Revision 48de039c
Added by Benoit Parmentier about 8 years ago
| climate/research/oregon/interpolation/global_product_assessment_part2.R | ||
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#Mosaic related on NEX |
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#script_path <- "/home/parmentier/Data/IPLANT_project/env_layers_scripts" |
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function_mosaicing_functions <- "global_run_scalingup_mosaicing_function_08232016.R" #Functions used to mosaic predicted tiles
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function_mosaicing <-"global_run_scalingup_mosaicing_08222016.R" #main scripts for mosaicing predicted tiles
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function_mosaicing_functions <- "global_run_scalingup_mosaicing_function_09282016.R" #Functions used to mosaic predicted tiles
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function_mosaicing <-"global_run_scalingup_mosaicing_09282016.R" #main scripts for mosaicing predicted tiles
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source(file.path(script_path,function_mosaicing)) #source all functions used in this script |
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source(file.path(script_path,function_mosaicing_functions)) #source all functions used in this script |
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#Product assessment |
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function_product_assessment_part1_functions <- "global_product_assessment_part1_functions_09192016b.R" |
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source(file.path(script_path,function_product_assessment_part1_functions)) #source all functions used in this script |
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function_product_assessment_part2_functions <- "global_product_assessment_part2_functions_10032016b.R" |
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source(file.path(script_path,function_product_assessment_part2_functions)) #source all functions used in this script |
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############################### |
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####### Parameters, constants and arguments ### |
| ... | ... | |
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setwd(out_dir) #use previoulsy defined directory |
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} |
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setwd(out_dir) |
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#setwd(out_dir)
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########### #################### |
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r_stack <- stack(lf_raster,quick=T) #this is very fast now with the quick option! |
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} |
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NAvalue(r_stack) |
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plot(r_stack,y=6,zlim=c(-10000,10000)) #this is not rescaled |
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plot(r_stack,zlim=c(-50,50),col=matlab.like(255)) |
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#plot(r_mosaic_scaled,y=6,zlim=c(-50,50)) |
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#plot(r_mosaic_scaled,zlim=c(-50,50),col=matlab.like(255)) |
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#debug(extract_date) |
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#test <- extract_date(6431,lf_mosaic_list,12) #extract item number 12 from the name of files to get the data |
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#list_dates_produced <- unlist(mclapply(1:length(lf_raster),FUN=extract_date,x=lf_raster,item_no=13,mc.preschedule=FALSE,mc.cores = num_cores)) |
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lf_mosaic_list <- lf_raster |
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list_dates_produced <- mclapply(1:2, |
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FUN=extract_date, |
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x=lf_mosaic_list, |
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item_no=13, |
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mc.preschedule=FALSE, |
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mc.cores = 2) |
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item_no <-13 |
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list_dates_produced <- unlist(mclapply(1:length(lf_raster), |
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FUN=extract_date, |
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x=lf_raster, |
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item_no=item_no, |
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mc.preschedule=FALSE, |
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mc.cores = num_cores)) |
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list_dates_produced_date_val <- as.Date(strptime(list_dates_produced,"%Y%m%d")) |
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month_str <- format(list_dates_produced_date_val, "%b") ## Month, char, abbreviated |
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year_str <- format(list_dates_produced_date_val, "%Y") ## Year with century |
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day_str <- as.numeric(format(list_dates_produced_date_val, "%d")) ## numeric month |
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df_raster <- data.frame(lf=basename(lf_raster), |
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date=list_dates_produced_date_val, |
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month_str=month_str, |
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year=year_str, |
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day=day_str, |
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dir=dirname(lf_mosaic_list)) |
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df_raster_fname <- file.path(out_dir,paste0("df_raster_",out_suffix,".txt"))
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write.table(df_raster,file= df_raster_fname,sep=",",row.names = F) |
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############### PART5: Make raster stack and display maps ############# |
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#### Extract corresponding raster for given dates and plot stations used |
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##################################### PART 5 ###### |
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##### Plotting specific days for the mosaics |
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r_mosaic_scaled <- stack(lf_mosaic_scaled) |
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NAvalue(r_mosaic_scaled)<- -3399999901438340239948148078125514752.000 |
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plot(r_mosaic_scaled,y=6,zlim=c(-50,50)) |
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plot(r_mosaic_scaled,zlim=c(-50,50),col=matlab.like(255)) |
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function_product_assessment_part2_functions <- "global_product_assessment_part2_functions_10032016b.R" |
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source(file.path(script_path,function_product_assessment_part2_functions)) #source all functions used in this script |
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#layout_m<-c(1,3) #one row two columns
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#levelplot(r_mosaic_scaled,zlim=c(-50,50),col.regions=matlab.like(255))
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#levelplot(r_mosaic_scaled,zlim=c(-50,50),col.regions=matlab.like(255))
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#NA_flag_val_mosaic <- -3399999901438340239948148078125514752.000
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r_stack_subset <- subset(r_stack,1:11)
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l_dates <- list_dates_produced_date_val[1:11]
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#png(paste("Figure7a__spatial_pattern_tmax_prediction_levelplot_",date_selected,out_prefix,".png", sep=""),
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# height=480*layout_m[1],width=480*layout_m[2])
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#plot(r_pred,col=temp.colors(255),zlim=c(-3500,4500))
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#plot(r_pred,col=matlab.like(255),zlim=c(-40,50))
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#paste(raster_name[1:7],collapse="_")
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#add filename option later
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#undebug(plot_raster_mosaic)
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zlim_val <- NULL
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list_param_plot_raster_mosaic <- list(l_dates,r_stack_subset,NA_flag_val,out_dir,out_suffix,
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region_name,variable_name, zlim_val)
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names(list_param_plot_raster_mosaic) <- c("l_dates","r_mosaiced_scaled","NA_flag_val_mosaic","out_dir","out_suffix",
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"region_name","variable_name","zlim_val")
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#NA_flag_val_mosaic <- -3399999901438340239948148078125514752.000 |
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lf_mosaic_plot_fig <- lapply(1:2, |
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FUN=plot_raster_mosaic, |
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list_param=list_param_plot_raster_mosaic) |
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lf_mosaic_plot_fig <- mclapply(1:length(l_dates), |
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FUN=plot_raster_mosaic, |
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list_param=list_param_plot_raster_mosaic, |
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mc.preschedule=FALSE, |
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mc.cores = num_cores) |
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list_param_plot_raster_mosaic <- list(l_dates,r_mosaic_scaled,NA_flag_val_mosaic,out_dir,out_suffix, |
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region_name,variable_name) |
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names(list_param_plot_raster_mosaic) <- c("l_dates","r_mosaic_scaled","NA_flag_val_mosaic","out_dir","out_suffix",
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"region_name","variable_name") |
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lf_mosaic_plot_fig <- mclapply(1:length(lf_mosaic_scaled),FUN=plot_raster_mosaic,list_param=list_param_plot_raster_mosaic,mc.preschedule=FALSE,mc.cores = num_cores) |
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#### PLOT ACCURACY METRICS: First test #### |
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##this will be cleaned up later: |
Also available in: Unified diff
script 2 product assessment, modification of figures