out_prefix<-"methods_09262012_"

path<-"/home/parmentier/Data/IPLANT_project/methods_interpolation_comparison" #Jupiter LOCATION on Atlas for kriging                              #Jupiter Location on XANDERS

################# PART 1: COMPARING RESULTS USING ALL MONTHNLY DATA AND SAMPLED FROM DAILY###################

######## Visualize data: USING ALL MONTHLY DATA...

#note differnces in patternin agricultural areas and 

############ PART 4: RESIDUALS ANALYSIS: ranking, plots, focus regions  ##################

############## EXAMINING STATION RESIDUALS ###########

########### CONSTANT OVER 365 AND SAMPLING OVER 365

#Plot daily_deltaclim_rast, bias_rast,add data_s and data_v

# RANK STATION by average or median RMSE

# Count the number of times a station is in the extremum group of outliers...

# LOOK at specific date...

#Examine residuals for a spciefic date...Jan, 1 using run of const_all i.e. same training over 365 dates

path_data_cai<-"/home/parmentier/Data/IPLANT_project/data_Oregon_stations_10242012_CAI"  #Change to constant

path_data_fus<-"/home/parmentier/Data/IPLANT_project/data_Oregon_stations_10242012_GAM"

setwd(path_data) #output data

#list files that contain raster tmax prediction (maps) for CAI and Fusion

#lf_c<-"GAM_predicted_mod7_20101231_30_1_365d_GAM_fusion_const_10172012.rst"

lf_cg<-list.files(pattern="GAM_predicted_mod2_.*_30_1_365d_GAM_fusion_const_10172012.rst$")    #changee to constant 

lf_ck<-list.files(pattern="fusion_tmax_predicted_.*_30_1_365d_GAM_fusion_const_10172012.rst$") #Fusion+Kriging

#list files that contain model objects and ratingin-testing information for CAI and Fusion

fus1_c<-load_obj("results2_fusion_Assessment_measure_all_365d_GAM_fusion_const_10172012.RData")

#fus1_c<-load_obj("results2_fusion_Assessment_measure_all_365d_GAM_fusion_const_10172012.RData")

gam_fus<-load_obj(file.path(path_data_fus,

                          "results2_fusion_Assessment_measure_all_365d_GAM_fusion_all_lstd_10242012.RData"))

gam_cai<-load_obj(file.path(path_dat_cai,

                          "results2_CAI_Assessment_measure_all_365d_GAM_CAI2_all_lstd_10262012.RData")  #This contains all the info

sampling_obj_cai<-load_obj(file.path(path_data_cai,

                                          "results2_CAI_sampling_obj_365d_GAM_CAI2_all_lstd_10262012.RData"))

sampling_date_list<-sampling_obj_cai$sampling_dat$date

date_selected<-"20100103"

k<-match(date_selected,sampling_date_list)

data_sf<-gam_fus[[k]]$data_s #object for the first date...20100103                  

data_vf<-gam_fus[[k]]$data_v #object for the first date...20100103                  

data_sc<-gam_fus[[k]]$data_s #object for the first date...20100103                  

data_vc<-gam_fus[[k]]$data_v #object for the first date...20100103                  

#Select background image for plotting

mod_pat<-glob2rx(paste("*",date_selected,"*",sep=""))   

image_file<-grep(mod_pat,lf_ck,value=TRUE) # using grep with "value" extracts the matching names         

raster_pred_k<-raster(image_file)

image_file<-grep(mod_pat,lf_cg,value=TRUE) # using grep with "value" extracts the matching names         

raster_pred_g<-raster(image_file)

plot(data_sf,add=TRUE)

plot(data_vf,pch=1,add=TRUE)

#Create a residual table...

res_mod9_list<-vector("list",365)

res_mod2_list<-vector("list",365)

tab_nv<-matrix(NA,365,1)

for(k in 1:365){

      tab_nv[k]<-length(fus1_c[[k]]$data_v$res_mod9)

}

#note that there might be some variation in the number!!!

for(k in 1:365){

   res_mod9<-fus1_c[[k]]$data_v$res_mod9

   res_mod2<-fus1_c[[k]]$data_v$res_mod2

   res_mod9_list[[k]]<-res_mod9

   res_mod2_list[[k]]<-res_mod2

   #subset data frame? or rbind them...and reshape?? think about it

}

tab_resmod9<-do.call(rbind,res_mod9_list)

data_v_list<-vector("list",365)

for(k in 1:365){

      data_v<-as.data.frame(fus1_c[[k]]$data_v)

      data_v<-data_v[,c("id","res_mod9")]

      #subset data frame? or rbind them...and reshape?? think about it

      data_v_list[[k]]<-data_v

}

tab_resmod9<-do.call(rbind,data_v_list)

#NOW USE RESHAPE TO CREATE TABLE....

#updated the analysis