Revision 68849df1
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: 10/21/2014
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#MODIFIED ON: 11/03/2014
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#Version: 3 |
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#PROJECT: Environmental Layers project |
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#COMMENTS: analyses for run 5 global using 6 specific tiles |
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#in_dir1 <- "/data/project/layers/commons/NEX_data/output_run6_global_analyses_09162014/output20Deg2" |
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# parent output dir for the curent script analyes |
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#out_dir <-"/data/project/layers/commons/NEX_data/output_run3_global_analyses_06192014/" #On NCEAS Atlas |
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out_dir <-"/data/project/layers/commons/NEX_data/output_run8_global_analyses_10212014/"
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out_dir <-"/data/project/layers/commons/NEX_data/output_run8_global_analyses_10292014/"
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# input dir containing shapefiles defining tiles |
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#in_dir_shp <- "/data/project/layers/commons/NEX_data/output_run5_global_analyses_08252014/output/subset/shapefiles" |
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y_var_name <- "dailyTmax" |
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interpolation_method <- c("gam_CAI")
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out_prefix<-"run8_global_analyses_10212014"
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out_prefix<-"run8_global_analyses_10292014"
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mosaic_plot <- FALSE |
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proj_str<- CRS_WGS84 |
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list_df_ac_mod[[i]] <- arrange(as.data.frame(ac_mod),desc(rmse))[,c("rmse","mae","tile_id")]
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} |
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#coordinates |
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coordinates(summary_metrics_v) <- c("lon","lat")
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summary_metrics_v$n_missing <- summary_metrics_v$n == 365 |
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#plot(summary_metrics_v) |
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p_shp <- layer(sp.polygons(reg_layer, lwd=1, col='black')) |
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#title("(a) Mean for 1 January")
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p <- bubble(summary_metrics_v,"n_missing",main=paste("Averrage RMSE per tile and by ",model_name[i]))
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p1 <- p+p_shp |
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print(p1) |
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###################### |
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### Figure 7: Number of predictions: daily and monthly |
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#xyplot(n~pred_mod | tile_id,data=subset(as.data.frame(summary_metrics_v), |
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# pred_mod!="mod_kr"),type="h") |
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#cor |
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# |
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## Figure 7a |
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pred_mod!="mod_kr"),type="h") |
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test |
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unique(test$tile_id) #71 tiles |
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dim(subset(test,test$predicted==365 & test$pred_mod=="mod2")) |
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histogram(subset(test, test$pred_mod=="mod2")$predicted) |
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unique(subset(test, test$pred_mod=="mod2")$predicted) |
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table((subset(test, test$pred_mod=="mod2")$predicted)) |
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LST_avgm_min <- aggregate(LST~month,data=data_month_all,min) |
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histogram(test$predicted~test$tile_id) |
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table(tb) |
Also available in: Unified diff
run 8 NEX scaling up assessment part2, production of figures for Asia, Africa and South America