Revision fae9ccb1
Added by Benoit Parmentier about 10 years ago
| climate/research/oregon/interpolation/global_run_scalingup_assessment_part2.R | ||
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#Analyses, figures, tables and data are also produced in the script. |
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#AUTHOR: Benoit Parmentier |
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#CREATED ON: 03/23/2014 |
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#MODIFIED ON: 08/14/2014
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#MODIFIED ON: 08/16/2014
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#Version: 3 |
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#PROJECT: Environmental Layers project |
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#COMMENTS: analyses for run 3 global using 2 specific tiles |
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CRS_WGS84<-c("+proj=longlat +ellps=WGS84 +datum=WGS84 +towgs84=0,0,0") #Station coords WGS84
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region_name <- "world" |
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# |
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###Table 1: Average accuracy metrics |
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###Table 2: daily accuracy metrics for all tiles |
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#lf_tables <- list.files(out_dir,) |
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pred_data_day_info <- read.table(file=file.path(out_dir,paste("pred_data_day_info_",out_prefix,".txt",sep="")),sep=",")
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df_tile_processed <- read.table(file=file.path(out_dir,paste("df_tile_processed_",out_prefix,".txt",sep="")),sep=",")
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#in_dir_list <- file.path(in_dir1,read.table(file.path(in_dir1,"processed.txt"))$V1) |
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gam_diagnostic_df <- read.table(file=file.path(out_dir,"gam_diagnostic_df_run4_global_analyses_08142014.txt"),sep=",") |
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########################## START SCRIPT ############################## |
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} |
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##### Diagnostic gam |
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gam_diagnostic_df |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,pred_mod=="mod1"),main="mod1 and term=s(lat,lon)",ylab="RMSE_f",xlab="k") |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,pred_mod=="mod2"),main="mod2 and term=s(lat,lon)",ylab="RMSE_f",xlab="k") |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,pred_mod=="mod1"),main="mod1 and term=s(elev_s)",ylab="RMSE_f",xlab="k") |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,pred_mod=="mod2"),main="mod2 and term=s(elev_s)",ylab="RMSE_f",xlab="k") |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,pred_mod=="mod2"),main="mod2 and term=s(LST)",ylab="RMSE_f",xlab="k") |
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res_pix <-480 |
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png(filename="test.png", |
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width=0.5*res_pix,height=6*res_pix) |
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#boxplot(rmse~pred_mod,data=tb,ylim=c(0,5),outline=FALSE)#,names=tb$pred_mod) |
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#title("RMSE per model over all tiles")
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#bwplot(rmse~k | term + month,data=subset(gam_diagnostic_df,pred_mod=="mod2"),) |
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xyplot(rmse~k | term + month,data=subset(gam_diagnostic_df,pred_mod=="mod2"),type="p") |
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xyplot(rmse~k | term + month,data=subset(gam_diagnostic_df,pred_mod=="mod1"),type="p") |
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xyplot(rmse~k | term + month,data=subset(gam_diagnostic_df,pred_mod=="mod1" & tile_id=="tile_7"),type="b") |
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xyplot(rmse~k | term + month,data=subset(gam_diagnostic_df,pred_mod=="mod2" & tile_id=="tile_7"),type="b") |
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xyplot(rmse~k | term + month,data=subset(gam_diagnostic_df,pred_mod=="mod1" & tile_id=="tile_8"),type="b") |
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xyplot(rmse~k | term + month,data=subset(gam_diagnostic_df,pred_mod=="mod2" & tile_id=="tile_8"),type="b") |
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xyplot(rmse~k | term + month,group=tile_id ,data=subset(gam_diagnostic_df,pred_mod=="mod1"),type="b", |
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auto.key=list(space = "top", cex=1.0,columns=8)) |
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dev.off() |
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boxplot(rmse~month,data=subset(gam_diagnostic_df,pred_mod=="mod2")) |
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boxplot(rmse~month,data=subset(gam_diagnostic_df,pred_mod=="mod1")) |
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gam_diagnostic_df$month <- as.factor(gam_diagnostic_df$month) |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,term=="s(lat,lon)" & pred_mod=="mod1"),main="mod1 and term=s(lat,lon)",ylab="RMSE_f",xlab="k") |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,term=="s(lat,lon)" & pred_mod=="mod2"),main="mod2 and term=s(lat,lon)",ylab="RMSE_f",xlab="k") |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,term=="s(elev_s)" & pred_mod=="mod1")) |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,term=="s(elev_s)" & pred_mod=="mod2")) |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,term=="s(LST)" & pred_mod=="mod2")) |
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boxplot(rmse~n,data=subset(gam_diagnostic_df,pred_mod=="mod2")) |
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boxplot(rmse~n,data=subset(gam_diagnostic_df,pred_mod=="mod1")) |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,term=="s(lat,lon)" & pred_mod=="mod1" & tile_id=="tile_8")) |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,term=="s(lat,lon)" & pred_mod=="mod1" & tile_id=="tile_7")) |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,term=="s(lat,lon)" & pred_mod=="mod2" & tile_id=="tile_8")) |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,term=="s(lat,lon)" & pred_mod=="mod2" & tile_id=="tile_7")) |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,term=="s(elev_s)" & pred_mod=="mod1" & tile_id=="tile_8")) |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,term=="s(elev_s)" & pred_mod=="mod1" & tile_id=="tile_7")) |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,term=="s(elev_s)" & pred_mod=="mod1" & tile_id=="tile_7" & month==1)) |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,term=="s(elev_s)" & pred_mod=="mod1" & tile_id=="tile_7" & month==7)) |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,term=="s(lat,lon)" & pred_mod=="mod1" & tile_id=="tile_7" & month==1)) |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,term=="s(lat,lon)" & pred_mod=="mod1" & tile_id=="tile_7" & month==7)) |
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boxplot(rmse~month,data=subset(gam_diagnostic_df,pred_mod=="mod1" & tile_id=="tile_7")) |
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boxplot(rmse~month,data=subset(gam_diagnostic_df,pred_mod=="mod2" & tile_id=="tile_7")) |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,term=="s(lat,lon)" & pred_mod=="mod2")) |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,term=="s(elev_s)" & pred_mod=="mod1")) |
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boxplot(rmse~k,data=subset(gam_diagnostic_df,term=="s(elev_s)" & pred_mod=="mod2")) |
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plot(n~tile_id,data=gam_diagnostic_df,type="h") |
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# |
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## Figure 3b |
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png(filename=paste("Figure3b_boxplot_overall_region_scaling_",model_name[i],"_",out_prefix,".png",sep=""),
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width=col_mfrow*res_pix,height=row_mfrow*res_pix) |
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boxplot(rmse~pred_mod,data=tb,ylim=c(0,5),outline=FALSE)#,names=tb$pred_mod) |
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title("RMSE per model over all tiles")
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dev.off() |
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################ |
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### Figure 4: plot predicted tiff for specific date per model |
Also available in: Unified diff
run4 assessment NEX part2: generating gam diagnostic for different k values