Revision 9ad802bf
Added by Benoit Parmentier over 8 years ago
| climate/research/oregon/interpolation/global_product_assessment_part1.R | ||
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#Combining tables and figures for individual runs for years and tiles. |
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#AUTHOR: Benoit Parmentier |
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#CREATED ON: 05/15/2016 |
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#MODIFIED ON: 09/16/2016
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#MODIFIED ON: 09/17/2016
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#Version: 1 |
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#PROJECT: Environmental Layers project |
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#COMMENTS: Initial commit, script based on part NASA biodiversity conferenc |
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# |
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#setfacl -Rmd user:aguzman4:rwx /nobackupp8/bparmen1/output_run10_1500x4500_global_analyses_pred_1992_10052015 |
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#COMMIT: fixing extraction function and and missing dates
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#COMMIT: clean up and first testing of extraction function
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################################################################################################# |
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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_mosaic_list),FUN=extract_date,x=lf_mosaic_list,item_no=13,mc.preschedule=FALSE,mc.cores = num_cores)) |
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#list_dates_produced <- unlist(mclapply(1:length(lf_mosaic_list),FUN=extract_date,x=lf_mosaic_list,item_no=13,mc.preschedule=FALSE,mc.cores = num_cores))
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#list_dates_produced <- mclapply(1:2,FUN=extract_date,x=lf_mosaic_list,item_no=13,mc.preschedule=FALSE,mc.cores = 2) |
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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_produced <- data.frame(basename(lf_mosaic_list),list_dates_produced_date_val,month_str,year_str,day_str,dirname(lf_mosaic_list)) |
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#### |
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df_points$date <- list_dates_produced_date_val |
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df_points$month <- month_str |
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df_points$year <- year_str |
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df_points$day <- day_str |
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in_dir_mosaic <- "/data/project/layers/commons/NEX_data/climateLayers/out/reg1/mosaics/mosaic" |
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in_dir_mosaic_rmse <- "/data/project/layers/commons/NEX_data/climateLayers/out/reg1/mosaicsRMSE/mosaic" |
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#pattern_str <- ".*.tif" |
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if(is.null(df_points_extracted_fname)){
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in_dir_mosaic <- "/data/project/layers/commons/NEX_data/climateLayers/out/reg1/mosaics/mosaic" |
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#in_dir_mosaic_rmse <- "/data/project/layers/commons/NEX_data/climateLayers/out/reg1/mosaicsRMSE/mosaic" |
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pattern_str <- ".*.tif" |
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df_points <- #this contains the location of points to be used for extraction |
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#extract from var pred mosaic, tmax in this case: |
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extract_obj_var_pred <- extract_from_time_series_raster_stack(df_points,date_start,date_end,lf_raster=NULL,item_no=13, |
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num_cores=11,pattern_str=NULL,in_dir=in_dir_mosaic,out_dir=out_dir,out_suffix=out_suffix) |
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df_points_extracted_fname <-extract_obj_var_pred$df_points_extracted_fname |
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df_raster_fname <- extract_obj_var_pred$df_raster_fname |
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df_time_series_fname <- extract_obj_var_pred$df_time_series_fname |
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extract_from_time_series_raster_stack(df_points,date_start,date_end,lf_raster,item_no=13,num_cores=4,pattern_str=NULL,in_dir=NULL,out_dir=".",out_suffix="") |
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# |
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df_raster <- read.table(df_points_extracted_fname,sep=",") |
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df_time_series <- read.table( df_time_series,sep=",") |
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df_points_extracted <- read.table(df_points_extracted_fname,sep=",") |
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}else{
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df_points_day_extracted <- read.table(df_points_extracted_fname,sep=",") |
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df_time_series <- read.table( df_time_series,sep=",") |
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df_points_extracted <- read.table(df_points_extracted_fname,sep=",") |
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} |
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df_points_day_extracted |
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names(df_points_day_extracted)[1:10] |
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(df_points_day_extracted$ID)[1:10] |
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df_points_day_extracted_tmp <- df_points_day_extracted |
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df_points_extracted <- cbind(df_points_day,df_points_day_extracted_tmp) |
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#df_points_extracted$id <- df_points_day$id |
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################################################################################################# |
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###################### PART 5: combine stations data and extracted values ############################ |
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#### Now combined with the station data extracted from the assessment stage |
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combine |
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#combine |
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data_stations_var_pred |
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##write function to combine data!!! |
Also available in: Unified diff
moving more functions, quick small test for extraction function, listing date produced and missing for mosaics