Project

General

Profile

« Previous | Next » 

Revision b46ff3f7

Added by Benoit Parmentier almost 9 years ago

assessment part 1 prediction 1992 for reg23

View differences:

climate/research/oregon/interpolation/global_run_scalingup_assessment_part1.R
5 5 
#Part 1 create summary tables and inputs files for figure in part 2 and part 3.
6 6 
#AUTHOR: Benoit Parmentier
7 7 
#CREATED ON: 03/23/2014
8 
#MODIFIED ON: 10/05/2015
8 
#MODIFIED ON: 12/07/2015
9 9 
#Version: 4
10 10 
#PROJECT: Environmental Layers project
11 11 
#TO DO:
......
15 15 
#
16 16 
#First source these files:
17 17 
#Resolved call issues from R.
18 
#source /nobackupp6/aguzman4/climateLayers/sharedModules/etc/environ.sh
18 
#source /nobackupp6/aguzman4/climateLayers/sharedModules2/etc/environ.sh
19 19 
#MODULEPATH=$MODULEPATH:/nex/modules/files
20 20 
#module load pythonkits/gdal_1.10.0_python_2.7.3_nex
21 21 

  		




  ......




  69
  69
  
    
#Make this a function


  		




  70
  70
  
    
#reg1 (North Am), reg2(Europe),reg3(Asia), reg4 (South Am), reg5 (Africa), reg6 (Australia-Asia)


  		




  71
  71
  
    
#master directory containing the definition of tile size and tiles predicted


  		




  72
  
  
    
#in_dir1 <- "/nobackupp6/aguzman4/climateLayers/output1000x3000_km/"


  		




  73
  
  
    
#in_dir1 <- "/nobackupp6/aguzman4/climateLayers/out_15x45" #PARAM1


  		




  74
  
  
    
#in_dir1b <- "/nobackupp6/aguzman4/climateLayers/output1500x4500_km/singles" #PARAM1, add for now in_dir1 can be a list...


  		




  75
  
  
    
#in_dir1 <- "/nobackupp6/aguzman4/climateLayers/output1500x4500_km/" #PARAM1, add for now in_dir1 can be a list...


  		




  76
  
  
    
#in_dir1 <- "/nobackupp6/aguzman4/climateLayers/output1500x4500_km/elevTest/1kmBuff/"


  		




  77
  72
  
    
in_dir1 <- "/nobackupp6/aguzman4/climateLayers/out_15x45/"


  		




  78
  73
  
    
#/nobackupp6/aguzman4/climateLayers/out_15x45/1982


  		




  79
  74
  
    

  		




  80
  
  
    
region_names <- c("reg4") #selected region names, #PARAM2


  		




  
  75
  
    
region_names <- c("reg23","reg4") #selected region names, #PARAM2 


  		




  81
  76
  
    
#region_names <- c("1992") #no specific region here so use date


  		




  82
  77
  
    
#region_names <- c("reg1","reg2","reg3","reg4","reg5","reg6") #selected region names, #PARAM2


  		




  83
  78
  
    
#region_namesb <- c("reg_1b","reg_1c","reg_2b","reg_3b","reg_6b") #selected region names, #PARAM2


  		




  84
  79
  
    

  		




  85
  80
  
    
y_var_name <- "dailyTmax" #PARAM3


  		




  86
  81
  
    
interpolation_method <- c("gam_CAI") #PARAM4


  		




  87
  
  
    
out_prefix<-"run10_1500x4500_global_analyses_pred_1992_10052015" #PARAM5


  		




  
  82
  
    
out_prefix<-"run10_1500x4500_global_analyses_pred_1992_12072015" #PARAM5


  		




  88
  83
  
    

  		




  89
  84
  
    
#output_run10_1500x4500_global_analyses_pred_2003_04102015/


  		




  90
  85
  
    

  		




  ......




  96
  91
  
    

  		




  97
  92
  
    
CRS_locs_WGS84 <- CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +towgs84=0,0,0") #Station coords WGS84, #PARAM8


  		




  98
  93
  
    

  		




  99
  
  
    
#day_to_mosaic <- c("20100101","20100901") #PARAM9


  		




  100
  
  
    
#day_to_mosaic <- c("20100829","20100830","20100831",


  		




  101
  
  
    
#                   "20100901","20100902","20100903")


  		




  102
  
  
    
day_to_mosaic <- c("19920101","19920102","19920103")


  		




  103
  
  
    
#,"19820104","19820105",


  		




  104
  
  
    
#                   "19820106","19820107","19820108","19820109","19820110",


  		




  105
  
  
    
#                   "19820111")


  		




  
  94
  
    
day_to_mosaic <- c("19920101","19920102","19920103,19920104,19920105")


  		




  
  95
  
    

  		




  106
  96
  
    

  		




  107
  97
  
    
#day_to_mosaic <- NULL #if day to mosaic is null then mosaic all dates?


  		




  108
  98
  
    

  		




  ......




  156
  146
  
    
in_dir_shp_list <- list.files(in_dir_shp,".shp",full.names=T)


  		




  157
  147
  
    

  		




  158
  148
  
    
## load problematic tiles or additional runs


  		




  159
  
  
    

  		




  160
  
  
    
#in_dir_listb <- list.dirs(path=in_dir1b,recursive=FALSE) #get the list regions processed for this run


  		




  161
  
  
    
#basename(in_dir_list)


  		




  162
  
  
    
#in_dir_listb<- lapply(region_namesb,FUN=function(x,y){y[grep(x,basename(y),invert=FALSE)]},y=in_dir_listb) 


  		




  163
  
  
    

  		




  164
  
  
    
#in_dir_list_allb  <- lapply(in_dir_listb,function(x){list.dirs(path=x,recursive=F)})


  		




  165
  
  
    
#in_dir_listb <- unlist(in_dir_list_allb)


  		




  166
  
  
    
#in_dir_list <- in_dir_list[grep("bak",basename(basename(in_dir_list)),invert=TRUE)] #the first one is the in_dir1


  		




  167
  
  
    
#in_dir_subsetb <- in_dir_listb[grep("subset",basename(in_dir_listb),invert=FALSE)] #select directory with shapefiles...


  		




  168
  
  
    
#in_dir_shpb <- file.path(in_dir_subsetb,"shapefiles")


  		




  169
  
  
    

  		




  170
  
  
    
#select only directories used for predictions


  		




  171
  
  
    
#in_dir_regb <- in_dir_listb[grep(".*._.*.",basename(in_dir_listb),invert=FALSE)] #select directory with shapefiles...


  		




  172
  
  
    
#in_dir_reg <- in_dir_list[grep("july_tiffs",basename(in_dir_reg),invert=TRUE)] #select directory with shapefiles...


  		




  173
  
  
    
#in_dir_listb <- in_dir_regb


  		




  174
  
  
    
    


  		




  175
  
  
    
#in_dir_listb <- in_dir_listb[grep("bak",basename(basename(in_dir_listb)),invert=TRUE)] #the first one is the in_dir1


  		




  176
  
  
    
#list of shapefiles used to define tiles


  		




  177
  
  
    
#in_dir_shp_listb <- list.files(in_dir_shpb,".shp",full.names=T)


  		




  178
  
  
    

  		




  179
  
  
    

  		




  180
  
  
    
#### Combine now...


  		




  181
  
  
    

  		




  182
  
  
    
#in_dir_list <- c(in_dir_list,in_dir_listb)


  		




  183
  
  
    
#in_dir_reg <- c(in_dir_reg,in_dir_regb)


  		




  184
  
  
    
#in_dir_shp <- c(in_dir_shp,in_dir_shpb)


  		




  185
  
  
    
#in_dir_shp_list <- c(in_dir_shp_list,in_dir_shp_listb)


  		




  186
  
  
    
#in_dir_list <- c(in_dir_list,in_dir_listb)


  		




  
  149
  
    
#modify later...


  		




  187
  150
  
    

  		




  188
  151
  
    
#system("ls /nobackup/bparmen1")


  		




  189
  152
  
    

  		




  ......




  535
  498
  
    
######################################################


  		




  536
  499
  
    
####### PART 2 CREATE MOSAIC OF PREDICTIONS PER DAY, Delta surfaces and clim ###


  		




  537
  500
  
    

  		




  
  501
  
    
#if mosaicing_tiles==TRUE then do it?


  		




  538
  502
  
    
#dates_l <- unique(robj1$tb_diagnostic_s$date) #list of dates to query tif


  		




  539
  503
  
    
#create date!!!


  		




  540
  504
  
    
if(is.null(day_to_mosaic)){


  		












Also available in:  Unified diff