_obj |
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#Change to results_mod_obj[[i]]$data_s to make it less specific |
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data_v <- method_mod_obj[[i]]$data_v |
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data_s <- method_mod_obj[[i]]$data_s |
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## Now create the stack |
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rast_day_mod <- stack(day_list) |
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names(rast_day_mod) <- names(day_list) |
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ns<-nrow(data_s) # some loss of data might have happened because of the averaging... |
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nv<-nrow(data_v) |
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sampling_dat_day<-(gam_fus_mod[[i]])$sampling_dat
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sampling_dat_day<-(method_mod_obj[[i]])$sampling_dat
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metrics_v_obj<-calc_val_metrics_rast(data_v,y_var_name,names_mod) |
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metrics_s_obj<-calc_val_metrics_rast(data_s,y_var_name,names_mod) |
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} |
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## Function to display metrics by months/seasons |
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boxplot_from_tb <-function(tb_diagnostic,metric_names,out_prefix){
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boxplot_month_from_tb <-function(tb_diagnostic,metric_names,out_prefix){
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#Add code here... |
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} |
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Also available in: Unified diff
Transforming validation function to allow explicit passing of arguments with calling from raster prediction function